Use of NIR spectroscopy and chemometrics to predict the concentration of different compounds in unroasted coffee beans.
Near infrared spectroscopy (NIR) coupled with chemometrics is considered as a low cost, rapid and eco-friendly methodology in both off-line and on-line analyses of various food products. However, there are some methodological restrictions regarding its use to quantify chemical constituents in raw coffee beans.
To overcome these limitations, a recent study carried out by a group of Brazilian researchers (Ribeiro et al., 2021) proposed some innovations in the methodological approach for quantifying caffeine, trigonelline and 5-caffeoylquinic acid (5-CQA) in unroasted beans.
In particular, this approach involves the use of novel mixtures and doping of matrices belonging to different coffee species and their addition with pure target compounds to increase their variability in calibration models. Partial least squares regression (PLSR) was used as a multivariate analysis to build the calibration model for each compound.
The results show that the calibration models constructed are suitable for a reliable prediction of the concentration of caffeine, trigonelline and 5-CQA, with mean square error (RMSE) values of 0.08, 0.07 and 0.27 and correlation coefficient (rvc) of 0.98, 0.96 and 0.96, respectively. In addition, 46 wavelength regions were selected to be used in subsequent studies to allow, for example, the prediction of the compounds concentration in coffee beans, irrespective of their degree of roasting.
Development of a smartphone-based biosensor for the detection of ochratoxin A in coffee.
Exposure to mycotoxins, such as ochratoxin A (OTA), is a serious risk to consumers’ health. Laboratory methods of analysis for the detection and quantification of OTA play a key role in ensuring food safety. However, to avoid contamination across the entire food supply chain, quick and easy-to-use screening tools are required, suitable for field analysis.
In this context, in a recent study carried out by a group of Italian researchers (Zangheri et al., 2021), a smartphone-based biosensor was developed for the detection and quantification of OTA in instant coffee. In particular, the proposed system combines the use of a lateral flow immunoassay (LFIA) with chemiluminescence (CL) detection. This system consists in a stand-alone device, integrated into a smartphone, and uses low-cost, disposable analytical cartridges containing all the reagents needed to perform the analysis.
The analyses can be carried out at the point of need by non-specialized operators through simple manual operations using the smartphone camera as a light detector. The biosensor allows OTA quantitative detection in coffee samples up to limits of detection of 0.1 μg L-1. In conclusion, the authors argue that the results so far demonstrate that the developed device can be used for routine monitoring of OTA contamination in coffee, allowing rapid and reliable identification of positive samples requiring confirmatory analysis. The same device can also be used for wine.
References: J.S. Ribeiro et al., Food Control, 125, 2021, 107967, Zangheri et al., Analytica Chimica Acta, 1163, 2021, 338515.