INTERCROPPING WHEAT AND BARLEY WITH NITROGEN FIXING LEGUME
SPECIES IN LOW INPUT ORGANIC SYSTEMS
by
TEJENDRA CHAPAGAIN
MSc Agriculture, Tribhuvan University, 2005
A THESIS SUBMITTED IN PARTIAL FULFILMENT OF
THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
in
THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES
(Plant Science)
THE UNIVERSITY OF BRITISH COLUMBIA
(Vancouver)
September 2014
© Tejendra Chapagain, 2014
Abstract
Declining land productivity associated with decreasing soil organic carbon (SOC) and
nitrogen (N) is an issue for conventional production of small grains. Intercropping grains
with legumes may provide a sustainable solution. I grew wheat (Triticum aestivum cv.
‘Scarlet’) as a monoculture and intercropped with either common bean (Phaseolus vulgaris
cv. ‘Red Kidney’, or cv. ‘Black Turtle’), or fava bean (Vicia faba cv. ‘Bell’) in rows of
wheat:bean 1:1 and 2:1 as well as broadcast arrangements to assess the effects of genotype
and spatial arrangements on crop agronomy, land productivity, biological nitrogen fixation
and transfer, N and carbon (C) accumulation in aboveground biomass, soil N balance, gross
ecosystem photosynthesis (GEP), net ecosystem productivity (NEP), and water use
efficiency (WUE). Barley (Hordeum vulgare cv. ‘Oxbridge’) and pea (Pisum sativum cv.
‘Reward’) were also included based on synchronized maturity, yield potential, protein
content, and root architecture. Stable isotope methods (13C and 15N) coupled with field CO2
exchange measurements were used to determine C and N transformations.
Intercrop plots had higher land productivity, improved grain and biomass quality,
increased legume nodulation and percent N derived from symbiotic N2 fixation. Wheat-fava
bean in the 1:1 arrangement displayed a 50% increase in land productivity. Barley-pea in
the 2:1 arrangement also had the highest total land outputs (5.9 t ha-1) and land equivalent
ratio (1.32). Wheat-fava bean in the 1:1 arrangement fixed the highest amount of N (74 kg
N ha-1), transferred the most N (13% of N in wheat), and accumulated more C (26% higher
than wheat monoculture) in shoot biomass. WUE of wheat was improved when grown with
fava bean. Pea in intercrop plots also displayed increased nodulation (27-45%) and
ii
symbiotic N2 fixation (9-17%) leading to the addition of 60-78 kg N ha-1. The GEP and NEP
were highest in the 2:1 arrangement and led to the highest daytime C sequestration (229
mg C m-2 hr-1).
I demonstrated that intercropping small grains with legumes, in specific spatial
arrangements and under low input organic conditions, can counter conventional
monoculture-associated SOC and N losses through higher land and ecosystem productivity,
and greater organic N-fixation and transfer.
iii
Preface
This thesis entitled ‘Intercropping Wheat and Barley with Nitrogen Fixing Legume Species in
Low Input Organic Systems’ is a product of field and lab research carried out at the
University of British Columbia - Vancouver. The author is responsible for designing and
implementing research activities, data collection, analysis and interpretation of the results,
and writing manuscripts presented in this thesis.
The findings presented in Chapters 2-5 have been published or accepted as the following
publications.
 Chapagain, T. and A. Riseman (2012). Evaluation of Heirloom and Commercial Cultivars
of Small Grains under Low Input Organic Systems. American Journal of Plant Sciences 3
(5): 655-669.
 Chapagain, T., L. Super and A. Riseman (2014). Root Architecture Variation in Wheat
and Barley Cultivars. American Journal of Experimental Agriculture 4 (7): 849-856.
 Chapagain, T. and A. Riseman (2014). Intercropping Wheat and Beans: Effects on
Agronomic Performance and Land Productivity. Crop Science 54 (5): 2285-2293.
 Chapagain, T. and A. Riseman (2014). Barley-Pea Intercropping: Effects on Land
Productivity, Carbon and Nitrogen Transformations. Field Crops Research 166: 18-25.
 Chapagain, T. and A. Riseman, Nitrogen Transformation, Water Use Efficiency and
Ecosystem Productivity in Monoculture and Wheat-Bean Intercropping Systems
(Manuscript accepted for publication in Nutrient Cycling in Agroecosystems).
iv
Table of Contents
Abstract....... .............................................................................................................................................................. ii
Preface……............................................................................................................................................................... iv
Table of Contents .................................................................................................................................................. v
List of Tables ........................................................................................................................................................... x
List of Figures ......................................................................................................................................................xiv
List of Acronyms and Abbreviations ........................................................................................................... xv
Acknowledgements ......................................................................................................................................... xvii
Dedication…………................................................................................................................................................ xx
CHAPTER 1: BACKGROUND INFORMATION AND OBJECTIVES ......................................................... 1
1.1 Small Grain Production: Opportunities and Challenges ............................................................. 1
1.1.1 Soil degradation: An emerging issue in small grain production ................................. 3
1.2 Intercropping: An Alternative to Conventional Small Grain Production ............................. 4
1.3 Nitrogen Transfer between Legumes and Associated Non-legume Plants......................... 6
1.4 Estimating Nitrogen Fixation and Transfer using 15N Isotope Methods.............................. 8
1.4.1 15N natural abundance method ............................................................................................. 10
1.5 Understanding Wheat and Barley Root Architecture .............................................................. 13
1.6 CO2 Uptake, Respiration and Carbon Sequestration................................................................. 15
1.7 Water Use Efficiency ............................................................................................................................. 17
v
1.8 Research Goal and Specific Objectives ........................................................................................... 18
CHAPTER 2: CULTIVAR EVALUATION TRIAL ........................................................................................ 20
2.1 Materials and Methods ......................................................................................................................... 20
2.1.1 Climate description of the study area ................................................................................. 20
2.1.2 Soil and site description ........................................................................................................... 21
2.1.3 Experimental details .................................................................................................................. 21
2.1.4 Data collection and analysis .................................................................................................... 22
2.2 Results and Discussion ......................................................................................................................... 24
2.2.1 Plant-based parameters ........................................................................................................... 24
2.2.2 Management-based parameters............................................................................................ 30
2.2.3 Protein content ............................................................................................................................ 33
2.3 Conclusions ............................................................................................................................................... 34
CHAPTER 3: WHEAT AND BARLEY ROOT ARCHITECTURE ............................................................. 57
3.1 Materials and Methods ......................................................................................................................... 57
3.1.1 Cultivar selection......................................................................................................................... 57
3.1.2 Seed treatment ............................................................................................................................. 57
3.1.3 Study design and set-up ........................................................................................................... 58
3.1.4 Root architecture data analysis ............................................................................................. 58
3.2 Results and Discussion ......................................................................................................................... 59
3.2.1 Wheat root architecture ........................................................................................................... 59
vi
3.2.2 Barley root architecture ........................................................................................................... 60
3.2.3 Root architecture association with field performance ................................................. 60
3.3 Conclusions ............................................................................................................................................... 62
CHAPTER 4: WHEAT-BEANS INTERCROPPING ..................................................................................... 67
4.1 Materials and Methods ......................................................................................................................... 68
4.1.1 Climate description of the study area ................................................................................. 68
4.1.2 Soil and field description.......................................................................................................... 68
4.1.3 Experimental details .................................................................................................................. 69
4.1.4 Data collection and analysis .................................................................................................... 71
4.2 Results ........................................................................................................................................................ 77
4.2.1 Soil mineral nitrogen and δ15N content .............................................................................. 77
4.2.2 Plant performance indices ....................................................................................................... 78
4.2.3 Biological N2 fixation and transfer ....................................................................................... 80
4.2.4 N and C accumulation in biomass ......................................................................................... 81
4.2.5 Net ecosystem CO2 exchange, ecosystem respiration, gross ecosystem
photosynthesis and net ecosystem productivity ............................................................ 83
4.2.6 Water use efficiency ................................................................................................................... 84
4.2.7 Crop competition, weed and disease pressure ................................................................ 85
4.3 Discussion ................................................................................................................................................. 86
4.4 Conclusions ............................................................................................................................................... 91
vii
CHAPTER 5: BARLEY-PEA INTERCROPPING ........................................................................................ 117
5.1 Materials and Methods ....................................................................................................................... 117
5.1.1 Climate description of the study area .............................................................................. 117
5.1.2 Soil and site description ........................................................................................................ 117
5.1.3 Experimental details ............................................................................................................... 118
5.1.4 Data collection and analysis ................................................................................................. 119
5.2 Results ...................................................................................................................................................... 126
5.2.1 Soil mineral nitrogen and δ15N content ........................................................................... 126
5.2.2 Plant performance indices .................................................................................................... 126
5.2.3 Biological N2 fixation and transfer .................................................................................... 128
5.2.4 Biomass N and C accumulation ........................................................................................... 128
5.2.5 Net ecosystem CO2 exchange, ecosystem respiration, gross ecosystem
photosynthesis and net ecosystem productivity ......................................................... 129
5.2.6 Crop competition, weed and disease pressure ............................................................. 130
5.3 Discussion ............................................................................................................................................... 131
5.4 Conclusions ............................................................................................................................................. 134
CHAPTER 6: CONCLUSIONS AND FUTURE NEEDS ............................................................................. 147
LITERATURE CITED ........................................................................................................................................ 156
Appendix A Protocol adopted for N-determination in small grains using the
Kjeldahl method. ..................................................................................................................... 173
viii
Appendix B Performance of wheat and bean components in monocultures and
wheat-bean intercrop combinations. .............................................................................. 177
Appendix C Performance of barley and pea components in monocultures and
barley-pea intercrop combinations.................................................................................. 179
Appendix D Coefficients of determination (r2) between bean performance metrics
in wheat-bean intercrop combinations. ......................................................................... 180
Appendix E Coefficients of determination (r2) between wheat performance metrics
in wheat-bean intercrop combinations. ......................................................................... 181
Appendix F Coefficients of determination (r2) between performance metrics in
wheat-fava bean intercrop combinations. ..................................................................... 182
Appendix G Coefficients of determination (r2) between pea performance metrics
in barley-pea intercrop combinations............................................................................. 183
Appendix H Coefficients of determination (r2) between barley performance metrics
in barley-pea intercrop combinations. ........................................................................... 184
Appendix I Performance of cereals and legumes in monocultures and intercropping
systems. ........................................................................................................................................ 185
Appendix J CO2 flux, leaf area and chlorophyll concentration index measurements in
cereal-legume intercropping systems. ............................................................................. 190
Appendix K Root growth and nodulation in cereal and legume genotypes. ............................. 191
Appendix L Types of cultivars based on the arrangement of spike-lets and seed
characteristics. .......................................................................................................................... 192
ix
List of Tables
Table 2.1 Meteorological data during 2010 cropping season at UBC Farm, Vancouver,
Canada. ............................................................................................................................................... 37
Table 2.2 Soil properties at site (prior to sowing i.e., spring 2010) at UBC Farm,
Vancouver, Canada. ....................................................................................................................... 38
Table 2.3 Small grain cultivars used for performance evaluation during 2010 spring
season at UBC Farm, Vancouver, Canada. ............................................................................. 39
Table 2.4 Legume crops and cultivars used for evaluation during 2010 cropping
season at UBC Farm, Vancouver, Canada. ............................................................................. 41
Table 2.5 Disease assessment key adopted during 2010 spring trial at UBC Farm,
Vancouver, Canada. ....................................................................................................................... 43
Table 2.6 Rating key for nodule assessment (after Corbin et al., 1977) in legume
during 2010 cropping season at UBC Farm, Vancouver, Canada. ............................... 44
Table 2.7 Response of commercial wheat cultivars to organic production systems
during 2010 cropping season at UBC Farm, Vancouver, Canada. ............................... 45
Table 2.8 Performance of commercial and heirloom barley cultivars to organic
production during 2010 cropping season at UBC Farm, Vancouver, Canada. ........ 47
Table 2.9 Performance of legume cultivars to the organic production during 2010
cropping season at UBC Farm, Vancouver, Canada. .......................................................... 49
Table 2.10 Performance of commercial and heirloom wheat cultivars during 2010
cropping season at UBC Farm, Vancouver, Canada. ....................................................... 51
Table 2.11 Performance of commercial and heirloom barley cultivars during 2010
cropping season at UBC Farm, Vancouver. ........................................................................ 53
x
Table 2.12 Protein content of wheat and barley cultivars grown under organic
production systems during 2010 cropping season at UBC Farm,
Vancouver, Canada. ..................................................................................................................... 54
Table 3.1 Root architecture metrics for heirloom and commercial wheat cultivars. .............. 63
Table 3.2 Root architecture metrics for heirloom and commercial barley cultivars. ............. 64
Table 3.3 Field performance of small grain cultivars grown under low input organic
conditions during 2010 spring season at UBC Farm, Vancouver, Canada. .............. 65
Table 4.1 Climate data during the cropping seasons of 2011 and 2012 at UBC Farm,
Vancouver, Canada. ....................................................................................................................... 93
Table 4.2 Soil mineral nitrogen (NH4+ and NO3-, mg kg -1 dry soil) at 0-15 cm depth
before planting (Spring-2011) and after final harvest (Fall-2012) in
monocultures and wheat-bean intercrop combinations. ............................................... 94
Table 4.3 Grain yields, land equivalency ratios and total land output values from
monocultures and wheat-bean intercrop combinations. ............................................... 96
Table 4.4 Total biomass (grain plus shoot biomass) yields, land equivalency ratios
and total land output values from monocultures and wheat-bean intercrop
combinations.................................................................................................................................... 98
Table 4.5 1000 seed weights, biomass C:N and grain protein content of wheat and
bean components in monocultures and wheat-bean intercrop combinations. ...100
Table 4.6 Nodule numbers, total N yield, biological nitrogen fixation and transfer by
legume in wheat-bean intercrop combinations during 2011-12 at UBC
Farm, Vancouver, Canada. .........................................................................................................102
xi
Table 4.7 Organic carbon and nitrogen yield from grain and shoot biomass in
monocultures and wheat-bean intercrop combinations during 2011-12
at UBC Farm, Vancouver, Canada. ..........................................................................................105
Table 4.8 Daytime averages of net ecosystem CO2 exchange, ecosystem respiration,
gross ecosystem photosynthesis and net ecosystem productivity in
monocultures and intercrop plots during 2011-12 at UBC Farm,
Vancouver, Canada. .....................................................................................................................107
Table 4.9 δ13C values in plant shoot tissue in monocultures and wheat-bean
intercrop combinations during 2011-12 at UBC Farm, Vancouver, Canada. ........110
Table 4.10 Crop on crop and crop on weed competition in wheat-bean intercrop
combinations. ..............................................................................................................................112
Table 5.1 Soil mineral nitrogen (NH4+ and NO3-; mg kg -1 dry soil) before planting
(Spring-2011) and after final harvest (Fall-2012) in monocultures and
intercrop plots. ..............................................................................................................................136
Table 5.2 Grain yields, land productivity, biomass C:N and grain protein from
monoculture and intercrop plots during 2011-12 at UBC Farm, Vancouver,
Canada. .............................................................................................................................................137
Table 5.3 Total biomass (grain plus shoot biomass) yields, land equivalency ratios
and total land output values from monocultures and intercrop plots
during 2011-12 at UBC Farm, Vancouver, Canada. .........................................................138
Table 5.4 Harvest index, biomass C:N, chlorophyll concentration, and grain protein
content in monocultures and intercrop plots during 2011-12 at UBC Farm,
Vancouver, Canada. .....................................................................................................................139
xii
Table 5.5 Nodule numbers, total N yield, biological nitrogen fixation and transfer
by pea in monoculture and intercrop plots during 2011-12 at UBC Farm,
Vancouver, Canada. .....................................................................................................................140
Table 5.6 Average nitrogen yield from grain and shoot biomass in monocultures
and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada. .................141
Table 5.7 Average carbon yield from grain and shoot biomass in monocultures
and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada. .................142
Table 5.8 Daytime averages of net ecosystem CO2 exchange, ecosystem respiration,
gross ecosystem photosynthesis and net ecosystem productivity in
monocultures and intercrop plots during 2011-12 at UBC Farm,
Vancouver, Canada. .....................................................................................................................143
Table 5.9 Crop on crop and crop on weed competition in barley-pea intercrop
combinations during 2011-12 at UBC Farm, Vancouver, Canada. ............................144
Table 6.1 Summary of the effects of genotypes and spatial configurations on
agronomic and ecosystem metrics over monocultured plots. ....................................149
xiii
List of Figures
Figure 2.1 Disease assessment score and severity of leaf damage in wheat and barley. ....... 56
Figure 3.1 Root length (cm) distribution in diameter classes (mm) in wheat cultivars. ....... 66
Figure 3.2 Root length (cm) distribution in diameter classes (mm) in barley cultivars. ....... 66
Figure 4.1 Field layout and treatment composition in completely randomized block
design. .............................................................................................................................................113
Figure 4.2 Grain yield of wheat and bean components in monocultures and intercrop
combinations. ..............................................................................................................................114
Figure 4.3 Daytime average gross ecosystem photosynthesis (µmol CO2 m-2 s-1) in
monocultures and wheat-bean intercrop combinations during 25, 50 and
75 days after sowing. ................................................................................................................115
Figure 4.4 Daytime average net ecosystem productivity (µmol CO2 m-2 s-1) in
monocultures and wheat-bean intercrop combinations during 25, 50
and 75 days after sowing. .......................................................................................................116
Figure 5.1 Field layout and treatment composition in completely randomized block
design. .............................................................................................................................................145
Figure 5.2 Daytime average gross ecosystem photosynthesis (µmol CO2 m-2 s-1) in
monocultures and barley-pea intercrop plots during 25, 50 and 75 days
after sowing. .................................................................................................................................146
Figure 5.3 Daytime average net ecosystem productivity (µmol CO2 m-2 s-1) in
monocultures and barley-pea intercrop plots during 25, 50 and 75 days
after sowing. .................................................................................................................................146
xiv
List of Acronyms and Abbreviations
AAFC
Agriculture and Agri-Food Canada
ANOVA
Analysis of Variance
ARS
Agricultural Research Stations
CCI
Chlorophyll Concentration Index
CGC
Canada Grains Council
cm
Centimeter
DAS
Days after Sowing
FAO
Food and Agriculture Organization
g
Gram
GEP
Gross Ecosystem Photosynthesis
ha
Hectare
HI
Harvest Index
kg
Kilogram
LER
Land Equivalent Ratio
LSD
Least Significant Difference
masl
Meter above sea level
ml
Millilitre
NEP
Net Ecosystem Productivity
xv
NS
Non-significant
PLP
Plant Lodging Percentage
pp.
Page
RCBD
Randomized Complete Block Design
Re
Ecosystem Respiration
RH
Relative Humidity
SEM
Standard Error of Mean
SPSS
Statistical Package for Social Sciences
t
Ton
TGW
Thousand Grain Weight
TLO
Total Land Outputs
UBC
University of British Columbia
USDA
United States Department of Agriculture
WUE
Water Use Efficiency
xvi
Acknowledgements
The author feels immense pleasure to express his deep sense of gratitude and appreciation
to Dr. Andrew Riseman, Associate Professor in the Faculty of Land and Food Systems-LFS,
and the Chairman of the Supervising Committee, for his constant supervision, friendly
support, constructive comments, and invaluable counsel during the course of this
investigation and writing of the thesis. I feel greatly fortunate to have Dr. Riseman as my
mentor who helped me in every difficult time with his exceptional knowledge and
experience. This work wouldn’t have been accomplished without his academic supervision
and moral support in all phases of this research.
The author is indebted to Dr. Art Bomke, Professor Emeritus and a member of supervising
committee for his deep insight and interest in the subject of this thesis, and for his constant
encouragement to move towards the results. The author also wishes to express heartfelt
thanks to Dr. Murray Isman, Professor and Dean of the Faculty of Land and Food Systems,
and a committee member for his tremendous inspiration and guidance throughout this
project. The author would like to offer sincere thanks to Dr. Mahesh Upadhyaya, Professor
and committee member for his precious suggestions and creative comments during field
experimentation and manuscript preparation.
The author is extremely grateful to the Graduate and Post-doctoral Studies (formerly
known as the Faculty of Graduate Studies) of the University of British Columbia for offering
the Four Year Doctoral Fellowship (4YF) with full tuition coverage during the first four
years of his doctoral research. He is also thankful to the Faculty of Land and Food Systems
(LFS) for offering the May L. Barnett Memorial Scholarship in Plant Science along with
xvii
other departmental fellowships throughout his time at UBC. This financial support meant a
lot for the author to study, research and spend a meaningful life in this multicultural
community on campus at UBC - Vancouver. The author wishes to thank Ms. Shelley Small,
the LFS Program Manager; Ms. Allison Barnes, the former LFS Manager; and Ms. Lia Maria,
a graduate Secretary, for their moral support and necessary suggestion during his tenure at
LFS.
The author greatly acknowledges the entire team at the Centre for Sustainable Food
Systems at UBC Farm for providing organically managed land for this research. Sincere
thanks are due to the collaborating farmers in BC, Canada, and various states throughout
the USA (i.e., Alaska, California, Colorado, Connecticut, Idaho, Maine, Oregon, Vermont,
Wisconsin, and Washington), and institutions (Agriculture and Agri-Food Canada- AAFC,
and Agricultural Research Service- ARS/USDA, Pullman, USA) who provided us with the
seed of commercial and heirloom cultivars.
The author has been quite fortunate to be surrounded by good people while at UBC. He
wants to extend his deepest sense of thanks and appreciation to Ms. Laura Super and Mr.
Greg Rekken, Plant Science lab members, for their friendly assistance in setting up and
conduction of lab experiments, and for their contribution in implementing the lab
protocols. Dr. Bishnu Pandey, Dr. Umesh Phuyal, Dr. Madhav Nepal, and Mr. Kapil Dev
Regmi, and their families deserve special thanks for their familial coordination,
encouragement, sharing of ideas, and other help from each possible corner.
Words fail to express his emotional feelings towards his parent Mr. Prem Kumar Chapagain
and Mrs. Kamala Chapagain, sister Mrs. Rama Neupane, brother-in-law Mr. Gyanu Neupane,
xviii
nephew Mr. Ayush Neupane, and beloved brothers Bikash and Prakash and their families,
for their love, affection, endless patience, constant sacrifices as well as moral support
extended to him during the study period. He has no words to express his deepest sense of
love and emotions for his ever-loving wife Sarita, lovely son Sujal and daughter Shilu for
care, love, understanding, encouragement and patience throughout the entire period of this
study.
Author
(Tejendra Chapagain)
xix
Dedication
In Loving Memory of My Mother
HARIMAYA CHAPAGAIN
xx
CHAPTER 1: BACKGROUND INFORMATION AND OBJECTIVES
1.1 Small Grain Production: Opportunities and Challenges
Wheat (Triticum spp.) is the third most produced cereal grain in the world after maize, (Zea
mays L.; 875 million tons) and rice, (Oryza sativa L.; 718 million tons) with a production of
over 674 million tons on over 216 million ha, or 3.1 t ha-1 (FAO, 2013). In Canada, it is the
principal cereal grain grown as monoculture in Saskatchewan, Manitoba, Alberta and
British Columbia (CGC, 2014), with a total production of 33 million tons on over 10 million
ha, or 3.3 t ha-1 (AAFC, 2014). Barley (Hordeum vulgare L.) is also a major cereal grain
grown worldwide with production of over 132 million tons on over 49 million hectares, or
2.7 t ha-1 (FAO, 2013). Like wheat, it is grown as monoculture in the prairies of Canada with
a total national production of 9.4 million tons on over 2.8 million ha, or 3.7 t ha-1 (AAFC,
2014).
The majority of wheat grown in Canada is spring wheat (including durum wheat),
accounting for 94% of total production (Oleson, 2010); the remaining 6% is mostly winter
wheat. The normal planting time of spring wheat and barley across Canada is from April to
June with harvest from August to October. The cropping season for winter wheat, on the
other hand, is from September through August. Spring non-durum wheat is planted on 75
percent of the harvested area (CGC, 2014) and is the largest category of wheat grown in
Canada. However, in recent decades, crops such as canola (Brassica napus L.), dry pea
(Pisum sativum L.), soybean (Glycine max L.), lentil (Lens culinaris Medik.) and broad beans
(e.g., kidney beans- Phaseolus vulgaris L., and fava bean- Vicia faba L., etc.) have witnessed
increased production in areas with sufficient precipitation (Statistics Canada, 2014). In
1
areas with insufficient precipitation, wheat production typically follows a summer-fallow
monoculture system.
On Vancouver Island, cereal grains were first grown during the early years of European
colonization. However, wheat and barley gained economic importance after World War II
when railways connected the prairies to the west coast (Ormsby, 1945) and production
moved away from the region. However, this region has cool summer temperatures and long
grain filling period suitable for cereals grown as a spring crop. In addition, spring cereals
have a nitrogen demand more aligned with natural soil nitrogen cycles. Unfortunately, the
availability of relatively poor quality spring wheat cultivars coupled with the availability of
limited and expensive land, and the supply of large amount of grains from the Prairies
provinces (Bomke et al., 1991), results in limited local production, and only supplies 10%
the food grains consumed locally while food self-sufficiency was 85% 40-50 years ago (ESE,
2007).
Currently, there are hundreds of high yielding cultivars available in Canada that are
hybridized, patented and mostly selected under high chemical input conditions. Therefore,
a constant supply of recently developed or new cultivars is available to the region’s
growers. However, tremendous genetic diversity exists in wheat and barley cultivar
collections including those considered heritage cultivars (i.e., pre 1960 introduction).
These heirloom cultivars were selected under low-input production so are thought to grow
well without conventional chemical inputs and may be well suited for sustainable, lowinput production (Rempel, 2008). However, decisions to grow a cultivar are rarely based
on information from local trials. Therefore, comparative cultivar trials, including both
2
heirloom and commercial cultivars, conducted under local conditions and organic
guidelines can provide important information for interested farmers.
1.1.1 Soil degradation: An emerging issue in small grain production
Soil degradation and declining land productivity are significant issues for conventional
small grain production. Farmers typically use an intensive monoculture-based farming
system with high reliance on agrochemicals to maintain crop yields. However, over time,
intensive agrochemical use promotes soil degradation and erosion (Liu et al., 2009; McGill
et al., 1981; Dumanski et al., 1986), increases air and water pollution (Louis et al., 1996),
accumulates chemical residues in food (Oates and Cohen, 2009), reduces biodiversity
(McLaughlin and Mineau, 1995), and increases greenhouse gas emissions (Campbell et al.,
1995). These consequences have serious implications for food security of both rural and
urban populations. In addition, as soils become less productive, farmers’ earnings decrease
making it more difficult to sustain their livelihoods.
In Canada, soil health and quality are the most significant agricultural issues. Farmers in
the Canadian prairies typically follow chemical intensive practices to maintain soil
productivity and that compensate for the effects of increased loss of organic matter, soil
erosion, acidification and salinization. The annual estimated loss from soil erosion in terms
of lost productivity on the prairies is between 350-450 million dollars (Dumanski et al.,
1986) of which 40-45% loss is governed by water erosion. The top soil losses in the
prairies exceed the rate of soil formation with the annual loss of more than 117 and 160
million tons of soil from water and wind erosion, respectively (Sparrow, 1984). These
losses significantly reduce soil productivity through nutrient removal, organic matter
3
degradation, and reduced soil water holding capacity. In terms of grain yield, annual losses
are near 4.6 million tons, 15% of which cannot be compensated for by additional fertilizer
application (Sparrow, 1984).
Conventional high-till cereal production increases the rate of organic matter loss from the
top soil. The average loss of organic matter ranges between 36 to 49 percent in
chernozemic soils of the prairies (McGill et al., 1981). In addition, nearly 2.2 million
hectares of land in the prairies suffer from salinization from the use of synthetic fertilizers,
with an estimated annual economic loss between 104-257 million CAD (Dumanski et al.,
1986).
These important soil quality issues suggest that more effort is needed to develop
environmentally and economically sustainable production systems for small grain
producers. Furthermore, it is equally important to restore the degraded soil by using
integrated agroecological approaches in crop production and soil management. One
strategy that may meet these goals is to intercrop grain legumes with small grains under
organic production conditions.
1.2 Intercropping: An Alternative to Conventional Small Grain Production
Intercropping is defined as growing of two or more crops simultaneously on the same land
during a single growing season (Ofori and Stern, 1987). It can meet several ecological goals
including increasing biological diversity, promoting species interaction and enabling
natural nutrient regulation (Hauggaard-Nielsen et al., 2007). Also, intercropping provides a
number of additional benefits including reducing soil erosion (Lithourgidis et al., 2011),
increasing weed suppression (Bulson et al., 1997; Haymes and Lee, 1999), increasing
4
moisture retention (Ghanbari et al., 2010), maintaining soil fertility (Hauggaard-Nielsen et
al., 2009), and increasing nutrient cycling (Hauggaard-Nielsen et al., 2003) and biological
nitrogen fixation (Bulson et al., 1997; Jensen, 1996). It provides an opportunity to improve
agriculture through increased production (Hauggaard-Nielsen et al., 2007), enhanced soil
conservation (Lithourgidis et al., 2011) and significant labour savings (Thurston, 1996).
Typically, intercrop components are from different species or families with one crop of
primary importance (e.g., food) while the other primarily providing some other benefit
(e.g., N2 fixation). An effective intercrop combination is one that produces greater total
yield on a piece of land and uses resources more efficiently than would otherwise be used
when each crop is grown as a monoculture (Inal et al., 2007).
Beans are a group of valuable legume species being assessed as intercrops in small grain
cropping systems (Ghanbari-Bonjar and Lee, 2002; Gooding et al., 2007; Haymes and Lee,
1999; Pristeri et al., 2006). Other legumes used as an intercrop in sustainable wheat and
barley production include pea, (Pisum sativum L.; Ghaley et al., 2005; Subedi, 1997), lentil,
(Lens culinaris L.; Dusa, 2009) and red clover, (Trifolium pratense L.; Blaser et al., 2006).
The combination of a non-N2-fixing cereal (i.e., wheat, barley) with a N2-fixing leguminous
species (i.e., bean, pea) can provide multiple benefits over monoculture production (Ofori
and Stern, 1987; Trenbath, 1974) as legumes improve soil fertility through the legumerhizobia symbiosis (Jensen, 1986; 1996). This combination also fits well within the
principles of organic farming since it is practiced without the use of agrochemicals or
synthetic N fertilizers (USDA, 1980). Therefore, growing small grains with grain legumes
under organic farming practices is seen as a strong component of a farm-wide production
system that fulfills economic and environmental sustainability concerns.
5
In wheat and barley intercrop research, many studies have included pea, while few
assessed common bean (Phaseolus vulgaris L.) or fava bean (Vicia faba L.). Furthermore,
the effect of species ratios and spatial configuration within an organic production context
has yet to be investigated. Similarly, most of the previous research on intercropping
systems has only assessed traditional performance metrics i.e., yield, disease and pest
pressure, crop competition, and weed control (Ghaley et al., 2005; Gooding et al., 2007;
Hauggaard-Nielsen et al., 2003; 2009; Jensen, 1996; Lauk and Lauk, 2008; Subedi, 1997).
However, metrics related to environmental sustainability also need to be measured. These
include N-use efficiency (i.e., biological nitrogen fixation and transfer to the companion
plants), net ecosystem CO2 exchange (NEE), ecosystem respiration (Re), gross ecosystem
photosynthesis (GEP) also referred to as gross primary productivity of the cropland,
carbon sequestration or net ecosystem productivity (NEP), water use efficiency (WUE), and
their association with crop performance, grain yield, and biomass production.
1.3 Nitrogen Transfer between Legumes and Associated Non-legume Plants
Nitrogen is an essential element in crop production and often the most limiting nutrient in
agro-ecosystems. In addition, N management in small grain production is especially
challenging for farmers due to the large acreage planted and the observed increases in
fertilizer prices, emission of nitrous oxide (N2O) from these fertilizers, and their potential
to contaminate ground and surface water sources (Ferguson et al., 1999). Effective
nitrogen management, therefore, is a key to improving soil health, environmental quality,
and financial returns from crop production. With this context, it is important to understand
crop nitrogen requirements and the amount of N present in the system in order to supply
6
optimum N levels for profitable yields, while also protecting the environment (Campbell et
al., 1995; Robertson, 1997).
Biological nitrogen fixation (BNF) by the legume component helps to fulfill the nitrogen
requirement of the companion species through improved soil fertility and the potential
transfer of nitrogen through root exudates and root connections. Advances in plant N
research suggest that a plant can acquire N from companion plants through transfer (He et
al., 2003; Stern, 1993) that usually occurs between a donor (i.e., a N2-fixing plant) and a
receiver (i.e., a non N2-fixing plant), a process termed inter-plant N transfer (Johansen and
Jensen, 1996; Stern, 1993). It is defined as ‘a process of N fixation and deposition from one
plant and subsequent transfer or uptake by another plant’ (Jensen, 1996).
There are two different pathways through which N-transfer occurs in plants, i.e., direct and
indirect N-transfers. Direct N-transfer occurs through the activities of mycorrhizae and
their hyphal network connecting donor and receiver plants, commonly known as common
mycorrhizal networks (CMN) (Habte, 2000; Newman, 1988). Mycorrhizae can form CMN by
extending their hyphae from the roots of mycorrhizal plants to the roots of nonmycorrhizal species when planted in close proximity thus, facilitating transfer (He et al.
2003; Newman, 1988). Indirect N-transfer however, is related to the release of soluble
nitrogen (e.g., NH4+, NO3-) from the legumes to the soil and subsequent movement to the
roots of receiver plants through mass-flow or diffusion (San-nai and Ming-pu, 2000).
Alternatively, mycorrhizal hyphae in the receiver’s roots may absorb and translocate the N
released by the donor plant (San-nai and Ming-pu, 2000). Nitrogen transfer is particularly
evident when soil nitrogen is limited (Fujita et al., 1992).
7
A number of reports have revealed the significance of inter-plant N transfer by using
isotopic nitrogen variation using
15N
15N
labelled fertilizers (He et al., 2003; Stern, 1993) and
natural abundance methods (Shearer and Kohl, 1988). Results from
15N
studies,
however, vary greatly for the amount of N transferred (i.e., ≤5 to 20% of the N in the
receiver plants) from N2-fixing donor to the non-N2-fixing receiver (He et al., 2003; 2009).
Some reports indicate that inter-plant N transfer occurs and may increase the growth of the
grass community when planted with N2-fixing forage legumes (Brophy et al., 1987; Heichel
and Henjum, 1991).
Despite these observations of inter-plant N transfer, there are a number of questions yet to
be investigated. These include: 1) Is inter-plant N transfer within a growing season
occurring? 2) If occurring, what are the effects of N transfer on donor crop performance? 3)
What level of variation exists among individual legume species and cultivars in terms of N
transfer? and 4) Does spatial arrangement affect the extent of N fixation and transfer?
1.4 Estimating Nitrogen Fixation and Transfer using 15N Isotope Methods
The most useful and commonly used methods for estimating N2 fixation are classified into
three groups: nitrogen accumulation, acetylene reduction, and use of 15N, with each method
having its own advantages and limitations. The
15N
isotopic methods are considered the
most precise for studies in complex biological systems because N has several stable
isotopes available for monitoring. Isotopes are ‘atoms of the same element that differ in
atomic mass due to differences in the number of neutrons contained in the atoms' nuclei’ (He
et al., 2009). There are several known isotopes of nitrogen (i.e., 10N, 11N, 11mN, 12N, 13N, 14N,
15N, 16N, 17N, 18N, 19N, 20N, 21N, 22N, 23N, 24N
and
25N),
but the most easily detectable are
8
radioactive and not suitable for this research because of half-lives of less than 11 min (He
et al., 2009). Although the radioactive isotopes can be traced and have been used in N2
fixation studies, the technical difficulties involved do not allow for their general use under
agricultural conditions (Warembourg, 1993).
Two stable isotopes of nitrogen useful for longer-term research are 14N and 15N. They occur
naturally in the environment and are most commonly used in ecological and agronomic
research. Of the two isotopes, 14N is more abundant (~99.6337%) than 15N (~0.3663%) in
the atmosphere with their ratio (i.e., 0.0036765) remaining constant (He et al., 2009). The
stability of this atmospheric ratio is the reason why atmospheric N2 is used as a ‘standard’
in mass spectrometric analysis of
15N
(Knowles and Blackburn, 1993; Mariotti, 1983).
However, the ratio of isotopes is normally different in the soil environment since
biochemical and physiological processes discriminate against 15N due to its greater atomic
mass (He et al., 2009). By using these naturally occurring processes (natural 15N abundance
method, δ15N, ‰), or by artificially inducing them through the addition of 15N, either in the
atmosphere (15N2 method) or in the soil (15N labelled fertilizer method, often called the 15N
isotope dilution method, usually expressed as atom %), it is possible to estimate the
amount of N derived from biological fixation.
Of the three isotopic methods,
15N
natural abundance (δ15N) and
15N
labelling methods
have been most commonly used in BNF and transfer studies (He et al., 2003; Newman,
1988; Stern, 1993). Both of these methods are considered appropriate for longer-term field
studies as they provide information on the extent of N added to soil through BNF (Hogberg,
1997), N input from fertilizers (Robinson, 2001), the extent of N cycling (Boddey et al.,
2000), and possible identification of alternate N sources available to plants (Dawson et al.,
9
2002). The 15N natural abundance method was deemed most appropriate for this research
and is further discussed below.
1.4.1 15N natural abundance method
The
15N
natural abundance method is considered a precise alternative for N2 fixation and
transfer studies to either the
15N
labelled fertilizer method or the classic N accumulation
method (Shearer and Kohl, 1988). In this method, endogenous N is used to estimate the
relative contribution of two sources (i.e., soil and atmosphere) to a common sink.
Therefore, it does not require an added tracer or artificially labelled fertilizer. This method
uses the differences in 15N abundance (δ15N, ‰ 15N) between atmospheric N2 and soil N to
estimate the relative contribution of symbiotically fixed N to plant-soil systems. The
difference is usually small but able to be measured precisely and calculated using the
following equation (Shearer and Kohl, 1988):
δ15N (‰) = 1000 x (R sample – R standard)/ R standard…………………………………………………………..1
where the subscript ‘sample’ refers to the experimental sample and the ‘standard’ is
typically atmospheric N2 (δ15N = 0; Mariotti, 1983). R is the ratio of the concentration of 15N
to the total N in the sample under investigation. This may be written as R = 15N / (15N + 14N)
or R =
15N/14N.
The first equation is generally more useful when the subject is source
identification with the latter more useful when the subject is isotope discrimination
(Shearer and Kohl, 1988). At the level of natural abundance, these two definitions are
operationally indistinguishable because the difference in δ15N values calculated using these
two equations is negligible i.e., much smaller than the error of measurement.
10
The percentage of plant N derived from atmospheric N2 (% NDFA) is calculated according
to Shearer and Kohl (1986) as follows:
% NDFA = 100 x (δ15Nref − δ15Nleg) / (δ15Nref − δ15Nfix)……………………………………………………2
In this equation, δ15Nref is the δ15N value of the non-N-fixing reference plants grown alone
and dependent on soil N; δ15Nleg is the δ15N value from the nodulating and potentially N2fixing legumes (grown in mixed culture in the case of intercropping) where fixed N and soil
N are both available as N sources; and δ15Nfix is the δ15N value for the nodulating N2-fixing
plants when they are totally dependent on biological nitrogen fixation (BNF) as their N
source. Therefore, inoculated N2-fixing plants should be grown in N-free nutrient media to
determine δ15N value for the nodulating N2-fixing plants (δ15Nfix). The δ15N of biologically
fixed N (δ15Nfix) is usually less than the atmospheric δ15N (= 0) and is often lies between −1
and −2‰ (Shearer and Kohl, 1991).
The amount of N transferred from donor to receiver plants in an intercropping system can
be calculated as one-way N transfer from N2-fixing legumes to the non- N2-fixing receiver
as follows (He, 2002):
% N transfer = 100 x (δ15N receiver mono - δ15N receiver intercrop) / δ15N receiver mono……..3
In some cases, N can be transferred from the non-N2-fixing donor to the N2-fixing receiver
and is calculated as:
% N transfer = 100 x (δ15N receiver intercrop - δ15N receiver mono) / δ15N receiver mono…….4
One of the major advantages of
15N
natural abundance method lies in its minimum
disturbance to the plant–soil system that makes it possible to trace long-term 15N variation
in agro-ecosystems (Shearer and Kohl, 1986; 1988). The similarity between the 15N natural
11
abundance method and the
15N
enrichment method is that they both require a reference
plant to estimate the amount of N2 fixed symbiotically and transferred to the non-N2-fixing
plant. The accuracy of these methods depends on the selection of appropriate reference
materials to avoid the difficulties associated with the soil’s spatial and temporal variation
in δ15N. Care must be taken that the δ15N values for soil derived nitrogen be the same in N2fixing and reference plants (Shearer and Kohl, 1986). Although an ideal non-N2-fixing
reference plant having similar root architecture and shoot morphology is very difficult to
find, studies of grain legumes such as common bean, fava bean, pea and soybean have used
non-nodulating cereals such as wheat, barley, and even rapeseed as reference plants
(Warembourg, 1993).
The 15N natural abundance method cannot be applied to all sites. This method requires that
the soil be homogeneous so that the variation in soil N across the test site is smaller than
the amount of biologically fixed nitrogen. This method gives reliable results in soils with
low N as N2 fixation, translocation or cycling processes are normally inhibited under high
soil N levels. This method is also based on the assumption that biological and chemical
processes in soil (e.g., mineralization) prefer
the heavier
15N
14N
as these processes discriminate against
form (Yoneyama, 1996) thereby enriching the soil with
15N
compared to
the atmosphere. This results in a significant difference (usually 3–4‰) in the δ15N values
between soil and the N derived from other sources (i.e., atmosphere). In general, soil
derived N shows higher δ15N values compared to atmospheric N2 resulting in a greater δ15N
value in non-N2-fixing plants (Shearer and Kohl, 1986).
12
1.5 Understanding Wheat and Barley Root Architecture
Increasing our understanding and characterization of inter- and intra-specific variation of
root architecture has implications in plant ecology, agronomy, and resource use efficiency.
A plant’s root architecture is an important trait in crop breeding and improvement
programs designed to develop improved cultivars with tolerance to drought and mineral
toxicity, water and nutrient uptake efficiency and lodging resistance (Manske and Vlek,
2002). This is especially true for small grain improvement programs that screen and select
appropriate crops and cultivars for specific soil and climatic conditions. Also, root
architecture is considered crucial in determining crop adaptability to marginal
environments, especially in the areas with limited water, nitrogen and phosphorus
availability. In cereal-legume intercropping systems, root growth and architecture play
important roles in determining which crops or cultivars are best suited to co-cultivate.
In addition to crop genotype, root growth and architecture are affected by soil type and
nutrient and water supplies in the rhizosphere. In general, shorter, thicker, and more
branched roots develop in compacted soils whereas non-compacted soils promote thinner
and longer root systems (Dexter, 1987). Cholick et al. (1977) and Vlek et al. (1996) suggest
that small grains produce thinner roots under water or nutrient stressed conditions, and
display a significant plasticity in root growth to help adapt to marginal soil conditions.
Furthermore, plants often respond to marginal soil conditions by increasing nutrient
uptake efficiency (Egle et al., 1999) through altering root growth and patterns (Horst et al.,
1996) and by increasing root to shoot ratios (Manske and Vlek, 2002).
13
Wheat and barley normally develop three to seven primary roots that constitute up to 14%
of the volume of the entire root system (Manske and Vlek, 2002). These primary roots grow
first and are important in early crop establishment while the secondary roots develop later
throughout the vegetative period (Klepper, 1991). The secondary roots grow shallower and
horizontally further from the stem with their number positively correlated with tillering
ability (Hockett, 1986). Wheat genotypes are classified as ‘high input’ and ‘low input’ based
on the number of tillers, harvest index-HI, and root architecture (Manske et al., 2000). High
input wheat genotypes normally possess fewer tillers, higher harvest index, and shorter
and coarser roots (i.e., greater root diameters) while the root systems of low-input
genotypes normally possess more tillers, lower harvest index, longer, and thinner roots
that allow for greater soil exploration (Masnke et al., 2000; Vlek et al., 1996).
Root architecture plays a significant role in water and nutrient uptake by plants. Root
length and diameter significantly affect nutrient and water uptake efficiencies in small
grains (Jones et al., 1989). The important feature of wheat and barley is that they acquire
the vast majority of their nutrients, including nitrogen, from their secondary roots shallow
in the soil profile, typically in the upper 10 cm (Bole, 1977). Unfortunately, conventional
selection under high input conditions has inadvertently co-selected for shorter and coarser
root systems. Therefore, wheat breeding programs designed to improve water and nutrient
uptake should include selection for longer and thinner root systems allowing plant roots to
explore a greater soil volume.
As root architecture strongly affects plant performance, understanding the inherent
variation among cultivars is important for both plant breeders and farmers. There remains
a great need to accurately characterize and associate root architectures with both
14
inheritance and production performance. In addition, characterizing root architecture
variation can help link our fundamental knowledge across plant science disciplines, e.g.,
plant ecology, plant physiology, and agronomy (Bodner et al., 2013). Finally, significantly
more research has been conducted on the above-ground plant parts compared with belowground parts, despite its accepted importance (Manske and Vlek, 2002). Therefore, we
assessed heirloom and commercial cultivars of wheat and barley to improve our
understanding of the variation in small grain root architecture and to assess their potential
for low input sustainable agriculture.
1.6 CO2 Uptake, Respiration and Carbon Sequestration
Carbon dioxide (CO2) is the primary greenhouse gas (GHG) associated with human
activities and accounts for approximately 84% of all GHG emissions (USEPA, 2013). CO2
concentrations in the atmosphere have been rising, from approximately 315 ppm in 1959
to a current atmospheric average of 401 ppm (UCSD, 2014), and are projected to reach as
high as 500-1000 ppm by 2100 (IPCC, 2007). Soil plays a crucial role in the global carbon
(C) cycle (Houghton et al., 1995; Schimel, 1995) as a major sink for atmospheric C
(Schlesinger and Andrews, 2000) through soil organic matter (SOM) accumulation. The soil
organic carbon (SOC) pools in agricultural systems, however, are currently in
disequilibrium with the environment as the losses attributed to decomposition exceed the
gains associated with biomass addition (Jarecki and Lal, 2003). This suggests development
of agricultural systems that fix more CO2 (i.e., greater gross ecosystem photosynthesisGEP) with the release of less CO2 (i.e., ecosystem respiration- Re) which would help balance,
and ultimately move to positive CO2 movement between agricultural ecosystems and the
atmosphere, a term referred to as net ecosystem CO2 exchange (NEE). Furthermore, it is
15
essential to enhance net SOM gains through simultaneously increasing plant biomass
deposition and decreasing decomposition to reduce agricultural emissions of GHGs.
Crop plants are the primary source of new carbon that enters the soil in agricultural
systems. Through photosynthesis, plants fix atmospheric CO2 to produce carbohydrates
(Beedlow et al., 2004) which drive the growth of new tissues. However, not all
carbohydrates fixed by plants are used for growth as nearly half is lost as CO2 during
respiration (Cambardella, 2005). A portion of the remaining carbohydrate is available for
transfer to the soil through different plant parts e.g., leaves, stem, root exudates, etc. which
over time, eventually transform into stable soil organic matter.
Plants require adequate N for photosynthesis and growth leading to increased SOM and
carbon stores (Beedlow et al., 2004). However, different species have different N
requirements with N2-fixing legumes requiring less soil nitrogen compared to non-N2fixing species such as cereals. When these two types are planted together in an
intercropping system, the legume component may provide additional N to the cereal
thereby inducing a positive growth response in it. If this is true, planting N2-fixing legumes
with N-demanding cereals (e.g., wheat, barley) under low input organic systems should
provide greater yields than with monoculture production. Therefore, in addition to
quantifying the amount of C accumulated in grains and shoot biomass, it is important to
measure CO2 movement between an agricultural ecosystem and the atmosphere, a term
referred to as net ecosystem CO2 exchange (NEE), and ecosystem respiration (Re) to
calculate gross ecosystem photosynthesis - GEP (i.e., ecosystem respiration (Re) minus NEE,
often referred to as gross primary productivity of the cropland), and net ecosystem
16
productivity - NEP (i.e., NEE with a negative sign). This information allows for the
assessment of intercrop systems’ potential to help mitigate agricultural GHG emissions.
1.7 Water Use Efficiency
Water use efficiency (WUE) in agronomy is often defined as the crop yield per unit of water
consumed. However, there are various ways of interpreting ‘yield’ (i.e., grain or total
biomass) and ‘water consumption’ (i.e., total water input, total water evapotranspired or
total water transpired) (VanLoocke et al., 2012). Regardless of how WUE is defined, the
increasing scarcity of and competition for water resources for agriculture is pressing us to
design more water efficient production systems, especially for rain-fed locations. WUE in
crop production can be improved by adopting crop management practices that reduce
evapotranspiration, surface run-off and drainage, and by effective N management that
promotes rapid early crop growth that shades the soil thereby reducing additional
evapotranspirative losses (Gaiser et al., 2004), and through breeding and selection to
acquire more C (i.e., biomass) in exchange for the water transpired by the crop, i.e.,
improving crop transpiration efficiency (Condon et al., 2004). Intercropping may improve
the production system’s WUE as it increases water uptake and storage in root zones
through the presence of diverse root systems, and reduces inter-row evaporation and
excessive transpiration by promoting crop growth that shades the soil creating a protected
microclimate (Zhang et al., 2012).
Plant carbon isotopic composition values (δ13C) can be considered a proxy of intrinsic
water use efficiency of crop plants (WUE) (Condon et al., 1987; 2002) where less negative
δ13C values indicate higher WUE and more negative δ13C values indicate lower WUE. The
17
basis of using δ13C values as a proxy of intrinsic WUE of plants lies on the fact that
biochemical reactions (e.g., photosynthesis) discriminate against the heavier 13C isotope as
it is less reactive than
12C.
Therefore, the isotopic composition (i.e.,
13C/12C)
reflects the
effect of plant water status on photosynthesis throughout the cropping season where
greater
12C
content is linked to increased photosynthesis relative to transpiration.
Therefore, measuring δ13C values and calculating intrinsic WUE of wheat in monoculture
and intercrop systems may allow the assessment of system wide WUE.
1.8 Research Goal and Specific Objectives
The overarching goal of this project is to increase the sustainability of small scale farming
systems through modification of the predominant cereal-based cropping system with the
integration of grain legumes as an intercrop component. This is aimed to maintain or
increase overall productivity of the system while reducing N fertilizer inputs and
promoting increased environmental benefits for society and economic benefits for farmers.
The specific objectives of this project were to:
1) Evaluate heirloom and commercial cultivars of cereals and legumes for plant
performance metrics (e.g., grain yield, 1000 seed weight, protein content, days to
heading, harvest index, disease incidence and severity, nodulation) and their
potential for inclusion in cereal:legume intercrop trials;
2) Identify the most functional genotype pairings for intercrop synergies (i.e., Nfixation and transfer, C sequestration, etc.) based on plant traits (i.e., root growth
and architecture, maturation dates, canopy cover, yield, disease resistance, etc);
18
3) Identify intercropping combinations and designs that maximize synergies, as
compared to monoculture plots, including N and water use efficiencies, C
sequestration and productivity metrics;
4) Quantify the amount of biologically fixed nitrogen introduced by different legume
genotypes and the amount transferred to wheat or barley across various spatial
arrangements;
5) Determine the carbon fluxes and WUE as affected by genotype and spatial
arrangement, and;
6) Recommend the optimal combination of practices that are both productive and
environmentally sustainable.
19
CHAPTER 2: CULTIVAR EVALUATION TRIAL
 A version of this chapter has been published as Chapagain, T. and A. Riseman (2012),
Evaluation of Heirloom and Commercial Cultivars of Small Grains under Low Input
Organic Systems. American Journal of Plant Sciences 3 (5): 655-669.
This study was conducted at the Centre for Sustainable Food Systems at UBC Farm in
Vancouver, BC, during 2010-cropping season (May to September) to assess plant
performance metrics of heirloom and commercial cultivars of small grains available in the
region, and their potential in a small grain:legume intercropping system. The experimental
site is located at 49° 15' 3" N and 123° 14' 20" W, at an altitude of 100 m above mean sea
level. Research was conducted under natural climatic conditions and organic growing
context.
2.1 Materials and Methods
2.1.1 Climate description of the study area
Climatic data are summarized for the experimental site during the spring-summer season
(June to September) of 2010 (Table 2.1). Average day-time temperature over the cropping
season was 17.1°C, with the warmest days in August, whereas the average night-time
temperature was 14.6°C. The average daily soil temperature at 10 cm and 20 cm depth was
18.9°C and 18.6°C, respectively. Monthly average of solar irradiance was 590.3 W m-2. The
monthly precipitation average was 61.5 mm with July receiving the least rain and
September receiving the most. Total precipitation during June to September was 245.8 mm.
The 24-hour average for relative humidity (RH) ranged from 73.2 to 83.8 in July and
September, respectively.
20
2.1.2 Soil and site description
Four random composite soil samples were collected at the time of plot establishment to
characterize soil fertility (i.e., pH, EC, organic matter, total N, and available P, K, Ca, Mg, Cu,
Zn, Fe, Mn and B). The average values are listed (Table 2.2). The soil was a coarse textured
sandy loam of the Bose series (Bertrand et al., 1991) with low to moderate fertility. Soil
was fairly homogeneous across the test site. The site was not used for grain production in
prior years but was a designated area for seasonal vegetable cultivation. The land has been
managed under organic guidelines for more than the 10 years and therefore does not
include any prohibited chemicals/substances.
2.1.3 Experimental details
Commercial and heirloom cultivars of wheat, barley, pea, lentil, fava bean, kidney bean, and
soybean were sourced from farmers in BC, Agriculture and Agri-Food Canada, and various
states throughout the USA (i.e., Alaska, California, Colorado, Connecticut, Idaho, Maine,
Oregon, Vermont, Wisconsin, and Washington). Commercial and heirloom cultivar
descriptions and planting details are listed (Table 2.3, 2.4, Appendix L).
All cultivars listed were provided with the same level of management. Seeds were cleaned
as necessary, counted (except for commercial cultivars for which 1000 seed weights were
provided), and weighed to calculate the appropriate seeding rate. Wheat and barley
cultivars were sown using a hand seeder (Jang Clean Hand Seeder, Jang Automation Co.
Ltd., Cheongju-city, South Korea) with adjustable sprockets (Front: 11, Rear: 14), and seed
plates (AA-6 for wheat and barley, G-12 for pea) whereas grain legumes were planted by
hand along the line using the seed rate as specified.
21
Spring cereals were planted at 12 cm spacing in late May (28-30 May, 2010) targeting 280300 viable plants m-2. Therefore, assuming a >80% germination rate, a seed density of 350
seed m-2 for wheat and barley cultivars was used. Our seed densities for pea, lentil, fava
bean, kidney bean and soybean were 66, 200, 33, 33, and 33 seeds m-2, respectively,
targeting 60, 160, 30, 30 and 30 viable plants m-2. This was a non-replicated trial with both
the commercial and heirloom cultivar plots measured 9m x 3m however, the plot was
divided into three subplots of 3m x 3m, and data were collected from 2 different areas of
0.5 x 0.5m2 within each subplot and averaged, serving as one sample.
Sowing depth varied with seed size and ranged from 3-4 cm for small seeds like wheat,
barley and lentil, and 4-5 cm for larger seeds like fava bean and kidney bean. Plot layout
was alternated between wheat, barley and legumes to minimize out-crossing between
cultivars. Plots were equipped with a sprinkle irrigation system for timely irrigation during
long dry periods. No external fertilizers, pesticides or fungicides were used on test plots
throughout the growing season.
2.1.4 Data collection and analysis
Plant-based parameters: Data were recorded for plant height (from soil surface to the tip of
apical leaf), number of effective tillers (heads) m-2, days to harvest, spike length, seed spike1,
grain yield (t ha-1), 1000 seed weight, harvest index [HI, defined as a ratio of economic
yield (grain yield) to the total plant mass (grain yield + shoot biomass)], and seed weight to
volume ratio. Chlorophyll concentration index (CCI) was measured using handheld
chlorophyll meter (Model CCM 200 plus, Opti-Sciences Inc., New Hampshire, USA) on the
flag leaf and the 3rd leaf during early growth stage (30 DAS). Spike color was a determinant
22
of maturity and considered ready for harvest when spikelets were straw-colored and 80%
of the grains of the spike were in the hard-dough stage. The plots were sampled by
harvesting the above ground biomass from 2 different areas of 0.5 x 0.5 m2 within each
subplot, leaving 10 cm stubble. Crop material was dried at 60oC and threshed. Grain was
ground to fine powder (<0.6 mm) and analyzed for total nitrogen, according to the Kjeldahl
method (Appendix A) and converted to crude protein levels (%N x 5.8 for wheat and
barley, and %N x 6.25 for pea and beans) (Jones, 1931). Each sample was replicated thrice.
Grain yield, 1000 grain weight, and protein concentrations were expressed at 12.5%
moisture.
Crop management parameters: General observations were made 30 and 70 days after
sowing (DAS) on the type and number of weeds present and insect pest and disease
pressures with regard to type and nature of damage. Cereal stem, leaf and head diseases of
economic importance including Fusarium (Fusarium spp.), Barley Stripe (Helminthosporium
gramineum),
Scald
or
Leaf
Blotch
(Rhynchosporium
secalis),
Stem/Leaf/Stripe/Yellow/Brown Rust (Puccinia spp.), Septoria Leaf Spot or Glume Blotch
(Septoria tritici) were monitored and noted over the course of the season. Plants were
assessed for disease resistance at Zadoks growth stages (ZGS) as devised by Zadoks et al.
(1974) and expanded by Tottman (1987). Disease assessments were conducted on five
random plants from each plot. Rating was done according to the assessment key (Table 2.5,
Figure 2.1) used by the Eco-friendly Crop Rotation Project operated in Delta, BC by the
Delta Farmers’ Institute & Faculty of Land and Food Systems, UBC, Canada (Temple, 2009).
Lodging was assessed before harvest on a 0-10 scale (i.e., 0 for 100% erect plants, and 10
for complete lodging of whole plot) based on visual observation. The angle of lodging was
23
also assessed. Plants that were completely bent down to the ground (60 to 90o) with all
spikes touching the soil surface were considered completely lodged while the plants up to
60o without having spikes contacting the soil surface were considered partially lodged. The
scores were averaged and transformed into percentages.
Legume nodulation: Nodulation was assessed by examining the roots of 3 randomly
selected plants, 30 and 70 DAS, from each plot. Measurements included earliness of
nodulation, total nodule number, color and distribution followed by the visual nodulation
scores as described in Table 2.6. Visual scoring used a 0 to 5 scale and was based on nodule
number, size, pigmentation and distribution (Corbin et al., 1977). The scores from all plants
were added and then divided by the number of plants to obtain a mean nodule score.
Data were compiled and subjected to analysis using MSTAT-C (MSU, 1993). Simple
correlation coefficients and coefficients of determination were determined between
selected parameters using Statistical Package for the Social Sciences (SPSS) software.
2.2 Results and Discussion
2.2.1 Plant-based parameters
Wheat: The response of commercial and heirloom wheat cultivars on key vegetative and
reproductive parameters is shown (Table 2.7). In general, heirloom cultivars showed
notable response in a number of parameters compared with commercial cultivars including
later maturity, taller plants, greater number of spikes m-2, longest spike, higher number of
seed spike-1, and greater seed weight to volume ratio. There existed significant variation
among the heirloom cultivars while the commercial cultivars were more uniform for a
number of plant based parameters. Significant variation was also observed between 6-row
24
hulless and 2-row hulled cultivars with 2-row hulled-type showing higher disease
resistance but with lower grain yield and HI. Commercial cultivars displayed the highest
1000 seed weights, grain weights and HIs (Table 2.7).
Heirloom cultivars matured 1-4 weeks later as compared to the commercial cultivars,
though harvest date varied. ‘Pacific Blue Stem’ took 135 days to harvest followed by
‘Einkorn’ and ‘Red Fife’ (125 days) while ‘Sounders’ and ‘Reward’ matured the earliest (95
days). Except for ‘Snowbird’ and ‘Snowstar’, commercial cultivars were near the average of
105 days to harvest. ‘Snowstar’ and ‘Snowbird’ matured 5-15 days earlier than the other
commercial cultivars.
Heirloom cultivars produced taller plants compared to commercial cultivars. The tallest
cultivar was ‘Red Fife’ (135 cm) followed by ‘Red Bobs’ (133 cm), and ‘Reward’ (127 cm).
Commercial cultivars produced short to medium plants, the shortest being the ‘Strongfield’
(98 cm) accompanied by the heirloom ‘Sounders’ (100 cm). The earliest heirloom cultivar
‘Reward’ produced taller plants (127 cm) while the latest commercial cultivar ‘Strongfield’
produced the shortest (98 cm) plant.
Except for ‘Red Fife’, heirloom cultivars produced greater numbers of spikes m-2 compared
to commercial cultivars (Table 2.7). The lowest spike density (419 m-2) in ‘Red Fife’ was
due low germination rate (as low as 20%). However, the spike density of 419 was achieved
as it produced greater number of tillers plant-1. The commercial cultivar ‘Lillian’ showed
similar responses.
‘Red Fife’, a 6-row hulless heirloom cultivar, produced the longest spikes (10.6 cm)
followed by ‘Calcutta’ and ‘Pacific Blue Stem’ (9.3 cm) while ‘Red Bobs’ gave the highest
25
number of seed spike-1. However, 2-row heirloom hulled wheat (e.g., Emmer and Enkorn
series) produced the shortest spikes with the fewest number of seeds spike-1 resulting in
comparatively lower grain yields than 6-row hulless cultivars (Table 2.7).
The 6-row heirloom hulless cultivars (e.g., ‘Reward’, ‘Glenn’, ‘Cerebs’, ‘Red Bobs’, and
‘Sounders’) produced grain yields (5.2, 5.1, 4.9, 4.6, and 4.6 t ha-1, respectively) comparable
to the commercial cultivars. Despite having a moderate number of seeds spike-1 (39) and
comparatively higher 1000 seed weight (44 g), ‘Red Fife’ produced lower yield (4.1 t ha-1)
and could be associated with fewer spikes m-2. The heirloom cultivars typically had lower
HI as they produced taller plants (i.e., greatest biomass). The cultivar ‘Pacific Blue Stem’
had the lowest yield (2.5 t ha-1) and HI (21%) which may be due to the spikes containing
unfilled spikelets with mold developing, perhaps due to the later harvest.
Among commercial cultivars, ‘Scarlet’, a 6-row hulless, gave the longest spikes (9.2 cm)
with a moderate number of seeds spike-1 (39), the highest 1000 seed weight (48 g)
resulting in highest grain yields (5.4 t ha-1) and HI (48.4%). It was followed by ‘Norwell’
with the highest number of seeds spike-1 (42), good 1000 seed weight (45 g), and grain
yield (5.3 t ha-1).
Heirloom wheat showed greater weight to volume ratios compared to commercial cultivars
with ‘Glenn’ and ‘Reward’ displaying the greatest weight to volume ratio (0.85:1). The ratio
was lowest in 2-row hulled wheat (e.g., Emmer and Enkorn series) as the hulled (with awn)
and longer grains occupied more volume but were lighter in weight. The ratio was highest
in the hulless cultivars with smaller sized and more uniform seeds.
26
Overall, the yield from commercial cultivars was greater than the Canadian yield average
(~3 t ha-1). This finding is in line with the reports of Halstead (2007) who reported the
yield of two different cultivars ‘Reaper’ and ‘Monopol’ as 5.8 t ha-1 and 7.2 t ha-1,
respectively, when grown at the UBC Farm. Similar yield responses were reported by
Kidwell et al. (2009) in eastern Washington using other cultivars. They found the grain
yield averages of ‘Kelse’, ‘WestBred 926’, ‘Tara 2002’, and ‘Hank’ as 5.2, 5.3, 5.4, and 5.7 t
ha-1, respectively. In addition, Temple (2009) also reported a yield of 5.5 t ha-1 from
‘Norwell’ when working with spring wheat grown by farmer co-operators in Delta, BC.
Barley: Production characteristics of the commercial and heirloom barley cultivars are
presented (Table 2.8). Overall, heirloom and commercial cultivars did not differ materially
with respect to a number of plant based parameters including plant height, spike length,
and seed weight to volume ratio. However, a number of heirloom cultivars displayed
greater responses including earliness, number of spikes m-2, grain yield, and seed weight to
volume ratio (Table 2.8).
A clear difference was observed in maturity times between hulless (e.g., ‘Purple’, ‘Sunshine’,
‘Dolma’, ‘Andie’, Excelsior’, ‘Himalayan’, ‘Jet’, ‘Ethiopian’ and ‘CDC Gainer’) and hulled (e.g.,
‘Oxbridge, ‘Westminster’, ‘Decanter’, ‘Copeland’ and ‘Camus’) cultivars with the hullesstypes maturing 1-2 weeks earlier than the hulled-types. This was true for both the 2 and 6row hulless cultivars with 2-row hulless (e.g., ‘Jet’, ‘Ethiopian’ and ‘CDC Gainer’) and 6-row
hulless (e.g., ‘Purple’, ‘Sunshine’, ‘Dolma’, ‘Andie’, Excelsior’ and ‘Himalayan’) maturing 1-2
weeks earlier than 2-row hulled-types (e.g., ‘Oxbridge, ‘Westminster’, ‘Decanter’, ‘Copeland’
and ‘Camus’). One exception was the 6-row hulless cultivar ‘Hooded’ that required 100
days to mature.
27
Except for ‘CDC Gainer’ and ‘Copeland’, 2-row cultivars produced the shortest plants (65-80
cm) compared with 6-row cultivars. UK hulled barley ‘Oxbridge’ produced the shortest
plants (65 cm) while the Canadian hulless ‘CDC Gainer’ and hulled ‘Copeland’ produced the
tallest plants (100 cm). UK spring barleys (e.g., ‘Oxbridge’, ‘Westminster’ and ‘Decanter’)
produced greater number of spikes m-2 compared to other commercial cultivars. The fewer
spikes in ‘Hooded’ (358 m-2), a 6-row hulless barley, was due to poor germination (30%).
The 6-row hulless cultivars (e.g., ‘Burbank’, ‘Sunshine’, ‘Hooded’, ‘Purple’, ‘Dolma’, ‘Andie’,
Excelsior’ and ‘Himalayan’) produced greater numbers of seeds spike-1 and seed weight to
volume ratios but typically consisted of shorter spikes, lower 1000 seed weight, grain yield
and HI than 2-row cultivars. On the other hand, the 2-row hulled cultivars (e.g., ‘Oxbridge,
‘Westminster’, ‘Decanter’, ‘Copeland’ and ‘Camus’), displayed greater 1000 seed weight,
yield and HI but consisted of lower weight to volume ratios than the 2-row hulless cultivars
(e.g., ‘Jet’, ‘Ethiopian’ and ‘CDC Gainer’).
The 2-row UK spring barley ‘Oxbridge’ had the highest yield (6.9 t ha-1) followed by
‘Westminster’ (5.8 t ha-1) and ‘Decanter’ (5.6 t ha-1) while the other commercial barleys
yielded slightly more than 5 t ha-1 (Table 2.8). Hulless barleys had the greatest weight to
volume ratio (up to 0.86:1) with 6-rowed cultivars showing slightly higher ratios than 2row hulless cultivars. Black barleys also appeared promising with 2-row ‘Jet’ producing the
highest yield (5.5 t ha-1) followed by 6-row hulless ‘Hooded’ (4.2 t ha-1). The cultivars
‘Sunshine’ and ‘Dolma’, 6-row brown barleys, also produced greater yields (4.9 t ha-1)
compared to other hulless barleys.
28
Legumes: Production traits of the different legume crops and cultivars are shown (Table
2.9). The heirloom peas ‘Corgi’, ‘De Grace’, ‘Snowbird’, and ‘Golden’ were early maturing
(75-80 DAS) with greater shell to seed ratio (up to 1:6.4) but produced relatively lower
yields, 1000 seed weights, and seed weight to volume ratios compared to the commercial
pea cultivar ‘Reward’. ‘Reward’ produced higher yields although there was significant
variation between the sampled plants and the remaining plot (3 t ha-1 vs. 1.2 t ha-1,
respectively) due to poor germination affecting plant density. Neither lentil cultivar
produced satisfactory results in terms of yield though they had excellent vegetative growth
and flowered. However, most of the pods were barren and/or underdeveloped, perhaps
due to low temperature. The cultivar ‘Essex’ produced relatively good pods containing
white seeds whereas ‘Crimson’ had more pods plant-1 but containing no or only undersized
brown seeds.
Among fava bean cultivars (Table 2.9), heirloom cultivar ‘Bergeron’ matured earliest (95100 DAS) producing the shortest plants (63.8 cm), while ‘Crimson Flowered’ matured latest
(120-125 DAS). Except for ‘Bergeron’, all other cultivars required at least two harvests at
10 day intervals, with ‘Andy’ and ‘Windsor requiring three. The cultivar ‘Bell’ developed an
upright growth habit and produced the highest number of pods plant-1 (7.6) containing
relatively small round seeds that gave the highest seed weight to volume ratio (0.81:1) and
yield (2.9 t ha-1). Cultivars ‘Andy’, ‘Windsor’ and ‘Crimson Flowered’ produced longer pods
than ‘Bell’ (23, 14.6 and 10.3 cm, respectively) containing flat large-sized seeds. As a result,
1000 seed weight was highest in ‘Windsor’ (1512.8 g) followed by ‘Andy’ (1383.6 g).
Kidney beans, although requiring a relatively long growing season (approximately 120
days), did well under UBC’s climate (Table 2.9). On an average, cultivars produced ~4 t ha-1.
29
Cultivar ‘Candy’, a vine-type kidney bean, had the longest plants (97.2 cm) followed by
‘Black Turtle’ (89.4 cm). On cultivar ‘Candy’, pods rotted before maturity because they were
not trellised and received a significant amount of rain while ripening. However, ‘Black
Turtle’ pods did not rot, perhaps due to their shorter more round pods that were held
above the soil surface. Cultivar ‘Golden Rocky’, a dwarf bush bean cultivar, matured 20 days
earlier than other cultivars producing a relatively good yield (4.2 t ha-1) and the greatest
seed weight to volume ratio (0.88:1).
Soybean cultivars ‘Black Jet’ and ‘Edamame’ were the latest to mature (130-135 DAS)
compared with other legumes (Table 2.9). Plant density was low in ‘Edamame’ (20 m-2) due
to poor germination but displayed dwarf bushy growth habit. Cultivar ‘Black Jet’ produced
the tallest plants (79.8 cm) with fewer pods plant-1 (24 vs. 27 in ‘Edamame’) and shorter
pods (5 vs. 6 cm in ‘Edamame’). However, ‘Black Jet’ had higher yield (3.4 t ha-1 compared
to 2 t ha-1 in ‘Edamame’) but most likely due to greater plant density. Cultivar ‘Edamame’
produced large-sized yellow seeds that resulted in greater 1000 seed weight (380.7 g)
compared to ‘Black Jet’ (273.8 g).
2.2.2 Management-based parameters
Weed pressure: The most common weeds were Common Chickweed (Stellaria media L.),
Green Smartweed (Polygonum lapathifolium L.), Prostrate Knotweed (Polygonum aviculare
L.), Pigweed (Amaranthus spp.), Crab Grass (Digitaria spp.), Barnyard Grass (Echinochloa
crusgalli L.), Black nightshade (Solanum nigrum L.), and Field horsetail (Equisetum arvense
L.). Common Chickweed, an excellent colonizer that forms a succulent mat on the soil
surface, covered the whole field starting 20 DAS. Pigweed was observed early in the season
30
in wheat and barley plots along with the chickweed. Other weeds gradually infested the
plots during mid to late season. Wheat and barley plots, with moderate to good plant
density, grew well despite the weed pressure. No weeding/cultivation was done except for
hilling the legumes.
Disease pressure: The most prevalent diseases encountered at our test site included stripe
and stem rusts (Puccinia spp.) and Septoria leaf blotch (Septoria spp.), with most
commercial plots showing some infection starting at the end of June and continuing
through mid-September. Except for ‘Lillian’ and ‘Snowbird’, commercial wheat cultivars
were moderate to highly susceptible to Stripe rust (Table 2.10). Septoria leaf blotch
infection was most severe on ‘Strongfield’, 30 DAS. However stripe/stem rust were most
severe on ‘Snowstar’ and ‘Scarlet’ followed by ‘Norwell’ and ‘Strongfield’ cultivars. ‘Lillian’
was the most resistant commercial wheat cultivar against these diseases followed by
‘Snowbird’.
Except for ‘Pacific Blue Stem’, heirloom wheat cultivars displayed intermediate to high
disease resistance compared with commercial cultivars (Table 2.10). The 2-row hulled
wheat (e.g., Emmer and Einkorn series) were among the most highly resistance cultivars
followed by the 6-row heirloom cultivars. Heirloom 6-row wheat cultivars ‘Red Bobs’, ‘Red
Fife’, ‘Calcutta’ and ‘Red Wheat’ displayed the highest overall performance rating, 30 DAS,
with ‘Red Fife’ producing dark green leaves with the highest chlorophyll concentration
index (18.4 and 16.1 in flag and 3rd leaves, respectively). However, the heirloom wheat e.g.,
‘Red Wheat’ ‘Cerebs’, ‘Black Bearded’, ‘Red Bobs’ and ‘Calcutta’ displayed high plant lodging
percentage compared to the commercial cultivars (Table 2.10), and could be associated
31
with the plant height as well as the location of the trial plots (the border plots in the southwest direction were observed with increased lodging due to wind).
Among the barley cultivars, UK spring barleys (‘Westminster’, ‘Decanter’ and ‘Oxbridge’)
displayed the least disease severity compared with heirloom and other commercial
cultivars (Table 2.11). Hulless cultivars ‘Sunshine’, ‘Andie’ and ‘Ethiopian’ were moderately
susceptible to stripe rust disease whereas the majority of cultivars including, ‘CDC Gainer’,
‘Purple’, ‘Hooded’, ‘Jet’, ‘Dolma’, ‘Excelsior’, ‘Himalayan’ and ‘Burbank’ showed intermediate
resistance. Commercial cultivars (e.g., ‘McGwire’, ‘Copeland’ and ‘Camus’) were moderate to
highly susceptible to stripe rust disease.
The barley cultivars showed variable response with respect to lodging intensity. In general,
6-row cultivars displayed greater lodging compared to 2-row cultivars (Table 2.11).
Heirloom cultivars ‘Excelsior’ and ‘Himalayan’, both 6-rowed and hulless cultivars, despite
of having dwarf plants, showed complete lodging (>80%) whereas ‘Purple’, ‘Dolma’, ‘CDC
Gainer’ and ‘Burbank’ displayed only partial lodging (40-60%). The 2-row UK spring
barleys (‘Westminster’, ‘Decanter’, ‘Oxbridge’) and black seeded heirloom ‘Jet’ showed no
lodging. Besides the activity of six-spotted lady bird beetles, no insect damage was
observed.
Root growth and nodulation: Heavy nodulation and deep penetrating root systems are
desirable traits for sustainable organic farming as they have the genetic potential to fix
atmospheric nitrogen and acquire water from deep in the soil profile. Through qualitative
assessment, legume cultivars differed in several parameters including degree of
nodulation, total root mass, and depth of rooting. Kidney bean (‘Candy’) and fava bean
32
(‘Andy’, ‘Bell’ and ‘Windsor’) cultivars displayed good nodulation during the later stages of
growth (flowering to pod setting), indicating good potential for N2 fixation. In these
cultivars, 10 or more pink-red nodules were observed in the crown-root zone and
elsewhere on the root system. Cultivars ‘Reward’ (pea), ‘Crimson’ and ‘Essex’ (lentil), on
the other hand, produced nodule-like structures approximately 20 DAS but disappeared as
the plants matured. The reason behind no or few numbers of nodules could be because no
pre-plant inoculation was used and these crops were planted in new sites.
2.2.3 Protein content
Grain protein concentration (GPC) has a major impact on the end-use quality of products
made from hard wheat and barley. Therefore, this trait is typically a high priority in wheat
and barley improvement programs aimed at improving bread-making or malting qualities.
High protein contents are required for wheat used for baking pan breads and blending,
typically >13% for Canadian Western Red Spring wheat and 11-13% for UK wheat, with
lower levels used for other types of bread, noodles or other food uses. In barley, low
protein levels (generally below about 11%) are required for malting, brewing and
distilling, with higher levels resulting in reduced quality (Shewry, 2006). Wibberley (1989),
on the other hand, reported the minimum required protein content for bread wheat as 11%
whereas for malting barley, it is desirable to be below 9.4%.
A clear difference was observed between commercial and heirloom wheat cultivars for
protein content (Table 2.12). Overall, heirloom cultivars showed higher protein contents
with the highest level in ‘Einkorn’ (16.2%) followed by ‘Emmer- 2’ (15.4%) and ‘Reward’
(15%). The higher protein level in the heirloom cultivars demonstrates their suitability for
33
baking and blending purpose compared to the commercial cultivars. However, the highest
yielding commercial cultivar, ‘Scarlet’, contained the lowest protein content (9.2%).
Except for the heirloom cultivars, no significant difference in protein content was observed
between the UK spring barleys (i.e., ‘Oxbridge’, ‘Westminster’, and ‘Decanter’) and other
commercial cultivars (Table 2.12). Commercial cultivars had lower protein levels (8-9.6%),
most appropriate for malting purposes. The heirloom black barley cultivar ‘Jet’ had the
highest protein content (13.7%) followed by ‘Dolma’ (13.6%) and ‘Purple’ (12.8%), a level
desirable for livestock feed.
Variation in protein levels was observed in wheat and barley cultivars when grown under
different environments and management practices. Halstead (2007) reported the protein
content in ‘Red Fife’ as 9%, 1.4% less than observed in this experiment. Similarly, Temple
(2009) observed higher protein levels in ‘Norwell’ (13.1%) and ‘Scarlet’ (11.5%) when
grown under different management practices in Delta, BC. Some researchers have observed
that the grain protein is higher in conventional systems than in organic systems (Poutala et
al., 1993; Starling and Richards, 1993). In contrast, Shier et al. (1984) and Ryan et al.
(2004) reported no differences in grain protein levels of spring wheat grown in organic and
conventional cropping systems, which they attributed to adequate soil nutrient levels in
both systems.
2.3 Conclusions
This trial assessed performance of heirloom and commercial cultivars of wheat, barley, and
several legume crops and cultivars. Above all, the tested wheat and barley cultivars
34
performed well under organic management systems at the UBC Farm. The following
conclusions have been made and will be used to structure future trials:

There was significant variation in yield among both heirloom wheat (2.5 to 5.2 t ha1)
and barley (2.9 to 6.9 t ha-1) cultivars. The heirloom wheats ‘Reward’, ‘Glenn’,
‘Cerebs’, ‘Sounders’ and ‘Red Bobs’ produced comparable grain yields (~5 t ha-1) to
the commercial cultivars with greater resistance to stripe rust disease. Hulled wheat
cultivars (e.g., Emmer and Einkorn Series) displayed high resistance to stripe rust
disease. Similarly, 2-row UK spring barleys (e.g., ‘Oxbridge’, ‘Westminster’ and
‘Decanter’) and heirloom cultivar (e.g., ‘Jet’) displayed higher yield and resistance to
disease compared to other commercial and the 6-row heirloom cultivars.
Furthermore, hulled barleys showed strong resistance to stripe rust disease.
Therefore, this trial has demonstrated the potential value of heirloom wheat and
barley cultivars in terms of yield and disease resistance.

Heirloom wheat cultivars showed higher protein levels most desirable for baking
and blending purposes as compared to the commercial cultivars, with ‘Einkorn’
displaying the highest level (16.2%). The highest yielding commercial wheat
‘Scarlet’ displayed the lowest protein content (9.2%). The heirloom black-seeded
barleys contained higher protein levels most suitable for animal feed. No significant
difference was observed between commercial and UK spring barleys. The UK spring
barleys contained lower protein levels most suitable for malting purposes.

Among the commercial cultivars, ‘Scarlet’ and ‘Norwell’ appeared to be best in terms
of grain yield and yield related parameters. Similarly, ‘Camus’, ‘McGwire’, and
35
‘Copeland’ barleys showed only marginal yield differences with moderate to high
susceptibility to stripe rust.

Most of the barley cultivars matured 2-4 weeks earlier than the wheat cultivars. The
coincidence in harvesting time (80-90 DAS) showed that barley can be successfully
integrated with pea and lentil for combined harvesting. Hulless barley appeared to
be best suited to early pea (‘Snowbird, ‘Corgi’, ‘De Grace’ and ‘Golden’) and lentil
(‘Crimson’, and ‘Essex’) while hulled barley could be integrated with mid to late
cultivars (e.g., ‘Reward’ pea). Early wheat cultivars (e.g., ‘Sounders’, ‘Reward’,
‘Snowstar’, and ‘Snowbird’) showed potential with late peas whereas late wheat
appeared to be best suited to fava beans, kidney beans, and soybeans. However,
some fava bean cultivar may require multiple harvests over time.

The significant variation among heirloom cultivars for plant based parameters,
disease resistance and protein content suggests the possibility of crop improvement
through an accelerated breeding program. Therefore, heirloom cultivars should be
considered for inclusion in cultivar-improvement programs.

As a seed crop, soybean, fava bean and kidney bean requires early planting (i.e., late
April to early May). Also, lentil appeared to be sensitive to the low temperatures
experienced during the end of the season as they produced excellent vegetative
growth but contained no or only underdeveloped brown seeds making them
inappropriate for late-spring planting.
36
Table 2.1 Meteorological data† during 2010 cropping season at UBC Farm, Vancouver, Canada.
Mean Air Temperature (°C)
Mean Soil Temperature (°C) at different depth
Month
Day
Night
24hours
June
15.1 (21)
12.8
July
18.6 (28.9)
August
September
Average
10-cm
20-cm
Relative Humidity (%)
Day
Night
24hours
Solar
Total
Irradiance1
Rainfall
(W m-2)
(mm)
Day
Night
24hours
Day
Night
24hours
13.9
18.2
18.6
18.4
17.6
18.1
17.9
76.3
83.2
79.7
569 (1419)
57.4
15.8
17.4
20.3
21
20.6
19.6
20.3
19.9
69.7
77.7
73.2
779 (1424)
6.6
18.9 (30)
16.1
17.6
19
19.5
19.3
18.7
19.3
19
70.1
78.2
73.9
603 (1345)
61.2
15.7 (22.6)
13.8
14.7
17.3
17.7
17.5
17.3
17.7
17.5
79.7
87.9
83.8
411 (1188)
120.6
17.1
14.6
15.9
18.7
19.2
18.9
18.3
18.9
18.6
73.9
81.8
77.7
590.3
61.5
†Source: UBC Climate Station adjacent to Totem Park, 1 km northwest of UBC farm; and 1Daytime averages
Figures in parenthesis under mean air temperature column indicate the highest temperature in respective months
Figures in parenthesis under solar energy column indicate the highest intensity of solar radiation on the earth surface in respective months
37
Table 2.2 Soil properties† at site (prior to sowing i.e., spring 2010) at UBC Farm, Vancouver, Canada.
Sample
pH
#
Buffered
Total C
EC
Total N
P
K
Ca
Mg
Cu
Zn
Fe
Mn
B
pH
(%)
(mmhos/cm)
(%)
(ppm)
(ppm)
(ppm)
(ppm)
(ppm)
(ppm)
(ppm)
(ppm)
(ppm)
1
5.6
6.6
6.8
0.88
0.29
178
240
3050
160
0.6
15
25
45
0.5
2
5.4
6.5
6.6
1.28
0.32
130
280
3100
175
0.6
12
30
38
0.7
3
5.6
6.7
6.4
0.98
0.30
162
225
2600
175
0.6
13
30
35
0.7
4
5.5
6.5
5.5
1.20
0.30
108
200
2100
155
0.6
9.3
25
24
0.5
Average
5.5
6.5
6.32
1.085
0.302
144.5
236.3
2713
166
0.6
12.3
27.5
35.5
0.6
†Analyses
conducted by Pacific Soil Analysis Inc., Richmond, Canada
38
Table 2.3 Small grain cultivars used for performance evaluation during 2010 spring season at UBC Farm, Vancouver, Canada.
100 Seed
Seeding Density
Seed Rate
Weight (g)
(m2)
(g m-2)
Hard red spring wheat, 6-row, awned
4.2
350 (12cm- row)
15
AAFC1, Canada
Lillian
Canada western red spring wheat, 6-row, awnless
3.7
350 (12cm- row)
13
AAFC1, Canada
Commercial
Snowstar
Hard white spring wheat, 6-row, awnless
2.9
350 (12cm- row)
10
AAFC1, Canada
Cultivars
Norwell
Hard red spring wheat, 6-row, awned
4.0
350 (12cm- row)
14
BC, Canada
Strongfield
Canadian Western Amber Durum, 6-row, awned
4.6
350 (12cm- row)
16
BC, Canada
Snowbird
Hard white spring wheat, 6-row, awnless
3.4
350 (12cm- row)
12
BC, Canada
Heirloom
Red Fife
Hard red spring wheat, 6-row, awnless
3.8
350 (12cm- row)
14
BC, Canada
Cultivars
Glenn
Hard red spring wheat, 6-row, awned
2.5
350 (12cm- row)
9
Maine, USA
Red Wheat
6-row, awned, from the hills of Sicily, Italy
3.4
350 (12cm- row)
12
BC, Canada
Red Bobs- 222
Hard red spring wheat, 6-row, awnless
3
350 (12cm- row)
11
BC, Canada
Calcutta
Hard red spring wheat, 6-row, awned
2.8
350 (12cm- row)
10
BC, Canada
Cerebs
Hard red spring wheat, 6-row, awned
3.4
350 (12cm- row)
12
BC, Canada
Sounders
Hard red spring wheat, 6-row, awnless
2.3
350 (12cm- row)
8.5
BC, Canada
Emmer- 1
Primitive, 2-row, flat and long spike, hulled, awned
9.1
350 (12cm- row)
32
BC, Canada
Emmer- 2
Primitive, 2-row, flat but short spike, hulled, awned
6.5
350 (12cm- row)
23
BC, Canada
Einkorn
Primitive, 2-row, hulled, flat black spike, awned
3
350 (12cm- row)
11
BC, Canada
Black Bearded
Tall, beautiful large head, 6-row, awned
4.6
350 (12cm- row)
16.5
Crop
Cultivar
Type/ Characteristics
Scarlet
Source
Wheat
Minnesota, USA
39
100 Seed
Seeding Density
Seed Rate
Weight (g)
(m2)
(g m-2)
Hard red, Canadian heirloom, 6-row, awnless
4.2
350 (12cm- row)
15
Washington, USA
Pacific Blue Stem
White spring, 6-row, awnless
5.3
350 (12cm- row)
19
Oregon, USA
Copeland
2-row, awned, hulled, malting type
4.5
350 (12cm- row)
16
BC, Canada
McGwire
2-row, awned, hulless, malting type
4.2
350 (12cm- row)
15
BC, Canada
Camus
2 row, awned and hulled
4.9
350 (12cm- row)
17
AAFC1, Canada
Oxbridge
2-row, awned, hulled, UK spring barley
4.7
350 (12cm- row)
17
BC, Canada
Westminster
2-row, awned, hulled, UK spring barley
5.4
350 (12cm- row)
19
BC, Canada
Decanter
2-row, awned, hulled, UK spring barley
4.5
350 (12cm- row)
16
BC, Canada
CDC Gainer
2-row, awned, Canadian hulless, malting type
4.4
350 (12cm- row)
16
BC, Canada
Sunshine
6-row, awned, early, hulless barley
3.4
350 (12cm- row)
12
Alaska, USA
Purple (Black)
6-row, awned, hulless, brown-seeded barley
4.2
350 (12cm- row)
15
BC, Canada
Hooded (Black)
6-row, awnless, hulless, brown-seeded barley
3.3
350 (12cm- row)
12
BC, Canada
Heirloom
Jet (Black)
2-row, awned, hulless, black-seeded barley
3.7
350 (12cm- row)
13
Idaho, USA
Cultivars
Dolma
6-row, awned, hulless, easy threshing
3.3
350 (12cm- row)
12
Idaho, USA
Andie
6-row, awnless, hulless
3.2
350 (12cm- row)
12
California, USA
Ethiopian Hulless
2-row, awned, hulless, heat resistant
4.2
350 (12cm- row)
15
California, USA
Excelsior (Black)
6-row, awned, hulless, brown-seeded barley
4.3
350 (12cm- row)
15
BC, Canada
Himalayan
6-row, awned, hulless
3.9
350 (12cm- row)
14
BC, Canada
Burbank (Brown)
6-row, awned, hulless, easy threshing
2.4
350 (12cm- row)
9
Maine, USA
Crop
Cultivar
Type/ Characteristics
Reward
Source
Barley
Commercial
Cultivars
1Agriculture
and Agri-Food Canada
40
Table 2.4 Legume crops and cultivars used for evaluation during 2010 cropping season at UBC Farm, Vancouver, Canada.
Crop
Sowing Density
Name of Cultivar
Cultivar Characteristics
Reward
Powdery mildew resistance field pea
66 (30x5 cm2)
AAFC1, Canada
Snowbird
Very early, dwarf plants, entire pods are edible
66 (30x5 cm2)
Wisconsin, USA
Corgi
Small round dark green pod, very sweet and prolific
66 (30x5 cm2)
California, USA
Golden
Edible yellow pods, purple flowers, good bearer
66 (30x5 cm2)
Maine, USA
De Grace
Early, no disease, compact, better than modern sugar
66 (30x5 cm2)
Connecticut, USA
Crimson Flowered
Short red edible flower, excellent in salads, smaller bushes, bright green seeds
33 (30x10 cm2)
Washington, USA
Bergeron
Early maturity, one-picking, dwarf plant and short pod
33 (30x10 cm2)
Vermont, USA
Windsor
Bush type, classic heir-loom variety of flat bean
33 (30x10 cm2)
Maine, USA
Bell
Short pod, small and roundish seed
33 (30x10 cm2)
BC, Canada
Andy
Longer growing season, tall plant and longest pod
33 (30x10 cm2)
BC, Canada
Artec Red Kidney
Dry kidney bean, bush-type, dark amber seed
33 (30x10 cm2)
BC, Canada
Red Kidney
Dry kidney bean, bush-type, red seed
33 (30x10 cm2)
BC, Canada
Black Turtle
Dry bush bean, small and black seed
33 (30x10 cm2)
BC, Canada
Candy
Dry kidney bean, vine-type, colored seed with red spots
33 (30x10 cm2)
BC, Canada
Golden Rocky
Dry bush bean, black seeded with white eye
33 (30x10 cm2)
BC, Canada
(seed m-2)
Sourcing Area
Pea
Fava bean
Broad bean/Kidney bean
41
Crop
Name of Cultivar
Cultivar Characteristics
Sowing Density
(seed m-2)
Sourcing Area
Soybean
Black Jet
Tall plant, black seed, grain type
33 (30x10 cm2)
BC, Canada
Edamame
Dwarf plant, yellow seed, vegetable type
33 (30x10 cm2)
BC, Canada
Crimson
Brown lentils with red cotyledons
200 (20x2.5 cm2)
AAFC1, Canada
Essex
Green lentil with yellow cotyledons
200 (20x2.5 cm2)
ARS2, Pullman, USA
Lentil
1Agriculture
and Agri-Food Canada; and 2Agricultural Research Service/USDA
42
Table 2.5 Disease assessment key adopted during 2010 spring trial at UBC Farm, Vancouver, Canada.
Score
Description
1
Highly resistant: no visible symptoms
2
Highly resistant: occasional symptoms of infection including necrotic flecks and small stripes without sporulation
3
Resistant: symptoms evident and may include stripes with necrosis and chlorosis, limited sporulation, and affected leaf area up to 15%
4
Moderately resistant: sporulating areas arranged in stripes, some chlorosis and necrosis, and affected leaf area up to 30%
5
Intermediate: Sporulating areas arranged in stripes with some chlorosis, and affected leaf area up to 50%
6
Moderately susceptible: sporulating stripes and affected leaf area up to 70%
7
Moderately susceptible to susceptible: sporulating stripes merging into broader leaf areas supporting symptoms, chlorosis and necrosis
evident, leaf area affected up to 90%
8
Susceptible: sporulation across the whole leaf surface with no stripes but with evidence of chlorotic areas
9
Highly susceptible: abundant sporulation across the whole leaf area with no evidence of stripes
10
Dead leaf
43
Table 2.6 Rating key for nodule assessment (after Corbin et al., 1977) in legume during 2010 cropping season at UBC Farm,
Vancouver, Canada.
Field Assessment Key
Score
0
Visual Observation
No nodulation
Mean Score and Indication
Mean Nodule Score
0
Indication
No nodulation and no N2 fixation
<5 in the crown-root zone (regarded as the region up to
1
5 cm below the first lateral roots) with no nodules on
0-1
Very poor nodulation and probably little or no N 2
fixation
elsewhere on the root system
2
5-10 in the crown-root zone with <5 nodules on
1-2
Poor nodulation and probably little N2 fixation
elsewhere on the root system
3
>10 in the crown-root zone with <5 nodules on
2-3
elsewhere on the root system
4
>10 in the crown-root zone with 5-10 nodules on
Fair nodulation; N2 fixation may not be sufficient to
supply the N demand of the crop
3-4
Good nodulation; good potential for N2 fixation
4-5
Excellent nodulation; excellent potential for N2 fixation
elsewhere on the root system
5
>10 in the crown-root zone with >10 nodules on
elsewhere on the root system
44
Table 2.7 Response of commercial wheat cultivars to organic production systems during 2010 cropping season at UBC Farm,
Vancouver, Canada.
Harvest
Type
Cultivar
Days to
Height
Harvest
No. of
Spike m-2
(cm)
Spike
Length
(cm)
Seed
1000 Seed
Grain
Grain
Weight
Yield
Yield1
Spike-1
(g)
(g m-2)
(t ha-1)
HI2
(%)
W:V3
Lillian
105 (100-105)
104
461
7.5
33.3
41.7
440
4.4
45.9
0.82
Scarlet
105 (105-110)
103
500
9.2
38.7
48.0
544
5.4
48.4
0.83
Commercial
Norwell
105 (105-110)
114
588
8.2
42.0
44.7
525
5.3
42.7
0.84
Cultivars
Snowstar
100 (95-100)
103
726
6.9
34.0
32.7
472
4.7
45.5
0.81
Strongfield
110 (105-110)
98
426
6.0
36.7
42.7
500
5.0
46.1
0.83
Snowbird
100 (95-100)
122
655
6.2
34.0
39.5
477
4.8
43.2
0.82
Red Fife
125 (120-125)
135
419
10.6
38.7
43.7
407
4.1
37.4
0.81
Glenn
110 (105-110)
109
602
7.3
38.3
40.0
505
5.1
42.4
0.85
Red Wheat
100 (100-105)
109
574
6.7
27.3
40.5
361
3.6
30.5
0.82
Red Bobs
105 (100-105)
133
704
9.1
50.0
37.7
462
4.6
32.5
0.80
Calcutta
105 (105-110)
114
722
9.3
31.7
34.4
420
4.2
31.9
0.80
Cerebs
105 (105-110)
122
588
8.5
29.3
34.7
488
4.9
41.9
0.78
95 (95-100)
100
712
7.3
31.3
38.5
458
4.6
36.5
0.83
Heirloom
Cultivars
Sounders
45
Harvest
Type
Cultivar
Days to
Height
Harvest
No. of
Spike m-2
(cm)
Length
(cm)
Seed
1000 Seed
Grain
Grain
Weight
Yield
Yield1
Spike-1
(g)
(g m-2)
(t ha-1)
HI2
(%)
W:V3
Emmer- 1
110 (110-115)
105
722
5.5
29.0
40.6
377
3.8
37.7
0.65
Emmer- 2
105 (105-110)
108
628
5.6
21.3
42.4
389
3.9
43.7
0.67
Einkorn
125 (120-125)
126
544
7.2
36.3
26.6
281
2.8
36.1
0.49
Black Bearded
105 (105-110)
116
702
6.8
41.0
39.3
448
4.5
31.0
0.75
95 (95-100)
127
826
7.2
27.7
41.0
520
5.2
32.5
0.85
135 (135-140)
118
668
9.3
24.0
32.0
252
2.5
21.2
0.74
SEM (±)
3.67
5.23
14.5
1.02
3.99
2.82
32
0.31
2.66
0.04
LSD0.05
7.35
10.5
29
2.05
8
5.65
65
0.65
5.32
0.08
Reward
Pacific Blue Stem
1Calculated
Spike
at 12.5% moisture; 2Harvest Index; 3 Seed weight to volume ratio; SEM = Standard Error of the Mean; and LSD = Least Significant Difference
46
Table 2.8 Performance of commercial and heirloom barley cultivars to organic production during 2010 cropping season at
UBC Farm, Vancouver, Canada.
Type
Commercial
Cultivars
Cultivar
Days to
Harvest
Harvest
Height
(cm)
No. of
Spike m-2
Spike
Length
(cm)
Seed
Spike-1
1000 Seed
Grain
Grain
Weight
Yield
Yield1
(g)
(g m-2)
(t ha-1)
HI2
(%)
W:V3
Copeland
95 (90-95)
100
565
7.6
27.7
53.0
510
5.1
45.5
0.66
McGwire
90 (90-95)
73
594
9.0
27.0
40.1
520
5.2
46.9
0.83
Camus
95 (90-95)
81
510
7.8
26.7
54.0
498
5.0
53.8
0.68
Oxbridge
95 (90-95)
65
766
7.9
21.3
55.3
690
6.9
53.8
0.66
Westminster
100 (100-105)
80
804
7.8
23.3
57.7
580
5.8
52.9
0.71
Decanter
100 (100-105)
71
804
8.2
26.0
57.9
560
5.6
57.8
0.68
CDC Gainer
90 (90-95)
100
880
8.5
22.0
38.5
507
5.1
39.0
0.79
Sunshine
85 (80-85)
92
668
6.4
50.0
31.1
496
4.9
42.0
0.79
Purple (Black)
85 (80-85)
87
496
6.0
38.0
46.9
388
3.9
45.2
0.86
Hooded (Black)
100 (100-105)
92
358
7.6
46.0
38.3
423
4.2
48.3
0.79
Jet (Black)
80 (80-85)
75
736
6.9
15.7
48.5
552
5.5
29.2
0.73
Dolma
80 (75-80)
78
656
5.9
34.3
36.3
488
4.9
41.7
0.78
Andie
80 (75-80)
92
658
5.5
36.0
34.3
420
4.2
37.7
0.81
Ethiopian Hulless
85 (80-85)
85
576
7.1
15.7
49.8
444
4.4
34.4
0.77
Excelsior (Black)
90 (90-95)
82
532
5.4
33.0
42.9
297
2.9
43.1
0.83
Himalayan
80 (80-85)
89
648
6.5
36.7
39.3
420
4.2
41.8
0.77
Burbank
95 (90-95)
102
500
5.8
52.0
38.7
450
4.5
32.1
0.81
Heirloom
Cultivars
47
Type
1Calculated
Cultivar
Days to
Harvest
Harvest
Height
(cm)
No. of
Spike m-2
Spike
Length
(cm)
Seed
Spike-1
1000 Seed
Grain
Grain
Weight
Yield
Yield1
(g)
(g m-2)
(t ha-1)
HI2
(%)
W:V3
SEM (±)
3.49
4.18
12.5
0.85
3.45
3.22
32
0.29
3.12
0.05
LSD0.05
7.0
8.36
25
1.7
6.9
6.45
65
0.6
6.25
0.1
at 12.5% moisture; 2Harvest Index; 3Seed weight to volume ratio; SEM = Standard Error of the Mean; and LSD = Least Significant Difference
48
Table 2.9 Performance of legume cultivars to the organic production during 2010 cropping season at UBC Farm, Vancouver,
Canada.
Crop Cultivar
Days to Seed
Harvest
Harvest
Height
(cm)
No. of
Plant m-2
No. of
Pod
No. of
Pod
Length
Seed
Plant-1
(cm)
Pod-1
Seed Yield
(g plot-1)
Grain
1000 Seed
Seed to
Yield1
Weight
Shell
(t ha-1)
(g)
Ratio
W:V2
Pea
Reward*
90 (85-90)
95
46
3.8
5.6
5.3
298
3.0
207
3.7
0.88
Snowbird
80 (75-80)
-
-
-
-
-
104
1.0
143
5.2
0.81
Corgi
80 (75-80)
-
-
-
-
-
92
0.9
168
4.6
0.73
Golden
80 (80-85)
-
-
-
-
-
166
1.7
177
6.4
0.79
De Grace
80 (75-80)
-
-
-
-
-
89
0.9
128
3.7
0.80
SEM (±)
3.59
-
-
-
-
-
14.3
0.14
8.54
0.21
0.06
LSD0.05
7.2
-
-
-
-
-
28.6
0.29
17.1
0.42
0.13
125 (120-125)
106
32
5.6
10.3
3.2
265
2.6
1090
2.6
0.65
Bergeron
95 (95-100)
64
28
4.0
7.0
3.2
251
2.5
718
2.3
0.74
Windsor
115 (110-120)
100
24
7.6
14.6
4.2
171
1.7
1513
2.4
0.61
Bell
110 (110-120)
100
32
7.6
7.7
3.8
292
2.9
533
2.6
0.81
Andy
115 (110-120)
123
28
6.8
23.0
5.6
279
2.8
1384
1.8
0.69
SEM (±)
4.25
7.36
1.5
1.25
1.31
0.72
18.65
0.19
15.75
0.25
0.06
LSD0.05
8.5
14.7
3.0
2.5
2.62
1.45
37.3
0.38
31.5
0.5
0.12
Fava bean
Crimson
Flowered
49
Crop Cultivar
Days to Seed
Harvest
Harvest
Height
(cm)
No. of
Plant m-2
No. of
Pod
No. of
Pod
Length
Seed
Plant-1
(cm)
Pod-1
Seed Yield
(g plot-1)
Grain
1000 Seed
Seed to
Yield1
Weight
Shell
(t ha-1)
(g)
Ratio
W:V2
Broad bean/Kidney bean
Artec Red Kidney
120 (120-125)
58
32
8.0
16.2
4.8
425
4.3
737
2.3
0.79
Red Kidney
110 (110-115)
51
32
8.4
12.5
3.6
483
4.8
631
2.7
0.84
Candy
120 (120-125)
97
30
11.2
14.8
3.0
388
3.9
821
2.1
0.77
Black Turtle
110 (110-115)
89
32
17.2
8.6
6.2
418
4.2
171
3.2
0.83
Golden Rocky
100 (100-105)
25
24
16.0
12.0
3.8
423
4.2
273
3.0
0.88
SEM (±)
3.79
5.43
1.23
1.51
1.55
0.84
21.42
0.22
17.53
0.18
0.05
LSD0.05
7.6
10.8
2.45
3.02
3.10
1.68
42.8
0.43
35.1
0.36
0.1
Black Jet
130 (130-135)
80
32
24.4
5.1
2.0
345
3.4
274
-
0.72
Edamame
130 (130-135)
41
20
27.4
6.1
2.4
204
2.0
381
-
0.71
Crimson
80 (80-85)
40
160
23.4
1
1.6
77
0.8
34
2.9
0.81
Essex
85 (80-85)
44
188
16.4
1.2
1.8
98
1.0
41
2.3
0.85
Soybean
Lentil
1Calculated
at 12.5% moisture; 2Seed weight to volume ratio; * Commercial pea cultivar; SEM = Standard Error of the Mean; and LSD = Least Significant Difference
50
Table 2.10 Performance of commercial and heirloom wheat cultivars during 2010 cropping season at UBC Farm, Vancouver,
Canada.
Chlorophyll Concentration
Type
Cultivar
Index (71
Flag Leaf
mm2),
Performance Assessment/rating*,
30 DAS
3rd
Leaf
30 Days after Seeding
Greenness
Disease1
Pests
Overall
Rating, 70 DAS
Disease2
Remarks
Lodging (%)
Poor
Commercial
germination
but
good
Lillian
14.83
12.75
8
2
1
8
2
0
tillering (up to 6/plant), no disease
Scarlet
16.98
11.55
8
2
1
9
8
0
Good stand, vigorous but diseased
Norwell
15.25
16.55
8
2
1
9
7
0
Good stand, vigorous but diseased
Snowstar
14.03
14.23
8
2
1
8
8
0
Good stand, vigorous but diseased
Strongfield
17.50
11.15
7
6
1
6
7
0
Septoria Leaf Blotch
Snowbird
13.22
17.17
8
2
1
9
4
10
Good stand, low disease
Poor
Red Fife
18.45
16.10
9
2
1
9
4
20
germination
but
good
tillering (up to 6/plant), low
disease
Glenn
-
-
9
4
1
8
4
0
Red Wheat
-
-
9
1
1
9
4
90
Lodging: Partial 40, complete 60%
Red Bobs
-
-
9
1
1
10
5
50
Partial lodging
Calcutta
-
-
9
1
1
9
5
40
Partial lodging
Cerebs
-
-
8
1
1
8
5
60
Lodging: Partial 40, complete 60%
Sounders
-
-
8
1
1
8
5
0
Emmer- 1
-
-
8
1
1
8
2
60
Heirloom
Partial lodging
51
Chlorophyll Concentration
Type
Cultivar
Index (71
Flag Leaf
mm2),
Performance Assessment/rating*,
30 DAS
3rd
Leaf
30 Days after Seeding
Greenness
Disease1
Pests
Rating, 70 DAS
Overall
Disease2
Lodging (%)
Emmer- 2
-
-
8
1
1
8
4
0
Einkorn
-
-
8
1
1
8
1
0
Bearded
-
-
8
1
1
8
5
20
Reward
-
-
8
1
1
8
4
0
-
-
8
1
1
8
8
0
Remarks
Black
Complete lodging
Pacific
Blue Stem
*Rated as 1-10, 1 being the lowest and 10 highest; 1Assessment for Septoria leaf blotch and scald; 2Assessment for stripe rust; and DAS = Days after Seeding
52
Table 2.11 Performance of commercial and heirloom barley cultivars during 2010 cropping season at UBC Farm, Vancouver.
Type
Cultivar
Chlorophyll Concentration Index
Performance Assessment/rating*,
Rating,
(71 mm2), 30 Days after Seeding
30 Days after Seeding
70 Days after Seeding
Flag Leaf
Commercial
Cultivars
3rd
Leaf
Greenness
Disease1
Pests
Overall
Disease2
Lodging (%)
Remarks
Copeland
15.60
13.87
6
4
1
8
7
20
Disease susceptible
McGwire
15.55
14.03
6
4
1
7
8
0
Disease susceptible
Camus
15.97
18.00
8
2
1
8
7
20
Disease susceptible
Oxbridge
-
-
8
1
1
9
4
0
Westminster
-
-
8
1
1
9
2
0
Decanter
-
-
8
1
1
9
2
0
CDC Gainer
-
-
8
1
1
8
5
40
Sunshine
-
-
8
1
1
8
7
0
Purple
-
-
8
1
1
8
5
60
Hooded
-
-
8
1
1
8
5
0
Jet
-
-
7
1
1
8
5
0
Dolma
-
-
8
1
1
9
5
40
Andie
-
-
8
1
1
9
6
0
Ethiopian Hulless
-
-
6
1
1
7
7
0
Excelsior
-
-
8
1
1
7
5
90
Complete lodging 90%
Himalayan
-
-
8
1
1
9
5
80
Complete lodging 80%
Burbank
-
-
8
1
1
8
5
60
Partial lodging
Partial lodging
Partial lodging
Partial lodging
Heirloom
Cultivars
*Rated as 1-10, 1 being the lowest and 10 highest; 1Assessment for Septoria leaf blotch and scald; and 2Assessment for stripe rust
53
Table 2.12 Protein content of wheat and barley cultivars grown under organic production systems during 2010 cropping
season at UBC Farm, Vancouver, Canada.
Type
Cultivar
Nitrogen
Protein
(%)
(%)
End Uses
Type
Cultivar
WHEAT
Nitrogen
Protein
(%)
(%)
End Uses
BARLEY
Lillian
2.01
11.5
Baking/bread type
Copeland
1.38
8.0
Malting type
Scarlet
1.62
9.2
Cake/pastry/malting
McGwire
1.49
8.6
Malting type
Commercial
Norwell
1.81
10.3
Cake/pastry/noodles
Camus
1.66
9.6
Malt/feed
Cultivars
Snowstar
1.74
9.9
Cake/pastry
Oxbridge
1.39
8.1
Malting type
Strongfield
2.01
11.4
Baking/bread type
Westminster
1.57
9.1
Malting type
Snowbird
2.08
11.9
Baking/bread type
Decanter
1.54
8.9
Malting type
Red Fife
1.82
10.4
Noodles/pastry/cake
CDC Gainer
1.37
7.9
Malting type
Glenn
2.17
12.4
Baking/bread type
Sunshine
1.62
9.4
Malt/feed
Red Wheat
2.49
14.2
Baking/bread type
Purple
2.20
12.8
Feed type
Red Bobs
2.32
13.2
Baking/bread type
Hooded
2.31
13.4
Feed type
Calcutta
2.61
14.9
Baking/bread type
Jet
2.36
13.7
Feed type
Cerebs
2.10
12.0
Baking/bread type
Dolma
2.35
13.6
Feed type
Andie
2.11
12.3
Feed type
Commercial
Cultivars
Heirloom
Cultivars
Heirloom
Sounders
2.04
11.6
Baking/bread type
Cultivars
Emmer- 1
2.35
13.4
Baking/bread type
Ethiopian Hulless
2.24
13.0
Feed type
Emmer- 2
2.69
15.4
Baking/bread type
Excelsior
2.01
11.7
Feed type
Einkorn
2.85
16.2
Baking/bread type
Himalayan
2.05
11.9
Feed type
Black Bearded
2.60
14.8
Baking/bread type
Burbank
2.25
13.1
Feed type
54
Type
Nitrogen
Protein
(%)
(%)
Reward
2.64
15.0
Pacific Blue
1.93
11.0
Cultivar
Stem
End Uses
Type
Cultivar
Nitrogen
Protein
(%)
(%)
End Uses
Baking/bread type
Baking/bread type
SEM (±)
0.45
SEM (±)
0.34
LSD0.05
0.91
LSD0.05
0.69
SEM = Standard Error of the Mean; and LSD = Least Significant Difference
55
Figure 2.1 Disease assessment score and severity of leaf damage in wheat and barley.
Please refer to Table 2.5 for details.
56
CHAPTER 3: WHEAT AND BARLEY ROOT ARCHITECTURE
 A version of this chapter has been published as Chapagain, T., L. Super and A. Riseman
(2014), Root Architecture Variation in Wheat and Barley Cultivars. American Journal of
Experimental Agriculture 4 (7): 849-856.
This chapter presents major activities and outcomes of root architecture experiment that
assessed heirloom and commercial cultivars of wheat and barley to improve our
understanding of the variation in small grain root architecture, and to see their potential
for improved nutrient uptake and drought tolerance. This study also compared laboratory
based root architecture measures with 2010-cultivar field performance data.
3.1 Materials and Methods
3.1.1 Cultivar selection
Heirloom and commercial cultivars of hard red spring wheat (Triticum aestivum L.) and
barley (Hordeum vulgare L.) that performed well (i.e., high yield, protein content, and
disease resistance) in cultivar trials (Chapagain and Riseman, 2012) were selected for root
architecture experiments. These included five wheat cultivars (commercial cvs. ‘Scarlet’
and ‘Norwell’ and heirloom cvs. ‘Red Fife’, ‘Glenn’, and ‘Reward’) and four barley cultivars
(commercial cvs. ‘Oxbridge’ and ‘Camus’ and heirloom cvs. ‘Dolma’ and ‘Jet’).
3.1.2 Seed treatment
Seeds were surface sanitized in 70% ethanol for 5 minutes followed by rinsing thrice with
distilled water under aseptic conditions. After rinsing, seeds were left to imbibe in distilled
water for 12 hours.
57
3.1.3 Study design and set-up
We used a completely randomized design (CRD) with five replications for each cultivar.
Seedlings were grown on germination paper (10”x10”, Anchor Paper Co. Seed Solution,
Saint Paul, MN) following a modified version of B. Snyder and J. Lynch (Department of
Horticulture, Penn State University, PA, USA, personal communication). In brief, we used
two sheets of blotting paper (Anchor Paper Co., St. Paul, MN, USA) and cut a notch (1 cm
wide and 4 cm long) at the center of the top edge of each sheet. Then, we placed two pieces
of paper without notches on top. These layers were then placed in a large, clear bag
(10”x11”, SC Johnson and Son Limited, Brantford, ON, Canada) and moistened completely
with 0.5 mM CaSO4 (MW 136) solution. Next, a germination cradle was prepared; this was
achieved by pressing the paper without notches into the underlying notch. One seed was
then placed embryo side down into the germination cradle. This germination unit (i.e., bag,
moistened paper and seed) was then secured with two binder clips to a similar sized sheet
of plexiglass, and held at a 45 degree angle. The germination units were kept in a growth
chamber (Controlled Environments Ltd., Winnipeg, MB, Canada) set at 25oC and 60%
relative humidity and grown for 10 days. Light was provided using fluorescent lights at an
intensity of 90 µmols m-2 s-1 for 16 hours each day. All germination units were periodically
moistened with 0.5 mM CaSO4 to prevent drying.
3.1.4 Root architecture data analysis
After 10 days, the paper and seedlings were removed from the bags and scanned on a
calibrated, lighted flatbed scanner at 300 dpi. Scans were then analyzed by WinRHIZO
software (WinRHIZO Pro 2009c, Regent Instruments Inc.). WinRHIZO data were
58
transferred to MSTAT-C for statistical analyses (MSU, 1993). Metrics calculated with
WinRHIZO include: total root length, surface area, average diameter, root volume, number
of tips, and branching angle. We also dried samples, in a drying oven at 70 oC for 48 hours,
and then weighed them to calculate dry root weight, dry shoot weight, and subsequently
shoot to root ratios. These results were compared to parameters previously measured in
the field for these cultivars in performance trials (Chapagain and Riseman, 2012).
3.2 Results and Discussion
3.2.1 Wheat root architecture
Root architecture metrics for commercial and heirloom wheat are shown (Table 3.1). In
general, heirloom cvs. ‘Glenn’ and ‘Reward’ displayed notable differences (i.e., longer root,
greater surface area and higher number of tips) compared with the commercial cvs.
‘Scarlet’ and ‘Norwell’. Overall, the commercial cultivars showed coarser roots (i.e., higher
root diameter), greater volume, higher dry root weight, and shoot to root ratios compared
to the heirloom cultivars, with cv. ‘Scarlet’ displaying the highest values. There is significant
variation among the heirloom cultivars with cv. ‘Reward’ displaying the highest surface
area, diameter, root volume, and number of tips compared to cv. ‘Red Fife’ and cv. ‘Glenn’.
The lowest shoot:root ratio (0.88) was observed in heirloom wheat cv. ‘Reward’ indicating
the greatest biomass partitioning to the roots among all cultivars and a trait associated
with drought tolerance potential (Bernier et al., 1995). The commercial cultivars were
more uniform for a number of parameters including surface area, diameter, volume, and
angle of branching (Table 3.1). Heirloom cultivars with typically longer and thinner roots,
59
greater surface area, more tips, and higher branching angles, are predicted to have larger
and deeper root systems than the commercial cultivars.
Root length distribution across diameter classes in heirloom and commercial wheat
cultivars is shown (Figure 3.1). Heirloom cultivars produced thinner roots than commercial
cultivars with 75-95% of all roots within the <0.5 mm diameter class compared with 5075% in commercial cultivars. Cultivar ‘Glenn’ possessed the highest percentage (95%) of
thin roots while the commercial cvs. ‘Scarlet’ and ‘Norwell’ displayed the lowest
percentage, i.e., coarsest.
3.2.2 Barley root architecture
Barley cultivars also showed significant variation in most root parameters including length,
area, volume, and angle of branching (Table 3.2). No trends differentiating commercial and
heirloom cultivars are identified. The heirloom cv. ‘Jet’, however, produced the longest
roots with the greatest surface area along with the highest branching angle and the lowest
shoot:root ratio compared to all other cultivars (Appendix K).
Figure 3.2 shows root length distribution by diameter class (mm) in barley cultivars. The
heirloom barley cv. ‘Jet’ produced the finest roots with almost 100% roots falling in <0.5
mm diameter class followed by the commercial cv. ‘Oxbridge’ (>90%). Commercial barley
cv. ‘Camus’ displayed the coarsest roots (0.5-1.0 mm) compared to either heirloom cultivar.
3.2.3 Root architecture association with field performance
Field performance of both heirloom and commercial cultivars, grown under low input
organic conditions, are presented (Table 3.3). There exists variation for the association
between wheat root architecture (Table 3.1, Figure 3.1) and plant performance metrics
60
(Table 3.3). In general, the heirloom wheat cultivars produced tall plants with long
internodes (Table 3.3) and longer finer more branched root systems (Table 3.1) compared
to the commercial cultivars. However, they also tended to lodge more than the commercial
cultivars due to their taller culms. The commercial cultivar cv. ‘Scarlet’, with its greatest
root diameter, root volume, dry root weight, and shoot:root ratios (Table 3.1) produced
higher grain yield, harvest index [HI, defined as a ratio of economic yield (grain yield) to
the total above ground biomass (grain yield + shoot biomass)], and 1000 seed weight
(Table 3.3) compared to the heirloom cultivars suggesting that cultivars with the shorter
(i.e., more feeder or surface) roots are also suitable under organic systems. Unlike wheat,
barley did not show any meaningful associations between root metrics and field
performance (Table 3.2, 3.3).
Among the few heirloom and commercial wheat and barley cultivars assessed in this study,
significant variation was observed for many root architectural parameters. A number of
reports link root architecture with traits associated with low-input production including
nutrient uptake efficiency, culm strength, and drought tolerance. Jones et al. (1989) showed
that root diameter is one of the most important determinants of nutrient uptake efficiency
with thinner roots having greater efficiency. Furthermore, several reports support the
association between thinner roots and improved P and water uptake (Jones et al., 1989;
Manske et al., 1996). In wheat, it has been reported that many wild forms and landraces
possess large root systems with thin roots, but tend to lodge because of their tall culms
(Manske, 1989; Vlek et al., 1996). Last, Bernier et al. (1995) suggested that plants with low
shoot:root ratio possess a water stress avoidance potential while plants with a higher
ratios are more likely to suffer from water stress. The variation observed among these few
61
heirloom and commercial cultivars indicates significant variation persists in these
germplasm pools, and is available to breeders interested in developing cultivars for lowinput agriculture.
3.3 Conclusions
This study assessed the variation among heirloom and commercial cultivars of wheat and
barley for several root architectural traits. Our assessment showed significant variation
among heirloom and commercial wheat cultivars and between root and agronomic
performance traits. Overall, heirloom wheat cultivars displayed longer and thinner roots,
more surface area, higher number of tips, and greater branching angle compared to
commercial cultivars. These traits are often associated with resistance to drought stress
and improved P uptake. The commercial cultivars, on the other hand, generally displayed
coarser roots and greater shoot:root ratios. There exists variation between heirloom and
commercial wheat cultivars for the association between root architecture and plant
performance. Barley, however, did not show any meaningful associations between root
metrics and field performance. Overall, the longer and finer roots, and the lowest
shoot:root ratio of some heirloom cultivars (e.g., ‘Reward’ wheat and ‘Jet’ barley) suggest
they may be useful candidates for inclusion in breeding programs designed to improve
nutrient uptake efficiency and drought tolerance.
62
Table 3.1 Root architecture metrics for heirloom and commercial wheat cultivars.
Cultivar
Root
Surface
Average
Root
Length
Area
Diameter
Volume
(cm)
(cm2)
(mm)
(cm3)
No. of Branching
Dry
Shoot:Root
Tips
Angle
Root
Ratio
(degrees)
Weight
(mg)
Scarlet-C
64.8
9.43
0.47
0.11
85
35.7
11.4
1.41
Norwell-C
57.0
7.92
0.46
0.09
52
34.7
8.6
1.05
Red Fife-H
65.6
5.81
0.33
0.05
87
37.2
7.0
1.07
Glenn-H
75.5
8.18
0.34
0.07
66
35.0
9.7
1.22
Reward-H
71.4
9.62
0.43
0.10
103
35.6
9.7
0.88
SEM (±)
1.69
0.87
0.04
0.01
4.0
0.62
0.76
0.11
LSD0.05
4.80
2.47
0.11
0.03
11.37
1.76
2.16
0.31
C = Commercial cultivar, H = Heirloom cultivars, SEM = Standard Error of the Mean, and LSD = Least
Significant Difference
63
Table 3.2 Root architecture metrics for heirloom and commercial barley cultivars.
Cultivar
Root
Surface
Length
Area
(cm)
(cm2)
Average
Root
Diameter Volume
(mm)
(cm3)
No.
Branching
Dry
Shoot:Root
of
Angle
Root
Ratio
Tips (degrees) Weight
(mg)
Oxbridge-C
80.3
8.2
0.33
0.07
139
34.8
7.4
1.09
Camus-C
73.4
9.7
0.42
0.10
250
34.3
8.1
1.15
Jet-H
100.1
11.1
0.35
0.10
197
36.2
7.2
0.83
Dolma-H
84.6
8.5
0.43
0.09
137
35.4
10.0
1.06
SEM (±)
3.40
0.62
0.03
0.01
12.1
0.64
0.59
0.09
LSD0.05
9.67
1.76
0.08
0.28
34.4
1.82
1.67
0.25
C = Commercial cultivar, H = Heirloom cultivars, SEM = Standard Error of the Mean, and LSD = Least
Significant Difference
64
Table 3.3 Field performance of small grain cultivars grown under low input organic
conditions during 2010 spring season at UBC Farm, Vancouver, Canada.
Cultivar
Plant Height
Grain Yield
Harvest Index
1000 Seed
at Harvest (cm)
(t ha-1)
(%)
Weight (g)
Wheat
Scarlet (C)
103
5.4
48.4
48.0
Norwell (C)
114
5.3
42.7
44.7
Red Fife (H)
135
4.1
37.4
43.7
Glenn (H)
109
5.1
42.4
40.0
Reward (H)
127
5.2
32.5
41.0
SEM (±)
3.67
0.31
2.66
2.82
LSD0.05
7.35
0.65
5.32
5.65
Barley
Oxbridge (C)
65
5.8
53.8
55.3
Camus (C)
81
5.0
53.8
54.0
Jet (H)
75
5.5
29.2
48.5
Dolma (H)
78
4.9
41.7
36.3
SEM (±)
3.49
0.29
3.12
3.22
LSD0.05
7.0
0.6
6.25
6.45
C = Commercial cultivar, H = Heirloom cultivars, SEM = Standard Error of the Mean, and LSD = Least
Significant Difference
65
Root Length (cm)
80
60
40
20
0
<0.5
Scarlet
0.5 - 1.0
1.0 -1.5
Root Diameter Class (mm)
Norwell
Red Fife
Glenn
Reward
Figure 3.1 Root length (cm) distribution in diameter classes (mm) in wheat cultivars.
Root Length (cm)
100
80
60
40
20
0
<0.5
0.5 - 1.0
1.0 -1.5
Root Diameter Class (mm)
Oxbridge
Camus
Jet
Dolma
Figure 3.2 Root length (cm) distribution in diameter classes (mm) in barley cultivars.
66
CHAPTER 4: WHEAT-BEANS INTERCROPPING
 One component of this chapter has been published in Crop Science as Chapagain, T. and
A. Riseman (2014), Intercropping Wheat and Beans: Effects on Agronomic Performance
and Land Productivity (DOI: 10.2135/cropsci2013.12.0834).
 A second component of this chapter has been accepted for publication in Nutrient
Cycling in Agroecosystems as Chapagain, T. and A. Riseman, Nitrogen Transformation,
Water Use Efficiency and Ecosystem Productivity in Monoculture and Wheat-Bean
Intercropping Systems.
This study was conducted at the Centre for Sustainable Food Systems at UBC Farm in
Vancouver, BC, during 2011 and 2012 cropping seasons (May to September) to investigate
the effects of species ratios and spatial configuration on plant performance and system
productivity within an organic production system. In addition, the effects of the proportion
of genotype and their spatial configurations on N-use efficiency (i.e., biological nitrogen
fixation and transfer to the companion plants), CO2 fixation (i.e. gross ecosystem
photosynthesis - GEP), net ecosystem productivity (NEP) or carbon sequestration, water
use efficiency (WUE), and their association with biomass yield and quality were also
assessed. The experimental site is located at 49° 15' 3" N and 123° 14' 20" W, at an altitude
of 100 m above mean sea level. Research was conducted under rainfed conditions using
organic production practices.
67
4.1 Materials and Methods
4.1.1 Climate description of the study area
Climate data are summarized for the experimental site during the spring-summer seasons
(May to September) of 2011 and 12 (Table 4.1). Mean air temperatures at 1.5 m above the
ground over the two cropping seasons ranged from 15.0 to 15.1°C, with the warmest days
in August (17.5 to 18.2°C). The mean soil temperature at the 20 cm depth ranged from
17.9°C in year 1 to 18.3°C in year 2. Monthly average solar irradiance ranged from 389 to
404 W m-2, with the higher values in June-August. The average monthly precipitation was
42.4 and 32.3 mm in year 1 and 2, respectively. The least monthly precipitation (2.4 mm)
occurred in August of year 2 while the highest monthly precipitation (78 mm) occurred in
May of year 1. Year 2 was dry compared to year 1 with greater levels of solar irradiance
associated with lower precipitation and relative humidity.
4.1.2 Soil and field description
The soil was moderately well drained coarse textured sandy loam with low to moderate
fertility. According to the Canadian system of soil classification, it was a Duric Humo-Ferric
Podzol which is typified by a contact between reddish brown sub-soils and the greyish
transition to the basal glacial till (AAFC, 1998). The specific soil type was a Haplorthod,
according to the American system of soil classification (USDA-SCS, 1992), which is usually
found with forest vegetation, the land cover prior to clearing for agriculture. Three random
soil samples from across the whole test site were collected (0-15 cm depth) at the time of
plot establishment and showed acceptably homogeneous conditions. The average pH,
organic matter content, total N, δ15N, P and K were 5.8, 119 g kg-1, 3.6 g kg-1, 3.74 ‰, 156
68
mg kg-1 and 193 mg kg-1 based on dry soil, respectively. Additional samples were taken
from two different areas within each plot before planting (Spring-2011) and after final
harvest (Fall-2012), and sent to an analytical laboratory (Pacific Soil Analysis Inc.,
Richmond, Canada) to determine soil mineral N (NH4+ and NO3-) content. The site had not
been used for grain production in previous years but had been used for annual vegetable
cultivation. The site had been managed under organic vegetable production guidelines for
more than the 10 years using green manures and compost.
4.1.3 Experimental details
Cultivars of hard red spring wheat (Triticum aestivum cv. ‘Scarlet’), common bean
(Phaseolus vulgaris cv. ‘Red Kidney’ and ‘Black Turtle’) and fava bean (Vicia faba cv. ‘Bell’)
that performed well (i.e., in terms of synchronized maturity for combined harvesting, yield
potential, protein content, and nodulation potential in beans) in previous cultivar trials
(Chapagain and Riseman, 2012) were selected for intercropping trials. Common bean (bush
type with steep basal roots) and the fava bean (upright growth with a well-developed tap
root which produces extensive fibrous root architecture) were chosen to assess the impact
of different genera (Vicia and Phaseolus) and different cultivars (common bean cv. ‘Red
Kidney’ or ‘Black Turtle’) on companion wheat plants. Over two years of study, plants were
grown on the same plots under organic and rain-fed conditions, and managed equally
across combinations.
Research plots (4m x 3m) were laid out in a randomized complete block design (RCBD)
with five treatments and four replications for each crop combination (Figure 4.1).
Treatments consisted of wheat and beans grown as monocultures, and wheat cv. ‘Scarlet’
69
intercropped with either a common bean cultivar (cv. ‘Red Kidney’, or cv. ‘Black Turtle’), or
a fava bean cultivar (cv. ‘Bell’) in rows of 1:1, 2 wheat:1 bean and broadcast arrangements
(Appendix I). In monoculture, wheat and beans were planted in rows at the recommended
plant densities targeting 300 and 24 viable plants m-2, respectively. Row and mixed
arrangements used a proportional replacement design in which the proportion of species
was varied as the monoculture densities differed between the two species (Jolliffe, 2000).
Row intercropping consisted of planting wheat and bean at 30 cm spacing in alternate rows
of 1:1 targeting 150 wheat and 12 bean plants m-2, and in 2:1 row arrangements targeting
200 wheat and 8 bean plants m-2. In the mixed arrangement, seeding densities of wheat and
bean were reduced by one half of monoculture densities targeting 150 and 12 plants m-2,
respectively, and broadcasted evenly in cultivated plots. This resulted in different
combined densities as species proportions changed. There was a gap at least 50 cm wide
between plots to minimize treatment interactions, and 1 meter wide gap between blocks to
facilitate management.
Bean seeds were inoculated with commercial rhizobia (Garden Inoculant for Beans, EMD
Crop Bioscience, WI, USA) and planted immediately. Wheat and common bean cv. ‘Black
Turtle’ were sown in mid-May (15-16 May) in rows using a hand seeder (Jang Clean Hand
Seeder, Jang Automation Co. Ltd., Cheongju-city, South Korea) with adjustable sprockets
(Front: 11, Rear: 14), and seed plates (G-12 for wheat and AA-6 for BT) whereas common
bean cv. ‘Red Kidney’ and fava bean cv. ‘Bell’ were hand seeded the same day. Sowing depth
varied with seed size and ranged from 3-4 cm for wheat and 5-6 cm for beans. No
fertilizers, pesticides or fungicides were used throughout the growing season.
70
4.1.4 Data collection and analysis
Plant-based parameters: Data were recorded for plant height (from soil surface to the tip of
apical leaf), number of effective tillers (spikes) m-2, days to harvest, number of nodules (in
beans), pod or spike length, seed number, grain yield (t ha-1), 1000 seed weight (g), and
harvest index [HI, defined as a ratio of economic yield (grain yield) to the total above
ground biomass (grain yield + shoot biomass)]. Chlorophyll concentration index (CCI) was
measured using a handheld chlorophyll meter (Model CCM 200 Plus, Opti-Sciences Inc.,
New Hampshire, USA) on the flag leaf and the 3rd leaf prior to the flowering (50 DAS).
Nodulation was assessed by counting and inspecting the nodules of 3 randomly selected
bean plants in both monoculture and intercrop plots prior-to-flowering (i.e., 50 days after
sowing) following a procedure similar to Chapagain and Riseman (2012). Spike or pod
color was a determinant of maturity and considered ready for harvest when they were
straw-colored and 80% of the grains of the spike were in the hard-dough stage.
Plants in the middle section of each plot, leaving two rows on either side, were harvested at
maturity for yield measurements. Sub-samples were collected from two different 1 m2
areas within each plot, and averaged. Shoots of beans and wheat plants were harvested by
hand leaving 5 cm tall stubble, oven dried at 70°C for 72 hours, and threshed separately by
a stationary thresher. Individual crop yield (grain and total biomass) was calculated to
permit comparison of yields, land equivalent ratios (LER) and N contents with those when
they were grown alone.
Relative and total intercrop productivity: The benefits of multispecies systems i.e., system
productivity, was estimated using the Land Equivalent Ratio (LER, Mead and Willey, 1980)
71
that compares the yields obtained by growing two or more species together with yields
obtained by growing the same crops as monocultures. The LER for two intercrop species in
proportional replacement design was calculated as follows:
LER = intercrop yieldw/mono yieldw + intercrop yieldb/mono yieldb
where subscript w indicates wheat and subscript b indicates bean. The yields of mono and
intercrop species were calculated as t ha-1.
Intercropped plots with LER values greater than 1.0 were considered advantaged
combinations, whereas plots with LER values less than 1.0 were considered disadvantaged
combinations. Grain yield was expressed at 12.5% moisture. LER in terms of total plant
mass (grain + shoot biomass) production was also calculated. Intercrop productivity was
also assessed in terms of Total Land Output (TLO, Jolliffe and Wanjau, 1999) as follows:
TLO = wheat yield + bean yield
Intercrop plots with greater TLO values compared to monoculture plots showed a yield
advantage.
Tissue N, C,
15N
and
13C
analysis: Plant tissue samples for N and C analyses were prepared
from the shoots (i.e., leaves and stem) and grains separately of both nodulated bean and
non-fixing wheat plants harvested at maturity while samples for 15N and 13C analyses were
prepared from all aboveground biomass harvested at pod or grain filling stages in bean and
wheat, respectively. They were bulked by plot and species and dried at 70oC for 72 hours
and subsequently homogenized into a fine powder using a 115 V Wig-L-Bug grinding mill
(International Crystal Laboratories, Garfield, NJ, USA). The subsamples, 2-3 mg each, were
weighed into tin capsules using a Mettler AT20 micro-balance (Toledo, OH), and analyzed
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for total N, C, δ15N and δ13C by high-temperature flash combustion using an elemental
analyzer (Vario EL Cube elemental analyzer, Elementar Analysensysteme GmbH, Hanau,
Germany) coupled by continuous flow to an isotope ratio mass spectrometer (Isoprime
isotope ratio mass spectrometer, Isoprime Ltd., Cheadle, UK). The percentage of plant N
derived from atmospheric N2 (% NDFA), based on the natural variation in the abundance of
15N,
was calculated according to Shearer and Kohl (1988) as follows:
% NDFA = 100 x (δ15Nref − δ15Nleg) / (δ15Nref − δ15Nfix)
where δ15Nref is the δ15N value for the non-fixing wheat reference plant grown alone and
dependent on soil N; δ15Nleg is the δ15N value for the nodulating and potentially N2-fixing
beans grown in mixed culture where fixed N and soil N are available as N sources; and
δ15Nfix is the δ15N value for the nodulating beans when they are totally dependent on
biological N fixation (BNF) as the N source.
In addition, the quantification of N transferred to the companion wheat plants was
determined by using the following formula (He, 2002):
% N transfer = 100 x (δ15N wheat mono - δ15N wheat intercrop) / δ15N wheat mono
where δ15N wheat
mono
is the δ15N value for wheat when they are grown alone and
dependent on soil N, and δ15N wheat intercrop is the δ15N value for companion wheat plants
grown in intercrop plots.
In order to calculate the δ15Nfix value for beans, identical cultivars were grown separately in
plant boxes filled with quartz sand, and supplied with N-free media and commercial
rhizobia (Garden Inoculant for beans, EMD Crop Bioscience, WI, USA) as inoculum. The
medium was prepared following the modified version of Mae and Ohira (1981) and
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contained: 50 mM Fe-EDTA, 50 mM KCl (MW 74.55), 0.5M K2SO4 (MW 174.26), 1M KH2PO4
(MW 136.09), 0.5 M MgSO4·7H2O (MW 246.49), 1M CaCl2 (MW 110.98) as macroelements;
and 0.5 mM CuSO4·5H2O (MW 249.7), 25 mM H3BO3 (MW 61.84), 2 mM ZnSO4·7H2O (MW
287.55), 2 mM MnSO4·H2O (MW 169.01), and 0.5 mM Na2MoO4·2H2O (MW 241.9) as
microelements. The macro and microelement solutions were prepared separately with
distilled water, and then poured at 5-10 ml per day into plant boxes each containing 4
plants.
The δ13C values from plant samples were considered as proxy for direct measurement of
water use efficiency (WUE) (Condon et al., 1987; 2002). In this method, less negative δ13C
values indicate higher WUE whereas more negative δ13C values indicate lower WUE.
Grain nitrogen values were converted to crude protein levels as %N x 6.25 for beans, and
%N x 5.8 for wheat (Jones, 1931). Total N and C yields were derived by using grain and
shoot biomass yield, and N and C content in grain and shoot biomass in each crop
component.
Gross ecosystem photosynthesis, ecosystem respiration and net ecosystem productivity
measurements: Field measurements of net ecosystem CO2 exchange (NEE) in cropland (i.e.,
monoculture and intercrop plots) and ecosystem respiration (Re) were conducted at the
soil surface using a dynamic closed automated chamber connected to a portable CO2 gas
analyzer by following a procedure similar to that of Jassal et al. (2010). The automated
chamber consisted of a PVC cylinder that was equipped with a calibrated photosensor
(RainWise Quantum Solar Sensor, RainWise Inc., Bar Harbor, ME, USA) for the
measurement of photosynthetically active radiation (PAR), an ordinary axial fan to ensure
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uniform CO2 concentration in the chamber, and outlet vent tube of 15 cm long and 3 mm
internal diameter to prevent pressure differences between the chamber and the
atmosphere. The cylinder dimensions were 19.5 cm internal diameter, 60.8 cm height, and
1 cm wall thickness. The chamber effective volume when deployed was 20.34 dm3 while
the surface area covered by the chamber was 0.0298 m2. The cylinder was inserted to a
depth of about 2 cm below the soil surface during field measurements.
The CO2 gas analyzer unit consisted of an infrared gas analyzer (IRGA) (model LI-820, LICOR Inc., Lincoln, NE), a 21X data logger (model 21X, Campbell Scientific Inc. (CSI), Logan,
UT, USA), an AC linear pump (model SPP-40GBLS-101, GAST Manufacturing Corp., Benton
Harbor, MI, USA), and a data storage module (SM192, CSI.). The IRGA was calibrated in the
UBC Biometeorology and Soil Physics Laboratory with cylinders of CO2 in dry air calibrated
using standards provided by the Canadian Greenhouse Gases Measurement Laboratory,
Meteorological Service of Canada, Downsview, Ontario. The effective volume was assumed
to be approximately 12% higher than the geometric headspace volume, due to the nearsurface soil porosity and the adsorption of CO2 on the soil surface and chamber walls
(Jassal et al., 2010; 2012).
NEE in a cropland was measured from two different areas within each plot by placing the
chamber on the soil surface three times a day (i.e., morning, afternoon and evening) at 25,
50 and 75 days after sowing enclosing the plants (Appendix J). This was followed by the
measurement of Re by placing the chamber on bare soil plus plant roots after harvesting.
When measuring NEE and Re, the pump was turned on 1 minute before chamber placement
on the soil surface and continued for 3 minutes. The IRGA and the axial fan in the cylinder
were kept on between measurements. The time rate of change in the CO2 mole fraction in
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the chamber headspace (dC/dt, µmol mol-1 s-1) during a period of 90 seconds beginning 20
seconds after chamber closure, which was found to be linear, was used to calculate the flux,
F (µmol m-2 s-1) as follows (Jassal et al., 2005):
F=
where P is the atmospheric pressure (Pa), R is the universal gas constant (8.314 J mol-1 K-1),
T is the temperature of the chamber air (K), V is the geometric volume of the chamber
headspace (0.02034 m3), A is the surface area covered by the chamber (0.0298 m2), and a is
the ratio of the effective volume to the geometric volume of the chamber (i.e., 1.12). Since
the rate of increase in relative humidity in the chamber was less than 2% minute -1 over the
90 seconds, the water vapour dilution effect was estimated to be less than 1% of F, and was
therefore neglected (Welles, 2001).
Gross ecosystem photosynthesis - GEP (i.e., Re minus NEE), often referred to as gross
primary productivity of the cropland, and net ecosystem productivity - NEP (i.e., NEE with
a negative sign, often referred to as seasonal net carbon sequestration) were calculated for
all planting arrangements. The micromole values of NEP were converted to mg C m-2 hr-1
using a conversion factor of 43.2 (Jassal et al., 2005). When NEE is positive, the ecosystem
is releasing C to the atmosphere while when negative, the ecosystem is absorbing C from
the atmosphere.
Crop management parameters: General observations were made 30 and 70 days after
sowing (DAS) on the type, number and the amount of weeds present, and insect pest and
disease pressures with regard to type and nature of damage. Diseases of economic
importance
e.g.,
Scald
or
Leaf
Blotch
(Rhynchosporium
secalis),
76
Stem/Leaf/Stripe/Yellow/Brown Rust (Puccinia spp.), and Septoria Leaf Spot or Glume
Blotch (Septoria tritici) were monitored and noted over the course of the season as
suggested by Chapagain and Riseman (2012).
Data analysis: The data collected were analyzed using MSTAT-C (MSU, 1993) and MATLAB
(Mathworks-MATLAB and Simulink for Technical Computing, Natick, MA, USA). Analyses of
variance were performed on individual plot data for plant performance metrics, yields, C
and N accumulation. Fisher’s least significant differences were calculated with 5%
significance levels in MSTAT-C using the error variance from the analysis. Simple
correlation coefficients and coefficients of determination were determined between
selected parameters using Statistical Package for the Social Sciences (SPSS) software.
4.2 Results
4.2.1 Soil mineral nitrogen and δ15N content
Pre-plant plots were homogenous and showed uniform distribution of soil mineral N
(Table 4.2). Soil samples taken after final harvest (Fall-2012) showed monoculture fava
bean cv. ‘Bell’ plots displayed the highest soil mineral N balance (+0.7 mg NH4+ and +6 mg
NO3- kg-1 dry soil) compared with common bean cv. ‘Red Kidney’ (+0.4 mg NH4+ and +4 mg
NO3- kg-1 dry soil) or ‘Black Turtle’ (+0.5 mg NH4+ and +3 mg NO3- kg-1 dry soil) plots. Both N
pools declined in the wheat monoculture plots (-0.9 mg NH4+ and -5.8 mg NO3- kg-1 dry soil)
(Table 4.2). Wheat-common bean intercrop plots displayed a less negative N balance
compared to wheat monoculture plots (Table 4.2). The wheat-fava bean cv. ‘Bell’
combination in 1:1 arrangement was the only plot that showed the highest mineral N
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balance (+0.2 mg NH4+ and +1.1 mg NO3- kg-1 dry soil) compared to all other intercrop
combinations.
The average δ15N values of nodulating legumes grown in N-free media were -1.34 ‰ (fava
bean cv. ‘Bell’), -1.04 ‰ (common bean cv. ‘Black Turtle’) and -0.97 ‰ (common bean cv.
‘Red Kidney’) while the non-fixing wheat reference plants grown in field as monoculture
had average δ15N value of 2.87 ‰ (data not shown). There was sufficiently a large
difference between soil δ15N (3.74 ‰) and atmospheric δ15N (0 ‰) in order to measure
dilution effects as suggested by Shearer and Kohl (1988).
4.2.2 Plant performance indices
Grain yield and LER values from monoculture and wheat-bean intercrop combinations are
shown (Table 4.3). In monocultures, the yield of ‘Red Kidney’ increased significantly from
2.3 t ha-1 to 3 t ha-1 from year 1 to year 2 (average 2.6 t ha-1, Figure 4.2). Common bean cv.
‘Black Turtle’ and fava bean cv. ‘Bell’ also displayed similar trends. Grain yields of wheat
across monoculture plots were similar. However, yields declined from 3.4 t ha-1 in year 1 to
3 t ha-1 in year 2 (average 3.2 t ha-1, Figure 4.2). These trends (i.e., legumes increasing and
wheat decreasing) were similar in intercrop plots.
Grain yields of wheat and bean components in intercrop plots were lower than their
monocultured counterparts due to reduced seed densities. However, wheat grain yield
from wheat-fava bean plots were relatively higher than wheat-common bean combinations
with the highest yield (3.1 t ha-1) from the 2:1 arrangement (Figure 4.2). In addition, the
productivity of mixtures (i.e., Total Land Outputs - TLO and Land Equivalent Ratio - LER)
were significantly higher in intercrop plots with the higher values observed in year 2
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across all cultivar combinations (Table 4.3). Among the intercrop combinations, wheat-fava
bean cv. ‘Bell’ in row arrangement displayed the highest land productivity (32 to 50%)
compared to their sole crops (Table 4.3). This was true when planted in rows of 1:1 (up to
50%) or 2:1 (up to 32%), with the average TLOs of 4.36 and 4 t ha-1, respectively.
Wheat-common bean cv. ‘Red Kidney’ also showed higher TLO and LER in row
arrangements with the highest TLO (4.05 t ha-1) and LER (1.33) in the 2:1 arrangement
which resulted in a 33% greater land productivity. Plots with 1:1 arrangement showed
13% higher land productivity than sole crops. Mixed planting arrangements across all
cultivar combinations did not produce significantly different LER values from monoculture
plots. Wheat-common bean cv. ‘Black Turtle’ did not show significant effects on LER values,
though the 1:1 arrangement produced 14% more yield compared to the sole crops.
The TLO and LER values calculated using total biomass (all above ground biomass)
production in monoculture and intercrop plots displayed similar trends as when calculated
with grain yield (Table 4.4).
Lower grain yields and LER with common beans were associated with poor plant
performance metrics (i.e., CCI, number of pods, seed number, and 1000 seed test weight) in
year 1 (Table 4.5, Appendix B). However, performance improved significantly in year 2 for
the common bean cv. ‘Red Kidney’ showing higher values for 1000 seed weight and grain
protein content in 2:1 arrangements (Table 4.5). The common bean cv. ‘Black Turtle’, on
the other hand, displayed higher 1000 seed weight, biomass nitrogen content and grain
protein in mixed planting arrangements compared to row intercropping. Compared to
monoculture plots, common bean in intercrop plots displayed reduced biomass N which
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significantly increased biomass C:N ratios (Table 4.5). The performance of fava bean cv.
‘Bell’, however, was relatively more stable than either common bean cultivars over the two
years.
Unlike beans, the performance of wheat declined over time in both monoculture and
intercrop plots (Table 4.3, Appendix B). In addition, wheat components in wheat-common
bean combinations displayed significantly lower 1000 seed weight and harvest index in
year 2 (Table 4.5, Appendix B) probably due to increased competition with beans. Wheat
from all intercrop plots displayed increased biomass and grain nitrogen content with the
highest values from the highest bean density (i.e., 1:1 arrangement) in year 2. This resulted
in lower biomass C:N ratios and higher grain protein levels compared to the wheat
monoculture plots (Table 4.5).
4.2.3 Biological N2 fixation and transfer
Intercropping increased nodulation, percent N derived from symbiotic N2 fixation, and
transfer to the companion wheat plants (Table 4.6). The number of nodules and the
proportion of nitrogen fixed by beans were significantly higher in intercrop plots as
compared to their monoculture counterparts. Fava bean cv. ‘Bell’ developed 60 to 80%
more nodules in intercrops resulting in 10-12% more N derived from symbiotic N2 fixation
compared to when grown as a monoculture. Fava bean cv. ‘Bell’ in 1:1 arrangement
displayed the highest amount of N (average of 96 kg ha-1) compared to other bean cultivars
of which 74 kg (77%) was derived from symbiotic N2 fixation (Table 4.6).
Similarly, nodules of common bean cvs. ‘Red Kidney’ and ‘Black Turtle’ increased by 3871% and 46-69%, respectively, in intercrops as compared to their monoculture plots
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(Table 4.6). Common bean in intercrop plots also fixed more N2 (up to 12% increase) than
their sole stands. The rate of biological N fixation improved in year 2 as compared to year 1
with fava bean cv. ‘Bell’ fixing the most (average of 72% of total biomass N in year 1 to 89%
in year 2) in the 2:1 arrangement, and common bean cv. ‘Red Kidney’ fixing the most
(average of 57% in year 1 to 75% in year 2) in the 1:1 arrangement (Table 4.6).
N-transfer rates between the legume and wheat varied with legume genotypes and spatial
arrangements (Table 4.6). The greatest transfer rates were in the wheat-fava bean cv. ‘Bell’
arrangements with the 1:1 plots highest at 13% followed by 2:1 and mixed planting
arrangements at 11%. The highest amount of N-transfer, however, observed in wheat-fava
bean cv. ‘Bell’ in the 2:1 arrangement (i.e., 7.8 kg of N in companion wheat). Wheatcommon bean cv. ‘Red Kidney’ transferred an average of 4% while common bean cv. ‘Black
Turtle’ did not transfer any N to the companion wheat (Table 4.6). The rate of N transfer
improved in year 2 as compared to year 1 with fava bean cv. ‘Bell’ in the 1:1 arrangement
transferring the most (average of 12% of N in wheat biomass in year 1 to 14% in year 2).
Common bean cv. ‘Red Kidney’ in the 1:1 arrangement transferred an average of 5% of N in
wheat biomass in year 1 to 7% in year 2 (Table 4.6).
4.2.4 N and C accumulation in biomass
Monocultured legumes accumulated more N in grains and shoots than their intercrop
components with the greatest amount in the fava bean cv. ‘Bell’ plot (average of 132 kg ha-1
of which 90 kg was derived from BNF) while common bean cvs. ‘Red Kidney’ and ‘Black
Turtle accumulated 125 and 106 kg ha-1, respectively, of which 69 kg ha-1 in common bean
cv. ‘Black Turtle’ and 58 kg ha-1 in common bean cv. ‘Red Kidney’ were derived from BNF
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(Table 4.6). Lower N content in intercrop plots was associated with both reduced biomass
production and lower biomass N content.
Bean and wheat accumulated significantly more N in the grain than in the shoot biomass.
However, C accumulation was slightly higher in shoot biomass than in the grain (Table 4.7).
Wheat in intercrops displayed increased grain N percentage compared to wheat grown as a
monoculture. However, the total grain N yield decreased with increasing bean density
(Table 4.7).
Wheat biomass N content in intercrop plots increased with increasing bean density (i.e.,
higher in 1:1 than 2:1). However, the total amount of N accumulated in biomass decreased
with increasing bean density due to a reduction in wheat biomass (Table 4.7). Beans in
intercrop plots also displayed reduced biomass N and a decrease in total N perhaps due to
increased competition as densities increased.
All intercrop plots accumulated more N (i.e., 1.1 to 29.4 kg ha-1 higher) in shoot biomass
compared to monocultured wheat but not more than any monocultured bean (Table 4.7).
The wheat-fava bean cv. ‘Bell’ in 1:1 arrangement, however, accumulated the highest with
an average of 34 kg N ha-1, an amount higher than monocultured fava. Wheat-fava bean cv.
‘Bell’ combinations accumulated the highest amount of N among intercrop plots with 84176% increases over wheat monoculture plots, with the highest gain in the 1:1
arrangement. Biomass N accumulation in wheat-common bean cv. ‘Red Kidney’ or ‘Black
Turtle’ combinations were 18-50% and 42-63% higher, respectively, than wheat
monoculture (Table 4.7). Wheat-fava bean cv. ‘Bell’ in 1:1 arrangement displayed the
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highest total N (grain plus shoot biomass) yield (150 kg N ha-1) followed by wheat-common
bean cv. ‘Red Kidney’ (129 kg ha-1) in the 2:1 arrangement.
The most shoot biomass C was produced by the wheat-fava bean cv. ‘Bell’ 1:1 arrangement
plot (214 g C m-2 y-1, i.e. 26% higher) followed by the 2:1 arrangement (195 g C m-2 y-1, i.e.,
15% higher) compared to wheat monoculture plots (Table 4.7). Wheat-common bean cvs.
‘Red Kidney’ or ‘Black Turtle’, however, did not accumulate different amounts of C
compared to wheat monoculture plots. In addition, the total biomass C produced (i.e., grain
plus shoot biomass) was highest in the wheat-fava bean cv. ‘Bell’ 1:1 plots (396 g C m-2 y-1)
followed by the 2:1 arrangement (365 g C m-2 y-1). A strong correlation (r2=0.98) was
observed between the amount of N and C in beans (Appendix D). Wheat components in
wheat-common bean cv. ‘Red Kidney’ and Wheat-fava bean cv ‘Bell’ plots showed a very
strong and positive relationships (r2=0.77 and 0.67, respectively) between the accumulated
N and C (Appendix E). In addition, wheat components in wheat-fava bean cv. ‘Bell’
displayed very strong association between grain yield and N content (r2=0.98), as well as
between grain yield and biomass C accumulation (r2=0.95) (Appendix F).
4.2.5 Net ecosystem CO2 exchange, ecosystem respiration, gross ecosystem
photosynthesis and net ecosystem productivity
Average daytime NEE, Re, GEP and NEP in monoculture and intercrop plots are presented
in Table 4.8 with NEE, GEP and NEP varying by spatial arrangement. The greatest GEP
values were observed during the mid-growth stage (50 days after seeding i.e., just prior to
flowering, Figure 4.3a, 4.3b, 4.3c) in all planting arrangements.
83
Cropped areas averaged 164%-202% more CO2 fixation (i.e., greater GEP) than CO2 loss
(i.e., Re) from bare soil plus plant roots with the highest GEP from the wheat-common bean
cv. ‘Red Kidney’ in the 2:1 arrangement. However, NEP in wheat-common bean cv. ‘Red
Kidney’ (2:1 arrangement) was lower than the wheat-fava bean cv. ‘Bell’ plots in the 1:1
arrangement. Wheat-fava bean cv. ‘Bell’ in the 1:1 arrangement displayed the greatest NEP
(Figure 4.4a, 4.4b, 4.4c) resulting in the sequestration of the most C with a seasonal average
rate of 208 mg C m-2 hr-1 (i.e., 7% higher than wheat monoculture plots). Bean monoculture
and all intercrop plots displayed greater NEP in year 2 as compared to year 1.
Wheat-fava bean cv. ‘Bell’ and wheat-common bean cv. ‘Red Kidney’ in the 2:1
arrangements also showed greater NEP compared to wheat monoculture plots (Table 4.8).
Mixed crop arrangements, on the other hand, displayed the least NEP leading to lower C
sequestration compared to all other combinations. Beans in intercrop plots fixed less CO2
than monocultured beans. However, the proportion of CO2 fixed by the wheat component
was higher in row intercrop plots than monocultured wheat (data not shown).
4.2.6 Water use efficiency
The effect of genotype and spatial arrangement on tissue δ13C values in monoculture and
intercrop plots is presented (Table 4.9). Wheat in wheat-common bean cv. ‘Red Kidney’ and
wheat-fava bean cv. ‘Bell’ combinations displayed less negative δ13C values compared to
monocultured wheat indicating that the intrinsic WUE of wheat is improved when grown
with common bean cv. ‘Red Kidney’ or fava bean cv. ‘Bell’, with improved WUE in year 2 as
compared to year 1. Table 4.9 shows that values are higher (less negative) for common
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bean cv. ‘Black Turtle’, but lower (more negative) for fava bean cv. ‘Bell’ relative to their
monocultures. Common bean cv. ‘Red Kidney’ has a variable response.
The δ13C values of the common bean cv. ‘Black Turtle’ were higher (less negative) when
grown in combination with wheat (Table 4.9) indicating that WUE of the common bean cv.
‘Black Turtle’ improved when intercropped. This particular legume, however, did not
influence the δ13C values of the companion wheat.
4.2.7 Crop competition, weed and disease pressure
Higher biomass of common beans in year 2 suppressed the growth of wheat resulting in
reduced 1000 seed weight, HI, and yield (Table 4.3, 4.5). Wheat growth and grain qualities
were significantly affected in all planting arrangements of wheat-common bean cv. ‘Black
Turtle’ combinations compared with wheat-fava bean cv. ‘Bell’ and wheat-common bean cv.
‘Red Kidney’. Wheat-fava bean exhibited the least competition (Table 4.10) regardless of
planting arrangement or production year, possibly due to their upright growth habit.
The most common weeds in either monoculture or intercrop plots were common
chickweed (Stellaria media L.), green smartweed (Polygonum lapathifolium L.), prostrate
knotweed (Polygonum aviculare L.), pigweed (Amaranthus spp.), crab grass (Digitaria spp.),
barnyard grass (Echinochloa crusgalli L.), black nightshade (Solanum nigrum L.), and field
horsetail (Equisetum arvense L.). Pigweed was observed early in the season along with
chickweed. Common chickweed, an excellent colonizer that forms a succulent mat on the
soil surface, was the predominant weed from mid to late season. All crop plots grew well
with 3 manual weedings, 15, 30 and 45 days after sowing. In general, less late-season
weeds were observed in the wheat-fava bean plots compared with wheat-common bean
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plots. Wheat-common bean cv. ‘Black Turtle’ plots were impacted the most by weed
pressure. Total weed biomass was greater in bean monoculture plots than wheat and was
greatest early to mid-season compared with late-season. Weed biomass in intercrop plots
was reduced as wheat density increased.
In general, the occurrence of wheat disease was low over the two production years. When
present, the most prevalent diseases included stripe and stem rusts (Puccinia spp.) and
Septoria leaf blotch (Septoria spp.). No significant differences were observed among
treatments regarding the occurrence or the extent of disease. Septoria leaf blotch infection
was most severe early in the season whereas stripe and stem rusts were most severe mid
to late season.
4.3 Discussion
Our results indicate multiple benefits of organic intercropping compared to monoculture
plots including higher yields and greater LER. In organic production systems, higher yields
and greater land productivity are possible when wheat is intercropped with common bean.
For example, Bulson et al. (1997) reported the highest LER value (1.29) among pure and
intercropped plots when wheat and bean were intercropped at 75% the recommended
density while, Hauggaard-Nielsen et al. (2009) found a 25% to 30% grain yield increase in
intercrop plots compared to monoculture plots. They attributed the higher yields in
intercrop plots to a more efficient use of limited plant resources (i.e., water, light, and
nutrients) compared to monoculture plots. Sahota and Malhi (2012) also reported that
intercropping required 7-17% less land than monoculture crops to produce the same level
of yield. Chen et al. (2004) compared a barley, Hordeum vulgare L.- pea intercrop system
86
with monoculture plots and identified higher LER in the intercrop plots, ranging from 1.05
to 1.24 on a biomass basis, and from 1.05 to 1.26 on a grain protein basis.
Our research identified changes in wheat grain quality associated with intercrop planting.
In support, intercropping was found to be effective in enhancing wheat grain quality by
increasing grain nitrogen and sulfur content resulting in higher protein and thus, more
suitable for baking (Gooding et al., 2007). The extent of change, however, may depend on
the density of legume species used in the intercrop. Bulson et al. (1997) found an increase
in grain N and protein content while increasing bean densities in intercrops. Lauk and Lauk
(2008) also showed a positive association of pea density with increased protein content of
the cereal grains. However, they further noted the formation of smaller grains in cereals
with increased pea density resulting in the substantial decreases in grain yield.
We observed less late-season weed growth in wheat-fava bean intercrop plots compared
with monoculture plots. This is similar to the findings of Bulson et al. (1997) and Haymes
and Lee (1999) who reported reduced weed growth in intercrop plots compared with
monocultured wheat. Hauggaard-Nielsen et al. (2007) further noticed reduced diseases
occurrence when cereal grains are intercropped with legumes. However, we did not
observe a change in disease incidence among our plots.
The proportion of legume species in intercrop plots can affect biomass yield and quality.
We observed an increased yield and N content of wheat biomass in intercrop plots
compared to monocultured wheat. Bulson et al. (1997) also showed a positive association
between increased bean densities and higher biomass N content in the wheat component.
Similarly, Ghanbari-Bonjar and Lee (2002), and Lithourgidis and Dordas (2010) working
87
with wheat-bean intercrop found greater forage dry matter and greater crude protein
compared to the monocultured wheat. In addition, Putnam et al. (1986) demonstrated that
intercropping corn with soybean increases forage yield and crude protein content by 1151% compared to sole corn plots. Therefore cereals, when intercropped with legumes,
often display higher biomass and grain quality that significantly affects nutritional interests
(Lithorgidis et al., 2011).
Biological nitrogen fixation by beans can supplement or replace the nitrogen requirement
of the subsequent crop. This is especially true under low soil N conditions (Fujita et al.
1992; Lunnan 1989). Our results showed that wheat N requirement can be reduced by
intercropping with bean through direct N-transfer. We found that beans transferred up to 8
kg N ha-1 to the companion wheat plant, and have accumulated 6-22 kg N ha-1 through
shoot biomass when planted as an intercrop. This further shows that N transfer occurred
within a season at a greater rate from higher bean (common bean cv. ‘Red Kidney’ and fava
bean cv. ‘Bell’) density plots in row arrangements (1:1), perhaps due to physical co-location
of the root systems that facilitate more direct N transfer between species. Increase in N
transfer in the second year could be due to combination of within year and residual legume
N inputs from the first year mineralizing and becoming available to the wheat in the second
year. The benefits of other legume-based intercrops have been shown through direct plantto-plant N transfer, however, significant variation is reported in the amount of N
transferred (i.e., ≤5 to 20% of the N in the receiver plants) (He et al., 2003; 2009; Johansen
and Jensen 1996).
Wheat-bean intercropping appeared to be very important for the development of
sustainable food production systems as they recycle both atmospheric CO2 and N into the
88
production of grains or plant biomass (i.e., living matter). Our studies identified multiple
benefits of organic intercropping related to these two important elements i.e., higher infield nitrogen use efficiency, N2 fixation and transfer to companion wheat, greater
ecosystem productivity (i.e., GEP and NEP), C sequestration, and improved WUE in wheat.
Interestingly both common and fava beans fixed more N in intercrop plots than
monoculture perhaps in response to the increased competition with wheat plants for soil N
and promoting bean’s greater reliance on symbiotic N2-fixation. Hauggaard-Nielsen et al.
(2009) reported that under organic conditions, total N recovery was greater in pea-barley
intercrop plots than in the monoculture comparisons, and suggested a high degree of
complementarities due to species interaction that enables natural regulation mechanisms
between intercrop components. They further reported that pea-barley intercrops used
nitrogen sources 17 to 31% more efficiently than by the monoculture plots due to the
increased acquisition of soil mineral N by the barley component which promoted pea to
rely more on internal N2-fixation. Izaurralde et al. (1992) reported increased N yield,
greater N-fixation efficiency, and more shoot and root residue-N mineralization for
subsequent crops when field pea and barley were intercropped. Prasad and Brook (2005)
also reported a possibility of improving soil C and N by establishing cereal-legume
intercrops as they increase agroecosystem complexity and enhance complementary use of
resources in time and space. The inclusion of legumes with a cereal regulates the internal N
cycle via N2 fixation (Schipanski et al., 2010) and reduces the amount of fertilizer required
for crop growth (Inal et al., 2007).
Intercropping cereals and legumes may stimulate greater GEP by increasing N availability
from BNF and subsequently stimulating photosynthesis in the cereals (Hartwig et al., 2002;
89
Zanetti et al., 1997), and therefore may support greater overall ecosystem productivity.
Also, increased CO2 fixation and reduced respiration (i.e., Re) is positively associated with
increased NEP and WUE, with the greater values observed in year 2 as compared to year 1.
Wheat in our intercrop plots produced increased biomass N, increased GEP (i.e., CO2
fixation) and greater water use efficiency resulting in greater NEP than monocultured
wheat. This suggests a synergy is created when legumes are intercropped with cereals
(Cardoso et al., 2007).
Our experiment showed that soil respiration rates (Re) across all treatments were not
affected by plot composition and were comparable with the values reported by Jassal et al.
(2005) for our geographic zone (i.e., Vancouver, BC region). However, CO2 fixation (i.e.,
GEP) and biomass C yield were higher when wheat and fava bean were planted in 1:1 and
2:1 arrangements leading to the highest observed NEP, also referred to as seasonal net
carbon sequestration, compared to all other crop combinations. The higher GEP and NEP
from this intercrop combination also led to higher grain and above ground biomass yields
with the highest grain (4.36 t ha-1) and total above ground biomass (9.23 t ha-1) production
from the 1:1 arrangement. Dyer et al. (2012) reported an increase in soil organic carbon
(SOC) concentration and a lowering of GHG emission rates from intercrop plots compared
to when the legume and cereal were grown as monocultures. This suggests that increased
GEP and associated C sequestration through biomass production improved SOC content.
Our observation of increased intrinsic WUE in wheat when grown with either fava bean cv.
‘Bell’ or common bean cv. ‘Red Kidney’ is perhaps related to improved N nutrition. As
wheat N status is improved, photosynthesis is enhanced relative to transpiration rate
(Livingston et al., 1999) leading to more water efficient grain and biomass production. In
90
addition, intercropping might help regulate source-sink relationship by creating special
microclimatic situation, reduce inter-row evaporation, and excessive transpiration which
together help enhance overall system water use efficiency (Zhang et al., 2012). The effect of
wheat on improved WUE in common bean cv. ‘Black Turtle’, on the other hand, seems to be
related to increased competition for water between wheat and bean.
Overall, the specific intercrop combination of wheat (small grain) and bean (grain legume)
may provide a new opportunity to better manage nutrients in a low-input small grain
production system, one that fulfills both economic and environmental interests through
higher land productivity, improved grain and biomass quality, increased GEP, NEP, WUE,
and reduced reliance on mineral N fertilizer inputs and GHGs emissions.
4.4 Conclusions
Our organically managed trials on intercropping systems revealed significant and positive
responses from the interacting species on plant performance and overall system
productivity. Wheat-fava bean combinations increased land productivity (32-50% higher)
compared to monoculture counterparts with the highest values in a 1:1 arrangement while
wheat intercropped with common bean produced better performance values in a 2:1
arrangement (i.e., 32% higher land productivity than monocultured wheat). Grain and nonharvested biomass nitrogen content of the wheat component increased significantly with a
higher density of bean (i.e., 1:1 arrangement) while the total amount of N accumulated by
wheat residues decreased with increasing bean density (i.e., in 1:1 arrangement) due to a
reduction in wheat biomass. Total weed biomass in intercrop plots was reduced with
increased wheat densities (i.e., 2:1 arrangement).
91
This study further demonstrated that intercropping wheat with fava bean gave the highest
total biomass, higher amount of N derived from symbiotic N2 fixation, greater percent of Ntransfer, higher N and C accumulation in aboveground biomass, improved GEP, NEP and
WUE compared to wheat-common bean combinations, and monocultured wheat. For all
bean cultivars, the number of nodules and the proportion of symbiotically fixed N were
significantly higher in intercrop plots resulting in the accumulation of 18-176% more N in
shoot biomass than in wheat monoculture plots. The highest rates of N-transfer (13%)
were also observed in wheat-fava bean cv. ‘Bell’ combination when planted in the 1:1
arrangement. The highest C accumulation in plant biomass (214 g C m-2 yr-1, i.e., 26%
higher than wheat monoculture) was also achieved in wheat-fava bean cv. ‘Bell’ (1:1)
compared to wheat monoculture (170 g C m-2 yr-1). Wheat-fava bean cv. ‘Bell’ (1:1
arrangement) also showed the greatest NEP with a daytime average sequestration of 208
mg C m-2 hr-1 compared to other crop combinations. Wheat intercrops sequestered more C
than their monoculture counterparts, perhaps related to increased N availability from the
bean component.
This study demonstrated that intercropping wheat with fava bean is an efficient strategy to
increase land productivity, increased N and C accumulation, greater NUE, NEP and WUE
than monocultures under low soil N and C conditions typical of organic systems.
Furthermore, the wheat-fava bean cv. ‘Bell’ (1:1) combination appeared to be the most
productive in terms of grain, N and C yields followed by wheat-fava bean cv. ‘Bell’ (2:1) and
wheat-common bean cv. ‘Red Kidney’ (2:1) arrangements.
92
Table 4.1 Climate data† during the cropping seasons of 2011 and 2012 at UBC Farm, Vancouver, Canada.
Mean Air Temperature
Month
at 1.5 m height
Solar Irradiance1
Total Precipitation
(W m-2)
(mm)
(C)
Y1
Y2
Y1
Y2
Y1
May
10.7
11.8
364
440
78.0
June
14.5
13.7
458
352
July
16.3
17.0
453
August
17.5
18.2
September
16.0
Average
SD
(20-cm depth)
(C)
Y1
Y2
48.6
14.2
15.4
25.6
72.4
18.1
17.4
441
33.8
32.4
19.4
20.3
458
412
17.0
2.4
20.3
20.5
14.8
285
303
57.8
5.6
17.5
17.7
15.0
15.1
404
389
42.4
32.3
17.9
18.3
2.62
2.9
51.8
49.6
0.15
0.18
1.18
1.31
212
161
Total Rainfall
†Source:
Soil Temperature
Y2
UBC Climate Station adjacent to Totem Park, 1 km northwest of UBC farm; 124-hour averages; Y1 = year 1; Y2 = year
2; and SD = Standard Deviation
93
Table 4.2 Soil mineral nitrogen (NH4+ and NO3-, mg kg -1 dry soil) at 0-15 cm depth before planting (Spring-2011) and after
final harvest (Fall-2012) in monocultures and wheat-bean intercrop combinations.
Before Planting
After Final Harvest
Mean Difference
(BP)
(AH)
(AH-BP)
Treatments
NH4+
NO3-
NH4+
NO3-
NH4+
NO3-
Wheat-common bean cv. ‘Red Kidney’ combinations
RK Monoculture
4.3
25.0
4.7
29.0
0.4
4.0
Wheat:RK (1:1)
4.0
27.0
3.8
26.1
-0.2
-0.9
Wheat:RK (2:1)
4.3
26.3
3.9
23.8
-0.4
-2.5
Wheat-RK (mixed)
3.3
25.7
2.9
24.5
-0.4
-1.2
Wheat Monoculture
4.1
28.6
3.2
22.8
-0.9
-5.8
SEM (±)
0.34
0.99
0.47
1.13
0.10
0.59
LSD0.05
NS
NS
1.34
3.21
0.28
1.68
Wheat-common bean cv. ‘Black Turtle’ combinations
BT Monoculture
3.3
28.0
3.8
31.0
0.5
3.0
Wheat:BT (1:1)
3.0
26.0
2.8
24.9
-0.2
-1.1
Wheat:BT (2:1)
3.0
27.7
2.7
26.1
-0.3
-1.6
94
Before Planting
After Final Harvest
Mean Difference
(BP)
(AH)
(AH-BP)
Treatments
NH4+
NO3-
NH4+
NO3-
NH4+
NO3-
Wheat-BT (mixed)
3.7
28.3
3.2
26.6
-0.5
-1.7
Wheat Monoculture
3.9
27.5
3.0
21.7
-0.9
-5.8
SEM (±)
0.29
1.98
0.31
1.61
0.14
0.41
LSD0.05
NS
NS
0.88
4.58
0.40
1.17
Wheat-fava bean cv. ‘Bell’ combinations
Bell Monoculture
4.0
27.3
4.7
33.3
0.7
6.0
Wheat:Bell (1:1)
4.3
27.7
4.5
28.8
0.2
1.1
Wheat:Bell (2:1)
4.3
26.0
4.3
26.5
0.0
0.5
Wheat-Bell (mixed)
4.5
28.7
4.4
28.9
-0.1
0.2
Wheat Monoculture
4.5
29.0
3.6
23.2
-0.9
-5.8
SEM (±)
0.34
1.68
0.38
1.24
0.15
0.39
LSD0.05
NS
NS
1.08
3.53
0.43
1.11
RK = Red Kidney; BT = Black Turtle; SEM = Standard Error of the Mean; and LSD = Least Significant Difference
95
Table 4.3 Grain yields, land equivalency ratios and total land output values from monocultures and wheat-bean intercrop
combinations.
Treatments
Grain Yield
Grain Yield
(t ha-1): Y1
( t ha-1): Y2
Bean
Wheat
Bean
Wheat
Land Equivalent Ratio
Y1
Total Land Outputs
Y2
Y1
Y2
Wheat-common bean cv. ‘Red Kidney’ combinations
RK Monoculture
2.30
-
2.96
-
1.00
1.00
2.30
2.96
Wheat:RK (1:1)
0.50
2.66
2.51
1.15
1.01
1.23
3.16
3.66
Wheat:RK (2:1)
0.53
2.92
2.95
1.68
1.10
1.56
3.46
4.63
Wheat-RK (mixed)
0.69
2.33
1.86
1.52
1.00
1.14
3.02
3.38
Wheat Monoculture
-
3.35
-
2.99
1.00
1.00
3.35
2.99
SEM (±)
0.24
0.17
0.13
0.22
0.04
0.08
0.18
0.17
LSD0.05
0.68
0.48
0.37
0.63
NS
0.23
0.51
0.48
Wheat-common bean cv. ‘Black Turtle’ combinations
BT Monoculture
2.79
-
3.84
-
1.00
1.00
2.79
3.84
Wheat:BT (1:1)
0.82
2.66
2.70
0.86
1.09
0.99
3.49
3.56
Wheat:BT (2:1)
0.58
3.09
3.01
1.09
1.13
1.15
3.66
4.10
96
Treatments
Grain Yield
Grain Yield
(t ha-1): Y1
( t ha-1): Y2
Land Equivalent Ratio
Total Land Outputs
Bean
Wheat
Bean
Wheat
Y1
Y2
Y1
Y2
Wheat-BT (mixed)
0.56
2.86
1.81
0.92
1.05
0.78
3.42
2.73
Wheat Monoculture
-
3.35
-
2.99
1.00
1.00
3.35
2.99
SEM (±)
0.28
0.14
0.22
0.19
0.05
0.06
0.14
0.18
LSD0.05
0.80
0.40
0.63
0.54
NS
0.17
0.40
0.51
Wheat-fava bean cv. ‘Bell’ combinations
Bell Monoculture
2.20
-
2.78
-
1.00
1.00
2.20
2.78
Wheat:Bell (1:1)
1.19
3.20
2.41
1.91
1.50
1.51
4.39
4.32
Wheat:Bell (2:1)
0.46
3.66
1.41
2.46
1.30
1.33
4.12
3.87
Wheat-Bell (mixed)
0.58
2.54
1.15
1.86
1.02
1.04
3.12
3.01
Wheat Monoculture
-
3.35
-
2.99
1.00
1.00
3.35
2.99
SEM (±)
0.22
0.18
0.20
0.22
0.07
0.08
0.27
0.20
LSD0.05
0.63
0.51
0.57
0.63
0.20
0.23
0.77
0.57
RK = Red Kidney; BT = Black Turtle; SEM = Standard Error of the Mean; and LSD = Least Significant Difference
97
Table 4.4 Total biomass (grain plus shoot biomass) yields, land equivalency ratios and total land output values from
monocultures and wheat-bean intercrop combinations.
Treatments
Total Biomass Yield
Total Biomass
(t ha-1): Y1
Yield (t ha-1): Y2
Bean
Wheat
Bean
Wheat
Land Equivalent Ratio
Y1
Total Land Outputs
Y2
Y1
Y2
Wheat-common bean cv. ‘Red Kidney’ combinations
RK Monoculture
4.92
-
5.43
-
1.00
1.00
4.92
5.43
Wheat:RK (1:1)
1.01
5.59
4.42
2.73
0.99
1.22
6.60
7.15
Wheat:RK (2:1)
1.04
6.03
5.01
3.65
1.06
1.46
7.07
8.66
Wheat-RK (mixed)
1.41
4.90
3.19
3.38
0.98
1.09
6.31
6.57
Wheat Monoculture
-
7.11
-
6.79
1.00
1.00
7.11
6.79
SEM (±)
0.55
0.27
0.28
0.55
0.03
0.08
0.26
0.37
LSD0.05
1.56
0.77
0.80
1.56
NS
0.23
0.74
1.05
Wheat-common bean cv. ‘Black Turtle’ combinations
BT Monoculture
5.00
-
6.84
-
1.00
1.00
5.00
6.84
Wheat:BT (1:1)
1.38
5.54
5.00
2.21
1.06
1.06
6.92
7.21
Wheat:BT (2:1)
0.92
6.50
5.55
2.90
1.10
1.24
7.42
8.45
98
Treatments
Total Biomass Yield
Total Biomass
(t ha-1): Y1
Yield (t ha-1): Y2
Land Equivalent Ratio
Total Land Outputs
Bean
Wheat
Bean
Wheat
Y1
Y2
Y1
Y2
Wheat-BT (mixed)
0.90
5.90
3.86
2.43
1.01
0.92
6.80
6.29
Wheat Monoculture
-
7.11
-
6.79
1.00
1.00
7.11
6.79
SEM (±)
0.57
0.20
0.36
0.58
0.04
0.08
0.22
0.39
LSD0.05
1.62
0.57
1.02
1.65
NS
0.23
0.63
1.11
Wheat-fava bean cv. ‘Bell’ combinations
Bell Monoculture
4.08
-
5.83
-
1.00
1.00
4.08
5.83
Wheat:Bell (1:1)
2.37
6.59
5.24
4.25
1.51
1.52
8.96
9.49
Wheat:Bell (2:1)
0.87
7.58
3.02
5.59
1.28
1.34
8.45
8.61
Wheat-Bell (mixed)
1.10
5.28
3.39
4.09
1.01
1.18
6.38
7.48
Wheat Monoculture
-
7.11
-
6.79
1.00
1.00
7.11
6.79
SEM (±)
0.43
0.29
0.40
0.49
0.07
0.10
0.32
0.43
LSD0.05
1.22
0.83
1.14
1.39
NS
0.28
0.91
1.22
RK = Red Kidney; BT = Black Turtle; Y1 = year 1; Y2 = year 2; SEM = Standard Error of the Mean; and LSD = Least Significant
Difference
99
Table 4.5 1000 seed weights, biomass C:N and grain protein content of wheat and bean components in monocultures and
wheat-bean intercrop combinations.
Bean Performance
Treatments
1000 Seed
Biomass C:N
Weight (g)
Y1
Y2
Y1
Y2
Wheat Performance
Grain Protein
1000 Seed
(%)
Weight (g)
Y1
Y2
Y1
Y2
Biomass C:N
Grain Protein
(%)
Y1
Y2
Y1
Y2
Wheat-common bean cv. ‘Red Kidney’ combinations
RK Monoculture
435
482
52.7
50.7
19.8
20.4
-
-
-
-
-
-
Wheat:RK (1:1)
421
488
73.9
72.5
23.3
22.6
45.7
34.2
115
110
10.0
11.0
Wheat:RK (2:1)
447
511
74.0
63.4
24.0
24.8
47.7
37.7
127
120
10.1
10.2
Wheat-RK (mixed)
410
489
69.1
71.1
23.3
23.7
47.3
35.9
132
127
10.3
10.2
Wheat Monoculture
-
-
-
-
-
-
45.7
39.5
137
138
10.0
9.0
SEM (±)
6.66
9.88
2.91
2.29
0.56
0.57
1.37
1.29
4.71
4.64
0.32
0.37
LSD0.05
18.9
28.1
8.28
6.52
1.59
1.62
NS
3.67
13.4
13.2
NS
1.05
Wheat-common bean cv. ‘Black Turtle’ combinations
BT Monoculture
143
158
46.6
49.3
22.8
23.5
-
-
-
-
-
-
Wheat:BT (1:1)
134
173
71.8
66.1
23.9
24.8
46.1
29.2
108
101
10.2
10.6
100
Bean Performance
Treatments
1000 Seed
Weight (g)
Biomass C:N
Wheat Performance
Grain Protein
1000 Seed
(%)
Weight (g)
Biomass C:N
Grain Protein
(%)
Y1
Y2
Y1
Y2
Y1
Y2
Y1
Y2
Y1
Y2
Y1
Y2
Wheat:BT (2:1)
137
169
73.8
66.8
22.4
23.4
46.1
28.3
105
107
10.0
10.0
Wheat-BT (mixed)
136
180
60.9
52.3
23.4
25.5
46.4
26.0
114
114
10.2
10.0
Wheat Monoculture
-
-
-
-
-
-
45.7
39.5
137
138
10.0
9.0
SEM (±)
1.95
4.00
3.91
3.02
0.68
0.69
1.42
1.87
5.91
6.54
0.23
0.25
LSD0.05
5.55
11.4
11.1
8.59
NS
1.96
NS
5.32
16.8
18.6
NS
0.71
Wheat-fava bean cv. ‘Bell’ combinations
Bell Monoculture
394
445
36.2
34.5
25.1
25.9
-
-
-
-
-
-
Wheat:Bell (1:1)
390
519
39.2
39.8
25.9
25.2
49.1
37.6
113
107
10.4
11.7
Wheat:Bell (2:1)
358
518
43.2
45.7
25.5
26.8
49.2
38.9
113
122
10.1
10.2
Wheat-Bell (mixed)
406
534
36.5
35.6
25.9
25.8
47.4
38.0
127
136
9.6
9.9
Wheat Monoculture
-
-
-
-
-
-
45.7
39.5
137
138
10.0
9.0
SEM (±)
12.6
13.9
1.81
1.83
0.42
0.61
1.05
1.26
4.57
5.2
0.38
0.28
LSD0.05
35.9
39.8
5.15
5.21
NS
NS
2.98
NS
13.0
14.8
NS
0.80
RK = Red Kidney; BT = Black Turtle; Y1 = year 1; Y2 = year 2; SEM = Standard Error of the Mean; and LSD = Least Significant Difference
101
Table 4.6 Nodule numbers, total N yield, biological nitrogen fixation and transfer by legume in wheat-bean intercrop
combinations during 2011-12 at UBC Farm, Vancouver, Canada.
Year 1
Year 2
Total
Treatments
Nodules1
Plant-1
Total
N
BNF2 Transfer
Yield
(%)
(%)
(kg
BNF2
(kg
ha-1)
Transfer Nodules1
(kg ha-1)
Plant-1
ha-1)
N
Yield
(kg
BNF2 Transfer
(%)
(%)
BNF2
(kg
ha-1)
Transfer
(kg ha-1)
ha-1)
Wheat-common bean cv. ‘Red Kidney’ combinations
RK Monoculture
6
95
47
-
45
-
15
118
62
-
73
-
Wheat:RK (1:1)
10
22
57
4.6
13
1.9
26
103
75
6.7
77
2.7
Wheat:RK (2:1)
9
24
60
2.4
14
1.2
22
131
71
4.7
93
2.4
Wheat-RK
11
30
50
3.3
15
1.5
18
79
63
5.4
50
2.4
SEM (±)
1.31
3.67
3.25
-
2.92
-
1.38
4.13
3.44
-
4.21
-
LSD0.05
3.69
10.4
9.24
-
8.31
-
3.93
11.7
9.78
-
11.9
-
(mixed)
102
Year 1
Year 2
Total
Treatments
Total
N
Nodules1
Plant-1
Yield
(kg
BNF2
BNF2
Transfer
(%)
(%)
(kg
ha-1)
N
Transfer
Nodules1
(kg ha-1)
Plant-1
ha-1)
Yield
(kg
BNF2
BNF2
Transfer
(%)
(%)
(kg
ha-1)
Transfer
(kg ha-1)
ha-1)
Wheat-common bean cv. ‘Black Turtle’ combinations
BT Monoculture
5
101
49
-
50
-
8
149
60
-
89
-
Wheat:BT (1:1)
8
35
57
-7.6
20
-3.1
11
121
67
-1.1
81
-0.5
Wheat:BT (2:1)
7
23
57
-13.5
13
-6.5
15
128
62
-6.8
79
-3.3
Wheat-BT
7
24
51
-9.8
12
-4.2
13
91
58
-3.9
53
-1.7
SEM (±)
0.77
4.66
2.47
-
3.69
-
0.86
4.94
2.08
-
2.72
-
LSD0.05
2.19
13.3
7.02
-
10.5
-
2.45
14.1
5.91
-
7.74
-
(mixed)
103
Year 1
Year 2
Total
Treatments
N
Nodules1
Plant-1
Yield
(kg
Total
BNF2 Transfer
(%)
(%)
BNF2
(kg
N
Transfer Nodules1
(kg ha-1)
Plant-1
ha-1)
ha-1)
Yield
(kg
BNF2 Transfer
(%)
(%)
BNF2
(kg
Transfer
(kg ha-1)
ha-1)
ha-1)
Wheat-fava bean cv. ‘Bell’ combinations
Bell Monoculture
21
111
62
-
69
-
40
152
75
-
115
-
Wheat:Bell (1:1)
34
62
72
11.9
45
6.5
75
129
81
13.9
104
7.6
Wheat:Bell (2:1)
33
23
72
11.8
17
7.7
78
75
89
11.2
67
8.0
Wheat-Bell
33
30
75
10.8
23
4.9
66
75
87
10.9
65
5.1
SEM (±)
1.74
4.35
2.18
-
3.17
-
3.67
4.48
3.02
-
3.96
-
LSD0.05
4.95
12.4
6.21
-
9.01
-
10.4
12.7
8.59
-
11.3
-
(mixed)
150
days after sowing; 2BNF = Biological Nitrogen Fixation; RK = Red Kidney; BT = Black Turtle; SEM = Standard Error of the
Mean; and LSD = Least Significant Difference
104
Table 4.7 Organic carbon and nitrogen yield from grain and shoot biomass in monocultures and wheat-bean intercrop
combinations during 2011-12 at UBC Farm, Vancouver, Canada.
Carbon Yield : 2011
Carbon Yield : 2012
Nitrogen Yield : 2011
Nitrogen Yield : 2012
(g C m-2 y-1)
(g C m-2 y-1)
(kg/h)
(kg/h)
Treatments
Grain
Shoot
Total Grain
Shoot
Total
Grain
Shoot
Total
Grain
Shoot
Total
Wheat-common bean cv. Red Kidney combinations
RK Monoculture
97
113
210
125
119
244
74
21
95
97
21
118
Wheat:RK (1:1)
135
153
288
154
154
308
64
13
77
111
18
129
Wheat:RK (2:1)
145
160
305
195
175
370
73
15
88
149
22
171
Wheat-RK (mixed)
131
148
279
143
142
285
69
14
83
100
15
115
Wheat Monoculture
142
170
312
128
169
297
58
12
70
53
12
65
SEM (±)
5.97
5.9
11.9
6.68
5.44
12.1
1.8
1.1
2.9
10.7
0.96
11.7
LSD0.05
17.0
16.9
33.9
19.0
15.5
34.5
5.1
3.1
8.2
30.6
2.73
33.4
Wheat-common bean cv. Black Turtle combinations
BT Monoculture
119
90
209
163
123
286
82
19
101
124
25
149
Wheat:BT (1:1)
147
151
298
153
147
300
79
16
95
123
19
142
Wheat:BT (2:1)
154
167
321
175
179
354
75
17
92
132
23
155
105
Carbon Yield : 2011
Carbon Yield : 2012
Nitrogen Yield : 2011
Nitrogen Yield : 2012
(g C m-2 y-1)
(g C m-2 y-1)
(kg/h)
(kg/h)
Treatments
Grain
Shoot
Total Grain
Shoot
Total
Grain
Shoot
Total
Grain
Shoot
Total
Wheat-BT (mixed)
143
152
295
113
154
267
72
15
87
91
23
114
Wheat Monoculture
142
170
312
128
169
297
58
12
70
53
12
65
SEM (±)
4.49
9.82
14.3
8.85
6.7
15.5
3.9
0.9
4.8
11.1
0.75
11.8
LSD0.05
12.8
27.9
40.7
25.2
19.1
44.2
11.1
2.5
13.6
31.5
2.13
33.7
Wheat-fava bean cv. Bell combinations
Bell Monoculture
91
81
172
115
129
244
88
23
111
115
37
152
Wheat:Bell (1:1)
184
200
384
182
227
409
104
27
131
130
42
172
Wheat:Bell (2:1)
175
191
366
166
200
366
84
20
104
105
26
131
Wheat-Bell (mixed)
133
145
278
128
196
324
67
16
83
79
35
114
Wheat Monoculture
142
170
312
127
169
296
58
12
70
53
12
65
SEM (±)
12.3
15.7
28.0
5.8
10.6
16.4
5.8
1.3
7.1
8.4
2.43
10.8
LSD0.05
35.1
44.6
79.7
16.4
30.2
46.6
16.5
3.6
20.2
23.8
6.91
30.8
RK = Red Kidney; BT = Black Turtle; SEM = Standard Error of the Mean; and LSD = Least Significant Difference
106
Table 4.8 Daytime† averages of net ecosystem CO2 exchange, ecosystem respiration, gross ecosystem photosynthesis and net
ecosystem productivity in monocultures and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada.
Year : 2011
Treatments
NEEa
Reb
GEPc
(µmol CO2 (µmol CO2 (µmol CO2
m-2 s-1)
m-2 s-1)
m-2 s-1)
Year : 2012
NEPd
NEEa
Re b
GEPc
NEPd
(mg C
(µmol CO2
(µmol CO2
(µmol CO2
(mg C
m-2 hr-1)
m-2 s-1)
m-2 s-1)
m-2 s-1)
m-2 hr-1)
Wheat-common bean cv. ‘Red Kidney’ combinations
RK Monoculture
-4.67
4.90
9.57
202
-5.17
4.60
9.77
223
Wheat:RK (1:1)
-3.15
4.47
7.62
136
-3.65
4.17
7.82
158
Wheat:RK (2:1)
-4.47
4.84
9.31
193
-4.97
4.54
9.51
214
Wheat-RK (mixed)
-2.64
4.73
7.37
114
-3.14
4.43
7.57
136
Wheat Monoculture
-4.67
4.49
9.16
202
-4.37
4.19
8.56
189
SEM (±)
0.21
0.27
0.47
12.5
0.54
0.24
0.45
15.9
LSD0.05
0.59
NS
1.35
35.6
1.54
NS
1.28
45.2
107
Year : 2011
Treatments
NEEa
Reb
GEPc
(µmol CO2 (µmol CO2 (µmol CO2
m-2 s-1)
m-2 s-1)
m-2 s-1)
Year : 2012
NEPd
NEEa
Re b
GEPc
NEPd
(mg C
(µmol CO2
(µmol CO2
(µmol CO2
(mg C
m-2 hr-1)
m-2 s-1)
m-2 s-1)
m-2 s-1)
m-2 hr-1)
Wheat-common bean cv. ‘Black Turtle’ combinations
BT Monoculture
-4.09
4.72
8.81
177
-4.59
4.42
9.01
198
Wheat:BT (1:1)
-2.34
3.88
6.22
101
-2.84
3.58
6.42
123
Wheat:BT (2:1)
-2.68
4.51
7.19
116
-3.18
4.21
7.39
137
Wheat-BT (mixed)
-1.89
4.52
6.41
82
-2.39
4.22
6.61
103
Wheat Monoculture
-4.67
4.49
9.16
202
-4.37
4.19
8.56
189
SEM (±)
0.23
0.27
0.44
16.3
0.6
0.28
0.49
17.4
LSD0.05
0.65
NS
1.26
46.4
1.71
NS
1.39
49.5
4.48
7.79
143
Wheat-fava bean cv. ‘Bell’ combinations
Bell Monoculture
-3.01
4.78
7.79
130
-3.31
108
Year : 2011
Treatments
NEEa
Reb
GEPc
(µmol CO2 (µmol CO2 (µmol CO2
NEPd
NEEa
Re b
GEPc
NEPd
(mg C
(µmol CO2
(µmol CO2
(µmol CO2
(mg C
m-2 hr-1)
m-2 s-1)
m-2 s-1)
m-2 s-1)
m-2 hr-1)
m-2 s-1)
m-2 s-1)
Wheat:Bell (1:1)
-4.68
4.06
8.74
202
-4.98
3.76
8.74
215
Wheat:Bell (2:1)
-4.50
3.88
8.38
194
-4.80
3.58
8.38
207
Wheat-Bell (mixed)
-3.25
4.09
7.34
140
-3.55
3.79
7.34
153
Wheat Monoculture
-4.67
4.49
9.16
202
-4.37
4.19
8.56
189
SEM (±)
0.17
0.28
0.32
12.7
0.46
0.29
0.47
17.8
LSD0.05
0.50
NS
0.91
36.1
1.31
NS
1.34
50.6
†Averages
m-2 s-1)
Year : 2012
of 25, 50 and 75 days after seeding; 1Net ecosystem CO2 exchange (NEE); 2Ecosystem respiration; 3Gross ecosystem
photosynthesis also referred to as gross primary productivity of the cropland; 4Net ecosystem productivity; RK = Red Kidney;
BT = Black Turtle; SEM = Standard Error of the Mean; and LSD = Least Significant Difference
109
Table 4.9 δ13C values in plant shoot tissue in monocultures and wheat-bean intercrop combinations during 2011-12 at UBC
Farm, Vancouver, Canada.
Year : 2011
Year : 2012
Treatments
δ13C Legume
δ13C Wheat
δ13C Legume
δ13C Wheat
Wheat-common bean cv. ‘Red Kidney’ combinations
Red Kidney Monoculture
-28.22
Wheat:Red Kidney (1:1)
-28.97
-29.64
-28.06
-28.73
Wheat:Red Kidney (2:1)
-27.71
-29.36
-26.81
-28.45
Wheat-Red Kidney (mixed)
-27.83
-29.59
-26.92
-28.68
Wheat Monoculture
-27.31
-29.95
-30.26
SEM (±)
0.21
0.23
0.18
0.24
LSD0.05
0.59
0.65
0.51
0.68
Wheat-common bean cv. ‘Black Turtle’ combinations
Black Turtle Monoculture
-27.57
-27.66
Wheat:Black Turtle (1:1)
-26.62
-30.12
-26.71
-29.69
Wheat:Black Turtle (2:1)
-26.85
-29.93
-26.94
-29.82
110
Year : 2011
Year : 2012
Treatments
Wheat-Black Turtle (mixed)
δ13C Legume
δ13C Wheat
δ13C Legume
δ13C Wheat
-26.16
-30.17
-26.25
-29.96
Wheat Monoculture
-29.95
-30.26
SEM (±)
0.21
0.19
0.19
0.20
LSD0.05
0.59
NS
0.54
0.58
Wheat-fava bean cv. ‘Bell’ combinations
Bell Monoculture
-28.37
Wheat:Bell (1:1)
-28.79
-29.31
-27.88
-28.40
Wheat:Bell (2:1)
-28.74
-29.36
-27.83
-28.45
Wheat-Bell (mixed)
-29.27
-29.48
-28.36
-28.57
Wheat Monoculture
-27.46
-29.95
-30.26
SEM (±)
0.19
0.18
0.19
0.20
LSD0.05
0.54
0.51
0.54
0.58
RK = Red Kidney; BT = Black Turtle; SEM = Standard Error of the Mean; and LSD = Least Significant Difference
111
Table 4.10 Crop on crop and crop on weed competition in wheat-bean intercrop combinations.
Crop on Crop Competitions1
Treatments
Wheat-RK
Wheat-BT Wheat-Bell
Weed Infestation Scores2
Wheat-RK
30 DAS
Wheat-BT
Wheat-Bell
70 DAS
30 DAS
70 DAS
30 DAS
70 DAS
Year 2011
Cereal:legume (1:1)
2-1
2-1
1-1
7
7
8
8
5
4
Cereal:legume (2:1)
2-1
2-1
1-1
8
7
8
8
4
4
Mixed Cropping
1-1
2-1
1-1
7
6
8
7
5
4
Year 2012
Cereal:legume (1:1)
1-2
1-2
1-1
6
4
8
7
4
3
Cereal:legume (2:1)
1-2
1-2
1-1
6
4
8
8
4
3
Mixed Cropping
1-2
1-2
1-1
6
3
8
7
3
4
Monoculture - Wheat
7
4
8
8
5
4
Monoculture - Legumes
6
4
6
6
4
3
11-1
no competition; 1-2: beans dominate wheat; 2-1: wheat dominates beans; 2 0 = no weed, and 10 = highly infested; RK =
Red Kidney; BT = Black Turtle; and DAS = days after sowing
112
S
W
E
N
T3
T2
T4
T1
T5
T1
T2
T4
T3
T5
T3
T1
T5
T4
T2
T1
T5
T3
T2
T4
T5
T4
T3
T1
T2
T4
T2
T3
T1
T5
T2
T4
T1
T5
T3
T2
T3
T5
T4
T1
T1
T5
T2
T3
T4
T5
T3
T2
T4
T1
T3
T5
T1
T2
T4
T2
T4
T1
T5
T3
Wheat-common bean cv. ‘Red Kidney’ plots
Wheat-common bean cv. ‘Black Turtle’ plots
Wheat-fava bean cv. ‘Bell’ plots
Figure 4.1 Field layout and treatment composition in completely randomized block design.
T1 indicates monocultured legumes, T2 indicates wheat and legumes in rows of 1:1; T3 indicates wheat and legumes in rows of
2 wheat:1 legume; T4 indicates broadcast planting arrangements; and T5 indicates monocultured wheat plots
113
5
Yield (t/ha)
4
2.6
2.3
3
1.9
1.9
2
1
1.8
2.1
3.1
1.9
2.2
3.2
3.3
2.6
1.5
1.7
1.8
1.3
1.8
2.5
1.2
1.8
0.9
0.9
0
Treatments
Bean
Wheat
Figure 4.2 Grain yield of wheat and bean components in monocultures and intercrop
combinations.
RK, BT and Bell are bean cultivars
114
GEP (µmol CO2 m-2 s-1)
4.3a. wheat-common bean cv. 'Red Kidney'combinations
15
12.69
12.40
10
9.67
5
11.59
9.80
6.65
5.66
8.89
7.73
9.10
8.87
8.47
6.72
6.14
5.05
0
RK Mono
(1:1)
(2:1)
(mixed)
Wheat Mono
Planting Arrangements
GEP (µmol CO2 m-2 s-1)
25 DAS
50 DAS
75 DAS
4.3b. wheat-common bean cv. 'Black Turtle' combinations
15
10
5
11.59
11.53
9.02
7.66
8.91
6.29
4.98
6.32
5.54
7.91
8.87
7.28
5.11
6.51
6.14
0
BT Mono
(1:1)
(2:1)
(mixed)
Wheat Mono
Planting Arrangements
25 DAS
50 DAS
75 DAS
GEP (µmol CO2 m-2 s-1)
4.3c. Wheat-fava bean cv. 'Bell' combinations
15
10.17
11.25
11.59
10.86
8.87
10
5
7.79
5.41
8.74
6.22
8.71
5.56
5.81
7.34
8.87
6.14
0
Bell Mono
(1:1)
(2:1)
(mixed)
Wheat Mono
Planting Arrangements
25 DAS
50 DAS
75 DAS
Figure 4.3 Daytime average gross ecosystem photosynthesis (µmol CO2 m-2 s-1) in
monocultures and wheat-bean intercrop combinations during 25, 50 and 75 days after
sowing.
115
NEP (µmol CO2 m-2 s-1)
4.4a. wheat-common bean cv. 'Red Kidney'combinations
7.13
8
6.73
6
4.93
4
2
6.55
3.74
4.92
4.72
3.40
2.71
1.87
0
RK Mono
(1:1)
2.71
4.52
2.04
(2:1)
2.89
(mixed)
2.49
Wheat Mono
Planting Arrangements
NEP (µmol CO2 m-2 s-1)
25 DAS
50 DAS
75 DAS
4.4b. wheat-common bean cv. 'Black Turtle' combinations
8
6
3.76
4
2
0
6.55
6.29
4.24
3.10
4.52
4.34
2.39
1.43
BT Mono
2.59
(1:1)
1.61
2.93
1.18
(2:1)
2.14
(mixed)
2.49
Wheat Mono
Planting Arrangements
NEP (µmol CO2 m-2 s-1)
25 DAS
50 DAS
75 DAS
4.4c. Wheat-fava bean cv. 'Bell' combinations
6.99
8
6
4.58
4.48
4
2
0
6.55
6.29
4.83
1.74
3.16
Bell Mono
4.65
3.01
2.66
(1:1)
(2:1)
2.32
3.40
(mixed)
4.52
2.49
Wheat Mono
Planting Arrangements
25 DAS
50 DAS
75 DAS
Figure 4.4 Daytime average net ecosystem productivity (µmol CO2 m-2 s-1) in monocultures
and wheat-bean intercrop combinations during 25, 50 and 75 days after sowing.
116
CHAPTER 5: BARLEY-PEA INTERCROPPING
 A version of this chapter has been published in Field Crops Research as Chapagain, T. and
A. Riseman (2014), Barley-Pea Intercropping: Effects on Land Productivity, Carbon and
Nitrogen Transformations (DOI: 10.1016/j.fcr.2014.06.014).
This study was conducted at the Centre for Sustainable Food Systems at UBC Farm in
Vancouver, BC, during 2011 and 2012 cropping season (May to September) to observe the
effects of the proportion of barley and pea genotype and their spatial configurations on
crop performance, land productivity, biological N fixation and transfer, gross ecosystem
photosynthesis (GEP), and net ecosystem productivity (NEP) within an organic production
system. The experimental site is located at 49° 15' 3" N and 123° 14' 20" W, at an altitude
of 100 m above mean sea level. Research was conducted under natural climatic conditions
using organic production practices.
5.1 Materials and Methods
5. 1.1 Climate description of the study area
Climatic data for the experimental site during the spring-summer seasons (May to
September) of 2011 and 2012 have been presented in Table 4.1 of the previous section
(please refer to 4.1.1).
5.1.2 Soil and site description
Soil in the experimental field was a Duric Humo-Ferric Podzol according to the Canadian
system of soil classification (AAFC, 1998) whereas it was a Haplorthod in the American
system (USDA-SCS, 1992). Four random soil samples from across the whole test site were
117
collected from 0-15 cm depth at the time of plot establishment to characterize soil fertility
(i.e., pH, organic matter, total N, δ15N, and available P, K, Ca, Mg, Cu, Zn, Fe, Mn and B). The
soil was moderately well drained coarse textured sandy loam with low to moderate
fertility. Soil was homogeneous with a pH value of 5.9, organic matter content of 117 g kg -1,
total N content of 3.5 g kg-1, δ15N of 3.02 ‰, P of 144 mg kg-1, and K of 183 mg kg-1 based on
dry soil. Additional soil samples were taken from two different areas within each plot
before planting (Spring-2011) and after final harvest (Fall-2012), and sent to an analytical
laboratory (Pacific Soil Analysis Inc., Richmond, Canada) to determine soil mineral N (NH 4+
and NO3-) content. The site had not been used for grain production in previous years but
had been used for annual vegetable cultivation. The site had been managed under organic
vegetable production guidelines for more than the 10 years using green manures and
compost.
5.1.3 Experimental details
Barley cv. ‘Oxbridge’ and pea cv. ‘Reward’ were selected for intercropping trials based on
agronomic performance (i.e., synchronized maturity for combined harvest, yield, protein
content and nodulation potential in pea) from cultivar evaluation trials (Chapagain and
Riseman, 2012). Plants were grown on the same plots under organic and rain-fed
conditions over two years of study, and managed equally across combinations.
Research plots (4m x 3m) were arranged in a randomized complete block design (RCBD)
with five treatments and four replications (Figure 5.1). Treatments consisted of barley cv.
‘Oxbridge’ and pea cv. ‘Reward’ grown as monocultures, and intercropped in rows of 1:1, 2
barley : 1 pea, and broadcast (Appendix I). In monocultures, barley and pea were planted in
118
rows at the recommended plant density targeting 400 and 60 viable plants m-2,
respectively. Row and mixed intercropping consisted of planting barley and pea in
proportional replacement design in which the combined density of the population varied as
the proportions of the species changed (Jolliffe, 2000). The 1:1 arrangement consisted of
planting barley and pea in alternate rows targeting 200 and 30 plants m-2, respectively,
whereas, 2:1 arrangement targeted 300 barley and 20 pea plants m-2. In broadcast
arrangement, seeding densities of barley and pea were reduced by one half of monoculture
densities targeting 200 and 30 plants m-2, respectively, and broadcasted and incorporated
evenly into the soil. Barley grown as a monoculture was considered the non-N2-fixing
reference plant in analyses. There was a gap at least 50 cm wide between plots to minimize
treatment interactions, and 1 meter wide gap between blocks to facilitate management.
Pea seeds were inoculated with commercial rhizobia (Garden Inoculant for pea, EMD Crop
Bioscience, WI, USA) and planted immediately after inoculation. Barley and pea were sown
in mid-May (15-16 May) in rows using a hand seeder (Jang Clean Hand Seeder, Jang
Automation Co. Ltd., Cheongju-city, South Korea) with adjustable sprockets (Front: 11,
Rear: 14), and seed plates (G-12 for barley and N-6 for pea). Sowing depth varied with seed
size and ranged from 3-4 cm for barley and 4-5 cm for pea. No fertilizers, pesticides or
fungicides were used.
5.1.4 Data collection and analysis
Plant-based parameters: Data were recorded for plant height (from soil surface to the tip of
apical leaf), number of effective tillers (spikes) m-2, days to harvest, number of nodules (in
pea), pod or spike length, seed number, grain yield (t ha-1), 1000 seed weight, and harvest
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index [HI, defined as a ratio of economic yield (grain yield) to the total above ground
biomass (grain yield + shoot biomass)]. Chlorophyll concentration index (CCI) was
measured using a handheld chlorophyll meter (Model CCM 200 Plus, Opti-Sciences Inc.,
New Hampshire, USA) on the flag leaf and the 3rd leaf prior to the flowering (50 DAS).
Nodulation was assessed by counting and inspecting the nodules of 3 randomly selected
pea plants in both monoculture and intercrop plots prior-to-flowering (i.e., 50 days after
sowing) following a procedure similar to Chapagain and Riseman (2012). Spike or pod
color was a determinant of maturity and considered ready for harvest when they were
straw-colored and 80% of the grains of the spike were in the hard-dough stage.
Plants in the middle section of each plot, leaving two rows on either side, were harvested at
maturity for yield measurements. Sub-samples were collected from two different 1 m2
areas within each plot, and averaged. Shoots of pea and non-N2-fixing barley reference
plants were harvested by hand leaving 5 cm tall stubble, oven dried at 70°C for 72 hours,
and threshed separately by a stationary thresher. Individual crop yield (grain and shoot
biomass) was calculated to permit comparison of yields, land equivalent ratios (LER) and N
contents with those when they were grown alone.
Relative and total intercrop productivity: System productivity was estimated using the Land
Equivalent Ratio (LER) which compares the yield obtained by intercropping two or more
species together with yields obtained by growing the same crops as monocultures. The LER
for two intercrop species in proportional replacement design were calculated as follows
(Mead and Willey, 1980):
LER = intercrop yieldbarley/mono yieldbarley + intercrop yieldpea/mono yieldpea
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The yields of mono and intercrop species were calculated as t ha-1.
Intercropped plots with LER values greater than 1.0 produced a yield advantage while plots
with values less than 1.0 showed a yield disadvantage. Grain yield was expressed at 12.5%
moisture. LER in terms of total plant mass (grain + shoot biomass) production was also
determined. Intercrop productivity was also assessed in terms of Total Land Output (TLO,
Jolliffe and Wanjau, 1999) as follows:
TLO = barley yield + pea yield
Intercrop plots with greater TLO values compared to monoculture showed a yield
advantage.
Tissue N, C, 15N and 13C analyses: Plant tissue samples for N and C analyses were prepared
from the shoots (i.e., leaves and stem) and grains separately of both nodulated pea and
non-fixing barley plants harvested at maturity while samples for 15N and 13C analyses were
prepared from all aboveground biomass harvested at pod or grain filling stages in pea and
barley, respectively. Samples were dried at 70oC for 72 hours and subsequently
homogenized into fine powder (<6 mm) using a 115 V Wig-L-Bug grinding mill
(International Crystal Laboratories, Garfield, NJ, USA). The subsamples, 2-3 mg each, were
then weighed into tin capsules using a Mettler AT20 micro-balance (Toledo, OH), and
analyzed for total N, C, δ15N and δ13C by high-temperature flash combustion using an
elemental analyzer (Vario EL Cube elemental analyzer, Elementar Analysensysteme GmbH,
Hanau, Germany) coupled by continuous flow to an isotope ratio mass spectrometer
(Isoprime isotope ratio mass spectrometer, Isoprime Ltd., Cheadle, UK).
121
The percentage of plant N derived from atmospheric N2 (% NDFA), based on the natural
variation in the abundance of 15N, was calculated according to Shearer and Kohl (1988):
% NDFA = 100 x (δ15Nref − δ15Nleg) / (δ15Nref − δ15Nfix)
where δ15Nref is the δ15N value for the non-fixing barley reference plant grown alone and
dependent on soil N; δ15Nleg is the δ15N value for the nodulating and potentially N2-fixing
pea grown in intercrop plots where fixed N and soil N are available as N sources; and δ15Nfix
is the δ15N value for the nodulating pea plant when they are totally dependent on biological
nitrogen fixation as the N source.
In addition, the quantification of N transferred to the companion barley plant was
determined by using the following formula (He, 2002):
% N transfer = 100 x (δ15N barley mono - δ15N barley intercrop) / δ15N barley mono
where δ15N barley
mono
is the δ15N value for the barley when they are grown alone and
dependent on soil N, and δ15N barley
intercrop
is the δ15N value for the companion barley
plants grown in intercrop plots. The estimates of N transfer are performed using treatment
averages.
In order to get the δ15Nfix value for pea, it was grown in plant boxes filled with quartz sand,
and supplied with N-deficient media and commercial rhizobia (Garden Inoculant for pea,
EMD Crop Bioscience, WI, USA) as inoculum. The medium was prepared following the
modified version of Mae and Ohira (1981) and contained: 50 mM Fe-EDTA, 50 mM KCl
(MW 74.55), 0.5M K2SO4 (MW 174.26), 1M KH2PO4 (MW 136.09), 0.5 M MgSO4·7H2O
(246.49), 1M CaCl2 (MW 110.98) as macroelements; and 0.5 mM CuSO4·5H2O (MW 249.7),
25 mM H3BO3 (MW 61.84), 2 mM ZnSO4·7H2O (MW 287.55), 2 mM MnSO4·H2O (MW
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169.01), and 0.5 mM Na2MoO4·2H2O (MW 241.9) as microelements. The macro and
microelement solutions were prepared separately with distilled water, and then poured at
5-10 ml per day into plant boxes each containing 4 plants.
Grain nitrogen values were converted to crude protein levels as %N x 6.25 for pea, and %N
x 5.8 for barley (Jones, 1931). Total N and C yields were derived by using grain and shoot
biomass yield, and N and C content in grain and shoot biomass in each crop component.
Gross ecosystem photosynthesis, ecosystem respiration and net ecosystem productivity
measurements: Field measurements of net ecosystem CO2 exchange (NEE) in cropland (i.e.,
monoculture and intercrop plots) and ecosystem respiration (Re) were conducted at the
soil surface using a dynamic closed automated chamber connected to a portable CO2 gas
analyzer by following a procedure similar to that of Jassal et al. (2010). The automated
chamber consisted of a PVC cylinder that was equipped with a calibrated photosensor
(RainWise Quantum Solar Sensor, RainWise Inc., Bar Harbor, ME, USA) for the
measurement of photosynthetically active radiation (PAR), an ordinary axial fan to ensure
uniform CO2 concentration in the chamber, and outlet vent tube of 15 cm long and 3 mm
internal diameter to prevent pressure differences between the chamber and the
atmosphere. The cylinder dimensions were 19.5 cm internal diameter, 60.8 cm height, and
1 cm wall thickness. The chamber effective volume when deployed was 20.34 dm3 while
the surface area covered by the chamber was 0.0298 m2. The cylinder was inserted to a
depth of about 2 cm below the soil surface during field measurements.
The CO2 gas analyzer unit consisted of an infrared gas analyzer (IRGA) (model LI-820, LICOR Inc., Lincoln, NE), a 21X data logger (model 21X, Campbell Scientific Inc. (CSI), Logan,
123
UT, USA), an AC linear pump (model SPP-40GBLS-101, GAST Manufacturing Corp., Benton
Harbor, MI, USA), and a data storage module (SM192, CSI.). The IRGA was calibrated in the
UBC Biometeorology and Soil Physics Laboratory with cylinders of CO2 in dry air calibrated
using standards provided by the Canadian Greenhouse Gases Measurement Laboratory,
Meteorological Service of Canada, Downsview, Ontario. The effective volume was assumed
to be approximately 12% higher than the geometric headspace volume, due to the nearsurface soil porosity and the adsorption of CO2 on the soil surface and chamber walls
(Jassal et al., 2010; 2012).
NEE in a cropland was measured from two different areas within each plot by placing the
chamber on the soil surface three times a day (i.e., morning, afternoon and evening) at 25,
50 and 75 days after sowing enclosing the plants (Appendix J). This was followed by the
measurement of Re by placing the chamber on bare soil plus plant roots after harvesting.
When measuring NEE and Re, the pump was turned on 1 minute before chamber placement
on the soil surface and continued for 3 minutes. The IRGA and the axial fan in the cylinder
were kept on between measurements. The time rate of change in the CO2 mole fraction in
the chamber headspace (dC/dt, µmol mol-1 s-1) during a period of 90 seconds beginning 20
seconds after chamber closure, which was found to be linear, was used to calculate the flux,
F (µmol m-2 s-1) as follows (Jassal et al., 2005):
F=
where P is the atmospheric pressure (Pa), R is the universal gas constant (8.314 J mol-1 K-1),
T is the temperature of the chamber air (K), V is the geometric volume of the chamber
headspace (0.02034 m3), A is the surface area covered by the chamber (0.0298 m2), and a is
124
the ratio of the effective volume to the geometric volume of the chamber (i.e., 1.12). Since
the rate of increase in relative humidity in the chamber was less than 2% minute -1 over the
90 seconds, the water vapour dilution effect was estimated to be less than 1% of F, and was
therefore neglected (Welles, 2001).
Gross ecosystem photosynthesis - GEP (i.e., Re minus NEE), often referred to as gross
primary productivity of the cropland, and net ecosystem productivity - NEP (i.e., NEE with
a negative sign, often referred to as seasonal net carbon sequestration) were calculated for
all planting arrangements. The micromole values of NEP were converted to mg C m-2 hr-1
using a conversion factor of 43.2 (Jassal et al., 2005). When NEE is positive, the ecosystem
is releasing C to the atmosphere while when negative, the ecosystem is absorbing C from
the atmosphere.
Crop management parameters: General observations were made 30 and 70 days after
sowing on the type, number and the amount of weeds present, and insect pest and disease
pressures with regard to type and nature of damage. Disease of economic importance e.g.,
Scald or Leaf Blotch (Rhynchosporium secalis), Stem/Leaf/Stripe/Yellow/Brown Rust
(Puccinia spp.), and Septoria Leaf Spot or Glume Blotch (Septoria tritici) were monitored
and noted over the course of the season as suggested by Chapagain and Riseman (2012).
Data analysis: Data were analyzed using MSTAT-C (MSU, 1993) and MATLAB (MathworksMATLAB and Simulink for Technical Computing, Natick, MA, USA). Analyses of variance
were performed on individual plot data for plant performance metrics, yields, and C and N
accumulation. Fisher’s least significant differences were calculated with 5% significance
levels in MSTAT-C using the error variance from the analysis. Simple correlation
125
coefficients and coefficients of determination were determined between selected
parameters using Statistical Package for the Social Sciences (SPSS) software.
5.2 Results
5.2.1 Soil mineral nitrogen and δ15N content
Soil mineral N (NH4+ and NO3-) values from samples collected before planting and after
final harvest are presented (Table 5.1). Pre-plant plots were homogenous and deemed
suitable for 15N natural abundance studies as suggested by Shearer and Kohl (1988). After
harvest, plots varied in their N content. Specifically, monoculture pea plots displayed the
highest increase in mineral N (i.e., +0.6 mg NH4+ and +6.4 mg NO3- kg-1 dry soil) whereas
barley monoculture plots displayed the greatest decrease (i.e., -0.8 mg NH4+ and -4.4 mg
NO3- kg-1 dry soil) (Table 5.1). Intercrop plots displayed intermediate N values with the
greatest net increase of about +0.1 mg NH4+ and +0.7 mg NO3- kg-1 dry soil from the 1:1
plots.
The average δ15N value of nodulating pea grown in N-free media was -1.08 ‰ while the
non-fixing barley reference plants grown in field as monoculture had average δ15N value of
2.38 ‰ (data not shown). There was sufficiently a large difference between soil δ15N (3.02
‰) and atmospheric δ15N (0 ‰) in order to measure dilution effects as suggested by
Shearer and Kohl (1988).
5.2.2 Plant performance indices
Grain yield, land equivalency ratio (LER), and total land output (TLO), under monoculture
and intercrop arrangements, are presented (Table 5.2). In monoculture plots, pea yield
increased from 5.1 t ha-1 in year 1 to 5.4 t ha-1 in year 2 resulting in a two-year average of
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5.3 t ha-1. However, barley yield declined over the 2 years from 4.3 t ha-1 in year 1 to 3.6 t
ha-1 in year 2 with an average of 4 t ha-1. System productivity indices, TLO and LER, were
generally higher in intercrop plots with productivity increasing between 12-32%
compared to monoculture plots. The 2:1 arrangement produced the greatest increase
(32%) and highest individual year and two-year average for LER values (1.48 and 1.32,
respectively) with the same occurring for TLO values (6.53 t ha-1 and 5.9 t ha-1,
respectively) (Table 5.2). The TLO and LER values calculated using total biomass
production (i.e., all above ground tissue) displayed similar trends as when calculated with
grain yield, with a 28% increase in land productivity from the 2:1 arrangement (Table 5.3).
Pea in intercrop plots displayed significantly higher harvest index (HI) and increased C:N
ratio compared to monoculture plots with the highest values from the 2:1 arrangement
(Table 5.4). Intercropped pea displayed up to a 24% higher C:N ratio compared to
monoculture plots due to reduced biomass N in intercrops. Pea grain protein, on the other
hand, was not significantly affected by intercropping. Pea performance in intercrop and
monoculture plots improved significantly in years 2 as compared with year 1, with
increased plant biomass, longer and more plentiful pods, greater grain yield and total
biomass.
Barley in intercrop plots showed notable responses for chlorophyll concentration indexCCI, biomass C:N ratio and grain protein compared to monoculture plots (Table 5.4). Barley
displayed the highest biomass N (thus lowering C:N ratio) and grain protein percentage
when planted in the 1:1 arrangement. Unlike pea, the performance of barley declined over
the two years in both monocultured and intercropped plots, with lower 1000 seed weight,
lower HI, and lower yield across all arrangements (Table 5.2, Appendix C).
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5.2.3 Biological N2 fixation and transfer
Intercropping had a significant impact on nodulation, percent N derived from symbiotic
fixation and N transfer to the companion barley plants (Table 5.5). The number of nodules
and the proportion of nitrogen fixed by pea were significantly higher in intercrop plots as
compared to monoculture pea plots. Pea in intercrop plots developed an average of 2745% more nodules than in monoculture plots resulting in 9-17% more N derived from
symbiotic N2 fixation. On average, the 1:1 arrangement generated the highest percent of
biologically fixed N2 (72%) and the highest rate of N-transfer to barley (11%) compared to
N transfer in the 2:1 arrangement (4%) and the mixed planting arrangement (2%).
Pea in the 1:1 arrangement displayed the highest amount of aboveground biomass N
(average of 108 kg ha-1) compared to other planting arrangements of which 78 kg (72%)
was derived from symbiotic N2 fixation. Nitrogen fixation and transfer occurred within a
season and improved significantly in year 2 as compared with year 1 (Table 5.5). Pea in the
1:1 arrangement fixed an average of 69% of total biomass N in year 1 to 76% in year 2, and
transferred an average of 6% of N in barley biomass in year 1 to 16% in year 2 (Table 5.5).
5.2.4 Biomass N and C accumulation
Monocultured pea accumulated the greatest N in biomass followed by all intercrop
arrangements with the monocultured barley accumulating the least. Pea monoculture
accumulated an average of 54 kg N ha-1 (Table 5.6) in shoot biomass of which 30 kg was
derived from symbiotic N fixation. Pea in intercrop plots displayed reduced biomass N and
a decrease in total N accumulation due to reduced total biomass. However, this amount still
reduced the N requirement of the subsequent crop by 14-22 kg ha-1 (Table 5.6).
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Compared to monoculture barley, the total amount of shoot biomass N accumulated in
intercrop plots was 122-202% higher (Table 5.6). Barley in intercrop plots displayed
increased biomass N compared to barley monoculture. However, the total amount of N
accumulated by the barley component decreased slightly with increasing pea density
(Table 5.6). Barley-pea in 1:1 arrangement accumulated the highest N in aboveground
biomass (grain plus shoot biomass) (160 kg N ha-1) followed by 159 kg N ha-1 in the 2:1
arrangement.
Barley and pea grown in 2:1 arrangements accumulated 53% more carbon (196 g C m-2 yr1)
in shoot biomass compared to the monoculture barley plots (128 g C m-2 yr-1) (Table 5.7).
The 1:1 and mixed arrangements also accumulated more C in shoots than the monoculture
barley plots with 48% and 36% higher C, respectively. However, the greatest amount of C
accumulated in shoot biomass was from the monoculture pea plots (232 g C m-2 yr-1) while
the least was accumulated in the barley monoculture plots. In addition, the total biomass C
produced (i.e., grain plus shoot biomass) was highest in the 2:1 plots (442 g C m -2 y-1, i.e.,
50% higher than monocultured barley (Table 5.7). In peas, strong correlations were
observed between the amount of organic C and grain yield (r2=0.98) and harvest height
(r2=0.90) (Appendix G). Also, a significant correlation was identified between biomass N
and biomass C in pea (r2=0.99), and barley (r2=0.66) (Appendix H).
5.2.5 Net ecosystem CO2 exchange, ecosystem respiration, gross ecosystem
photosynthesis and net ecosystem productivity
Daytime averages of NEE, Re, GEP and NEP in monoculture and intercrop plots are
presented (Table 5.8) with NEE, GEP and NEP varying by spatial arrangement. The greatest
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GEP values were observed during the mid-growth stage (50 days after seeding i.e., just
prior to flowering, Figure 5.2) in all planting arrangements.
Cropped areas averaged 148%-224% more CO2 fixation (i.e., greater GEP) than CO2 loss
(i.e., Re) from bare soil plus plant roots with the highest GEP from the 2:1 arrangement. The
2:1 arrangement also displayed the greatest NEP resulting in the sequestration of the most
C with a seasonal average rate of 229 mg C m-2 hr-1 (i.e., 10% higher than barley
monoculture plots).
Mixed crop arrangements, on the other hand, displayed the least NEP (Figure 5.3) leading
to the lowest C sequestration compared to all other combinations (Table 5.8). Pea in
intercrop plots fixed less CO2 than monocultured pea. However, the proportion of CO2 fixed
by the barley component was higher in row intercrop plots than monocultured barley (data
not shown).
5.2.6 Crop competition, weed and disease pressure
The most common weeds in either monoculture or intercrop plots were common
chickweed (Stellaria media L.), green smartweed (Polygonum lapathifolium L.), prostrate
knotweed (Polygonum aviculare L.), pigweed (Amaranthus spp.), crab grass (Digitaria spp.),
barnyard grass (Echinochloa crusgalli L.), black nightshade (Solanum nigrum L.), and field
horsetail (Equisetum arvense L.). Pigweed was observed early in the season along with
chickweed. Common chickweed, an excellent colonizer that forms a succulent mat on the
soil surface, was the predominant weed from mid to late season. All crop plots grew well
with 3 manual weedings, 15, 30 and 45 days after sowing. In general, total weed biomass
was greater in barley and pea monoculture plots during early to mid-season compared
130
with late-season (Table 5.9). Weed biomass in intercrop plots was reduced as barley
density increased.
In general, the occurrence of barley disease was low over the two production years. When
present, the most prevalent diseases included stem rusts (Puccinia spp.) and Septoria leaf
blotch (Septoria spp.). No significant differences were observed among treatments
regarding the occurrence or the extent of disease. Septoria leaf blotch infection was most
severe early in the season whereas stripe and stem rusts were most severe mid to late
season.
Higher biomass of pea suppressed reproductive growth of barley resulting into fewer filled
grains, lower 1000 seed weight and HI of barley components when they were planted in
1:1 arrangement compared to all other planting arrangements (Table 5.9, Appendix C).
5.3 Discussion
Our organically managed intercropping trials showed several benefits of pairing barley and
pea including greater land productivity (12-32% higher compared to monocultured
barley), higher biomass quality (increased N and protein content), higher C and N
accumulation in aboveground biomass, and greater GEP and NEP. Higher yields and greater
land productivity are reported when barley is intercropped with pea. However, the degree
of success varied greatly with the growing conditions and the proportion of species used in
the field (Hauggaard-Nielsen et al., 2009; Jensen, 1996; Lauk and Lauk, 2008). Our
experiment indicated that increasing barley density in intercrops (i.e., 2:1 arrangement)
yielded higher productivity (32%) than 1:1 or broadcast arrangements. Barley:pea in 1:1
and broadcast arrangements performed poorly due to pea shading the barley plants
131
resulting in a higher proportion of unfilled grains. Lauk and Lauk (2008) reported that
increasing pea density in intercrops led to smaller grains and lower yields. Chen et al.
(2004) reported that intercropping barley and winter pea (Pisum sativum sp. arvense)
yielded 5-24% higher LER values based on biomass, and indicated that separate row
arrangements were more advantageous than growing each species in separate fields.
Similarly, Hauggaard-Nielsen et al. (2009) found 25-30% more grain yield in barley-pea
intercrops due to better use of plant resources including water, light, and nutrients. Sahota
and Malhi (2012) also reported that barley-pea intercrops required 7-17% less land than
monoculture production to produce the same yield.
The proportion of pea in the mixture affects the cereal’s yield and quality. Barley in our
experiment displayed increased biomass N and grain protein content with increasing pea
density and is perhaps related to more N available from the pea component and/or greater
soil N uptake due to increased competition. Lauk and Lauk (2008) also showed a positive
association of pea density with increased protein content of the cereal grain. Intercropping
cereals with crops that increase the protein content of the forage has both nutritional and
financial value (Lithourgidis et al., 2011). This was true for our experiment and other
barley-pea combinations (Carr et al., 2004).
Intercropping with a legume offers an opportunity for low input organic systems to better
use N complementarity without compromising yield. This study demonstrated that pea
fixed 9-18% more N in intercrop plots perhaps in response to the increased competition
with barley plants for soil N and promoting pea’s greater reliance on symbiotic N2-fixation.
Hauggaard-Nielsen et al. (2009) reported that pea-barley intercrops used nitrogen sources
17 to 31% more efficiently than by the monoculture plots. They further suggest that this
132
could in part be due to the increased acquisition of soil mineral N by the barley component
which promoted pea to rely more on internal N2-fixation. Izaurralde et al. (1992) also
reported increased N yield, greater N-fixation efficiency, and more shoot and root residueN mineralization for subsequent crops when field pea and barley were intercropped.
Biological nitrogen fixation by pea can supplement or replace the nitrogen requirement of
the subsequent crop. This is especially true under low soil N conditions (Fujita et al., 1992;
Lunnan, 1989). Our results showed that intercropping can increase soil N pools by 22-30
kg ha-1 through shoot biomass, and be available for use by the subsequent crop.
Furthermore, the highest rate of N-transfer (up to 8.6 kg N ha-1, i.e., 16% N in barley) from
pea was observed in the 1:1 arrangement compared to the 2:1 or mixed planting
arrangement. This further shows that N transfer occurred within a season at a greater rate
from higher pea density plots in row arrangements (1:1), perhaps due to physical colocation of the root systems that facilitate more direct N transfer between species. The
benefits of legume-based intercrop have been shown through direct plant-to-plant N
transfer but with significant variation reported in the amount of N transferred, i.e., ≤5 to
20% of the N in the receiver plants (He et al., 2003; 2009; Johansen and Jensen, 1996).
Only limited information is available regarding NEE, GEP and NEP from temperate cereallegume intercrop systems, with no reports specifically for barley and pea combinations.
When a legume and non-legume species are planted together in an intercropping system,
the legume might positively affect the performance of the non-legume species through
increased N availability in the system (Hartwig et al., 2002; Zanetti et al., 1997), and
therefore may support greater overall ecosystem productivity. Our 2:1 arrangement fixed
the greatest amount of CO2 (i.e., greatest GEP) and sequestered higher C in soil (i.e., greatest
133
NEP) compared to the 1:1, mixed or barley monoculture plots. Ecosystem respiration rates
across all treatments were not affected by plot composition and were comparable with the
values reported by Jassal et al. (2005) for our geographic zone (i.e., Vancouver, BC region).
Dyer et al. (2012) also reported an increase in soil organic carbon (SOC) concentration and
a lowering of GHG emission rates compared to when either crop was grown as a
monoculture. Overall, the specific intercrop combination of barley and pea may provide a
new opportunity to better manage nutrients in a small grain production system, one that
fulfills both economic and environmental interests through higher land productivity,
improved grain and biomass quality, increased GEP and NEP, and reduced reliance on
mineral fertilizer inputs.
5.4 Conclusions
Our trials on barley-pea intercrop arrangements revealed significant and positive
responses for higher total land outputs (TLO) and land equivalent ratios (LER), thereby
increasing land productivity compared to monoculture counterparts. Biomass and grain
nitrogen content of the barley component increased significantly with a higher pea density
(i.e., 1:1 arrangement) while the total amount of N accumulated by pea decreased with
increasing barley density (i.e., in 2:1 arrangement) due to a reduction in pea biomass.
Intercropping was associated with increased nodulation, percent N derived from symbiotic
N2 fixation, N and C accumulation in aboveground biomass, soil mineral N balance, and
greater NEP thereby sequestering C with a seasonal daytime average rate of 229 mg C m-2
hr-1 (i.e., 10% higher than barley monoculture plots). This study demonstrated that
intercropping barley and pea is an efficient strategy to achieve higher land productivity, N
and C yields, and higher C sequestration than when barley was grown as a monoculture,
134
and that increased leaf chlorophyll concentration coupled with greater availability of N and
CO2 fixation were associated with higher NEP and yields. Also, planting barley and pea in
rows of 2:1 appeared to be the most productive arrangement compared to other
combinations.
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Table 5.1 Soil mineral nitrogen (NH4+ and NO3-; mg kg -1 dry soil) before planting (Spring2011) and after final harvest (Fall-2012) in monocultures and intercrop plots.
Before Planting
After Final Harvest
Mean Difference
(BP)
(AH)
(AH-BP)
Treatments
NH4+
NO3-
NH4+
NO3-
NH4+
NO3-
Pea Monoculture
3.3
27.0
3.9
33.4
0.6
6.4
Barley:Pea (1:1)
3.2
25.7
3.3
26.4
0.1
0.7
Barley:Pea (2:1)
3.2
25.2
3.0
25.4
-0.2
0.2
Barley-Pea (mixed)
3.2
25.0
3.0
25.4
-0.2
0.4
Barley Monoculture
3.0
26.0
2.2
21.6
-0.8
-4.4
SEM (±)
0.10
0.69
0.18
1.03
0.08
0.34
LSD0.05
NS
NS
0.51
2.93
0.23
0.97
SEM = Standard Error of the Mean; and LSD = Least Significant Difference
136
Table 5.2 Grain yields, land productivity, biomass C:N and grain protein from monoculture
and intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada.
Grain Yield
Grain Yield
ha-1):
ha-1):
(t
TLO2
Y1
(t
Pea
Barley
Pea
Barley
Y1
Y2
Y1
Y2
Pea Monoculture
5.14
-
5.41
-
1.00
1.00
5.15
5.41
Barley:Pea (1:1)
1.87
3.06
3.10
2.37
1.07
1.23
4.93
5.47
Barley:Pea (2:1)
1.57
3.65
3.57
2.96
1.15
1.48
5.22
6.53
Barley-Pea (mixed)
1.82
3.17
2.78
2.35
1.09
1.16
4.99
5.13
Barley Monoculture
-
4.31
-
3.61
1.00
1.00
4.31
3.61
SEM (±)
0.45
0.18
0.34
0.23
0.06
0.08
0.14
0.29
LSD0.05
1.28
0.51
0.97
0.65
NS
0.23
0.40
0.83
Treatments
1Land
Y2
LER1
Equivalent Ratio (Mead and Willey, 1980); 2Total Land Output (Jolliffe and Wanjau,
1999); Y1 = year 1; Y2 = year 2; SEM = Standard Error of the Mean; and LSD = Least
Significant Difference
137
Table 5.3 Total biomass (grain plus shoot biomass) yields, land equivalency ratios and
total land output values from monocultures and intercrop plots during 2011-12
at UBC Farm, Vancouver, Canada.
Treatments
Total Biomass
Total Biomass
Yield (t ha-1):
Yield (t ha-1):
Y1
Y2
LER1
TLO2
Pea
Barley
Pea
Barley
Y1
Y2
Y1
Y2
Pea Monoculture
11.02
-
10.13
-
1.00
1.00
11.02
10.13
Barley:Pea (1:1)
3.82
5.28
5.34
4.74
1.07
1.25
9.10
10.08
Barley:Pea (2:1)
2.94
6.15
5.95
5.61
1.12
1.45
9.09
11.56
Barley-Pea (mixed)
3.27
5.44
4.61
4.65
1.05
1.17
8.71
9.26
Barley Monoculture
-
7.25
-
6.52
1.00
1.00
7.25
6.52
SEM (±)
1.11
0.26
0.72
0.25
0.05
0.07
0.38
0.47
LSD0.05
3.16
0.74
2.05
0.71
NS
0.20
1.08
1.34
1Land
Equivalent Ratio (Mead and Willey, 1980); 2Total Land Output (Jolliffe and Wanjau,
1999); Y1 = year 1; Y2 = year 2; SEM = Standard Error of the Mean; and LSD = Least
Significant Difference
138
Table 5.4 Harvest index, biomass C:N, chlorophyll concentration, and grain protein content
in monocultures and intercrop plots during 2011-12 at UBC Farm, Vancouver,
Canada.
Pea Performance
Treatments
HI1 (%)
Barley Performance
Biomass C:N
CCI2
Biomass C:N
Grain Protein (%)
Y1
Y2
Y1
Y2
Y1
Y2
Y1
Y2
Y1
Y2
Pea Monoculture
46.7
53.4
44.1
41.7
-
-
-
-
-
-
Barley:Pea (1:1)
48.9
58.2
42.5
42.1
14.7
13.3
104
107
9.0
9.3
Barley:Pea (2:1)
55.7
60.5
54.4
51.4
15.2
14.7
123
120
8.0
8.1
Barley-Pea (mixed)
53.3
60.3
49.7
52.9
14.4
13.8
115
113
8.2
8.2
Barley Monoculture
-
-
-
-
10.2
10.4
123
128
7.1
7.3
SEM (±)
1.12
1.03
1.83
1.68
0.89
0.72
2.76
2.40
0.26
0.31
LSD0.05
3.19
2.93
5.21
4.78
2.53
2.05
7.85
6.83
0.74
0.88
1Harvest
Index; 2Chlorophyll Concentration Index per 71mm2; Y1 = year 1; Y2 = year 2; SEM =
Standard Error of the Mean; and LSD = Least Significant Difference
139
Table 5.5 Nodule numbers, total N yield, biological nitrogen fixation and transfer by pea in
monoculture and intercrop plots during 2011-12 at UBC Farm, Vancouver,
Canada.
Treatments
Nodules
Total N Yield
BNF1
Transfer
BNF1
Transfer
Plant-1
(kg ha-1)
(%)
(%)
(kg ha-1)
(kg ha-1)
Year 1
Pea Monoculture
4
244
52
-
127
-
Barley:Pea (1:1)
5
85
69
5.6
59
2.9
Barley:Pea (2:1)
5
66
60
1.5
40
0.8
Barley-Pea (mixed)
6
74
55
0.3
41
0.2
SEM (±)
0.52
6.18
2.39
-
5.67
-
LSD0.05
1.48
17.6
6.80
-
16.1
-
144
-
Year 2
Pea Monoculture
7
248
58
Barley:Pea (1:1)
11
130
76
16.6
100
8.6
Barley:Pea (2:1)
9
141
68
6.3
96
3.5
Barley-Pea (mixed)
10
108
78
3.6
84
1.7
SEM (±)
0.69
7.56
3.12
-
6.43
-
LSD0.05
1.96
21.5
8.87
-
18.3
-
1Biological
Nitrogen Fixation; SEM = Standard Error of the Mean, and LSD = Least
Significant Difference
140
Table 5.6 Average nitrogen yield from grain and shoot biomass in monocultures and
intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada.
Treatments
Pea
Grain N
Shoot Biomass N
(kg ha-1)
(kg ha-1)
Barley
Total
Pea
192
54
Pea Monoculture
192
Barley:Pea (1:1)
86
43
129
22
Barley:Pea (2:1)
87
46
133
Barley-Pea (mixed)
77
39
116
47
47
Barley Monoculture
Barley
Total N Yield
Total
(kg ha-1)
54
246
9
31
160
16
10
26
159
14
9
23
139
10
10
57
SEM (±)
6.5
3.0
6.3
5.45
0.70
4.15
12.3
LSD0.05
18.6
8.6
17.9
15.5
NS
11.8
34.9
SEM = Standard Error of the Mean, and LSD = Least Significant Difference
141
Table 5.7 Average carbon yield from grain and shoot biomass in monocultures and
intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada.
Treatments
Pea
Grain C
Shoot Biomass C
(g C m-2 y-1)
(g C m-2 y-1)
Barley
Total
Pea
221
232
Pea Monoculture
221
Barley:Pea (1:1)
106
115
222
91
Barley:Pea (2:1)
108
139
247
Barley-Pea (mixed)
96
114
210
166
166
Barley Monoculture
Barley
Total C Yield
Total
(g C m-2 y-1)
232
453
100
190
412
83
113
196
443
72
102
174
384
128
128
294
SEM (±)
9.62
7.78
9.60
12.9
4.4
9.44
16.1
LSD0.05
27.4
22.1
27.3
36.7
12.6
26.8
45.8
SEM = Standard Error of the Mean, and LSD = Least Significant Difference
142
Table 5.8 Daytime† averages of net ecosystem CO2 exchange, ecosystem respiration, gross
ecosystem photosynthesis and net ecosystem productivity in monocultures and
intercrop plots during 2011-12 at UBC Farm, Vancouver, Canada.
Leaf Area (cm2)
Treatments
Legume Barley
NEE1
(µmol CO2
Re2
GEP3
(µmol
(µmol
CO2
CO2
m-2 s-1)
m-2 s-1)
NEP4
(mg C m-2
Plant -1
Tiller -1
m-2 s-1)
Pea Monoculture
957
-
-4.16
5.42
9.58
180
Barley:Pea (1:1)
515
60
-4.27
5.26
9.53
184
Barley:Pea (2:1)
729
81
-5.31
5.20
10.51
229
Barley-Pea (mixed)
436
68
-3.21
4.98
8.19
139
Barley Monoculture
-
65
-4.80
5.30
10.10
207
SEM (±)
67.6
2.5
0.23
0.30
0.63
27.6
LSD0.05
192.3
7.2
0.68
NE
1.79
78.5
†Averages
hr-1)
of 25 (PAR: 1404 µmol photons m-2 s-1, and inside chamber temperature 32.5oC),
50 (PAR: 1545 µmol photons m-2 s-1, and inside chamber temperature 34.6oC), and 75 (PAR:
1482 µmol photons m-2 s-1, and inside chamber temperature 32.3oC) days after seeding;
1Net
ecosystem CO2 exchange; 2Ecosystem respiration; 3Gross ecosystem photosynthesis
also referred to as gross primary productivity of the cropland; 4Net ecosystem productivity;
RK = Red Kidney; BT = Black Turtle; SEM = Standard Error of the Mean; and LSD = Least
Significant Difference
143
Table 5.9 Crop on crop and crop on weed competition in barley-pea intercrop
combinations during 2011-12 at UBC Farm, Vancouver, Canada.
Crop on Crop
Treatments
Weed Infestation Scoring2
Competitions1
Year 1
Year 2
Pea Monoculture
0
Barley:Pea (1:1)
Year 1
Year 2
30 DAS
70 DAS
30 DAS
70 DAS
0
7
2
6
2
1-2
1-2
5
4
4
4
Barley:Pea (2:1)
1-1
1-1
4
4
4
4
Barley-Pea (mixed)
1-1
1-1
4
3
3
2
Barley Monoculture
0
0
6
4
5
4
11-1
no competition; 1-2: legume dominates cereals; 20 = no weed, and 10 = highly infested;
and DAS = days after seeding
144
S
W
E
T1
T5
T4
T2
T3
N
T4
T2
T3
T5
T1
T3
T5
T1
T4
T2
T2
T1
T5
T3
T4
Figure 5.1 Field layout and treatment composition in completely randomized block design.
T1 indicates monocultured pea, T2 indicates barley and pea in rows of 1:1; T3 indicates
barley and pea in rows of 2 barley:1 pea; T4 indicates broadcast planting arrangements;
and T5 indicates monocultured barley plots
145
GEP (µmol CO2 m-2 s-1)
16
14
12
10
8
6
4
2
0
14.49
12.62
13.88
12.72
10.56
9.58
10.61
10.31
9.53
8.19
6.54
6.74
6.34
Pea Mono
(1:1)
5.82
(2:1)
5.81
(mixed)
Barley Mono
Planting Arrangements
25 DAS
50 DAS
75 DAS
Figure 5.2 Daytime average gross ecosystem photosynthesis (µmol CO2 m-2 s-1) in
monocultures and barley-pea intercrop plots during 25, 50 and 75 days after sowing.
NEP (µmol CO2 m-2 s-1)
10
7.70
8
6
5.70
4.65
5.31
4
2
6.96
6.18
2.61
3.21
2.93
2.35
1.77
0
Pea Mono
4.80
4.27
4.16
(1:1)
(2:1)
(mixed)
2.65
Barley Mono
Planting Arrangements
25 DAS
50 DAS
75 DAS
Figure 5.3 Daytime average net ecosystem productivity (µmol CO2 m-2 s-1) in monocultures
and barley-pea intercrop plots during 25, 50 and 75 days after sowing.
146
CHAPTER 6: CONCLUSIONS AND FUTURE NEEDS
This dissertation has investigated the performance of heirloom and commercial small grain
cultivars, wheat and barley root architectures, and the effects of species proportion and
spatial configuration in cereal-legume intercropping systems. The findings from the studies
have made several contributions to the current literature and have enhanced our
understanding in the following:

Cultivar trials demonstrated significant variation in plant performance and yield
among both heirloom wheat and barley cultivars with some heirloom wheat (i.e.,
‘Reward’, ‘Glenn’, ‘Cerebs’, ‘Sounders’ and ‘Red Bobs’) and barley (i.e., ‘Jet’) produced
comparable grain yields to the commercial cultivars. The heirloom wheat and barley
cultivars displayed greater resistance to stripe rust disease of which hulled wheat
and barley cultivars showed strong resistance compared to hulless type. Heirloom
wheat cultivars showed higher protein levels most desirable for baking and
blending purposes as compared to the commercial cultivars, with ‘Einkorn’
displaying the highest level (16.2%). The heirloom black-seeded barleys contained
higher protein levels most suitable for animal feed. The UK spring barleys (i.e.,
‘Oxbridge’, ‘Westminster’ and ‘Decanter’) contained lower protein levels most
suitable for malting purposes.

The coincidence in harvesting time (80-90 DAS) showed that barley can be
successfully integrated with pea and lentil for combined harvesting. Early wheat
cultivars (e.g., ‘Sounders’, ‘Reward’, ‘Snowstar’, and ‘Snowbird’) showed possibility
147
with late peas whereas late wheat appeared to be best suited to fava beans, kidney
beans, and soybeans.

The root architectures of the heirloom wheat and barley cultivars indicate they may
be better suited for low phosphorus and/or drought conditions, typical of low input
or organic production. The root architectures of the commercial cultivars, on the
other hand, were deemed more suitable for high input conditions. There exists a
positive association between root length, surface and yield potential when heirloom
wheat cultivars were grown under low input conditions. Longer and finer roots, and
the lower shoot:root ratio in some heirloom cultivars further suggest breeding
potential for improved nutrient uptake efficiency and drought tolerance in wheat
and barley.
Furthermore, two-year’s study on cereal-legume intercropping systems revealed
significant and positive responses for several plant performance metrics and overall
system productivity (Table 6.1). Intercropping displayed the highest total land outputs
(TLO) and land equivalent ratios (LER), thereby significantly increasing land productivity
(up to 50%) over monoculture counterparts. The experiment further demonstrated that:

Inter-plant N-transfer occurs within a growing season though the extent of transfer
varied between legume genotypes. This study also revealed that pairing genotypes
with similar root architectures that occupy the same root zone (e.g., wheat cv.
‘Scarlet’ and fava bean cv. ‘Bell’) transferred greater amounts of N (up to 13%) to
the companion wheat plants compared to other legume genotypes with dissimilar
148
Table 6.1 Summary of the effects of genotypes and spatial configurations on agronomic and ecosystem metrics over
monocultured plots.
Treatments
Cereal
Cereal
Biomass
Grain
C:N
Protein
%N-fixation
N-
by Legumes
transfer
Net
Water
Land
Total
Ecosystem
Use
Equivalent
Land
Productivity
Efficiency
Ratio
Outputs
Wheat-common bean cv. ‘Red Kidney’ combinations
Wheat:RK (1:1)
↓
↑
↑
Yes
↓
↑
ns
ns
Wheat:RK (2:1)
↓
↑
↑
Yes
↑
↑
↑
↑
Wheat-RK (mixed)
ns
ns
ns
Yes
↓
↑
ns
ns
Wheat-common bean cv. ‘Black Turtle’ combinations
Wheat:BT (1:1)
↓
↑
ns
No
↓
ns
ns
ns
Wheat:BT (2:1)
↓
↑
ns
No
↓
ns
ns
ns
Wheat-BT (mixed)
↓
↑
ns
No
↓
ns
ns
ns
Wheat-fava bean cv. ‘Bell’ combinations
Wheat:Bell (1:1)
↓
↑
↑
Yes
↑
↑
↑
↑
Wheat:Bell (2:1)
↓
↑
↑
Yes
↑
↑
↑
↑
Wheat-Bell (mixed)
ns
↑
↑
Yes
↓
↑
ns
ns
149
Treatments
Cereal
Cereal
Biomass
Grain
C:N
Protein
%N-fixation
N-
by Legumes
transfer
Net
Water
Land
Total
Ecosystem
Use
Equivalent
Land
Productivity
Efficiency
Ratio
Outputs
Barley-pea combinations
Barley:Pea (1:1)
↓
↑
↑
Yes
ns
ns
ns
↑
Barley:Pea (2:1)
↓
↑
↑
Yes
↑
ns
↑
↑
Barley-Pea (mixed)
↓
↑
↑
Yes
ns
ns
ns
↑
RK = Red Kidney; BT = Black Turtle; and ns = Not Significant
150
root architectures (e.g., wheat cv. ‘Scarlet’ and common bean cv. ‘Red Kidney’ or
‘Black Turtle’). Increase in N transfer in the second year could be due to combination
of within year and residual legume N inputs from the first year mineralizing and
becoming available to the wheat in the second year.

No significant effect of N transfer on ‘donor’ legume performance was observed in
intercrops. However, biomass N content in legumes was slightly reduced in
intercrop plots compared to monocultured legumes, perhaps related to the transfer
of N to the non-N2-fixing counterparts.

Significant variation was observed among the legume genotypes in terms of
biological N2 fixation and transfer to the companion wheat and barley plants. Fava
bean cv. ‘Bell’ fixed the greatest amount of atmospheric N (>80% of total plant N)
and transferred the greatest amount of biologically fixed N (13% of N in wheat
biomass) to the wheat counterpart.

The extent of N fixation and transfer was higher in high legume density plots (i.e.,
1:1 arrangement) compared to the 2:1 and broadcast arrangements. The difference,
however, was relatively small between the spatial arrangements.

Compared to the monocultured wheat and barley, the forage yield and quality of
intercrops improved. A positive association was observed between increased
legume densities and higher biomass and grain N content in the cereal component.
Therefore, cereals when intercropped with legumes displayed higher nutritional
value and were deemed more suitable as animal food and fodder.
151

Legume genotypes differed in their BNF contribution with the higher rate of N2
fixation and transfer in row intercrops. This led to the stimulation of CO2 fixation by
wheat and barley in intercrop plots leading to the greater amounts of carbon
assimilation and soil organic matter addition.

Wheat showed increased intrinsic water use efficiency (WUE) when grown with
either fava bean cv. ‘Bell’ or common bean cv. ‘Red Kidney’ perhaps related to
improved N nutrition that enhance photosynthesis relative to transpiration rate
leading to more water efficient grain and biomass production.

Cropland (both monoculture and intercrop plots) fixed the most CO2 during midgrowth stage (i.e., 50-60 days after seeding, just prior to flowering). Wheat-fava
bean cv. ‘Bell’ in the 1:1 arrangement displayed the greatest NEP sequestering C at a
seasonal daytime average rate of 208 mg C m-2 hr-1 (i.e., 7% higher than wheat
monoculture plots). Similarly, barley-pea in the 2:1 arrangement displayed the
greatest NEP with the sequestration of 229 mg C m-2 hr-1 (i.e., 10% higher than
barley monoculture plots).

Intercrop plots displayed both selection and complementary effects on the
performance of co-occurring species. Selection differences were observed for light
interception or radiation uptake, nitrogen fixation and transfer to the cereal
counterparts, and crop growth, yield and total biomass production in monoculture
and intercrop combinations. Wheat-fava and barley-pea combinations displayed
greater response due to their upright growth habit than wheat-common bean
combinations. Complementary effects were observed mainly on ecosystem
152
productivity metrics when the cereal component received more nitrogen from its
legume
counterpart
leading
to
the
greater
photosynthesis,
relative
to
transpiration, leading to more water efficient grain and biomass production.

Common bean cv. ‘Black Turtle’ did not transfer any N to the wheat component nor
improve NEP or WUE of the wheat in intercrop plots. Indeed, increased biomass of
common beans in Year 2 in intercrop plots suppressed wheat growth, grain filling,
1000 seed test weight, and harvest index leading to lower yield and LER values
compared to monocultured wheat. Similarly, pea when intercropped with barley in
the 1:1 arrangement also provided shading effects on barley resulting to fewer filled
grains, lower 1000 seed test weight, yield and LER than other planting
arrangements.
Overall, this research demonstrated that intercropping can be a viable option to increase
land productivity, to improve grain and biomass quality of non-N2-fixing cereals, to
increase N and C accumulation, NUE, GEP, NEP and WUE than monocultures under low soil
N and C conditions typical of organic systems. Furthermore, intercropping helps decrease
reliance on synthetic N-fertilizers, increase soil organic matter concentrations, and carbon
sequestration thereby improving soil health and environmental quality. The wheat-fava
bean cv. ‘Bell’ in the 1:1 and 2:1 arrangements, and barley-pea in the 2:1 arrangement
appeared to be the most productive combinations compared to monoculture and other
intercropping arrangements.
Future research/directions: This research revealed several advantages of cereal-legume
intercropping over monoculture systems in terms of land productivity, nitrogen and water
use efficiencies, carbon accumulation and NEP in organic system. However, a number of
153
limitations need to be addressed before the adoption and effective deployment of
intercropping to large agricultural production:

The contribution of legume genotypes may differ with the soil type, topography, and
growing environment. For example, acidic soils with limited phosphorus availability
may lessen N contribution in the system. Similarly, high soil N or mineral N-fertilizer
application is known to inhibit BNF. Therefore, it is important that we carry out
multiyear experiments in different locations using similar treatments to confirm
these results across a wider range of agro-climatic situations.

Another factor to consider while using organic intercropping is weed control during
early stage of crop establishment. Hand weeding practice might be practical in small
scale agriculture with plentiful labor, but would be difficult in medium to large
agricultural production.

For effective dissemination or adoption of intercropping technologies in medium to
large agricultural production, it is essential that wheat and barley are planted and
harvested together with beans and pea, respectively. This can be achieved only
when the combined planter and harvester are available making it suitable to
mechanized agricultural systems. In addition to the grain harvests, there is a
tremendous potential of increasing forage quality (i.e., quality of green fodder,
silage, etc.) by integrating legumes into the grass community.

Despite their tremendous contribution to improve soil fertility, legumes are often
not preferred by smallholder/resource-poor farmers compared to cereals, largely
attributed to their lack of short-term benefits (e.g., food and income). Furthermore,
most basic research on cereal-legume intercropping systems has little direct
154
involvement by farmers, particularly resource-poor farmers. Consequently, there is
lack of information and knowledge about the role of legume integration in the soil
fertility management among smallholder farmers. This situation needs to be
improved by conducting participatory intercropping trials in the farmer’s fields and
with their strong involvement.
155
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Appendix A Protocol adopted for N-determination in small grains using the Kjeldahl
method.
Reagents/ Chemicals Required

Conc. Sulfuric acid (H2SO4): 95-98%, nitrogen-free

Fisher’s Kjeltabs: Copper/Titanium tablets with 5.57 g K2SO4 + 0.0033g CuSO4 + 0.2
g TiO2

Sodium hydroxide (NaOH, 99.6-100.1%)
O.1 N NaOH = 4g NaOH/litre and titrate against standard acid (0.1N HCl, for
example) after adding 2-3 drops of phenolphthalein indicator to determine the
exact normality of prepared solution; and 32% NaOH= 32 g/100 ml or 960 g/3 litre.

Hydrochloric acid (HCl, 36.5-38%)
0.5 N HCl = 42 ml HCl/litre and titrate against standard base (0.1 N NaOH, for
example) after adding 2-3 drops of phenolphthalein indicator to determine the
exact normality of prepared solution.

De-ionized water: Prepare all reagents and dilutions in de-ionized water

Boiling chips (Fisher’s Bioleezers Granules, B365-250)

Methyl red indicator (Dissolve 0.1 g of bromocresol green and 0.02 g of methyl red
in 100 ml ethanol)
Apparatus Required

Usual lab equipment (weighing balance of 0.1 mg accuracy, beakers, petriplates,
etc.)

Kjeldahl digestion flasks (500-900 ml) or tubes
173

Digestion and distillation chamber

Burette (graduated in intervals of 0.01 ml or smaller), pipette, stand, etc.
Sample Preparation

Grind grain sample (homogeneous and dried at 60-65°C, moisture content 13.5%)
to <0.6mm size by a good sample blender. The particle size of the sample should
ideally be reduced to a size < 1 mm. The speed of the digestion will be improved
when small particle sizes are used.
Sample Weight

Weigh 1 g sample (Expected nitrogen content 1 to 3% in wheat and barley, thereby
contains 5 to 20% Protein) into a 900-ml Kjeldahl digestion flask. Use an analytical
balance accurate to 0.1 mg for weighing samples.
(Note: Reducing agent such as Sucrose (0.5 g) + Conc. H2SO4 (20 ml) will be added prior to
digestion to include Nitrogen in nitrate form and variation in total nitrogen content will be
observed than is achieved by using the normal (except reduction step) procedure).
Digestion

Add catalyst, 1 Kjeltabs (Copper/Titanium tablets with 5.57 g K2SO4 + 0.0033g
CuSO4 + 0.2 g TiO2).

Add 20 ml of Conc. H2SO4 into the digestion flask. Add boiling chips to prevent
bumping while heating or boiling the sample.

Load the digestion tubes and run digestion chamber (BUCHI Digest System K-431,
BUCHI Switzerland) for 2 hours (at 400°C)
174

After completion of the digestion step, allow the flask or tube for few hours to cool
down (or overnight) at room temperature.
(Using classical Kjeldahl apparatus, a general digestion procedure for routine use, requires
a minimum of 2 hours total digestion. With the improved sample to sample temperature
control, the “after boil” period is significantly reduced to 30-60 minutes. The term “boiling
time” can be divided in two parts. First, the time it takes until the digest has cleared or
become colourless, usually called “digestion time”. Next, the “after boil” time, to convert the
last part of the nitrogen into a form that can be distilled, usually called “boil period”. In
general, a “boiling time” two to three times the clearing time is usually sufficient to achieve
complete recovery)
Distillation

Add 75 ml of ammonia free water to the cooled acid digestion mixture. Dilution of
the digestion mixture before making it alkaline and distilling prevents or minimizes
caking and also reduces the likelihood of bumping.

Add NaOH (32% solution) to the diluted digestion mixture to make the total volume
up to 200 ml. The solution now becomes strongly alkaline (pH of >11)

Connect flask containing diluted mixture of digestion to the condenser and mixed
before heating and distillation begins. Additional boiling chips can be added just
before distillation to reduce bumping, especially towards the end of the distillation
as the solution becomes more concentrated.

Put 3-4 ml (Expected nitrogen content in sample 1.5 to 3%) of 0.5 N HCl in a
receiving flask and increase volume by adding de-ionized water (up to 75 ml or as
175
necessary) so that the tip of the delivery tube immersed into the solution. Add 2-3
drops of Indicator (Methyl red) and place the flask under condenser of the
distillation chamber (BUCHI Distillation Unit K-350, BUCHI Switzerland).

Distil for about 4 minutes. A distillation rate of about 25 ml/minute is adopted to
collect 75-100 ml of condensate.

Allow delivery tubes to drain momentarily into the receiving flask before removal
from the distillation apparatus. Rinse the end of the condenser before removal.
Titration
The ammonia is captured by a carefully measured excess of a standardized acid solution in
the receiving flask. That solution is neutralized by a carefully measured standardized
alkaline base solution such as sodium hydroxide (0.1 N NaOH). A color change is produced
at the end point of the titration.

Titrate the condensate with 0.1 N NaOH solution till orange color appeared
Calculations
The calculations for % nitrogen or % protein must take into account which type of
receiving solution was used and any dilution factors used during the distillation process. In
the equations below, “N” represents normality. “ml blank” refers to the milliliters of base
needed to back titrate a reagent blank if standard acid is the receiving solution, or refers to
milliliters of standard acid needed to titrate a reagent blank if boric acid is the receiving
solution. When standard acid is used as the receiving solution, the equation is:
% Nitrogen =
176
Appendix B Performance of wheat and bean components in monocultures and wheat-bean intercrop combinations.
Bean Performance
Treatments
Pods plant-1
CCI1
Y1
Wheat Performance
Harvest Index Spike Length
(#)
Y2
Y1
(%)
Y2
Y1
Seeds spike-1
Harvest Index
(#)
(%)
(cm)
Y2
Y1
Y2
Y1
Y2
Y1
Y2
Wheat-common bean cv. ‘Red Kidney’ combinations
RK Monoculture
18.5
17.8
9.9
7.9
47.0
54.3
-
-
-
-
-
-
Wheat:RK (1:1)
15.1
17.2
4.8
9.2
48.5
57.2
7.2
6.5
33.9
28.0
47.2
42.1
Wheat:RK (2:1)
14.3
18.2
5.1
10.9
50.7
59.2
7.6
7.5
36.1
34.1
48.4
46.0
Wheat-RK (mixed)
16.6
17.4
5.9
7.4
46.8
59.3
6.8
7.0
31.4
30.0
47.6
44.9
Wheat Monoculture
-
-
-
-
-
-
6.9
6.9
33.1
29.5
47.1
43.9
SEM (±)
1.05
0.94
1.37
1.53
1.36
1.48
0.26
0.36
2.41
1.78
1.17
1.41
LSD0.05
2.99
NS
3.89
NS
NS
4.21
NS
NS
NS
5.06
NS
NS
Wheat-common bean cv. ‘Black Turtle’ combinations
BT Monoculture
22.6
21.6
16.4
14.3
55.8
56.1
-
-
-
-
-
-
Wheat:BT (1:1)
11.6
22.3
8.3
19.2
59.4
53.7
7.3
7.6
35.4
32.5
48.3
38.9
Wheat:BT (2:1)
15.4
24.1
8.8
20.9
63.2
54.4
7.4
7.3
33.7
32.4
47.4
37.6
177
Bean Performance
Treatments
Pods plant-1
CCI1
Wheat Performance
Harvest Index Spike Length
(#)
(%)
Seeds spike-1
Harvest Index
(#)
(%)
(cm)
Y1
Y2
Y1
Y2
Y1
Y2
Y1
Y2
Y1
Y2
Y1
Y2
Wheat-BT (mixed)
13.0
21.2
7.3
14.1
61.9
48.5
7.1
7.3
34.4
31.4
48.3
37.9
Wheat Monoculture
-
-
-
-
-
-
6.9
7.0
33.1
29.5
47.1
43.9
SEM (±)
1.65
1.33
1.15
0.93
1.15
1.39
0.19
0.23
1.63
1.4
1.56
1.19
LSD0.05
4.69
NS
3.27
2.65
3.27
3.95
NS
NS
NS
NS
NS
3.39
Wheat-fava bean cv. ‘Bell’ combinations
Bell Monoculture
15.4
14.3
8.6
7.3
54.0
47.6
-
-
-
-
-
-
Wheat:Bell (1:1)
13.9
14.8
6.4
7.9
50.3
45.8
7.3
8.2
34.2
33.3
48.6
44.9
Wheat:Bell (2:1)
12.5
14.3
4.9
5.9
51.9
47.7
7.6
8.1
34.3
35.2
48.4
44.0
Wheat-Bell (mixed)
13.4
13.5
5.3
6.1
51.6
36.5
7.0
7.8
33.5
30.9
48.2
45.4
Wheat Monoculture
-
-
-
-
-
-
6.9
6.9
33.1
29.5
47.1
43.9
SEM (±)
1.04
0.92
0.54
0.63
1.85
1.81
0.21
0.34
1.05
1.76
1.37
1.27
LSD0.05
NS
NS
1.54
NS
NS
5.06
NS
0.97
NS
5.07
NS
NS
1Chlorophyll
Concentration Index (per 71mm2); Y1 = year 1; Y2 = year 2; RK = Red Kidney; BT = Black Turtle; SEM =
Standard Error of the Mean; and LSD = Least Significant Difference
178
Appendix C Performance of barley and pea components in monocultures and barley-pea intercrop combinations.
Pea Performance
Treatments
CCI1
Barley Performance
1000 Seed Weight
Grain Protein
(g)
(%)
1000 Seed
Weight
Harvest Index
(%)
(g)
Y1
Y2
Y1
Y2
Y1
Y2
Y1
Y2
Y1
Y2
Pea Monoculture
15.2
16.2
251
226
22.4
22.9
-
-
-
-
Barley:Pea (1:1)
16.7
16.4
243
248
21.6
21.6
48.1
41.8
57.9
50.0
Barley:Pea (2:1)
18.3
17.5
250
246
21.7
21.1
49.0
43.7
59.4
52.7
Barley-Pea (mixed)
16.0
16.2
243
243
21.1
20.7
49.8
40.5
58.3
50.5
Barley Monoculture
-
-
-
-
-
-
45.1
41.8
59.5
55.3
SEM (±)
0.59
0.64
3.99
3.94
0.52
0.82
1.79
1.18
0.95
1.38
LSD0.05
1.68
NS
NS
11.2
NS
NS
NS
NS
NS
3.91
1Chlorophyll
Concentration Index (per 71mm2); Y1 = year 1; Y2 = year 2; SEM = Standard Error of the Mean; and LSD = Least
Significant Difference
179
Appendix D Coefficients of determination (r2) between bean performance metrics in wheat-bean intercrop combinations.
Common bean cv. ‘Red Kidney’
Common bean cv. ‘Black Turtle’
NP
NS
GY
TW
HI
CCI
C:N
GP
BN
BC
CS
NP
NS
GY
TW
HI
CCI
C:N
GP
BN
BC
CS
HH
0.26
0.08
0.26
0.22
0.08
0.05
0.38
0.03
0.36
0.36
0.16
0.77
0.06
0.86
0.32
0.38
0.58
0.42
0.00
1.00
0.98
0.59
NP
-
0.34
0.92
0.15
0.01
0.10
0.48
0.37
0.98
0.98
0.50
-
0.21
0.90
0.56
0.32
0.61
0.27
0.08
0.96
0.96
0.66
NS
-
-
0.38
0.23
0.27
0.09
0.12
0.11
0.64
0.62
0.55
-
-
0.17
0.06
0.02
0.08
0.04
0.00
0.26
0.29
0.13
GY
-
-
-
0.10
0.00
0.13
0.48
0.52
1.00
1.00
0.62
-
-
-
0.45
0.42
0.52
0.45
0.03
1.00
1.00
0.58
TW
-
-
-
-
0.15
0.05
0.17
0.02
0.06
0.05
0.23
-
-
-
0.23
0.52
0.06
0.30
0.94
0.92
0.49
HI
-
-
-
-
-
0.25
0.06
0.04
0.27
0.28
0.02
-
-
-
-
-
0.34
0.17
0.01
0.81
0.84
0.14
CCI
-
-
-
-
-
-
0.09
0.18
0.59
0.61
0.00
-
-
-
-
-
-
0.14
0.08
0.86
0.82
0.45
C:N
-
-
-
-
-
-
-
0.19
0.70
0.72
0.23
-
-
-
-
-
-
-
0.14
0.79
0.76
0.07
GP
-
-
-
-
-
-
-
-
0.98
0.98
0.30
-
-
-
-
-
-
-
-
0.07
0.06
0.25
BN
-
-
-
-
-
-
-
-
-
0.98
0.66
-
-
-
-
-
-
-
-
-
0.98
1.00
BC
-
-
-
-
-
-
-
-
-
-
0.64
-
-
-
-
-
-
-
-
-
-
0.98
HH = Harvest Height; NP = Number of Pods plant-1; NS = Number of Seeds pod-1; GY = Grain Yield; TW = 1000 Seed Weight; HI = Harvest
Index; CCI = Chlorophyll Concentration Index; C:N = Carbon to Nitrogen Ratios; GP = Grain Protein; BN = Biomass Nitrogen; BC = Biomass
Carbon; and CS = Carbon Sequestration
180
Appendix E Coefficients of determination (r2) between wheat performance metrics in wheat-bean intercrop combinations.
Wheat-common bean cv. ‘Red Kidney’
Wheat-common bean cv. ‘Black Turtle’
SL
NS
GY
TW
HI
CCI
C:N
GP
BN
BC
CS
SL
NS
GY
TW
HI
CCI
C:N
GP
BN
BC
CS
HH
0.10
0.17
0.56
0.21
0.29
0.00
0.15
0.10
0.64
0.20
0.09
0.30
0.01
0.05
0.04
0.04
0.25
0.18
0.02
0.38
0.42
0.19
SL
-
0.74
0.00
0.03
0.04
0.00
0.03
0.09
0.25
0.00
0.23
-
0.36
0.01
0.04
0.04
0.01
0.01
0.00
0.62
0.19
0.00
NS
-
-
0.02
0.07
0.18
0.05
0.03
0.05
0.35
0.03
0.15
-
-
0.29
0.26
0.24
0.00
0.08
0.08
0.05
0.94
0.04
GY
-
-
-
0.14
0.10
0.06
0.01
0.30
0.94
0.94
0.28
-
-
-
0.06
0.00
0.00
0.03
0.05
0.04
0.98
0.16
TW
-
-
-
-
0.44
0.16
0.00
0.06
0.04
0.29
0.03
-
-
-
-
0.49
0.42
0.07
0.14
0.00
0.56
0.04
HI
-
-
-
-
-
0.04
0.12
0.02
0.00
0.27
0.00
-
-
-
-
-
0.26
0.58
0.62
0.06
0.96
0.00
CCI
-
-
-
-
-
-
0.10
0.04
0.45
0.73
0.20
-
-
-
-
-
-
0.18
0.00
0.00
0.88
0.02
C:N
-
-
-
-
-
-
-
0.30
0.01
0.14
0.05
-
-
-
-
-
-
-
0.42
0.14
0.68
0.19
GP
-
-
-
-
-
-
-
-
0.29
0.31
0.38
-
-
-
-
-
-
-
-
0.12
0.96
0.00
BN
-
-
-
-
-
-
-
-
-
0.77
0.92
-
-
-
-
-
-
-
-
-
0.04
0.00
BC
-
-
-
-
-
-
-
-
-
-
0.90
-
-
-
-
-
-
-
-
-
-
0.79
HH = Harvest Height; SL = Spike Length; NS = Number of Seeds pod-1; GY = Grain Yield; TW = 1000 Seed Weight; HI = Harvest Index; CCI =
Chlorophyll Concentration Index; C:N = Carbon to Nitrogen Ratios; GP = Grain Protein; BN = Biomass Nitrogen; BC = Biomass Carbon; and
CS = Carbon Sequestration
181
Appendix F Coefficients of determination (r2) between performance metrics in wheat-fava bean intercrop combinations.
Wheat Performance Metrics
Fava bean Performance Metrics
NP
NS
CCI
C:N
GY
TW
HI
GP
BN
BC
CS
SL
NS
CCI
C:N
GY
TW
HI
GP
BN
BC
CS
HH
0.19
0.28
0.03
0.04
0.11
0.32
0.19
0.34
0.04
0.05
0.00
0.05
0.03
0.04
0.00
0.06
0.19
0.01
0.41
0.13
0.16
0.01
NP
-
0.00
0.35
0.14
0.86
0.05
0.23
0.01
0.69
0.17
0.00
-
0.21
0.30
0.08
0.17
0.21
0.05
0.03
1.00
0.98
0.01
NS
-
-
0.00
0.00
0.00
0.34
0.11
0.22
0.46
0.02
0.05
-
-
0.05
0.03
0.04
0.01
0.00
0.00
0.06
0.05
0.00
CCI
-
-
-
0.06
0.41
0.02
0.01
0.06
0.58
0.82
0.00
-
-
-
0.13
0.04
0.05
0.08
0.00
0.58
0.52
0.12
C:N
-
-
-
-
0.11
0.02
0.01
0.00
0.39
0.00
0.23
-
-
-
-
0.01
0.27
0.40
0.32
0.38
0.33
0.10
GY
-
-
-
-
-
0.03
0.11
0.00
0.98
0.95
0.09
-
-
-
-
-
0.09
0.00
0.11
1.00
1.00
0.04
TW
-
-
-
-
-
-
0.32
0.08
0.34
0.00
0.00
-
-
-
-
-
-
0.12
0.02
0.16
0.12
0.00
HI
-
-
-
-
-
-
-
0.05
0.07
0.13
0.06
-
-
-
-
-
-
-
0.04
0.34
0.30
0.01
GP
-
-
-
-
-
-
-
-
0.55
0.74
0.12
-
-
-
-
-
-
-
-
0.39
0.37
0.45
BN
-
-
-
-
-
-
-
-
-
0.67
0.54
-
-
-
-
-
-
-
-
-
1.00
0.59
BC
-
-
-
-
-
-
-
-
-
0.48
-
-
-
-
-
-
-
-
-
-
0.53
HH = Harvest Height; NP = Number of Pods plant-1; NS = Number of Seeds pod-1; GY = Grain Yield; TW = 1000 Seed Weight; HI = Harvest
Index; CCI = Chlorophyll Concentration Index; C:N = Carbon to Nitrogen Ratios; GP = Grain Protein; SL = Spike Length; BN = Biomass
Nitrogen; BC = Biomass Carbon; and CS = Carbon Sequestration
182
Appendix G Coefficients of determination (r2) between pea performance metrics in barley-pea intercrop combinations.
NP
NS
GY
TW
HI
CCI
C:N
GP
NN
BNF
NT
PBN
BC
CS
HH
0.38
0.08
0.83
0.48
0.30
0.29
0.03
0.38
0.42
0.14
0.02
0.86
0.90
0.55
NP
-
0.04
0.21
0.15
0.12
0.06
0.14
0.16
0.40
0.00
0.00
0.35
0.37
0.14
NS
-
-
0.07
0.11
0.36
0.00
0.08
0.14
0.10
0.00
0.01
0.18
0.14
0.02
GY
-
-
-
0.19
0.45
0.23
0.14
0.24
0.42
0.14
0.10
0.98
0.98
0.40
TW
-
-
-
-
0.03
0.04
0.04
0.41
0.01
0.00
0.05
0.27
0.31
0.34
HI
-
-
-
-
-
0.01
0.16
0.10
0.25
0.00
0.06
0.67
0.62
0.15
CCI
-
-
-
-
-
-
0.06
0.02
0.27
0.17
0.00
0.29
0.34
0.05
C:N
-
-
-
-
-
-
-
0.09
0.09
0.01
0.00
0.34
0.28
0.00
GP
-
-
-
-
-
-
-
-
0.02
0.16
0.17
0.77
0.79
0.34
NN
-
-
-
-
-
-
-
-
-
0.05
0.01
0.86
0.88
0.01
BNF
-
-
-
-
-
-
-
-
-
-
0.71
0.35
0.38
0.05
NT
-
-
-
-
-
-
-
-
-
-
-
0.56
0.64
0.12
PBN
-
-
-
-
-
-
-
-
-
-
-
-
0.99
0.83
BC
-
-
-
-
-
-
-
-
-
-
-
-
-
0.88
HH = Harvest Height; NP = Number of Pods plant-1; NS = Number of Seeds pod-1; GY = Grain Yield; TW = 1000 Seed Weight; HI = Harvest
Index; CCI = Chlorophyll Concentration Index; C:N = Carbon to Nitrogen Ratios; GP = Grain Protein; NN = Number of Nodules; BNF =
Biological Nitrogen Fixation; NT = Nitrogen Transfer; PBN = Plant Biomass Nitrogen; BC = Biomass Carbon; and CS = Carbon
Sequestration
183
Appendix H Coefficients of determination (r2) between barley performance metrics in barley-pea intercrop combinations.
SL
NS
GY
TW
HI
CCI
C:N
GP
PBN
BC
CS
HH
0.07
0.05
0.07
0.35
0.13
0.32
0.01
0.05
0.56
0.38
0.02
SL
-
0.40
0.02
0.00
0.14
0.05
0.30
0.12
0.37
0.04
0.18
NS
-
-
0.03
0.15
0.50
0.00
0.31
0.05
0.07
0.05
0.24
GY
-
-
-
0.17
0.28
0.17
0.40
0.64
0.61
1.00
0.12
TW
-
-
-
-
0.35
0.50
0.04
0.09
0.96
0.71
0.20
HI
-
-
-
-
-
0.07
0.45
0.20
0.25
0.81
0.23
CCI
-
-
-
-
-
-
0.03
0.12
0.69
0.71
0.17
C:N
-
-
-
-
-
-
-
0.58
0.06
0.59
0.08
GP
-
-
-
-
-
-
-
-
0.32
0.85
0.18
PBN
-
-
-
-
-
-
-
-
-
0.66
0.00
BC
-
-
-
-
-
-
-
-
-
-
0.17
HH = Harvest Height; SL = Spike Length; NS = Number of Seeds pod-1; GY = Grain Yield; TW = 1000 Seed Weight; HI = Harvest Index; CCI =
Chlorophyll Concentration Index; C:N = Carbon to Nitrogen Ratios; GP = Grain Protein; PBN = Plant Biomass Nitrogen; BC = Biomass
Carbon; and CS = Carbon Sequestration
184
Appendix I Performance of cereals and legumes in monocultures and intercropping systems.
A. 20 days after sowing
Fava bean monoculture
Wheat monoculture
Wheat:fava bean (1:1)
Common bean monoculture
Wheat monoculture
Wheat:common bean (1:1)
Pea monoculture
Barley monoculture
Barley:pea (1:1)
Wheat:fava bean (2:1)
Wheat-fava bean (mixed)
Wheat:common bean (2:1) Wheat-common bean (mixed)
Barley:pea (2:1)
Barley-pea (mixed)
185
B. 40 days after sowing
Fava bean monoculture
Wheat monoculture
Wheat:fava bean (1:1)
Wheat:fava bean (2:1)
Wheat-fava bean (mixed)
Common bean monoculture
Wheat monoculture
Wheat:common bean (1:1)
Wheat:common bean (2:1)
Wheat-common bean (mixed)
Pea monoculture
Barley monoculture
Barley:pea (1:1)
Barley:pea (2:1)
Barley-pea (mixed)
186
C. 60 days after sowing
Fava bean monoculture
Wheat monoculture
Wheat:fava bean (1:1)
Common bean monoculture
Wheat monoculture
Wheat:common bean (1:1)
Pea monoculture
Barley monoculture
Barley:pea (1:1)
Wheat:fava bean (2:1)
Wheat-fava bean (mixed)
Wheat:common bean (2:1) Wheat-common bean (mixed)
Barley:pea (2:1)
Barley-pea (mixed)
187
D. 80 days after sowing
Fava bean monoculture
Wheat monoculture
Wheat:fava bean (1:1)
Common bean monoculture
Wheat monoculture
Wheat:common bean (1:1)
Pea monoculture
Barley monoculture
Barley:pea (1:1)
Wheat:fava bean (2:1)
Wheat-fava bean (mixed)
Wheat:common bean (2:1) Wheat-common bean (mixed)
Barley:pea (2:1)
Barley-pea (mixed)
188
E. 100 days after sowing
Fava bean monoculture
Wheat monoculture
Wheat:fava bean (1:1)
Common bean monoculture
Wheat monoculture
Wheat:common bean (1:1)
Pea monoculture
Barley monoculture
Barley:pea (1:1)
Wheat:fava bean (2:1)
Wheat-fava bean (mixed)
Wheat:common bean (2:1) Wheat-common bean (mixed)
Barley:pea (2:1)
Barley-pea (mixed)
189
Appendix J CO2 flux, leaf area and chlorophyll concentration index measurements in cereal-legume intercropping systems.
CO2 flux measurements using an automated chamber connected to the portable gas analyzer unit
Leaf area measurements
CCI measurements
190
Appendix K Root growth and nodulation in cereal and legume genotypes.
Commercial barley
Fava bean, 30 days after sowing
Heirloom barley
Fava bean, 60 days after sowing
Common bean cv. ‘Black Turtle’
Common bean, 60 days after sowing
191
Appendix L Types of cultivars based on the arrangement of spike-lets and seed characteristics.
2-row type
Hulled barley
6-row type
Awnless
Hulless barley
Black barley, a heirloom cultivar
192