Calibração de modelos agrometeorológicos para estimar a produtividade da cultura do trigo, considerando sistemas de manejo do solo, em Ponta Grossa-PR

Abstract

Recebido Julho de 2011 -Aceito Maio de 2013RESUMO O presente estudo teve por objetivo avaliar as relações hídricas e o desempenho de modelos simplificados e agrometeorológicos na estimativa da produtividade da cultura do trigo, em quatro sistemas de manejo do solo, na região de Ponta Grossa, Estado do Paraná. O local estudado possui um Latossolo Vermelho distrófico típico e clima Cfb, segundo a classificação de Köppen. Os dados de produtividade da cultura do trigo (cinco safras) e meteorológicos foram disponibilizados pela Fundação ABC e SIMEPAR, respectivamente. Os modelos agrometeorológicos utilizados têm como variáveis de entrada a produtividade potencial e as relações ER/ETc (evapotranspiração real e cultura), que foram determinadas em balanços hídricos diários sequenciais, durante os estádios fenológicos da cultura. A evapotranspiração de referência (ETo) foi estimada com o método de Penman-Monteith. Considerando as inúmeras análises realizadas, o modelo que permitiu as melhores estimativas de produtividade foi o de Jensen, utilizando coeficientes hídricos de penalização obtidos por regressão múltipla. Palavras-chave: Planejamento de safras, Triticum aestivum, balanço hídrico. ABSTRACT: CALIBRATION OF AGROMETEOROLOGICAL MODELS FOR PREDICTING THE WHEAT CROP PRODUCTIVITY, CONSIDERING SOIL TILLAGE SYSTEMS, IN PONTA GROSSA REGION, STATE OF PARANA, BRAZILThe objective of this work was to evaluate hydric relations and the performance of simplified and agrometeorological models to estimate the productivity of wheat crop, considering four tillage soil systems, in Ponta Grossa, Parana State. The soil type at the experimental area has been classified as Typic Hapludox and the climate of the region classified as Cfb type, according to Köppen climatic classification. The yield data of wheat crop (five seasons) and meteorological were supplied by the ABC Foundation and SIMEPAR, respectively. The tested models are based on the crop yield potential and the ER/ETc relation (actual / crop evapotranspiration), determined by daily water balance occurred during different growth stages. The reference evapotranspiration (ETo) was estimated by the Penman-Monteith method. Considering the numerous tests carried out, the Jensen model show the best estimates of productivity, using yield response factor obtained by multiple regression.

Biostimulants in the Indicators of Yield and Industrial and Chemical Quality of Oat Grains

“…Prior knowledge of precipitation conditions may indicate management methods that ensure the success of the activity (Arf et al, 2012;Arenhardt et al, 2015). In winter cereals, however, rainfall without large volumes, which favors adequate soil moisture and well distributed throughout the crop cycle, characterizes a favorable environment for nitrogen management and greater expression of yield (Castro et al, 2012;Souza et al, 2013). In addition to precipitation, air temperature also acts strongly on nitrogen utilization dynamics and productivity expression.…”

Time of nitrogen supply in yield, industrial and chemical quality of oat grains

“…Prior knowledge of precipitation conditions may indicate forms of management that ensure the success of the activity (Arf et al, 2012;Arenhardt et al, 2015). In winter cereals, rainfall without large volumes, which favors adequate soil moisture and is well distributed throughout the cultivation cycle, characterizes an environment favorable to nitrogen management and greater expression of productivity (Castro et al, 2012;Souza et al, 2013).…”

The sowing density on oat productivity indicators

“…Arenhardt et al (2015) emphasized that the condition of the cultivation year of wheat is predominantly defined by distribution and volume of rainfall. The temperature, sunlight and solar radiation also influence the productivity (Souza et al, 2013). The temperature Romitti et al 907 acts as a catalyst of the biological process, reason why the plants require the minimum and maximum temperature for normality of the physiological activity (Tonin et al, 2014).…”