UNCOVERING CARBON EMISSION CHARACTERISTICS OF AGRICULTURAL CROPS AND LIVESTOCK BY ARTIFICIAL INTELLIGENCE

Authors

  • Rodrin Rivelleza Rivera Northwestern Mindanao State College of Science and Technology, Tangub City, Misamis Occidental http://orcid.org/0000-0002-5725-7443
  • Vincent T. Lapinig Northwestern Mindanao State College of Science and Technology, Tangub City, Misamis Occidental http://orcid.org/0000-0003-1838-5300
  • Johnny Mark M. Bolante Northwestern Mindanao State College of Science and Technology, Tangub City, Misamis Occidental http://orcid.org/0000-0003-2161-862X
  • Celia Judith Vasquez Universidad Nacional Agraria La Molina, Peru

Keywords:

carbon dioxide, photosynthesis, livestock, crop production

Abstract

This study attempts to verify the results reported by Atkin (2017) that plants are in fact, ultimate source of carbon dioxide. The study utilized the descriptive design of research. Data of carbon dioxide emissions were gathered from Carbon Dioxide Information Analysis and data of livestock and crop production were gathered from Food and Agricultural Organization from 1960 to 2013. The data analysis is based on a simplified assumption that the accumulated CO2 in the atmosphere includes agricultural crop production and livestock production as sources. In order to treat the data, symbolic regression was used. Symbolic regression is a type of regression analysis that does not specify the functional form of relationships between two variables. It utilizes genetic algorithm to execute the analysis.  The study provides further evidence of the claim that plants actually produce more carbon dioxide than was previously held. The study also strengthens the hypothesis that with global warming and with countries in tropical climates like the Philippines, CO2 emissions from plants can be more than 11 times higher than traditional knowledge held.

References

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Published

2018-12-31