Agrometeorological models for estimating sweet cassava yield
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| Natura: | Artículo científico |
| Lingua: | en |
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Universidade Federal de Goiás
2018
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| _version_ | 1876423424038928384 |
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| author | Victor Brunini Moreto |
| author_facet | Victor Brunini Moreto |
| contents | Agrometeorological models for estimating sweet cassava yield Victor Brunini Moreto Lucas Eduardo de Oliveira Aparecido Glauco de Souza Rolim José Reinaldo da Silva Cabral de Moraes Agrociencias climatology crop modeling Manihot esculenta Brazil 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. 2018 artículo científico 1517-6398 https://www.redalyc.org/articulo.oa?id=253067973006 https://www.redalyc.org/journal/2530/253067973006/ https://www.redalyc.org/journal/2530/253067973006/html/ https://www.redalyc.org/journal/2530/253067973006/253067973006.epub https://www.redalyc.org/journal/2530/253067973006/movil en http://www.redalyc.org/revista.oa?id=2530 Pesquisa Agropecuária Tropical application/pdf Universidade Federal de Goiás Pesquisa Agropecuária Tropical (Brasil) Num.1 Vol.48 |
| format | Artículo científico |
| id | redalyc_253067973006 |
| institution | Redalyc |
| language | en |
| publishDate | 2018 |
| publisher | Universidade Federal de Goiás |
| spellingShingle | Agrometeorological models for estimating sweet cassava yield Victor Brunini Moreto Agrociencias climatology crop modeling Manihot esculenta Agrometeorological models for estimating sweet cassava yield Victor Brunini Moreto Lucas Eduardo de Oliveira Aparecido Glauco de Souza Rolim José Reinaldo da Silva Cabral de Moraes Agrociencias climatology crop modeling Manihot esculenta Brazil 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. 2018 artículo científico 1517-6398 https://www.redalyc.org/articulo.oa?id=253067973006 https://www.redalyc.org/journal/2530/253067973006/ https://www.redalyc.org/journal/2530/253067973006/html/ https://www.redalyc.org/journal/2530/253067973006/253067973006.epub https://www.redalyc.org/journal/2530/253067973006/movil en http://www.redalyc.org/revista.oa?id=2530 Pesquisa Agropecuária Tropical application/pdf Universidade Federal de Goiás Pesquisa Agropecuária Tropical (Brasil) Num.1 Vol.48 |
| title | Agrometeorological models for estimating sweet cassava yield |
| topic | Agrociencias climatology crop modeling Manihot esculenta |
| url | https://www.redalyc.org/articulo.oa?id=253067973006 https://www.redalyc.org/journal/2530/253067973006/ https://www.redalyc.org/journal/2530/253067973006/html/ https://www.redalyc.org/journal/2530/253067973006/253067973006.epub https://www.redalyc.org/journal/2530/253067973006/movil |