【摘要】：煙草(Nicotiana tabacum L.)屬管狀花目,茄科一年生或有限多年生草本植物。煙草的分布范圍遍及北緯60度到南緯45度間的絕大部分國家和地區(qū)。中國是世界煙葉生產(chǎn)第一大國,常年種植煙100多萬公頃,煙葉年產(chǎn)量達到200多萬噸。在我國,煙草種植分布于絕大部分省份和地區(qū),同時煙草也是重要的經(jīng)濟作物,煙草行業(yè)的稅收是我國財政收入的重要組成部分。由于煙草對生態(tài)環(huán)境的適應(yīng)性較強,所以在世界多地廣泛種植,但作為葉用植物,其煙葉的長相、組織結(jié)構(gòu)、物質(zhì)轉(zhuǎn)化與積累狀況等因素直接影響質(zhì)量。從煙葉質(zhì)量角度看,煙草又對生態(tài)環(huán)境的變化十分敏感。生態(tài)環(huán)境的差異及栽培措施的不同,不僅影響煙株形態(tài)和農(nóng)藝性狀,還導(dǎo)致煙葉內(nèi)在化學(xué)成分的變化,進而影響煙葉品質(zhì)。長期以來,人們從生態(tài)環(huán)境、品種、栽培措施、調(diào)制等與煙葉質(zhì)量的關(guān)系方面開展了大量研究,并提出了生態(tài)環(huán)境、品種、栽培技術(shù)對煙葉質(zhì)量的貢獻率分別為56%、32%、10%左右的說法。生態(tài)環(huán)境是決定煙葉品質(zhì)最重要的因素,主要體現(xiàn)在生態(tài)環(huán)境影響煙葉香氣物質(zhì)含量和組成比例,進而主導(dǎo)烤煙香氣風(fēng)格,并使煙葉香氣和吃味彰顯典型的地域特征等方面。生態(tài)因素中,氣候因子對煙葉香型和感官質(zhì)量指標(biāo)的影響及貢獻率最大,人們圍繞氣候因子與煙葉香氣物質(zhì)的關(guān)系開展了系列研究,但大多局限在某一特定地區(qū)的單一氣候因子與烤煙香氣物質(zhì)之間關(guān)系研究。常見的氣候因子主要包括光照、濕度、降水量、溫度等。本論文以煙葉品質(zhì)(包括外觀質(zhì)量、物理特性、感官質(zhì)量、化學(xué)成分)為研究對象,通過系統(tǒng)分析煙葉生產(chǎn)過程中的大田生長環(huán)境(海拔、氣溫、濕度、降雨量和光照)和倉儲環(huán)境(溫度、濕度、微生物)兩個階段中環(huán)境因子對煙葉品質(zhì)的影響,建立非線性模型,并將此方法應(yīng)用于不同環(huán)境條件下煙葉的品質(zhì)預(yù)測研究。(1)煙葉品質(zhì)特性的分析研究。從化學(xué)成分和感官質(zhì)量兩個不同方面對不同環(huán)境條件下煙葉的風(fēng)格類型和品質(zhì)特征進行表征,并以感官評價風(fēng)格特征指數(shù)為導(dǎo)向,挑選代表性化學(xué)指標(biāo)體系：與品質(zhì)特征指數(shù)相關(guān)的代表性化學(xué)指標(biāo)為總糖、總氮、鉀、多酚總量、茄酮、巨豆三烯酮A、香葉基丙酮、苯乙醇、辛酸；與風(fēng)格特征指數(shù)相關(guān)的代表性化學(xué)指標(biāo)為總糖、總氮、鉀、多酚總量、巨豆三烯酮D、藏花醛、香葉基丙酮、苯乙醛、丙二酸、蘋果酸。(2)種植環(huán)境對煙葉品質(zhì)的影響研究。采用相關(guān)性分析、多重比較分析、偏最小二乘判別分析、回歸分析及神經(jīng)網(wǎng)絡(luò)分析等方法指標(biāo)篩選受環(huán)境因子影響的煙葉品質(zhì)指標(biāo)。受海拔因子影響較的指標(biāo)主要有清甜香、堅果香、清香型、中間香型、濃香型、風(fēng)格指數(shù)、檸檬酸、棕櫚酸、亞油酸、異戊酸、2-甲基-丁酸、揮發(fā)性酸總量、葉黃素、p-胡蘿卜素、蕓香苷、醇類和酸類共計17項指標(biāo)。通過回歸分析可知,上述17項指標(biāo)受低、中、高海拔的影響,交叉驗證正確率分別為：77.8%,83.0%和85.0%。受年平均氣溫影響的指標(biāo)主要有：濃度、清甜香、堅果香、焦甜香、木香、蜜甜香、清香型、煙堿、綠原酸和醇類共計12項指標(biāo),通過回歸分析可知,上述12項指標(biāo)受低、中、高氣溫的影響,交叉驗證正確率分別為：80.00%,81.25%和80.00%。受年平均濕度影響的指標(biāo)主要有：還原糖、總氮、鉀、檸檬酸、棕櫚酸、2-甲基-丁酸、葉黃素、β-胡蘿卜素、綠原酸、多酚總量和醇類共計12項指標(biāo),通過回歸分析可知,上述12項指標(biāo)受低、中、高濕度的影響,交叉驗證正確率分別為：83.3%,92.9%和91.7%。受年平均降雨影響的指標(biāo)主要有：木香、煙堿、總糖、鉀、蘋果酸、亞油酸、非揮發(fā)性酸總量、苯甲酸、辛酸、葉黃素、β-胡蘿卜素、莨菪亭、蕓香苷、多酚總量、醛類和雜環(huán)類共計16項指標(biāo),通過回歸分析可知,上述16項指標(biāo)受低、中、高降雨的影響,交叉驗證正確率分別為：83.8%,86.6%和83.3%。受年平均日照影響的指標(biāo)主要有：香氣量、濃度、雜氣、干凈度、濕潤、品質(zhì)指數(shù)、清甜香、干草香、堅果香、蜜甜香、中間香型、風(fēng)格指數(shù)、戊酸、己酸、苯甲酸、綠原酸和蕓香苷共計17項指標(biāo),通過回歸分析可知,上述17項指標(biāo)受低、中、高日照的影響,交叉驗證正確率分別為：100.0%,83.3%和83.3%。為進一步研究環(huán)境因子(海拔、年平均氣溫、年平均降雨、年平均濕度和年平均日照)共同對煙葉品質(zhì)指標(biāo)的影響,采用神經(jīng)網(wǎng)絡(luò)分析優(yōu)化受環(huán)境因子影響較的指標(biāo),通過BP網(wǎng)絡(luò)通過多次迭代分析,建立了清香型、濃香型和清甜香指標(biāo)的預(yù)測模型,該3項指標(biāo)訓(xùn)練集相關(guān)系數(shù)分別為：98.16%、96.89%、85.52%和79.29%,且測試集效果較好,可用于上述三個指標(biāo)的預(yù)測。通過本章系統(tǒng)研究環(huán)境因子對煙葉品質(zhì)指標(biāo)的影響,這為后續(xù)進一步研究環(huán)境因子對煙葉生理生化、生長發(fā)育的影響奠定了基礎(chǔ)。(3)煙葉倉儲環(huán)境中的霉菌及其對煙葉品質(zhì)的影響研究。首先進行霉菌微生物的分離、純化及致腐性測定,篩選出煙葉中的導(dǎo)致霉變的主要霉菌,并通過微生物的培養(yǎng)及形態(tài)學(xué)鑒定判斷霉菌種屬,本研究煙葉中的霉菌主要為曲霉屬和青霉屬。對霉變煙葉的化學(xué)成分進行分析。通過對煙葉營養(yǎng)成分的分析,表明霉變煙葉樣品中C源、N源和礦物質(zhì)類化學(xué)成分均有不同程度的變化。糖類、淀粉、纖維素、木質(zhì)素、有機酸、多酚等C源類物質(zhì)含量降低幅度較大,氯離子、硫酸根、硝酸根和磷酸根等陰離子元素含量基本沒有變化；通過霉變煙葉揮發(fā)性及半揮發(fā)性成分分析,表明霉變煙葉中新產(chǎn)生的化合物有丁醇、2-甲基-丁醇、戊醇、己醇、亞油酸乙酯、亞麻酸乙酯、硬脂酸乙酯。含量變化程度較大的化合物：棕櫚酸乙酯、棕櫚酸甲酯、3-甲基-丁醇、4-甲基苯酚、3-羥基-2-丁酮、5-甲基糠醛、吲哚、亞麻酸甲酯、苯乙醇、糠醛、苯甲醇和糠醇。應(yīng)用篩選出的這19種煙葉霉變的揮發(fā)性特征成分建立模型,正常樣品判別模型的預(yù)測準(zhǔn)確率達95.0%、霉變樣品的預(yù)測準(zhǔn)確率達94.4%。預(yù)測準(zhǔn)確率可滿足實際應(yīng)用,應(yīng)用本方法可實現(xiàn)煙葉霉變的有效判定。在系統(tǒng)分析煙葉霉變的化學(xué)成分變化及霉變程度的判定方法基礎(chǔ)上,應(yīng)用近紅外光譜技術(shù)進行煙葉霉變預(yù)測模型的建立與驗證和麥角甾醇定量預(yù)測模型的建立與驗證。應(yīng)用近紅外光譜儀在780 nm-2500 nm范圍內(nèi)對煙葉的近紅外光譜進行采集,獲得煙葉樣本的基礎(chǔ)光譜數(shù)據(jù)。建立GBA算法,對基礎(chǔ)光譜數(shù)據(jù)進行特征波長的篩選,并建立PLS-DA判別模型。判別模型具有較小的Wilks'λ0.216 (P0.001)和誤差率2.92%。將該模型應(yīng)用于煙葉樣品的識別,準(zhǔn)確率高達95.79%。尤其是,可以在煙葉霉變的I期得到滿意的識別,適用于煙葉霉變的預(yù)測及倉儲煙葉的實時監(jiān)控。在煙葉出現(xiàn)霉變或者有出現(xiàn)霉變趨勢的情況下,及時采取通風(fēng)、降溫、除濕、翻垛、打葉復(fù)烤降低含水率等措施,防止霉變的進一步擴散和蔓延,最大可能的降低損失。應(yīng)用近紅外光譜法對煙葉中的麥角甾醇含量進行預(yù)測,提供一種檢測速度快、操作簡單方便、預(yù)測結(jié)果準(zhǔn)確的快速測定的方法,對于煙葉霉變的預(yù)測具有實際意義。
[Abstract]:Nicotiana tabacum L., an annual or Limited perennial herb of the family Solanaceae. The distribution range of tobacco is in the vast majority of countries and regions between 60 degrees north latitude and 45 degrees south latitude. China is the world's largest tobacco production country, growing about 1000000 hectares of tobacco in a year and the annual yield of tobacco to about 2000000 tons. In China, tobacco Planting is distributed in most provinces and regions, and tobacco is also an important economic crop, and the tax revenue of the tobacco industry is an important part of our financial income. Because tobacco has a strong adaptability to the ecological environment, it is widely cultivated in the world, but as a Ye Yongzhi, the length, structure, material transformation and product of the tobacco leaves. From the point of view of the quality of tobacco, tobacco is very sensitive to the changes in the ecological environment. The differences in the ecological environment and the different cultivation measures not only affect the tobacco plant morphology and agronomic traits, but also change the chemical composition of the tobacco leaves, and then affect the quality of tobacco. For a long time, people have from the ecological environment, A lot of studies have been carried out on the relationship between varieties, cultivation measures and modulation and the quality of tobacco leaves. The contribution rate of ecological environment, variety and cultivation technology to tobacco quality is 56%, 32%, and 10% respectively. The ecological environment is the most important factor in determining the quality of tobacco leaves, which is mainly reflected in the effects of the ecological environment on the aroma content of tobacco leaves. In the ecological factors, the influence and contribution rate of climate factors on tobacco flavor and sensory quality indexes are the greatest. The relationship between a single climate factor in a particular area and the aroma substances of flue-cured tobacco. The common climatic factors mainly include light, humidity, precipitation, and temperature. In this paper, the quality of tobacco (including appearance quality, physical properties, sensory quality, chemical composition) was studied by systematic analysis of field growth in the process of tobacco production. The environment (altitude, temperature, humidity, rainfall and illumination) and storage environment (temperature, humidity, microorganism) in two stages of environmental factors on the quality of tobacco leaf quality, establish a nonlinear model, and apply this method to the quality prediction of tobacco under different environmental conditions. (1) analysis of the quality characteristics of tobacco leaves, from chemical composition and sensory quality The style and quality characteristics of tobacco leaves under different environmental conditions were characterized by two different parties, and the representative chemical index system was selected based on the sensory evaluation style index. The representative chemical indexes related to the quality characteristic index were total sugar, total nitrogen, potassium, total polyphenols, Solanone, soybean three ketone A, and fragrant leaf base C Ketone, benzol, and octanic acid; the representative chemical indexes related to the style characteristic index are total sugar, total nitrogen, potassium, polyphenols, three ketone D, Tibetan aldehyde, fragrant leaf acetone, phenylacetaldehyde, malonic acid, malic acid. (2) study on the effect of planting environment on tobacco quality. Correlation analysis, multiple comparison analysis, partial least squares discriminant analysis, and recovery The indexes of tobacco leaf quality influenced by environmental factors were selected by regression analysis and neural network analysis. The main indexes affected by altitude factors were sweet fragrance, nut aroma, fragrance type, middle flavor type, Luzhou flavor, style index, citric acid, palmitic acid, linoleic acid, isovaleric acid, 2- methyl butyric acid, total volatile acid, lutein, p- carrot. According to the regression analysis, the above 17 indexes were affected by low, middle and high altitude, and the accuracy of cross validation was 77.8%, 83% and 85.0%. were mainly influenced by annual mean temperature: concentration, sweet fragrance, hard incense, coke sweet, wood aroma, honey sweet, fragrance, nicotine, chlorogenic acid. A total of 12 indexes and alcohols, through regression analysis, the above 12 indexes were affected by low, middle and high temperature. The accuracy of cross validation was 80%, 81.25% and 80.00%. were mainly affected by annual average humidity: reducing sugar, total nitrogen, potassium, citric acid, brown acid, 2- methyl butyric acid, lutein, beta carotene, chlorogenic acid, polyphenols. Total and alcohols were 12 indicators. Through regression analysis, the above 12 indexes were affected by low, medium and high humidity. The accuracy of cross validation was 83.3%, 92.9% and 91.7%. were mainly affected by annual rainfall: wood, nicotine, total sugar, potassium, malic acid, linoleic acid, total non volatile acid, benzoic acid, octanoic acid, lutein, beta - carotene, scopolamine, rutin, rutin, polyphenols total, aldehydes and heterocyclic 16 indexes. Through regression analysis, the above 16 indexes are affected by low, middle and high rainfall. The accuracy of cross validation is 83.8%, 86.6% and 83.3%. are mainly affected by annual average sunshine: aroma, concentration, impurity, cleanliness, wetness, and quality. Quality index, sweet scent, hay fragrance, nut fragrance, honey sweet, middle flavor type, style index, valerate, hexanic acid, benzoic acid, chlorogenic acid and rutin are 17 indexes. Through regression analysis, the above 17 indexes are affected by low, medium and high sunshine, and the accuracy of cross validation are 100%, 83.3% and 83.3%. for further study of environmental factors (SEA). The effects of annual average temperature, annual average rainfall, annual average humidity and annual average sunshine on the quality index of tobacco leaf were combined, and neural network was used to optimize the index of the influence of environmental factors. Through multiple iterative analysis of BP network, the prediction model of scent, Luzhou flavor and sweet scent was established, and the 3 indexes were trained. The number of relations is 98.16%, 96.89%, 85.52% and 79.29% respectively, and the test set effect is good. It can be used for the prediction of the above three indexes. Through this chapter, the influence of environmental factors on the quality of tobacco leaves is studied, which lays a foundation for further research on the effects of environmental factors on the physiological and biochemical, growth and development of tobacco. (3) the storage environment of tobacco leaves Study on the mold and its effect on the quality of tobacco. First, the isolation, purification and rot induced determination of fungi were carried out, and the main moulds in the leaves were screened out, and the fungi were judged by the culture of microbes and the morphological identification. The mold in the tobacco leaves was mainly Aspergillus and Penicillium. The chemical composition of the tobacco leaf was analyzed. Through the analysis of the nutrient composition of the tobacco, it was shown that the C source, the N source and the chemical composition of the minerals in the moldy tobacco leaves varied in varying degrees. The contents of C sources such as carbohydrates, starch, cellulose, lignin, organic acids and polyphenols were greatly reduced, and chloride, sulfate, nitrate and phosphate were removed. The content of the subelements is basically unchanged. Through the analysis of the volatile and semi volatile components of mouldy tobacco, it is shown that the newly produced compounds in the mouldy tobacco are butanol, 2- methyl butanol, pentanol, hexanol, ethyl linolenic acid ethyl ester, and ethyl stearate. The content of the compounds with a large change in content: ethyl palmitate, palmitate methyl ester, 3- a Base butanol, 4- methyl phenol, 3- hydroxy -2- butanone, 5- methyl furfural, indole, linolenic acid methyl ester, benzyl alcohol, furfural, benzyl alcohol and furfuryl alcohol. The model was established to determine the volatile characteristics of the 19 kinds of tobacco leaves. The prediction accuracy of the normal sample model was 95%, and the prediction accuracy of the mouldy samples reached the accuracy of 94.4%. prediction. It can be applied to the practical application. This method can be used to realize the effective determination of the leaf mould. On the basis of the systematic analysis of the chemical composition and the degree of mildew, the near infrared spectroscopy is used to establish and verify the mould prediction model and the establishment and verification of the model of the quantitative prediction of ergosterol. The infrared spectrum of the tobacco leaves is collected in the range of 780 nm-2500 nm to obtain the basic spectral data of the tobacco leaf samples. The GBA algorithm is established to screen the characteristic wavelengths of the basic spectral data and establish the PLS-DA discriminant model. The discriminant model has a smaller Wilks'lambda 0.216 (P0.001) and an error rate 2.92%. to apply the model to the model. The accuracy of the tobacco leaf sample is up to 95.79%., especially, it can be recognized satisfactorily in the I period of the leaf mold. It is suitable for the prediction of the leaf mould and the real-time monitoring of the storage leaf. Measures to prevent further spread and spread of mildew, the maximum possible reduction of loss. Using near infrared spectroscopy to predict the content of ergosterol in tobacco leaves, providing a rapid detection method, simple and convenient operation, accurate prediction results, for the prediction of tobacco moldy is of practical significance.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：S572

【參考文獻】

相關(guān)期刊論文 前10條

1 鐘楚;張明達;胡雪瓊;朱勇;;溫度變化對煙草光合作用光響應(yīng)特征的影響[J];生態(tài)學(xué)雜志;2012年02期

2 王暉;邢小軍;許自成;;涼山煙區(qū)主要氣候因素與烤煙質(zhì)量特點分析[J];中國農(nóng)業(yè)氣象;2007年04期

3 楊興有;劉國順;;成熟期光強對烤煙理化特性和致香成分含量的影響[J];生態(tài)學(xué)報;2007年08期

4 杜文;譚新良;易建華;蘇慶德;;用煙葉化學(xué)成分進行煙葉質(zhì)量評價[J];中國煙草學(xué)報;2007年03期

5 黎妍妍;黃元炯;許自成;吳軍;李富欣;;河南煙區(qū)煙葉質(zhì)量可用性的綜合評價[J];安徽農(nóng)業(yè)科學(xué);2006年09期

6 周冀衡,王勇,邵巖,楊虹琦,李永平,朱列書;產(chǎn)煙國部分煙區(qū)烤煙質(zhì)體色素及主要揮發(fā)性香氣物質(zhì)含量的比較[J];湖南農(nóng)業(yè)大學(xué)學(xué)報(自然科學(xué)版);2005年02期

7 周冀衡,楊虹琦,林桂華,楊述元;不同烤煙產(chǎn)區(qū)煙葉中主要揮發(fā)性香氣物質(zhì)的研究[J];湖南農(nóng)業(yè)大學(xué)學(xué)報(自然科學(xué)版);2004年01期

8 胡國松,楊林波,魏巍,章新軍,熊斌,張光輝,陳丙輝,黃立新;海拔高度、品種和某些栽培措施對烤煙香吃味的影響[J];中國煙草科學(xué);2000年03期

9 李炎強,冼可法;同時蒸餾萃取法與水蒸氣蒸餾法分離分析煙草揮發(fā)性、半揮發(fā)性中性成分的比較[J];煙草科技;2000年02期

10 陳傳孟,陳繼樹,谷堂生,戴興武,鄧正平,陳煥章,龍甲林;南嶺山區(qū)不同海拔烤煙品質(zhì)研究[J];中國煙草科學(xué);1997年04期

相關(guān)博士學(xué)位論文 前4條

1 劉好寶;清甜香烤煙質(zhì)量特色成因及其關(guān)鍵栽培技術(shù)研究[D];中國農(nóng)業(yè)科學(xué)院;2012年

2 李強;曲靖烤煙品質(zhì)特征及主要生態(tài)因素對其影響的研究[D];湖南農(nóng)業(yè)大學(xué);2011年

3 李鵬飛;主要生態(tài)因素和烘烤對烤煙致香物質(zhì)含量的影響[D];湖南農(nóng)業(yè)大學(xué);2009年

4 胡建軍;煙葉質(zhì)量評價方法優(yōu)選與實證研究[D];湖南農(nóng)業(yè)大學(xué);2009年

相關(guān)碩士學(xué)位論文 前9條

1 趙妮娜;基于NIR/FTIR的煙草淀粉和總氮測定方法的研究[D];西北農(nóng)林科技大學(xué);2013年

2 白柯;不同海拔高度光譜及生態(tài)因子對煙葉品質(zhì)的影響[D];湖南農(nóng)業(yè)大學(xué);2012年

3 古戰(zhàn)朝;烤煙主產(chǎn)區(qū)生態(tài)因子與煙葉品質(zhì)的關(guān)系[D];河南農(nóng)業(yè)大學(xué);2012年

4 皇甫曉瓊;不同基因型烤煙對光溫環(huán)境的生理生化響應(yīng)研究[D];福建農(nóng)林大學(xué);2012年

5 甄才紅;恩施州不同海拔和品種烤煙香氣物質(zhì)變化規(guī)律的研究[D];河南農(nóng)業(yè)大學(xué);2010年

6 畢慶文;海拔高度對烤煙生長發(fā)育及品質(zhì)的影響[D];河南農(nóng)業(yè)大學(xué);2009年

7 周俊學(xué);洛陽煙區(qū)烤煙化學(xué)成分與生態(tài)因素的關(guān)系[D];河南農(nóng)業(yè)大學(xué);2009年

8 劉春奎;湖北恩施煙區(qū)氣候因素和烤煙質(zhì)量綜合評價[D];河南農(nóng)業(yè)大學(xué);2008年

9 楊興有;光照強度對烤煙生長發(fā)育和品質(zhì)的影響[D];河南農(nóng)業(yè)大學(xué);2006年

，

本文編號：2120340