Effect of a forage-type soybean cover crop on wheat forage production and animal performance in a continuous wheat pasture system

Beck, Paul; Hubbell, D. S.; Hess, Tom; Wilson, K.D.; Williamson, Jessica A.

doi:10.15232/pas.2017-01660

Cited by 4 publications

(6 citation statements)

References 16 publications

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“…Consistent with findings of Beck et al. (2017), the NTSF and NTCC systems had consistently higher gains relative to the CTSF and CTCC systems.…”

Section: Resultssupporting

confidence: 88%

“…There is some evidence that suggests NT establishment improves cattle performance on wheat pasture (Bowman et al, 2008). Beck et al (2017) concluded that NTSF and NTCC systems produced higher ADG and BW gain relative to a CTSF system. However, these results were found in a region with an annual precipitation greater than 127 cm.…”

Section: Introductionmentioning

confidence: 99%

“…Beck et al. (2017) concluded that NTSF and NTCC systems produced higher ADG and BW gain relative to a CTSF system. However, these results were found in a region with an annual precipitation greater than 127 cm.…”

Section: Introductionmentioning

confidence: 99%

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Profitability of grazing no‐till established winter cereal pasture and summer cover crops

Sestak¹,

Biermacher

Brorsen

et al. 2023

Agronomy Journal

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No-till establishment (NT) and cover crops (CC) are two agricultural practices promoted to reduce externalities with clean-till (CT) and fallow practices, better soil health, and improve producer profitability. Some research reports economic value for NT on water-limited cropland acres, helping to advance farmer adoption; however, economic research associated with CC is limited. This study determined the economics of NT and CC for small grain pasture grazing systems in the Southern Great Plains (SGP). Data from a 5-year, completely randomized design (CRD) grazing experiment were used in mixed-effects regression models to estimate the effects of establishment method (CT and NT) and either summer fallow (SF) or summer CC on average daily gain (ADG), steer grazing days (SGD), and total gain (TG) ha −1 .Enterprise budgeting was used to determine the relative net benefits of CTSF, NTSF, CTCC, and NTCC systems. Winter TG was the same for CTSF and NTSF systems; however, the NTSF realized 39 and 21 kg TG ha −1 more (p ≤ 0.01) than the CTCC and NTCC systems, respectively. TG on CC was 11 kg ha −1 greater (p ≤ 0.01) for NT than CT. NT realized lower costs for machinery labor and fuel than CT, giving it an economic advantage; however, revenues from grazing CC did not outweigh the additional costs of seed, fuel, and chemical applications. Overall, the NTSF system produced US$34.04 ha −1 greater net returns than the next best system. This result was not sensitive to relative changes in prices of glyphosate, labor, fuel, or cover crop seed.

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“…Consistent with findings of Beck et al. (2017), the NTSF and NTCC systems had consistently higher gains relative to the CTSF and CTCC systems.…”

Section: Resultssupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

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Profitability of grazing no‐till established winter cereal pasture and summer cover crops

Sestak¹,

Biermacher

Brorsen

et al. 2023

Agronomy Journal

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“…Soybean was initially introduced as a forage into the US in the 19th Century, but is now one of the most widely grown grain legumes in the Southern Great Plains [14]. In the last two decades, there has been increased interest from researchers in utilizing soybean as a summer forage in the US [28][29][30]. Hence the need for rapid and low-cost techniques for estimating forage quality.…”

Section: Soybeanmentioning

confidence: 99%

Predicting Forage Quality of Warm-Season Legumes by Near Infrared Spectroscopy Coupled with Machine Learning Techniques

Baath

Gowda

et al. 2020

Sensors

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Warm-season legumes have been receiving increased attention as forage resources in the southern United States and other countries. However, the near infrared spectroscopy (NIRS) technique has not been widely explored for predicting the forage quality of many of these legumes. The objective of this research was to assess the performance of NIRS in predicting the forage quality parameters of five warm-season legumes—guar (Cyamopsis tetragonoloba), tepary bean (Phaseolus acutifolius), pigeon pea (Cajanus cajan), soybean (Glycine max), and mothbean (Vigna aconitifolia)—using three machine learning techniques: partial least square (PLS), support vector machine (SVM), and Gaussian processes (GP). Additionally, the efficacy of global models in predicting forage quality was investigated. A set of 70 forage samples was used to develop species-based models for concentrations of crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), and in vitro true digestibility (IVTD) of guar and tepary bean forages, and CP and IVTD in pigeon pea and soybean. All species-based models were tested through 10-fold cross-validations, followed by external validations using 20 samples of each species. The global models for CP and IVTD of warm-season legumes were developed using a set of 150 random samples, including 30 samples for each of the five species. The global models were tested through 10-fold cross-validation, and external validation using five individual sets of 20 samples each for different legume species. Among techniques, PLS consistently performed best at calibrating (R2c = 0.94–0.98) all forage quality parameters in both species-based and global models. The SVM provided the most accurate predictions for guar and soybean crops, and global models, and both SVM and PLS performed better for tepary bean and pigeon pea forages. The global modeling approach that developed a single model for all five crops yielded sufficient accuracy (R2cv/R2v = 0.92–0.99) in predicting CP of the different legumes. However, the accuracy of predictions of in vitro true digestibility (IVTD) for the different legumes was variable (R2cv/R2v = 0.42–0.98). Machine learning algorithms like SVM could help develop robust NIRS-based models for predicting forage quality with a relatively small number of samples, and thus needs further attention in different NIRS based applications.

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“…However, grain land area surpassed forage land area by 1941 due to the demand for its oil and meal. In the last two decades, there has been renewed interest by researchers in evaluating soybean as a forage crop in the United States (Sheaffer et al, 2001;Rao and Northup, 2008;Nielsen, 2011;Beck et al, 2017). In the SGP, forage yields of soybean ranged between 1.1 and 5.4 Mg ha -1 with 150 to 190 g kg -1 CP and 740 to 790 g kg -1 in vitro digestible dry matter (IVDDM; Rao et al, 2005;MacKown et al, 2007;Rao and Northup, 2009a;Northup and Rao, 2015).…”

mentioning

confidence: 99%

Forage Potential of Summer Annual Grain Legumes in the Southern Great Plains

Baath¹,

Northup

Rocateli³

et al. 2018

Agronomy Journal

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Winter wheat (Triticum aestivum L.) and perennial warm-season grasses are the primary forage resources for grazing yearling stocker cattle (Bos taurus) in the US Southern Great Plains (SGP). However, low nutritive value of perennial grasses during mid to late summer limits high rates of growth by stocker cattle. In response, there has been a continued search for plant materials with the potential to provide forage high in crude protein (CP) and digestibility during August through September. A broad range of under-utilized legume species that are grown as grain crops in Africa, India, and South and Central America may have some capacity to serve as high quality pasture or harvested forage in the SGP. However, any crop selection must account for limitations related to unpredictable summer rainfall amounts and patterns, and the frequent occurrence of prolonged drought. Further, any selection should not create water deficits for following winter wheat, the primary forage and grain crop in the region. This article summarizes a small subset of the broad range of underutilized grain legumes (pulses) which exist worldwide and soybean [Glycine max (L.) Merr.] that may have capacity to serve as high quality forage for late-summer grazing. Bringing these crops into forage-stocker production systems could improve the overall system effectiveness, in addition to providing other ecosystem services (e.g., ground cover, grain crops).

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Effect of a forage-type soybean cover crop on wheat forage production and animal performance in a continuous wheat pasture system

Cited by 4 publications

References 16 publications

Profitability of grazing no‐till established winter cereal pasture and summer cover crops

Profitability of grazing no‐till established winter cereal pasture and summer cover crops

Predicting Forage Quality of Warm-Season Legumes by Near Infrared Spectroscopy Coupled with Machine Learning Techniques

Forage Potential of Summer Annual Grain Legumes in the Southern Great Plains

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