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 | Acceso al texto completo restringido a Biblioteca INIA La Estanzuela. Por información adicional contacte bib_le@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
21/02/2014 |
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Actualizado : |
20/02/2018 |
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Tipo de producción científica : |
Abstracts/Resúmenes |
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Autor : |
CASTELLS, M.; SCHILD, C.; CAFFARENA, D.; GIANNITTI, F.; FRAGA, M.; RIET-CORREA, F.; VICTORIA, M.; COLINA, R. |
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Afiliación : |
CARLOS SCHILD, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; RUBEN DARÍO CAFFARENA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FEDERICO GIANNITTI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARTIN FRAGA COTELO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FRANKLIN RIET-CORREA AMARAL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Drinking water: a potential vehicle for rotavirus transmission in neonate calves. |
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Fecha de publicación : |
2016 |
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Fuente / Imprenta : |
In: LATIN AMERICAN SYMPOSIUM OF ENVIRONMENTAL VIROLOGY, 3a.,Salta, Argentina, 2016. |
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Idioma : |
Inglés |
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Thesagro : |
ROTAVIRUS DIARREA DE TERNEROS; TERNEROS; VIRUS. |
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Asunto categoría : |
L73 Enfermedades de los animales |
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Marc : |
LEADER 00665nam a2200217 a 4500
001 1049608
005 2018-02-20
008 2016 bl uuuu u01u1 u #d
100 1 $aCASTELLS, M.
245 $aDrinking water$ba potential vehicle for rotavirus transmission in neonate calves.$h[electronic resource]
260 $aIn: LATIN AMERICAN SYMPOSIUM OF ENVIRONMENTAL VIROLOGY, 3a.,Salta, Argentina$c2016
650 $aROTAVIRUS DIARREA DE TERNEROS
650 $aTERNEROS
650 $aVIRUS
700 1 $aSCHILD, C.
700 1 $aCAFFARENA, D.
700 1 $aGIANNITTI, F.
700 1 $aFRAGA, M.
700 1 $aRIET-CORREA, F.
700 1 $aVICTORIA, M.
700 1 $aCOLINA, R.
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Registro original : |
INIA La Estanzuela (LE) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
14/03/2022 |
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Actualizado : |
14/03/2022 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
IRISARRI, J.G.N.; DURANTE, M.; DERNER, J.D.; OESTERHELD, M.; AUGUSTINE, D.J. |
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Afiliación : |
JORGE GONZALO N. IRISARRI, Sustainable Agriculture Sciences, Rothamsted Research, North Wyke, Okehampton EX20 2SB, UK; MARTÍN DURANTE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Estación Experimental Agropecuaria Concepción del Uruguay, Instituto Nacional de Tecnología Agropecuaria (INTA), Concepcion del Uruguay 3260, Argentina; JUSTIN D. DERNER, USDA-Agricultural Research Service (ARS), Rangeland Resources and Systems Research Unit, Cheyenne, WY 82009, USA; MARTIN OESTERHELD, Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura, Buenos Aires 1417, Argentina; DAVID J. AUGUSTINE, USDA-Agricultural Research Service (ARS), Rangeland Resources and Systems Research Unit, Fort Collins, CO 80526, USA. |
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Título : |
Remotely sensed spatiotemporal variation in crude protein of shortgrass steppe forage. |
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Fecha de publicación : |
2022 |
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Fuente / Imprenta : |
Remote Sensing, 2022, Volume 14, Issue 4, Article number 854. OPEN ACCESS. doi: https://doi.org/10.3390/rs14040854 |
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ISSN : |
2072-4292 |
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DOI : |
10.3390/rs14040854 |
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Idioma : |
Inglés |
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Notas : |
Article 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 |
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Contenido : |
ABSTRACT.- 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. MenosABSTRACT.- 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 range... Presentar Todo |
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Palabras claves : |
Crude protein threshold; Forage quality; MOD09A1; Remote sensing; Risk assessment; Semi-arid environment; Shortgrass rangeland. |
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Asunto categoría : |
-- |
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URL : |
https://www.mdpi.com/2072-4292/14/4/854/pdf
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Marc : |
LEADER 03289naa a2200289 a 4500
001 1062825
005 2022-03-14
008 2022 bl uuuu u00u1 u #d
022 $a2072-4292
024 7 $a10.3390/rs14040854$2DOI
100 1 $aIRISARRI, J.G.N.
245 $aRemotely sensed spatiotemporal variation in crude protein of shortgrass steppe forage.$h[electronic resource]
260 $c2022
500 $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
520 $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.
653 $aCrude protein threshold
653 $aForage quality
653 $aMOD09A1
653 $aRemote sensing
653 $aRisk assessment
653 $aSemi-arid environment
653 $aShortgrass rangeland
700 1 $aDURANTE, M.
700 1 $aDERNER, J.D.
700 1 $aOESTERHELD, M.
700 1 $aAUGUSTINE, D.J.
773 $tRemote Sensing, 2022, Volume 14, Issue 4, Article number 854. OPEN ACCESS. doi: https://doi.org/10.3390/rs14040854
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