大数据在精准农业上的应用
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摘要
精准农业是农业现代化的必由之路,现代急剧膨胀的农业数据和大数据技术的发展为精准农业的发展提供了一种新的方法,成为引领精准农业发展的一支重要力量。首先介绍了大数据的定义及获取方式,同时针对当前农业领域存在的一些问题,引入了精准农业的概念,并介绍了其来源与发展条件,将农业产业链与大数据应用结合起来,解析大数据实现精准农业的过程,并剖析了中国农业大数据应用方面所存在的问题。
Precision agriculture is the future way for agricultural modernization. The rapid expansion of agricultural data and the development of big data technology provide a new method for the development of precision agriculture,and become an important force leading to the development of precision agriculture. Firstly,this paper introduced the definition and acquisition methods of big data. At the same time,the concept of precision agriculture were introduced for some problems existing in the current agricultural field,and its source and development conditions. Combining the industrial chain of agriculture with the application of big data,this paper analyzed the process of big data to achieve precision agriculture,and the problems in the application of China's agricultural big data.
Precision agriculture is the future way for agricultural modernization. The rapid expansion of agricultural data and the development of big data technology provide a new method for the development of precision agriculture,and become an important force leading to the development of precision agriculture. Firstly,this paper introduced the definition and acquisition methods of big data. At the same time,the concept of precision agriculture were introduced for some problems existing in the current agricultural field,and its source and development conditions. Combining the industrial chain of agriculture with the application of big data,this paper analyzed the process of big data to achieve precision agriculture,and the problems in the application of China's agricultural big data.
引文
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[3]蔡书凯.大数据与农业:现实挑战与对策[J].电子商务,2014(1):3-4.Cai S K. Big data and Agriculture:Realistic challenges and countermeasures[J]. E-Business J.,2014(1):3-4.
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[9]柳彩莲.论“互联网+农业”的新经营策略[J].中国集体经济,2015(19):63-65.
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[12]褚成斌. Descartes Labs用卫星遥感数据预测农作物收成,目标是掌握全球循环系统[EB/OL〗. https://mp.weixin. qq.com/s/HL6m844MfeUYkl8N8xlXkA,2018-01-18.
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[14] Li S N,Dragicevic S,Antón Castro F,et al.. Geospatial big data handling theory and methods:a review and research challenges[J]. ISPRS J. Photogram. Remote Sensing,2016,115:119-133.
[15] Moore T S,Campbell J W,Feng H. Characterizing the uncertainties in spectral remote sensing reflectance for SeaWiFS and MODIS-Aqua based on global in situ matchup data sets[J]. Remote Sensing Environ.,2015,159:14-27.
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[18] Waga D, Rabah K. Environmental conditions'big data management and cloud computing analytics for sustainable agriculture[J]. World J. Computer Appl. Technol.,2014,2(3):73-81.
[19] King A. The future of agriculture[J]. Nature,2017,544(7651):S21-S23.
[20] Steduto P,Hsiao T C,Raes D,et al.. Aqua Crop——The FAO crop model to simulate yield response to water:I.Concepts and underlying principles[J]. Agron. J.,2009,101(3):426-437.
[21]王静,李新.基于作物生长模型和多源数据的融合技术研究进展[J].遥感技术与应用,2015,30(2):209-219.Wang J,Li X. Progresses on data fusion technology of crop growth model and multi-source observation information[J].Remote Sensing Technol. Appl.,2015,30(2):209-219.
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[23] Tan S,Wang Q,Zhang J,et al.. Performance of AquaCrop model for cotton growth simulation under film-mulched drip irrigation in southern Xinjiang, China[J]. Agric. Water Manage.,2018,196:99-113.
[24]曹卫星,罗卫红.作物系统模拟及智能管理[M].北京:华文出版社,2000.Cao W X,Luo W H. Crop System Simulation and Intelligent Management[M]. Beijing:Huawen Publishing House,2000.
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[26] Tao F,Zhang Z. Climate change,wheat productivity and water use in the North China Plain:A new super-ensemble-based probabilistic projection[J]. Agric. Forest Meteorol.,2013,170:146-165.
[27]刘双印,徐龙琴,沈玉利,等.基于.NET的对虾病害防治专家系统的设计与实现[J].计算机工程与设计,2008,29(13):3444-3447.Liu S Y, Xu L Q, Shen Y L, et al.. Design and implementation fo expert system for prawn disease diagnose and prevention based on. NET platform[J]. Computer Engin.Design,2008,29(13):3444-3447.
[28] Kang Y S, Park I H, Rhee J, et al.. MongoDB-based repository design for Io T-generated RFID/sensor big data[J].IEEE Sensors J.,2016,16(2):485-497.
[29] Zaslavsky A,Perera C,Georgakopoulos D. Sensing as a service and big data[A]. In:Proceedings of the international conference on advances in cloud computing[C]. India Bangalore,2012.
[30]谢文霞,王光火,张奇春. WOFOST模型的发展及应用[J].土壤通报,2006(1):154-158.Xie W X,Wang G H,Zhang Q C. Development of WOFOST(World Food Studies)and its application[J]. Chin. J. Soil Sci.,2006(1):154-158.
[31] Huang J,Tian L,Liang S,et al.. Improving winter wheat yield estimation by assimilation of the leaf area index from Landsat TM and MODIS data into the WOFOST model[J]. Agric.Forest Meteorol.,2015,204:106-121.
[32] Huang J,Sedano F,Huang Y,et al.. Assimilating a synthetic Kalman filter leaf area index series into the WOFOST model to improve regional winter wheat yield estimation[J]. Agric.Forest Meteorol.,2016,216:188-202.
[33]何亮,侯英雨,赵刚,等.基于全局敏感性分析和贝叶斯方法的WOFOST作物模型参数优化[J].农业工程学报,2016,32(02):169-179.He L,Hou Y Y,Zhao G,et al.. Parameters optimization of WOFOST model by integration of global sensitivity analysis and Bayesian calibaration method[J]. Trans. Chin. Soc. Agric.Engin.,2016,32(02):169-179.
[34] Xu S,Li G,Li Z. China agricultural outlook for 2015-2024based on China agricultural monitoring and early-warning system(CAMES)[J]. J. Integrative Agric.,2015,14(9):1889-1902.
[35]吴佩.中国农业展望报告是如何出炉的[N].农民日报,2017-05-06,第006版.
[36]许世卫.农业大数据与农产品监测预警[J].中国农业科技导报,2014,16(5):14-20.Xu S W. Agrucultural big data and monitoring and early warning of agricultural products[J]. J. Agric. Sci. Technol.,2014,16(5):14-20.
[37] Bhushan B. Observational network and drought monitoring[A]. In:Handbook of Drought and Water Scarcity:Principles of Drought and Water Scarcity[M]. 2017:3.??
[38] Marvin H J P, Kleter G A, Bolton A, et al.. Early identification systems for emerging foodborne hazards[J]. Food Chem. Toxicol.,2009,47(5):915-926.
[39]中国农业大数据中心(中国农批价格与指数发布中心)[EB/OL]. http://ww w. sohu. com/a/219007753_687259,2018-01-26.
[40]安信证券.中国农业现代化路径[J].资本市场,2016(Z1):19-39,18.
[41]王文生,郭雷风.农业大数据及其应用展望[J].江苏农业科学,2015,43(9):1-5.Wang W S,Guo L F. Agricultural big data and its application prospects[J]. Jiangsu Agric. Sci.,2015,43(9):1-5.
[42]全球十大农业大数据经典案例之一中国[EB/OL].https://mp. weixin. qq. com/s/l xo Ft BY2TaXy8 mt V-Wj6YA,2018-07-10.
[43] Rene A E S,Simone P,Ignacio P D. Partial stochastic analysis with the Aglink-Cosimo model:A methodological overview[R]. Joint Research Centre(Seville site),2017.
[44]中国农业展望报告(2015-2024)[N].农民日报,2015-04-21,第006版.
[45]张浩然,李中良,邹腾飞,魏旭阳,等.农业大数据综述[J].计算机科学,2014,41(S2):387-392.Zhang H R,Li Z L,Zou T F,et al.. Overview of agriculture big data research[J]. Computer Sci.,2014,41(S2):387
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