Machine learning models for net photosynthetic rate prediction using poplar leaf phenotype data.

ABSTRACT: BACKGROUND: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 method to offset CO2 emissions. A high net photosynthetic rate (Pn) with fast-growing trees could efficiently fulfill the goal of CO2 emission reduction. Net photosynthetic rate model can provide refernece for plant's stability of photosynthesis productivity. METHODS AND RESULTS:Using leaf phenotype data to predict the Pn can help effectively guide tree planting policies to offset CO2 release into the atmosphere. Tree planting has been prop

SUBMITTER: Zhang XY 

PROVIDER: S-EPMC7012418 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature