review Open AccessTop 1% cited
Machine Learning for High-Throughput Stress Phenotyping in Plants
Trends in Plant Science · 2015 · Vol. 21(2) · pp. 110–124
Arti Singh✉(Iowa State University)Baskar Ganapathysubramanian(Iowa State University)Asheesh K. Singh(Iowa State University)Soumik Sarkar(Iowa State University)
Smart Agriculture and AISpectroscopy and Chemometric AnalysesBiologyThroughputPlant scienceComputational biologyBotanyComputer science
MeSH terms
Machine LearningBreedingPhenotypePlantsStress, PhysiologicalHigh-Throughput Screening Assays
Funding
- Iowa State University
- Plant Sciences Institute, Iowa State University
Citations
1,057
FWCI
59.48
field-weighted impact
References
91
Percentile
100%
vs. same field & year
Citations per year
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References
A Review of Imaging Techniques for Plant Phenotyping
Sensors · 2014 · 1,045 citations
Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype–phenotype relationships and its relevance to crop improvement
Theoretical and Applied Genetics · 2013 · 652 citations
Classification of brain tumor type and grade using MRI texture and shape in a machine learning scheme
Magnetic Resonance in Medicine · 2009 · 835 citations
Gene Selection for Cancer Classification using Support Vector Machines
Machine Learning · 2002 · 9,679 citations
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