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| Filter results3 paper(s) found. |
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1. Pa Adoption By A Korean Rice Farming Group: Case Study Of Pyeongtaek CityResearch on precision agriculture (PA) has been conducted in Korea for about 10 years since 1999. Most of the research was focused on rice paddy fields that were flooded, flat, and small sized (e.g., 30 m x 100 m). Accomplishment during the period includes investigation on spatial variability in soil, crop growth, and yield properties, application of imported sensors and variable rate applicators, and development of Korean version of these sensors... S. Chung, H. Yoo, S. Hong |
2. Towards a Digital Peanut Profile Board: a Deep Learning ApproachArtificial intelligence techniques, particularly deep learning, offer promising avenues for revolutionizing object detection and counting algorithms in the context of digital agriculture. The challenges faced by peanut farmers, particularly the precise determination of optimal maturity for digging, have prompted innovative solutions. Traditionally, peanut maturity assessment has relied on the Peanut Maturity Index (PMI), employing a manual classification process with the aid of a peanut profile... M.F. Freire de oliveira, B.V. Ortiz, J.B. Souza, Y. Bao, E. Hanyabui |
3. Use of Crop and Drought Spectral Indices to Support Harvest Decisions of Peanut Fields in AlabamaHarvest efficiency expressed in quantity and quality of peanut fields could increase if farmers are provided with tools to support harvest decisions. Peanut farmers still rely on a visual and empiric method to assess the right time of peanut maturity but this method does not account for within-field variability of crop growth and maturity. The integration of spectral vegetation indices to assess drought, soil moisture, and crop growth to predict peanut maturity can help farmers strengthen decisions... M.F. Oliveira, B.V. Ortiz, E. Hanyabui, J.B. Costa souza, A. Sanz-saez, S. Luns hatum de almeida , C. Pilcon, G. Vellidis |