Proceedings
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| Filter results5 paper(s) found. |
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1. Probfuse Dashboard: Uncertainty-aware Geospatial Fusion For Climate-smart Conservation Recommendations In The Maumee River BasinNutrient losses from tile-drained row crops in the Maumee River Basin remain a primary driver of harmful algal blooms in western Lake Erie, despite expanding conservation programs and cost-share incentives like the Environmental Quality Incentives Program (EQIP). Existing tools rely on static look-up tables or county averages, lacking probabilistic fusion of multi-source data or uncertainty estimates. This hinders field staff and producers from integrating soils, climate and program rules under... H. Subramoni, A. Murumkar, K. Ard, S.A. Shearer, A. Radhakrishnan, J.P. Fulton, K. Mundada |
2. Detection of Banana Bunches and Peduncles in the Prata Catarina Cultivar Using Faster R-CNN With Transfer LearningBanana is one of the most produced and consumed fruits worldwide, being strategic for precision agriculture, especially in applications aimed at intelligent management and automated harvesting. Its economic and social relevance in tropical countries reinforces the need for technological solutions that increase productive efficiency and reduce losses in the field. In this context, the automatic detection of bunches and stalks in a natural environment represents a relevant challenge due to occlusion,... Y. Costa G. Da Silva, E. Freitas, P.S. Costa, D.V. Beserra, D.G. Gomes |
3. Spatial Distribution of Coffee Leaf Miner Infestation and Its Impact on Coffee Fruit Maturation, Yield, and Beverage QualityDifferences in the maturation rate of coffee fruits can be associated with plant stress. The incidence of pests, such as the coffee leaf miner (Leucoptera coffeella), compromises the photosynthetically active area, which can reduce yield and beverage quality. Computer vision can assist in damage reduction by identifying the pest's spatial and temporal behavior. This study aimed to verify, spatially and temporally, the impact of damage caused by the coffee leaf miner on fruit... L.V. Lazzarini, A. , G.P. Cândido, V.M. Nunes, S.M. Hurtado, F.H. Leandro, I.D. Gonçalves |
4. Spatial Analysis of Physical and Sensory Attributes of Coffee BeansArabica coffee (Coffea arabica L.) is one of the crops with the greatest economic and social relevance in Brazil, with beverage quality being a differential of broad commercial value. This study aimed to evaluate the spatial variability of the physical and sensory attributes of coffee beans. The study was conducted during the 2023-24 crop season in a 27-hectare plot belonging to Fazenda Mandaguari, in Indianópolis, Minas Gerais, cultivated with the Topázio cultivar under... V.M. Nunes, S.M. Hurtado, I. Almeida, A. , W.G. Siquieroli, G.P. Cândido, L.V. Lazzarini |
5. NDVI Index and Its Correlation with Biennial Coffee YieldPrecision agriculture (PA) has consolidated itself as an important tool in agricultural management, allowing greater productive efficiency, cost reduction, and environmental sustainability. Among PA tools, the use of vegetation indices stands out, as it allows inferences about crop biomass both spatially and temporally. In this context, this study aimed to evaluate the relationship between the normalized difference vegetation index (NDVI) and the yield of Arabica coffee (Coffea arabica... L.V. Lazzarini, S.M. Hurtado, I.D. Gonçalves, M.F. Carneiro Filho, A. , G.P. Cândido |