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研究生:黃冠賓
研究生(外文):Kuan-pin Huang
論文名稱:以近紅外線光譜技術進行國產與泰國進口蜂蜜快速品質分析與鑑別之研究
論文名稱(外文):Rapid Quality Analysis and Discrimination of Taiwan and Thailand-imported Honey by Near Infrared Spectroscopy
指導教授:區少梅區少梅引用關係
指導教授(外文):Andi Shau-mei Ou
學位類別:碩士
校院名稱:國立中興大學
系所名稱:食品科學系
學門:農業科學學門
學類:食品科學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:102
中文關鍵詞:近紅外線蜂蜜品質分析鑑別泰國
外文關鍵詞:near infrared spectroscopyNIRhoneyquality analysisdiscriminationThailand
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蜂蜜是養蜂業最重要的產品之一,近年來蜂蜜產品自世界各國進口,其中以泰國為最大宗,然而國內對於國產與泰國進口蜂蜜品質差異的分析研究卻少有報告可供參考。本研究除了以一般傳統物化分析兩者品質及差異外,並以近紅外線光譜技術進行蜂蜜成分的快速定量分析以及來源的鑑別。
本研究以111件涵蓋兩個生產年度之國產及泰國進口蜂蜜樣品為試驗材料。對於蜂蜜物化特性的分析結果顯示,國產及泰國進口蜂蜜樣品在一般組成分分析上差異並不大。兩者主要差異在前者水分含量普遍較高及而後者之澱粉酶活性值較低。若以中國國家標準之等級區分,2001年樣品部分國產蜂蜜與泰國蜜樣品達乙級以上標準者分別佔74及80 %。2000年蜂蜜樣品,國產蜂蜜與泰國蜜樣品不列入等級標準者,則各佔66.67以及81.82 %。
利用近紅外線光譜技術於111件蜂蜜樣品組成份之快速分析上,色澤之L值、a值、b值、可溶性固形物、水活性、水分含量、還原糖、葡萄糖含量等8條檢量線,其R2值分別可達0.93、0.97、0.83、0.95、0.99、0.93、0.85以及0.91,預測效果之相關係數分別為0.93、0.97、0.86、0.95、0.98、0.91、0.87以及0.85,顯示此七條物化分析值之檢量線已可應用於蜂蜜之快速分析上。
蜂蜜樣品之17項物化分析特性進行主成分分析的結果顯示,樣品加入產地及生產年度兩項類別變異,可解釋所有樣品變異之44 %,整體來說,利用類別變異進行蜂蜜樣品主成分分析,可將大部分樣品依生產地區及年度區分開來。
利用蜂蜜之物化特性進行蜂蜜來源的模式鑑別分析時,泰國進口蜂蜜被鑑別錯誤的機率為0 %,而國產蜂蜜被鑑別錯誤的平均機率為10.1 %。近紅外線光譜數據以PCA法及Fisher weight法鑑別蜂蜜來源的結果顯示,國產及泰國進口蜂蜜彼此之間並不會鑑別錯誤,而以正典鑑別分析進行區分時,可利用第一項正典變數CAN1= -2作為區分國產及泰國進口蜂蜜之界限。
有鑒於蜂蜜樣品物化分析值之測定較近紅外線光譜費時,因此利用近紅外線光譜技術分析及鑑別國產及泰國進口蜂蜜為一快速且有效之方法。
Honey is one of the most important products in honey business. Recently honey is imported from different countries in Taiwan. Among them, Thailand-imported honey is the most abundant. However, little information about the difference between the quality of Taiwan and Thailand-imported honey was found in the literature. In this study, physicochemical analyses were used to examine the quality of honey from the two origins, and with Near Infrared Spectroscopy (NIRS) to investigate the feasibility of rapid quality analysis and discrimination of the origins of honey.
Totally 111 samples including Taiwan and Thailand-imported honey harvested in year 2000 and 2001 were collected for this study. In the result of physicochemical analysis, the qualities between two regions of honey did not differ much. The major differences between the two regions of honey were that the water contents were higher in Taiwan honey and the diastatic activities were lower in Thailand-imported one. According to the Chinese National Standard (CNS), 74 and 80 % of Taiwan and Thailand-imported honey harvested in year 2001 respectively were of grade B. And 66.67 and 81.82 % of Taiwan and Thailand-imported honey harvested in year 2000 respectively were all below the grades A and B of CNS.
The R2 of NIRS calibration curves of 111 honey samples for Hunter L, a, b, total soluble solids, water activities, moisture contents, reducing sugar and glucose contents were 0.93, 0.97, 0.83, 0.95, 0.99, 0.93 0.85 and 0.91, respectively. The correlation coefficients (r) for prediction of these eight constituents were 0.93, 0.97, 0.86, 0.95, 0.98, 0.91, 0.87 and 0.85, respectively. It showed that these calibration curves could be used for rapidly determining the eight physicochemical characteristics of these honey samples.
Based on the results of principal component analysis (PCA) with seventeen physicochemical characteristics, PCA with origins and harvested years categories could explain the 44 % variation of total honey samples. Generally speaking, PCA with categories could separate the honey samples with different origins and harvested years.
The pattern recognition analysis with the physicochemical characteristics of honey was applied to classify the origins of honey. The average of error classification of Thailand-imported and Taiwan honey were 0 % and 10.1 % respectively. The results of the pattern recognition analysis with NIR spectra by PCA and fisher weights showed that the average of error classification for both Taiwan and Thailand-imported honey was 0 %. When the canonical discriminant analysis was used in pattern recognition, the first canonical variable (CAN1) could used to discriminate the Taiwan and Thailand-imported honey by CAN1 = -2.
In conclusion, the results of this study indicated that NIRS is a rapid and effective method for quality analysis and discrimination of Taiwan and Thailand-imported honey.
中文摘要………………………………………….……………..……....V
英文摘要………………………………………….……………………VII
圖次…………………………………………….…….………………....IX
表次……………………………………………………………...…...…XI
壹、前言…………………………………………………………………..1
貳、文獻整理…………………………………………………………….4
I. 台灣主要蜜源植物………………………………….……………..4
一、龍眼…………………………………………………………..5
二、荔枝…………………………………………………………..5
II. 蜂蜜之物理化學特性…………………………………...………..6
一、水分…………………………………………………………..6
二、醣類………………………………..…………………………7
三、酸類…………………………..………………………………7
四、其他……………………………………...……………………8
五、蜂蜜之結晶………………………..………………………….8
六、蜂蜜之加工處理與貯藏…………….………………………..9
III. 蜂蜜之應用……………………………….…….……………….9
IV. 近紅外線光譜技術…………………….…….…………………10
一、 分析原理…………………….………….…………………10
二、 近紅外線光譜儀………………………..…………………14
三、 數據處理之方法……………………………..……………18
四、 應用軟體…………………………………………………..18
五、 近紅外線光譜技術於食品分析上之應用………………..21
V. 多變量統計分析…………………………………………………22
一、 主成分分析…………………………………….…………26
二、 線性鑑別分析………………………….…..………..……26
三、 正典鑑別分析………………………….…………………26
參、材料與方法…………………………………….………………….28
I. 試驗材料…………………………………….…….……………..28
一、原料…………………………………………………………28
二、試藥………………………………..…………….…….…….28
II. 試驗設計及流程……………………………………...…………31
III. 試驗方法…………………………………………….….………33
一、 蜂蜜物理化學特性分析…………………….……….……33
(一) 水分含量及可溶性固形物……………………………..33
(二) 糖類分析……………………………………….……….33
(三) 還原糖…………………………………………..………33
(四) 酸度………………………………………….….………34
(五) HMF…………………………………………….……….34
(六) 水活性…………………………………….…………….34
(七) Hunter L、a及b值……………………………….……..35
(八) 灰分………………………………………….….………35
(九) 澱粉酶活性值…………………………………………..35
二、近紅外線光譜分析………………………………….………36
(一) 近紅外線光譜掃描……………………………….……36
(二) 圖譜的處理…………………………………………….36
(三) 檢量線的製備……………………………………….…36
(四) 利用預測組檢測檢量線的預測能力……………….…36
三、統計分析……………………………………………….…..37
肆、結果與討論………………………………………………………..38
I. 蜂蜜物理化學品質分析及等級概況之比較及探討…………….39
一、 國產及泰國進口蜂蜜樣品一般組成差異之探討….……39
(一) 色澤……………………………………………….…….41
(二) 可溶性固形物含量、水活性………………….……….44
(三) 水分含量………………………………………..………44
(四) 酸度……………………………………………..………45
(五) 澱粉酶活性值………………………………….……….45
(六) HMF……………………………………………………..46
(七) 灰分……………………………………….…………….47
(八) 醣類……………………………….……….……………47
二、蜂蜜等級之探討…………………………..…….………….48
(一) 水分含量……………………………….….……………50
(二) 蔗糖含量………………………………………………..50
(三) 還原糖含量………………………………………..……50
(四) 灰分……………………………………………….…….51
(五) 酸度…………………………………………….……….51
(六) 澱粉酶活性值…………………………………………..51
(七) HMF…………………………………………...………...52
三、 蜂蜜樣品各物化分析值相關性之探討…………………..53
II. 利用近紅外線光譜技術於蜂蜜物理化學品質快速分析之探
討...............................................................................................53
一、 掃描光徑之選擇…………………………………..………53
二、 蜂蜜樣品之近紅外線穿透光譜圖………………………..55
三、製作蜂蜜樣品各物化分析值檢量線之探討………….…....58
(一) 檢量線組與預測組樣品的選取…………....……..……58
(二) 檢量線之製作………………………………..…………59
(三) 檢量線之評估指標………………………….…….……62
(四) 建立蜂蜜各物化分析值之檢量線………………….….63
III. 以蜂蜜各物化分析值配合模式鑑別分析區分不同蜂蜜樣品來源之應用……………………………………………………….68
一、利用主成分分析法區分蜂蜜樣品來源……………………..68
二、利用Fisher Weights法配合線性鑑別分析區分蜂蜜來源..70
IV. 以近紅外線光譜技術配合模式鑑別分析區分不同蜂蜜來源之應用…………………………………………………………....74
一、利用主成分分析法處理圖譜鑑別蜂蜜樣品來源…….……74
二、利用Fisher Weights 法配合線性鑑別分析區分蜂蜜來源...76
三、利用CDA鑑別分析進行蜂蜜樣品來源之鑑定…………..79
伍、結論…………………………………………………….….….……84
陸、參考文獻……………………………………………….…..………86
柒、附錄…………………………………………………………………97
1.三浦 剛 1988. 近紅外線分析儀在加工食品製造管理上之應用. 食品資訊. 48: 17-24.
2.方清居、徐月泙、鍾國雄、林洋山、林信山 2000 台灣蜂產品之產銷結構調整. 台灣地區重要農產品產銷研討會專輯.
3.安奎、何鎧光 1997. 養蜂學. 華香園出版社. 台北.
4.安奎、鄭元春 1990. 台灣產蜜源植物圖說(上). 台灣省立博物館出版部. 台北.
5.行政院農業委員會 2001. 89年農業生產統計提要. P.29, 59.
6.行政院農業委員會 2001. 89年農業統計年報. P.148-149
7.行政院農業委員會中部辦公室 2001. 台灣地區主要農畜產品生產及進出口量值. P.137-138.
8.吳杰、梁詩魁、彭文君 1997. 蜜源植物開花泌蜜與休眠期營養狀況的關係研究進展. 中國養蜂. 6: 16-17.
9.吳添金、林俊彥、林洋三、張世揚 1996. 蜂蜜濃縮與機械之研發. 農特產品加工研討會專刊. pp.46-49.
10.李仁雄 1998. 近紅外線光譜儀在分析纖維成份之應用. 紡織中心期刊. 8(4): 353-360.
11.李春芳 1999. 近紅外線反射光譜分析 (NIRS)在牧草營養研究上之應用. 畜牧半月刊. 64(8): 90-96.
12.林建森 1999. 台灣茶類滋味品質快速分析之研究. 國立中興大學食品科學研究所碩士論文.
13.林添立 1996. 近紅外線光譜技術在蜂蜜品質分析上的應用. 國立中興大學食品科學研究所碩士論文.
14.林添立、區少梅 1997. 台灣市售龍眼蜜之品質分析. 食品科學. 24(4): 479-489.
15.林清山 1983. 多變量分析統計法. 東華書局. 台北.
16.洪端良1994. 豆腐用大豆原料大豆品質之研究及其檢定. 國立中興大學食品科學研究所博士論文.
17.孫安迪 1999. 以醫學保健觀點論蜂產品. 台灣養蜂業展望研討會專刊. P.1-19.
18.高美丁 1999. 以食品營養觀點論蜂產品. 台灣養蜂業展望研討會專刊. P.92-104.
19.區少梅 1992. 蜂蜜之品質分析. 蜂產品加工研討會論文集. P27-43.
20.區少梅、何維彰、劉士綸 2000. 利用近紅外線光譜技術分析醬油之主要成分. 台灣農業化學與食品科學. 38(3): 255-261.
21.區少梅、林聖敦、林添立、吳松杰、田美純 1997. 近紅外線光譜技術分析椪柑品質相關成分之研究. 中國農業化學會誌. 35(5): 462-474.
22.區少梅、陳揚壽、陳玉舜、謝能 1993. 近紅外線光譜儀定量生乳之一般組成份及在生乳計價上之評估. 中國農業化學會誌. 32(4): 384-394.
23.張世揚 1988. 蜜蜂與蜂產品. 淑馨出版社. 台北.
24.張世揚 1991. 養蜂概論. 淑馨出版社. 台北.
25.張世揚 1992. 基礎養蜂學. 淑馨出版社. 台北.
26.張世揚 1994. 蜂蜜的採收與保鮮. 八十三年度蜂蜜處理與加工訓練班講義. D-1-D-2. 蠶蜂業改良場. 苗栗.
27.陳保良、張世揚、潘建銘 1996. 省產蜂蜜品質調查分析與探討. 台灣農業. 32(5): 106-122.
28.陳淑華 2000. 國產與進口龍眼蜜之鑑定. 行政院農業委員會中部辦公室農業行政及建設計劃成果報告.
29.陳陽壽 1994. 近紅外線光譜技術在牛乳品質分析、摻入檢出及乳價評估上之應用. 國立中興大學食品科學研究所碩士論文.
30.陳運造 1994. 蜂蜜的其他用途與處理. 八十三年度蜂蜜處理與加工訓練班講義. L-1-L-20. 蠶蜂業改良場. 苗栗.
31.章加寶 1995. 氣象條件對龍眼流蜜及蜜蜂採蜜之影響. 中華農業氣象. 2(3): 103-108.
32.魚住 純(葉詩鈴 編譯)1984. 近紅外線分析與日本食品及飼料工業品質管制自動化. 食品工業. 16(11): 13-25.
33.溫惠美、陳景川、陳淑華 1995. 市售蜂蜜之品質調查. 藥物食品分析. 3(4): 295-306.
34.經濟部中央標準局 1984. 中國國家標準. 食品中粗灰分之檢驗方法. 總號 5034. 類號 N6115. 經濟部. 台北.
35.經濟部中央標準局 1998. 中國國家標準. 蜂蜜. 總號 1305. 類號 N5024. 經濟部. 台北.
36.經濟部中央標準局 1998. 中國國家標準. 蔗糖檢驗法. 總號 1338. 類號 N6026. 經濟部. 台北.
37.經濟部中央標準局 1999. 中國國家標準. 蜂蜜檢驗法. 總號 1344. 類號 N6027. 經濟部. 台北.
38.葉詩鈴 1981. 應用近紅外線反射光譜儀快速測定食品成分之方法. 食品工業. 13(12): 35-38.
39.鄒箎生、洪端良 1990. 如何製備近紅外線分光儀之檢量線. 近紅外線分光儀在各種農產品品質管制上之應用研討會. 台南. 台灣.
40.鄒箎生、洪端良 1991. 近紅外線分光術定量毛豆之一般成分. 中國農業化學會誌. 29(1): 26-32.
41.劉士綸 2001. 台灣省產水果酒物理化學品質及以近紅外線光譜技術進行快速分析之研究. 國立中興大學食品科學研究所碩士論文.
42.蔡佳芬 1996. 近紅外線光譜技術在話梅品質分析上之應用. 國立中興大學食品科學研究所碩士論文.
43.羅金蓮、蘇新元 1995. 加工與貯存對蜂蜜品質影響之研究. 農特產品研討會專刊. P. 37-45.
44.羅蘇秦、張世英 1999. 近紅外線光譜儀之分析技術及其應用. 科儀新知. 25(5): 13-30.
45.關崇智 1994. 蜂王漿•蜂蜜•花粉. 青春出版社. 台北. P.83.
46.Aastveit, A. H. and Marum, P. 1993. Near-infrared reflectance spectroscopy: Different strategies for local calibrations in analysis of forage quality. Appl. Spectro. 47(4): 463-469.
47.Abu-Tarboush, H. M., Al-Kahtani, H. A. and El-Sarrage, M. S. 1993. Floral types identification and quality evaluation of some honey types. Food Chemistry. 46: 13-17.
48.Aishima, T. and Nakai, S. 1987. Pattern recognition of GC profiles for classification of cheese variety. J. Food Chem. 52(4): 939-942.
49.Amantea, G. F., Skura, B. J. and Nakai, S. 1986. Culture effect of ripening characteristics and rheological behavior of Cheddar cheese. J. Food Chem. 51(4): 912-918.
50.Anklam, E. 1999. A review of the analytical methods to determine the geographical and botanical origin of honey.
51.AOAC. 1990. Official Methods of Analysis, 15th ed. Helrich, K., ED. Association of Official Analytical Chemists. Washington, D.C., USA.
52.Assil, H. I., Sterling, R., and Sporns, P. 1991. Crystal control in processed liquid honey. J. Food Sci. 56(4): 1034-1037, 1041.
53.Bayer, S., McHard, J. A. and Winefordner, J. 1980. Determunation of geographic origins of frozen concentrated orange juices via pattern recognition. J. Agric. Food Chem. 28: 1306.
54.Chen, H. and Marks. B. P. 1998. Visible/ Near-infrared spectroscopy for physical characteristics of cooked chicken patties. J. Food Sci. 63(2): 279-282.
55.Cherchi, A., Porcu, M., Spariedda, L. and Tuberoso, C. I. G. 1997. Influence of aging on the quality of honey. Industria Conseve. 72: 266-271.
56.Dardenne, P., Sinnaeve, G., Bollen, L. and Bistion, R. 1994. Reduction of wet chemistry for NIR calibrations. Proc. of the 6th International NIRS Conference. pp. 154-160.
57.Delwiche, S. R. and Weaver, G.. 1994. Bread quality of wheat flour by near-infrared spectroscopy: feasibility of modeling. J. Food Sci. 59(2): 410-415.
58.Doner, L. W. 1977. The sugars of honey — A review. J. Sci. Fd. Agric. 28: 443.
59.Ellekjaer, M. R., Isaksson, T. and Solheim, R. 1994. Assessment of sensory quality of meat sausages using near infrared spectroscopy. J. Food Sci. 59(3): 456-464.
60.Etievant, P., Schilich, P., Bouvier, J., Symonds, P. and Bertrand, A. 1988. Varietal geographic classification of French red wines in terms of elements, amino acids and aromatic alcohols. J. Sci. Food Agric. 45: 21.
61.Fodor, P. and Molnar, E. 1993. Honey as an environmental indicator: effect of sample preparation on trace element determination by ICP-AES. Microchimica Acta. 112: 113-118.
62.García-Alvarez, M., Huidobro, J. F., Hermida, M. and Rodríguez- Otero, J. L. 2000. Major components of honey analysis by near-infrared transflectance spectroscopy. J. Agric. Food Chem. 48: 5154-5158.
63.Ghazali, H. M. and Sin M. K. 1986. Coconut honey: The effect of storage temperature on some of its physico-chemical properties. J. of Apic. Res. 25(2): 109-112.
64.Gonzales, A. P., Burin, L. and Buera, M. P. 1999. Color changes during storage of honeys in relation to their composition and initial color. Food Research International. 32: 185-191.
65.Huxsoll, C. C., Bolin, H. R. and Mackey, B. E. 1995. Near infrared analysis potential for grading raisin quality and moisture. J. Food Sci. 60(1): 176-180.
66.ISI. 1992. Routine operation and calibration software for near infrasoft instruments. Version 3.00. Infrasoft International.
67.ISI. 1998. WINISI II Manual. Infrasoft International. p. 139-194.
68.Jeuring, H. L. and Kuppers, F. J. E. M. 1980. High performance liquid chromatography of furfural and hydroxymethylfurfural in Spritis and honey. J. Assoc. Off. Anl. Chem. 63(6): 1215-1218.
69.Jimenez, M. J., Mateo, J. J., Huerta, T. and Mateo, R. 1994. Influence of the storage condition on some physicochemical and mycological parameters of honey. J. Sci. Food Agric. 64: 67-74.
70.Kamishikiryo-Yamashita, H., Oritani, Y., Takamura, H. and Matoba, T. 1994. Protein content in milk by near-infrared spectroscopy. J. Food Sci. 59(2): 313-315.
71.Kirsch, J. D. and Drennen, J. K. 1995. Near-infrared spectroscopy: Application in the analysis of tablets and solid pharmaceutical dosage forms. Appl. Spectro. Rev. 30(3): 139-174.
72.Kowalski, B. R. and Bender, C. F. 1972. Pattern recognition. A powerful approach to interpreting chemical data. I. Am. Chem. Soc. 94: 5632-5639.
73.Kwan, W. O. and Kowalski, B. R. 1978. Classification of wines applying pattern recognition to chemical composition data. J. Food Sci. 13: 1320.
74.Kwan, W. O. and Kowalski, B. R. 1980. Pattern recognition analysis of gas chromatographic data. Geographic classification of Vitis Vinifera cv. Pinot Noir from France and the United States. J. Agric. Food Chem. 28: 356.
75.Lanza, E. and Li, B. W. 1984. Application for near infrared spectroscopy for predicting the sugar content of fruit juices. J. Food Sci. 49: 995-998.
76.Latorre, M. J. García-Jares, G. Mèdina, B. and Herrero, C. 1994. Pattern recognition analysis applied to classification of wines from Galicia (northwestern Spain)with certified brand of origin. J. Agric. Food Chem. 42: 1451-1455.
77.Legrand, A., Scotter, C. N. G. and Voyiagis, M.; 1995. The NIR for juice authenticity screening. Leaping Ahead with Near Infrared Spectroscopy. P.307-311. Batten, G. D., Flinn, P. C., Welsh, L. A., and Blakeney, A. B. ED.; NIR Spectroscopy Group, Victoria Australia.
78.Mark, H. and Workman, J. Jr. 1992. Selection of the calibration samples. Spectroscopy. 7(6): 16-19.
79.Mateo, R., and Bosch-Reig, F. 1997. Sugar profiles of Spanish unifloral honeys. Food Chem. 60(1): 33-41.
80.McGlone, V. A. and Kawano, S. 1998. Firmness, dry-matter and soluble-solids assessment of postharvest kiwifruit by NIR spectroscopy. Postharvest biology and technology. 13: 131-141.
81.Meloun, M., Militky, J. and Forina, M. 1992. Clustering. Chemometrics for analytical chemistry. Ellis Horwood: New York.
82.Mitsuru, M., Maeda, S., Mitsuhashi, T. and Ozawa, S. 1991. Near-infrared spectroscopy determination of physical and chemical characteristics in beef cuts. J. Food Sci. 56(6): 1493-1496.
83.Mroczyk, W. B. and Michalski, K. M. 1998. Application of modern computer methods for recognition of chemical compounds in NIRS. Computers Chem. 22(1):119-122.
84.NSAS. 1990. Manual for near infrared spectral analysis software. NIRSystem, Inc. P. CA1-CA62.
85.Osborne, B. G. 1993. Practical NIR spectroscopy with applications in food and beverage analysis. Flour Milling and Baking Research Association.
86.Osborne, B. G., Fearn, T. and Hindle, P. H. 1993. 2nd ed. Practical Nir Spectroscopy with Applications in Food and Beverage Analysis. Longman Group UK Limited, England.
87.Peña, R. and Latorre, C. H. 1993. Pattern recognition analysis applied to classification of honeys from two geographic origins. J. Agric. Food Chem. 41: 560-564.
88.Perez-Arquille, C., Conchello, P., Arino, A., Juan, T. and Herresa, A. 1994. Quality evaluation of Spanish rosemary (Rosmarinus officinalis) honey. Food Chemistry. 51: 207-210.
89.Perez-Cerrda, M., Herrero-Villen, M. A. and Maquieira, A. 1989. Sugar rich food: determination of inorganic anions by ionic chromatography. Food Chemistry. 34: 285-294.
90.Purnomoadi, A., Batajoo, K. K., Ueda, K. and Terada, F. 1999. Influence of feed source on determination of fat and protein in milk by near-infrared spectroscopy. International Dairy Journal. 9: 447-452.
91.Purnomoadi, A., Batajoo, K. K., Ueda, K. and Terada, F. 1999. Influence on feed source on determination of fat and protein in milk by near-infrared spectroscopy. International Dairy Journal. 9: 447-452.
92.Rødbotten, R., Nilsen, B. N. and Hildrum, K. I. 2000. Prediction of beef quality attributes from early post mortem near infrared reflectance spectra. Food Chem. 69: 427-436.
93.Rodriguez-Otero, J. L., Paseiro, P., Simal, J. and Cepeda, A. 1994. Mineral content of the honeys produced in Galicia (North-west Spain). Food Chemistry. 49: 169-171.
94.Sancho, M. T., Muniategui, S., Huidobro, J. F. and Lazano, J. S. 1992. Aging of honey. J. Agric. Food Chem. 40, 134-138.
95.Scanlon, M. G., Pritchard, M. K. and Adam, L. R. 1999. Quality evaluation of processing potatoes by near infrared reflectance. J. Sci. Food Agric. 79: 763-771.
96.Schmilovitch, Z., Mizrach, A., Hoffman, A., Egozi, H. and Fuchs, Y. 2000. Determination of mango physiological indices by near-infrared spectrometry. Postharv. Biol. Technol. 19: 245-252.
97.Scotter, C. N. G. and Day, L. Z. 1992. The authentication of orange juices using near infrared spectroscopy. Making Light Work: Advances in Near Infrared Spectroscopy. P.359-398. Murray, I. and Cowe, I. A. ED.; Infrared Spectroscopy, Aberdeen, Scotland.
98.Shenk, J. S. and Westerhaus, M. O. 1991. Population definitation, sample selection, and calibration procedures for near infrared reflectance spectroscopy. Crop. Sci. 31: 469-474.
99.Singh, N. and Bath, P. K. 1997. Quality evaluation of different types of Indian honey. Food Chemistry. 58: 129-133.
100.Singh, N. and Bath, P. K. 1998. Relationship between heating and hydroxymethylfurfural formation in different honey types. J. Food Sci. Technol. 35: 154-156.
101.Smola, N. and Urleb, U. 2000. Qualitative and quantitative analysis of oxytetracycline by near-infrared spectroscopy. Anal. Chim. Acta. 410: 203-210.
102.Sollid, H., and Solberg, C. 1992. Salmon fat content estimation by near infrared transmission spectroscopy. J. Food Sci. 57(3): 792-793.
103.Steuer, B., Schulz, B. and Läger, E. 2001. Classification and analysis of citrus oils by NIR spectroscopy. Food Chem. 72: 113-117.
104.Thrasyvoulou, A. T. 1986. Use of HMF and diastase as quality of Greek honey. Journal of Apicultural Research. 25: 186-195.
105.Twomey, M., Doweney, G., and Mcnulty, P. B. 1995. The potential of NIR Spectroscopy for the detection of the adulteration of orange juice. J. Sci. Food Agric. 67, p.77-84.
106.Vasconcelos, A. M. P. and Chaves das Neves, H. J. 1989. Characterization of elementary wines of Vitis vinifera varieties by pattern recognition of free amino acid profiles. J. Agric. Food Chem. 37: 931-937.
107.Vogels, J. T. W. E., Terwel, L. Tas, A. C., Van den Berg, F., Dukel, F. and Van der Greef, J. 1996. Detection of adulteration in orange juices by a new screening method using proton NMR spectroscopy in combination with pattern recognition techniques. 44: 175-180.
108.Westerhaus, M. O. 1991. Computer simulation of partial least squares. Making Light Work: Advances in Near Infrared Spectroscopy. The 4th International Conference on Near Infrared Spectroscopy, Aberdeen, Scotland. pp. 134-139.
109.White, J. W. 1969. Moisture in honey: Review of chemical and physical methods. J. AOAC. 52(4): 729-737.
110.White, J. W. 1975. Composition of honey. From Honey: a comprehensive surveyed. Ed. By E. Crane Chapter 5. pp.157-206.
111.White, J. W. 1992. Quality evaluation of honey: role of HMF and diastase assays. I. Am-Bee-J. 132(11): 738-743.
112.White, J. W. 1992. Quality evaluation of honey: role of HMF and diastase assays. II. Am-Bee-J. 132(12): 792-794.
113.Williams, P. C. 1996. Recent advances in near-infrared applications for the agriculture and food industries. Proceeding of the 12th Non-destructive Measurements Symposium. Tsuba. p.1-15.
114.Williams, P. C., Preston, K. R., Norris, K. H. and Starkey, P. M. 1984. Determination of amino acids in wheat and barley by near-infrared reflectance spectroscopy. J. Food Sci. 49: 17-20.
115.Windham, W. R., Lyon, B. G., Champagne, E. T., Barton, F.E., Webb, B. D., McCLUNG, A. M., Moldenhauer, K. A., Linscombe, S., McKENZIE, K. S. 1989. Prediction of cooked rice texture quality using Near-Infrared reflectance analysis of whole-grain milled samples. Cereal Chem. 74(5): 626-632.
116.Workman, J. J. and Mark, H. 1992. Selecting the calibration samples. Spectroscopy. 7(6): 16-19.
117.Zagrodzki, P., Schlegel-Zawadzka, M., Krośniak, M., Malec, P., Bichoński, A. and Dutkiewicz, E. 1995. Characterisation of flour by means of pattern recognition methods. Food Chem. 53: 295-298.
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