大数据在农业中的应用
在农业生产和科研中产生了大量的数据，这些数据的集成和未来的挖掘、使用，对于现代农业的发展将会发挥极其重要的作用。如果农民能随时掌握天气变化、市场需求和供给、农作物生长等数据，农民和农技专家在家就可观测到田地里的情况和相关数据，准确判断农作物是否要施肥、灌溉或施药，不仅能避免因自然因素造成的产量下降，而且可以避免因市场因素给农民带来的经济损失。当前，在精准农业、农产品流通体系、农业气象预测、粮食安全、病虫害预测与防治、土壤治理、动植物育种、农业结构调整、农产品价格、农副产品消费、小城镇建设等诸多农业领域，都可通过大数据技术进行预测和干预。4OBSERVATION 观察大数据在农业中的应用包括但不局限于：
（1）精准农业。精准农业是信息技术与农业生产全面结合的一种新型农业，其由六个子系统组成：全球定位系统、农田信息采集系统、农田遥感监测系统、农田地理信息系统、农业专家系统、智能化农机具系统，其核心是建立一个完善的农田地理信息系统[3]。大数据通过对不同系统获取的庞大信息量为基础，为精准农业的发展提供了大量的机会。可以用于土壤肥力管理、农田边界图管理、产量分布图管理、精确定位病虫害控制方法和施肥决策管理等。
（2）农产品流通体系。大数据可以提供经系统整合的相关气候、农产品价格走势、进城道路交通信息、终端消费
需求等相关数据，辅之以菜场超市摊位监测评估数据体系等，通过对这些专业数据的解读可以判断农产品需求、价格变动等情况。
（3）农业气象预测。通过建立天气识别模型，然后将这些模型与当前的气候条件进行比较，再运用预测性分析，进行天气预报。这种情况下，气象的预测时间更长、准确度更高。
（4）环境预测。进行环境预测需要了解获得区域作物、土壤、水、动物、气候和天气之间的复杂的相互作用。需要收集这些不同因素的数据进行分析，
大数据技术有助于整合提高不同地区的海量数据。
（5）提升人类健康。通过对人和周围生物群落之间的相互作用分析，包括生物群落的基因组、动物的营养、人类的营养状况数据，大数据可以更好地预测人类的健康和幸福感。并通过对农作物的基因组进行测序，从质上改变农作物的质量，培育出营养价值更高的农作物，提升人类健康水平。同时，随着大数据与农业的深度融合发展和基础设施、信息管理模式、软件技术的改进，以前依靠传统方法和技术解决不了的诸多问题也会迎刃而解。
Application of large data in agriculture
A large amount of data is generated in agricultural production and research, the data integration and future mining, use, development formodern agriculture will play a very important role in the. If farmers can keep abreast of changes in the weather, the market supply and demand, the growth of crops and other data, farmers and agricultural experts at homecan be observed in the field and related data, accurately judge whether tofertilization, irrigation and crop spraying, can not only avoid the naturalfactors causing the decline in output, but also can avoid the market factorsto farmers bring economic losses. At present, in precision agriculture, the circulation system of agricultural products, agricultural weather forecasting,food security, disease and pest forecast and control, soil management,animal and plant breeding, agricultural structure adjustment, the price of agricultural products, agricultural and sideline products consumption, the construction of small towns and so on many agricultural fields, can passprediction and intervention data technology. Application of 4OBSERVATIONobservation data in agriculture including but not limited to:
Precision agriculture (1). Precision agriculture is a new agricultural information technology and agricultural production overall combination,which consists of six subsystems: the global positioning system, farmland information collection system, remote monitoring system of farmland,farmland geographic information system, agricultural expert system,intelligent agricultural system, its core is to establish a perfect Farmland Geographic Information System [3]. Large data through the huge amount ofinformation in different systems are obtained as the foundation, offers a great opportunity for the development of precision agriculture. Can be used for soil fertility management, field boundary map management, yield distribution map management, precise positioning of pest control methods and fertilization decision-making management.
(2) the circulation system of agricultural products. Big data can be provided by the relevant climate, system integration of agricultural product price trend, the city road traffic information, the terminal consumption
Relevant data demand, supplemented by market supermarket boothmonitoring and assessment data system, through the interpretation of theseprofessional data can determine the demand for agricultural products, price changes etc..
(3) the agro meteorological forecasting. Through the establishment of the weather identification model, these models were then compared with the current climate conditions, and then use the predictive analysis, forecasting the weather. In this case, the prediction time is longer, the more accurateweather.
(4) environment prediction. Environmental prediction requires an understanding of regional crop, soil, obtained between animal, water,climate and weather complicated interaction. The need for collecting and analyzing the data of these different factors,
Big data technology helps to improve the massive data integration ofdifferent regions.
(5) to enhance human health. Through the analysis of the interaction between human and the surrounding communities of organisms, including biological community genome, animal nutrition, human nutrition status data,large data can better predict human health and well-being. And sequencedthe crop genome, from the quality of quality change crops, cultivate a higher nutritional value of crops, improve the level of human health. At the same time, along with the improvement of fusion development andinfrastructure, information management model, software technology of largedata and the depth of the problems of agriculture, relied on traditionalmethods and techniques to solve the deal will be smoothly done or easily solved.
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