Selecting statistical models to study the relationship between soybean yield and soil physical properties

Abstract

SUMMARYStatistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plantatmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.Index terms: autocorrelation, cross correlation, linear regression, state-space model, soil and plant properties.(1) Extracted from the dissertation of the first author.

Comparison of maps of spatial variability of soil resistance to penetration constructed with and without covariables using a spatial linear model

“…COLLARES et al (2008) found that the presence of compacted areas on the soil restricts root growth at that point and the roots are induced to grow in another direction. OLIVEIRA et al (2011) studied the relation between soybean yield and soil chemical properties for the selection of statistical models and found that there is autocorrelation and cross-correlation between soil resistance to penetration in the first layers and soybean yield measured over the transversal space, and that in the scenario considered by the authors, the soil bulk density is not autocorrelated or have cross-correlation with soybean yield.…”

Compared performance of penetrometers and effect of soil water content on penetration resistance measurements

“…Soil penetration resistance (PR) has been prioritized in soil management and studies on soil physics (Blainski et al, 2008;Assis et al, 2009, Souza et al, 2010Medeiros et al, 2011;2013), due to the ease and speed of measurement (Busscher et al, 2000. ) and correlation with plant properties, such as root growth (Dexter, 1987;Busscher & Bauer, 2003;Otto et al, 2011) and yield (Whalley et al, 2008;Oliveira et al, 2011;Bangita & Rao, 2012;Costa et al, 2012).…”

Seleção Aleatória De Elementos Amostrais Para a Construção De Mapas De Resistência Do Solo a Penetração

“…A resistência do solo à penetração é uma medida indireta do estado de compactação do solo que pode ser limitante ao crescimento das plantas. A investigação do comportamento dessa variável em solos agrícolas permite planejar as operações agrícolas que serão apropriadas para essa área como o tipo de manejo que será adotado: sistema convencional, sistema direto, entre outros (OLIVEIRA et al, 2011). A compactação do solo pode ser avaliada por meio da resistência do solo à penetração, e a compactação está associada com o desenvolvimento de culturas, como a soja, que apresentou decréscimo na produtividade ante ao acréscimo da resistência do solo à penetração (BEUTLER & CENTURION, 2004).…”