Analysis of the Potential of Remote Piloted Aircraft in the Detection of Damage by Frost in Coffee Plants

Abstract

The current methods for monitoring and evaluating the frost damage of coffee plants are not only costly but also impractical in areas of extensive cultivation. Therefore, remote sensing using Remotely Piloted Aircraft (RPA) can be a feasible alternative, providing coffee producers with a fast, continuous, and accessible method to identify and evaluate the frost damage in coffee plants. Therefore, the objective of this study was to evaluate the frost damage in coffee plantations using multispectral images obtained from RPA. For the analysis of frost on the coffee plants, 18 sampling points were selected in the field. Each sampling point consisted of 5 plants, 1 central plant and 2 sets of 2 plants in the east-west direction from the main plant. The evaluations of the frost damage were performed visually through scores. Subsequently, 3 levels were defined according to the percentage of damage to the plant. The images were obtained with a multispectral camera coupled to an RPA with rotating wings. The spectral signatures of each of the 3 levels of frost damage were determined. The spatial distribution of the frost damage on the plantation allowed the identification of the plantation regions most susceptible to the effects of frost. The spectral signatures made it possible to differentiate coffee plants with different levels of frost damage. The Modified Photochemical Reflectance Index (MPRI) showed the most significant variation in the different levels of frost damage, during the Green Normalized Difference Vegetation Index (GNDVI) had the slightest deviation..