Quantitation of volatile aldehydes using chemoselective response dyes combined with multivariable data analysis

Discrimination of toxigenic and non-toxigenic Aspergillus flavus in wheat based on nanocomposite colorimetric sensor array

A novel method was developed for the early detection of wheat infected with Aspergillus flavus (A. flavus) using a nanocomposite colorimetric sensors array (CSA). LC-MS analysis revealed the presence of Aflatoxin B1 (AFB1) and Aflatoxin B2 (AFB2) on day seven, demonstrating mycotoxin variabilities in infected wheat. HS-SPME-GC-MS analysis detected 2-methylbutyral, a gas exclusively associated with toxigenic A. flavus. The CSA was modified using three nanoparticles of MOF and successfully used to detect the wheat infected with A. flavus. Discrimination of different types of infected wheat samples was achieved using the RGB difference map and Principal Component Analysis (PCA) model. Additionally, the Linear Discriminant Analysis (LDA) model accurately predicted the presence of toxigenic A. flavus at various stages of infection. These findings highlight the promising capabilities of nanocomposite CSA for early-stage detection of A. flavus infection in wheat.

Study on the Characteristics of Vacuum-Bagged Fermentation of Apo Pickle and Visualization Array Analysis of the Fermentation Process

Apo pickle is a fermented food with a long edible history in the Jiangnan region of China. Traditionally, plastic bottles are used as Apo pickle's fermentation containers, and artificial bottling costs are high. The goal of this study is to compare the fermentation effects of Apo pickle fermented under low pressure in a vacuum bag (VBA) and Apo pickle fermented under normal pressure in plastic bottles (TBA) to determine the feasibility of fermenting Apo pickle in a vacuum bag rather than a plastic bottle, thereby lowering production costs. At the same time, a gas-sensitive colorimetric sensor array (CSA) was developed to distinguish different fermentation stages of Apo pickle. The results revealed that the main genera in the initial and final phases of Apo pickle fermentation were Weissella and Lactobacillus, unaffected by fermentation containers. At the same fermentation time, the abundance of Lactobacillus and the content of flavor substances in VBA were higher, and the fermentation speed of VBA was faster at 0-15 d, so a vacuum bag could be used instead of a plastic bottle. The CSA could discriminate between different fermentation procedures of Apo pickles with an accuracy rate of 93.8%. Its principle is similar to that of an electronic nose. It has the advantages of convenience, rapidity, and no need for professional equipment, so it can be used as a new method to judge the fermentation degree of apo pickle.

A rapid aroma quantification method: Colorimetric sensor-coupled multidimensional spectroscopy applied to black tea aroma

Aroma affects the quality of black tea, and the rapid evaluation of aroma quality is the key to realize the intelligent processing of black tea. A simple colorimetric sensor array coupled with a hyperspectral system was proposed for the rapid quantitative detection of key volatile organic compounds (VOCs) in black tea. Feature variables were screened based on competitive adaptive reweighted sampling (CARS). Furthermore, the performance of the models for VOCs quantitative prediction was compared. For the quantitative prediction of linalool, benzeneacetaldehyde, hexanal, methyl salicylate, and geraniol, the CARS-least-squares support vector machine model's correlation coefficients were 0.89, 0.95, 0.88, 0.80, and 0.78, respectively. The interaction mechanism of array dyes with VOCs was based on density flooding theory. The optimized highest occupied molecular orbital levels, lowest unoccupied molecular orbital energy levels, dipole moments, and intermolecular distances were determined to be strongly correlated with interactions between array dyes and VOCs.

Fusion-based strategy of CSA and mobile NIR for the quantification of free fatty acid in wheat varieties coupled with chemometrics

The use of sensor fusion, a novel method of combining artificial senses, has become increasingly popular in the assessment of food quality. This study employed a combination of the colorimetric sensor array (CSA) and mobile near-infrared (NIR) spectroscopy to predict free fatty acids in wheat flour. In conjunction with a partial least squares model, Low- and mid-level fusion strategies were used for quantification. Accordingly, performance of the built model was evaluated based on higher correlation coefficients between calibration and prediction (R_C and R_P), lower root mean square error of prediction (RMSEP), and a higher residual predictive deviation (RPD). The mid-level fusion coupled PLS model produced superior data fusion findings, with R_C = 0.8793, RMSECV = 7.91 mg/100 g, R_P = 0.8747, RMSEP = 6.99 mg/100 g, and RPD = 2.27. The findings of the study suggest that the NIR-CSA fusion approach could be effectively applied to the prediction of free fatty acids in wheat flour.

Advanced applications of chemo-responsive dyes based odor imaging technology for fast sensing food quality and safety: A review

Public attention to foodquality and safety has been increased significantly. Therefore, appropriate analytical tools are needed to analyze and sense the food quality and safety. Volatile organic compounds (VOCs) are important indicators for the quality and safety of food products. Odor imaging technology based on chemo-responsive dyes is one of the most promising methods for analysis of food products. This article reviews the sensing and imaging fundamentals of odor imaging technology based on chemo-responsive dyes. The aim is to give detailed outlines about the theory and principles of using odor imaging technology for VOCs detection, and to focus primarily on its applications in the field of quality and safety evaluation of food products, as well as its future applicability in modern food industries and research. The literatures presented in this review clearly demonstrated that imaging technology based on chemo-responsive dyes has the exciting effect to inspect such as quality assessment of cereal , wine and vinegar flavored foods , poultry meat, aquatic products, fruits and vegetables, and tea. It has the potential for the rapid, reliable, and inline assessment of food safety and quality by providing odor-image-basedmonitoring tool. Practical Application: The literatures presented in this review clearly demonstrated that imaging technology based on chemo-responsive dyes has the exciting effect to inspect such as quality assessment of cereal , wine and vinegar flavored foods, poultry meat, aquatic products, fruits and vegetables, and tea.