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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 葉仲基(Chung-Kee Yeh) | |
dc.contributor.author | Tai-Jung Wu | en |
dc.contributor.author | 吳岱蓉 | zh_TW |
dc.date.accessioned | 2021-07-11T14:39:42Z | - |
dc.date.available | 2022-02-21 | |
dc.date.copyright | 2017-02-21 | |
dc.date.issued | 2016 | |
dc.date.submitted | 2017-02-06 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/78014 | - |
dc.description.abstract | 蔬菜是人類飲食當中重要的項目之一,但蔬菜常因栽種方式不當或天氣因素影響而殘留過量可轉化為致癌物的硝酸鹽。兆赫波(Terahertz wave)為一20世紀80年代中期才興起的電磁波研究領域,具有許多獨特且極具發展潛力的性質。本研究目的即為測試兆赫波是否可作為檢測蔬菜中硝酸鹽含量的有效方法,若兆赫波能檢測出硝酸鹽,則進一步明確探討相關的檢測指標性質。
本研究分別使用京都大學提供傅立葉轉換紅外光譜儀之FARIS-1與浙江大學提供之時域型兆赫波光譜儀TAS7500SP對樣本進行檢測,兩者之間的差異是可檢測的頻率範圍不同。 使用傅立葉轉換紅外光譜儀FARIS-1進行的檢測中,以衰減式全反射(ATR)方式檢測NaNO3、KNO3、NH4NO3與Ba(NO3)2四種硝酸鹽粉末、萵苣菜粉、青江菜葉與硝酸鈉溶液,以透射方式檢測硝酸鹽與萵苣菜粉製成的pellets(錠片)與青江菜葉,並觀察分析各檢測結果。檢測結果顯示,本研究檢測的硝酸鹽在兆赫波範圍內具有吸收特徵,但萵苣菜粉沒有吸收特徵,且當不同物質混合時,混合物的兆赫波吸收譜並非成分物質各自吸收譜的疊加。 在使用時域型兆赫波光譜儀TAS7500SP進行檢測時,以衰減式全反射方式檢測45個不同硝酸鹽濃度的青江菜葉片,以透射方式檢測相同的青江菜葉片與3組不同硝酸鹽濃度的萵苣菜粉製成的共93個pellets,並將檢測結果通過不同的濃度分組方式與4種不同數據前處理方法建立176組SIMCA分類模型,通過比較其分類準確度來辦別以兆赫波檢測蔬菜中硝酸鹽含量的最佳指標與參數。在以SIMCA模型分析測得的數據並進行比較後,發現在將樣本分組時,組別之間濃度差異較大的話可以更精確地分類。 比較ATR測葉片、透射測葉片與透射測pellets三種檢測組合的結果,發現最佳的數據前處理方式為使用Autoscale+Savitzky–Golay平滑化或僅使用Autoscale。上述三種組合中,以透射測pellets的分類效果最佳,以測得的樣本相位移(Phase Shift)或折射率(Refractive Index)性質作為指標,可以建立校正正確率與驗證正確率均為100%的模型,但缺點是製作pellets為破壞性檢測。透射測葉片結果稍差,但以測得的樣本對數透射度(Transmittance(dB))性質作為指標時,也可建立校正正確率為100%與驗證正確率為80%的模型,且其優勢是其為非破壞性檢測。ATR測葉片在三種方式中的分類效果最差,但以相位移(Phase Shift)作為指標時,仍可建立校正正確率為100%與驗證正確率為60%的模型,且也屬於非破壞性檢測。雖然以非破壞性方式檢測葉片的結果較破壞性檢測稍差,但由於其仍有一定程度的分類正確率,故顯示兆赫波技術具有以非破壞性方式檢測葉菜中硝酸鹽含量的潛力。 本研究結果發現,兆赫波具有檢測蔬菜中硝酸鹽的潛力,並且以樣本相位移(Phase Shift)與葉菜中硝酸鹽含量最為相關:這顯示兆赫波極可能成為一個能有效地檢測蔬菜中硝酸鹽含量的技術。然而,由於目前兆赫波仍有許多性質未被解明,故未來仍必須對兆赫波之形成原因及基本性質進行更多研究,才能將兆赫波技術進一步實用化。 | zh_TW |
dc.description.abstract | Vegetables are important foods. High amount of nitrates in human body would cause health problems; and one of the sources of the nitrates in human body is from eating vegetables. Terahertz wave is a new research aspect of spectrum field. Terahertz has many unique and potential characteristics, but it had not been intensively studied until mid-1980s. The purpose of this research is to find out whether terahertz wave could be used as an effective method to detect the nitrate in vegetables. If it proves that terahertz wave can show the features of nitrates, the next step is to figure out which property of the samples could be the best property for detection.
In this research, the Fourier transform infrared spectrometer (FTIR) FARIS-1 and terahertz time-domain spectrometer (THz-TDS) TAS7500SP were provided by Kyoto University and Zhejiang University, separately. The difference between these two devices is different detecting frequency range. Regarding the experiments using the FTIR FARIS-1 device, 4 kinds of nitrate powder (NaNO3、KNO3、NH4NO3 and Ba(NO3)2), Romaine lettuce powder, Bok Choy leaves and NaNO3 solution were measured in the attenuated total reflectance (ATR) mode; while the pellets made by nitrate powder and Romaine lettuce powder and Bok Choy leaves were measured in the transmission mode. The results showed that the nitrate samples have absorption features in the terahertz frequency range, while the Romaine lettuce powder has no feature in the range. Furthermore, it was found when using terahertz wave to measure the mixture of two materials, the result spectrum is not the addition of the two individual spectra of the materials. As of the experiments using the THz-TDS TAS7500SP device, 45 Bok Choy leaf samples with different nitrate contents were measured in both ATR and transmission modes. In addition, 93 pellets were measured in transmission mode, which were made from 3 groups of Romaine lettuce powder with different nitrate contents. The detecting results were combined with 2 grouping methods and 4 data preprocessing methods to build 176 SIMCA classification analyses. The best property of using terahertz wave to discriminate vegetables with different nitrate contents can be found by comparing the correction rate of classification in each analysis. Comparing the results of the SIMCA analyses, it was found the grouping method of keeping a nitrate content gap between the groups can lead to a better precise classification. Comparing the SIMCA results of using ATR to measure leaves, using transmission to measure leaves and using transmission to measure pellets, the best data preprocessing method was found to be using autoscale and Savitzky–Golay smoothing at the same time or using autoscale alone. Using transmission to measure pellets is the best pattern for using terahertz wave to separate vegetables samples with different nitrate contents. By choosing phase shift or refractive index as the target property, the transmission and pellets combination pattern can lead to an almost perfect SIMCA model, whose calibration correct rate and validation correct rate are both 100%. The only disadvantage of this pattern is making pellets must destruct the origin sample. The transmission and leaves combination pattern can build a model whose calibration correct rate is 100% and validation correct rate is 80% when choosing Transmittance (dB) as target property, while the ATR and leaves combination pattern can build a model whose calibration correct rate is 100% and validation correct rate is 60% when choosing phase shift as target property. It shows that terahertz wave still has the potential to be a non-destructive detection method to detect the nitrate content in leafy vegetables although the non-destructive detection result was not as good as the destructive detection result in the pellet form. This research proved that terahertz certainly has the potential to detect the nitrate in vegetables. The most important finding is that phase shift has very good relationship with the nitrate content in leafy vegetables. However, many basic properties of terahertz wave still remain unclear nowadays. More research on terahertz wave is needed to advance the technology toward applications. | en |
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dc.description.tableofcontents | 誌 謝 i
摘 要 iii Abstract v 目 錄 viii 圖目錄 xii 表目錄 xviii 第一章 前 言 1 1-1 前言 1 1-2 研究目的 2 第二章 文獻探討 3 2-1 硝酸鹽 3 2-1-1 植物體內的硝酸鹽 3 2-1-2 硝酸鹽對人體的危害 6 2-1-3 硝酸鹽檢測技術 8 2-2 兆赫波(Terahertz)技術 9 2-2-1 兆赫波光譜 11 2-2-1-1 傅立葉轉換紅外光譜 11 2-2-1-2 兆赫波時域光譜 12 2-2-2 兆赫波技術的特性 14 2-2-3 兆赫波技術的應用 15 2-2-4 兆赫波技術的限制 18 2-3 數據分析方法 20 2-3-1 主成分分析法PCA 21 2-3-2 簇類獨立軟模式法SIMCA 22 第三章 材料與方法 24 3-1 材料準備 25 3-1-1 蘿蔓萵苣菜粉 25 3-1-2 硝酸鹽 30 3-2 比色法量測硝酸鹽濃度 32 3-2-1 原理 33 3-2-2 量測操作 34 3-2-2-1 實驗儀器 34 3-2-2-2 量測溶液製備 37 3-2-2-2-1 硝酸鹽標準液製備 37 3-2-2-2-2 菜粉萃取液製備 38 3-2-2-3 比色法量測操作 38 3-3 兆赫波光譜量測 42 3-3-1 傅立葉轉換紅外光譜儀檢測 42 3-3-1-1 實驗儀器 42 3-3-1-2 衰減式全反射(ATR)檢測 44 3-3-1-2-1 ATR原理 44 3-3-1-2-2 ATR固態樣品量測 46 3-3-1-2-3 ATR液態樣品量測 50 3-3-1-3 透射 51 3-3-1-3-1 透射原理 51 3-3-1-3-2 pellets(錠片)製作 52 3-3-1-3-3 透射量測 57 3-3-2 時域型兆赫波光譜儀(THz-TDS)檢測 61 3-3-2-1 材料準備 67 3-3-2-2 實驗儀器 68 3-3-2-3 兆赫波量測 69 3-3-2-3-1 ATR量測 70 3-3-2-3-2 透射量測 70 3-3-2-4 青江菜葉硝酸鹽量測 71 3-4 兆赫波數據分析 72 3-4-1 PLS 函式庫(PLS Toolbox) 72 3-4-1-1 前處理方法:自動調整(Autoscale) 73 3-4-1-2 前處理方法:Savitzky–Golay平滑化 74 第四章 結果與討論 76 4-1 蘿蔓萵苣之硝酸鹽濃度 76 4-1-1 不同硝酸鹽含量蘿蔓萵苣栽培結果 76 4-1-2 比色法量測混合菜粉之硝酸鹽濃度結果 78 4-2 傅立葉轉換紅外光譜儀檢測結果 79 4-2-1 ATR檢測結果 79 4-2-1-1 ATR固態樣品檢測結果 80 4-2-1-1-1 水氣對檢測結果的影響之討論 80 4-2-1-1-2 ATR校正與否對檢測結果的影響之討論 80 4-2-1-1-3 硝酸鹽粉末檢測結果與粉末濃度影響結果之討論 82 4-2-1-1-4 蘿蔓萵苣菜粉(T1)檢測結果 83 4-2-1-1-5 青江菜葉片(A)檢測結果 84 4-2-1-2 ATR液態樣品檢測結果 85 4-2-1-2-1 蒸餾水檢測結果 85 4-2-1-2-2 不同濃度NaNO3溶液檢測結果 85 4-2-2 透射檢測結果 86 4-2-2-1 四種硝酸鹽pellets檢測結果 87 4-2-2-2 不同pellet濃度的相同粉末製pellets檢測結果之討論 88 4-2-2-3 不同硝酸鹽濃度蘿蔓萵苣菜粉pellets檢測結果與討論 90 4-2-2-4 T1與不同量NaNO3混合粉末製pellets檢測結果與討論 92 4-2-2-5 青江菜葉(A)檢測結果 93 4-2-3 NaNO3的ATR與3% pellet透射結果之比較與討論 94 4-2-4 青江菜葉的透射與ATR檢測結果之討論 95 4-3 時域型兆赫波光譜儀檢測結果 96 4-3-1 ATR檢測結果 97 4-3-2 透射檢測結果 99 4-3-2-1 青江菜葉片 99 4-3-2-2 3%蘿蔓萵苣菜粉pellets 100 4-4 SIMCA分類結果 102 4-4-1 校正正確率比較之分析討論 105 4-4-2 校正正確率高的模型之正確分類能力比較與討論 110 第五章 結 論 115 5-1 研究結論 115 5-2 未來研究建議 120 參考文獻 124 | |
dc.language.iso | zh-TW | |
dc.title | 以兆赫波偵測葉菜中硝酸鹽之研究 | zh_TW |
dc.title | Preliminary Study on Using Terahertz to Detect Nitrates in Leafy Vegetables | en |
dc.type | Thesis | |
dc.date.schoolyear | 105-1 | |
dc.description.degree | 碩士 | |
dc.contributor.coadvisor | 陳世銘(Suming Chen) | |
dc.contributor.oralexamcommittee | 羅筱鳳(Hsiao-Feng Lo),盛中德(Chung-Teh Sheng),莊永坤(Yung-Kun Chuang) | |
dc.subject.keyword | 兆赫波,硝酸鹽,葉菜,衰減式全反射,相位移, | zh_TW |
dc.subject.keyword | Terahertz wave,Nitrates,Vegetables,Attenuated Total Reflectance (ATR),Phase Shift, | en |
dc.relation.page | 138 | |
dc.identifier.doi | 10.6342/NTU201700375 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2017-02-07 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 生物產業機電工程學研究所 | zh_TW |
顯示於系所單位: | 生物機電工程學系 |
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