Prediction of Cotton Field on Integrated Environmental Data

Sarthak Mishra, Long Ma, Nischal Aryal

Abstract

The agriculture and farming industry plays a vital role in the economy. However, the importance of agriculture cannot be fully quantified in terms of its economic profit. Agriculture affecting global hunger is a much more sensitive and vital topic. One of the leading reasons for this is un-improvised crop production. Crop production is affected by various factors, and monitoring those factors is the key to solving the problem. This paper describes a comprehensive experiment predicting the cotton yield under various environments, such as Acres Harvested, Acres Planted, Soil pH, Bulk Density, Clay-High, Clay-Low, Organic-Carbon, and Water-Area.

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Paper Citation


in Harvard Style

Mishra S., Ma L. and Aryal N. (2021). Prediction of Cotton Field on Integrated Environmental Data.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-484-8, pages 781-786. DOI: 10.5220/0010240707810786


in Bibtex Style

@conference{icaart21,
author={Sarthak Mishra and Long Ma and Nischal Aryal},
title={Prediction of Cotton Field on Integrated Environmental Data},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2021},
pages={781-786},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010240707810786},
isbn={978-989-758-484-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Prediction of Cotton Field on Integrated Environmental Data
SN - 978-989-758-484-8
AU - Mishra S.
AU - Ma L.
AU - Aryal N.
PY - 2021
SP - 781
EP - 786
DO - 10.5220/0010240707810786