Abstract
Tibraca limbativentris is considered one of the main species of insect pests in irrigated rice. This species can be found in plants in the vegetative and reproductive stages. This study aimed to select semivariogram models to estimate rice stem bug population densities by ordinary kriging. Two fields were used to survey the T. limbativentris population in Oryza sativa. A grid of 30 x 30 m was drawn, which generated 143 and 385 sample units for the first and second fields, respectively. Seven evaluations of two hundred plants per sampling unit were performed during cultivation. From the insect counts, the results were input into circular, spherical, pentaspherical, exponential, Gaussian, rational quadratic, cardinal sine, K-Bessel, J-Bessel, and stable semivariogram models via ordinary kriging interpolation and the best model was selected via cross-validation. Each assessment had a particular spatial structure and semivariogram model that best fit the experimental data.
Highlights
Tibraca limbativentris (Hemiptera: Pentatomidae) is considered one of the main species of insect pests in irrigated rice (Pazini, Botta, & Silva, 2012; Rampelotti et al, 2008; Silva, Lima, & Oliveira, 2010; Sociedade Sul-Brasileira de Arroz Irrigado [SOSBAI], 2014)
According to Webster and Oliver (2007), selecting a model that adequately represents the semivariances is highly desirable in the kriging process and influences the prediction of unknown values
In Field 2 (F2), the highest number of adults was recorded, 10,454; the average number of adults per sample was 3.87 m-2 evaluation-2 adult-1, which was greater than the average value found in the crop, which was in Field 1 (F1) (3.35 m-2 evaluation-2 adult-1)
Summary
Tibraca limbativentris (Hemiptera: Pentatomidae) is considered one of the main species of insect pests in irrigated rice (Pazini, Botta, & Silva, 2012; Rampelotti et al, 2008; Silva, Lima, & Oliveira, 2010; Sociedade Sul-Brasileira de Arroz Irrigado [SOSBAI], 2014) This species can be found in vegetative and reproductive stages directly affecting yield components and causing symptoms of dead heart when they attack the stems, causing the formation of white panicles or partial spikelet sterility, which is the most influential component in income reduction in rice grains yield (Costa & Link, 1992; Souza et al, 2009). Kriging uses the spatial dependence between neighboring samples, expressed in a semivariogram, to estimate values at any position within the experimental area with no tendency and minimum variance (Webster & Oliver, 2007; Coelho, Souza, Uribe-Opazo, & Pinheiro Neto, 2009; Silva et al, 2010; Souza, Lima, Xavier, & Rocha, 2010; Dinardo-Miranda, Fracasso, & Perecin, 2011). According to Webster and Oliver (2007), selecting a model that adequately represents the semivariances is highly desirable in the kriging process and influences the prediction of unknown values
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