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Management Optimization System for Precision Farming Japan model

日本精准农业模式管理优化系统

基本信息

批准号：
12460112
负责人：
SASAO Akira
金额：
$ 8.13万
依托单位：
Tokyo University of Agriculture and Technology
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2000
资助国家：
日本
起止时间：
2000 至 2001
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-12460112/
关键词：
precision farming soil map soil sensor plant growth model Lotka-Volterra model nonlinear pattern NIR spectroscopy weed management 土壌センサ

项目摘要

The project has aimed at developing a decision support system for farm work management based on the spatiotemporal variability of soil fertility and growing crops in the field, considering how to introduce precision farming in Japan. Results were as follows.1. Investigation was conducted during 1999 to 2000 on the competition of growth between white clover and weeds at 420 plots with different densities of white clover in two fields of different former crops, com and white clover. Results showed that cultivating the white clover inhibited the emergence and growth of weeds over all plots and that survivals were white clover for white clover plots and white clover for corn plots. A proposed Lotka Volterra model simulated well the dynamic behavior of growth competition between white clover and weeds ; and four behavior patterns could be classified.2. The real-time soil spectrophotometer developed was used for collecting the soil reflectance under the ground in a 0.5 ha paddy and a 0.3 ha upland fields. With about 900 and 500 data sets obtained form the paddy field and the upland field, respectively, at 1 m data scanning intervals, precise soil parameter maps were generated for moisture, soil organic matter, nitrate nitrogen, pH and EC.3. Analysis on the temporal variations in the soil parameter maps derived management maps for a decision support system on farm works, where three management units : stable high, stable low and unstable parts of soil parameters were clearly depicted.4. Crop growth maps of wheat and silage corn plants were produced by kriging technique using 432 treatments at 72 locations in a 0,4 ha field. About ten growth parameters were obtained including crop height and SPAD value. Airborne multi-spectral images of growing crops gave NDVI maps with high correlation with SPAD maps.5. The technical report was published.

该项目旨在开发一个基于土壤肥力时空变化和田间种植作物的农业工作管理决策支持系统，考虑如何在日本引入精准农业。结果如下：1999 ~ 2000年，在玉米和白三叶草两种不同作物的田间，选取420块不同密度白三叶草地，对白三叶草与杂草的生长竞争情况进行了调查。结果表明：栽培白三叶草对杂草的出苗和生长均有抑制作用，且白三叶草地和玉米地的成活率均为白三叶草。提出的Lotka Volterra模型较好地模拟了白三叶草与杂草生长竞争的动态行为；行为模式可分为四种。研制的实时土壤分光光度计用于0.5 ha水田和0.3 ha旱田土壤反射率的实时采集。利用水田和旱田分别获得约900和500个数据集，以1 m数据扫描间隔生成精确的土壤参数图，包括水分、土壤有机质、硝态氮、pH和ec3。3 .通过对土壤参数图时间变化的分析，导出了农业决策支持系统的管理图，其中清晰地描述了土壤参数的稳定高、稳定低和不稳定三个管理单元。小麦和青贮玉米作物生长图谱采用克里格技术，在0.4公顷的土地上，在72个地点使用432个处理。得到了作物高度和SPAD值等10个生长参数。作物生长的机载多光谱图像提供了与SPAD地图高度相关的NDVI地图。技术报告发表。