Remotely sensed spatiotemporal variation in crude protein of shortgrass steppe forage

• Autores: Irisarri, Jorge Gonzalo Nicolás; Durante, Martín; Derner, Justin D.; Oesterheld, Martín; Augustine, David J.
• Año de publicación: 2022
• Idioma: inglés
• Tipo de recurso: artículo
• Fuente: Remote Sens; Vol.14, no.4; art.854; http://www.mdpi.com
• Materia: CRUDE PROTEIN THRESHOLD; FORAGE QUALITY; MOD09A1; SHORTGRASS RANGELAND; REMOTE SENSING; RISK ASSESSMENT; SEMI-ARID ENVIRONMENT
• Institución: Universidad de Buenos Aires. Facultad de Agronomía

Fil: Irisarri, Jorge Gonzalo Nicolás. Rothamsted Research. Sustainable Agriculture Sciences. North Wyke, Okehampton, UK.
Fil: Durante, Martín. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Concepción del Uruguay (EEA Concepción del Uruguay). Entre Ríos, Argentina.
Fil: Durante, Martín. Instituto Nacional de Investigación Agropecuaria (INIA). Estación Experimental INIA Tacuarembó. Programa Pasturas y Forrajes. Tacuarembó, Uruguay.
Fil: Derner, Justin D. United State Department of Agriculture (USDA). Agricultural Research Service (ARS). Rangeland Resources and Systems Research Unit. Cheyenne, Wyoming, Estados Unidos.
Fil: Oesterheld, Martín. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Buenos Aires, Argentina.
Fil: Oesterheld, Martín. CONICET – Universidad de Buenos Aires. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Buenos Aires, Argentina.
Fil: Augustine, David J. United state department of agricultura (USDA). Agricultural Research Service (ARS). Rangeland Resources and Systems Research Unit. Fort Collins, Colorado, Estados Unidos.
In the Great Plains of central North America, sustainable livestock production is dependent on matching the timing of forage availability and quality with animal intake demands. Advances in remote sensing technology provide accurate information for forage quantity. However, similar efforts for forage quality are lacking. Crude protein (CP) content is one of the most relevant forage quality determinants of individual animal intake, especially below an 8% threshold for growing animals. In a set of shortgrass steppe paddocks with contrasting botanical composition, we (1) modeled the spatiotemporal variation in field estimates of CP content against seven spectral MODIS bands, and (2) used the model to assess the risk of reaching the 8% CP content threshold during the grazing season for paddocks with light, moderate, or heavy grazing intensities for the last 22 years (2000–2021). Our calibrated model explained up to 69% of the spatiotemporal variation in CP content. Different from previous investigations, our model was partially independent of NDVI, as it included the green and red portions of the spectrum as direct predictors of CP content. From 2000 to 2021, the model predicted that CP content was a limiting factor for growth of yearling cattle in 80% of the years for about 60% of the mid-May to October grazing season. The risk of forage quality being below the CP content threshold increases as the grazing season progresses, suggesting that ranchers across this rangeland region could benefit from remotely sensed CP content to proactively remove yearling cattle earlier than the traditional October date or to strategically provide supplemental protein sources to grazing cattle.
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