MODEL OF POTENTIAL AREAS FOR THE ESTABLISHMENT OF HUANGLONGBING DISEASE IN THE STATE OF TABASCO

Abstract

Background. Huanglongbing is a lethal disease for citrus, affecting all citrus species, causing young plants that become infected fail to produce and adult plants become unproductive for a period of two to five years. Objective. The objective of this study was to determine the potential areas for the establishment of huanglongbing in Tabasco. Methodology. In order to achieve this objective, the model of maximum entropy (MaxEnt) was used, which is a general purpose machine learning method. For its validation, the Receiver Operating Characteristic (ROC) technique applied in presence-only distribution models was applied. To generate the model, 19 climatic variables taken from Worldclim were used, a soil variable taken from Jiménez et al., (2013) and 195 records of the presence of Candidatus Liberibacter asiaticus detected in plant material were used. Results. The results show that the municipalities of Huimanguillo and Balancán are the areas with the greatest potential distribution of the disease with values greater than 0.7. According to the area under the curve (AUC), the model has a high ability to predict correctly by presenting values of 0.936 in the training data. Implications. The present study could contribute to the planning of surveillance areas for the detection and control of huanglongbing disease. Conclusion. The model obtained is a good approximation of the potential presence of the disease in the state of Tabasco, giving clarity when choosing the surveillance areas for the pathogen and its vector.

Keywords

• análisis geoespacial
• fitopatología
• hlb
• maxent
• variables climáticas