From Image Series to Resilient Soybean Genotypes: Transformer-Based Canopy Cover Extraction and Weather-Informed Nonlinear Modeling

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Abstract
Green canopy cover dynamics extracted from high-throughput RGB imagery via automated labeled segmentation enabled nonlinear modeling that accounted for short-term weather variation, explaining up to 56% of protein yield variation in 150 soybean genotypes across ten seasons and enabling prediction in new environments as well as identification of tolerant genotypes.