A Hybrid Artificial Intelligence Model for Aeneolamia varia (Hemiptera: Cercopidae) Populations in Sugarcane Crops
Abstract:
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 week-long intervals during the rainy season (May to November 2005-2007). The resulting data were analyzed using the univariate Forest-Genetic method. The best pbkp_redictive model explained 75.8% variability in physiological damage threshold. It pbkp_redicted 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 pbkp_redictive 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.
Año de publicación:
2021
Keywords:
- random forest
- population management threshold
- pest insect
- Genetic Algorithm
Fuente:
Tipo de documento:
Article
Estado:
Acceso abierto
Áreas de conocimiento:
- Ecología
- Inteligencia artificial
Áreas temáticas:
- Ciencias de la computación