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A Decision Support Framework for National Crop Production Planning

Authors :
Nida Rasheed
Shoab Ahmed Khan
Ali Hassan
Saria Safdar
Source :
IEEE Access, Vol 9, Pp 133402-133415 (2021)
Publication Year :
2021
Publisher :
IEEE, 2021.

Abstract

This paper proposes a decision support framework for defining planning parameters for national crop production. The proposed framework addresses the gaps in policymaking, the role of all stakeholders, and uses historical data of crop production in different sectors of land in optimizing the profits that shall meet the defined constraints including national requirement, and export demand of different crops. There are many agro-economy-based countries where agriculture is the main contributor to their GDP, while there are others who always struggle to meet their national need while optimizing the agro-economy component of their earnings. Crops are not always produced with keeping the demand and production balance. Rather, the crops are mostly produced according to the farmer’s ease and last year’s prices for profit maximization leading to excessive production of one type of crop, lowering of profit margins, and shortage of some key crops for national need. This paper presents a decision aiding tool that can be used for farmer’s awareness for crop production planning that meets the national and export needs while maximizing farmer’s earnings. The model is tested on historical data of different segments of cultivated lands in Pakistan for validation, with the first experiment performed on single farmland with multi-fields while the second performed for multi-locations and multi-fields. The results are promising and provide estimates of net profit, expected production against the demand for each crop, and analysis that aids in crop planning, before and after the application of our model while meeting all necessary constraints.

Details

Language :
English
ISSN :
21693536
Volume :
9
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.656e92659a1f4a0f8b697d65b8d76b24
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2021.3115801