請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/47364完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳世銘 | |
| dc.contributor.author | Jin-Shi Huang | en |
| dc.contributor.author | 黃君席 | zh_TW |
| dc.date.accessioned | 2021-06-15T05:56:38Z | - |
| dc.date.available | 2016-09-21 | |
| dc.date.copyright | 2011-09-21 | |
| dc.date.issued | 2011 | |
| dc.date.submitted | 2011-08-19 | |
| dc.identifier.citation | 王文政、藍惠玲、葉蕙玲。2001。近紅外光譜於水產飼料鑑別之應用。近紅外光技術應用於農畜產品品質檢測訓練班及研討會論文集。P. 1-8。台北：財團法人農業機械化研究發展中心。
全秀華。2005。萵苣的營養成分。台北：財團法人台灣癌症基金會。網址：http://www.canceraway.org.tw/。上網日期：2010-09-23。 呂宏志。2005。溫室多功能監測系統之開發-苗床植株遙測與環境因子量測。碩士論文。台北：臺灣大學生物產業機電工程學研究所。 杜威霆。2009。光譜標準化模式應用於水果糖度檢測之研究。碩士論文。台北：國立台灣大學生物產業機電工程研究所。 李明達。2001。水份逆境下植物影像特徵分析之研究。碩士論文。台北：臺灣大學生物產業機電工程學研究所。 林育菁。2002。蓮霧及木瓜內部品質之近紅外光檢測。碩士論文。台北：國立臺灣大學生物產業機電工程學研究所。 邱鶴圍。1999。近紅外光應用於芒果內部品質分析之研究。碩士論文。台北：國立台灣大學農業機械工程學所。 區少梅、陳玉舜。1993。近紅外線分光技術鑑定茶品質之研究。中國農業化學會誌。31（2）：183 - 199。 張文宏。1998。水果品質檢測模式之研究。博士論文。台北：臺灣大學農業機械工程學系研究所。 張晉倫。2006。應用溫室內多功能監測系統於甘藍種苗生長性狀判別之研究。碩士論文。台北：臺灣大學生物產業機電工程學研究所。 張嘉麟、陳世銘。1999。近紅外光與核磁共振應用於乳粉脂肪含量之檢測。農業機械學刊。8(3):43-59。 章國威、郭寶錚。2008。水庫水質之遙測模式建立與應用研究成果報告 (精簡版)。行政院國家科學委員會專題研究計畫成果報告。計畫編號：NSC97-2410- H-156-009-。 陳世銘、張文宏、謝廣文。1998。果汁糖度檢測模式之研究。農業機械學刊7（3）：41 - 60。 陳世銘、黃政偉、吳德輝、楊智凱、黃竣吉、蔡養正、繆八龍。2002。稻株含氮量地面多光譜影像遙測系統之開發研究。水稻精準農業（耕）體系之研究」計畫成果研討會暨展示會大會手冊，93-99。台中縣：農業試驗所。 陳世銘、謝廣文、黃裕益、楊宜璋、陳加增、呂宏志、張晉倫、林慧美、陳毓良、陳俊吉。2007。溫室遠端監控及精準栽培自動化之研究。2007 農業資訊科技應用研討會論文集，64-75。台北：財團法人台灣農業資訊科技發展協會。 陳加增。2001。近紅外光應用於水果糖酸度線上檢測之研究。碩士論文。台北：國立台灣大學生物產業機電工程學研究所。 陳加增。2006。應用智慧型光譜資訊分析於蔬菜植株氮含量檢測之研究。博士論文。台北：國立臺灣大學生物產業機電工程學系。 陳加增、陳世銘、楊蕙綺、楊宜璋、蕭世傑。2006。蔬菜葉片氮含量之近紅外光反射光譜分析。農業機械學刊 15(4): 39-52。 楊宜璋。2001。近紅外光技術應用於柑桔類水果果汁糖酸度之測定。學士論文。台北：國立臺灣大學生物產業機電工程學系。 楊宜璋。2008。應用光學非破壞性檢測技術於生物材料分析。博士論文。台北：國立臺灣大學生物產業機電工程學系。 黃君席。2009。應用近紅外光於酒精汽油乙醇濃度測定之研究。學士論文。台北：國立臺灣大學生物產業機電工程學系。 黃君席、陳世銘、羅筱鳳、蔡兆胤、莊永坤、胡易平、王啟維、楊宜璋、陳毓良。2010。應用光譜影像檢測蔬菜硝酸鹽含量。2010年農機與生機科技論文發表會論文集：419-424。 黃政偉。2002。多光譜影像應用於水稻植株含氮量之遙測。碩士論文。台北：國立臺灣大學生物產業機電工程學研究所。 黃竣吉。2003。稻株含氮量多光譜影像遙測系統之研究。碩士論文。台北：國立臺灣大學生物產業機電工程學研究所。 黃竣吉、陳世銘、楊翕雯、陳加增。2004。近紅外光技術應用於穿山甲中藥成份之研究。農業機械學刊13（3）：36 - 52。 蔡志成。2004。以近紅外光檢測幾丁類物質去乙醯率之研究。碩士論文。台北：國立臺灣大學生物產業機電工程學研究所。 環境檢驗所。2000。水中硝酸鹽氮及亞硝酸鹽氮之鎘還原流動注入分析法 (NIEA W436.50C)。網址：http://www.niea.gov.tw/。上網日期：2010-09-23。 環境檢驗所。2004。水中硝酸鹽氮及亞硝酸鹽氮檢測方法－鎘還原法 (NIEA W452.50C)。網址：http://www.niea.gov.tw/。上網日期：2010-09-23。 環境檢驗所。2005。水中硝酸鹽檢測方法－馬錢子鹼比色法 (NIEA W417.51A)。網址：http://www.niea.gov.tw/。上網日期：2010-09-23。 環境檢驗所。2006。水中硝酸鹽氮檢測方法－分光光度計法 (NIEA W419.51A)。網址：http://www.niea.gov.tw/。上網日期：2010-09-23。 羅聖傑。2009。茶葉醱酵度之高光譜影像檢測。碩士論文。台北：國立臺灣大學生物產業機電工程學研究所。 譚增偉、黃維廷、江志峰。2009。合理化施肥之回顧與展望。農業試驗所技術服務 12 (80): 29-32。 Allied Vision Technologies. 2006a. Catalog: Dolphin F-145B/ F-145C. Available at: www.alliedvisiontec.com. Accessed 20 August 2010. Allied Vision Technologies. 2006b. Catalog: Guppy F-044B NIR/ F-044C NIR. Available at: www.alliedvisiontec.com. Accessed 20 August 2010. ATSDR. 2007. Case studies in environmental medicine: nitrate/nitrite toxicity. Atlanta: Agency for Toxic Substances and Disease Registry. Available at: www.atsdr.cdc.gov/. Accessed 20 August 2010. Balabin, R. M., R. Z. Safieva, and E. I. Lomakina. 2007. Comparison of linear and nonlinear calibration models based on near infrared (NIR) spectroscopy data for gasoline properties prediction. Chemometrics and intelligent laboratory systems. 88 (2007) 183-188. Belasque, J., Jr., M. C. G. Gasparoto, and L. G. Marcassa. 2007. Detection of mechanical and disease stresses in citrus plants by fluorescence spectroscopy. Applied Optics 47 (11):1922-1926. Blanco, M., J. Coello, H. Iturriaga, S. Maspoch, and C. de la Pezuela. 1997. Effect of date preprocessing methods in near-infrared diffuse reflectance spectroscopy for the determination of the active compound in a pharmaceutical preparation. Applied Spectroscopy 51 (2):240-24. Blanco, M., J. Coello, H. Iturriaga, S. Maspoch, and C. de la Pezuela. 1998. Near-infrared spectroscopy in the pharmaceutical industry. Analyst 123 (1998):135R– 150R. Blanco, M., A. Eustaquio, J. M. Gonzalez and D. Serrano. 1999. Identification and quantitation assays for intact tablets of two related pharmaceutical preparations by reflectance near-infrared spectroscopy：validation of the procedure. Journal of Pharmaceutical and Biomedical Analysis 22：139-148. Blanco, M., and I. Villarroya. 2002. NIR spectroscopy: a rapid-response analytical tool. Trends in Analytical Chemistry 21 (4):240-250. Bogrekci I., W. S. Lee, J. D. Jordan, J. C. Craig. 2005. Multispectral image analysis for phosphorus measurement in bahia grass. ASAE Paper No. 051067. St. Joseph, MI: ASAE. Bolster, K. L., M. E. Martin, and J. D. Aber. 1996. Determination of Carbon fraction and Nitrogen Concentration in Tree Foliage by Near Infrared: a Comparison of Statistical Methods. Can. J. For. Res. 26:590-600. Borah, S. and M. Bhuyan. 2005. A computer based system for matching colours during the monitoring of tea fermentation. IJFST. 40: 675-682 Borhan, M. S., S. Panigrahi, J. H. Lorenzen and H. Gu. 2004. Multispectral and color imaging techniques for nitrate and chlorophyll detection of potato leaves in a controlled environment. Transactions of the ASAE 47(2):599-608. Bravo, C., D. Moshou, R. Oberti, J. West, A. McCartney, L. Bodria, and H. Ramon. 2004. Foliar disease detection in the field using optical sensor fusion. Agricultural Engineering International: the CIGR Journal of Scientific Research and Development 6 (2004):1-14. Candolfi, R. De Maesschalck, D. Jouan-Rimbaud, P. A. Hailey, D. L. Massart. 1999. The influence of data pre-processing in the pattern recognition of excipients near-infrared spectra. Journal of Pharmaceutical and Biomedical Analysis 21：115-132. Cataldo, D. A., M. Maroon, L. E. Schrader, and V. L. Youngs. 1975. Rapid colorimetric determination of nitrate in plant tissue by nitration of salicylic acid. Communications in Soil Science and Plant Analysis 6 (1):71-80. Chang, W. H., S. Chen, and C. C. Tsai. 1998. Development of a universal algorithm for use of NIR in estimation of soluble solids in fruit juices. Transactions of the ASAE 41(6):1739-1745. Chen, S. 2008. The status of precision agriculture in Taiwan: from field to greenhouse. In “Proceedings of the 4th International Symposium on Machinery and Mechatronics for Agricultural and Bio-systems Engineering (ISMAB 2008)”, Invited Speech IS03. Taichung, Taiwan: National Chung Hsing University. Chen, S. 2010. Current status of plant factories in Taiwan and future development. In “Proceedings of 2010 Annual Meeting of Japanese Society of Agricultural, Biological and Environmental Engineers and Scientists (JSABEES)”, Invited Speech, P. 302-308. Kyoto, Japan: Kyoto University. Chen, S. and M. T. Li, 2001. Multispectral imaging of chlorophyll content for vegetable status monitoring. In “Fruit, Nut, and Vegetable Production Engineering, Proceedings of the 6th International Symposium held in Potsdam 2001”, P.603-608. Potsdam, Germany: Institute of Agricultural Engineering Bornim e.V. (ATB). Chen, S., M. T. Li, C. T. Chen, Y. C. Lin, C. W. Huang, T. H. Wu, and K. W. Hsieh. 2002. Remote sensing of crop growth characteristics in greenhouses. In “Proceedings of International Symposium on Design and Environmental Control of Tropical and Subtropical Greenhouses”, eds. S. Chen and T. T. Lin. Acta Horticulturae 578:295-301. Chen, S., C. W. Huang, C. C. Huang, C. K. Yang, T. H. Wu, Y. Z. Tsai, and P. L. Miao. 2003. Determination of nitrogen content in rice crop using multi-spectral imaging. ASAE Paper No. 03-1132, St. Joseph, MI, USA: ASAE. Chen, S. et al. 2004a. Growth status monitoring and quality evaluation for bio-production and products using spectral sensing techniques. In “Proceedings of the Second International Symposium on Machinery and Mechatronics for Agriculture and Bio-systems Engineering”, Keynote Speech, KN-9 ~ 23. Kobe, Japan: Kobe University. Chen, S, C. T. Chen, I. C. Yang, M. T. Li, C. W. Huang, C. C. Huang, K. W. Hsieh. 2006a. Precision greenhouse cultivation using multi-spectral imaging techniques. In “Proceedings of APO Multi-Country Study Mission on Precision Farming -- Resource Papers”, Taoyuan, Taiwan. Sponsored by Asian Productivity Organization and Council of Agriculture, Taiwan. Chen, S., H. C. Lu, K. W. Hsieh, Y. I. Huang, C. T. Chen, I. C. Yang, C. L. Chang, and G. H. Yeh. 2006b. Development of multi-functional remote sensing system for greenhouse production. In “Proceedings of SPIE -- Optics for Natural Resources, Agriculture, and Foods”, Vol. 6381, p 638103-1~8. Boston, MA, USA: The International Society for Optical Engineering. Chen, S., C. T. Chen, C. Y. Wang, I. C. Yang, and S. C. Hsiao. 2007a. Evaluation of nitrogen content in cabbage seedlings using hyper-spectral images. In “Proceedings of SPIE -- Optics for Natural Resources, Agriculture, and Foods II”, Vol. 6761, p 63810L-1~8. Boston, MA, USA: The International Society for Optical Engineering. Chen, S., W. T. Tu, I. C. Yang, C. T. Chen, C. L. Chang, J. C. Li, H. M. Lin, Y. L. Chen, and C. C. Chen. 2008a. Automation on multi-functional remote sensing system for greenhouse production. In “Proceedings of the 4th International Symposium on Machinery and Mechatronics for Agricultural and Bio-systems Engineering (ISMAB 2008)”, PA-21~25. Taichung, Taiwan: National Chung Hsing University. Chen, C. T., S. Chen, K. W. Hsieh, H. C. Yang, S. Hsiao, and I. C. Yang. 2004. Estimation of nitrogen content by spectral responses of cabbage seedlings using artificial neural network approach. ASAE Paper No. 04-1082, St. Joseph, MI, USA: ASAE. Chen, C. T., S. Chen, K. W. Hsieh, H. C. Yang, S. Hsiao, and I. C. Yang. 2007. Estimation of leaf nitrogen content using artificial neural network with cross-learning scheme and significant wavelengths. Transactions of the ASABE 50(1): 295-301. Chen, C. T., S. Chen, C. Y. Wang, I. C. Yang, S. C. Hsiao, and C. Y. Tsai. 2008b. Evaluation of nitrogen content in cabbage seedlings using hyper-spectral images. Sensing and Instrumentation for Food Quality and Safety 2(2): 97-102. Cogdill, R. P., C. R. Hurburgh, Jr. and G. R. Rippke. 2004. Single-kernel maize analysis by near-infrared hyperspectral imaging. Transactions of the ASAE 47(1):311-320. Cozzolino, D., and I. Murray. 2002. Effect of sample presentation and animal muscle species on the analysis of meat by near infrared reflectance spectroscopy. Journal of Near Infrared Spectroscopy 10 (2002): 37-44. Crawford, N. M. 1995. Nitrate: Nutrient and signal for plant growth. The Plant Cell 7 (1995): 859-868. Delwiche, S. R., and M. S. Kim. 2000. Hyperspectral Imaging for Detection of Scab in Wheat. Biological Quality and Precision Agriculture II 4203 (2000):13-20. De Marchi, M., P. Berzaghi, A. Boukha, M. Mirisola, and L. Gallo. 2007. Use of near infrared spectroscopy for assessment of beef quality traits. Italian Journal of Animal Science 6 (1):421-423. Dortch, Q., 1982. Effect of growth conditions on accumulation of internal nitrate, ammonium, amino acids, and protein in three marine diatoms. Elsevier Biomedical Press 61 (1982):243-264. Dou, Y. N. Qu, B. Wang, Y. Z. Chi, and Y. L. Ren. 2007. Simultaneous determination of two active components in compound aspirin tablets using principal component artificial neural networks (PC-ANNs) on NIR spectroscopy. European Journal of Pharmaceutical Sciences 32 (2007):193-199. Ferree, M. A., and R. D. Shannon. 2001. Evaluation of a second derivative UV/Visble spectroscopy technique for nitrate and total nitrogen analysis of wastewater samples. PERGAMON 25 (1):2001. FOSS NIRSystems Inc. 2005. A brief introduction to NIR spectroscopy. USA：FOSS NIRSystems Inc. Available at: http://www.winisi.com/. Accessed 20 August 2010. GSU. 2001. Quantum Harmonic Oscillator Georgia: Department of Physics and Astronomy. Available at: hyperphysics.phy-astr.gsu.edu/hbase/hframe.html. Accessed 12 August 2010. Garcia-Ciudad, A., A. Ruano, F. Becerro, I. Zabalgoeazcoa, B. R. Vazquez de Aldana, and B. Garcia-Criado. 1999. Assessment of Potential of NIR Spectroscopy for the Estimation of Nitrogen content in Grasses from Semiarid Grasslands. Animal Feed Science and Technology 77:91-98. Gillon, D., C. Houssard, and R. Joffre. 1999. Usinf Near-Infrared Reflectance Spectroscopy to Predict Carbon, Nitrogen and Phosphorus Content in Heterogeneous Plant Material. Oecologia. 118:173-182. Grossman, Y. L., S. L. Ustin, S. Jacquemoud, E. W. Sanderson, G. Schmuck, and J. Verdebout. 1996. Critique of Stepwise Multiple Linear Regression for the Extraction of Leaf Biochemistry Information from Leaf Reflectance Data. Remote Sens. Environ. 56:182-193. Hikosaka, K. and I. Terashima. 1995. A model of the acclimation of photosynthesis in the leaves of C3 plant to sun and shade with respect to nitrogen use. Plant Cell Envir. 18:605:618. Huang, W, D. W. Lamb, Z. Niu, Y. Zhang, L. Liu, and J. Wang. 2007. Identification of yellow rust in wheat using in-situ spectral reflectance measurements and airborne hyperspectral imaging. Precision Agric 8 (2007):187-197. Johnson L. F., S. R. Herwitz, B. M. Lobitz, S. E. Dunagan. 2004. Feasibility of monitoring coffee field ripeness with airborne multispectral imagery. Transactions of the ASAE 20(6): 845-849. Johnson, L. F., and C. R. Billow. 1996. Spectroscopic estimation of total nitrogen concentration in Douglas-fir Foliage. Int. J. Remote Sens. 17:489-500. Kim, M. S., Y. R. Chen, and P. M. Mehl. 2001a. Hyperspectral reflectance and fluorescence imaging system for food quality and safety. American Society of Agricultural Engineers 44 (3) 721-729. Kim, M. S., J. E. McMurtrey, C. L. Mulchi, C. S. T. Daughtry, E. W. Chappelle, and Y. R. Chen. 2001b. Steady-state multispectral fluorescence imaging system for plant leaves. Applied Optics 40 (1):157-166. Kramer, K. and S. Ebel. 2000. Application of NIR reflectance spectroscopy for the identification of pharmaceutical excipients. Analytica Chimica Acta 420：155-161. Lee, W. S., J. F. Sanchez, R. S. Mylavarapu, J. S. Choe. 2003. Estimating Chemical Properties of Florida Soils Using Spectral Reflectance. Transactions of the ASAE 46(5):1443-1453. Melzer, J. M., A. Kleinhofs, and R. L. Warner. 1989. Nitrate reductase regulation: Effects of nitrate and light on nitrate reductase mRNA accumulation. Mol Gen Genet 217 (1989):341-346. Merckle, P., and K.-A. Kovar. 1998. Assay of effervescent tablets by near-infrared spectroscopy in transmittance and reflectance mode: Acetylsalicylic acid in mono and combination formulations. Journal of Pharmaceutical and Biomedical Analysis 17 (1998):365-374. Naganathan, G. K., L. M. Grimes, J. Subbiah, C. R. Calkins, A. Samal, and G. E. Meyer. 2008. Visible/near-infrared hyperspectral imaging for beef tenderness prediction. Computers and Electronics in Agriculture 64 (2): 225-233. Naidu, R. A., E. M. Perry, F. J. Pierce, and T. Mekuria. 2009. The potential of spectral reflectance technique for the detection of grapevine leafroll-associated virus-3 in two red-berried wine grape cultivars. Computers and Electronics in Agriculture 66 (2009)38-45. Plugge,W. C. and van der Vlies. 1996. Near-infrared spectroscopy as a tool to improve quality. Journal of Pharmaceutical and Biomedical Analysis 14: 891-898. Rao, K. P., and D. W. Rains. 1976. Nitrate absorption by barley II. Influence of nitrate reductase activity. Plant Physiol 57 (1976):59-62. Reinink, K., and A. H. Eenink. 1988. Genotypical differences in nitrate accumulation in shoots and roots of lettuce. Scientia Horticulturae 37 (1988):13-24. Sankaran, Sindhuja. A. Mishra, R. Ehsani, and C. Davis. 2010. A review of advanced techniques for detecting plant diseases. Computers and Electronics in Agricultures 72 (2010)1-13. Scaife, A., K. L. Stevents. 1983. Monitoring Sap nitrate in vegetable crops: Comparison of test strips with electrode methods, and effects of time of day and leaf position. Soil Science Plant Analysis 14 (9):761-771. Stalcup, H., and R. W. Williams. 1955. Volumetric determination of nitrocellulose and nitroguanidine by transnitration of salicylic acid. Analytical Chemistry 27 (4):1955. Trafford, A. D., R. D. Jee, A. C. Moffat, and P. Graham. 1998. A rapid quantitative assay of intact paracetamol tablets by reflectance near-infrared spectroscopy. Analyst 124 (1999):163-167. Valyi-Nagy, I., K. J. Kaffka, J. M. Jako, E. Gonczol and G. Domjan. 1997. Application of near infrared spectroscopy to the determination of haemoglobin. Clinica Chimica Acta. 264: 117-125. VariSpecTMTunableFilter. 2001. User's Manual. Ver. 4.5. U.S.A.: Cambridge Research & Instrumentation, Inc. Vomhof , D. W., and J. H. Thomas. 1970. Determination of moisture in starch hydrolyzates by near-infrared and infrared spectrophotometry. Analytical Chemistry 42 (1):1230:1233. Warren, R. J., J. E. Zarembo, C. W. Chong, and M. J. Robinson. 1970. Determination of trace amounts of water in glycerides by near-infrared spectroscopy. Journal of Pharmaceutical Sciences 59 (1):109-110. Yang, C. M., and C. H. Cheng. 2001. Spectral characteristics of rice plants infested by brown planthoppers. Proceedings of the National Science Council, Republic of China. Part B, Life Sciences 25 (3):180-186. Yano, T., T. Aimi, Y. Nakano and M. Tamai. 1997. Prediction of the Concentrations of Ethanol and Acetic Acid in the Culture Broth of a Rice Vinegar Fermentation Using Near-Infrared Spectroscopy. Journal of Fermentation and Bioengineering 84(5)：461-465. Yao, w., R. H. Byrne, and R. D. Waterbury. 1998. Determination of nanomolar Concentrations of nitrite and nitrate in natural waters using long path length Absorbance Spectroscopy. Environmental Science and Technology 32 (17):1998. Yoder, B. J. and R. E. Pettigrew-Crosby. 1995. Predicting Nitrogen and Chlorophyll Content and Concentrations from Reflectance Spectra(400-2500 nm) at Leaf and Canopy Scales. Remote Sens. Environ. 53:199-211. Zhang, M., Z. Qin, X. Liu, and S. L. Ustin. 2003. Detection of stress in tomatoes induced by late blight disease in California, USA, using hyperspectral remote sensing. International Journal of Applied Earth Obserbation 4 (2003):295-310. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/47364 | - |
| dc.description.abstract | 蔬菜為人類日常飲食中不可或缺之食物，然而蔬菜容易因天氣、施氮肥過度等因素，而殘留過多有害健康之硝酸鹽，因此本研究應用光譜影像檢測技術，建立出可快速檢測蔬菜中硝酸鹽濃度之方法。
本研究以皺葉萵苣為樣本，在種植過程中施加不同濃度之硝酸鹽溶液，以增加實驗樣本間硝酸鹽濃度之差異性，實驗進行時，樣本先以實驗型分光光度計NIRS 6500掃描及自行開發之高光譜影像系統對樣本進行取像，並將取得之影像經處理得樣本之吸收光譜資訊。最後將光譜資訊及實際硝酸鹽濃度進行MLR迴歸分析，結果顯示NIRS 6500搭配波長740, 496, 460, 680, 468 nm時之結果，rc可達0.66、SEC= 467 ppm，而驗證組之rv為0.57、SEV=470 ppm，顯示硝酸鹽與近紅外光光譜吸收度有一定程度之相關性。 以研究中自行開發的高光譜影像系統檢測硝酸鹽濃度，並搭配波長480, 690, 790, 930, 760 nm時，其結果rc更可高達0.91、SEC= 307 ppm，而驗證組之rv為0.59、SEV=589 ppm，此結果推測是高光譜影像系統具備空間解析能力，使吸收光譜與成份值間之關係更加吻合。研究最後將高光譜影像系統之檢測結果，與市售硝酸鹽檢測器進行比較，實驗過程中，市售之硝酸鹽檢測器在採樣時必須以蔬菜汁液進行量測，乃是破壞性之量測，相較於高光譜影像之非侵入、非破壞性，優劣其實已顯而易見，而實驗結果也證明高光譜影像系統的檢測能力明顯超越了市售硝酸鹽度計（SEC= 307 vs 534 ppm），高光譜影像系統同時也具備了其他技術所沒有的空間解析資訊，故本研究成果具有蔬菜產業之應用性。 | zh_TW |
| dc.description.abstract | Vegetable is an indispensable food. However, excessive nitrate in vegetable due to over-fertilization or weather is become a health problem to human. In this study, the spectral imaging technique is applied to establish a method, which can rapidly measure nitrate concentration in vegetables.
Both NIRS 6500 spectrophotometer and hyperspectral imaging system (HIS) which was designed and developed in this study were used to measure the spectra and spectral images of loose-leaf lettuce. The lettuce was cultured under different nitrate concentrations. Multiple linear regression (MLR) was adopted to establish calibration models. The best model for NIRS 6500, was found at wavelengths 480, 602, 1,210, 1,580, 1,688 nm, and the results showed that rc= 0.66, SEC= 467 ppm, rv= 0.57, and SEV= 470 ppm. The best model for hyperspectral imaging system with wavelengths 480, 690, 790, 930, 760 nm indicated that rc= 0.91, SEC= 307 ppm, rv= 0.59, and SEV= 589 ppm. The result is much better than that of NIRS 6500 spectrophotometer, mainly because hyperspectral imaging system has spatial resolutions while spectrophotometer can only measure single spot. The hyperspectral imaging system was then compared with commercial nitrate meter, and HSIS still had better results (SEC= 307 vs 533 ppm). Since hyperspectral imaging system is a non-invasive non-destructive and rapid measurement method, it has great potential for applications to vegetable cultivation. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T05:56:38Z (GMT). No. of bitstreams: 1 ntu-100-R98631003-1.pdf: 2559530 bytes, checksum: 10f88329ca9d45939f69823f9f3d3b07 (MD5) Previous issue date: 2011 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
誌 謝 ii 摘 要 iii Abstract iii 目 錄 v 圖目錄 vii 表目錄 ix 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 硝酸鹽相關探討 3 2-1-1 硝酸鹽對人體之影響 3 2-1-2 植物生理與硝酸鹽之關係 4 2-1-3 植物中硝酸鹽濃度之定義 5 2-1-4 硝酸鹽濃度之標準檢測方法 6 2-2 近紅外光檢測技術 9 2-2-1 近紅外光技術應用於生物材料檢測 11 2-2-2 光譜影像技術應用於生物材料檢測 13 2-3 光譜學技術檢測硝酸鹽 17 第三章 研究方法 22 3-1 實驗材料 22 3-2 實驗設備 23 3-2-1 近紅外光分光光度計 23 3-2-2 高光譜影像系統 25 3-2-3 手持式硝酸鹽度計 26 3-3 實驗方法 27 3-3-1 高光譜影像處理與分析 27 3-3-2 硝酸鹽化學值分析 30 3-4 檢量模式建立方法 31 3-4-1 光譜前處理 31 3-4-2 多重線性迴歸 32 3-4-3 檢量線建立方法與指標 32 第四章 結果與討論 35 4-1 硝酸鹽濃度化學分析結果 35 4-1-1 比色法檢量線建立 35 4-1-2 蔬菜中硝酸鹽濃度 35 4-2 皺葉萵苣之吸收光譜 36 4-2-1 NIRS 6500量測之光譜吸收度 36 4-2-2 高光譜影像系統量測之光譜吸收度 37 4-3 檢量模式建立 38 4-3-1 NIRS 6500之檢量模式建立 38 4-3-2 高光譜影像系統之檢量模式建立 41 4-3-3 高光譜影像之檢量模式應用 43 4-4 手持式硝酸鹽度計檢測結果 44 第五章 結論與建議 46 5-1 結論 46 5-2 建議 46 參考文獻 46 | |
| dc.language.iso | zh-TW | |
| dc.subject | 硝酸鹽檢測 | zh_TW |
| dc.subject | 光譜影像技術 | zh_TW |
| dc.subject | 近紅外光技術 | zh_TW |
| dc.subject | Nitrate Measurement | en |
| dc.subject | Near-Infrared | en |
| dc.subject | Spectral Imaging | en |
| dc.title | 以光譜影像技術檢測葉菜類蔬菜之硝酸鹽含量 | zh_TW |
| dc.title | Evaluation of Nitrate Content in Leafy Vegetable
Using Spectral Imaging Techniques | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 99-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 艾群,謝廣文,羅筱鳳,顏炳郎 | |
| dc.subject.keyword | 光譜影像技術,近紅外光技術,硝酸鹽檢測, | zh_TW |
| dc.subject.keyword | Spectral Imaging,Near-Infrared,Nitrate Measurement, | en |
| dc.relation.page | 55 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2011-08-19 | |
| 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 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-100-1.pdf 未授權公開取用 | 2.5 MB | Adobe PDF |
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。