STEWART ET AL.: PHENOLOGICAL TEMPERATURE RESPONSE OF MAIZE
of residue management on the number of volunteer
seedlings in fine fescue merit further investigation.
The total area allowed for open-field burning in Oregon will be reduced to only 16200 ha after 1997. In
western Oregon, perennial ryegrass and tall fescue seed
crops may be managed successfully by mechanical removal of the postharvest residue (Young et aI., 1998).
Results of the present study likewise indicate that in
Chewings fescue the mechanical removal of the straw
results in similar seed yields as with residue burning.
Therefore, a high priority should be given to red fescue
when allocating the acreage that is allowed for field
burning. In western Oregon, the majority of red fescue
is grown along the less densely populated eastern side
ofthe Willamette Valley, and the westerly winds usually
carry the smoke from open-field burning farther to the
east, where few people live. This would make the practice of open-field burning more acceptable for red fescue. However, to minimize smoke pollution, burning
regulations restrict the times when burning is allowed;
thus, field burning may not be done in a timely manner,
and research efforts should continue to look for alternatives to open-field burning. Alternating mechanical residue removal with burning by a mobile sanitizer in different years resulted in the same mean seed yields for
Chewings fescue as continuous burning (Young et aI.,
1984b). Comparing continuous open-field burning with
alternating burning for production of red fescue seed
merits further investigation.
REFERENCES
73
Chilcote, D.O. 1969. Burning boosts grass seed yields. Crops Soils
21(8):18.
Chilcote, D.O., and W.e. Young III. 1991. Grass seed production in
the absence of open-field burning. J. App!. Seed Prod. 9:33-37.
Chilcote, D.O., and H.W. Youngberg. 1975. Propane flamer burning
of grass seed field stubble. Progress Rep. Ext/ACS 8, Agric. Exp.
Stn. Oregon State Univ., Corvallis.
Chilcote, D.O., H.W. Youngberg, P.e. Stanwood, and S. Kim. 1980.
Post-harvest residue burning effects on perennial grass development and seed yield. p. 91-103. In P.O. Hebblethwaite (ed.) Proc.
Easter School in Agric. Sci., 28th, Univ. of Nottingham. 1978.
Butterworth, London.
Chilcote, D.O., H.W. Youngberg, and W.C. Young III. 1983. Postharvest residue burning as a management tool in grass-seed production. p. 254--257. In J.A. Smith and V.W. Hays (ed.) Proc. Int.
Grassl. Congr., 14th, Lexington, KY. 15-24 June 1981. Westview
Press, Boulder, CO.
Hare, M.D., and W.J. Archie. 1990. Red fescue seed production:
Post-harvest management, nitrogen and closing date. N.Z. Grassl.
Assoc. 52:81--85.
Pumphrey, F.Y. 1965. Residue management in Kentucky bluegrass
(Poa pratensis L.) and red fescue (Festuca rubra L.) seed fields.
Agron J. 57:559-561.
Young, W.e., III., B.M. Quebbeman, T.B. Silberstein, and D.O. Chilcote. 1994. An evaluation of equipment used by Willamette Valley
grass seed growers as a substitute for open-field burning. Ext/CrS
99. Dep. of Crop and Soil Sci., Oregon State Univ., Corvallis.
Young, W.C., III., H.W. Youngberg, and D.O. Chilcote. 1984a. Postharvest residue management effects on seed yield in perennial
grass seed production: I. The long-term effect from non-burning
techniques of grass seed residue removal. 1. Appl. Seed Prod.
2:36--40.
Young, W.e., III., H.W. Youngberg, and D.O. Chilcote. 1984b. Postharvest residue mana~ement effects on seed yield in perennial grass
seed production: II. The effect of less than annual burning when
alternated with mechanical residue removal. J. Appl. Seed Prod.
2:41--44.
Canode, C.L., and A.G. Law. 1978. Influence of fertilizer and residue
management on grass seed production. Agron. J. 70:543-546.
Phenological Temperature Response of Maize
Douglas W. Stewart,* Lianne M. Dwyer, and Lori L. Carrigan
ABSTRACT
Variability ofdevelopment rate estimates across locations and years
.... the CUlTent heat unit system of growing degree-days (GDD)
wlth maDmum and minimum temperature tbresholds of 30 and 10"C
(GDDlI,I') limits predictability of maturity in bybrid maize (Zea
""" L). Data sets of daily maximum and minimum air temperatures
... dates of maize denlopment stages were collected for a range of
IIJbrids at locations in Canada and the northem USA (39" to 4SO N lat).
DatIl were analyzed to impron the temperature response functions for
..ae at different stages of development. Results indicate tbat during
ftletltin growth, phenological response to mean daily air temperalire followed a sigmoidal c:urve beginning below SOC, with maximum
nIpOase to temperatures between 2S and 3O"C. During reproductive
pnrth, the temperature response function was nat from 0 to IrC
IIlII'OIe significantly omy witb mean daily air temperatures greater
...... this range. A general thermal index (GTI) based on these two
nIpODse functions improved estimation of maturity dates by 50%
0ftI' estimates made using GDDlO.1' (SE of6.7 d for GTI and 13.6 d for
GDDlI,Io In estimating time from planting to maturity). The greatest
-,ro,.ement using GTI occurred for the reproductive period (SE of
U d using GTI, compared with tl.l d using GDDlO.l0)' These results
..... that incorporating the temperature response function reported
II lids paper would impron prediction of maize development.
T
HE ACCURATE PREDICfION of maize development rate
in temperate regions is the basis of a thermal index
and thermal zonation. Development rate can be modified by several factors, such as photoperiod, soil moisture, solar radiation and fertility, but it is primarily affected by temperature (e.g., Baron et aI., 1975; Cross and
Zuber, 1972; Gilmore and Rogers, 1958; Hodges, 1991).
The effect of temperature on development rate has
been described using a thermal-time concept, such as
Abbreviations: CHU, crop heat units; Fr, temperature response function; GOD, growing degree days; GDD"l,Io, growing degree days with
temperature thresholds of 30 and lOoC; GTI, general thermal index;
TA, average daily airtemperature; TO/" average daily air temperature at
maximum value of FT ; TMAXL, maximum threshold air temperature;
TMINL, minimum threshold air temperature.
D.W. Stewart and L.M. Dwyer, Agric. & Agri-Food Canada, Eastern
Cereal & Oilseed Res. Clr., Ottawa, ON KIA OC6, Canada; L. Carrigan, Pioneer Hybrid Int., Plant Breeding Div., Willmar, MN 56201.
Contribution no. 961105 of the Eastern Cereal & Oilseed Res. Ctr.
Received 16 Jan. 1997. *Corresponding author ([email protected]).
Published in Agron. J. 90:73-79 (1998).
74
AGRONOMY JOURNAL. VOL. 90, JANUARY-FEBRUARY 1998
the growing degree day (GDD), which assumes that
phenological development is constant per degree of
temperature between a base temperature (TMINL) and
an upper threshold temperature (TMAXL), above and
below which the development rate is zero. The simplicity of the GDD and its improvement over a day counter
for prediction of development has led to its widespread
adoption, particularly for the vegetative period (planting to silking). Estimates of TMINL for the vegetative
period range from lOoC (Brown and Bootsma, 1993),
to SoC (Ritchie and Nesmith, 1991), to 6°C (Derieux and
Bonhomme, 1982a, for germplasm from 11 European
countries including the most northerly maize production
areas). Estimates ofTMAXL for the same period range
from 19 to 34°C (Ellis et a1., 1992; Ritchie and Nesmith,
1991; Tollenaar et aI., 1979).
Various nonlinear models have been developed to
describe the temperature response of developmental
processes. These include the crop heat unit (CHU),
which assumes that all stages of development are a quadratic function of TMAXL and a linear function of
TMINL (Brown and Bootsma, 1993), and methods of
Blacklow (1972) and Tollenaar et a1. (1979), which demonstrate a nonlinear response of maize seedling shoot
elongation and maize leaf appearance, respectively, to
thermal time. Bonhomme et a1. (1994) and Ellis et a1.
(1992) also developed nonlinear temperature response
functions to fit measured maize development during the
vegetative period.
The reproductive period (silking to physiological maturity), measured in days, is less variable than the vegetative period (Derieux and Bonhomme, 1982b); therefore, temperature response studies have focused on the
vegetative period (e.g., Bonhomme et a1., 1994). However, thermal-time concepts, such as the GDD and
CHU, have been less useful for the reproductive period,
because thermal time required for specific genotypes to
reach maturity has been found to vary with the thermal
environment (represented by mean daily air temperature) (Major et aI., 1983; Plett, 1992).
Our objective was to quantify maize temperature response during both vegetative and reproductive periods
for hybrids representing 75 to 115 d relative maturity
grown at locations from 39° to 48°N latitude and, based
on these fitted temperature response functions, present
a general thermal index to improve on the predictive
accuracy of existing thermal indices.
MATERIALS AND METHODS
Field measurements were obtained on 28 Pioneer maize
hybrids at 19 locations in the north-central and northeastern
USA and southern Ontario from 1992 to 1995 (Table 1). Hybrids used in this study were rated from 2400 to 3400 CHU, or
75 to 117 d relative maturity based on the Minnesota Relative
Rating System (Peterson and Hicks, 1973). Planting, silking
(50% of plants with silk), and maturity (50% of plants at 100%
milk line) dates were recorded based on observations taken
a minimum of three times weekly on the center rows of fourrow plots replicated four times. Daily maximum and minimum
air temperatures were measured at each location from planting
to maturity. Hybrid data were divided into four groups, based
on heat unit requirements (Table 2).
Tollenaar and Bruulsema (1988) reported on a growth room
experiment to measure the length of the grain filling period
for two hybrids under a range of temperature treatments. In
that study, plants were grown in 22.5-L pots filled with baked
montmorillonite throughout grain filling at 28/18, 21/15 and
Table 1. Site descriptions and maize hybrids in the 19·1ocatioD, 4-yr (1992-1995) data set.
Location
1. ClImIUton, MO
Z. Sbelbyville, IL
3. Champaign, IL
4. Macomb,IL
5. WindfaU, IN
6. York, NE
7. North Platte, NE
8. Princeton, IL
9. Johnston, IA
10. Marion, IA
11. Huron, SD
tz. J mesville, WI
13. Algoma, IA
14. Woodstock, ON
15. Ithaca, MI
16. Mankato, MN
17. Willmar, MN
18. Moorhead, MN
19. Grand Forks, ND
Geographic coordinates
39"22' N, 94°49' W
39"43' N, 89"6' W
39"59' N, 88°15' W
40"22' N, 9O"JO' W
40"22' N, SS056' W
40°51' N, 97"32' W
41"8' N, 100"47' W
41"22' N,89"24' W
41°40' N, 93°42' W
42"4' N, 92"34' W
42"22' N, 98"13' W
42°40' N, 88"55' W
43°4' N, 94°14' W
43°17' N, 80"51' W
43°18' N, 84°36' W
44"8' N, 94°1' W
45°14' N, 95"6' W
46°46' N, 99"33' W
48"14' N, 97"Z7' W
Hybrid name
3. Pioneer 3489
d
117
116
115
4. Pioneer 3514
5. Pioneer 3525
6. Pioneer 3531
111
110
1. Pioneer 3394
2. Pioneer 3417
7. Pioneer 3556
8.
9.
10.
11.
tz.
13.
14.
15.
16.
17.
18.
19.
20.
Zl.
22.
23.
24.
25.
Z6.
27.
:zs.
t MRMR, Minnesota relative maturity rating (Peterson and Hicks, 1973).
MRMRt
Pioneer 3563
Pioueer 3733
Pioneer 3751
Pioneer 3752
Pioneer 3769
Pioneer 3787
Pioneer 3790
Pioneer 3845
Pioneer 3861
Pioueer 3876
Pioneer 3893
Pioueer 3902
Pioneer 3905
Pioneer 3907
Pioneer 392.1
Pioneer 3947
Pioneer 3962
Pioueer .3963
Pioneer 3979
Pioneer 3982
Pioneer 3984
III
109
107
102
98
98
9lI
95
95
91
93
90
89
87
87
87
86
79
80
79
76
75
75
STEWART ET AL.: PHENOLOGICAL TEMPERATURE RESPONSE OF MAIZE
l6/1O° day/night temperatures, or at 28/18°C for 6 d followed
by 1412°C for the remainder of the filling period, or at 14/2°C
for 6 d followed by 281l8°C. Photoperiod was 16 h and light
intensity was 430 /-Lmo! m- 2 S-I at the top of the canopy. Due
to the limited height of the growth room, plants were trimmed
so that only two leaves remained above the ear. Development
and temperature data from this experiment were also analyzed.
Analysis
Growing degree days with maximum (TMAXL) and minimum (TMINL) temperature limits of 30 and 10°C, respectively
(i.e., ODDl(I,1(1) (Cross and Zuber, 1972; Gilmore and Rogers,
1(58). can be expressed as
GDD 3o.,o
"
=L
(n - 10) t:.t
[1]
j=1
where TX is the average of daily maximum (:5TMAXL) and
minimum (~TMINL) temperatures. The expression TX - 10
is the temperature response function in growing degree days
per day (or simply °C), and t:.{ is a time step in days. When
weather station data were used to calculate GDD, maximum
daily temperatures were set equal to TMAXL when they exceeded TMAXL, and minimum daily temperatures were set
equal to TMINL when they were less than TMINL For the
rare occasions when maximum temperatures were less than
TMINL, they were set to TMINL; when minimum temperatures exceeded TMAXL, they were set equal to TMAXL
Setting temperatures equal to maximum and minimum limits
W,IS proposed by Gilmore and Rogers (1958) to improve the
sensitivity of GDD to temperatures outside the threshold
limits.
To avoid temperature limits, a more general thermal index
(GTI, in°C) was described as
GTI =
L
Fr
t:.t
[2]
j=l
where FT is a temperature response function representing the
rale of phenological development in modified growing degree
days per day (or simply modified growing degrees at a given
average daily temperature), t:.{ is a time step in days, and n
is the number of days in a period (e.g., from planting to silking
or silking to maturity) for any location and year.
The general thermal index (GTI) was expressed as a cubic
polynomial temperature function (F r ):
Fr
=
n
Bo + B 1
+ B2
n
[3]
where TA is the average daily temperature and Bu, Bi> and B2
are empirical coefficients. In this application, it was assumed
that when TA = 0, the slope of F r is also zero. Thus, Eq. [3]
does not have a linear term and has one less coefficient than
the normal cubic polynomial. The GTI avoids confusion generated by temperature limits by being continuous from DOC and
fable 2. Characterization of four hybrid groups of maize, num·
bered from highest to lowest relative maturity ratings.
HIhrid
group
Hybrids
included
Location·
years
Mean thermal timet
Vegetath'e
no.
5
5
5
13
Reproductive
GOD",,,·,
146
115
69
109
748
710
651
595
669
631
588
525
t Grol\ing degree days with threshold limits of 30°C (maximum) and
llIoe (minimum).
75
using an average daily temperature (TA ). For weather station
data, this was the sum of the daily maximum and minimum
temperatures divided by two. For the growth room data, however, day and night temperatures replaced daily maximum
and minimum temperatures. Since a 16-h photoperiod was
used, a weighted average daily temperature was calculated
by multiplying the day temperature by 2, adding the night
temperature, and dividing by 3. This better represented the
square wave temperature pattern of the growth room than
did a simple average of the day and night temperatures. When
the night temperature was 2°C, it was set equal to TMINL
(10°C) to calculate GDD.
In order that GTI should have the same approximate numerical range as ODDJtl.l ro , average values of ODD,tl.!o were
calculated for each hybrid from planting to silking and silking
to maturity for all location-years. Values of B ro , BI> and B ,
that minimized the squares of the differences between these
average values of ODD Jo,o and values generated by Eq. [3]
for individual hybrid-location-year data sets were calculated
by least squares, using Marquardt's algorithm (Marquardt,
1963). Because GTI and ODD have near-equal numerical
values, units of FT are inoC and are called modified growing
degrees.
One of the methods to evaluate the GTI was a coefficient
of variation (CV). The reliability of a thermal index is determined by its constancy across years and locations but not
across hybrids, since the index is to be used to characterize
the thermal requirements of individual hybrids. Therefore, a
mean variance was calculated by summing the squares of the
differences between OTIs for individual hybrids for each location, year, and phenological period, and hybrid means for each
period averaged over all locations and years. The square root
of the mean variance for all locations and years divided by
the overall mean was the CV for the phenological period.
A similar CV was calculated for thermal time estimated by
GDD,o.!o and for actual time in recorded days. The OTI and
GDD''-'.J(J were used to calculate time in days from planting to
silking aDd from silking to maturity and these calculated days
were compared with recorded days. A root mean square error
was calculated between recorded time in days and time in
days estimated from GTI and GDD,,,III calculations. Then the
entire data set (Set A) was divided into two subsets by selecting
alternate years: Set B included all odd-numbered years, Set
C, all even-numbered years. Coefficients were calculated for
Sets Band C and then tested against each other, using CVs
and standard errors.
RESULTS AND DISCUSSION
For the vegetative period (planting to silking), the
response function for the four hybrid groupings were
sigmoid-type curves (Fig. 1). The coefficient BII was
never significantly different from zero, and Eg. [3] for
this period reduced to
Fr
=
BIn + B 2n
[4]
These response curves were similar to those measured
by Ellis et al. (1992) on maize hybrids under controlled
environment conditions. Their data were fit to a l3-function by Yin et a!. (1995). Beta functions are nonsymmetric and rise from an initial temperature to a maximum
function value and then decline to a maximum endpoint temperature. The main difference between the
GTI (Eq. [4]) and the l3-function occurred at low temperatures, as the GTI temperature response increased
76
AGRONOMY JOURNAL, VOL. 90, JANUARY-FEBRUARY 1998
20...------------------------,
pressed FT as a function of T M . Since the differential of
Eq. [4] was equal to zero when T A = TNt. we expressed
B2 as
o
B2
~15
.2
U
=
-0.667 B,/TM
[5]
Substituting B 2 into Eq. [4] results in
c:
:>
LL
FT
:l
c:
~10
~
e
:>
!
-Group 1
a.
e"
--- Group 2
- -Group 3
--'Group4
{!!. 5
0+-...:::::..-,-----.----,.-----,---...,----,.----1
o
5
10
15
20
25
30
35
Mean Daily Temperature (e)
Fig. I. Temperature response function (FT , Eq. [4]) of four maize
hybrid groups for the planting to silking period.
slowly as temperatures rose above zero, but the (3-function increased abruptly from a minimum temperature
of about 100e. Both GTI and the (3-function increase
to a maximum and then decrease, while GDD 30.10 rises
linearly from 10 to 30°C with a slope of 1 and then is
constant (Fig. 2). The bulk of the empirical evidence
indicates that phenological temperature response functions for the vegetative period are sigmoidal (Shaykewich, 1995).
In the present study, the hybrid groups with greater
relative maturity ratings tended to have higher maximum values of FT , which occurred at greater values of
T A (Fig. 1), although this pattern was not followed by
Hybrid Group 4 (the group with the largest number of
hybrids) (Table 2). The average daily air temperature
at a maximum value of FT is T M • To determine if hybrid
differences in TM were significant (P :5 0.05), we ex-
=
B1
n (1 -
0.667TA /TM )
[6]
When T M and its standard error were solved for, no
significant differences in T~, were found between the
groups (P > 0.05; data not shown), This was not surprising, since only a small fraction of average daily temperatures were greater than 30°C (Fig. 3). There were only
small differences in the functions between 10 and 25°C,
where the bulk of the mean temperatures fell. Thus, a
single average FT function represented the vegetative
period (Fig. 2; Table 3).
The GTI for all hybrid groups combined had important differences from GDD 311 ,lo (Fig. 2). The GTI was
more responsive than GDD 30,Io to T A below 10°C, but
was not as responsive as GDD 311 ,IfI when T A was above
20°e. Others have noted that 30 and 10°C are not the
most appropriate temperature limits for maize phenological development (e.g., Ritchie and Nesmith, 1991).
However, even in the temperature range within which
vegetative temperature response function described by
GTI is linear, the slope of the line is about 0.64, compared with 1.0 for GDD 30 ,Io (Fig. 2). That is, GTI has a
zero slope (the slope equals the phenological response
per 1°C air temperature) at oDe, rises to a maximum of
0.64 at about 15°C, and then falls to zero at 30°e. In
contrast, GDD 30. IO has a constant slope of one phenological unit per 1°C between 10 and 30°C and zero slope
above and below these limits.
When GTI was fit to hybrid group data from silking
to maturity (Fig. 4), the y-intercept (B o) was significantly
greater than zero, and the overall function was much
flatter than the function for the planting to silking period
(Fig. 1). There were no significant differences between
20,----------------------:;,
50
45
CJ Planting to Silking
o
40
o
:;::
35
Silking to Maturity
~15
"
c:
..
:>
LL
,
~30
~
>.
"c:
...e~ 25
~10
~
e
~
LL
/,///
.
a.
e
20
15
~ 5
/
,,/'
10
/
,,/'
""
o-f-"""""=----,-----f'-----,.---..,.-----,.-----!
o
10
15
20
25
30
Mean Daily Temperature (C)
Fig. 2. Comparison of the temperature response functions (FT ) for
GTI (solid line) and GDDJ\l,'O (broken line) for the planting to
silking period in maize.
o
0-5
n~
5-10
IiJ
10-15
15-20
20-25
25-30
I
30-35
Temperature Range (e)
Fig. 3. Frequency distribution of average daily air temperatures during the vegetative (planting to silking) and reproductive (silking
to maturity) periods of maize.
77
STEWART ET AL.: PHENOLOGICAL TEMPERATURE RESPONSE OF MAIZE
r
Table 3. Coefficients and standard errors (in parentheses) of the polynomials from planting to silldng (P-S) (Eq. 4]) a.nd from silking
to maturity (S-M) (Eq. [3]) of maize, for the entire data set (Set A) and for subsets with odd-numbered (Set B) and even-numbered
(Set C) years.
Data
,et
Developmental
period
B,
P-S
S-M
P-S
S-M
P-S
S-M
.\
R
C
H,
HI
0.043177
0.011178
0.042184
0.011638
0.044180
0.011355
5.3581 (0.181)
5.1313 (0.247)
5.3363 (0.268)
hybrid groups, as the function fitted to each group had
a similar shape and there were no significant differences
in any of the coefficients (P > 0.05; data not shown).
As with the planting to silking function, there were
nly smaJl differences in the silking to maturity group
functions in the 10 to 25°e ranges, where the bulk of the
temperatures occurred (Fig. 3). Again, a single function
could represent all the data (Fig. 5; Table 3).
As was the case for the vegetative period, GTI was
much less responsive to T A above 20°e. In addition, FT
for the reproductive period had a positive y-intercept
and showed a relatively flat response to mean daily
I mperatures from 0 to 12°e, rising significantly only
with temperatures greater than this range (Fig. 5). Although this response was very different from that fitted
to vegetative period data and from that assumed by
GDD'OIIi' it appeared to be consistent for the reproduclive period across both field and controlled environment
nditions. Fitting the growth chamber data of Tollenaar and Bruulsema (1988) produced a function of simihlr shape (Fig. 5). It should be noted that in the growth
chamber study, one of the treatments was a day/night
temperature regime of 14/2°e, yet grain filling was completed in a reasonable time. This provides further evidence that development continues during the reproductive period at or below lO°e. We did try to modify Eq.
[ ] to bend the function at low temperatures (0-10°e)
to force it through the origin, with no improvement in
(0.00082)
(0.00044)
(0.00109)
(0.00061)
(0.00121)
(0.00066)
-0.000894 (0.0000386)
-0.000848 (0.0000514)
-0.000940 (0.0000569)
the fit (data not shown). This could be in part due to a
lack of temperature data below lOoe (Fig. 3). However,
Eq. [3] with the coefficients listed in Table 3 estimates
significant phenological development below lOoe for
the silking to maturity period. The relatively small standard error of Btl (Table 3) and the agreement with
growth chamber data of Tollenaar and Bruulsema
(1988) suggest that development occurs at these Jow
temperatures, and that this part of the function contributes to the improvement of GTI over GDD 3u.,o .
The shape of the function for the reproductive period
was the most puzzling aspect of this study. By choosing
the third-order polynomial, we were essentially letting
the least squares procedure determine the optimum
shape, and the best fit had a y-intercept that was significantly different from zero and indicated substantial phenological development below lO°e. An earlier attempt
to improve on GD0 3o .,o by lowering the value ofTMINL
improved the GOO calculations, but not to the level of
GTI (data not shown). Low-temperature development
may be a phenomenon of northern locations, where
low temperatures and frost occur during reproductive
development and affect end-point calculations. That is,
when temperatures fall below lOoe, GDD'Ii.lll additions
per day are very small or zero, making it difficult to
calculate an exact end-of-period date. The GTI calcu20..-----------------------,
20..----------------------,
0-
~15
o
0"
-; 15
..-::
.2
;;
,oj
.
<
/.
.."'"
u.
/
c
o
~10
/
~
nc
~
j, .. /
e
.--:/
~
/
[
e
:. 5
"-- Group2
- -Group 3
-_·Group 4
0+----..----1----...---,------.------1
o
5
10
15
20
25
5
10
15
20
25
30
Mean Dally Temperature (C)
O+----r-----;,-----,------r---~--_t
o
,>//:,/
----
-Group 1
-
30
Mean Daily Temperature (e)
Fig. 4. Temperature response function (Fy, Eq. [3]) of four maize
hybrid groups for the silking to maturity period.
Fig. 5. Comparison of temperature response functions (ET ) for GTl
(solid line) of maize, using field dat.a, and GDDJO.'o (dotted line)
and GTl (dashed line), using growth room data of Tollenaar and
Brunlsema (1988), for the silking to maturity period.
78
AGRONOMY JOURNAL. VOL 90, JANUARY-FEBRUARY [990
Table 4. Goodness of estimate of days required from planting to silking (P-S) and from silking to maturity (5-M) of maize, using actual
days, growing degree da)'s (GDD3(I,lo), and the general thermal index (GTI) to estimate development based on coefficients of variation
or standard errors of est'imate.
Goodness of esomate
Developmental
period
GTI:r.
Data set
Da)'s
GDD.l.tl.lf,·j-
P-S
S-M
P-S
S-M
P-S
S-M
A
A
0.091
0.117
0,092
0.105
0.087
0.113
0.056
0.109
0.053
0.104
0-058
0.110
P-S
S-M
P-M
P-S
S-M
P-M
P-S
S-M
P-M
A
A
A
Dependent
Independent
Coefficient of variation
B
B
C
C
B
B
B
C
C
C
3.56
12.14
13.56
3.28
12.18
13.51
3.69
11.80
13.39
0.047
0.077
0,045
0.072
0.047
0.077
Standard error of estimate, d
3.04
5.86
6.95
2.88
5.96
6.84
3.05
5.88
6.85
0,045
0.071
0.049
0.077
2.82
5.67
6.56
3.14
5.88
6.97
t Growing degree da)'s with threshold limits of 30·C (maximum) and IO·C (minimum).
:;: GTI calculations used the enOre data set (Set A) to determine coefficients and then fit the same data set using those coefficients (dependent), or used
data subsets (Set B, odd-numbered years. and Set C, even-numbered years) to determine coefficients and then fit the same data set (dependent) or
alternate dala set (independent) from thai used to determine coefficients.
lated development at temperatures too low to accumulate GDD, and reduced uncertainty associated with endpoint date.
Comparison of CVs and standard errors indicates that
the GTI using the coefficient values listed in Table 3
improved estimation of development rate over GDD 30,lfI
(Table 4). Coefficients of variation for the total planting
to maturity period were reduced by 35% and standard
errors in estimating maturity dates were reduced by
50% when GTI rather than GDD 30 ,lfI was used. The
greatest improvement occurred from silking to maturity
when the standard error of estimating maturity was reduced from 12.5 d using GDD111,1O to 5.8 d using GTI.
Note that CVs show GDD111,10 was only marginally better
than days for this period.
Dividing the data into two subsets had little effect
on the results. Coefficients for each set did not differ
significantly (P > 0.05) from each other, nor from coefficients calculated from the combined data set (Table 3).
As well, when the coefficients from one set were tested
against the other, CVs were almost identical and standard errors were only slightly larger in one of the data
sets (Table 4, Set C). Standard errors for GTI using
independent data were much smaller than for GDD.lO . lO •
Thus, the GTI function was stable under independent
testing. This was expected, since only two coefficients
were solved for, per equation, using more than 430 data
points, which resulted in more than 200 degrees of freedom for each test. As well, dividing the data into four
groups based on hybrid maturity and calculating similar
coefficients for each group was further evidence of the
stability of the GTI function.
In summary, the phenological response to temperature was sigmoidal from planting to silking, but was
much more flat from silking to maturity. Functions for
both periods had markedly different forms than
GDD 3U •IO ' The significance of the temperature insensitivity of reproductive development from 0 to 12°C for any
location-year will depend on the distribution of average
daily air temperatures during the reproductive period.
The GTI calculated faster development rates for days
with cool temperatures (which typically occur near the
end of the growing season) than did GDD'l1lO' The fact
that this function accounted for the influence of low
temperatures on development was important to its better performance in calculating maturity dates. These
results suggest that incorporation of actual temperature
response functions could significantly improve the performance of heat unit systems used to compare hybrid maturity.
ACKNOWLEDGMENTS
The authors wish to thank B. Wilson. D. Balchin. and L.
Evenson for technical assistance with data collection and data
analysis. V. Puskaric provided helpful advice and technical
assistance at the Pioneer Hi-Bred Research Station at Woodstock, ON. Pioneer Hi-Bred International contributed financial support and data to this study.
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Forage and Nitrogen Yield of Barley-Pea and Oat-Pea Intercrops
Patrick M. Carr,t.' Glenn B. Martin, Joel S. Caton, and W. W. Poland
ABSTRACT
Barley (Hordeum vulgare L.) and oat (A vena sativa L.) have
heen in.tercropped with field pea [Pisum sativum subsp. sativum \·ar.
un·el1.l·e (L.)Poir.] to increase forage yield and quality. Our objective
lIas to enluate the effects of two barley and two oat cultivars and
seeding rates of cereal-pea intercrop on forage production, crude
protein (CP) concentration, and N yield. A field experiment was
rnnduded in 1993 and 1994 under dryland management in both fa.lluwed and continuously cropped, no-tillage environments. 'Bowman'
and 'Horsford' barley, and 'Dumont' and 'Magnum' oat, were each
sown lit 93, 185, and 278 kernels m- l with 'Trapper' pea at 40, 80,
and 120 seeds m- l , in all possible rate combinations. The cereal cultilars also were sown alone at 185 kernels m- l • Cultivars de\-eloped
fur forage production (Horsford, Magnum) produced as much or
more forage than cultivars developed for grain production (Bowman,
Dumont) across sole-crop and intercrop plots (P :5 0.05). Forage yield
was unaffected by intercropping when the cereal crop was sown at
the sole-crop or greater rate. Less forage was produced by intercrops
w'hen the cereal component was sown at half the sole-crop rate. Forage
yield was not affected by the pea seeding rate, but CP concentration
increased with increasing seeding rate of pea in three of four environment-~'ears. Forage N yield was unaffected by intercropping. These
dala indicate that lhe cereal component in barley-pea and oat-pea
midures should be sown at a sole-crop or greater seeding rate for
maximum forage production. Forage CP concentration can be increased as the relative proportion of pea seed to cereal kernels sown
in a mixture is increased, but forage N yield may not be affected,
,ince the cereal component contributes more to yield than the pea
cumponent.
P.M. Carr. G.B. Martin, and W.W. Poland, North Dakota State Univ.,
Dickinson Res. & Ext Ctr., 1089 Stale Ave., Dickinson. NO 5860]:
J.S. Caton. Dep. of Animal and Range Sci., North Dakota State Univ.,
1.lrgo. ND 58105. Contribution from the North Dakota Agric. Exp.
tp. Received 20 Feb. 1997. "Corresponding author (pat_carr@
J,u l.dsu.nodak.edu).
Published in Agron. J. 90:79-84 (1998).
B
are intercropped with pea for forage.
Intercropping pea with oat increases protein content of haylage compared with growing oat alone
(Droushiotis, 1989; Robinson, 1960; Walton, 1975).
Some studies revealed that intercropping oat with pea
increased yield of haylage (Robinson, 1960), but other
studies did not (Walton, 1975). Similarly, intercropping
pea with barley has increased dry matter production in
some instances (Chapko et aI., 1991), but not in others
(Izaurralde et at., 1990).
Seeding rates for the component crops in cereal-pea
mixtures generally are less than when either the cereal
crop or pea is sown alone. Carter and Larson (1964)
reduced the cereal seeding rate by 38% and the pea
rate by 33% compared with a sole crop when oat was
intercropped with pea. Seeding rates of both oat and pea
were reduced by at least 20% in cereal-pea intercrop
evaluated by Droushiotis (1989). Work done by Izaurralde et at. (1990) suggested that no yield advantage
resulted when barley and pea were intercropped at a
sole-crop rate compared with lower rates in barley-pea
mixtures; however, N yield was increased by intercropping when both barley and pea were sown at more than
half the sole-crop rate.
When intercropping barley or oat with pea, cultivar
selection was not as important a consideration as choosing which cereal crop to grow when intercropping barley
or oat with pea as a companion crop for alfalfa (Medicago sativa L.) establishment (Chapko et a!., 1991).
Oat-pea mixtures were preferred over barley-pea mixtures on the basis offorage quality, although barley-pea
mixtures generally produced more forage. The interaction between cultivar selection and the rate at which
ARLEY AND OAT
Abbreviations: CP, crude protein.