Agronomic Analysis and Nutrient Application Guidance Using Machine Learning

Authors

  • K. Sai Saketh Reddy UG Scholar, Department of Information Technology, Sreenidhi Institute of Science and Technology, Telangana, India
  • Sengar Vikrant Pratap Singh UG Scholar, Department of Information Technology, Sreenidhi Institute of Science and Technology, Telangana, India
  • Bingi Sai Keerthan UG Scholar, Department of Information Technology, Sreenidhi Institute of Science and Technology, Telangana, India
  • B. Ravinder Reddy Assistant Professor, Department of Information Technology, Sreenidhi Institute of Science and Technology, Telangana, India

DOI:

https://doi.org/10.51983/ajeat-2023.12.1.3657

Keywords:

Machine Learning, Decision Tree, Random Forest, Database, Python

Abstract

The Indian economy has always been based primarily on agriculture. The industry has met the entire nation’s food consumption needs while ranking among the top exporters of agricultural products worldwide. Although this industry has faced its fair share of difficulties lately, few of them are as pressing as they were before Covid-19’s limits on local and international travel. Agriculture and farming enterprises have an opportunity to expand as more people become aware of the value of wholesome food and the reasons why terms like “organic” actually matter. Online marketing is a simple way to improve sales, brand awareness, and market share in the farming and agricultural sectors. One of the most significant factors that makes websites useful is that unlike in the past, this growth is enabling business owners and farmers to specify how they must operate. But because of the shortage of labour caused by the reverse labour migration, which hindered harvesting, farmers need a strategy to boost production. Farmers must grow the appropriate crops and apply the appropriate fertilisers in order to maintain a constant output. Many farmers plant crops that are inappropriate for a particular piece of land because they are unaware of this, wasting a tonne of time and resources. Farmers can therefore use web tools to help them find the best crop to cultivate on their land in order to overcome this dilemma.

References

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Published

01-06-2023

How to Cite

Sai Saketh Reddy, . K., Pratap Singh, S. V., Sai Keerthan, B., & Ravinder Reddy, B. (2023). Agronomic Analysis and Nutrient Application Guidance Using Machine Learning. Asian Journal of Engineering and Applied Technology, 12(1), 45–50. https://doi.org/10.51983/ajeat-2023.12.1.3657

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