A rapid food chain approach for authenticity screening: The development, validation and transferability of a chemometric model using two handheld near infrared spectroscopy (NIRS) devices

Abstract

This study assesses the application of a handheld, near infrared spectroscopy (NIRS) device, namely the NeoSpectra Micro, for the determination of oregano authenticity. Utilising a large sample set of oregano ( n = 295) and potential adulterants of oregano ( n = 109), models were developed and validated using SIMCA 15 software. The models demonstrated excellent predictability for the determination of authentic oregano and adulterant samples. The optimal model resulted in a 93.0% and 97.5% correct prediction for oregano and adulterants, respectively. Different standardisation approaches were assessed to determine model transferability to a second NIRS device. In the case of the second device, the best predictions were achieved with data that had not undergone any spectral standardisation (raw). Subsequently, the optimal model was able to correctly predict 90% of authentic oregano samples and 100% of the adulterant samples on the second device. This study demonstrates the potential of the device to be used as a simple, cost effective, reliable and handheld screening tool for the determination of oregano authenticity, at various stages of the food supply chain. It is believed that such forms of monitoring could be highly beneficial in other areas of food authenticity analysis to help combat the negative economical and health implications of food fraud.

Combining targeted metabolite analyses and transcriptomics to reveal the specific chemical composition and associated genes in the incompatible soybean variety PI437654 infected with soybean cyst nematode HG1.2.3.5.7

“…The metabolites were identified by using a local metabolite-calibrated database that contained about 500 metabolites based on the standards of peak information involving retention time and high-precision mass values [ 16 , 69 , 70 ]. Multivariate statistical analyses, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), were performed using SIMCA-P + 14.0 version software [ 84 ] to distinguish the differences in metabolic profiles between the incompatible soybean variety PI437654 and the three compatible soybean varieties, WM82, ZH13 and HF47, infected by HG1.2.3.5.7. The Hotelling’s T2 region, shown as an ellipse in the score plots of the models, defined the 95% confidence interval of the modeled variation.…”

Handheld Devices for Food Authentication and Their Applications: A Review

“…In the same wavelength range but with another NIR device, turmeric adulteration with metanil yellow (1–25%) ( w / w ) was detected with high accuracy (R 2 P > 0.96, RMSEP < 0.89%, [ 119 ]). Adulterated oregano with cistus, myrtle, olive leaf, and sumac was correctly classified by up to 98%, in addition to 93% of the authentic oregano classifications, using a miniaturised NIR device [ 120 ]. In the wavelength range from 1600 to 2400 nm, spiked soy bean samples with melamine (0.25–2% ( w / w )) could be predicted in a high precision with R 2 values from 0.94 to 0.99 and RMSEP values around 0.08–0.22% [ 121 ].…”

Unscrambling the Provenance of Eggs by Combining Chemometrics and Near-Infrared Reflectance Spectroscopy

“…As a consequence, fraud involving the false declaration of information related to egg quality has often been reported, including substitution or mislabeling [13]. Pandemics (e.g., , conflicts between countries, and climate change are significant disruptions in food supply chains, contributing to interrupting or slowing food trade, in addition to increasing food demand and lifting prices [14]. As highlighted by different scholars, these scenarios have created favorable conditions for food fraud, even in low-cost products, such as eggs [1,2,11].…”