【摘要】：精準(zhǔn)農(nóng)業(yè)是現(xiàn)代農(nóng)業(yè)的主要技術(shù)特征之一。進(jìn)入規(guī)模產(chǎn)業(yè)化的新疆加工番茄種植業(yè),由于普遍采用傳統(tǒng)的規(guī)�；芾�,機(jī)械化作業(yè),肥效問(wèn)題成為考驗(yàn)規(guī)模效益的一個(gè)及其重要問(wèn)題,精準(zhǔn)農(nóng)業(yè)勢(shì)在必行。作為精準(zhǔn)農(nóng)業(yè)的一項(xiàng)核心技術(shù)—精準(zhǔn)施肥,可以有效提高加工番茄產(chǎn)業(yè)種植效益,降低施肥的盲目性,減少浪費(fèi),盡可能地維護(hù)土壤原有理化性質(zhì),有效降低肥料對(duì)土壤團(tuán)粒結(jié)構(gòu)的破壞。本文以實(shí)現(xiàn)精準(zhǔn)施肥為目標(biāo),通過(guò)對(duì)土壤、肥料、作物生長(zhǎng)特性進(jìn)行分析與評(píng)價(jià)、大量的相關(guān)樣本數(shù)據(jù)進(jìn)行綜合,運(yùn)用數(shù)學(xué)、智能控制算法、計(jì)算機(jī)技術(shù)等建立與肥效相關(guān)的數(shù)學(xué)模型,并基于決策理論及方法生成精準(zhǔn)施肥機(jī)制,形成決策支持系統(tǒng)。土壤肥力的高低是進(jìn)行精準(zhǔn)施肥的前提,針對(duì)土壤肥力問(wèn)題提出了基于加權(quán)模糊聚類分析算法的評(píng)價(jià)方法,建立了土壤肥力評(píng)價(jià)模型并根據(jù)肥力狀況提出了施肥建議。不同肥料對(duì)作物的生長(zhǎng)影響不一樣,為確定肥料的肥效,以鉀肥為例,通過(guò)利用灰色關(guān)聯(lián)分析法得出了鉀肥對(duì)番茄產(chǎn)量的影響以及品質(zhì)性狀的關(guān)聯(lián)度排序。在確定了土壤肥力和肥料肥效后,針對(duì)具體施肥模型,構(gòu)建了傳統(tǒng)的“3414”施肥模型并提出了基于BP神經(jīng)網(wǎng)絡(luò)的施肥模型,結(jié)果表明基于BP神經(jīng)網(wǎng)絡(luò)的施肥模型優(yōu)于傳統(tǒng)的“3414”施肥模型,為精準(zhǔn)施肥提供了有效指導(dǎo)。最后,對(duì)決策支持系統(tǒng)的體系結(jié)構(gòu)和各模塊功能進(jìn)行分析,初步設(shè)計(jì)出加工番茄產(chǎn)業(yè)精準(zhǔn)施肥決策支持系統(tǒng)。
[Abstract]:Precision agriculture is one of the main technical characteristics of modern agriculture. Because of the traditional large-scale management and mechanized operation, fertilizer efficiency has become an important problem to test the scale efficiency of the processing tomato planting industry in Xinjiang, and precision agriculture is imperative. As a core technology of precision agriculture, precision fertilization can effectively improve the benefit of tomato processing industry, reduce the blindness of fertilization, reduce waste, and maintain the original physical and chemical properties of soil as much as possible. It can effectively reduce the damage to soil aggregate structure caused by fertilizer. This paper aims to achieve precision fertilization, through the analysis and evaluation of soil, fertilizer, crop growth characteristics, a large number of related sample data synthesis, using mathematics, intelligent control algorithm, The mathematical model related to fertilizer efficiency is established by computer technology, and the decision support system is formed based on the decision theory and method. The level of soil fertility is the premise of precision fertilization. The evaluation method based on weighted fuzzy cluster analysis algorithm is put forward to solve the problem of soil fertility. The evaluation model of soil fertility is established and the fertilization suggestions are put forward according to the fertility status. The effects of different fertilizers on the growth of crops were different. In order to determine the fertilizer efficiency, the effect of potash fertilizer on tomato yield and the ranking of correlation degree of quality traits were obtained by using grey relational analysis method, taking potash fertilizer as an example. After determining the soil fertility and fertilizer efficiency, the traditional "3414" fertilization model was constructed according to the specific fertilization model, and the fertilization model based on BP neural network was put forward. The results show that the fertilization model based on BP neural network is superior to the traditional "3414" fertilization model, which provides effective guidance for precision fertilization. Finally, the system structure and the function of each module of decision support system are analyzed, and the precision fertilization decision support system of tomato processing industry is designed preliminarily.
【學(xué)位授予單位】：新疆大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：S641.2;S126

【參考文獻(xiàn)】

相關(guān)期刊論文 前4條

1 高丙朋;姜波;南新元;;基于LS-SVM的番茄產(chǎn)量在線預(yù)測(cè)[J];湖北農(nóng)業(yè)科學(xué);2012年05期

2 胡偉;張炎;王海燕;齊桂紅;楊洛成;;幾種鉀肥在加工番茄上的應(yīng)用效果研究[J];新疆農(nóng)業(yè)科學(xué);2007年04期

3 呂貞龍;王小兵;仲曉春;劉芳;許莉莉;莊恒揚(yáng);;基于地理信息系統(tǒng)的濱海鹽土土壤肥力評(píng)價(jià)[J];系統(tǒng)工程理論與實(shí)踐;2008年09期

4 葉回春;張世文;黃元仿;王勝濤;;北京延慶盆地農(nóng)田表層土壤肥力評(píng)價(jià)及其空間變異[J];中國(guó)農(nóng)業(yè)科學(xué);2013年15期

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本文編號(hào)：2339302