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September 5, 2025Agrosystems Geosciences & EnvironmentOpen Access

Image processing and machine learning identify high‐yield branching phenotypes in soybean

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Authors

AAAnne B. AlerdingCKChristopher KushnerKHKristen Hoffman

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Overview

Image analysis shows significant correlations between morphological traits and yield in soybeans, highlighting machine learning's role in agriculture.

Key Points

  • Greater circularity of the shoot convex hull profile correlates with higher seed yield in soybeans, indicating important traits to focus on.
  • The machine learning model achieved 80% accuracy in distinguishing between high-yield phenotypes (PT1 and PT2) among soybean plants.
  • Different soybean cultivars employ unique growth strategies to achieve high yields, emphasizing the importance of phenotypic variations.
  • This study demonstrates the practical application of image processing technologies for yield prediction in agricultural practices.

Cite This Study

Alerding et al. (2025) studied this question.

synapsesocial.com/papers/68bb4df56d6d5674bcd021efhttps://doi.org/10.1002/agg2.70206
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