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Smart Agriculture ›› 2019, Vol. 1 ›› Issue (4): 62-71.doi: 10.12133/j.smartag.2019.1.4.201910-SA001

• 信息处理与决策 • 上一篇    下一篇

信息农机农艺技术融合的小麦智慧生产模式研究

马新明1,2, 马兆务1, 许鑫1,2, 席磊1, 熊淑萍2, 李海洋1   

  1. 1. 河南农业大学信息与管理科学学院,河南郑州 450046
    2. 河南农业大学农学院,河南郑州 450046
  • 收稿日期:2019-10-20 修回日期:2019-11-11 出版日期:2019-10-30
  • 基金资助:
    河南省科技创新杰出人才基金(184200510008);河南省现代农业产业技术体系(S2010-01-G04);十三五国家重点研发计划(2016YFD0300609)
  • 通信作者:

Developmental model of wheat smart production based on the integration of information technology, agricultural machinery and agronomy

Ma Xinming1,2, Ma Zhaowu1, Xu Xin1,2, Xi Lei1, Xiong Shuping2, Li Haiyang1   

  1. 1. College of Information and Management Science, Henan Agricultural University, Zhengzhou 450046, China
    2. Agricultural College of Henan Agricultural University, Zhengzhou 450046, China
  • Received:2019-10-20 Revised:2019-11-11 Online:2019-10-30

摘要:

为研究智慧农业发展模式与实现途径,本研究设计了小麦产前、产中和产后各生产阶段信息技术与农机农艺融合的基本框架,即产前利用精准导航和激光平地技术实现对土地精准规范化作业,利用空间插值技术和变量施肥技术实现精准化播种与施肥;产中利用物联网和图像处理技术开展营养诊断服务;产后运用传感器技术开展产量实时预测服务。完成并实现了普通农机装备的智能化改造和与农业生产相适应的播种收获装备的研发;研究了具有高效利用光热资源、提高产量和绿色发展的小麦生产优化种植模式;研发了与小麦产前品种播期播量选择和施肥推荐、产中苗情营养诊断、产后产量实时测报等相关系统,并在河南省进行了试验。试验结果表明,采用信息技术与农机农艺融合方案可使小麦增产18.4%,增加产投比16.7%和8.1%,表明信息技术与农机农艺融合的小麦智慧化生产模式是有效的、可行的。

关键词: 信息农机农艺融合, 小麦, 智慧生产, 发展模式, 农业信息化

Abstract:

In order to study the development mode and realization way of smart agriculture, the technical route of agricultural information fusion of agricultural machinery in different production stages before, during and after wheat production was designed. Pre-production: use Beidou precision navigation technology and motion planning optimization method to realize the full area coverage path planning of the field operation of the automatic navigation tractor, combine the laser leveling equipment to realize the accurate and standardized land leveling and laser leveling, and realize the accurate and standardized operation of the land. On this basis, the spatial interpolation technology was used to make the variable fertilization prescription map and combining variable rate fertilizer machine and realized variable rate precise application of fertilizer and precise seeding. At the same time, combining with the optimal design of planting scheme, based on the prenatal database and knowledge base, it optimizes the decision-making of variety configuration and sowing time and seeding amount were optimized, and the software intelligent decision-making technology was used to recommend the varieties and sowing time and seeding amount suitable for planting at the decision-making point, and constructs the wheat and maize prenatal information service recommendation system based on WebGIS was constructed. In production: based on the image technology of automatic segmentation and color feature extraction of wheat image in the field environment, a remote monitoring model of wheat nutritional status with the function of wheat population image segmentation and nutritional estimation was established to realize the non-destructive monitoring of wheat nutritional status in the field environment. After production, the integrated measurement sensor, speed sensor, header height sensor and GPS were adopted, and controller area network bus was adopted with wireless communication technology, a real-time wheat yield measurement system was developed, which was installed on a large-scale combine harvester to carry out the real-time prediction service of wheat yield, so as to realize the synchronous process of wheat harvest and yield measurement, with the error less than 5%. The intelligent transformation of common agricultural machinery equipment and the research and development of sowing and harvesting equipment adapted to agricultural production were completed and realized, and the small scale with high-efficiency utilization of light and heat resources, increase of output and green development were studied. The model of wheat planting production was optimized .A real time measurement and prediction system for postpartum yield was developed, which included the selection of sowing date, fertilization recommendation, seedling growth and nutrition diagnosis. The experimental results show that the adoption of agricultural information fusion technology can increase wheat yield by 18.4%, input-output ratio by 16.6% and 7.9%, which shows that the intelligent agriculture of Henan province is effective and feasible.

Key words: information technology agricultural machinery and agronomy integration, wheat, smart production, development model, agricultural informatization

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