High-resolution suborbital remote sensing for detecting injuries caused by Saccharicoccus sacchari (Cockerell, 1895) (Hemiptera: Pseudococcidae) in sugarcane - Silva, Allef de Souza; de Oliveira, Robério; Neto, Jacob Soares Pereira; Borges, Valéria Peixoto; Guerrero, Milton Fernando Cabezas; Filho, André Augusto Castro do Amaral; Sousa, Rhadija Gracyelle Costa; Nascimento, Antônio Rogério Bezerra do; Malaquias, José Bruno (Frontiers in Agronomy, 2025)
The pink mealybug (Saccharicoccus sacchari) is a significant pest of sugarcane, causing reductions in growth, sucrose content, and crop productivity. Its efficient management requires accurate field monitoring methods. This study evaluated the use of suborbital remote sensing with Remotely Piloted Aircraft (RPAs) in detecting injuries caused by this pest, using the vegetation indices NDVI and NDRE. The research was carried out in two periods (2023 and 2024), in an area of 1.5 hectares located in Alagoa Grande, Paraiba State, Brazil. Flights with a multispectral RPA and field surveys were conducted to determine the proportion of plants with low (<20 individuals/plant) and high infestation (>20 individuals/plant). Data were analyzed using both supervised and unsupervised machine learning methods. The results indicated a significant negative correlation between NDRE and low levels of infestation, while NDVI was more effective in detecting severe infestations. Multivariate analyses reinforced the complementarity of the indices in identifying the pest, with NDRE standing out in early detection and NDVI in identifying advanced damage. Kappa coefficients (> 0.80) comparing plant infestation with NRDE and NDVI yielded excellent results, with an overall Accuracy and Sensitivity of over 80.00% for the relationship between NDVI and high infestation per plant, and 73.33% and 83.33%, respectively, for NDRE with low infestation per plant. It is concluded that the integrated use of NDVI and NDRE, via remote sensing, is a promising tool for monitoring S. sacchari in sugarcane, contributing to faster and more efficient decision-making in pest management.