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Rapid Quality Analysis and Discrimination of Taiwan and Thailand-imported Honey by Near Infrared Spectroscopy
|關鍵字:||near infrared spectroscopy;近紅外線;NIR;honey;quality analysis;discrimination;Thailand;蜂蜜;品質分析;鑑別;泰國||出版社:||食品科學系||摘要:||
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。
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.
|Appears in Collections:||食品暨應用生物科技學系|
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