EverCrop
Examining the impact of perennial pastures on
profitability
Graeme Sandral, Richard Hayes, Guangdi Li
NSW Department of Primary Industries and E H Graham Centre
Tony Swan and Mark Peoples
CSIRO
Shawn McGrath
Fred Morley Unit and E H Graham Centre
Jim Virgona
Graminus Consulting
Aims
• Grow more pasture
• Fix more Nitrogen
Sites
Sites
Average Rainfall
(mm)
April to Oct Rainfall % April to October
(mm)
(mm)
Mirrool
471
288
61
Burrumbuttock
580
384
66
Eurongilly
535
329
62
Wagga Wagga
530
331
63
Lockhart
484
308
64
Treatments
Species and species
combination
Pasture description and sowing rate (kg/ha)
Sub clover Monoculture
Sub clover only (4 kg/ha)
Lucerne Monoculture
Lucerne only (3 kg/ha)
Lucerne Sub clover Mix
Lucerne (3 kg/ha) and Sub clover (4 kg/ha) in the same row
Lucerne Sub clover 1:1
Lucerne (3 kg/ha) and Sub clover (4 kg/ha) in alternate rows
Lucerne Biserrula 1:1
Lucerne (3 kg/ha) and Biserrula (1kg/ha) in alternate rows
Lucerne annual Medic 1:1
Lucerne (3 kg/ha) and annual Medic (3 kg/ha) in alternate rows
Lucerne Sub clover 1:2
Lucerne (3 kg/ha) sown in one row and Sub clover (4 kg/ha) sown in two rows
Phalaris Lucerne Sub clover
Mix
Phalaris (1.5 kg/ha), Lucerne (1.5 kg/ha) and Sub clover (4 kg/ha) sown in every row
Phalaris Lucerne 1:1 Sub
clover
Phalaris (1.5 kg/ha) sown in one row, Lucerne (1.5 kg/ha) sown in the other row with
Sub clover (4 kg/ha) sown in all rows.
Phalaris Lucerne 1:2 Sub
clover
Phalaris (1.5 kg/ha) sown in one row, Lucerne (1.5 kg/ha) sown in the next two rows
with Sub clover (4 kg/ha) sown in all rows.
Phalaris Sub clover 1:1
Phalaris (3 kg/ha) and Sub clover (4 kg/ha) in alternate rows
Phalaris Sub clover Mix
Phalaris (3 kg/ha) and Sub clover (4 kg/ha) in the same row
1 Lucerne : 2 sub clover
Sub clover only
1 Phalaris : 1 sub clover
Phalaris & sub clover mix
Wagga Wagga
4th Sept 2013
Mirrool
14th Nov 2013
Lockhart
11th March 2014
Burrumbuttock
10th Dec 2013
Details
• Sown: Autumn 2012
– Measurements
•
•
•
•
•
•
•
•
Seedling counts (annuals + perennials year 1)
Basal frequency (perennials)
Dry matter and botanical composition (4 times a year)
Seed bank of annual legume (summer)
N-fix and OMD (potentially 4 times a year)
Soil nitrogen (pre-cropping)
Estimated N-fix
Estimated livestock performance
The Nitrogen Story
Relationship between sub clover dry matter and
amount of atmospheric nitrogen fixed
For every 1000 kg/ha of
legume shoot dry matter
you gain approximately
20 kg/ha of fixed N.
(Unkovich et al 2010)
Relationship between legume dry matter and
amount of nitrogen available prior to cropping
Mineral N in May prior to cropping
to 1 m (kg/ha)
400
N = 130 + 0.0148 x legume DM
R2 = 0.66
350
300
250
200
150
For every 1000 kg/ha of
legume shoot dry matter
you gain approximately
15 kg/ha of mineral N.
100
50
2
4
6
8
10
12
Legume dry matter accumulated over 3 years (kg/ha)
14
N-fix estimation & valuation
• To estimate the value of the N contribution by the pastures (in
N fixed kg/ha) we have assumed 15 kg N /ha for every 1000
kg/ha of legume.
• The estimated dollar value of the N was provided by assuming
Urea cost was $550/t with an N concentration of 46%.
• The estimated value to crops assumes 15% of the N fixed by
the pasture is utilised by the following crop.
N-fix estimations
Wagga Wagga assuming 15 N kg per
1000 kg/ha of legume
Scenario 1
Species & species combination
Sub clover mono
Lucerne mono
Lucerne + Sub clover mix
Lucerne + Sub clover 1:1
Lucerne + Biserrula 1:1
Lucerne + Medic 1:1
Lucerne + Sub clover 1:2
Phalaris + Lucerne + Sub
Phalaris + Lucerne 1:1 + Sub
Phalaris + Lucerne 1:2 + Sub
Phalaris + Sub clover 1:1
Phalaris + Sub clover mix
LSD
Cumulative Cumulative
%
Cumulative Estimated Value to
DM
Legume DM Legume
N-fix
Value of N
crop
Ranking
(kg/ha)
(kg/ha)
(kg N/ha)
$/ha
$/ha
28595
26034
91.0
391
988
148
3
22839
18268
80.0
274
693
104
8
27993
26951
96.3
404
1,023
153
2
27109
25480
94.0
382
967
145
4
17376
15264
87.8
229
579
87
9
16314
13807
84.6
207
524
79
11
28762
27614
96.0
414
1,048
157
1
38611
18390
47.6
276
698
105
7
35472
19061
53.7
286
723
109
5
32736
18836
57.5
283
715
107
6
35385
14339
40.5
215
544
82
10
38045
8727
22.9
131
331
50
12
5792
4142
N-fix estimations
Wagga Wagga measured
30 N kg per 1000 kg/ha of sub clover and
20.4 N kg per 1000 kg/ha of Lucerne
Scenario 2
Cumulative Cumulative
%
Cumulative Estimated Value to
DM (kg/ha) Legume DM Legume
Species & species combination
(kg/ha)
N-fix
Value of N crop
(kg N/ha)
$/ha
Ranking
$/ha
Sub clover mono
28595
26034
91.0
781
1,976
296
1
Lucerne mono
22839
18268
80.0
373
944
142
10
Lucerne + Sub clover mix
27993
26951
96.3
689
1,743
261
3
Lucerne + Sub clover 1:1
27109
25480
94.0
639
1,617
243
4
Lucerne + Biserrula 1:1
17376
15264
87.8
374
946
142
9
Lucerne + Medic 1:1
16314
13807
84.6
332
840
126
11
Lucerne + Sub clover 1:2
28762
27614
96.0
719
1,819
273
2
Phalaris + Lucerne + Sub
38611
18390
47.6
475
1,202
180
7
Phalaris + Lucerne 1:1 + Sub
35472
19061
53.7
477
1,207
181
6
Phalaris + Lucerne 1:2 + Sub
32736
18836
57.5
489
1,237
186
5
Phalaris + Sub clover 1:1
35385
14339
40.5
421
1,065
160
8
Phalaris + Sub clover mix
38045
8727
22.9
261
660
99
12
5792
4142
LSD
N-fix estimations
Wagga Wagga methods compared
Species & species combination
Sub clover mono
Lucerne mono
Lucerne + Sub clover mix
Lucerne + Sub clover 1:1
Lucerne + Biserrula 1:1
Lucerne + Medic 1:1
Lucerne + Sub clover 1:2
Phalaris + Lucerne + Sub
Phalaris + Lucerne 1:1 + Sub
Phalaris + Lucerne 1:2 + Sub
Phalaris + Sub clover 1:1
Phalaris + Sub clover mix
Scenario 1
Estimated Value to
Value of N crop
Ranking
$/ha
$/ha
988
148
3
693
104
8
1023
153
2
967
145
4
579
87
9
524
79
11
1048
157
1
698
105
7
723
109
5
715
107
6
544
82
10
331
50
12
Scenario 2
Estimated
Value of N crop
$/ha
$/ha
1,976
944
1,743
1,617
946
840
1,819
1,202
1,207
1,237
1,065
660
Ranking
296
142
261
243
142
126
273
180
181
186
160
99
1
10
3
4
9
11
2
7
6
5
8
12
Nitrogen fixation (N-fix)
Wagga Wagga results
• Adding phalaris to the mix increased dry matter yield but
decreased N-fixation.
• Lucerne plus sub clover in any combination produced
more fixed N than lucerne plus medic or lucerne plus
biserrula.
• The sub clover monoculture performed as well as sub
clover plus lucerne combinations as determined by N-fix
The Livestock Story
Livestock modelling details
• An estimate of the value/ranking of each of the treatments on
livestock production was calculated using GrazFeed®. Dry matter
available for grazing was calculated by assuming an efficiency of
utilisation of 40% above a minimum amount of 1800 kg/ha of
available pasture.
• The daily intake rate and growth rates of 30 kg merino wether
lambs, were calculated for each of the treatments based on the
legume composition achieved and assuming digestibility of 80 %
and 45% for green and dead pasture respectively. Total weight gain
was then calculated based on the dry matter available for grazing,
the daily intake rates and the daily growth rates predicted. Each of
the treatments was then ranked according to estimated weight gain
(per ha).
Livestock estimations
Model 1
Model 1
Species & species combination
Cumulative
%
DM grazed
Est intake
Est live
DM
Legume
kg/ha
g/hd/day
wt gain
(kg/ha)
1800
Ranking
Kg/ha
Sub clover mono
7149
91.0
2140
1.64
405
7
Lucerne mono
5710
80.0
1564
1.61
285
10
Lucerne + Sub clover mix
6998
96.3
2079
1.65
401
8
Lucerne + Sub clover 1:1
6777
94.0
1991
1.64
381
9
Lucerne + Biserrula 1:1
4344
87.8
1018
1.63
191
11
Lucerne + Medic 1:1
4079
84.6
911
1.62
169
12
Lucerne + Sub clover 1:2
7191
96.0
2156
1.65
415
6
Phalaris + Lucerne + Sub
9653
47.6
3141
1.54
509
1
Phalaris + Lucerne 1:1 + Sub
8868
53.7
2827
1.55
469
2
Phalaris + Lucerne 1:2 + Sub
8184
57.5
2554
1.56
429
5
Phalaris + Sub clover 1:1
8846
40.5
2819
1.52
445
4
Phalaris + Sub clover mix
9511
22.9
3085
1.48
455
3
LSD
1448
Livestock modelling details
• An estimate of the value/ranking of each of the treatments on
livestock production was calculated using GrazFeed®. Dry matter
available for grazing was calculated by assuming an efficiency of
utilisation of 40% above a minimum amount of 1800 kg/ha of
available pasture.
• Model run using 4 month old wether XB lamb, 35 kg LW. Legume
pastures were assumed to have a OMD of 75% and phalaris based
pastures were assumed at 70% OMD.
• The dry matter available for grazing was divided by the predicted
dry matter intake and then multiplied by the predicted liveweight
gains to produce an estimate (“index”) of lamb production.
Livestock estimations
Model 2
Model 2
DM Grazed Digestability
Species & species combination
Sub clover mono
(kg/ha)
% DM
Est live
KG of
Protein
Est intake
wt gain
lamb
% DM
kg/hd
g/hd/day
/ha/yr
Ranking
10718
75
28.1
1.80
382
758
7
8416
75
27.3
1.77
360
571
10
Lucerne + Sub clover mix
10477
75
28.5
1.82
391
750
8
Lucerne + Sub clover 1:1
10124
75
28.3
1.81
388
723
9
Lucerne + Biserrula 1:1
6230
75
27.9
1.78
367
428
11
Lucerne + Medic 1:1
5806
75
27.7
1.77
360
394
12
Lucerne + Sub clover 1:2
10785
75
28.5
1.82
392
774
5
Phalaris + Lucerne + Sub
14724
70
21.3
1.68
305
891
1
Phalaris + Lucerne 1:1 + Sub
13469
70
21.6
1.69
313
832
2
Phalaris + Lucerne 1:2 + Sub
12374
70
21.9
1.70
317
769
6
Phalaris + Sub clover 1:1
13434
70
20.8
1.66
292
788
4
Phalaris + Sub clover mix
14498
70
19.7
1.62
267
796
3
Lucerne mono
Livestock estimations
Methods compared
Model 2
Model 2
KG of
Species & species combination
Sub clover mono
DM Grazed
Est intake
lamb
Ranking
(kg/ha)
kg/hd
/ha/yr
Est intake
Est live
g/hd/day
wt gain
Ranking
kg/ha
10718
1.80
758
7
1.64
405
7
8416
1.77
571
10
1.61
285
10
Lucerne + Sub clover mix
10477
1.82
750
8
1.65
401
8
Lucerne + Sub clover 1:1
10124
1.81
723
9
1.64
381
9
Lucerne + Biserrula 1:1
6230
1.78
428
11
1.63
191
11
Lucerne + Medic 1:1
5806
1.77
394
12
1.62
169
12
Lucerne + Sub clover 1:2
10785
1.82
774
5
1.65
415
6
Phalaris + Lucerne + Sub
14724
1.68
891
1
1.54
509
1
Phalaris + Lucerne 1:1 + Sub
13469
1.69
832
2
1.55
469
2
Phalaris + Lucerne 1:2 + Sub
12374
1.70
769
6
1.56
429
5
Phalaris + Sub clover 1:1
13434
1.66
788
4
1.52
445
4
Phalaris + Sub clover mix
14498
1.62
796
3
1.48
455
3
Lucerne mono
Livestock performance
Wagga Wagga results
• Adding phalaris to the pasture mix increased dry matter
and is likely to increase animal performance even when a
lower OMD is assigned to phalaris in the modeling
process.
• Lucerne plus biserrula and lucerne plus annual medic
under performed.
• The lucerne monoculture under performed and required
the addition of sub clover to boost production.
Overall performance
Wagga Wagga
Species & species combination
Sub clover mono
Livestock
Livestock
N-fix
N-fix
Overall
Model 1
Model 2
Scenario 1
Scenario 2
mean
ranking
ranking
ranking
ranking
rank
7
7
1
3
5
10
10
10
8
10
Lucerne + Sub clover mix
8
8
3
2
5
Lucerne + Sub clover 1:1
9
9
4
4
7
Lucerne + Biserrula 1:1
11
11
9
9
10
Lucerne + Medic 1:1
12
12
11
11
12
Lucerne + Sub clover 1:2
6
5
2
1
4
Phalaris + Lucerne + Sub mix
1
1
7
7
4
Phalaris + Lucerne 1:1 + Sub
2
2
6
5
4
Phalaris + Lucerne 1:2 + Sub
5
6
5
6
6
Phalaris + Sub clover 1:1
4
4
8
10
7
Phalaris + Sub clover mix
3
3
12
12
8
Lucerne mono
Overall performance
Wagga Wagga results
• Best performing phalaris treatments had two legumes
species included (lucerne and sub clover either mixed or
1:1 sowing arrangement).
• The best performing pasture in the absence of phalaris
was lucerne plus sub clover 1:2 sowing arrangement.
Overall performance
Mirrool
Species & species combination
Livestock
Livestock
N-fix
N-fix
Overall
Model 1
Model 2
Scenario 1
Scenario 2
mean
ranking
ranking
ranking
ranking
rank
Sub clover mono
7
6
1
6
5
Lucerne mono
9
9
8
3
7
Lucerne + Sub clover mix
8
8
3
2
5
Lucerne + Sub clover 1:1
10
10
5
4
7
Lucerne + Biserrula 1:1
6
7
2
1
4
Lucerne + Medic 1:1
12
12
7
7
10
Lucerne + Sub clover 1:2
11
11
4
5
8
Phalaris + Lucerne + Sub mix
3
2
9
9
6
Phalaris + Lucerne 1:1 + Sub
4
4
10
10
7
Phalaris + Lucerne 1:2 + Sub
2
1
6
8
4
Phalaris + Sub clover 1:1
5
5
11
11
8
Phalaris + Sub clover mix
1
3
12
12
7
Results in a wider context
Livestock Farm Monitor Project in Victoria – result
shown are for Northern Victoria
• Running since 1971
• Compares average farm result to top 20% of farms as determined by onfarm profitability
• The result highlight some important points.
Northern Victoria whole farm financial summary
Average
Top 20%
Difference
Gross income ($/ha)
433
607
174
Variable costs ($/ha)
151
146
-5
Overhead costs ($/ha)
104
112
8
EBIT ($/ha)
102
312
210
51
265
214
Return on assets (%)
2.0%
6.0%
0.04
Return on equity (%)
0.90%
6.80%
0.059
Net farm income ($/ha)
Northern Victoria livestock and pasture summary
Average
Top 20%
Difference
Avg. Rainfall (mm)
659
657
-2
Stocking rate (DSE/ha)
9.8
11.4
1.6
DSE/ha/100 mm
1.5
1.6
0.1
July stocking rate (DSE/ha)
9.3
8.9
-0.4
6
9
3
Kg P/ha/100 mm
0.9
1.2
0.3
Pasture costs
32
52
20
12.3
14.2
1.9
Kg P/ha
Sup feeding kg/DSE (grain)
Take home messages
• Look at ways to grow more pasture and maintain adequate legume
content (species selection and sowing arrangement). This allows
you to have a higher stocking rate (DSE/ha).
• Target soil Colwell P (phosphorus) at 30 to 35 mg/kg or Olsen P at
15 to 17 mg/kg for maximum pasture growth.
• Ensure your utilization of pasture is high (e.g. 40% plus) and
increased stocking rate will help achieve this.
• Match livestock demand as best as possible with pasture supply by
manipulating lambing/caving. This will help minimize additional
feeding costs.
Thank you
Livestock Farm Monitor Project in Victoria – result shown are for Northern Victoria
• Running since 1971
• Compares average farm result to top 20% as determined by profitability
Findings include – the most profitable farms had:
• More income per ha = higher profits
• More red meat and/or wool per ha but at a lower cost per ha
• Grow more pasture
• Have higher utilisation efficiencies and achieve this with higher stocking rates
• Match livestock demands with feed supply (lambing / calving timing)
http://agriculture.vic.gov.au/agriculture/livestock/farm-monitor-project
Northern Victorian livestock farm in 2013/14.
Average Top 20%
Sheep (head)
5,473
7,485
Cattle (head)
727
1,333
Labour efficiency (ha/person)
Labour efficiency
(DSE/person)
601
724
5,782
8,146
Effective hectares
1,103
1,415
Northern Victoria enterprise mix
Average
Top 20%
Wool
45%
11%
Lamb
23%
41%
Beef
Hay / cropping
28%
4%
46%
2%