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  5. November 2018

Grazing Systems Research Update: Year-Round Forage Options

By Twain Butler, Ph.D., Professor,
Jon Biermacher, Ph.D., Senior Economist,
Justin Hoffman, Sensor Technology Coordinator
and Sindy Interrante, Ph.D., Technical Scientist

Posted Nov. 1, 2018

The ultimate goal for every forage producer is to have high-quality forage in a sufficient quantity to feed livestock every day all year long.

Current research at the Noble Research Institute aims to develop year-round grazing systems for the Southern Great Plains. Because no single forage can accomplish this (Figure 1), we are evaluating several forage species in mixtures or in combination.

Figure 1: Forage DistributionFigure 1: Forage Distribution

We are using a put-and-take stocking method to measure grazing days, average daily gain and total pounds of beef gain per acre for each system. Using the animal performance data and expected prices for cattle and agronomic inputs, we have developed detailed enterprise budgets that report calculated revenues, costs and net returns to land, labor, management and overhead for each of the alternative grazing systems we have evaluated during the past 16 years.

Alternative Systems

Table 1 summarizes the animal performance and economics of 11 alternative systems. Because of differences in the cattle market across the various study periods, we normalized the revenue for each system by assigning a common value of gain for each pound of beef produced by each cool-season component. If graze-out wheat and bermudagrass systems are considered the standard, many of the systems are equal to them or greater in economic net return. The bermudagrass system was the least profitable because of extremely low animal performance and would not be recommended for stocker cattle production.

Table 1. Average Production and Expected Economics for Alternative Forage-based Stocker Systems Evaluated at the Noble Research Institute

Production
System

Study
Years

Normal
Rainfall
(%)

Grazing
Initiation
Date

Grazing
Termination
Date

Grazing
Duration
days)

Steer
Grazing
Days
(days/A)

Average
Daily
Gain
(lbs/hd/day)

Total
Gain
(lbs/A)

Value
of
Gain
($/lb)

Gross
Revenue
($/A)

Total
Cost
($/A)

Net
Return
($/A)

NF101
wheat/
Impact
Crabgrass

5 yr avg (2013-18)

114

12/16

8/19

164

288

1.9

549

0.80/0.60

400

213

187

800RR
experimental
alfalfa

3 yr avg

2015-18

110

3/13 and 10/23

7-30 and 11/25

157

247

2.03

501

0.80

401

241

160

Maton II
rye /
Marshall
ryegrass

7 yr avg (2005-12)

82

11/18

4/28

130

183

2.3

421

0.80

337

183

154

Flecha
summer
dormant
TF

5 yr avg (2013-18)

114

12/28

5/22

144

188

1.8

340

0.80

272

133

139

Chisholm
summer-
dormant
TF

5 yr avg (2013-18)

114

12/28

5/22

145

185

1.8

327

0.80

262

127

135

Wheat-
Alfalfa#-
Crabgrass
(2 paddock)
system

5 yr avg (2013-18)

114

9/18 

 8/19

127

210

2.0

424

0.80

339

222

117

NF101
wheat

5 yr avg (2013-18)

114

12/16

4/20

118

165

2.2

356

0.80

285

183

102

Impact
crabgrass

5 yr avg (2013-18)

142

6/27

8/19

46

123

1.6

192

0.60

115

29

86

Bulldog
505
Alfalfa#

5 yr avg (2013-18)

114

4/24 and 9/18

6/18 and 11/12

90

130

2.0

265

0.80

212

166

46

TF-wheat-TF
system
(20 bu wheat*)

5 yr avg (2013-18)

114

12/16

5/22

187

157

2.0

311

0.80

299

182

117

Flecha-
Bulldog 505
Alfalfa#
checkerboard
mix

5 yr avg (2013-18)

114

11/19

5/20

103

154

2.2

343

0.80

275

162

113

Texoma
MaxQII
summer-
active
tall
fescue

6 yr avg (2005-11)

78

1/24

6/9

116

157

2.0

298

0.80

238

133

105

Alfagraze
alfalfa

3 yr avg (2002-04)

89

4/29

9/16

140

204

2.1

420

0.80

336

237

99

Bermudagrass

3 yr avg (2008-10)

92

5/23

8/29

98

477

0.35

167

0.8

134

87

47

Perennial systems are generally considered desirable since they do not require annual establishment (less labor and fuel) and can potentially have greater soil health benefits (less erosion and greater carbon sequestration).

It’s important to point out that the alfalfa systems planted in 2013 (alfalfa/tall fescue and alfalfa/wheat/crabgrass) had to be replanted in 2015 when Tropical Storm Bill dropped 12 inches of rain in 12 hours and the alfalfa did not survive. Therefore, we used an amortized stand life of 3.5 years in the analysis, and the trials are ongoing. These alfalfa systems are going into their fourth season, and final economic conclusions cannot be reported until the alfalfa stands decline below a critical threshold of 15 percent in mixtures and 50 percent in monoculture. However, preliminary results from a sensitivity analysis suggest alfalfa needs to persist for approximately five seasons to be economically competitive in these systems.

New Technologies

We are also developing and deploying new technology to improve efficiency in grazing research.

The photo you see above the title of this article depicts our walk-over-weighing (WOW) systems, which are designed to measure an animal’s weight each time it accesses water. The systems are equipped with wireless connectivity that transmits the date, time, pasture identification, animal electronic identification (EID) and weight the instant an animal walks over the scales. The data is transmitted to a specified computer that enables researchers and producers to access it in real time.

This system consists of Tru-Test brand components (WOW load bar/scale, platform, EID reader and associated electronics), a custom-designed solar power system, and a fabricated metal platform designed to be mobile. Each system is positioned in front of the sole water source, so each animal has to walk over the scales to access water.

Ultimately, we would like to develop decision support tools to help producers make management decisions — involving, for example, stocking rate adjustments, marketing opportunities and quick identification of sick animals — on the best-adapted and most profitable forage systems in the region. In order to accomplish this, we need to be able to estimate daily forage biomass and daily animal weight in conjunction with the integration of weather and proven crop models that will help us predict future biomass.

We plan to collaborate with a systems data modeler once these systems are fully functional to help us develop an infield real-time forage biomass growth prediction model.

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