Mathematical Modelling for Crop Selection Using Fuzzy Logic

Phagun Mehta, Manju Singh Tonk, Kautiliya Chaudhary, Vikas Siwach and Anu Tonk

Asian Journal of Agricultural Extension, Economics & Sociology, 2023, vol. 41, issue 10, 15

Abstract: In today's rapidly advancing world, research in agriculture is rapidly shifting towards mathematical modeling using soft computing techniques. Modeling techniques applied in agriculture can provide valuable insights into research priorities and the fundamental interactions of the entire soil-plant-atmosphere system. By using a model to estimate the significance and impact of specific parameters, a researcher can identify the most influential factors, leading to more informed decisions. The primary objective of this paper is to present a decision-making tool constructed with a fuzzy logic model, designed to enhance precision and reduce ambiguity in crop selection based on available soil nutrients for better crop yields. The model is applied to five samples selected from different land areas, providing a robust and representative data set. The proposed fuzzy logic model provides a powerful tool for addressing the challenge of crop selection under conditions of uncertain and incomplete information, enabling agricultural experts to make informed decisions and optimize yields.

Keywords: Research; Methods/Statistical; Methods (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ageconsearch.umn.edu/record/367696/files/Mehta41102023AJAEES104897.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:ajaees:367696

Access Statistics for this article

More articles in Asian Journal of Agricultural Extension, Economics & Sociology from Asian Journal of Agricultural Extension, Economics & Sociology
Bibliographic data for series maintained by AgEcon Search ().