Improving crop yield prediction accuracy by embedding phenological heterogeneity into model parameter sets

Simone Bregaglio, Fabrizio Ginaldi, Elisabetta Raparelli, Gianni Fila and Sofia Bajocco

Agricultural Systems, 2023, vol. 209, issue C

Abstract: The assimilation of Remote Sensing (RS) data into crop models improves the accuracy of yield predictions by considering crop growth dynamics and their spatial heterogeneity due to the different management practices and environmental conditions.

Keywords: MODIS; Normalized Difference Vegetation Index; WOFOST_GT; Downhill simplex; Agrophenotype; Yield prediction (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:agisys:v:209:y:2023:i:c:s0308521x23000719

DOI: 10.1016/j.agsy.2023.103666

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