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Smart Agriculture ›› 2020, Vol. 2 ›› Issue (2): 82-93.doi: 10.12133/j.smartag.2020.2.2.202003-SA012

• 专题--农业传感器与物联网 • 上一篇    下一篇

水肥浓度智能感知与精准配比系统研制与试验

金洲1,4, 张俊卿1,2,4, 郭红燕1,4, 胡宜敏1,4, 陈翔宇1,4(), 黄河1,4(), 王红艳3   

  1. 1.中国科学院 合肥物质科学研究院智能机械研究所,安徽 合肥 230031
    2.中国科学技术大学,安徽 合肥 230026
    3.宁夏农业物联网工程技术研究中心,宁夏 银川 750000
    4.安徽省智慧农业工程实验室,安徽 合肥 230031
  • 收稿日期:2020-03-31 修回日期:2020-05-20 出版日期:2020-06-30
  • 基金资助:
    宁夏智慧农业产业技术协同创新中心建设任务(2017DC53);宁夏智慧农业关键技术研究与集成示范项目(2017BY067);安徽省自然科学基金青年项目(1908085QE202);合肥研究院院长基金青年“火花”项目(YZJJ2019QN14)
  • 作者简介:金 洲(1985-),男,博士,助理研究员,研究方向为农业信息化与数据挖掘。E-mail:jinzhou@iim.ac.cn。
  • 通信作者:

Development and Testing of Intelligent Sensing and Precision Proportioning System of Water and Fertilizer Concentration

JIN Zhou1,4, ZHANG Junqing1,2,4, GUO Hongyan1,4, HU Yimin1,4, CHEN Xiangyu1,4(), HUANG He1,4(), WANG Hongyan3   

  1. 1.Institute of Intelligent Machines, Hefei Institute of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
    2.University of Science and Technology of China, Hefei 230026, China
    3.Ningxia Agricultural IoT Engineering and Technology Research Center, Yinchuan 750000, China
    4.Intelligent Agriculture Engineering Laboratory of Anhui Province, Hefei 230031, China
  • Received:2020-03-31 Revised:2020-05-20 Online:2020-06-30

摘要:

为解决农场当地当时的复合肥料精准化配料问题,本研究将水肥一体化智能灌溉施肥系统作为研究对象,构建了水肥浓度智能感知与精准配比系统。首先提出现场在线水肥溶液智能感知模型的快速建立方法,利用数据分析算法从传感器实时监测的一系列浓度梯度的肥料溶液中挖掘出模型。其次基于上述模型设计水肥浓度智能感知与精准配比系统的框架结构,阐述系统工作原理;并通过三种水体模拟在线配肥验证了该系统原位指导水肥浓度配比的有效性,同时评价了水体电导率对水肥配比浓度的干扰。试验结果表明,正则化条件下二阶的多项式拟合曲线是表达溶液电导率与水肥浓度的变化关系最优的模型,相关系数R2均大于0.999,由此模型可得出用户关心的复合肥各指标浓度。三种水体模拟在线配肥结果表明,水体会干扰电导率导致无法准确反演水肥配比的浓度,相对偏差值超过了0.1。因此,本研究提出的在线水肥智能感知与精准配比系统实现了消除当地水体电导率对水肥配比准确性的干扰,通过模型计算实现复合肥精准化配比,并得出各指标浓度。该系统结构简单,配比精准,易与现有水肥一体机或者人工配肥系统结合使用,可广泛应用于设施农业栽培、果园栽培和大田经济作物栽培等环境下的精准智能施肥。

关键词: 水肥一体化, 电导率, 感知, 精准配比, 系统建模, 多项式拟合

Abstract:

Water and fertilizer integration technology can effectively improve nutrient utilization efficiency. However, the existing water and fertilizer machines have some shortcomings, such as huge cost, single fertilizer injection, need for cleaning water and so on, which hinder the development of water and fertilizer integration technology. Aiming at the problems of precise and low-cost compounding of compound fertilizer at the local farm, the water and fertilizer integrated intelligent irrigation and fertilization system were taken as the research object. In this research, new concept of an intelligent sensing system was proposed, and accurate proportioning system of water and fertilizer concentration was constructed and implemented. Firstly, a fast on-line method of intelligent sensing model of water and fertilizer was established based on a series of concentration gradient compound fertilizer solutions. The conductivity values of these formulated solutions were tested by contactless conductivity detection electrodes. Subsequently, the data analysis algorithms were discussed and compared to fit regression model. Based on the intelligent sensing model of water and fertilizer , the framework structure of in-situ intelligent sensing and accurate proportioning system of water and fertilizer concentration was designed, and the working principle of the system was also explained. The system proposed includs a first-level water and fertilizer concentration intelligent perception model building subsystem and a second-level water and fertilizer accurate proportioning subsystem. The first-level subsystem was designed as a portable device, which mainly included a precise pump for quantitative dosing, a large-range online conductivity sensor, a plastic bucket and supporting control and model building software. The second-level subsystem was designed as a dynamic and precise fertilizer distribution device. The effectiveness of the system was verified by three types of water intelligent fertilizer application so as to guide the in-situ water and fertilizer concentration ratio. The testing results showed that the second-order polynomial fitting curve under regularization conditions was the best model to express the relationship between the conductivity and the concentration of water and fertilizer, and the correlation coefficients R2 was higher than 0.999. Combined with the proportion of each index of compound fertilizer, the concentration of each index of compound fertilizer that the user cares about can be obtained according to this model. The results of three types of water intelligent fertilizer application showed that the conductivity of natural water had an effect on the water and fertilizer system, and the relative deviation was more than 0.1. The online water and fertilizer perception and ratio system proposed in this research realized the elimination of the interference of the local water conductivity on the accuracy of the ratio of water and fertilizer, and the accurate calculation of compound fertilizer was achieved through model calculation. This system has a simple structure and accurate ratio, low cost, and can be easily combined with the existing water and fertilizer integrated machine or artificial fertilizer system. The system could be widely used in facility agriculture, orchard cultivation and field cash crop cultivation, et al.

Key words: water and fertilizer integration, conductivity, intelligent sensing, precision proportioning, system modeling, polynomial curve fitting

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