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A Proposal of Oat Productivity Simulation by Meteorological Elements,Growth Regulator and Nitrogen

作     者:Anderson Marolli José Antonio Gonzalez da Silva Osmar Bruneslau Scremin Rúbia Diana Mantai Ana Paula Brezolin Trautmann Angela Teresinha Woschinski de Mamann Roberto Carbonera Adriana Roselia Kraisig Cleusa Adriane Menegassi Bianchi Krüger Emilio Ghisleni Arenhardt 

作者机构:Department of Exact Sciences and EngineeringRegional University of the Northwestern of Rio Grande do Sul State(UNIJUí)IjuiBrazil Department of Agrarian StudiesRegional University of the Northwestern of Rio Grande do Sul State(UNIJUí)IjuiBrazil Department of Crop PlantsFederal University of Rio Grande do Sul(UFRGS)Porto AlegreBrazil 

出 版 物:《American Journal of Plant Sciences》 (美国植物学期刊(英文))

年 卷 期:2017年第8卷第9期

页      面:2101-2118页

学科分类:1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

主  题:Avena sativa Biomass Lodging Trinexapac-Ethyl Regression 

摘      要:The simulation of oat grain productivity does not contemplate the use of efficient models that involve important management with meteorological elements. The objective of the study is to propose a mathematical model capable of simulating the oat grain productivity through the management of nitrogen and growth regulator with variables related to the plant and to meteorological elements. In this study, two experiments were conducted in the years of 2013, 2014 and 2015: one to quantify biomass productivity and another to determine grain productivity and lodging at the management doses of nitrogen and growth regulator. The experimental design was a randomized block with four replications in a 4 × 3 factorial scheme for 0, 200, 400 and 600 mL·ha-1 growth regulator doses and 30, 90 and 150 kg·ha-1 nitrogen doses, respectively. During the crop cycles, the meteorological variables thermal sum, radiation and rainfall were quantified. The mathematical model proposed, which combines polynomial regression of the harvest index with multiple linear regression of the biological productivity, is efficient in the simulation of oat grains productivity with the use of growth regulator, nitrogen and meteorological elements. Thus, it adds to the conventional models of simulation and becomes an aid tool for making decisions regarding the management of oats culture.

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