Academic Journal of Agricultural Sciences, 2022, 3(2); doi: 10.38007/AJAS.2022.030204.
Shu Chen
Zhanjiang Science and Technology College, Zhanjiang, China
In recent years, big data analysis technology has become one of the important research topics in the information field, and has been widely used in many fields such as web search, e-commerce, financial analysis, and medical services. As one of the important industries in the era of big data, e-commerce affects the level of China's social and economic development. As one of the most promising high-yield economic crops in China, potato occupies a considerable proportion in agricultural e-commerce. To this end, this article will take the potato industry as an example and develop regional e-commerce in China based on big data research. This paper uses a combination of SWOT analysis method and literature research method for research, and selects Guangxi Guigang as a case study for analysis. The study found that the total output of fresh potatoes in Guigang City increased from 97,500 tons in 2013 to 215,500 tons in 2019.The average unit area output of fresh potatoes in the past 7 years was 21343.41 kg / hm2, which was equivalent to a yield of 4178.14 kg per 5: 1 / hm2, far exceeding the national unit yield of 3387kg / hm2. It can be seen that with the advent of the era of big data and the development of e-commerce for agricultural products, the potato industry in Guigang is getting better and better.
Big Data Analysis, Regional Agricultural Products, E-Commerce Development, Potato Industry
Shu Chen. The Development of Regional Agricultural E-commerce in China Based on Big Data Analysis: A Case Study of Potato Industry. Academic Journal of Agricultural Sciences (2022), Vol. 3, Issue 2: 38-53. https://doi.org/10.38007/AJAS.2022.030204.
[1] Kubra Eryasar, & Seda Karasu-Yalcin. (2016). “Evaluation of Some Lignocellulosic Byproducts of Food Industry for Microbial Xylitol Production by Candida Tropicalis,” Biotech, 6(2), pp.202. https://doi.org/10.1007/s13205-016-0521-8
[2] V. Tyurin, V. Yu. Kryukov, O. N. Yaroslavtseva, E. A. Elisafenko, & V. V. Glupov. (2016). “Comparative Analysis of Immune Responses in Colorado Potato Beetle Larvae During Development of Mycoses Caused by Metarhizium Robertsii, m. Brunneum, and m. Pemphigi,” Journal of Evolutionary Biochemistry & Physiology, 52(3), pp.252-260. https://doi.org/10.1134/S002209301603008X
[3] He, G. (2021). Enterprise E-Commerce Marketing System Based on Big Data Methods of Maintaining Social Relations in the Process of E-Commerce Environmental Commodity. Journal of Organizational and End User Computing (JOEUC), 33(6), 1-16. http://doi.org/10.4018/JOEUC.20211101.oa16
[4] Kent F. McCue. (2018). “Mitigation of Acrylamide: a Multidisciplinary Approach to an Industry Problem,” American Journal of Potato Research, 95(4),pp.1-2. https://doi.org/10.1007/s12230-018-9661-1
[5] V.K. Bosak, A.C. VanderZaag, A. Crolla, C. Kinsley, & R.J. Gordon. (2016). “Treatment of Potato Farm Wastewater with Sand Filtration,” Environmental Technology, 37(13), pp.1-8. https://doi.org/10.1080/09593330.2015.1122095
[6] Amy E. Wiberley-Bradford, & Paul C. Bethke. (2017). “Rate of Cooling Alters Chip Color, Sugar Contents, and Gene Expression Profiles in Stored Potato Tubers,” American Journal of Potato Research, 94(5), pp.1-10. https://doi.org/10.1007/s12230-017-9591-3
[7] Igor V Tetko, Ola Engkvist, Uwe Koch, Jean-Louis Reymond, & Hongming Chen. (2016). “Bigchem: Challenges and Opportunities for Big Data Analysis in Chemistry,” Molecular Informatics, 35(11-12), pp.615-621. https://doi.org/10.1002/minf.201600073
[8] Oswald Aguilar Dowins , Omar Mar Cornelio, (2021). Computer Network Design of the office area of the telecommunications company SERTOD, Fusion: Practice and Applications, 6(1), pp. 26-31https://doi.org/10.54216/FPA.060101
[9] Robert Thorstad, & Phillip Wolff. (2018). “A Big Data Analysis of the Relationship Between Future Thinking and Decision-Making,” Proceedings of the National Academy of Sciences of the United States of America, 115(8), pp.201706589. https://doi.org/10.1073/pnas.1706589115
[10] Juyoung Song, Tae Min Song, Dong-Chul Seo, Dal-Lae Jin, & Jung Sun Kim. (2017). “Social Big Data Analysis of Information Spread and Perceived Infection Risk During the 2015 Middle East Respiratory Syndrome Outbreak in South Korea,” Cyberpsychology Behavior & Social Networking, 20(1), pp.22-29. https://doi.org/10.1089/cyber.2016.0126
[11] M.M.El-Gayar , M. EL-Hasnony, (2021). Intelligent System for Ranking Big Data in Search Engine, Journal of Intelligent Systems and Internet of Things, 3(2), pp. 43-56 https://doi.org/10.54216/JISIoT.030201
[12] Sarbesh Das Dangol, Abdellah Barakate, Jennifer Stephens, Mehmet Emin Çalıskan, & Allah Bakhsh. (2019). “Genome Editing of Potato Using Crispr Technologies: Current Development and Future Prospective,” Plant Cell Tissue and Organ Culture(12),pp.1-14. https://doi.org/10.1007/s11240-019-01662-y
[13] Elisa Boyd, Eileen Carpenter, Brian T. Ross, Nina Zidack, & Michelle L. Flenniken. (2018). “Potato Cultivar and Seed Type Affect the Development of Systemic Potato Virus Y (Pvyn-wi) Infection,” American Journal of Potato Research, 95(1),pp.183-190. https://doi.org/10.1007/s12230-017-9625-x
[14] Yuan, C., Wu, C., Wang, D., Yao, S., & Feng, Y. (2021). Review of Consumer-to-Consumer E-Commerce Research Collaboration. Journal of Organizational and End User Computing (JOEUC), 33(4), 167-184. http://doi.org/10.4018/JOEUC.20210701.oa8
[15] Shawn C. Beam, Katherine M. Jennings, David W. Monks, Jonathan R. Schultheis, & Sushila Chaudhari. (2017). “Influence of Herbicides on the Development of Internal Necrosis of Sweetpotato,” Weed Technology, 31(6), pp.1-7. https://doi.org/10.1017/wet.2017.60
[16] Jin-Hee Kim, Jun-Hoi Kim, Won-Sam Jo, Jeong-Gwan Ham, & Kyung-Min Kim. (2016). “Characterization and Development of Est-Ssr Markers in Sweet Potato (Ipomoea Batatas (l.) lam),” Biotech, 6(2),pp. 243. https://doi.org/10.1007/s13205-016-0565-9
[17] Hou, J., Li, Q., Liu, Y., & Zhang, S. (2021). An Enhanced Cascading Model for E-Commerce Consumer Credit Default Prediction. Journal of Organizational and End User Computing (JOEUC), 33(6), 1-18. http://doi.org/10.4018/JOEUC.20211101.oa13