Assessment of high pressure processed mandarin juice in the headspace by using electronic nose and chemometric analysis

Influence of the Degree of Fruitiness on the Quality Assessment of Virgin Olive Oils Using Electronic Nose Technology

The electronic nose is a non-invasive technology suitable for the analysis of edible oils. One of the practical applications in the olive oil industry is the classification of virgin oils based on their sensory characteristics. Notwithstanding that this technology, at this stage, cannot realistically replace the currently used methods, it is fruitful for a preliminary analysis of the oil quality. This work makes use of this technology to develop a methodology for the detection of the threshold by which an extra-virgin olive oil (EVOO) drops into the virgin olive oil (VOO) category. With this aim, two features were studied: the level of fruitiness level and the type of defect. The results showed a greater influence of the level of fruitiness than the type of defect in the determination of the detection threshold. Furthermore, three of the sensors (S2, S7 and S9) of the commercial e-nose PEN3 were identified as the most discriminating in the classification between EVOO and VOO oils.

Effect of swelling agent treatment on grape fruit quality and the application of electronic nose identification detection

The swelling agent is a plant growth regulator that alters the composition and content of nutrients and volatile gases in the fruit. To identify whether grape fruit had been treated with swelling agent, the odor information and quality indexes of grape berries treated with different concentrations of swelling agent were examined by using electronic nose technology and traditional methods. The contents of soluble sugars, soluble solids, soluble proteins and vitamin C were significantly increased in N-(2-chloro-4-pyridyl)-N'-phenylurea (CPPU) treated fruit. The contents of hexanal, (E)-2-hexenal, and nonanal aldehydes decreased significantly. Similarly, the levels of phenyl ethanol, 1-octanol, ethanol, and ethyl acetate alcohols and esters also decreased noticeably. Additionally, the levels of damascenone, linalool, and geraniol ketones and terpenoids decreased. However, the contents of benzaldehyde, D-limonene, acetic acid and hexanoic acid increased. In addition, the electrical signals generated by the electronic nose (e-nose) were analyzed by linear discriminant analysis (LDA), support vector machine (SVM) and random forest (RF). The average recognition rate of SVM was 94.4%. The results showed that electronic nose technology can be used to detect whether grapes have been treated with swelling agent, and it is an economical and efficient detection method.

Geographical origin identification of mandarin fruits by analyzing fingerprint signatures based on multielemental composition

Given rising traders and consumers concerns, the global food industry is increasingly demanding authentic and traceable products. Consequently, there is a heightened focus on verifying geographical authenticity as food quality assurance. In this work, we assessed pattern recognition approaches based on elemental predictors to discern the provenance of mandarin juices from three distinct citrus-producing zones located in the Northeast region of Argentina. A total of 202 samples originating from two cultivars were prepared through microwave-assisted acid digestion and analyzed by microwave plasma atomic emission spectroscopy (MP-AES). Later, we applied linear discriminant analysis (LDA), k-nearest neighbor (k-NN), support vector machine (SVM), and random forest (RF) to the element data obtained. SVM accomplished the best classification performance with a 95.1% success rate, for which it was selected for citrus samples authentication. The proposed method highlights the capability of mineral profiles in accurately identifying the genuine origin of mandarin juices. By implementing this model in the food supply chain, it can prevent mislabeling fraud, thereby contributing to consumer protection.

Rapid discrimination of the identity of infant formula by triple-channel models

Infant formula is related to children's life and health. However, the existing identification methods for infant formula are time-consuming, costly and prone to environmental pollution. Therefore, a simple, efficient and less polluting identification method for infant formula is urgently needed. The aim of this study was to distinguish between goat and cow infant formula using HS-SPME-GC-MS and E-nose combined with triple-channel models. The results indicated that the main difference of them attributed to thirteen volatile compounds and three sensor variables. Based on this, the linear discriminant and partial least squares discriminant analyses were conducted, and a multilayer perceptron neural network model was constructed to identify the commercial samples. There was a high percentage of correct classifications (>90%) in samples. Together, our work demonstrated that the volatile compounds of infant formula combined with chemometric analysis were effective and rapid for detecting two infant formulas.

Effect of dense phase carbon dioxide treatment on the flavor, texture, and quality changes in new-paocai

This study investigated the effect of dense phase carbon dioxide (DPCD) treatment on the organoleptic properties of new-paocai. Optimal DPCD treatment (25 MPa/40 °C/40 min) was determined by conducting single-factor and orthogonal experiments with the sensory, bactericidal, and electronic eye evaluations. DPCD treatment (25 MPa/40 °C/40 min) did not significantly affect the nitrite, pH, total acid, and organic acid of the new-paocai brine, and the texture of the radish slices did not display substantial changes. Gas chromatography-mass spectrometry (GC-MS) was employed to characterize the new-paocai brine flavor, revealing 63 and 60 respective flavor compounds with and without DPCD treatment. In addition, DPCD treatment significantly reduced the total organic volatile compound content in the paocai from 48.182 μg/mL to 35.952 μg/mL, DPCD has a great influence on volatile flavor substances. The electronic nose (E-nose) effectively distinguished the flavor differences in the new-paocai brine with and without DPCD treatment. This study combined new food processing technology with traditional food production, could provide a new idea for pickle production technology.

Citrus juice off-flavor during different processing and storage: Review of odorants, formation pathways, and analytical techniques

As the most widespread juice produced and consumed globally, citrus juice (mandarin juice, orange juice, and grapefruit juice) is appreciated for its attractive and distinct aroma. While the decrease of characteristic aroma-active compounds and the formation of off-flavor compounds are easy to occur in processing and storage conditions. This review provides a comprehensive literature of recent research and discovery on citrus juice off-flavor, primarily focusing on off-flavor compounds induced during processing and storage (i.e., thermal, storage, light, oxygen, package, fruit maturity, diseases, centrifugal pretreatment, and debittering process), formation pathways (i.e., terpene acid-catalyzed hydration, caramelization reaction, Maillard reaction, Strecker degradation, and other oxidative degradation) of the off-flavor compounds, effective inhibitor pathway to off-flavor (i.e., electrical treatments, high pressure processing, microwave processing, ultrasound processing, and chemical treatment), as well as odor assessment techniques based on molecular sensory science. The possible precursors (terpenes, sulfur-containing amino acids, carbohydrates, carotenoids, vitamins, and phenolic acids) of citrus juice off-flavor are listed and are also proposed. This review intends to unravel the regularities of aroma variations and even off-flavor formation of citrus juice during processing and storage. Future aroma analysis techniques will evolve toward a colorimetric sensor array for odor visualization to obtain a "marker" of off-flavor in citrus juice.

Study on the Application of Electronic Nose Technology in the Detection for the Artificial Ripening of Crab Apples

Ripening agents can accelerate the ripening of fruits and maintain a similar appearance to naturally ripe fruits, but the fruit flavor and quality will be changed compared to naturally ripe fruits. To find an efficient detection method to distinguish whether crab apples were artificial ripened, the naturally ripe and artificially ripe fruits were detected and analyzed using the electronic nose (e-nose) technique in this study. The fruit quality indexes of samples were determined by the traditional method as a reference. Significant differences were found between naturally ripe and artificially ripe fruits based on the analysis of soluble sugar content, titratable acidity content, sugar–acid ratio, soluble protein content, and soluble solids content. In addition, principal component analysis (PCA), linear discriminant analysis (LDA), support vector machine (SVM), and random forest (RF) analyses were performed on the electrical signals generated by the electronic nose sensor, respectively. The results showed that the RF is the best recognition algorithm for distinguishing which crab apples were naturally ripe or artificially ripe; the average recognition accuracy is 98.3%. On the other hand, the prediction models between the e-nose response data and fruit quality indexes were constructed by partial least squares regression (PLSR), which showed that the feature value of e-nose response curves extracted by wavelet transform was highly correlated with the quality indexes of fruits, the determination coefficients (R2) of regression models were higher than 0.91. The results demonstrated that the detection technology with an electronic nose could be used to test whether the fruit of the crab apple was artificially ripe, which is an economical and efficient method.

Tea quality evaluation by applying E-nose combined with chemometrics methods

Tea is one of the most popular beverage with distinct flavor consumed worldwide. It is of significance to establish evaluation method for tea quality controlling. In this work, electronic nose (E-nose) was applied to assess tea quality grades by detecting the volatile components of tea leaves and tea infusion samples. The "35th s value", "70th s value" and "average differential value" were extracted as features from E-nose responding signals. Three data reduction methods including principle component analysis (PCA), multi-dimensional scaling (MDS) and linear discriminant analysis (LDA) were introduced to improve the efficiency of E-nose analysis. Logistic regression (LR) and support vector machine (SVM) were applied to set up qualitative classification models. The results indicated that LDA outperformed original data, PCA and MDS in both LR and SVM models. SVM had an advantage over LR in developing classification models. The classification accuracy of SVM based on the data processed by LDA for tea infusion samples was 100%. Quantitative analysis was conducted to predict the contents of volatile compounds in tea samples based on E-nose signals. The prediction results of SVM based on the data processed by LDA for linalool (training set: R2 = 0.9523; testing set: R2 = 0.9343), nonanal (training set: R2 = 0.9617; testing set: R2 = 0.8980) and geraniol (training set: R2 = 0.9576; testing set: R2 = 0.9315) were satisfactory. The research manifested the feasibility of E-nose for qualitatively and quantitatively analyzing tea quality grades.

Impact of high-pressure processing on the stability and bioaccessibility of bioactive compounds in Clementine mandarin juice and its cytoprotective effect on Caco-2 cells

Mandarin juice is a rich source of antioxidant bioactive compounds. While the content and profile of bioactives are known, the impact of high-pressure processing (HPP) on their stability and bioaccessibility (BA) is unknown, but may allow obtaining safe, nutritious, and fresh-tasting juices with highly extractable bioactive compounds. The stability and BA of bioactive antioxidant compounds in untreated and HPP-treated (400 MPa/40 °C/1 min) Clementine mandarin juices, and the cytoprotective effect of its bioaccessible fractions (BF) obtained after simulated gastrointestinal digestion against H2O2-induced oxidative stress in differentiated Caco-2 cells were investigated. The BF of HPP-treated juices showed a better retention of carotenoids, flavonoids, ascorbic acid, total polyphenols and FRAP value, and slightly higher cytoprotection (mitochondrial membrane potential and ROS) than untreated juices. Therefore, HPP can be recommended as a suitable technology to retain or indeed increase antioxidant bioactives and their cytoprotective activity in mandarin juices after gastrointestinal digestion.

Dynamic Changes of DNA Methylation Induced by Heat Treatment Were Involved in Ethylene Signal Transmission and Delayed the Postharvest Ripening of Tomato Fruit

Deoxyribonucleic acid (DNA) methylation plays an important role in fruit ripening and senescence. Here, the role of DNA methylation of the CpG island of SlACS10, LeCTR1, LeEIN3, LeERT10, and SlERF-A1 genes induced by heat treatment (37 °C) in postharvest ripening of tomato fruit was studied. After heat treatment, the firmness and vitamin C content showed higher levels, the loss of aldehydes in volatile components was delayed, and the activities of methylase and demethylase decreased in tomato fruit. Moreover, in heat-treated fruit, significant changes in DNA methylation of SlACS10, LeCTR1, LeEIN3, LeERT10, and SlERF-A1 were induced, the expression of LeERT10 and LeEIN3 was inhibited, the expression of SlERF-A1 was increased, by which ethylene signal transmission might be suppressed and the postharvest ripening of tomato fruit was delayed. The present study provided valuable information for understanding the essential role of DNA methylation in the postharvest ripening of tomato fruit.

Degradations of aroma characteristics and changes of aroma related compounds, PPO activity, and antioxidant capacity in sugarcane juice during thermal process

Alterations of aroma properties and aroma-related attributes of sugarcane juice during thermal processing under different temperatures (90, 100, and 110 ℃) and treating time (10 s, 20 s, and 30 s) were assessed in this study. Changes in the volatility of aroma compounds were extremely complicated and respected to thermal processing conditions. Fructose, serine, and glutanic acid of sugarcane juice were increased at first and decreased at the end of treatment at high temperature. Phenolic compounds and PPO activity presented the decrease trends throughout the thermal treatment. The thermal processing of sugarcane juice could be roughly divided into three stages based on the cluster analysis of all the data in this study. Sugars, amino acids, and phenolic compounds might be important potential precursors of aroma deteriorating reactions. The comprehensive analysis of aroma relevant compounds and enzyme activities was beneficial for the investigation of degradation mechanism of aroma for sugarcane juice, and providing a theoretical basis for optimization of juice processing. PRACTICAL APPLICATION: This study demonstrated the changing process of aroma quality and associated compounds in sugarcane juice during thermal processing. This could help to find out the reasons of aroma degradations in sugarcane juice and other thermal sensitive juice. Our manuscript created a paradigm for future studies on the aroma quality control and parameter optimization during the processing of fruit and vegetable juice.

Effect of high hydrostatic pressure on aroma components, amino acids, and fatty acids of Hami melon (Cucumis melo L. var. reticulatus naud.) juice

The changes and relationships between the volatile compounds and fatty acids, and between volatile compounds and free amino acids were analyzed after they were handled by 400 and 500 MPa (45°C/10 min) high hydrostatic pressure (HHP). The volatile components of 31, 30, and 32 were detected in the untreated, 400, and 500 MPa samples, respectively. Unlike the ketones and acids, the three contents, including ester (59.59%-71.34%), alcohol (5.95%-7.56%), and aldehyde (0.36%-1.25%), were greatly changed. While HHP treatment exerted a few effects on the contents of 12 kinds of fatty acids. With the increase in pressure, the contents of palmitic acid, linolenic acid, and α-linolenic acid were remarkably reduced. The correlations between flavor compounds and amino acids, and between flavor compounds and fatty acids were studied by Pearson's correlation analysis and visualized with using the corrplot package in R software. The analysis showed that the amino acids were positively correlated with (E)-6-nonenal, (2E,6Z)-nona-2,6-dienal and (Z)-6-nonen-1-ol, while they were negatively correlated with nonanal, (Z)-3-hexen-1-ol and ethyl caproate. Besides, the fatty acids were positively correlated with the esters of 2,3-butanediol diacetate and 2-methyl propyl acetate, while they were negatively correlated with (E)-2-octenal and (Z)-6-nonen-1-ol.

Tracing internal quality and aroma of a red-fleshed kiwifruit during ripening by means of GC-MS and E-nose

'Hongyang' kiwifruit is a new breed of red-fleshed cultivar that has become broadly popular with consumers in recent years. In this study, the internal quality and aroma of this kiwifruit during ripening were investigated by means of gas chromatography-mass spectrometry (GC-MS) and electronic nose (E-nose). Results showed that the green note aldehydes declined, the main fruity esters increased, and the terpenes had no obvious changes during ripening. Correlations between quality indices, volatile compounds, and E-nose data were analyzed by ANOVA partial least squares regression (APLSR), and the results showed that firmness and titratable acidity (TA) had highly positive correlations with (E)-2-hexenal and hexanal, while soluble solids content (SSC) and SSC/TA ratio had positive correlations with ester compounds. The E-nose sensors of S7, S10, S8, S6, S9, and S2 were positively correlated with ester compounds, S1, S3, and S5 were mainly correlated with hexanal, and S4 was correlated with terpene compounds. Partial least squares regression (PLSR) and support vector machine (SVM) were employed to predict the quality indices by E-nose data, and SVM presented a better performance in predicting firmness, SSC, TA, and SSC/TA ratio (R ² > 0.98 in the training set and R ² > 0.94 in the testing set). This study demonstrated that the E-nose technique could be used as an alternative to trace the flavor quality of kiwifruit during ripening.

A chemometric approach for the prediction of the aging levels of automatic transmission fluids by mid-infrared spectroscopy

Automatic transmission fluids (ATF) are highly complex multi-component systems with a variety of different additive packages which suffer from manifold aging processes due to interfering factors. This work describes the development of a straightforward approach to model the aging effects by means of Fourier Transform Infrared (FTIR) spectroscopy combined with multivariate data analysis. Therefore, ATF samples were artificially aged under defined conditions by considering effects of product type, temperature, storage time and exposure to metallic materials, yielding 144 samples. For multivariate data analysis, three different approaches have been applied and compared: supervised Fisher's Linear Discriminant Analysis of principal components (PCFDA), regularized FDA (RFDA) of variables, and unsupervised PCA after orthogonalization using Error Removal by Orthogonal Subtraction (EROS + PCA). All methods worked well in reducing unwanted effects and transforming the relevant information to the first components. Combined with k-Nearest-Neighbor (kNN) prediction, RFDA leads to the best model, improving the accuracy ratios by 13%, 41%, and 12% in comparison with direct kNN classification for the target classes storage temperature, additional material and aging level, respectively. These results suggest that RFDA is highly suitable for the reduction of unwanted effects in a dataset with manifold perturbation influences. The model also predicted a correct aging level ranking when applied to unknown field samples.

Novel analytical method for detection of orange juice adulteration based on ultra-fast gas chromatography

ABSTRACT

The food authenticity assessment is an increasingly important issue in food quality and safety. The application of an electronic nose based on ultra-fast gas chromatography technique enables rapid analysis of the volatile compounds from food samples. Due to the fact that this technique provides chemical profiling of natural products, it can be a powerful tool for authentication in combination with chemometrics. In this article, a methodology for classification of Not From Concentrate (NFC) juices was presented. During research samples of 100% orange juice, 100% apple juice, as well as mixtures of these juices with known percentage of base juices were tested. Classification of juice samples was carried out using unsupervised and supervised statistical methods. As chemometric methods, Hierarchical Cluster Analysis, Classification Tree, Naïve Bayes, Neural Network, and Random Forest classifiers were used. The ultra-fast GC technique coupled with supervised statistical methods allowed to distinguish juice samples containing only 1.0% of impurities. The developed methodology is a promising analytical tool to ensure the authenticity and good quality of juices.

GRAPHICAL ABSTRACT

Application of novel nanocomposite-modified electrodes for identifying rice wines of different brands

In this paper, poly(acid chrome blue K) (PACBK)/AuNP/glassy carbon electrode (GCE), polysulfanilic acid (PABSA)/AuNP/GCE and polyglutamic acid (PGA)/CuNP/GCE were self-fabricated for the identification of rice wines of different brands. The physical and chemical characterization of the modified electrodes were obtained using scanning electron microscopy and cyclic voltammetry, respectively. The rice wine samples were detected by the modified electrodes based on multi-frequency large amplitude pulse voltammetry. Chronoamperometry was applied to record the response values, and the feature data correlating with wine brands were extracted from the original responses using the 'area method'. Principal component analysis, locality preserving projections and linear discriminant analysis were applied for the classification of different wines, and all three methods presented similarly good results. Extreme learning machine (ELM), the library for support vector machines (LIB-SVM) and the backpropagation neural network (BPNN) were applied for predicting wine brands, and BPNN worked best for prediction based on the testing dataset (R 2 = 0.9737 and MSE = 0.2673). The fabricated modified electrodes can therefore be applied to identify rice wines of different brands with pattern recognition methods, and the application also showed potential for the detection aspects of food quality analysis.

An Integrated Approach to Mandarin Processing: Food Safety and Nutritional Quality, Consumer Preference, and Nutrient Bioaccessibility

Mandarins are a member of the Citrus genus and are the focus of growing commercial interest, with satsuma mandarins (Citrus unshiu) and the common mandarin (Citrus reticulata Blanco) being the most important mandarin varieties. The possible health benefits and functional properties of those fruits are often associated with the antioxidative function of vitamin C, carotenoids, and phenolic compounds. While most mandarins are consumed fresh, many are processed into juices (mostly cloudy), usually via thermal processing which can lead to the creation of off-flavors and may diminish nutritional quality. The aim of this review is to summarize the most significant and recent information on the safety, sensorial properties, and nutritional benefits of mandarins and their processing into juice. The article also discusses recent information regarding the bioaccessibility of valuable, mandarin specific, compounds.