新疆生产建设兵团棉花生产大数据平台建设与探索

doi:10.19788/j.issn.2096-6369.200109

Abstract

Abstract:

The Xinjiang Production and Construction Corps (XPCC) have created a modern cotton planting system with regional characteristics in China. This new system advances Chinese production techniques in the aspects of agricultural intensification, scale, development of agricultural machinery, and application of modern agricultural technology. During the years of systematic development and performance, massive data were accumulated by XPCC in the cotton planting field. As big data technology has become an important driving force for the development of intelligent agriculture in China, how to apply this technology to further improve the intelligent level of the cotton planting system and realize the healthy, efficient, and sustainable development of the whole cotton industry chain is a key problem in strengthening and enhancing XPCC’s ability to reclaim and defend the Chinese border in the information age. Thus, we constructed a big data platform that covers the entire industrial chain for cotton production in China based on a mature commercial big data storage and analysis system framework to promote the cooperation of industry, colleges, and institutes for cotton production big data in the XPCC. This platform was comprised of data, model, system, and application layers from the bottom up. In each layer, the cotton production chain was analyzed using five dimensions of agricultural resources, agricultural monitoring, production management, agricultural machinery scheduling, and market prediction. After completion, the developed platform intends to provide big data for comprehensive management and sharing, remote-sensing monitoring, agricultural machinery operation monitoring and maintenance, intelligent decision-making, quality traceability, and market early warning and prediction services for cotton production to potential users involved in cotton production and management. Finally, this paper analyzes the problems encountered in data sharing, model upgrades, and service modes in the process of platform research and development, and puts forward some suggestions to provide references for agricultural big data resource sharing and platform construction in China.

Key words: cotton, big data, informatization agriculture, intelligent agriculture, Xinjiang, agricultural big data, industry chain, data platform

CLC Number:

G203

Xin Lv, Bin Liang, Lifu Zhang, Fuyu Ma, Haijiang Wang, Yangchun Liu, Pan Gao, Zhangze, HouTongyu. Construction of an Agricultural Big Data Platform for XPCC Cotton Production[J].Journal of Agricultural Big Data, 2020, 2(1): 70-78.

Figures/Tables 2

References 30

1	中国农业科学院棉花研究所 . 中国棉花栽培学[M]. 中国上海: 上海科学技术出版社,2013.
	Institute of Cotton Research of CAAS . Chinese Cotton Cultivation[M]. China Shanghai: Shanghai Scientific and Technical Publishers,2013.
2	赵春江,杨信廷,李斌,等 . 中国农业信息技术发展回顾及展望[J]. 农学学报,2018,8(1): 180–186.
	Zhao C J , Yang X T , Li B , et al . The Retrospect and Prospect of Agricultural Information Technology in China[J],Journal of Agriculture,2018,8(1): 180-186.
3	王海江,吕新 . 基于GIS技术的新疆棉花施肥专家系统[J]. 农业工程学报,2006,22(10): 167–170.
	Wang HaiJ , Lv x . Fertilization Expert System for Xinjiang Cotton Production Based on GIS Technology. Transactions of the Chinese Society of Agricultural Engineering,2006,22(10): 167–170.
4	武建设,陈学庚 . 兵团棉花生产机械化发展现状问题及对策[J]. 农业工程学报,2015,31(18): 5–10.
	Wu J S , Chen X G . Present situation,problems and countermeasures of cotton production mechanization development in Xinjiang Production and Construction Corps. Transactions of the Chinese Society of Agricultural Engineering,2015,31(18): 5–10.
5	梁亚军,李雪源,龚照龙,等 . 新疆快速发展机采棉前后存在的问题比较及对策[J]. 棉花科学,2017,39(2): 2–5.
	Liang Y J , LI X Y , GONG Z L , et al . Comparison and countermeasures of problems before and after the rapid development of cotton picking in Xinjiang[J]. Cotton Science, 2017, 39(2): 2–5.
6	田景山,张煦怡,张旺锋 . 新疆近年机采棉发展过程中的棉纤维品质变化[J]. 中国棉花,2017,44(12): 27–31.
	Tian J S , Zhang Y Y , Zhang W F . Changes in cotton fiber quality during the development of cotton in recent years in Xinjiang[J]. China Cotton, 2017, 44(12): 27–31.
7	温孚江,宋长青 . 农业大数据应用、研究与展望[J]. 农业网络信息,2017(5): 31–36.
	Wen F J , Song C Q . Application Research and Prospect of Agricultural Big Data[J]. Agriculture Network Information,2017(5): 31–36.
8	李道亮 . 农业4.0——即将到来的智能农业时代[J]. 农业工程技术,2017,37(30): 42–49.
	Li D L . Agriculture 4.0——The Era of Intelligent Agriculture[J]. Agricultural Engineering Technology, 2017, 37(30): 42–49.
9	周国民 . 我国农业大数据应用进展综述[J]. 农业大数据学报,2019,1(1): 16–23.
	Zhou G M . Progress in the Application of Big Data in Agriculture in China [J]. Journal of Agricultural Big Data,2019,1(1):16-23
10	田笑明,李雪源,吕新,等 . 新疆棉作理论与现代植棉技术[M]. 北京: 科学出版社,2016.
	Tian X M , Li X Y , Lv X , et al . The Theory of Cotton Cultivation and Modern Cotton Planting Technology in Xinjiang[M]. Beijing: Beijing Science Press,2016.
11	赵岩,陈学庚,温浩军 . 兵团精准农业发展与北斗卫星导航技术的应用[J]. 石河子大学学报：自然科学版,2018,36(4): 397–404.
	Zhao Y , Chen X G , Wen H J . The Development of Precision Agriculture in Xinjiang Corps and the Application of Beidou Satellite Navigation Technology[J]. Journal of Shihezi University: Natural Science Edition, 2018, 36(4): 397–404.
12	欧阳金琼,马琼,肖云云 . 兵团农牧团场公司化改革的困境与对策[J]. 农业现代化研究,2018,39(4): 673–679.
	Ouyang J Q , Ma Q , Xiao Y Y . Difficulties and countermeasures of corporatization reform in Xinjiang Bingtuan Agricultural and Pastoral Corps[J]. Journal of Agricultural Modernization, 2018, 39(4): 673–679.
13	唐姚,邵战林,常哲 . 兵团综合配套改革中农业生产经营体制改革的研究及展望[J]. 农业与技术,2019,39(3): 160–163.
	Tang Y , Shao Z L , Chang Z . Research and Prospect of Agricultural Production Management System Reform in Comprehensive Reform of Corps[J]. Agriculture & Technology, 2019, 39(3): 160–163.
14	刘海启 . 以精准农业驱动农业现代化加速现代农业数字化转型[J]. 中国农业资源与区划,2019,40(1): 1–6.
	Liu H Q . Accelerating the Digital Transformation of Modern Agriculture by Accelerating Agriculture Driven by Precision Agriculture[J]. China Agricultural Resources and Regional Planning, 2019, 40(1): 1–6.
15	叶戬春 . 棉纺企业对棉花质量的需求[J]. 中国纤检,2018,0(1): 24–29.
	Ye Y C . The demand for cotton quality in cotton spinning enterprises[J]. China Fiber Inspection, 2018, 0(1): 24–29.
16	马欣楠 . 浅析我国棉花目标价格改革试点政策效应[J]. 中国统计,2018,0(4): 23–25.
	Ma X N . Analysis of the Policy Effect of China's Cotton Target Price Reform Pilot[J]. China Statistics, 2018, 0(4): 23–25.
17	张立福,陈浩,孙雪剑,等 . 多维遥感数据时空谱一体化存储结构设计[J]. 遥感学报,2017,21(1): 62–73.
	Zhang L F , Chen H , Sun X J , et al . Design of space-time spectrum integrated storage structure for multi-dimensional remote sensing data[J]. Journal of Remote Sensing, 2017, 21(1): 62–73.
18	贡军 . 浅议农业大数据背景下的互联网+“智慧农机”[J]. 2018(18): 56–59.
	Gong J . Discussion on the Internet + "Smart Agricultural Machinery" under the Background of Agricultural Big Data[J]. 2018(18): 56–59.
19	谢斌,吴仲斌,毛恩荣 . 农业拖拉机关键技术发展现状与展望[J]. 农业机械学报,2018,49(8).
	Xie B , Wu Z B , Mao E R . Current Status and Prospects of Key Technologies in Agricultural Tractor[J]. Transactions of the Chinese Society of Agricultural Machinery, 2018, 49(8).
20	侯亮,王新栋,高倩,等 . 基于Hadoop的农业大数据挖掘系统构建[J]. 农业图书情报学刊,2018,30(7): 19–21.
	Hou L , Wang X D , Gao Q , et al . Construction of Agricultural Big Data Mining System Based on Hadoop[J]. Journal of Agricultural Library and Information Sciences, 2018, 30(7): 19–21.
21	李俊清,宋长青,周虎 . 大数据背景下农业数据资源分类及应用前景浅析[J]. 农业图书情报学刊,2018,30(4): 23–27.
	Li J Q , Song C Q , Zhou H . Analysis on Classification and Application Prospect of Agricultural Data Resources under the Background of Big Data[J]. Journal of Agricultural Library and Information Sciences, 2018, 30(4): 23–27.
22	陈科文,张祖平,龙军 . 多源信息融合关键问题、研究进展与新动向[J]. 计算机科学,2013,40(8): 6–13.
	Chen K W , Zhang Z P , LONG Jun . Key Issues, Research Progress and New Trends of Multi-source Information Fusion[J]. Computer Science, 2013, 40(8): 6–13.
23	化柏林,李广建 . 大数据环境下多源信息融合的理论与应用探讨[J]. 图书情报工作,2015,0(16): 5–10.
	Hua B L , Li G J . Discussion on the Theory and Application of Multi-source Information Fusion in Big Data Environment[J]. Library and Information Service, 2015, 0(16): 5–10.
24	丁建国,穆月英 . 棉花市场价格时序变动、风险特征及作用因素分析[J]. 新疆农业科学,2018,55(9): 1755–1762.
	Ding J G , Mu Y Y . Analysis of price price changes, risk characteristics and contributing factors in cotton market[J]. Xinjiang Agricultural Sciences, 2018, 55(9): 1755–1762.
25	李德超 . 我国首份可持续发展遥感监测报告发布[J]. 智慧中国,2017,0(6): 10–11.
	Li D C . China's first sustainable development remote sensing monitoring report released [J]. Smart China, 2017, 0 (6): 10–11.
26	顾佳敏,王佩玲,刘阳天,等 . 基于数字图像的棉田复杂背景下棉蚜统计方法[J]. 新疆农业科学,2018,55(12): 2279–2287.
	Gu J M , Wang P L , Liu Y T , et al . Statistical method of cotton aphid under the complex background of cotton field based on digital image[J]. Xinjiang Agricultural Sciences, 2018, 55(12): 2279–2287.
27	宋长青,温孚江,李俊清,等 . 农业大数据研究应用进展与展望[J]. 农业与技术,2018,38(22): 153–156.
	Song C Q , Wen F J , Li J Q , et al . Progress and prospect of agricultural big data research and application[J]. Agriculture & Technology,2018,38(22): 153–156.
28	赵瑞雪,赵华,朱亮 . 国内外农业科学大数据建设与共享进展[J]. 农业大数据学报,2019,1(1): 24–37.
	Zhao R X , Zhao H , Zhu L . Progress in the Development and Sharing of Big Data in Agricultural Science between China and Foreign Countries[J]. Journal of Agricultural Big Data,2019,1(1): 24-37
29	程志强,蒙继华 . 作物单产估算模型研究进展与展望[J]. 中国生态农业学报,2015,23(4): 402–415.
	Cheng Z Q , Meng J H . Research Advances and Perspectives on Crop Yield Estimation Models[J]. Chinese Journal of Eco-Agriculture,2015,23(4): 402–415.
30	崔运鹏,王健,刘娟 . 基于深度学习的自然语言处理技术的发展及其在农业领域的应用[J]. 农业大数据学报,2019,1(1): 38–44.
	Cui Y P , Wang J , Liu J . The Development of Deep Learning Based Natural Language Processing (NLP) Technology and Applications in Agriculture[J]. Journal of Agricultural Big Data,2019,1(1): 38-44.

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Construction of an Agricultural Big Data Platform for XPCC Cotton Production

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