Feasibility of filter‐based NIR spectroscopy for the routine measurement of olive oil fruit ripening indices

The Use of Infrared Spectroscopy for the Quantification of Bioactive Compounds in Food: A Review

Infrared spectroscopy (wavelengths ranging from 750-25,000 nm) offers a rapid means of assessing the chemical composition of a wide range of sample types, both for qualitative and quantitative analyses. Its use in the food industry has increased significantly over the past five decades and it is now an accepted analytical technique for the routine analysis of certain analytes. Furthermore, it is commonly used for routine screening and quality control purposes in numerous industry settings, albeit not typically for the analysis of bioactive compounds. Using the Scopus database, a systematic search of literature of the five years between 2016 and 2020 identified 45 studies using near-infrared and 17 studies using mid-infrared spectroscopy for the quantification of bioactive compounds in food products. The most common bioactive compounds assessed were polyphenols, anthocyanins, carotenoids and ascorbic acid. Numerous factors affect the accuracy of the developed model, including the analyte class and concentration, matrix type, instrument geometry, wavelength selection and spectral processing/pre-processing methods. Additionally, only a few studies were validated on independently sourced samples. Nevertheless, the results demonstrate some promise of infrared spectroscopy for the rapid estimation of a wide range of bioactive compounds in food matrices.

Non-destructive Evaluation of the Quality Characteristics of Pomegranate Kernel Oil by Fourier Transform Near-Infrared and Mid-Infrared Spectroscopy

The pomegranate kernel oil has gained global awareness due to the health benefits associated with its consumption; these benefits have been attributed to its unique fatty acid composition. For quality control of edible fats and oils, various analytical and calorimetric methods are often used, however, these methods are expensive, labor-intensive, and often require specialized sample preparation making them impractical on a commercial scale. Therefore, objective, rapid, accurate, and cost-effective methods are required. In this study, Fourier transformed near-infrared (FT-NIR) and mid-infrared (FT-MIR) spectroscopy as a fast non-destructive technique was investigated and compared to qualitatively and quantitatively predict the quality attributes of pomegranate kernel oil (cv. Wonderful, Acco, Herskawitz). For qualitative analysis, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) was applied. Based on OPLS-DA, FT-MIR spectroscopy resulted in 100% discrimination between oil samples extracted from different cultivars. For quantitative analysis, partial least squares regression was used for model development over the NIR region of 7,498-940 and 6,102-5,774 cm-1 and provided the best prediction statistics for total carotenoid content (R 2, coefficient of determination; RMSEP, root mean square error of prediction; RPD, residual prediction deviation; R 2 = 0.843, RMSEP = 0.019 g β-carotene/kg, RPD = 2.28). In the MIR region of 3,996-1,118 cm-1, models developed using FT-MIR spectroscopy gave the best prediction statistics for peroxide value (R 2 = 0.919, RMSEP = 1.05 meq, RPD = 3.54) and refractive index (R 2 = 0.912, RMSEP = 0.0002, RPD = 3.43). These results demonstrate the potential of infrared spectroscopy combined with chemometric analysis for rapid screening of pomegranate oil quality attributes.

Near Infrared Spectroscopy as a Green Technology for the Quality Prediction of Intact Olives

Poorly emphasized aspects for a sustainable olive oil system are chemical analysis replacement and quality design of the final product. In this context, near infrared spectroscopy (NIRS) can play a pivotal role. Thus, this study aims at comparing performances of different NIRS systems for the prediction of moisture, oil content, soluble solids, total phenolic content, and antioxidant activity of intact olive drupes. The results obtained by a Fourier transform (FT)-NIR spectrometer, equipped with both an integrating sphere and a fiber optic probe, and a Vis/NIR handheld device are discussed. Almost all the partial least squares regression models were encouraging in predicting the quality parameters (0.64 < R²_pred < 0.84), with small and comparable biases (p > 0.05). The pair-wise comparison between the standard deviations demonstrated that the FT-NIR models were always similar except for moisture (p < 0.05), whereas a slightly lower performance of the Vis/NIR models was assessed. Summarizing, while on-line or in-line applications of the FT-NIR optical probe should be promoted in oil mills in order to quickly classify the drupes for a better quality design of the olive oil, the portable and cheaper Vis/NIR device could be useful for preliminary quality evaluation of olive drupes directly in the field.

Sensory and chemical profile of a phenolic extract from olive mill waste waters in plant-base food with varied macro-composition

Phenols from olive mill waste water (OMWW) represent valuable functional ingredients. The negative impact on sensory quality limits their use in functional food formulations. Chemical interactions phenols/biopolymers and their consequences on bioactivity in plant-base foods have been widely investigated, but no studies to date have explored the variation of bitterness, astringency and pungency induced by OMWW phenols as a function of the food composition. The aim of the paper was to profile the sensory and chemical properties of phenols from OMWW in plant-base foods varied in their macro-composition. Four phenol concentrations were selected (0.44, 1.00, 2.25, 5.06 g/kg) to induce significant variations of bitterness, sourness, astringency and pungency in three plant-base food: proteins/neutral pH - bean purée (BP), starch/neutral pH - potato purée (PP), fiber/low pH - tomato juice (TJ). The macro-composition affected the amount of the phenols recovered from functionalized food. The highest recovery was from TJ and the lowest from BP. Two groups of 29 and 27 subjects, trained to general Labelled Magnitude Scale and target sensations, participated in the evaluation of psychophysical curves of OMWW phenols and of functionalized plant-base foods, respectively. Target sensations were affected by the food macro-composition. Bitterness increased with phenol concentration in all foods. Astringency and sourness slightly increased with concentration, reaching the weak-moderate intensity at the highest phenol concentration in PP and TJ only. Pungency was suppressed in BP and perceived at weak-moderate intensity in PP and TJ sample at the highest phenol concentration. Proteins/neutral pH plant-food (BP) resulted more appropriate to counteract the impact of added phenol on negative sensory properties thus allowing to optimize the balance between health and sensory properties.