Román Montaña, Á. Roco-Videla, N. Maureira-Carsalade, Ana Nieves, Sergio Flores
{"title":"应用响应面方法优化玉米产量","authors":"Román Montaña, Á. Roco-Videla, N. Maureira-Carsalade, Ana Nieves, Sergio Flores","doi":"10.47280/revfacagron(luz).v40.n4.04","DOIUrl":null,"url":null,"abstract":"The objective of this study was based on the application of the response surface methodology (RSM) for yield optimization in maize (Zea mays L.). The hybrid INIA SQ-1 was used, and the Response Surface Methodology was used using the Box-Behnken design (DBB), with which the following factors were evaluated: plant density, nitrogen (N) dose and phosphorus (P) dose at three levels each; for the optimization of the response variables: “yield” (kg.ha-1) and the “number of grains per square meter” (g.m2). The response surface method provided a statistically validated predictive model, which through adjustments was adapted to an established optimization process. For the variable “yield”, a maximum response was found with the application of 150 Kg.ha-1 of N and 90 kg.ha-1 of P. In relation to the number of grains per square meter (g.m2), the optimum was obtained using 75,000 plants.ha-1 and an applied dose of 150 kg.ha-1.","PeriodicalId":509934,"journal":{"name":"Revista de la Facultad de Agronomía, Universidad del Zulia","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of the response surface methodology for yield optimization in maize (Zea mays L.)\",\"authors\":\"Román Montaña, Á. Roco-Videla, N. Maureira-Carsalade, Ana Nieves, Sergio Flores\",\"doi\":\"10.47280/revfacagron(luz).v40.n4.04\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The objective of this study was based on the application of the response surface methodology (RSM) for yield optimization in maize (Zea mays L.). The hybrid INIA SQ-1 was used, and the Response Surface Methodology was used using the Box-Behnken design (DBB), with which the following factors were evaluated: plant density, nitrogen (N) dose and phosphorus (P) dose at three levels each; for the optimization of the response variables: “yield” (kg.ha-1) and the “number of grains per square meter” (g.m2). The response surface method provided a statistically validated predictive model, which through adjustments was adapted to an established optimization process. For the variable “yield”, a maximum response was found with the application of 150 Kg.ha-1 of N and 90 kg.ha-1 of P. In relation to the number of grains per square meter (g.m2), the optimum was obtained using 75,000 plants.ha-1 and an applied dose of 150 kg.ha-1.\",\"PeriodicalId\":509934,\"journal\":{\"name\":\"Revista de la Facultad de Agronomía, Universidad del Zulia\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Revista de la Facultad de Agronomía, Universidad del Zulia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47280/revfacagron(luz).v40.n4.04\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista de la Facultad de Agronomía, Universidad del Zulia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47280/revfacagron(luz).v40.n4.04","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of the response surface methodology for yield optimization in maize (Zea mays L.)
The objective of this study was based on the application of the response surface methodology (RSM) for yield optimization in maize (Zea mays L.). The hybrid INIA SQ-1 was used, and the Response Surface Methodology was used using the Box-Behnken design (DBB), with which the following factors were evaluated: plant density, nitrogen (N) dose and phosphorus (P) dose at three levels each; for the optimization of the response variables: “yield” (kg.ha-1) and the “number of grains per square meter” (g.m2). The response surface method provided a statistically validated predictive model, which through adjustments was adapted to an established optimization process. For the variable “yield”, a maximum response was found with the application of 150 Kg.ha-1 of N and 90 kg.ha-1 of P. In relation to the number of grains per square meter (g.m2), the optimum was obtained using 75,000 plants.ha-1 and an applied dose of 150 kg.ha-1.