Comparison of Portable and Benchtop Near-Infrared Spectrometers for the Detection of Citric Acid-adulterated Lime Juice: A Chemometrics Approach.

IF 1.8 4区 医学 Q3 PHARMACOLOGY & PHARMACY Iranian Journal of Pharmaceutical Research Pub Date : 2022-12-01 DOI:10.5812/ijpr-128372
Reza Jahani, Saskia van Ruth, Yannick Weesepoel, Martin Alewijn, Farzad Kobarfard, Mehrdad Faizi, Mohammad Hossain Shojaee AliAbadi, Arash Mahboubi, Azadeh Nasiri, Hassan Yazdanpanah
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Abstract

Background: Since the incidence of food adulteration is rising, finding a rapid, accurate, precise, low-cost, user-friendly, high-throughput, ruggedized, and ideally portable method is valuable to combat food fraud. Near-infrared spectroscopy (NIRS), in combination with a chemometrics-based approach, allows potentially rapid, frequent, and in situ measurements in supply chains.

Methods: This study focused on the feasibility of a benchtop Fourier-transformation-NIRS apparatus (FT-NIRS, 1000 - 2500 nm) and a portable short wave NIRS device (SW-NIRS, 740 - 1070 nm) for the discrimination of genuine and citric acid-adulterated lime juice samples in a cost-effective manner following chemometrics study.

Results: Principal component analysis (PCA) of the spectral data resulted in a noticeable distinction between genuine and adulterated samples. Wavelengths between 1100 - 1400 nm and ‎‎1550 - 1900 nm were found to be more important for the discrimination of samples for the benchtop FT-NIRS data, while variables between 950 - 1050 nm contributed significantly to the discrimination of samples based on the portable SW-NIRS data. Following partial least squares discriminant analysis (PLS-DA) as a discriminant model, standard normal variate (SNV) or multiplicative scatter correction (MSC) transformation of benchtop FT-NIRS data and SNV in combination with the second derivative transformation of portable SW-NIRS data on the training set delivered equal accuracy (94%) in the prediction of the test set. In the soft independent modeling of class analogy (SIMCA) as a class-modeling approach, the overall performances of generated models on the auto-scaled data were 98% and 94.5% for benchtop FT-NIRS and portable SW-NIRS, respectively.

Conclusions: As a proof of concept, NIRS technology coupled with appropriate ‎multivariate classification models enables fast detection of citric acid-adulterated ‎lime juices. In addition, the promising results of portable SW-NIRS combined with SIMCA indicated its use as a screening tool for on-site analysis of lime juices at various stages of the food supply chain.

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便携式和台式近红外光谱仪检测柠檬酸掺假酸橙汁的比较:化学计量学方法。
背景:随着食品掺假事件的不断增加,寻找一种快速、准确、精密、低成本、用户友好、高通量、坚固耐用、理想便携的方法对打击食品欺诈具有重要意义。近红外光谱(NIRS)与基于化学计量学的方法相结合,可以在供应链中进行快速、频繁和现场测量。方法:通过化学计量学研究,探讨了台式傅里叶变换近红外光谱仪(FT-NIRS, 1000 ~ 2500 nm)和便携式短波近红外光谱仪(sww -NIRS, 740 ~ 1070 nm)鉴别柠檬酸掺假酸橙汁样品的可行性。结果:光谱数据的主成分分析(PCA)导致正品和掺假样品之间的显著区别。在台式FT-NIRS数据中,1100 ~ 1400 nm和1550 ~ 1900 nm之间的波长对样品的区分更为重要,而在便携式ss - nirs数据中,950 ~ 1050 nm之间的变量对样品的区分有显著影响。将偏最小二乘判别分析(PLS-DA)作为判别模型,将台式FT-NIRS数据和SNV的标准正态变量(SNV)或乘法散点校正(MSC)变换与便携式SW-NIRS数据在训练集上的二阶导数变换相结合,在测试集的预测中获得相同的准确度(94%)。在类类比的软独立建模(SIMCA)方法中,台式FT-NIRS和便携式SW-NIRS在自动缩放数据上生成的模型的总体性能分别为98%和94.5%。结论:作为概念验证,近红外光谱技术结合适当的多元分类模型可以快速检测柠檬酸掺假酸橙汁。此外,便携式SW-NIRS结合SIMCA的结果表明,它可以作为食品供应链各个阶段酸橙汁现场分析的筛选工具。
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来源期刊
CiteScore
3.40
自引率
6.20%
发文量
52
审稿时长
2 months
期刊介绍: The Iranian Journal of Pharmaceutical Research (IJPR) is a peer-reviewed multi-disciplinary pharmaceutical publication, scheduled to appear quarterly and serve as a means for scientific information exchange in the international pharmaceutical forum. Specific scientific topics of interest to the journal include, but are not limited to: pharmaceutics, industrial pharmacy, pharmacognosy, toxicology, medicinal chemistry, novel analytical methods for drug characterization, computational and modeling approaches to drug design, bio-medical experience, clinical investigation, rational drug prescribing, pharmacoeconomics, biotechnology, nanotechnology, biopharmaceutics and physical pharmacy.
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