Machine Learning Techniques for Predicting Crop Photosynthetic Capacity from Leaf Reflectance Spectra

Molecular Plant

Volumn 10, Issue 6, 2017, Pages 878-890

  Heckmann, David ^a   Schlüter, Urte ^a   Weber, Andreas P M ^a,b  

^a HEINRICH HEINE UNIVERSITY   (Germany)

^b Heinrich Heine Universität and Cluster of Excellence on Plant Sciences   (Germany)

Author keywords

C4; crops; leaf spectrometry; machine learning; phenotyping; photosynthesis

Indexed keywords

CROP; MACHINE LEARNING; METABOLISM; PHENOTYPE; PHOTOSYNTHESIS; PHYLOGENY; PHYSIOLOGY; PLANT LEAF;

CROPS, AGRICULTURAL; MACHINE LEARNING; PHENOTYPE; PHOTOSYNTHESIS; PHYLOGENY; PLANT LEAVES;

EID: 85019583576     PISSN: 16742052     EISSN: 17529867     Source Type: Journal    
DOI: 10.1016/j.molp.2017.04.009     Document Type: Article

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