Proceedings
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| Filter results3 paper(s) found. |
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1. Using Hyperspectral Imagery to Monitor Peanut Physiological Responses to Water StressPeanut production in Georgia plays an important role in the United States agriculture, as it is the country’s largest peanut producer. However, increasing climate variability poses major risks in peanut productivity, particularly through drought and heat stress. This study aimed to detect and monitor physiological responses of nine peanut genotypes under irrigated and drought conditions using high-resolution hyperspectral imaging (HSI). A field trial was conducted in the 2025 season at the... |
2. Evaluation of Transfer Learning in Semantic Segmentation Models for Soybean SeedlingsSeed vigor evaluation is fundamental in the quality control of commercial lots, as it is directly associated with the rapid and uniform emergence of seedlings and the initial performance of crops in the field. Traditional methods, although widely used, present limitations such as long execution time, dependence on the evaluator’s experience, and subjectivity. In this context, systems based on Computer Vision emerge as promising alternatives for automating vigor assessment, as they enable... E. Freitas, J. Martins Neto, P. Dos Santos E Silva, H.F. Abud, D.G. Gomes, V.C. Secundino |
3. Evaluation of Lettuce Image Classification with CNNs under Different NPK Nutritional ConditionsThe growing global demand for food has driven the development of technologies aimed at increasing productive efficiency in sustainable agricultural systems, such as hydroponics. In this context, proper monitoring of nutrient solutions is essential, particularly for the early detection of nitrogen (N), phosphorus (P), and potassium (K) deficiencies, which directly affect lettuce growth, yield, and quality. Traditional nutritional diagnostic methods often rely on destructive laboratory analyses,... E.L. Silva, E. Freitas, V.C. Secundino, D.G. Gomes |