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Predicting photosynthetic pathway from anatomy using machine learning.

Ian S Gilman1,2,3, Karolina Heyduk4, Carlos Maya-Lastra1,5

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|January 4, 2024
PubMed
Summary
This summary is machine-generated.

Crassulacean acid metabolism (CAM) plants show distinct anatomical differences from non-CAM plants. Machine learning accurately identifies CAM anatomy, revealing evolutionary links between CAM and specialized plant structures.

Keywords:
AsparagaceaeCrassulacean acid metabolismPortullugomachine learningphotosynthesis

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Area of Science:

  • Plant biology
  • Evolutionary biology
  • Computational biology

Background:

  • Crassulacean acid metabolism (CAM) is a water-conserving photosynthetic pathway.
  • CAM plants often exhibit specialized anatomical features like succulence.
  • Quantitative links between CAM and specific anatomical traits remain underexplored.

Purpose of the Study:

  • To investigate the relationship between plant anatomy and Crassulacean acid metabolism (CAM) phenotypes.
  • To determine if anatomical features can reliably distinguish CAM from non-CAM plants.
  • To explore the evolutionary anatomical trajectory associated with CAM.

Main Methods:

  • Utilized novel computer vision software for quantitative anatomical measurements.
  • Integrated new anatomical data with existing published data across diverse flowering plants.
  • Applied machine learning algorithms for classification and phylogenetic comparative methods (phylogenetic least squares regression, threshold analyses) to analyze CAM-anatomy relationships.

Main Results:

  • Significant anatomical differences were observed between plants with varying CAM phenotypes.
  • Machine learning achieved over 95% accuracy in classifying CAM versus non-CAM anatomy.
  • CAM evolution correlated significantly with larger mesophyll cell size, thicker leaves, and reduced intercellular airspaces.

Conclusions:

  • Machine learning can be a valuable tool for identifying potential new CAM species based on anatomy.
  • The evolution of strong, obligate CAM necessitates continuous anatomical specialization from non-CAM ancestors.