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An update of new flood-irrigated rice cultivars in the SimulArroz model
The objective of this work was to model, in the SimulArroz model, the three flood-irrigated rice (Oryza sativa) cultivars currently most grown in the state of Rio Grande do Sul, Brazil. The experiments to calibrate and validate the model were conducted in the municipalities of Cachoeirinha, Santa Ma...
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Published in: | Pesquisa agropecuaria brasileira 2020-01, Vol.55 |
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creator | Ribas, Giovana Ghisleni Streck, Nereu Augusto Duarte Junior, Ary José Ribeiro, Bruna San Martin Rolin Pilecco, Isabela Bulegon Rossato, Ioran Guedes Richter, Gean Leonardo Bexaira, Kelin Pribs Pereira, Vladison Fogliato Zanon, Alencar Junior |
description | The objective of this work was to model, in the SimulArroz model, the three flood-irrigated rice (Oryza sativa) cultivars currently most grown in the state of Rio Grande do Sul, Brazil. The experiments to calibrate and validate the model were conducted in the municipalities of Cachoeirinha, Santa Maria, Uruguaiana, Santa Vitória do Palmar, and Cachoeira do Sul during four crop seasons. The number of leaves, phenology, aboveground dry matter biomass, and yield of each cultivar were evaluated. The results showed a slight overestimate of the R1, R4, and R9 stages; however, overall, the SimulArroz model had a good performance in simulating rice phenology for the three studied genotypes. Furthermore, the model had a reasonable accuracy in simulating aboveground dry matter and yield. The root-mean-square error (RMSE) for aboveground dry matter (leaves, stems, panicles, and grains) ranged from 0.5 to 3.0 Mg ha-1. For yield, the RMSE ranged from 0.8 to 1.3 Mg ha-1. The calibration of the SimulArroz model is efficient in simulating the growth, development, and grain yield of the most important flood-irrigated rice cultivars in Southern Brazil and can be used to estimate harvest forecast and yield potential, as well for yield gap studies.
Resumo: O objetivo deste trabalho foi modelar, no modelo SimulArroz, as três cultivares de arroz (Oryza sativa) irrigado atualmente mais cultivadas no Estado do Rio Grande do Sul. Os experimentos para calibrar e validar o modelo foram conduzidos nos municípios de Cachoeirinha, Santa Maria, Uruguaiana, Santa Vitória do Palmar e Cachoeira do Sul, durante quatro safras. Foram avaliados o número de folhas, a fenologia, a biomassa da matéria seca da parte aérea e a produtividade de cada cultivar. Os resultados mostraram uma leve superestimativa dos estádios R1, R4 e R9; no entanto, no geral, o modelo SimulArroz apresentou bom desempenho na simulação da fenologia do arroz para os três genótipos estudados. Além disso, o modelo teve uma precisão razoável em simular matéria seca da parte aérea e produtividade. A raiz quadrada do erro quadrático médio (RMSE) para matéria seca da parte aérea (folhas, caules, panículas e grãos) variou de 0,5 a 3,0 Mg ha-1. Para produtividade, a RMSE variou de 0,8 a 1,3 Mg ha-1. A calibração do modelo SimulArroz é eficiente em simular o crescimento, o desenvolvimento e a produtividade de grãos das cultivares de arroz irrigado mais importantes no Sul do Brasil e pode ser utilizada para estimar a previsão de safr |
doi_str_mv | 10.1590/s1678-3921.pab2020.v55.00865 |
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Resumo: O objetivo deste trabalho foi modelar, no modelo SimulArroz, as três cultivares de arroz (Oryza sativa) irrigado atualmente mais cultivadas no Estado do Rio Grande do Sul. Os experimentos para calibrar e validar o modelo foram conduzidos nos municípios de Cachoeirinha, Santa Maria, Uruguaiana, Santa Vitória do Palmar e Cachoeira do Sul, durante quatro safras. Foram avaliados o número de folhas, a fenologia, a biomassa da matéria seca da parte aérea e a produtividade de cada cultivar. Os resultados mostraram uma leve superestimativa dos estádios R1, R4 e R9; no entanto, no geral, o modelo SimulArroz apresentou bom desempenho na simulação da fenologia do arroz para os três genótipos estudados. Além disso, o modelo teve uma precisão razoável em simular matéria seca da parte aérea e produtividade. A raiz quadrada do erro quadrático médio (RMSE) para matéria seca da parte aérea (folhas, caules, panículas e grãos) variou de 0,5 a 3,0 Mg ha-1. Para produtividade, a RMSE variou de 0,8 a 1,3 Mg ha-1. A calibração do modelo SimulArroz é eficiente em simular o crescimento, o desenvolvimento e a produtividade de grãos das cultivares de arroz irrigado mais importantes no Sul do Brasil e pode ser utilizada para estimar a previsão de safra e o potencial de produtividade, bem como para estudos de lacunas de produtividade.</description><identifier>ISSN: 0100-204X</identifier><identifier>ISSN: 1678-3921</identifier><identifier>EISSN: 1678-3921</identifier><identifier>DOI: 10.1590/s1678-3921.pab2020.v55.00865</identifier><language>eng</language><publisher>Embrapa Secretaria de Pesquisa e Desenvolvimento; Pesquisa Agropecuária Brasileira</publisher><subject>AGRICULTURE, DAIRY & ANIMAL SCIENCE ; AGRICULTURE, MULTIDISCIPLINARY ; mathematical model ; Oryza sativa ; yield</subject><ispartof>Pesquisa agropecuaria brasileira, 2020-01, Vol.55</ispartof><rights>This work is licensed under a Creative Commons Attribution 4.0 International License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c356t-78a7a0a3015411f9e995fc3de8c4d1a33846094d26e62918054e7be30137d0233</citedby><cites>FETCH-LOGICAL-c356t-78a7a0a3015411f9e995fc3de8c4d1a33846094d26e62918054e7be30137d0233</cites><orcidid>0000-0001-9643-7749 ; 0000-0001-8767-9295 ; 0000-0002-7194-9833 ; 0000-0002-9089-8517 ; 0000-0002-2498-2227 ; 0000-0001-5546-1291 ; 0000-0002-6213-945X ; 0000-0002-2495-0823 ; 0000-0002-2681-7882 ; 0000-0001-7135-666X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,24130,27903,27904</link.rule.ids></links><search><creatorcontrib>Ribas, Giovana Ghisleni</creatorcontrib><creatorcontrib>Streck, Nereu Augusto</creatorcontrib><creatorcontrib>Duarte Junior, Ary José</creatorcontrib><creatorcontrib>Ribeiro, Bruna San Martin Rolin</creatorcontrib><creatorcontrib>Pilecco, Isabela Bulegon</creatorcontrib><creatorcontrib>Rossato, Ioran Guedes</creatorcontrib><creatorcontrib>Richter, Gean Leonardo</creatorcontrib><creatorcontrib>Bexaira, Kelin Pribs</creatorcontrib><creatorcontrib>Pereira, Vladison Fogliato</creatorcontrib><creatorcontrib>Zanon, Alencar Junior</creatorcontrib><title>An update of new flood-irrigated rice cultivars in the SimulArroz model</title><title>Pesquisa agropecuaria brasileira</title><addtitle>Pesq. agropec. bras</addtitle><description>The objective of this work was to model, in the SimulArroz model, the three flood-irrigated rice (Oryza sativa) cultivars currently most grown in the state of Rio Grande do Sul, Brazil. The experiments to calibrate and validate the model were conducted in the municipalities of Cachoeirinha, Santa Maria, Uruguaiana, Santa Vitória do Palmar, and Cachoeira do Sul during four crop seasons. The number of leaves, phenology, aboveground dry matter biomass, and yield of each cultivar were evaluated. The results showed a slight overestimate of the R1, R4, and R9 stages; however, overall, the SimulArroz model had a good performance in simulating rice phenology for the three studied genotypes. Furthermore, the model had a reasonable accuracy in simulating aboveground dry matter and yield. The root-mean-square error (RMSE) for aboveground dry matter (leaves, stems, panicles, and grains) ranged from 0.5 to 3.0 Mg ha-1. For yield, the RMSE ranged from 0.8 to 1.3 Mg ha-1. The calibration of the SimulArroz model is efficient in simulating the growth, development, and grain yield of the most important flood-irrigated rice cultivars in Southern Brazil and can be used to estimate harvest forecast and yield potential, as well for yield gap studies.
Resumo: O objetivo deste trabalho foi modelar, no modelo SimulArroz, as três cultivares de arroz (Oryza sativa) irrigado atualmente mais cultivadas no Estado do Rio Grande do Sul. Os experimentos para calibrar e validar o modelo foram conduzidos nos municípios de Cachoeirinha, Santa Maria, Uruguaiana, Santa Vitória do Palmar e Cachoeira do Sul, durante quatro safras. Foram avaliados o número de folhas, a fenologia, a biomassa da matéria seca da parte aérea e a produtividade de cada cultivar. Os resultados mostraram uma leve superestimativa dos estádios R1, R4 e R9; no entanto, no geral, o modelo SimulArroz apresentou bom desempenho na simulação da fenologia do arroz para os três genótipos estudados. Além disso, o modelo teve uma precisão razoável em simular matéria seca da parte aérea e produtividade. A raiz quadrada do erro quadrático médio (RMSE) para matéria seca da parte aérea (folhas, caules, panículas e grãos) variou de 0,5 a 3,0 Mg ha-1. Para produtividade, a RMSE variou de 0,8 a 1,3 Mg ha-1. A calibração do modelo SimulArroz é eficiente em simular o crescimento, o desenvolvimento e a produtividade de grãos das cultivares de arroz irrigado mais importantes no Sul do Brasil e pode ser utilizada para estimar a previsão de safra e o potencial de produtividade, bem como para estudos de lacunas de produtividade.</description><subject>AGRICULTURE, DAIRY & ANIMAL SCIENCE</subject><subject>AGRICULTURE, MULTIDISCIPLINARY</subject><subject>mathematical model</subject><subject>Oryza sativa</subject><subject>yield</subject><issn>0100-204X</issn><issn>1678-3921</issn><issn>1678-3921</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNo9kU9LAzEQxYMoWP98hxy87jrZZHcT8FJEa6HgoQreQjaZ1JRtU7JbRT-9u21xLgNvZh7D-xFyxyBnpYL7jlW1zLgqWL4zTQEF5F9lmQPIqjwjk__pOZkAA8gKEB-X5Krr1gBFzat6QmbTLd3vnOmRRk-3-E19G6PLQkphNaiOpmCR2n3bhy-TOhq2tP9EugybfTtNKf7STXTY3pALb9oOb0_9mrw_P709vmSL19n8cbrILC-rPqulqQ0YDqwUjHmFSpXecofSCscM51JUoIQrKqwKxSSUAusGh31eOyg4vybzo6-LZq13KWxM-tHRBH0QYlppk_pgW9ToAazzlfGiEU4ZU6sGHTYouRBSyMErP3p1NmAb9Tru03Z4Xi_HtPSY1pjpUGwU2HDwcDywKXZdQv__AAM9EtEHInrMXJ-I6IGIPhDhfw0bfew</recordid><startdate>20200101</startdate><enddate>20200101</enddate><creator>Ribas, Giovana Ghisleni</creator><creator>Streck, Nereu Augusto</creator><creator>Duarte Junior, Ary José</creator><creator>Ribeiro, Bruna San Martin Rolin</creator><creator>Pilecco, Isabela Bulegon</creator><creator>Rossato, Ioran Guedes</creator><creator>Richter, Gean Leonardo</creator><creator>Bexaira, Kelin Pribs</creator><creator>Pereira, Vladison Fogliato</creator><creator>Zanon, Alencar Junior</creator><general>Embrapa Secretaria de Pesquisa e Desenvolvimento; Pesquisa Agropecuária Brasileira</general><general>Embrapa Informação Tecnológica</general><scope>AAYXX</scope><scope>CITATION</scope><scope>GPN</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-9643-7749</orcidid><orcidid>https://orcid.org/0000-0001-8767-9295</orcidid><orcidid>https://orcid.org/0000-0002-7194-9833</orcidid><orcidid>https://orcid.org/0000-0002-9089-8517</orcidid><orcidid>https://orcid.org/0000-0002-2498-2227</orcidid><orcidid>https://orcid.org/0000-0001-5546-1291</orcidid><orcidid>https://orcid.org/0000-0002-6213-945X</orcidid><orcidid>https://orcid.org/0000-0002-2495-0823</orcidid><orcidid>https://orcid.org/0000-0002-2681-7882</orcidid><orcidid>https://orcid.org/0000-0001-7135-666X</orcidid></search><sort><creationdate>20200101</creationdate><title>An update of new flood-irrigated rice cultivars in the SimulArroz model</title><author>Ribas, Giovana Ghisleni ; Streck, Nereu Augusto ; Duarte Junior, Ary José ; Ribeiro, Bruna San Martin Rolin ; Pilecco, Isabela Bulegon ; Rossato, Ioran Guedes ; Richter, Gean Leonardo ; Bexaira, Kelin Pribs ; Pereira, Vladison Fogliato ; Zanon, Alencar Junior</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c356t-78a7a0a3015411f9e995fc3de8c4d1a33846094d26e62918054e7be30137d0233</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>AGRICULTURE, DAIRY & ANIMAL SCIENCE</topic><topic>AGRICULTURE, MULTIDISCIPLINARY</topic><topic>mathematical model</topic><topic>Oryza sativa</topic><topic>yield</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ribas, Giovana Ghisleni</creatorcontrib><creatorcontrib>Streck, Nereu Augusto</creatorcontrib><creatorcontrib>Duarte Junior, Ary José</creatorcontrib><creatorcontrib>Ribeiro, Bruna San Martin Rolin</creatorcontrib><creatorcontrib>Pilecco, Isabela Bulegon</creatorcontrib><creatorcontrib>Rossato, Ioran Guedes</creatorcontrib><creatorcontrib>Richter, Gean Leonardo</creatorcontrib><creatorcontrib>Bexaira, Kelin Pribs</creatorcontrib><creatorcontrib>Pereira, Vladison Fogliato</creatorcontrib><creatorcontrib>Zanon, Alencar Junior</creatorcontrib><collection>CrossRef</collection><collection>SciELO</collection><collection>Directory of Open Access Journals</collection><jtitle>Pesquisa agropecuaria brasileira</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ribas, Giovana Ghisleni</au><au>Streck, Nereu Augusto</au><au>Duarte Junior, Ary José</au><au>Ribeiro, Bruna San Martin Rolin</au><au>Pilecco, Isabela Bulegon</au><au>Rossato, Ioran Guedes</au><au>Richter, Gean Leonardo</au><au>Bexaira, Kelin Pribs</au><au>Pereira, Vladison Fogliato</au><au>Zanon, Alencar Junior</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An update of new flood-irrigated rice cultivars in the SimulArroz model</atitle><jtitle>Pesquisa agropecuaria brasileira</jtitle><addtitle>Pesq. agropec. bras</addtitle><date>2020-01-01</date><risdate>2020</risdate><volume>55</volume><issn>0100-204X</issn><issn>1678-3921</issn><eissn>1678-3921</eissn><abstract>The objective of this work was to model, in the SimulArroz model, the three flood-irrigated rice (Oryza sativa) cultivars currently most grown in the state of Rio Grande do Sul, Brazil. The experiments to calibrate and validate the model were conducted in the municipalities of Cachoeirinha, Santa Maria, Uruguaiana, Santa Vitória do Palmar, and Cachoeira do Sul during four crop seasons. The number of leaves, phenology, aboveground dry matter biomass, and yield of each cultivar were evaluated. The results showed a slight overestimate of the R1, R4, and R9 stages; however, overall, the SimulArroz model had a good performance in simulating rice phenology for the three studied genotypes. Furthermore, the model had a reasonable accuracy in simulating aboveground dry matter and yield. The root-mean-square error (RMSE) for aboveground dry matter (leaves, stems, panicles, and grains) ranged from 0.5 to 3.0 Mg ha-1. For yield, the RMSE ranged from 0.8 to 1.3 Mg ha-1. The calibration of the SimulArroz model is efficient in simulating the growth, development, and grain yield of the most important flood-irrigated rice cultivars in Southern Brazil and can be used to estimate harvest forecast and yield potential, as well for yield gap studies.
Resumo: O objetivo deste trabalho foi modelar, no modelo SimulArroz, as três cultivares de arroz (Oryza sativa) irrigado atualmente mais cultivadas no Estado do Rio Grande do Sul. Os experimentos para calibrar e validar o modelo foram conduzidos nos municípios de Cachoeirinha, Santa Maria, Uruguaiana, Santa Vitória do Palmar e Cachoeira do Sul, durante quatro safras. Foram avaliados o número de folhas, a fenologia, a biomassa da matéria seca da parte aérea e a produtividade de cada cultivar. Os resultados mostraram uma leve superestimativa dos estádios R1, R4 e R9; no entanto, no geral, o modelo SimulArroz apresentou bom desempenho na simulação da fenologia do arroz para os três genótipos estudados. Além disso, o modelo teve uma precisão razoável em simular matéria seca da parte aérea e produtividade. A raiz quadrada do erro quadrático médio (RMSE) para matéria seca da parte aérea (folhas, caules, panículas e grãos) variou de 0,5 a 3,0 Mg ha-1. Para produtividade, a RMSE variou de 0,8 a 1,3 Mg ha-1. A calibração do modelo SimulArroz é eficiente em simular o crescimento, o desenvolvimento e a produtividade de grãos das cultivares de arroz irrigado mais importantes no Sul do Brasil e pode ser utilizada para estimar a previsão de safra e o potencial de produtividade, bem como para estudos de lacunas de produtividade.</abstract><pub>Embrapa Secretaria de Pesquisa e Desenvolvimento; Pesquisa Agropecuária Brasileira</pub><doi>10.1590/s1678-3921.pab2020.v55.00865</doi><orcidid>https://orcid.org/0000-0001-9643-7749</orcidid><orcidid>https://orcid.org/0000-0001-8767-9295</orcidid><orcidid>https://orcid.org/0000-0002-7194-9833</orcidid><orcidid>https://orcid.org/0000-0002-9089-8517</orcidid><orcidid>https://orcid.org/0000-0002-2498-2227</orcidid><orcidid>https://orcid.org/0000-0001-5546-1291</orcidid><orcidid>https://orcid.org/0000-0002-6213-945X</orcidid><orcidid>https://orcid.org/0000-0002-2495-0823</orcidid><orcidid>https://orcid.org/0000-0002-2681-7882</orcidid><orcidid>https://orcid.org/0000-0001-7135-666X</orcidid><oa>free_for_read</oa></addata></record> |
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title | An update of new flood-irrigated rice cultivars in the SimulArroz model |
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