Artificial neural networks as a tool for seasonal forecast of attack intensity of Spodoptera spp. in Bt soybean.

Soybean (Glycine max) is the world's most cultivated legume; currently, most of its varieties are Bt. Spodoptera spp. (Lepidoptera: Noctuidae) are important pests of soybean. An artificial neural network (ANN) is an artificial intelligence tool that can be used in the study of spatiotemporal dynamics of pest populations. Thus, this work aims to determine ANN to identify population regulation factors of Spodoptera spp. and predict its density in Bt soybean. For two years, the density of Spodoptera spp. caterpillars, predators, and parasitoids, climate data, and plant age was evaluated in commercial soybean fields. The selected ANN was the one with the weather data from 25 days before the pest's density evaluation. ANN forecasting and pest densities in soybean fields presented a correlation of 0.863. It was found that higher densities of the pest occurred in dry seasons, with less wind, higher atmospheric pressure and with increasing plant age. Pest density increased with the increase in temperature until this curve reached its maximum value. ANN forecasting and pest densities in soybean fields in different years, seasons, and stages of plant development were similar. Therefore, this ANN is promising to be implemented into integrated pest management programs in soybean fields.

Determining Factors and Economic Injury Levels for Sphenophorus levis for Chemical and Biological Control in Irrigated and Non-irrigated Sugarcane Crops.

Globally, people use sugarcane (Saccharum officinarum) to produce sugar and ethanol. Rainfed or irrigated sugarcane agricultural systems are available. Among the pests affecting this crop, the weevil Sphenophorus levis, Vaurie 1978 (Coleoptera: Curculionidae), is increasingly becoming a significant threat in southern South America. Sphenophorus levis populations are controlled using chemical or biological measures. Control decisions hinge upon the economic injury level (EIL). The EIL delineates the pest density that results in financial losses for producers. This study aims to determine the EIL for S. levis, considering the factors favoring this insect pest and chemical and biological control methods in rainfed and irrigated systems. The intensity of S. levis attacks was monitored in commercial sugarcane plantations over four years in João Pinheiro, Minas Gerais, Brazil. Sampling occurred in a 50 × 50 × 30-cm-deep trench dug in the soil surrounding the sugarcane clump. The total number of stumps in the clump, including those attacked by S. levis, was tallied. The EILs for this pest were 5.93% and 4.85% of targeted stumps for chemical control in rainfed and irrigated crops, respectively. Biological control in sugarcane plots resulted in an EIL of 4.15% and 3.40% for stumps attacked in rainfed and irrigated crops, respectively. Pest attacks were more severe during rainy years and in older sugarcane crops. The EIL values determined in this study could inform integrated pest management programs for sugarcane crops.