Modeling and optimization of technological process and means of mechanization of grain production for middle China based on Belarusian technology

One of the main problems in grain production in China is the high level of unit costs (high cost price). The main reason is the low level of mechanization. Development of efficient technologies and means of mechanization is a promising area allowing to decrease the level of unit costs at a given labor efficiency and maintaining the achieved yield. Grain production is a complex system associated with a large amount of information: agro-technological (crop variety, crop yield, physical-and-mechanical parameters of land plots, terms of operations, permissible speed range for specific operations, etc.), technical-and-economic (power and traction parameters, throughput, working width, operating weight, hopper volume , cost). At present, efficient methods for studying complex systems have appeared as a result of development and widespread implementation of computer mathematics systems, which allow us to study mechanization technologies and tools using multi-factor modeling and multi-criteria optimization. The paper presents a multi-factor mathematical model, peculiar for the fact that the three groups of simultaneously varying factors are taken for the first time engine power, MTA speed, timing of the main energy-intensive operations – plowing, harvesting, and as conflicting optimization parameters unit cost level, coefficient of crop losses, labor efficiency, which allowed a comprehensive study of the grain production process in any natural-production conditions. A technological process has been developed (units speed and timing of the main operations (plowing, harvesting) and the corresponding range of machines and equipment, ensuring minimum level of unit costs at a given labor efficiency and maintaining the achieved crop yield, taking into account the specifics of the Middle China (2 crops per year).

1. Tang Hua-Jun, Li Zhe-Min. 基于中国居民平衡膳食模式的人均粮食需求量研究 [Study on per capita grain demand based on Chinese reasonable dietary pattern]. 中国农业科学 = Scientia Agricultura Sinica, 2012, vol. 45, no. 11, pp. 2315-2327 (in Chinese). https://doi.org/10.3864/j.issn.0578-1752.2012.11.022

2. Zhu Xianfeng, Wu Chengfang. 从中美两国成本比较看我国粮食政策取向 [Grain production trend in China and the USA]. 中国粮食经济 = China Grain Economy, 2016, no. 9, pp. 36-39 (in Chinese).

3. Hunt D. Farm power and machinery management. 4th ed. Ames, Iowa State University Press, 1964. 274 p.

4. Shilo I. N., Rodov E. G. Features of optimizing the composition of technical equipment for multi-structured agriculture. Mekhanizatsiya i elektrifikatsiya sel’skogo khozyaistva: mezhvedomstvennyi tematicheskii sbornik [Mechanization and electrification of agriculture: an interdepartmental subject collection]. Minsk, 1996, iss. 35, pp. 9-17 (in Russian).

5. Shilo I. N., Dashkov V. N. Resource-saving technologies of agricultural production. Minsk, 2003. 183 p. (in Russian).

6. Shepelev S., Shepelev V., Almetova Z. Optimization of technical equipment for crop sowing processes. Procedia Engineering, 2016, vol. 150, pp. 1258-1262. https://doi.org/10.1016/j.proeng.2016.07.142

7. Zangiev A. A., Shpil’ko A. V., Glevshin A. G. Maintenance of machine and tractor park. Moscow, KolosS Publ., 2008. 318 p. (in Russian).

8. Savochkin V. A. Tractor traction calculation. Moscow, Moscow State Technical University “MAMI”, 2001. 48 p. (in Russian).

9. Novikov A. V., Lyakhov A. P., Neparko T. A., Shilo I. N., Timoshenko V. Ya., Chebotarev V. P. (et al.). Technical support for crop production. Minsk, Belarusian State Agrarian Technical University, 2011. 408 p. (in Russian).

10. Li Qingzhen, Leonov A. N. Determination of the rated power of the tractor engine and the speed of the MTA to perform a specific operation with a minimum level of unit costs. Agropanorama, 2019, no. 4 (134), pp. 26-32 (in Russian).

11. Sawaragi Y., Tanino T., Nakayama H. Theory of multiobjective optimization. Orlando, Academic Press, 1985. 296 р. https://doi.org/10.1016/s0076-5392(09)x6017-0

12. Leonov A. N., Li Qingzhen. Determination of the rated power of the combine engine and its speed when harvesting grain, providing a minimum level of unit costs at a given labor productivity. Agropanorama, 2019, no. 6 (136), pp. 10-18 (in Russian).

13. 播种方式和播期对小麦产量的影响 [Effects of different sowing stage on yield of wheat with different sowing methods]. 现代农业科技 = Modern Agricultural Science and Technology, 2014, no. 24, pp. 11-12 (in Chinese).

14. Wu Zhong-liang, Shen Wei-qing, Jiang Yin-lou. 不同收割时期对小麦产量及千粒重的影响 [Effects of harvesting period on the yield of wheat]. 安徽农业科学 = Journal of Anhui Agricultural Sciences, 2016, no. 3, pp. 46-47 (in Chinese).

15. Li, Yilоng. 不同收获期对玉米产量的影响 [Effects of harvesting period on the yield of corn]. 现代农业科技 = Modern Agricultural Science and Technology, 2017, no. 6, pp. 14-16 (in Chinese). https:doi.org/10.3969/j.issn.1007-5739.2017.06.010

16. Tian Zhi-gang, Tian Jun-qin, Cao Zhi-yan, Zhang Yao-hui. 播种期对夏玉米产量及主要性状的影响 [Affect of sowing date on yield and main characteristics of summer maize]. 河北农业科学 = Journal of Hebei Agricultural Sciences, 2006, vol. 10, no. 4, pp. 14-15 (in Chinese). https://doi.org/10.3969/j.issn.1088-1631.2006.04.004

17. Leonov A. N., Li Qingzhen’. Modeling the dependence of actual grain yields on sowing and harvesting dates. Agropanorama, 2018, no. 4 (128), pp. 21-30 (in Russian).

18. Seber G. A. F. Linear regression analysis. New York, Wiley, 1977. 465 p.