Machine Learning Approach: Recommendation of Suitable Crop for Land Using Meteorological Factors

7 Pages Posted: 2 Dec 2020

See all articles by Srilakshmi A

Srilakshmi A

SASTRA Deemed tO be University

Madhumitha K

SASTRA Deemed tO be University

Geetha K

SASTRA Deemed tO be University

Date Written: November 24, 2020

Abstract

Increasing population increases the need for food. As most population migrates towards cities for employment, the cultivable lands are turning into factories and apartments. The landlords are selling the plots due to the loss they face after cultivation. This loss occurs due to improper selection of crop for the particular field. The loss could be rectified if they are suggested with a suitable crop, based on the meteorological factors over the land area like testing soil quality, humidity, pH, etc. The farmers in interior places face difficulty in consulting with the experts for selection or rotation of crop. To overcome this problem, ANN came to play a role and also gave an effective solution. After knowing the suitable crop for the field, it is getting easier to decide the fertilizers and intercrop alongside. The profit rate will be considerably high using this method. It is also cost-efficient. This paper discusses the model for crop prediction using Machine learning algorithms. The model is compared with different approaches such as random forest, decision tree and SVM aiming to get a complete solution for the crop prediction and recommendation problem.

Keywords: Artificial neural networks (ANN), Decision Tree (DT), Support Vector Machine (SVM)

Suggested Citation

A, Srilakshmi and K, Madhumitha and K, Geetha, Machine Learning Approach: Recommendation of Suitable Crop for Land Using Meteorological Factors (November 24, 2020). Proceedings of the 2nd International Conference on IoT, Social, Mobile, Analytics & Cloud in Computational Vision & Bio-Engineering (ISMAC-CVB 2020), Available at SSRN: https://ssrn.com/abstract=3736550 or http://dx.doi.org/10.2139/ssrn.3736550

Srilakshmi A (Contact Author)

SASTRA Deemed tO be University ( email )

Thirumalaisamudrum
Thanjavur, TN Tamilnadu 613401
India

Madhumitha K

SASTRA Deemed tO be University ( email )

Thirumalaisamudrum
Thanjavur, TN Tamilnadu 613401
India

Geetha K

SASTRA Deemed tO be University ( email )

Thirumalaisamudrum
Thanjavur, TN Tamilnadu 613401
India

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