Machine learning models for net photosynthetic rate prediction using poplar leaf phenotype data
Machine learning models for net photosynthetic rate prediction using poplar leaf phenotype data
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Publisher
United States: Public Library of Science
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Language
English
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Publisher
United States: Public Library of Science
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Contents
As an essential component in reducing anthropogenic CO2 emissions to the atmosphere, tree planting is the key to keeping carbon dioxide emissions under control. In 1992, the United Nations agreed to take action at the Earth Summit to stabilize and reduce net zero global anthropogenic CO2 emissions. Tree planting was identified as an effective metho...
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Full title
Machine learning models for net photosynthetic rate prediction using poplar leaf phenotype data
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TN_cdi_plos_journals_2353557233
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2353557233
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ISSN
1932-6203
E-ISSN
1932-6203
DOI
10.1371/journal.pone.0228645
