干旱区滴灌棉花综合管理专家系统设计与实现

发布时间：2018-04-09 09:24

本文选题：干旱区　切入点：滴灌棉花　出处：《石河子大学》2017年硕士论文

【摘要】：近年来,随着科技与经济的发展,信息技术得到广泛应用,其在农业领域的应用已掀起一次新的技术革命。作为农业信息技术的分支之一,以专家系统为代表的智能化农业信息技术的作用尤为突出。新疆,作为我国最大的植棉区,由于生产管理水平较低,棉花产量和品质潜力未得到发挥,建立干旱区滴灌棉花综合管理专家系统,对于解决当前棉花栽培管理中的水、肥、药利用效率低等问题,实现棉花生长过程的动态调控及栽培技术的咨询服务等方面,具有十分重要的意义。本文开展了 29个品种、3个氮素的试验,定期调查棉花生育期、株高、叶龄、蕾铃数等数据。通过数据分析,构建棉花株高模拟模型、叶龄模拟模型,并进行模型的验证,结合新疆地区棉花栽培管理特性,建立了干旱区滴灌棉花综合管理专家系统。主要研究结果如下:1.构建了棉花株高动态模拟模型利用归一化和聚类分析法探明了棉花品种间相对有效积温与相对株高的关系,建立了基于相对有效积温的棉花相对株高模拟模型y = a/(1 + exp(b-cx)~(1/d)。根据模拟结果,将所有品种类型分为三大类,第Ⅰ类(棉花三叶期(相对株高值小于0.14)至十一叶期(相对株高小于0.7),株高生长速率较慢)y = 0.997/(1 + exp(26.08-33.62x))~(1/8.66)(r=0.9976);第 Ⅱ类(棉花三叶期(相对株高值在0.14～0.18之间)至十一叶期(相对株高在0.7～0.8之间),株高生长速率较快):(r=0.9967);第Ⅲ类(棉花三叶期(相对株高值大于0.18)至十一叶期(相对株高大于0.8),株高生长速率最快):y = 1.02/(1 + exp(8.55—12.68x))~(1/3.25)(r=0.9973)。对模型验证表明,RMSE= 1.6998cm,模拟值与观测值误差小,能够较好的反映干旱区滴灌条件下棉花株高的动态变化。2.构建了棉花叶龄动态模拟模型通过引入叶片生理发育因子,利用归一化处理及聚类分析法初步探明棉花品种间相对有效积温与主茎叶龄的关系,以8叶龄为界,对叶龄发育进程进行分段、分类模拟,分别建立了基于有理函数的棉花1-8叶龄动态模型和基于二次多项式、有理函数的8-13叶龄模拟模型,决定系数分别为0.9719、0.9964、0.9743、0.9733。模型验证表明,不同类型品种叶龄模拟值与观测值RMSE=0.3505,R2为0.9977,模拟值与观测值误差小,有理函数和二次多项式可以有效地预测棉花1-8叶龄及8-13叶龄的动态变化,可通过观测棉花叶龄生长状况为棉花精准管理提供依据。3.干旱区滴灌棉花综合管理专家系统的建立依据干旱区棉花栽培管理的主要措施和领域内专家知识,结合本研究所建立的模型和前人研究成果,建立了干旱区滴灌棉花综合管理专家系统,包括数据库、知识库、模型库、推理机、知识获取和人机接口等六部分,该系统实现了数据管理及系统维护、专家咨询、种植方案设计、模型模拟预测、实时调控等五大功能。系统可以根据用户输入决策地点的气候环境、土壤等基础数据,综合运用推理、预测、解释等机制帮助用户设计适宜的栽培管理方案。
[Abstract]:In recent years, with the development of science and economy, information technology has been widely used, its application in the field of agriculture has become a new technology revolution. As a branch of agricultural information technology, the expert system as the representative of the intelligent agricultural information technology's role is particularly prominent. Xinjiang, as China's largest cotton area, due to lower the level of production management, quality and yield potential of cotton did not get to play, the establishment of cotton under drip irrigation in arid area comprehensive management expert system to solve the current cotton cultivation management in water, fertilizer, low efficiency of drug use, dynamic regulation and Cultivation Techniques of cotton growth process to achieve the consulting service, it is very of great significance. This paper carried out the experiment of 29 varieties, 3 nitrogen, cotton growth period, regular surveys of plant height, leaf number, boll number data. Through data analysis, construction of cotton plant height model The leaf age model, simulation model validation and model, combined with the characteristics of cotton cultivation in Xinjiang area, the establishment of cotton under drip irrigation in arid area integrated management expert system. The main results are as follows: 1. the construction of cotton high dynamic simulation model using normalization and clustering analysis method proved the relationship among cotton varieties relatively effective accumulated temperature and the relative strain, established a relatively effective temperature of cotton relative height simulation model based on a/ (y = 1 + exp (b-cx) ~ (1/d). According to the simulation results, all varieties are divided into three categories, the first category (cotton leaf stage (relative height of less than 0.14 to eleven leaves) period (relative height of less than 0.7), plant height growth rate slower) y = 0.997/ (1 + exp (26.08-33.62x)) ~ (1/8.66) (r=0.9976); group II (cotton leaf stage (relative height in 0.14 ~ 0.18) to eleven leaf stage (relative plant height in 0.7 ~ 0.8), The height of a faster growth rate): (r=0.9967); group III (cotton leaf stage (relative height values greater than 0.18) to eleven leaf stage (relative height greater than 0.8), the height of the fastest growth rate of 1.02/ (1): y = exp + (8.55 - 12.68x) ~ (1/3.25) (r=0.9973) the model shows that). RMSE=, 1.6998cm, simulated and observed values of the error is small, can better reflect the arid area under drip irrigation cotton high dynamic.2. was constructed by introducing the physiological and developmental factor of cotton leaf dynamics simulation model, using normalization and clustering analysis method proved relatively effective temperature and the main stem when the relationship between cotton varieties, with 8 leaf age for the sector, the process of leaf development and segmentation, classification of simulation were established based on the rational function of cotton leaf 1-8 dynamic model and based on the two order polynomial, rational function of the 8-13 leaf age model, the determination coefficients were 0.9 The 719,0.9964,0.9743,0.9733. model shows that the simulation value of RMSE=0.3505 and age in different types of observations, R2 is 0.9977, the simulated and observed values of small error and dynamic changes of rational function and two polynomial can effectively predict the cotton leaf age and leaf age 1-8 8-13, can provide the basis for the growth of drip irrigation in arid area.3. cotton comprehensive management expert system establishment on the basis of arid area of cotton cultivation management measures and experts in the field of knowledge management through observation precision cotton cotton leaf age, combined with the model established by this research and previous research results, the establishment of cotton under drip irrigation in arid area comprehensive management expert system, including database, model base, knowledge base, inference engine, knowledge acquisition and man-machine interface the six part, the system realizes the data management and system maintenance, expert consultation, planting design, simulation and prediction model, real time control etc. Five functions. The system can help users design suitable cultivation management schemes based on basic data such as climate, environment and soil based on user input.

【学位授予单位】：石河子大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP182;S562

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