| Issue |
BIO Web Conf.
Volume 71, 2023
II International Conference on Current Issues of Breeding, Technology and Processing of Agricultural Crops, and Environment (CIBTA-II-2023)
|
|
|---|---|---|
| Article Number | 01066 | |
| Number of page(s) | 8 | |
| Section | Issues of Sustainable Development of Agriculture | |
| DOI | https://doi.org/10.1051/bioconf/20237101066 | |
| Published online | 07 November 2023 | |
Linear-dynamic model of the problem of optimization of placement and alternation of crops in cropping rotation
1 ”Tashkent Institute of Irrigation and Agricultural Mechanization Engineers” National Research University, Tashkent, Uzbekistan
2 Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, 108, Amir Temur Avenue, Tashkent, 100084, Uzbekistan
3 Fiscal Institute of the Tax Committee under the Ministry of Economy and Finance of the Republic of Uzbekistan, Uzbekistan
* Corresponding author: dilnoz134@rambler.ru
The problem of determining the best positioning and rotation of crops within fields of crop rotation has been approached through two different methods, static and dynamic. In the static model, specific schemes are chosen based on the predetermined number and size of rotation fields that can accommodate a particular crop. The model takes into consideration various factors such as crop yields within the same field, cotton production volume, labor costs, production expenses, and conditional net income. The optimization criterion in this model is to minimize production costs and maximize conditional net income, which is the difference between the costs of gross output per hectare and production expenses per hectare. The initial data is computed using long-term farm data, and information is prepared for each crop rotation scheme to enable a comprehensive evaluation of all crop rotation schemes and fields while taking into account major indicators of farm production.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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