Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage
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 forag...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/4/854 |
| _version_ | 1797476794879705088 |
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| author | Jorge Gonzalo N. Irisarri Martin Durante Justin D. Derner Martin Oesterheld David J. Augustine |
| author_facet | Jorge Gonzalo N. Irisarri Martin Durante Justin D. Derner Martin Oesterheld David J. Augustine |
| author_sort | Jorge Gonzalo N. Irisarri |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T21:08:46Z |
| format | Article |
| id | doaj.art-0653115f32164beea3013402b50b69d9 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T21:08:46Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-0653115f32164beea3013402b50b69d92023-11-23T21:53:10ZengMDPI AGRemote Sensing2072-42922022-02-0114485410.3390/rs14040854Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe ForageJorge Gonzalo N. Irisarri0Martin Durante1Justin D. Derner2Martin Oesterheld3David J. Augustine4Sustainable Agriculture Sciences, Rothamsted Research, North Wyke, Okehampton EX20 2SB, UKEstación Experimental Agropecuaria Concepción del Uruguay, Instituto Nacional de Tecnología Agropecuaria (INTA), Concepcion del Uruguay 3260, ArgentinaUSDA-Agricultural Research Service (ARS), Rangeland Resources and Systems Research Unit, Cheyenne, WY 82009, USAInstituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura, Buenos Aires 1417, ArgentinaUSDA-Agricultural Research Service (ARS), Rangeland Resources and Systems Research Unit, Fort Collins, CO 80526, USAIn 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.https://www.mdpi.com/2072-4292/14/4/854crude protein thresholdforage qualityMOD09A1shortgrass rangelandremote sensingrisk assessment |
| spellingShingle | Jorge Gonzalo N. Irisarri Martin Durante Justin D. Derner Martin Oesterheld David J. Augustine Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage Remote Sensing crude protein threshold forage quality MOD09A1 shortgrass rangeland remote sensing risk assessment |
| title | Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage |
| title_full | Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage |
| title_fullStr | Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage |
| title_full_unstemmed | Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage |
| title_short | Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage |
| title_sort | remotely sensed spatiotemporal variation in crude protein of shortgrass steppe forage |
| topic | crude protein threshold forage quality MOD09A1 shortgrass rangeland remote sensing risk assessment |
| url | https://www.mdpi.com/2072-4292/14/4/854 |
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