本文選題：干旱區(qū)　切入點(diǎn)：滴灌棉花　出處：《石河子大學(xué)》2017年碩士論文

【摘要】：近年來(lái),隨著科技與經(jīng)濟(jì)的發(fā)展,信息技術(shù)得到廣泛應(yīng)用,其在農(nóng)業(yè)領(lǐng)域的應(yīng)用已掀起一次新的技術(shù)革命。作為農(nóng)業(yè)信息技術(shù)的分支之一,以專(zhuān)家系統(tǒng)為代表的智能化農(nóng)業(yè)信息技術(shù)的作用尤為突出。新疆,作為我國(guó)最大的植棉區(qū),由于生產(chǎn)管理水平較低,棉花產(chǎn)量和品質(zhì)潛力未得到發(fā)揮,建立干旱區(qū)滴灌棉花綜合管理專(zhuān)家系統(tǒng),對(duì)于解決當(dāng)前棉花栽培管理中的水、肥、藥利用效率低等問(wèn)題,實(shí)現(xiàn)棉花生長(zhǎng)過(guò)程的動(dòng)態(tài)調(diào)控及栽培技術(shù)的咨詢(xún)服務(wù)等方面,具有十分重要的意義。本文開(kāi)展了 29個(gè)品種、3個(gè)氮素的試驗(yàn),定期調(diào)查棉花生育期、株高、葉齡、蕾鈴數(shù)等數(shù)據(jù)。通過(guò)數(shù)據(jù)分析,構(gòu)建棉花株高模擬模型、葉齡模擬模型,并進(jìn)行模型的驗(yàn)證,結(jié)合新疆地區(qū)棉花栽培管理特性,建立了干旱區(qū)滴灌棉花綜合管理專(zhuān)家系統(tǒng)。主要研究結(jié)果如下:1.構(gòu)建了棉花株高動(dòng)態(tài)模擬模型利用歸一化和聚類(lèi)分析法探明了棉花品種間相對(duì)有效積溫與相對(duì)株高的關(guān)系,建立了基于相對(duì)有效積溫的棉花相對(duì)株高模擬模型y = a/(1 + exp(b-cx)~(1/d)。根據(jù)模擬結(jié)果,將所有品種類(lèi)型分為三大類(lèi),第Ⅰ類(lèi)(棉花三葉期(相對(duì)株高值小于0.14)至十一葉期(相對(duì)株高小于0.7),株高生長(zhǎng)速率較慢)y = 0.997/(1 + exp(26.08-33.62x))~(1/8.66)(r=0.9976);第 Ⅱ類(lèi)(棉花三葉期(相對(duì)株高值在0.14～0.18之間)至十一葉期(相對(duì)株高在0.7～0.8之間),株高生長(zhǎng)速率較快):(r=0.9967);第Ⅲ類(lèi)(棉花三葉期(相對(duì)株高值大于0.18)至十一葉期(相對(duì)株高大于0.8),株高生長(zhǎng)速率最快):y = 1.02/(1 + exp(8.55—12.68x))~(1/3.25)(r=0.9973)。對(duì)模型驗(yàn)證表明,RMSE= 1.6998cm,模擬值與觀測(cè)值誤差小,能夠較好的反映干旱區(qū)滴灌條件下棉花株高的動(dòng)態(tài)變化。2.構(gòu)建了棉花葉齡動(dòng)態(tài)模擬模型通過(guò)引入葉片生理發(fā)育因子,利用歸一化處理及聚類(lèi)分析法初步探明棉花品種間相對(duì)有效積溫與主莖葉齡的關(guān)系,以8葉齡為界,對(duì)葉齡發(fā)育進(jìn)程進(jìn)行分段、分類(lèi)模擬,分別建立了基于有理函數(shù)的棉花1-8葉齡動(dòng)態(tài)模型和基于二次多項(xiàng)式、有理函數(shù)的8-13葉齡模擬模型,決定系數(shù)分別為0.9719、0.9964、0.9743、0.9733。模型驗(yàn)證表明,不同類(lèi)型品種葉齡模擬值與觀測(cè)值RMSE=0.3505,R2為0.9977,模擬值與觀測(cè)值誤差小,有理函數(shù)和二次多項(xiàng)式可以有效地預(yù)測(cè)棉花1-8葉齡及8-13葉齡的動(dòng)態(tài)變化,可通過(guò)觀測(cè)棉花葉齡生長(zhǎng)狀況為棉花精準(zhǔn)管理提供依據(jù)。3.干旱區(qū)滴灌棉花綜合管理專(zhuān)家系統(tǒng)的建立依據(jù)干旱區(qū)棉花栽培管理的主要措施和領(lǐng)域內(nèi)專(zhuān)家知識(shí),結(jié)合本研究所建立的模型和前人研究成果,建立了干旱區(qū)滴灌棉花綜合管理專(zhuān)家系統(tǒng),包括數(shù)據(jù)庫(kù)、知識(shí)庫(kù)、模型庫(kù)、推理機(jī)、知識(shí)獲取和人機(jī)接口等六部分,該系統(tǒng)實(shí)現(xiàn)了數(shù)據(jù)管理及系統(tǒng)維護(hù)、專(zhuān)家咨詢(xún)、種植方案設(shè)計(jì)、模型模擬預(yù)測(cè)、實(shí)時(shí)調(diào)控等五大功能。系統(tǒng)可以根據(jù)用戶(hù)輸入決策地點(diǎn)的氣候環(huán)境、土壤等基礎(chǔ)數(shù)據(jù),綜合運(yùn)用推理、預(yù)測(cè)、解釋等機(jī)制幫助用戶(hù)設(shè)計(jì)適宜的栽培管理方案。
[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.

【學(xué)位授予單位】：石河子大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP182;S562

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