03289naa a2200289 a 450000100080000000500110000800800410001902200140006002400280007410000210010224501140012326000090023750006960024652017170094265300280265965300190268765300120270665300190271865300200273765300260275765300250278370000160280870000170282470000190284170000200286077301190288010628252022-03-14       2022    bl uuuu     u00u1 u    #d  a2072-42927 a10.3390/rs140408542DOI1 aIRISARRI, J.G.N.  aRemotely sensed spatiotemporal variation in crude protein of shortgrass steppe forage.h[electronic resource]  c2022  aArticle history: Received: 4 January 2022; Revised: 28 January 2022; Accepted: 9 February 2022; Published: 11 February 2022. Academic Editors: Matthew Reeves, Humberto L. Perotto-Baldivieso, Luciano A. Gonzalez and Edward C. Rhodes. Corresponding author: Irisarri, J.G.N.; Sustainable Agriculture Sciences, Rothamsted Research, North Wyke, Okehampton, United Kingdom; email:gonzalo.irisarri@rothamsted.ac.uk  --  This article belongs to the Special Issue Applications of Remote Sensing for Livestock and Grazing Land Management: https://www.mdpi.com/journal/remotesensing/special_issues/Grazing_Land_Management  --  Supplementary Materials: https://www.mdpi.com/article/10.3390/rs14040854/s1  aABSTRACT.- 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.  aCrude protein threshold  aForage quality  aMOD09A1  aRemote sensing  aRisk assessment  aSemi-arid environment  aShortgrass rangeland1 aDURANTE, M.1 aDERNER, J.D.1 aOESTERHELD, M.1 aAUGUSTINE, D.J.  tRemote Sensing, 2022, Volume 14, Issue 4, Article number 854. OPEN ACCESS. doi: https://doi.org/10.3390/rs14040854