The coffee leaf miner (Leucoptera coffeella) is a primary pest for coffee plants. The attack of this pest reduces the photosynthetic area of the leaves due to necrosis, causing premature leaf falling, decreasing the yield and the lifespan of the plant. Therefore, this study aims to analyze vegetation indices (VI) from images of healthy coffee leaves and those infested by coffee leaf miner, obtained using a multispectral camera, mainly to differentiate and detect infested areas. The study was conducted in two distinct locations: At a farm, where the camera was coupled to a remotely piloted aircraft (RPA) flying at a 3 m altitude from the soil surface; and the second location, in a greenhouse, where the images were obtained manually at a 0.5 m altitude from the support of the plant vessels, in which only healthy plants were located. For the image processing, arithmetic operations with the spectral bands were calculated using the “Raster Calculator” obtaining the indices NormNIR, Normalized Difference Vegetation Index (NDVI), Green-Red NDVI (GRNDVI), and Green NDVI (GNDVI), the values of which on average for healthy leaves were: 0.66; 0.64; 0.32, and 0.55 and for infested leaves: 0.53; 0.41; 0.06, and 0.37 respectively. The analysis concluded that healthy leaves presented higher values of VIs when compared to infested leaves. The index GRNDVI was the one that better differentiated infested leaves from the healthy ones.

Coffee trading is an important source of income for the Brazilian commercial balance. Chlorophyll (Chl) are pigments responsible for converting radiation into energy; these pigments are closely related to the photosynthetic efficiency of plants, and the evaluation of the nutritional status of the coffee tree. The inversion method can be used for estimating the canopy chlorophyll content (Chl_canopy) using the leaf chlorophyll content (Chl_leaf) and the leaf area index (LAI). The application of vegetation indices (VIs) in high spatial resolution images obtained from remotely piloted aircraft (RPA) can assist in the characterization of Chl_canopy in addition to providing vital and fast information for monitoring crops and aiding decision-making. This study aimed to identify which VIs adequately explain the Chl and evaluate the relationships between the VIs obtained from remotely piloted aircraft (RPA) images and the Chl_leaf and Chl_canopy in coffee plants during the wet and dry seasons. The experiment was conducted on a Coffea arabica L. plantation in Lavras, Minas Gerais, Brazil. Images were collected on 26 November 2019 (wet), 11 August 2020 (dry), and 26 August 2021 (dry) by a multispectral camera embedded in a quadcopter. Plant height (H), crow diameter (D), and Chl_leaf (a, b and total) data were collected in the field by a metre ruler (H and D) and sensor (Chl_leaf). The LAI was calculated based on H and D. The Chl_canopy (a, b, and total) was calculated based on Chl_leaf and LAI. The image processing was performed in Pix4D software, and postprocessing and calculation of the 21 VIs were performed in QGIS. Statistical analyses (descriptive, statistical tests, Pearson correlation, residuals calculation, and linear regression) were performed using the software R. The VIs from the RPA that best correlates to Chl_canopy in the wet season were the Modified Chlorophyll Absorption Ratio Index 2 (MCARI2_RPA), Modified Simple Ratio (MSR_RPA) and Simple Ratio (SR_RPA). These VIs had high sensitivity and, therefore, were more affected by chlorophyll variability. For the two dry season studied days, there were no patterns in the relationships between Chl_leaf, Chl_canopy, and the VIs. It was possible to use the Chl inversion method for the coffee during the wet season.

Climate change threatens the survival of commercial crops due to their narrow genetic base. One of the alternatives is the identification of plants with potential for abiotic stress tolerance. This study aimed to verify the physiological and anatomical adaptations to the drought period and the impacts on the yield of ‘Híbrido de Timor’ coffee tree accessions. The experimental design was randomized blocks, in a 7 x 2 factorial arrangement, being seven genotypes (UFV 377-21, UFV 377-21, UFV 442-42, BE 5 Wush-Wush x UFV 366-08, UFV 428-02, UFV 376-31 and UFV 427-55) and two seasonal periods (dry and rainy), with two replications. The stomatal conductance; predawn water potential; levels of hydrogen peroxide and malondialdehyde; activity of the enzymes catalase, superoxide dismutase and ascorbate oxidase; ascorbate content; cuticle thickness of the adaxial surface and leaf lamina; stomatal density; ratio between polar and equatorial diameter; phloem area; area, diameter and frequency of xylem vessels; relative hydraulic conductivity; vulnerability index; and yield were evaluated. The results showed acclimatization of the accessions to the dry period, with some of them maintaining higher water potential values in the predawn; induction of the antioxidant system with the increase in the activity of the superoxide dismutase enzyme and ascorbate levels; increase in the cuticle and leaf lamina thickness; and a higher ratio between polar and equatorial diameters. Most of the evaluated accessions showed a good productive performance, especially the ‘UFV 377-21’, ‘UFV 442-42’ and ‘UFV 376-31’, with adaptations to the dry period and yield potential.