利用便携式 LED 荧光光谱仪和化学计量学快速鉴定无刺蜂蜂蜜 (SBH)。

IF 4.7 2区 农林科学 Q1 FOOD SCIENCE & TECHNOLOGY
Foods Pub Date : 2024-11-16 DOI:10.3390/foods13223648
Diding Suhandy, Dimas Firmanda Al Riza, Meinilwita Yulia, Kusumiyati Kusumiyati, Mareli Telaumbanua, Hirotaka Naito
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引用次数: 0

摘要

印度尼西亚无刺蜂蜂蜜(SBH)很受欢迎,价格昂贵。糙米糖浆(RS)经常被用作一种廉价的掺假剂,用于 SBH 的经济动机掺假(EMA)。在这项研究中,我们制备了正宗的印尼相思树Geniotrigona thoracica SBH(n = 100)、掺假的SBH(n = 120)、假冒的SBH(n = 100)和RS(n = 200)。简言之,将每种样品的 2 毫升直接滴入创新型样品夹中,无需进行任何样品制备,包括稀释。使用荧光光谱仪采集荧光强度。这种便携式仪器配备了 365 nm LED 灯作为固定激发光源。对平滑光谱数据进行了主成分分析(PCA)计算。结果表明,利用平滑光谱数据可以很好地区分真品 SBH 和非 SBH(掺假 SBH、假冒 SBH 和 RS)样品。校准和验证的前两个 PC 的累积方差百分比分别为 98.4749% 和 98.4425%。使用主成分分析-线性判别分析(PCA-LDA)获得的预测准确率最高,达到 99.5%。使用组合区间获得了最佳偏最小二乘法(PLS)校准,校准和验证的 R2cal = 0.898 和 R2val = 0.874。在预测方面,所建立的模型可以预测掺假蜂蜜样品中的掺假水平,预测偏差比(RPD)= 2.282,范围误差比(RER)= 6.612,均可接受。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rapid Authentication of Intact Stingless Bee Honey (SBH) by Portable LED-Based Fluorescence Spectroscopy and Chemometrics.

Indonesian stingless bee honey (SBH) of Geniotrigona thoracica is popular and traded at an expensive price. Brown rice syrup (RS) is frequently used as a cheap adulterant for an economically motivated adulteration (EMA) in SBH. In this study, authentic Indonesian Geniotrigona thoracica SBH of Acacia mangium (n = 100), adulterated SBH (n = 120), fake SBH (n = 100), and RS (n = 200) were prepared. In short, 2 mL of each sample was dropped directly into an innovative sample holder without any sample preparation including no dilution. Fluorescence intensity was acquired using a fluorescence spectrometer. This portable instrument is equipped with a 365 nm LED lamp as the fixed excitation source. Principal component analysis (PCA) was calculated for the smoothed spectral data. The results showed that the authentic SBH and non-SBH (adulterated SBH, fake SBH, and RS) samples could be well separated using the smoothed spectral data. The cumulative percentage variance of the first two PCs, 98.4749% and 98.4425%, was obtained for calibration and validation, respectively. The highest prediction accuracy was 99.5% and was obtained using principal component analysis-linear discriminant analysis (PCA-LDA). The best partial least square (PLS) calibration was obtained using the combined interval with R2cal = 0.898 and R2val = 0.874 for calibration and validation, respectively. In the prediction, the developed model could predict the adulteration level in the adulterated honey samples with an acceptable ratio of prediction to deviation (RPD) = 2.282, and range error ratio (RER) = 6.612.

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来源期刊
Foods
Foods Immunology and Microbiology-Microbiology
CiteScore
7.40
自引率
15.40%
发文量
3516
审稿时长
15.83 days
期刊介绍: Foods (ISSN 2304-8158) is an international, peer-reviewed scientific open access journal which provides an advanced forum for studies related to all aspects of food research. It publishes reviews, regular research papers and short communications. Our aim is to encourage scientists, researchers, and other food professionals to publish their experimental and theoretical results in as much detail as possible or share their knowledge with as much readers unlimitedly as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. There are, in addition, unique features of this journal: Ÿ manuscripts regarding research proposals and research ideas will be particularly welcomed Ÿ electronic files or software regarding the full details of the calculation and experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material Ÿ we also accept manuscripts communicating to a broader audience with regard to research projects financed with public funds
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