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methods for evaluating cotton fiber quality and identifying characteristics that promote reliable, predictable dye uptake. Through this experience, you will gain hands-on exposure to analytical
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sensors, RGB/IR cameras, video systems, insect traps, and other devices to build predictive, AI- and machine-learning based models for monitoring grain quality and detecting deterioration due to mold
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predictive insights that support improved food and feed safety. Learning Objectives: Under the guidance of a mentor, you will have the opportunity to learn to: (a) utilize field and laboratory methods in plant
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