Application of the JULES-crop model and agrometeorological indicators for forecasting off-season maize yield in Brazil

A - Papers appearing in refereed journals

Prudente Junior, A. C., Vianna, M. S., Willians, K., Galdos, M. and Marin, F. R. 2024. Application of the JULES-crop model and agrometeorological indicators for forecasting off-season maize yield in Brazil. Heliyon. 10 (8), p. e29555. https://doi.org/10.1016/j.heliyon.2024.e29555

AuthorsPrudente Junior, A. C., Vianna, M. S., Willians, K., Galdos, M. and Marin, F. R.
Abstract

Zea mays L is a crucial crop for Brazil, ranking second in terms of production and sixth in terms of exports. In Brazil, the second season, or off-season, accounts for 80 % of the overall maize output, which primarily occurs after the soybean main season. A maize yield forecast model for the off-season was developed and implemented throughout Brazilian territory due to its importance to the country's economy and food security. The model was built using multiple linear regressions that connected outputs simulated from a land surface model used in large-scale analysis for agriculture (JULES-crop), to agrometeorological indicators. The application of the developed model occurred every 10 days from the sowing until the maturation. A comparison of the forecasting model was verified with the official off-season maize yields for the years 2003–2016. Agrometeorological indicators during the reproductive phase accounted for 60 % of the interannual variability in maize production. When outputs simulated by JULES-crop were included, the forecasting model achieved Nash-Sutcliffe modeling efficiency (EF) of 0.77 in the maturation and EF = 0.72 in the filling-grain stage, suggesting that this approach can generate useful predictions for final maize yield beginning on the 80th day of the cycle. Outputs of JULES crop enhanced modeling performance during the vegetative stage, reducing the standard deviation error in prediction from 0.59 to 0.49 Mg ha−1

KeywordsZea mays L.; Yield forecast; Large-scale analysis
Year of Publication2024
JournalHeliyon
Journal citation10 (8), p. e29555
Digital Object Identifier (DOI)https://doi.org/10.1016/j.heliyon.2024.e29555
Open accessPublished as ‘gold’ (paid) open access
Publisher's version
Output statusPublished
Publication dates
Online11 Apr 2024
Publication process dates
Accepted10 Apr 2024
PublisherElsevier

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