Four-channel fluorescent sensor array based on various functionalized CdTe quantum dots for the discrimination of Chinese baijiu

A novel colorimetric and fluorometric dual-signal identification of crude baijiu based on La-CDs

The correct classification of strong-flavored crude baijiu affects its quality and overall standard and is crucial for the intelligent development of the baijiu industry. In this work, we developed a novel optical sensing array using lanthanum-doped carbon dots (La-CDs). Using La-CDs with three metal complex dyes-chromium black T, alizarin red, and dimethylphenol orange-we were able to detect organic acids and tannic acid (TA) in crude baijiu in a way that was both colorimetric and fluorescent for the first time. Based on the indicator displacement (IDA) principle, organic acids competitively replace the dyes' binding sites on La3+, causing the dye colors to change to varying degrees. TA quenches the fluorescence of quantum dots through an internal filtering effect. We analyzed the data using pattern recognition algorithms such as HCA, PCA, and LDA, successfully classifying and identifying 16 types of strong-flavored crude baijiu, which included 10 types of carboxylic acids and various grades. In blind tests of 32 crude baijiu samples, the colorimetric method achieved a 94 % accuracy rate, while the fluorescence method achieved 100 %. The sensor demonstrates significant advantages in response speed.

Nanotechnology-based optical sensors for Baijiu quality and safety control

Baijiu quality and safety have received considerable attention owing to the gradual increase in its consumption. However, owing to the unique and complex process of Baijiu production, issues leading to quality and safety concerns may occur during the manufacturing process. Therefore, establishing appropriate analytical methods is necessary for Baijiu quality assurance and process control. Nanomaterial (NM)-based optical sensing techniques have garnered widespread interest because of their unique advantages. However, comprehensive studies on nano-optical sensing technology for quality and safety control of Baijiu are lacking. In this review, we systematically summarize NM-based optical sensor applications for the accurate detection and quantification of analytes closely related to Baijiu quality and safety. Furthermore, we evaluate the sensing mechanisms for each application. Finally, we discuss the challenges nanotechnology poses for Baijiu analysis and future trends. Overall, nanotechnological approaches provide a potentially useful alternative for simplifying Baijiu analysis and improving final product quality and safety.

A novel organic acids-targeted colorimetric sensor array for the rapid discrimination of origins of Baijiu with three main aroma types

Given the severe problem of Baijiu authenticity, it is essential to discriminate Baijiu from different origins quickly and effectively. As organic acids (OAs) are the most dominant taste-imparting substances in Baijiu, we proposed a simple, fast, and effective OAs-targeted colorimetric sensor array based on the colorimetric reaction of 4-aminophenol (AP)/4-amino-3-chlorophenol (ACP) under oxidation of Cu(NO3)2 for the rapid discrimination of origins of Baijiu with three main aroma types. Hydrogen ions ionized from OAs induced the protonation of the amino group, which blocked the colorimetric reaction, and the different levels of OAs in Baijiu enabled the array to discriminate different origins of Baijiu. The array was implemented to analyze 10 simple OAs and 16 mixed OAs and further for the discrimination of 42 Baijius with an accuracy of 98%. This method provided an efficient research strategy for a basis for rapid quality analysis of Baijiu.

Organic-Acid-Sensitive Visual Sensor Array Based on Fenton Reagent-Phenol/Aniline for the Rapid Species and Adulteration Assessment of Baijiu

Baijiu is an ancient, distilled spirit with a complicated brewing process, unique taste, and rich trace components. These trace components play a decisive role in the aroma, taste, and especially the quality of baijiu. In this paper, the redox reaction between the Fenton reagent and four reducing agents, including o-phenylenediamine (OPD), p-phenylenediamine (PPD), 4-aminophenol (PAP), and 2-aminophenol (OAP), was adopted to construct a four-channel visual sensor array for the rapid detection of nine kinds of common organic acids in baijiu and the identification of baijiu and its adulteration. By exploiting the color-changing fingerprint response brought by organic acids, each organic acid could be analyzed accurately when combined with an optimized variable-weighted least-squares support vector machine based on a particle swarm optimization (PSO-VWLS-SVM) model. What is more, this novel sensor also could achieve accurate semi-quantitative analysis of the mixed organic acid samples via partial least squares discriminant analysis (PLSDA). Most importantly, the sensor array could be further used for the identification of baijiu with different species through the PLSDA model and the adulteration assessment with the one-class partial least squares (OCPLS) model simultaneously.

A three-modal fluorescent sensor harnessing diverse luminescent mechanisms for the purpose of segmented Baijiu identification

The classification and verification of segmented Baijiu hold significant importance as they profoundly influence the blending and overall quality of the Baijiu. Our scholarly investigation yielded a fluorescent sensor with three luminescent modes by integrating Tb3+ and RHB into UiO-66. The interplay between carboxyl-containing compounds and RHB/Tb@TLU-2 orchestrates a harmonious molecular association, where the convergence of carboxyl groups with Tb3+ yields a resonating impact on the antenna effect of BDC-SO3-. Furthermore, the acidity and alkalinity of reactants induced a charge transfer interaction between BDC-NH2 and Zr4+ and led to structural changes in RHB/Tb@TLU-2, resulting in observable fluorescence signal variations across the three emission centers. The sensor array successfully identified eight organic acids, achieving an impressive 97.5 % accuracy in discerning segmented Baijiu samples from four Baijiu pits. This meticulous methodology prioritizes simplicity, swiftness, and effectiveness, paving the path for comprehensive segmented Baijiu analysis in the esteemed realm of Brewing production.

Machine-learning-assisted SERS nanosensor platform toward chemical fingerprinting of Baijiu flavors

A novel fingerprinting platform for multiplex detection of flavor molecules in Baijiu was developed by using a surface-enhanced Raman scattering (SERS) nanosensor array in combination with machine learning. The SERS sensors were constructed by core-shell Fe₃O₄@Ag nanoparticles modified with molecules carrying end-groups of hydroxyl, pyridyl, methyl, and amino, respectively, which interacted with flavors and led to changes in the sensors' spectra. All the Raman spectra acquired from the nanosensor array contacting with the sample were concatenated into a single SERS super-spectrum, representing the flavor fingerprint which was recognized through machine learning. Principal component analysis, support vector machine, and partial least squares were utilized to build classification and quantitation models for predictive analyses. The SERS nanosensor array was successfully used for fingerprinting ten typical flavors in Baijiu including four esters, three alcohols, and three acids, with an accuracy of 100%, linear detection ranges over two orders of magnitude, and limits of detection ranging from 3.45 × 10^-3 mg/L of phenylethyl acetate to 1.21 × 10^-2 mg/L of ethyl hexanoate. It was also demonstrated that satisfactory accuracies (recoveries) ranging from 96.2 to 104% and relative standard deviations ranging from 0.65 to 2.78% were obtained for the simultaneous quantification of 3-methylbutyl acetate and phenylethyl acetate in eighteen Baijiu samples of three flavor types including sauce flavor, strong flavor, and light flavor. Compared with the existing detection techniques, this chemical fingerprinting platform is easy to use, highly sensitive, and can perform multiplex detection, which has great potential for practical applications.

Machine learning based age-authentication assisted by chemo-kinetics: Case study of strong-flavor Chinese Baijiu

The aged Chinese liquor, Baijiu, is highly valued for its superior organoleptic qualities. However, since age-authentication method and aging-mechanism elucidation of Baijiu is still in the exploratory stage, high-quality aged Baijiu is often replaced by lower-quality, less-aged product with fraudulent mislabeling. Authentic high-quality strong-flavor Baijiu was analyzed by gas chromatography-mass spectrometry. Total esters decreased with aging, while acids, alcohols, aldehydes, ketones, terpenes, pyrazines increased. Although concentrations of partial compounds showed non-monotonic profiling during aging, a close positive linear correlation (R² = 0.7012) of Baijiu Evenness index (0.55-0.59) with aging time was observed, indicating a more balanced composition in aged Baijiu. The reaction quotient (Qc) of each esterification, calculated by the corresponding reactant and product concentration, approached to the corresponding thermodynamic equilibrium constant Kc. This result demonstrated that the spontaneous transformation driven by thermodynamics explained part of the aging compositional profiling. Furthermore, an aging-related feature selection and an age-authentication method were established based on three models combined with five ranking algorithms. Forty-one key features, including thirty-six compound concentrations, four esterification Qc values and the Evenness index were selected out. The age-authentication based on neural network using forty-one input features accurately predicted the age group of Baijiu samples (F1 = 100 %). These findings have deepened understanding of the Baijiu aging mechanism and provided a novel, effective approach for age-authentication of Baijiu and other liquors.

Synergy of physicochemical reactions occurred during aging for harmonizing and improving flavor

Numerous counterfeit vintage Baijiu are widely distributed in the market driven by economic interest which disturb the market economic rules and damage the reputation of particular Baijiu brand. Found on the situation, the Baijiu system variation during aging period, aging mechanisms and discrimination strategies for vintage Baijiu are systematically illuminated. The aging mechanisms of Baijiu cover volatilization, oxidation, association, esterification, hydrolysis, formation of colloid molecules and catalysis by metal elements or other raw materials dissolved from storage vessels. The discrimination of aged Baijiu has been performed by electrochemical method, colorimetric sensor array or component characterization coupled with multivariate analysis. Nevertheless, the characterization of non-volatile compounds in aged Baijiu is deficient. Further research on the aging principles, more easy-operation and low-cost discrimination strategies for aged Baijiu are imperative. The above information is favorable to better understand the aging process and mechanisms of Baijiu, and promote the development of artificial aging techniques.

A novel dual-channel fluorescence sensor array based on the reaction of o-phenylenediamine/3,4-diaminotoluene and pyrocatechol for Baijiu discrimination

An effective method to discriminate Baijiu carries important applications for grade identification and quality control in the Baijiu industry. Herein, we report on a novel and straightforward dual-channel fluorescence sensor array for flavor compounds (FCs) and Chinese Baijiu discrimination. Unit 1 (U1) is the reaction between o-phenylenediamine (OPD) and pyrocatechol (ODHB), and unit 2 (U2) is the reaction between 3,4-diaminotoluene (3,4-DAT) and ODHB. The fluorescent products were changed via FCs in Baijiu relying on the influence of protonation of the amino group on OPD/3,4-DAT and chemical reactions. The array successfully achieves qualitative and quantitative identification of FCs with low detection limits and wide linear ranges. In addition, qualitative identification of 0.7 mmol/L FCs in Baijiu is achieved. Finally, this is applied to discriminate 32 Baijius varieties with different aromas, brands, and grades. The fluorescence sensor array is reliable and straightforward for FCs identification and Baijius discrimination, which is of great significance for authenticity identification in the Baijiu industry.

Boronate affinity-based template-immobilization surface imprinted quantum dots as fluorescent nanosensors for selective and sensitive detection of myricetin

In order to prepare a kind of efficient fluorescence sensors for determination of cis-diol-containing flavonoids, novel imprinted quantum dots for myricetin (Myr) were prepared based on boronate affinity-based template-immobilization surface imprinting. The obtained boronate affinity-based surface imprinted silica (imprinted APBA-functionalized CdTe QDs) was used as recognition elements. The quantum dots were used as signal-transduction materials. Under the optimum conditions, according to fluorescence quenching of imprinted APBA-functionalized CdTe QDs by Myr, the imprinting factor (IF) for Myr was evaluated to be 7.88. The result indicated that the boronate affinity functionalized quantum dots coated with imprinted silica were successfully prepared. The prepared imprinted APBA-functionalized CdTe QDs exhibited good sensitivity and selectivity for Myr. The fluorescence intensity was inversely proportional to the concentration of Myr in the 0.30-40 μM concentration range. And its detection limit was obtained to be 0.08 μM. Using the fluorescence sensors, the detection of Myr in real samples was successfully carried out, and the concentration of Myr in green tea and apple juice samples was evaluated to be 2.26 mg/g and 0.73 mg/g, respectively. The recoveries for the spiked green tea and apple juice samples were 95.2-105.0% and 91.5-111.0%, respectively. This study also provides an efficient fluorescent detection method for cis-diol-containing flavonoids in real samples.