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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
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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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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INIA Las Brujas (LB) |
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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 actual : |
26/02/2021 |
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Actualizado : |
10/08/2021 |
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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 : |
BAETHGEN, W.E.; PARTON, W.P-; RUBIO, V.; KELLY, R.H.; LUTZ, S. |
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Afiliación : |
WALTER E. BAETHGEN, International Research Institute for Climate and Society, The Earth Institute, Columbia University, New York, USA.; WILLIAM J. PARTON, Natural Resource Ecology Lab, Colorado State University, Fort Collins, Colorado, USA.; VALENTINA RUBIO DELLEPIANE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ROBIN H. KELLY, Natural Resource Ecology Lab, Colorado State University, Fort Collins, Colorado, USA.; SUSAN LUTZ, Natural Resource Ecology Lab, Colorado State University, Fort Collins, Colorado, USA. |
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Título : |
Ecosystem dynamics of crop-pasture rotations in a fifty-year field experiment in Southern South America: Century model and field results. |
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Fecha de publicación : |
2021 |
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Fuente / Imprenta : |
Soil Science Society of America Journal, Volume 85, Issue 2, Pages 423-437, March/April 2021. DOI: https://doi.org/10.1002/saj2.20204 |
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DOI : |
doi.org/10.1002/saj2.20204 |
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Idioma : |
Inglés |
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Notas : |
Article History: Accepted manuscript online: 26 November 2020; Manuscript accepted: 18 November 2020; Manuscript revised: 02 November 2020 ; Manuscript received: 12 February 2020; Published online: 24 March 2021. |
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Contenido : |
Abstract:
The Century model was used to simulate soil carbon (C) and nitrogen (N) cycling, and crop production dynamics in an ongoing field experiment in Uruguay (started in 1963). The model was calibrated using observed data from three treatments (crop or crop?pasture rotations) and validated with a fourth treatment. The model correctly predicted the impact of different treatments on microbial biomass, N mineralization, soil respiration, and crop yields. The model and observed data show that soil respiration, N mineralization, soil C, and crop yields increase with increasing plant derived C inputs caused by increasing the frequency of pastures in the rotations. This is one of the first papers which show the strong positive correlation of observed soil C with plant C soil inputs to field?observed microbial biomass, soil respiration, and N mineralization. The results also showed that reducing tillage and transitioning to a no?till system increased soil C and reduced soil erosion. The main path of soil C losses was heterotrophic microbial respiration which accounted for 66% of the total C lost in a continuous crop rotation and no fertilizers, 71% in a continuous crop rotation with fertilizers, and 86% in a crop?pasture rotation with fertilizers. Model results from a degraded cropping system showed that adding grass/clover pastures greatly increased plant production and soil C, while reducing the frequency of grass/clover pastures in high?fertility cropping systems from 50% of the time to 25% reduces crop yields and soil C. Including cover crops substantially increases crop production and maintains soil C in high fertility and degraded cropping systems MenosAbstract:
The Century model was used to simulate soil carbon (C) and nitrogen (N) cycling, and crop production dynamics in an ongoing field experiment in Uruguay (started in 1963). The model was calibrated using observed data from three treatments (crop or crop?pasture rotations) and validated with a fourth treatment. The model correctly predicted the impact of different treatments on microbial biomass, N mineralization, soil respiration, and crop yields. The model and observed data show that soil respiration, N mineralization, soil C, and crop yields increase with increasing plant derived C inputs caused by increasing the frequency of pastures in the rotations. This is one of the first papers which show the strong positive correlation of observed soil C with plant C soil inputs to field?observed microbial biomass, soil respiration, and N mineralization. The results also showed that reducing tillage and transitioning to a no?till system increased soil C and reduced soil erosion. The main path of soil C losses was heterotrophic microbial respiration which accounted for 66% of the total C lost in a continuous crop rotation and no fertilizers, 71% in a continuous crop rotation with fertilizers, and 86% in a crop?pasture rotation with fertilizers. Model results from a degraded cropping system showed that adding grass/clover pastures greatly increased plant production and soil C, while reducing the frequency of grass/clover pastures in high?fertility cropping systems from 50% of ... Presentar Todo |
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Palabras claves : |
CROP PASTURE ROTATION; CROPPING SYSTEMS; GRASS-CLOVER PASTURES; HIGH FERTILITY. |
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Thesagro : |
CICLO DEL CARBONO; CICLO DEL NITROGENO; ECOSISTEMAS; SUELOS. |
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Asunto categoría : |
-- |
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Marc : |
LEADER 02844naa a2200289 a 4500
001 1061775
005 2021-08-10
008 2021 bl uuuu u00u1 u #d
024 7 $adoi.org/10.1002/saj2.20204$2DOI
100 1 $aBAETHGEN, W.E.
245 $aEcosystem dynamics of crop-pasture rotations in a fifty-year field experiment in Southern South America$bCentury model and field results.$h[electronic resource]
260 $c2021
500 $aArticle History: Accepted manuscript online: 26 November 2020; Manuscript accepted: 18 November 2020; Manuscript revised: 02 November 2020 ; Manuscript received: 12 February 2020; Published online: 24 March 2021.
520 $aAbstract: The Century model was used to simulate soil carbon (C) and nitrogen (N) cycling, and crop production dynamics in an ongoing field experiment in Uruguay (started in 1963). The model was calibrated using observed data from three treatments (crop or crop?pasture rotations) and validated with a fourth treatment. The model correctly predicted the impact of different treatments on microbial biomass, N mineralization, soil respiration, and crop yields. The model and observed data show that soil respiration, N mineralization, soil C, and crop yields increase with increasing plant derived C inputs caused by increasing the frequency of pastures in the rotations. This is one of the first papers which show the strong positive correlation of observed soil C with plant C soil inputs to field?observed microbial biomass, soil respiration, and N mineralization. The results also showed that reducing tillage and transitioning to a no?till system increased soil C and reduced soil erosion. The main path of soil C losses was heterotrophic microbial respiration which accounted for 66% of the total C lost in a continuous crop rotation and no fertilizers, 71% in a continuous crop rotation with fertilizers, and 86% in a crop?pasture rotation with fertilizers. Model results from a degraded cropping system showed that adding grass/clover pastures greatly increased plant production and soil C, while reducing the frequency of grass/clover pastures in high?fertility cropping systems from 50% of the time to 25% reduces crop yields and soil C. Including cover crops substantially increases crop production and maintains soil C in high fertility and degraded cropping systems
650 $aCICLO DEL CARBONO
650 $aCICLO DEL NITROGENO
650 $aECOSISTEMAS
650 $aSUELOS
653 $aCROP PASTURE ROTATION
653 $aCROPPING SYSTEMS
653 $aGRASS-CLOVER PASTURES
653 $aHIGH FERTILITY
700 1 $aPARTON, W.P-
700 1 $aRUBIO, V.
700 1 $aKELLY, R.H.
700 1 $aLUTZ, S.
773 $tSoil Science Society of America Journal, Volume 85, Issue 2, Pages 423-437, March/April 2021. DOI: https://doi.org/10.1002/saj2.20204
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