Weather conditions and sprayer operating parameters influence spray quality. Unmanned aerial vehicles are considered a modern, useful, and very efficient technological tool in the application of pesticides, as they carry out punctual spraying, and reduce environmental and public health problems. The objective of this study was to characterize the spraying quality carried out with an unmanned aerial vehicle as a function of flight height and target position in a coffee plantation in a mountainous region. Three flight heights (2.5, 3.0, and 4.0 m) were used, and the targets were placed at the top and bottom of the plant. For each plant, six water sensitive papers were placed on top of the plant and six were placed at the bottom. CIR 1.5 software was applied to determine the coverage percentage, drop density, volume median diameter, volumetric diameter corresponding to 10 and 90%, numerical median diameter, and relative amplitude. The results showed that the flight height only influenced the parameters of the volumetric diameter corresponding to 10% of the volume, numerical median diameter, and coverage percentage. The target position on the canopy influenced all the evaluated spraying parameters. In mountainous coffee plantations, the spraying system using unmanned aerial vehicle spraying is more efficient for the lower part of the plant.
The growing human population added to the rural exodus has aggravated the pressure in the agricultural sector for greater production. Faced with this problem, research has developed optical sensors for more productive agriculture with the purpose of minimizing the effects of rural exodus, obtaining rapid information and promoting the rational use of natural resources. Optical sensors have a differential consisting of the ability to use the spectral signature of an attribute or part of it to gain information, often not obvious. This review provides recent advances in optical sensors as well as future challenges. The studies have shown the wide range of applicability of optical sensors in agriculture, from detection of weeds to identification of soil fertility, which favors management in different areas of agriculture. The main limitation to the use of optical sensors in agriculture in most parts of the world has been the cost of purchasing the devices, especially in poor countries. So one of the future challenges is the reduction of final prices paid by consumers.
High-throughput phenotyping (HTP) approaches are potentially useful for the accurate and efficient evaluation and selection of superior genotypes, leveraging high genetic gains. Vegetation indices are of particular interest because they allow indirect selection. Considering the lack of information regarding high-throughput phenotyping approaches in tropical wheat breeding, this study aimed to (i) determine the best stages to carry out image acquisition for applying multi-spectral vegetation indices; (ii) evaluate the heritability and accuracy of multi-spectral vegetation indices; (iii) understand the relationships between vegetation indices and target agronomic traits; and (iv) evaluate the efficiency of indirect selection via UAV-based high-throughput phenotyping. A diversity panel of 49 tropical wheat cultivars was evaluated during the 2022 winter season. Weekly flight campaigns were performed to further build multi-spectral vegetation indices, which were then analyzed together with four target agronomic traits. Mixed model analyses were performed to estimate genetic parameters and predict genetic values, which were subjected to correlation analysis. Additionally, factor analysis was applied, and the factorial scores were used in an indirect selection strategy (indirect via HTP). This strategy was compared to three alternative strategies: direct via grain yield, direct via days to heading, and the multi-trait genotype-ideotype distance index. The results indicate that vegetation indices are suitable for indirect selection strategies and highly efficient for the indirect selection of grain yield and cycle. The findings of this study will help decision making regarding the use of these approaches in Brazilian public wheat breeding programs.
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