2020
DOI: 10.1016/j.agee.2020.106917
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Tree species effects on understory forage productivity and microclimate in a silvopasture of the Southeastern USA

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Cited by 27 publications
(15 citation statements)
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“…Samples were scanned with a Foss NIRS Model 6500 (Foss North America) and NIRS model development was performed using a data analysis pipeline written in R environment (R Core Team, 2016). The pipeline was previously used in the successful development of NIRS models to determine forage nutritive value of native warm‐season grasses and bermudagrass (Bekewe et al., 2019; Castillo et al., 2020), and to compare predictions among benchtop and handheld NIRS devices (Acosta et al., 2020). To obtain a calibration for CP and ADF, a total of 147 samples (72 samples selected from this trial + 75 samples from bermudagrass trials previously conducted across North Carolina) were assembled into a library, in which both laboratory analyses and NIRS scans were available.…”
Section: Methodsmentioning
confidence: 99%
“…Samples were scanned with a Foss NIRS Model 6500 (Foss North America) and NIRS model development was performed using a data analysis pipeline written in R environment (R Core Team, 2016). The pipeline was previously used in the successful development of NIRS models to determine forage nutritive value of native warm‐season grasses and bermudagrass (Bekewe et al., 2019; Castillo et al., 2020), and to compare predictions among benchtop and handheld NIRS devices (Acosta et al., 2020). To obtain a calibration for CP and ADF, a total of 147 samples (72 samples selected from this trial + 75 samples from bermudagrass trials previously conducted across North Carolina) were assembled into a library, in which both laboratory analyses and NIRS scans were available.…”
Section: Methodsmentioning
confidence: 99%
“…Model development was performed using a data analysis pipeline written in R environment (R Core Team, 2016). The pipeline was previously used in the successful development of NIR models to determine chemical properties of wood (Hodge, Acosta, Unda, Woodbridge, & Mansfield, 2018) and nutritive value of switchgrass (Bekewe, Castillo, Acosta, & Rivera, 2019) and a mixture of native warm‐season grasses (Castillo, Tiezzi, & Franzluebbers, 2020). The pipeline has two separate phases: (a) transformations and outlier detection and (b) model training, cross‐validation, and prediction of new observations.…”
Section: Methodsmentioning
confidence: 99%
“…It indirectly affects the food crop production system in most parts of the country which is sustained on manure and other benefits of livestock farming. The policy destroys silvopasture-based livestock farming systems which are considered nature-based solutions and climate-smart farming even in developed countries [98,99]. The silvopasture system sequestrates carbon on-farm, reduces carbon emission associated with fertilizer application, and hedges pasture and livestock from extreme climatic variabilities.…”
Section: Weaknesses In Long Term Plansmentioning
confidence: 99%