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1. Precision Feeding Can Significantly Reduce Lysine Intake and Nitrogen Excretion Without Compromising the Performance of Growing PigsThe impact of using a mathematical model estimating real-time daily lysine requirements in a sustainable precision feeding program for growing pigs was investigated in two performance trials. Three treatments were tested in the first trial (60 pigs of 41.2±0.5 kg): a three-phase feeding program (3P) obtained by blending fixed proportions of feeds A (high nutrient concentration) and B (low nutrient concentration); and two daily-phase feeding programs in which the blended proportions of feeds... C. Pomar, I. Andretta, J. Rivest, L. Hauschild, J. Pomar |
2. Content Analysis of the Challenges of Using Drones in Paddy Fields in the Haraz Plain Watershed, IranDrone technology has gained popularity in recent years as a sustainable solution to changing agricultural conditions. Using drones in agriculture provides many advantages in farm management. However, the use of drones in paddy fields in Iran is a new phenomenon facing numerous challenges. This study aims to explore the challenges for using drones in paddy fields and provide practical guidelines to solve the challenges facing the their application. This research was conducted with a qualitative... J. Aliloo, E. Abbasi, E. Karamidehkordi , E. Ghanbari Parmehr, M. Canavari, G.-. Vitali |
3. AgGateway Traceability API – The Foundation to Track Raw Agricultural CommoditiesThere is increasing demand for food traceability, ranging from consumers wanting to know where their food comes from (GMO, organic, climate-smart commodities), to manufacturers of agricultural inputs wanting to know the effectiveness of their products as used by farmers. Existing traceability requirements focus on the supply chain of goods packaged from their origin to retail grocery stores, with regulations provided by the Food Safety Modernization Act (FSMA) from the US Food and Drug Administration... S.T. Nieman, J. Tevis, B.E. Craker |
4. Combining Remote Sensing and Machine Learning to Estimate Peanut Photosynthetic ParametersThe environmental conditions in which plants are situated lead to changes in their photosynthetic rate. This alteration can be visualized by pigments (Chlorophyll and Carotenoids), causing changes in plant reflectance. The goal of this study was to evaluate the performance of different Machine Learning (ML) algorithms in estimating fluorescence and foliar pigments in irrigated and rainfed peanut production fields. The experiment was conducted in the southeast of Georgia in the United States in... C. Rossi, S.L. Almeida, M.N. Sysskind, L.A. Moreno, A. Felipe Dos Santos, L. Lacerda, G. Vellidis, C. Pilcon, T. Orlando Costa Barboza |
5. Adapt Standard: Enabling Interoperability in Agricultural Field Operations DataModern agriculture increasingly relies on sophisticated technologies, including precision farming equipment, sensors, laboratory analyses, and farm management software, to generate critical operational data. Despite these advancements, the industry faces significant interoperability challenges, resulting in fragmented data ecosystems that impede optimized decision-making. While ISO 11783 (ISOBUS) successfully facilitates electronic communication at the machinery level, it does not adequately address... B. Craker, S.T. Nieman, J.W. Wilson, S. Rhea, K. Nelson, D. Danford, J.A. Wilson, B. Kemp |