Undergraduate students: Nelson Goosman (WSU), Ali Alsmael (WSU)
Develop a cultivar-specific dataset with due ground-truthing to model heat stress in apples and grapes
Develop and implement weather and crop physiology-driven machine learning models to predict heat stress in fresh market apples (cv. Honeycrisp, Cosmic Crisp) and grapes (cv. Chardonnay)
Machine learning models that ingest weather (open- or in-field) and crop/fruit physiology data to predict heat stress in apples and grapes will be able to address related complexities with existing energy balance and other modeling approaches, providing a reliable decision support tool for growers to timely mitigate the heat stress for improved fruit quality and packouts.
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