Proceedings
Authors
| Filter results5 paper(s) found. |
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1. Hyperspectral Imagery for the Detection of Nitrogen Stress in Potato for In-season Management... T.J. Nigon, C. Rosen, D. Mulla, Y. Cohen, V. Alchanatis, R. Rud |
2. Evaluating Water Status in Potato Fields Using Combined Information from RGB and Thermal Aerial ImagesPotato yield and quality are highly dependent on an adequate supply of water. In this study the combined information from RGB and thermal aerial images to evaluate... Y. Cohen, V. Alchanatis, B. Heuer, H. Lemcoff, M. Sprintsin, C. Rosen, D. Mulla, T. Nigon, Z. Dar, A. Cohen, A. Levi, R. Brikman, T. Markovits, R. Rud |
3. Integrated Data-driven Decision Support SystemsSite-specific and data-driven decision support systems in agriculture are evolving fast with the rapid advancements in cutting-edge technologies such as Agricultural Artificial Intelligence (AgAI) and big data integration. Data driven decision support systems have the potential to revolutionize various aspects of farming, from crop monitoring and precision management decisions to the way growers interact with complex technologies. The AgAI decision support-based systems excel at analyzing... L.A. Puntel, P. Pellegrini, S. Joalland , J. Rattalino, L. Vitantonio |
4. Precision Nitrogen Management Community MeetingAgenda Welcome to the meeting participants by Dr. Brenda Ortiz (Professor at Auburn University) 2022-2024 community leader and incoming leader Dr. Laila Puntel (Syngenta). Brief update of activities and opportunities for the upcoming years (Brenda Ortiz) Strategies to assess precision nutrient management educational needs and networking opportunities among community members and ISPA in general. Discuss possibilities for collaboration... B.V. Ortiz, L.A. Puntel |
5. Multivariate Linear Regression Modeling for Predicting Chicken Body Weight Using Age, Uniformity, and Growth RateAccurate estimation of chicken body weight is critical for optimizing feed management, harvesting schedules, and animal welfare in commercial poultry systems. This study proposes a robust predictive framework using multivariate linear regression to estimate the average weight of native broiler chickens based on three explanatory variables: age, uniformity, and daily growth rate. After rigorous data cleaning and outlier removal, the model was trained and validated on 43 field observations collected... H. Lin |