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Reseach Article

Eco: Digitization of Organic Farming in Sri Lanka

by K.M.A.B. Kiridena, J.A.U.M. Jayasinghe, T.R.M. Arachchi, Y.G.R.M. Bandara, Manori Gamage
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 185 - Number 3
Year of Publication: 2023
Authors: K.M.A.B. Kiridena, J.A.U.M. Jayasinghe, T.R.M. Arachchi, Y.G.R.M. Bandara, Manori Gamage
10.5120/ijca2023922681

K.M.A.B. Kiridena, J.A.U.M. Jayasinghe, T.R.M. Arachchi, Y.G.R.M. Bandara, Manori Gamage . Eco: Digitization of Organic Farming in Sri Lanka. International Journal of Computer Applications. 185, 3 ( Apr 2023), 13-19. DOI=10.5120/ijca2023922681

@article{ 10.5120/ijca2023922681,
author = { K.M.A.B. Kiridena, J.A.U.M. Jayasinghe, T.R.M. Arachchi, Y.G.R.M. Bandara, Manori Gamage },
title = { Eco: Digitization of Organic Farming in Sri Lanka },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2023 },
volume = { 185 },
number = { 3 },
month = { Apr },
year = { 2023 },
issn = { 0975-8887 },
pages = { 13-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume185/number3/32684-2023922681/ },
doi = { 10.5120/ijca2023922681 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:25:09.882419+05:30
%A K.M.A.B. Kiridena
%A J.A.U.M. Jayasinghe
%A T.R.M. Arachchi
%A Y.G.R.M. Bandara
%A Manori Gamage
%T Eco: Digitization of Organic Farming in Sri Lanka
%J International Journal of Computer Applications
%@ 0975-8887
%V 185
%N 3
%P 13-19
%D 2023
%I Foundation of Computer Science (FCS), NY, USA
Abstract

From the beginning, Sri Lanka has been an agrarian civilization. When Sri Lanka was colonized, the plantation sector, which specialized in rubber, tea, and coconut, was given precedence. Following independence in 1948, a greater focus was placed on the production of food crops. A significant portion of the Sri Lankan population works in agriculture, and there is a growing need to promote organic farming. Low economic growth has come from farmers and out-growers incapacity to make educated and productive judgments quickly. As a result, they're having trouble deciding what to grow next, as well as client consumption trends and the most in-demand locations for a certain crop. Farmers also require a reliable communication system to coordinate a variety of operations related to their crops, such as fertilizing, planting, and harvesting. Due to a lack of information exchange, farmers are now uninformed of the behavior of the Sri Lankan market and worldwide agricultural trends. Because of assessing these scenarios, a system for forecasting demand for certain vegetables is needed. As a consequence of this study, it is suggested that the major variables driving vegetable demand and price variations in Sri Lanka be identified and that a model be trained using machine learning to predict demand and price. Additionally, determine the optimum cultivation for current land and recommend favorable circumstances depending on the crop, making this computerized method more reliable and convenient. The system's ultimate goal is to assist users in making high-quality, timely judgments to achieve the sector's optimum growth.

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Index Terms

Computer Science
Information Sciences

Keywords

Agriculture demand forecasting Price prediction Neural network Sri Lanka Regression approach crop favorable conditions best crops for existing lands.