A Hybrid Artificial Intelligence Model for Aeneolamia varia (Hemiptera: Cercopidae) Populations in Sugarcane Crops

Sugarcane spittlebugs are considered important pests in sugarcane crops ranging from the southeastern United States to northern Argentina. To evaluate the effects of climate variables on adult populations of Aeneolamia varia (Fabricius) (Hemiptera: Cercopidae), a 3-yr monitoring study was carried out in sugarcane fields at weeklong intervals during the rainy season (May to November 2005–2007). The resulting data were analyzed using the univariate Forest-Genetic method. The best predictive model explained 75.8% variability in physiological damage threshold. It predicted that the main climatic factors influencing the adult population would be, in order of importance, evaporation; evapotranspiration by 0.5; evapotranspiration, cloudiness at 2:00 p.m.; average sunshine and relative humidity at 8:00 a.m. The optimization of the predictive model established that the lower and upper limits of the climatic variables produced a threshold in the population development rate of 184 to 267 adult insects under the agroecological conditions of the study area. These results provide a new perspective on decision-making in the preventive management of A. varia adults in sugarcane crops.
Pest insect, Population management threshold, Random Forest, Genetic algorithm