|
|
Registro completo
|
Biblioteca (s) : |
INIA La Estanzuela. |
Fecha : |
03/08/2021 |
Actualizado : |
02/09/2022 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
GASO, D.; DE WIT, A.; BERGER, A.; KOOISTRA, L. |
Afiliación : |
DEBORAH VIVIANA GASO MELGAR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALLARD DE WIT, Wageningen Environmental Research, Wageningen 6708 PB, The Netherlands.; ANDRES GUSTAVO BERGER RICCA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LAMMERT KOOISTRA, Laboratory of Geo-Information Science and Remote Sensing, Wageningen University and Research, Wageningen 6708 PB, Netherlands. |
Título : |
Predicting within-field soybean yield variability by coupling Sentinel-2 leaf area index with a crop growth model. |
Fecha de publicación : |
2021 |
Fuente / Imprenta : |
Agricultural and Forest Meteorology, 2021, Volumes 308-309, article 108553. OPEN ACCESS. Doi: https://doi.org/10.1016/j.agrformet.2021.108553 |
DOI : |
10.1016/j.agrformet.2021.108553 |
Idioma : |
Inglés |
Notas : |
Article history: Received 15 February 2021, Revised 3 June 2021, Accepted 9 July 2021, Available online 22 July 2021. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Contenido : |
ABSTRACT: Accurate within-field yield estimation is an essential step to conduct yield gap analysis and steer crop management towards more efficient use of resources. This study aims to develop and validate a process-based soybean model and to predict within-field yield variability by coupling leaf area index (LAI) retrieval from Sentinel-2 into the crop model. First, a soybean model is presented, which was successfully validated with field observations of total aboveground biomass, LAI and yield from seven contrasting field campaigns with strongly varying conditions. Within-field yield predictions were achieved by combining the model and the observations of LAI through an assimilation strategy. Four model parameters were chosen to optimize against the LAI curve: soil
depth, field capacity, initial LAI and nitrogen translocated from leaves to seed. Six fields were used to evaluate the methodology (21175 pixels). The accuracy assessment was conducted on a pixel-by-pixel basis using high density of information from the yield monitor. The overall accuracy quantified by the relative root mean square error (rRMSE) ranged from 28 to 51% (overall rRMSE 35.8%) across the studied fields. The Lee statistics index ranged from 0.61 to 0.71, confirming a high level of similarity between observed and simulated yield maps. Therefore, the methodology was capable of representing the observed spatial patterns of yield. Furthermore, the high consistency of the optimized WHC reflects the value of the assimilation data strategy to spatialize this relevant characteristic. Some challenges were identified for further study to reduce the sources of uncertainty and improve accuracy: i) the inability of the model to reallocate biomass by simulating plant response to source limitation, ii) the generalization of empirical algorithms to retrieve LAI, and iii) the exploration of an updating method as an assimilation strategy to overcome discrepancy between simulated and retrieved LAI. MenosABSTRACT: Accurate within-field yield estimation is an essential step to conduct yield gap analysis and steer crop management towards more efficient use of resources. This study aims to develop and validate a process-based soybean model and to predict within-field yield variability by coupling leaf area index (LAI) retrieval from Sentinel-2 into the crop model. First, a soybean model is presented, which was successfully validated with field observations of total aboveground biomass, LAI and yield from seven contrasting field campaigns with strongly varying conditions. Within-field yield predictions were achieved by combining the model and the observations of LAI through an assimilation strategy. Four model parameters were chosen to optimize against the LAI curve: soil
depth, field capacity, initial LAI and nitrogen translocated from leaves to seed. Six fields were used to evaluate the methodology (21175 pixels). The accuracy assessment was conducted on a pixel-by-pixel basis using high density of information from the yield monitor. The overall accuracy quantified by the relative root mean square error (rRMSE) ranged from 28 to 51% (overall rRMSE 35.8%) across the studied fields. The Lee statistics index ranged from 0.61 to 0.71, confirming a high level of similarity between observed and simulated yield maps. Therefore, the methodology was capable of representing the observed spatial patterns of yield. Furthermore, the high consistency of the optimized WHC reflects the valu... Presentar Todo |
Palabras claves : |
Crop growth model; Data assimilation; Sentinel-2; Soybean; Yield prediction. |
Thesagro : |
Soja. |
Asunto categoría : |
F01 Cultivo |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16670/1/1-s2.0-S0168192321002379-main.pdf
https://www.sciencedirect.com/science/article/pii/S0168192321002379/pdfft?md5=c4c224be450c53eba73eada140b04cc2&pid=1-s2.0-S0168192321002379-main.pdf
|
Marc : |
LEADER 03060naa a2200253 a 4500 001 1062331 005 2022-09-02 008 2021 bl uuuu u00u1 u #d 024 7 $a10.1016/j.agrformet.2021.108553$2DOI 100 1 $aGASO, D. 245 $aPredicting within-field soybean yield variability by coupling Sentinel-2 leaf area index with a crop growth model.$h[electronic resource] 260 $c2021 500 $aArticle history: Received 15 February 2021, Revised 3 June 2021, Accepted 9 July 2021, Available online 22 July 2021. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). 520 $aABSTRACT: Accurate within-field yield estimation is an essential step to conduct yield gap analysis and steer crop management towards more efficient use of resources. This study aims to develop and validate a process-based soybean model and to predict within-field yield variability by coupling leaf area index (LAI) retrieval from Sentinel-2 into the crop model. First, a soybean model is presented, which was successfully validated with field observations of total aboveground biomass, LAI and yield from seven contrasting field campaigns with strongly varying conditions. Within-field yield predictions were achieved by combining the model and the observations of LAI through an assimilation strategy. Four model parameters were chosen to optimize against the LAI curve: soil depth, field capacity, initial LAI and nitrogen translocated from leaves to seed. Six fields were used to evaluate the methodology (21175 pixels). The accuracy assessment was conducted on a pixel-by-pixel basis using high density of information from the yield monitor. The overall accuracy quantified by the relative root mean square error (rRMSE) ranged from 28 to 51% (overall rRMSE 35.8%) across the studied fields. The Lee statistics index ranged from 0.61 to 0.71, confirming a high level of similarity between observed and simulated yield maps. Therefore, the methodology was capable of representing the observed spatial patterns of yield. Furthermore, the high consistency of the optimized WHC reflects the value of the assimilation data strategy to spatialize this relevant characteristic. Some challenges were identified for further study to reduce the sources of uncertainty and improve accuracy: i) the inability of the model to reallocate biomass by simulating plant response to source limitation, ii) the generalization of empirical algorithms to retrieve LAI, and iii) the exploration of an updating method as an assimilation strategy to overcome discrepancy between simulated and retrieved LAI. 650 $aSoja 653 $aCrop growth model 653 $aData assimilation 653 $aSentinel-2 653 $aSoybean 653 $aYield prediction 700 1 $aDE WIT, A. 700 1 $aBERGER, A. 700 1 $aKOOISTRA, L. 773 $tAgricultural and Forest Meteorology, 2021, Volumes 308-309, article 108553. OPEN ACCESS. Doi: https://doi.org/10.1016/j.agrformet.2021.108553
Descargar
Esconder MarcPresentar Marc Completo |
Registro original : |
INIA La Estanzuela (LE) |
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
|
Registro completo
|
Biblioteca (s) : |
INIA Tacuarembó. |
Fecha actual : |
21/02/2014 |
Actualizado : |
22/11/2019 |
Tipo de producción científica : |
Actividades de Difusión |
Autor : |
INIA TACUAREMBÓ |
Afiliación : |
ESTACIÓN EXPERIMENTAL DEL NORTE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Sanidad forestal. |
Complemento del título : |
Seminario técnico, 26 noviembre, Tacuarembó, 2009. |
Fecha de publicación : |
2009 |
Fuente / Imprenta : |
Tacuarembó (Uruguay): INIA, 2009. |
Páginas : |
72 p. |
Serie : |
(INIA Serie Actividades de Difusión ; 594) |
Idioma : |
Español |
Contenido : |
RESULTADOS DEL PRIMER AÑO DEL MONITOREO CONTINUO DE Thaumastocoris peregrinus EN EUFORES. MONITOREO DE Thaumastocoris peregrinus. ANTECEDENTES,
SITUACION ACTUAL Y RESULTADOS DE FORESTAL ORIENTAL. INTERACCIÓN BIOLÓGICA DEL MONTE NATIVO Y LAS PLANTACIONES EXÓTICAS: EL CASO DE LAS ENFERMEDADES EN MIRTÁCEAS. PATOGENICIDAD DE Coniothyrium (Kirramyces gauchensis) EN Eucalyptus grandis. EFECTO DE LA FERTILIZACION CON N, P Y B EN EL NIVEL DE DAÑO DE Mycosphaerellas EN Eucalyptus globulus. RELEVAMIENTO SANITARIO DE OTOÑO EN PLANTACIONES JÓVENES DE Eucalyptus globulus y Eucalyptus dunnii en el Sureste y Litoral Oeste. |
Palabras claves : |
EUCALIPTUS; FOREST AND FORESTRY; MIRTÁCEAS; THAUMASTOCORIS PEREGRINUS. |
Thesagro : |
SANIDAD DE LOS BOSQUES. |
Asunto categoría : |
K70 Daños al bosque y protección forestal |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/2332/1/14432041209154239.pdf
|
Marc : |
LEADER 01132nam a2200193 a 4500 001 1023314 005 2019-11-22 008 2009 bl uuuu u00u1 u #d 100 1 $aINIA TACUAREMBÓ 245 $aSanidad forestal. 260 $aTacuarembó (Uruguay): INIA$c2009 300 $a72 p. 490 $a(INIA Serie Actividades de Difusión ; 594) 520 $aRESULTADOS DEL PRIMER AÑO DEL MONITOREO CONTINUO DE Thaumastocoris peregrinus EN EUFORES. MONITOREO DE Thaumastocoris peregrinus. ANTECEDENTES, SITUACION ACTUAL Y RESULTADOS DE FORESTAL ORIENTAL. INTERACCIÓN BIOLÓGICA DEL MONTE NATIVO Y LAS PLANTACIONES EXÓTICAS: EL CASO DE LAS ENFERMEDADES EN MIRTÁCEAS. PATOGENICIDAD DE Coniothyrium (Kirramyces gauchensis) EN Eucalyptus grandis. EFECTO DE LA FERTILIZACION CON N, P Y B EN EL NIVEL DE DAÑO DE Mycosphaerellas EN Eucalyptus globulus. RELEVAMIENTO SANITARIO DE OTOÑO EN PLANTACIONES JÓVENES DE Eucalyptus globulus y Eucalyptus dunnii en el Sureste y Litoral Oeste. 650 $aSANIDAD DE LOS BOSQUES 653 $aEUCALIPTUS 653 $aFOREST AND FORESTRY 653 $aMIRTÁCEAS 653 $aTHAUMASTOCORIS PEREGRINUS
Descargar
Esconder MarcPresentar Marc Completo |
Registro original : |
INIA Tacuarembó (TBO) |
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
Expresión de búsqueda válido. Check! |
|
|