Agrometeorological models for estimating sweet cassava yield

dc.creatorVictor Brunini Moreto
dc.creatorLucas Eduardo de Oliveira Aparecido
dc.creatorGlauco de Souza Rolim
dc.creatorJosé Reinaldo da Silva Cabral de Moraes
dc.date2018
dc.date.accessioned2026-07-07T04:30:10Z
dc.descriptionBrazil is the fourth largest producer of cassava in the world, with climate conditions being the main factor regulating its production. This study aimed to develop agrometeorological models to estimate the sweet cassava yield for the São Paulo state, as well as to identify which climatic variables have more influence on yield. The models were built with multiple linear regression and classified by the following statistical indexes: lower mean absolute percentage error, higher adjusted determination coefficient and significance (p-value < 0.05). It was observed that the mean air temperature has a great influence on the sweet cassava yield during the whole cycle for all regions in the state. Water deficit and soil water storage were the most influential variables at the beginning and final stages. The models accuracy ranged in 3.11 %, 6.40 %, 6.77 % and 7.15 %, respectively for Registro, Mogi Mirim, Assis and Jaboticabal.
dc.formatapplication/pdf
dc.identifier1517-6398
dc.identifierhttps://www.redalyc.org/articulo.oa?id=253067973006
dc.identifierhttps://www.redalyc.org/journal/2530/253067973006/
dc.identifierhttps://www.redalyc.org/journal/2530/253067973006/html/
dc.identifierhttps://www.redalyc.org/journal/2530/253067973006/253067973006.epub
dc.identifierhttps://www.redalyc.org/journal/2530/253067973006/movil
dc.identifier.urihttp://hdl.handle.net/123456789/463356
dc.languageen
dc.publisherUniversidade Federal de Goiás
dc.relationhttp://www.redalyc.org/revista.oa?id=2530
dc.rightsPesquisa Agropecuária Tropical
dc.sourcePesquisa Agropecuária Tropical (Brasil) Num.1 Vol.48
dc.subjectAgrociencias
dc.titleAgrometeorological models for estimating sweet cassava yield
dc.typeartículo científico

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