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| Filter results7 paper(s) found. |
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1. Integrating Management Zones, Artificial Neural Networks and Remote Sensing for Smart Peanut HarvestingThe integration of technologies contributes significantly to agricultural development, especially regarding the rational and more sustainable use of soil. Thus, the use of remote sensing and artificial intelligence techniques combined with precision agriculture can maximize smart harvesting for peanut crops, which face several challenges such as limited harvesting technology, indeterminate growth, and the development of pods below the soil surface. Therefore, this study aimed to develop a peanut... |
2. Characterizing Cross-Crop Stink Bug Spectral Signatures from Hyperspectral DataEffective crop protection in agricultural production systems requires the ability to detect pest-induced stress in a timely and reliable manner. In large-scale farming systems, stink bugs attack multiple crop species, making cross-crop pest detection a critical capability for scalable monitoring solutions. Rather than developing crop-specific models that require retraining for each species, identifying crop-independent spectral signatures of stink bug infestation enables transferable detection... A.O. Françani, L. Zhao, J. Ferreira , J. Yan, E.J. Ferreira, L.A. Jorge |
3. Mobile Edge AI for Detection of Grape Clusters and Disease Symptoms in VineyardsPrecision viticulture demands accessible technological solutions that enable rapid disease diagnosis and production monitoring directly in the field. In real-world production contexts, dependence on cloud connectivity, external servers, or specialized hardware limits the adoption of computer vision tools by small and medium-sized farmers. In this context, this work presents a solution based on artificial intelligence embedded in a mobile application for the detection of grape bunches and leaves... E.M. Da Silveira, F.I. Nogueira, S.D. Camargo, A. Freire Campos, J. Valiati, E.F. Leite |
4. Enhancing Pest Detection Through Spectral Signature Extraction in Hyperspectral DataDetecting insect infestation is essential for effective crop protection, particularly in large-scale systems. Caterpillars and stink bugs induce physiological and structural alterations in plant tissues that can be captured through hyperspectral reflectance sensing, which is a non-destructive technique that measures plant responses across hundreds of wavelengths. However, raw spectral signatures are characterized by high dimensionality, strong inter-band correlation, and they often exhibit baseline... A.O. Françani, J. Ferreira , L. Zhao, L.A. Jorge, K.M. De Oliveira, J.C. Felipe |
5. Producing Ordinary Kriging Interpolated Maps for Biomass Observation Through Values Captured with NDVI and NDRE Imagery.Geostatistics is a well-established method in the scientific community for aiding decision-making in situations with spatial dependence. Generally, the methodology adopted for interpolating fertility maps is the use of data from soil sampling on the property, generating representative thematic maps. However, the number of samples required for this methodology can be problematic when the analysis site is a small farm or one divided into multiple plots, common scenarios in Brazilian coffee farming. Considering... H.F. Gebler, C.R. Grego, G.C. Rodrigues, A. Pereira, F. Fagundes |
6. Evaluation of Variable-Rate Application of Growth Regulator in CottonThe application of plant growth regulators in cotton is widely used to control excessive vegetative growth and improve plant architecture. However, the spatial variability present in agricultural fields may reduce the efficiency of conventional fixed-rate application, making variable-rate application (VRA) a promising alternative. The objective of this study was to evaluate the effect of fixed-rate and variable-rate application of the growth regulator mepiquat chloride on plant height, leaf area... B. Costalonga Vargas, M.R. Furtado Junior, G.O. Paula, A.L. Coelho, M.C. Moreira, F.R. Carvalho |
7. Spatial Distribution of the Visual Evaluation of Soil Structure in a Coffee-growing AreaCoffee production has a significant socioeconomic impact in Brazil, requiring efficient and technological management practices to ensure high yields and soil conservation. In this context, assessing soil physical quality is indispensable, and the Visual Evaluation of Soil Structure (VESS) methodology is a rapid, cost-effective, and easily applicable field alternative compared to traditional laboratory analyses. The objective of this study was to visually evaluate the structure of a soil cultivated... E. De Souza Salles, C. Souza, E. Pereira De Morais, O. Filho |