請用此 Handle URI 來引用此文件: http://hdl.handle.net/11455/89990
標題: A Study on Nitrate Detection of Vegetables by Using Concave Grating Spectrometer
應用微型光譜儀檢測葉菜硝酸鹽含量之研究
作者: Tzong-Herng Wu
吳宗衡
關鍵字: 硝酸鹽檢測
光譜分析
小波轉換
Nitrate detection
Analysis by optical spectrum
Wavelet transform
引用: [1] 葉俐吟。2012。應用微型光譜儀建置蔬菜農藥殘留檢測分析之研究。碩士論文。台中:國立中興大學生物產業機電工程學研究所。 [2] 廖憶華。2007。以光學頻譜分析定性及定量廢水水質特性之研究。碩士論文。桃園:國立中央大學環境工程研究所。 [3] 王大凱、彭進業。2006。小波分析及其在信號處理中的應用。第一版。北京:電子工業出版社。 [4] 魏明果。2005。實用小波分析。第一版。北京:北京理工大學出版社。 [5] 張德豐。2011。MATLAB 小波分析。第二版。北京:機械工業出版社。 [6] 王明光、王敏昭。2003。實用儀器分析。第一版。台北:國立編譯館。 [7] 賴鴻裕、陳柏青、劉程煒。2012。吃得安心-蔬菜與硝酸鹽。科學發展第 479 期。第 66-69 頁。 [8] 康浩銓。2008。以 DSP 晶片實現最佳母小波之連續小波變換。碩士論文。雲林:國立雲林科技大學資訊工程所。 [9] 陳瑋芸、蔡沁玹、郭景豪、黃立宇、蔡佳芬、曾素香、闕麗卿、施養志。2012。利用離子層析法檢測蔬菜中硝酸鹽及亞硝酸鹽含量。食品藥物研究年報。 [10] WHO.1995. Evaluation of Certain Food Additives and Contaminants. Joint FAO/WHO Expert Committee on Food Additives, pp. 29-35 (WHO Technical Report Series No. 859). WHO, Geneva. [11] WHO.1996. Toxicological Evaluation of Certain Food Additives and Contaminants. Prepared by the Forty-Fourth Meeting of the Joint FAO/WHO Expert Committee on Food Additives (JECFA). International Programme on Chemical Safety (WHO Food Additives Series 35). WHO, Geneva. [12] European Community 1997. European Commission Regulation (EC) No. 194/97. Official Journal of the European Communities L 31/48. [13] European Community 2002. European Commission Regulation (EC) No. 563/2002. Official Journal of the European Communities L 86/5. [14] European Community 2001. European Commission Regulation (EC) No. 466/2001. Official Journal of the European Communities L 77/6. [15] M. Misiti, Y. Misiti, G. Oppenheim and J. M. Poggi, 1996, 'Wavelet Toolbox: For Use with MATlab,'pp.300-302. [16] B. Chen , X. G. Fu and D. l. Lu, 'Improvement of predicting precision of oil content in instant noodles by using wavelet transforms to treat near-infrared spectroscopy,' Journal of Food Engineering ,vol. 53 , pp.373–376, 2002. [17] L. H. Cherif, S. M. Debbal and F. Bereksi-Reguig, 'Choice of the wavelet analyzing in the phonocardiogram signal analysis using the discrete and the packet wavelet transform,' Expert Systems with Applications vol. 37, pp. 913–918, 2010. [18] X. Zhou, C. Zhou, and B. G. Stewart, 'Comparisons of Discrete Wavelet Transform, Wavelet Packet Transform and Stationary Wavelet Transform in Denoising PD Measurement Data,' Conference Record of the 2006 IEEE International Symposium on Electrical Insulation, pp237-240, 2006. [19] A. Grossman and J. Morlet, 'Decomposition of Hardy function into square integrable wavelets of constant shape,' SIAM J.MATH.Anal. vol.15, pp. 736–783, 1984. [20] S. Mallat, 'A theory for multiresolution signal decomposition: The wavelet representation,' IEEE Transaction on Pattern Analysis and Machine Intelligence vol. 11, No.11, pp. 674-693, 1989.
摘要: 人們所攝取的硝酸鹽大多來自於蔬菜 硝酸鹽經過相關機轉形成亞,硝酸鹽,而醫學證實亞硝酸鹽有害人體健康,因此近年來農產品中硝酸鹽殘留的問題日漸受到矚目。其中葉菜類為最被推薦與接受之新鮮食材,葉菜硝酸鹽含量檢測自然受到相關研究的最大關注。常見的檢測方法如高效能液相層析法、氣相層析法及離子層析法,皆能獲得準確的結果,但其缺點為器材昂貴、檢測耗時與前置作業繁瑣,不利於現場即時檢測。本研究則利用干涉型凹面光柵微型光譜儀對蔬菜進行即時檢測,探討不同濃度下硝酸鹽吸收光譜特徵之定性與定量分析 並以吸收光譜,信號進行小波轉換,擷取波長 210nm-350nm 分別對硝酸鹽氮溶液及加入 100ppm, 200ppm, 500ppm, 667ppm 以及 1000ppm 五種濃度藥品的樣品溶液做一階導數處理 取第六層細節訊號做為後續最佳母小波選擇,的分析基準。分析方法為選用 db、sym、coif 三種正交母小波對特徵波段進行分析並比較其均方誤差;結果顯示以 db1 及 sym4 有較低的均方誤差,表示對特徵波段有較佳的解釋能力;而選用吸收光譜中第二特徵峰進行硝酸鹽定量分析時,濃度與最大吸收度呈現高度正相關。相關結果皆顯示本研究所建置的實驗設備與方法 可有效對硝酸鹽進行即時初,步的定性及定量分析,將可做為未來相關微型光譜儀量測之技術基礎。
The content of nitrate in human body usually comes from the food of vegetables with the residue of nitrate. Since the nitrate in the human body may transfer into nitrite which is a carcinogenic substances approved recently, the detection of the content of nitrate is seriously concerned. As the most popular fresh food source, the leaf-vegetable is paid more attention on the detection of content of nitrate, then. There are many ways to detect the nitrate, such as the high performance liquid chromatography, gas chromatography and ion chromatography. Although these methods provide the most precise results, but the disadvantages such as time-consuming process, high equipment cost and complicated sample pretreatments restrict the real-time application. In this thesis the concave grating interference spectrometer was employed to the real-time detection of vegetables and the description of the characteristics of nitrate absorption spectrum with different concentrations was also discussed. The nitrate absorption spectrum and sample solutions with which 100ppm, 200ppm, 500ppm, 667ppm and 1000ppm five different concentrations of nitrate were added were transformed by wavelet transform. Then, the wavelengths from 210 to 350 nm of wavelet were chosen and manipulated by first order derivative to compare detail signal at the sixth levels as the best selecting of the basis mother wavelet. Three orthogonal mother wavelets including db、sym and coif were used to compare the mean square error at characteristic bands. Results showed that there were comparatively lower mean square errors at db1 and sym4, and have more excellent explanation for characteristic bands. In quantitative analysis, the second characteristic peak of absorption spectrum was selected to make mean square error comparison. There was significant positive correlation between concentrations and the maximum absorbance. This thesis contributes a good enough description to the identity and concentrations of nitrates in vegetable and also established basic detecting technique on nitrate preliminarily.
URI: http://hdl.handle.net/11455/89990
其他識別: U0005-2704201509060700
文章公開時間: 2018-05-11
顯示於類別:生物產業機電工程學系

文件中的檔案:
檔案 描述 大小格式 
nchu-103-7101040012-1.pdf2.19 MBAdobe PDF檢視/開啟


在 DSpace 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。