Alps food authentication, typicality and intrinsic quality by near infrared spectroscopy

Quantitative determination of zearalenone in wheat by the CSA-NIR technique combined with chemometrics algorithms

In the current study, a colorimetric sensor array combined with near-infrared (NIR) spectroscopy was used to quantitatively analyze zearalenone in wheat. The portable NIR spectrometer was used to scan the porphyrin reaction points of the wheat colorimetric sensor and collect spectral data. Subsequently, based on all the NIR spectral data, the two models and three feature selection algorithms are compared, and the best performance model and the best feature variable input are selected. Concurrently, the Kernel-based Extreme Learning Machine (KELM) model optimized by the two parameter optimization algorithms was compared, and the best parameter optimization algorithm was selected. Among all evaluation models, the KELM model optimized by the Competitive Adaptive Reweighted Sampling algorithm combined with the rime optimization algorithm has the best prediction effect. The predicted RP2 is 0.9900, and the root mean square error of prediction (RMSEP) is 18.4610 μg∙kg-1.

Establishing authenticity of hay milk: Detection of silage feeding through cyclopropane fatty acids analysis using 1H NMR spectroscopy

Cyclopropane fatty acids (CPFAs) serve as indicators of silage feeding, verifying the authenticity of hay milk where silage feeding is forbidden. In this study, the authenticity of hay milk was determined by detecting CPFAs using proton nuclear magnetic resonance (1H NMR) spectroscopy. 245 milk samples were collected in South Tyrol (Italy), categorized as follows: 98 from grass silage-fed cows, 98 from maize silage-fed cows, and 49 authentic hay milk. The limit of detection of CPFAs was 12 µM, corresponding to 70 mg/kg of freeze-dried milk. The CPFAs were absent in all of the hay milk samples, verifying their authenticity. In contrast, 97 % of maize silage and 77 % of grass silage samples exhibited distinct CPFAs signals. These findings were further corroborated by gas chromatography-mass detector (GC-MS) analysis. The study highlights 1H NMR as a robust, and rapid technique for hay milk authentication, supporting alpine dairy production and increasing consumer trust in food authenticity.

Analyzing the Quality Parameters of Apples by Spectroscopy from Vis/NIR to NIR Region: A Comprehensive Review

Spectroscopic methods deliver a valuable non-destructive analytical tool that provides simultaneous qualitative and quantitative characterization of various samples. Apples belong to the world's most consumed crops and with the current challenges of climate change and human impacts on the environment, maintaining high-quality apple production has become critical. This review comprehensively analyzes the application of spectroscopy in near-infrared (NIR) and visible (Vis) regions, which not only show particular potential in evaluating the quality parameters of apples but also in optimizing their production and supply routines. This includes the assessment of the external and internal characteristics such as color, size, shape, surface defects, soluble solids content (SSC), total titratable acidity (TA), firmness, starch pattern index (SPI), total dry matter concentration (DM), and nutritional value. The review also summarizes various techniques and approaches used in Vis/NIR studies of apples, such as authenticity, origin, identification, adulteration, and quality control. Optical sensors and associated methods offer a wide suite of solutions readily addressing the main needs of the industry in practical routines as well, e.g., efficient sorting and grading of apples based on sweetness and other quality parameters, facilitating quality control throughout the production and supply chain. This review also evaluates ongoing development trends in the application of handheld and portable instruments operating in the Vis/NIR and NIR spectral regions for apple quality control. The use of these technologies can enhance apple crop quality, maintain competitiveness, and meet the demands of consumers, making them a crucial topic in the apple industry. The focal point of this review is placed on the literature published in the last five years, with the exceptions of seminal works that have played a critical role in shaping the field or representative studies that highlight the progress made in specific areas.

Multi-Way Analysis Coupled with Near-Infrared Spectroscopy in Food Industry: Models and Applications

Near-infrared spectroscopy (NIRS) is a fast and powerful analytical tool in the food industry. As an advanced chemometrics tool, multi-way analysis shows great potential for solving a wide range of food problems and analyzing complex spectroscopic data. This paper describes the representative multi-way models which were used for analyzing NIRS data, as well as the advances, advantages and limitations of different multi-way models. The applications of multi-way analysis in NIRS for the food industry in terms of food process control, quality evaluation and fraud, identification and classification, prediction and quantification, and image analysis are also reviewed. It is evident from this report that multi-way analysis is presently an attractive tool for modeling complex NIRS data in the food industry while its full potential is far from reached. The combination of multi-way analysis with NIRS will be a promising practice for turning food data information into operational knowledge, conducting reliable food analyses and improving our understanding about food systems and food processes. To the best of our knowledge, this is the first paper that systematically reports the advances on models and applications of multi-way analysis in NIRS for the food industry.

Investigations into the Performance of a Novel Pocket-Sized Near-Infrared Spectrometer for Cheese Analysis

The performance of a newly developed pocket-sized near-infrared (NIR) spectrometer was investigated by analysing 46 cheese samples for their water and fat content, and comparing results with a benchtop NIR device. Additionally, the automated data analysis of the pocket-sized spectrometer and its cloud-based data analysis software, designed for laypeople, was put to the test by comparing performances to a highly sophisticated multivariate data analysis software. All developed partial least squares regression (PLS-R) models yield a coefficient of determination (R²) of over 0.9, indicating high correlation between spectra and reference data for both spectrometers and all data analysis routes taken. In general, the analysis of grated cheese yields better results than whole pieces of cheese. Additionally, the ratios of performance to deviation (RPDs) and standard errors of prediction (SEPs) suggest that the performance of the pocket-sized spectrometer is comparable to the benchtop device. Small improvements are observable, when using sophisticated data analysis software, instead of automated tools.

Feasibility of using a bacteriophage-based structural color sensor for screening the geographical origins of agricultural products

An M13 bacteriophage-based color sensor, which can change its structural color upon interaction with a gaseous molecule, was evaluated as a screening tool for the discrimination of the geographical origins of three different agricultural products (garlic, onion, and perilla). Exposure of the color sensor to sample odors induced the self-assembled M13 bacteriophage bundles to swell by the interaction of amino acid residues (repeating units of four glutamates) on the bacteriophage with the odor components, resulting in a change in the structural color of the sensor. When the sensor was exposed to the odors of garlic and onion samples, the RGB color changes were considerable because of the strong interactions of the odor components such as disulfides with the glutamate residues on the sensor. Although the patterns of the color variations were generally similar between the domestic and imported samples, some degrees of dissimilarities in their intensities were also observed. Although the magnitude of color change decreased for perilla, the color change patterns between the two groups were somewhat different. With the acquired RGB data, a support vector machine was employed to distinguish the domestic and imported samples, and the resulting accuracies in the measurements of garlic, onion, and perilla samples were 94.1, 88.7, and 91.6%, respectively. The differences in the concentrations of the odor components between both groups and/or the presence of specific components exclusively in the odor of one group allowed the color sensor-based discrimination. The demonstrated color sensor was thus shown to be a potentially versatile and simple as an on-site screening tool. Strategies able to further improve the sensor performance were also discussed.

Novel Molecular Spectroscopic Multimethod Approach for Monitoring Water Absorption/Desorption Kinetics of CAD/CAM Poly(Methyl Methacrylate) Prosthodontics

Water absorbed to poly(methyl methacrylate) (PMMA)-based CAD/CAM (computer-assisted design/computer-assisted manufacturing) prosthodontics can alter their properties including hardness and stability. In the present contribution, water absorption and desorption kinetics under defined experimental conditions were monitored employing several supplementary and advanced Fourier transform infrared (FT-IR) spectroscopic techniques in combination with multivariate analysis (MVA). In this synergistic vibrational spectroscopic multimethod approach, first a novel near-infrared (NIR) diffuse fiber optic probe reflection spectroscopic method was established for time-resolved analysis of water uptake within seven days under controlled conditions. Near-infrared water absorbance spectra in a wavenumber range between 5288-5100 cm^-1 (combination band) and 5424-5352 cm^-1 (second overtone) were used establishing corresponding calibration and validation models to quantify the amount of water in the milligram range. Therefore, 14 well-defined samples exposed to prior optimized experimental conditions were taken into consideration. The average daily water uptake conducting reference analysis was calculated as 22 mg/day for one week. Additionally, in this study for the first time NIR two-dimensional correlation spectroscopy (2D-COS) was conducted to monitor and interpret the spectral dynamics of water absorption on the prosthodontics in a wavenumber range of 5100-5300 cm^-1. For sensitive time-resolved recording of water desorption, a recently developed high-temperature, high-pressure FT-IR reaction cell with water-free ultra-dry in situ and operando operation was applied. The reaction cell, as well as the sample holder, was fully made of quartz glass, with no hot metal or ceramic parts in the vicinity of the high temperature zone. Applying a temperature gradient in the range of 25-150 ℃, mid-infrared (MIR) 2D-COS was successfully conducted to get insights into the dynamic behavior of O-H (1400-1800 cm^-1) absorption bands with increasing temperature over time and the release of CO₂ (2450 cm^-1) from the polymers. In addition, an ATR FT-IR imaging setup was optimized in order to investigate the surface homogeneity of the PMMA-based resins with a spatial resolution to 2 µm. From this vibrational spectroscopic multimethod approach and the collection of several analytical data, conclusions were drawn as to which degree the surface structure and/or its porosity have an impact onto the amount of water absorption.

Recent Developments in Solid-Phase Extraction for Near and Attenuated Total Reflection Infrared Spectroscopic Analysis

A review with more than 100 references on the principles and recent developments in the solid-phase extraction (SPE) prior and for in situ near and attenuated total reflection (ATR) infrared spectroscopic analysis is presented. New materials, chromatographic modalities, experimental setups and configurations are described. Their advantages for fast sample preparation for distinct classes of compounds containing different functional groups in order to enhance selectivity and sensitivity are discussed and compared. This is the first review highlighting both the fundamentals of SPE, near and ATR spectroscopy with a view to real sample applicability and routine analysis. Most of real sample analyses examples are found in environmental research, followed by food- and bioanalysis. In this contribution a comprehensive overview of the most potent SPE-NIR and SPE-ATR approaches is summarized and provided.

Non-invasive sensing for food reassurance

The main food quality traits of interest using non-invasive sensing techniques are sensory characteristics, chemical composition, physicochemical properties, health-protecting properties, nutritional characteristics and safety. A wide range of non-invasive sensing techniques, from optical, acoustical, electrical, to nuclear magnetic, X-ray, biosensor, microwave and terahertz, are organized according to physical principle.