Statistical models to predict densities of Sitophilus zeamais adults in wheat warehouse using probe traps. (December 2020)

• Record Type: Journal Article
• Authors: Zhang, Hao; Wang, Dianxuan; Jian, Fuji
• Is Part Of: Journal of stored products research. Volume 89(2021)
• Publication Date: 2020-12
• Subjects: Insect density prediction -- Sitophilus zeamais adults -- Probe traps -- Trapping frequency -- Statistical model; Food -- Storage -- Periodicals; Farm produce -- Storage -- Diseases and injuries -- Periodicals; Entomology -- Periodicals; Food Contamination -- Periodicals; Food Preservation -- Periodicals; Insect Control -- Periodicals; Aliments -- Entreposage -- Périodiques; Produits agricoles -- Entreposage -- Maladies et dommages -- Périodiques; Electronic journals; 631.568
• DOI: 10.1016/j.jspr.2020.101722
• Languages: English
• ISSNs: 0022-474X

Abstract

Abstract: Statistical models were developed to estimate the density of Sitophilus zeamais adults in a flat storage warehouse holding 230 tonne of wheat with 12.4 ± 0.2% (wet basis) moisture content at 18–33 °C. Published data were used to develop the models. To valid the developed models, trapping and manual sampling with 15 kg of sampling unit at five locations were conducted in the warehouse for more than 10 wk. Insect densities were calculated by using the developed models and the trapping frequency and temperatures at the sampling locations. The developed models were validated by calculating the average magnitude of relative error (MRE), regression slope, and residues between the calculated and measured insect densities. Three models were developed, and the best model was a linear model. The linear model could explain 96% of the measured insect densities. The temperature on the density prediction has a natural exponential effect. Highlights: Statistical models were developed to estimate the insect density. Models were validated in a warehouse holding 230 t of wheat. The best model was a linear equation. The best model could explain 96% of the measured insect densities.