Electronic nose guided determination of frying disposal time of sunflower oil using fuzzy logic analysis

An innovative carbon dots polarity probe based on intramolecular charge-transfer for visual monitoring of the total polar materials in frying oil

The presence of Total Polar Materials (TPM) in edible oils is a crucial indicator for assessing oil quality. It is of paramount importance to develop a rapid and dependable technique for monitoring polarity in frying oil. Sensitive polarity responsive fluorescence carbon dots (F-CDs) were synthesized by using p-phenylenediamine as precursors and 2-formylphenylboronic acid pinacol ester (2-FAPE) as a post-modifier. The construction of the fluorescent probe F-CDs involved a strong intramolecular charge-transfer (ICT) mechanism, with 2-FAPE serving as the electron-withdrawing fluorophore and the π-conjugated structure acting as a potent electron-donating group. A strong linear relationship was observed between the emission wavelength and the TPM value of frying oil within a range of 11% to 30%. Notably, the fluorescence color of the probe transitioned from blue to yellow under UV light at 365 nm as the TMP value increased. This study expands the range of sensing applications for CDs in food safety.

Synergistic rosemary extract with TBHQ and citric acid improves oxidative stability and shelf life of peanut

Lipid oxidation often accompanies the processing and storage of peanuts, which causes a serious waste of peanut resources. To solve the problem of being prone to oxidation in peanut processing, a ternary complex antioxidant based on rosemary extract (RE) was constructed to investigate its effect on the oxidative and thermal stability of peanuts, and the inhibition of peanut oxidation by compound antioxidants was revealed by dynamic Arrhenius formula and complexation theory. The results showed that there was a synergistic effect between RE and Tert-butyl hydroquinone (TBHQ), and the antioxidant effects of RE and TBHQ were 4.86 and 1.45 times higher when used in combination than when used alone, respectively. In addition, RE-TBHQ-CA (citric acid) effectively inhibited primary and secondary oxidation of peanuts with a shelf life 8.7 times longer than that of control peanuts. This study provides a novel antioxidant compounding idea, which has a positive effect on improving the quality of peanut and other nut products, prolonging the shelf life and reducing the waste of resources. PRACTICAL APPLICATION: Compounding a complex antioxidant that permits its use in peanuts. It was found that rosemary and TBHQ might have synergistic antioxidant effects. Meanwhile, this combination of RE-TBHQ-CA effectively inhibited the oxidation of peanut oils and prolonged the shelf life of peanuts. RE-TBHQ-CA is a highly efficient complex antioxidant that can reduce the amounts of antioxidants added while maintaining high antioxidant efficiency, which may be useful for the future preservation and storage of nut products as it positively affects the quality and shelf life of the product.

Rapid quantitative evaluation of total polar materials (TPM) in frying oil based on an "off-on" fluorescence viscosity response probe

The content of total polar material (TPM) is considered as a comprehensive indicator to evaluate the quality of edible oils which should be discarded and no longer be used when TPM content exceeding 27 %. Nevertheless, there is currently a lack of a convenient and efficient TPM detection method, which is a meaningful challenge. With the increase of TPM content, the viscosity of frying oil grows, and the two maintain a satisfactory positive correlation. Consequently, an "off-on" fluorescence probe TCF-PR method based on viscosity-response has been developed. There exists a good linear relationship between the fluorescence intensity of the probe and the TPM content of soybean oil ((R2 = 0.9936) and salad oil (R2 = 0.9878), accompanying with the advantage of fast response (3 s), which means the rapid detection of TPM can be realized to determine the quality of frying oil in the field of food safety.

Caciocavallo Podolico Cheese, a Traditional Agri-Food Product of the Region of Basilicata, Italy: Comparison of the Cheese's Nutritional, Health and Organoleptic Properties at 6 and 12 Months of Ripening, and Its Digital Communication

Traditional agri-food products (TAPs) are closely linked to the peculiarities of the territory of origin and are strategic tools for preserving culture and traditions; nutritional and organoleptic peculiarities also differentiate these products on the market. One such product is Caciocavallo Podolico Lucano (CPL), a stretched curd cheese made exclusively from raw milk from Podolian cows, reared under extensive conditions. The objective of this study was to characterise CPL and evaluate the effects of ripening (6 vs. 12 months) on the quality and organoleptic properties, using the technological "artificial senses" platform, of CPL produced and sold in the region of Basilicata, Italy. Additionally, this study represents the first analysis of cheese-related digital communication and trends online. The study found no significant differences between 6-month- and 12-month-ripened cheese, except for a slight increase in cholesterol levels in the latter. CPL aged for 6 and 12 months is naturally lactose-free, rich in bioactive components, and high in vitamin A and antioxidants and has a low PUFA-n6/n3 ratio. The "artificial sensory profile" was able to discriminate the organoleptic fingerprints of 6-month- and 12-month-ripened cheese. The application of a socio-semiotic methodology enabled us to identify the best drivers to create effective communication for this product. The researchers recommend focusing on creating a certification mark linked to the territory for future protection.

Determination of oxidative deterioration in edible oils by high-pressure photoionization time-of-flight mass spectrometry

Since lipid oxidation often causes serious food safety issues worldwide, determination of oil's oxidative deterioration becomes quite significant, which still calls for efficient analytical methods. In this work, high-pressure photoionization time-of-flight mass spectrometry (HPPI-TOFMS) was firstly introduced for rapid detection of oxidative deterioration in edible oils. Through non-targeted qualitative analysis, oxidized oils with various oxidation levels were successfully discriminated for the first time by coupling HPPI-TOFMS with the orthogonal partial least squares discriminant analysis (OPLS-DA). Furthermore, by targeted interpretation of the HPPI-TOFMS mass spectra and the subsequent regression analysis (signal intensities vs TOTOX values), good linear correlations were observed for several predominant VOCs. Those specific VOCs were promising oxidation indicators, which would play important roles as TOTOX to judge the oxidation states of tested samples. The proposed HPPI-TOFMS methodology can be used as an innovative tool for accurate and effective assessment of lipid oxidation in edible oils.

Investigation of volatile flavor compounds and characterization of aroma-active compounds of water-boiled salted duck using GC-MS-O, GC-IMS, and E-nose

To clarify the characteristic aroma substances of water-boiled salted duck (WSD), headspace-gas chromatography-mass spectrometry-olfactometry (HS-GC-MS-O), gas chromatography-ion mobility spectrometry (GC-IMS) combined with an electronic nose (E-nose) were used to analyze the volatile flavor profile of three types of WSD (containing four samples). Thirty-one and fifty volatile flavor components were identified by GC-MS and GC-IMS, including aldehydes, alcohols, esters, ketones, hydrocarbons, and others. The characteristic aroma compounds of WSD, including pentanal, hexanal, heptanal, octanal, nonanal, (E)-2-octenal, benzaldehyde, (E)-2-nonenal, decanal, 1-octen-3-ol, 1-octanol, 1-pentanol, ethyl acetate, d-limonene, and 2-pentylfuran, were confirmed by GC-O, odor activity values (OAVs), and aroma-recombination and omission experiments. The aroma description of these aroma-active compounds can be divided into 6 categories, namely, "fruity", "mushroom", "fat", "sweet", "faint scent" and "potato, scorch" aromas. The difference between samples was mainly caused by the differential volatile compounds, followed by the identification method.

Current progress on innovative pest detection techniques for stored cereal grains and thereof powders

For stored grains and their powders, pest infestation has always been a knotty problem and thus comprises a serious threat to global food security. Obviously, timely, rapid and accurate pest detection methods are of extreme importance to protect grains from pest mouth. In facing the defects of traditional methods, such as visual inspection, grain flotation and pest trap, diverse innovative approaches progressed fast alternatively, either targeting pest itself or diagnosing pest-induced changes. The former includes machine vision, metabolite analysis, pest-specific protein techniques, molecular techniques, bioacoustics analysis, conductive roller mill, low-field nuclear magnetic resonance spectroscopy and imaging, while the latter consists of thermal imaging, near-infrared spectroscopy and hyperspectral imaging, impact acoustics analysis, soft X-ray imaging and tomography. The principle, operation procedure, pros and cons and application scenarios were discussed for each method. The results herein hope to promote the technical revolution of pest inspection in stored cereal grains and their powders.

Application of Artificial Intelligence in Food Industry—a Guideline

Artificial intelligence (AI) has embodied the recent technology in the food industry over the past few decades due to the rising of food demands in line with the increasing of the world population. The capability of the said intelligent systems in various tasks such as food quality determination, control tools, classification of food, and prediction purposes has intensified their demand in the food industry. Therefore, this paper reviews those diverse applications in comparing their advantages, limitations, and formulations as a guideline for selecting the most appropriate methods in enhancing future AI- and food industry–related developments. Furthermore, the integration of this system with other devices such as electronic nose, electronic tongue, computer vision system, and near infrared spectroscopy (NIR) is also emphasized, all of which will benefit both the industry players and consumers.

A novel electronic nose for the detection and classification of pesticide residue on apples

Excessive pesticide residues are a serious problem faced by food regulatory authorities, suppliers, and consumers. To assist with this challenge, this work aimed to develop a method of detecting and classifying pesticide residue on fruit samples using an electronic nose, through the application of three different data-recognition algorithms. The apple samples carried various concentrations of two known pesticides, namely cypermethrin and chlorpyrifos. Data collection was performed using a PEN3 electronic nose equipped with 10 metal oxide semiconductor (MOS) sensors. In order to classify and analyze these pesticide residues on the apple samples, principal component analysis (PCA), linear discriminant analysis (LDA), and support vector machine (SVM) results were combined with sensor output responses to realize MOS sensor array data visualization. The results indicated that all three data-recognition algorithms accurately identified the pesticide residues in the apple samples, with the PCA algorithm exhibiting the best classification and discrimination ability. Consequently, this work has shown that the MOS electronic nose, in combination with data-recognition algorithms, can provide support for the rapid and non-destructive identification of pesticide residues in fruits and can provide an effective tool for the detection of pesticide residues in agricultural products.

The MOS electronic nose in combination with data-recognition algorithms can provide an effective tool for the detection of pesticide residues in agricultural products.

An Outlook of Recent Advances in Chemiresistive Sensor-Based Electronic Nose Systems for Food Quality and Environmental Monitoring

An electronic nose (Enose) relies on the use of an array of partially selective chemical gas sensors for identification of various chemical compounds, including volatile organic compounds in gas mixtures. They have been proposed as a portable low-cost technology to analyse complex odours in the food industry and for environmental monitoring. Recent advances in nanofabrication, sensor and microcircuitry design, neural networks, and system integration have considerably improved the efficacy of Enose devices. Here, we highlight different types of semiconducting metal oxides as well as their sensing mechanism and integration into Enose systems, including different pattern recognition techniques employed for data analysis. We offer a critical perspective of state-of-the-art commercial and custom-made Enoses, identifying current challenges for the broader uptake and use of Enose systems in a variety of applications.

Multisensory Gas Analysis System Based on Reconstruction Attractors

The paper describes the substance image formation based on the measurements by multisensor systems and the possibility of the development of a gas analysis device like an electronic nose. Classification of gas sensors and the need for their application for the recognition of difficult images of multicomponent air environments are considered. The image is formed based on stochastic transformations, calculations of correlation, and fractal dimensions of reconstruction attractors. The paper shows images created for substances with various structures that were received with the help of a multisensor system under fixed measurement conditions.

Fuzzy controller based E-nose classification of Sitophilus oryzae infestation in stored rice grain

Fuzzy controller artmap based algorithms via E-nose selective metal oxides sensor (MOS) data was applied for classification of S. oryzae infestation in rice grains. The screened defuzzified data of selective sensors was further applied to detect S. oryzae infested rice with PCA and MLR techniques. Reliability of data was cross validated with reference methods of protein and uric acid content. Out of 18 MOS, 6 sensors namely P30/2, P30/1, T30/1, P40/2, T70/2 and PA/2 showed maximum resistivity change. Defuzzified score of 62.17 for P30/2 and 59.33 for P30/1 MOS further confirmed validity studies of E-nose sensor response with reference methods. The PCA plots were able to classify up to 84.75% of rice with variable degree of S. oryzae infestation. The MLR values of predicted versus reference values of protein and uric acid content were found to be fitting with R² of 0.972, 0.997 and RMSE values of 2.08, 1.05.

Odor Discrimination by Similarity Measures of Abstract Odor Factor Maps from Electronic Noses

The aim of this study is to improve the discrimination performance of electronic noses by introducing a new method for measuring the similarity of the signals obtained from the electronic nose. We constructed abstract odor factor maps (AOFMs) as the characteristic maps of odor samples by decomposition of three-way signal data array of an electronic nose. A similarity measure for two-way data was introduced to evaluate the similarities and differences of AOFMs from different samples. The method was assessed by three types of pipe and powder tobacco samples. Comparisons were made with other techniques based on PCA, SIMCA, PARAFAC and PARAFAC2. The results showed that our method had significant advantages in discriminating odor samples with similar flavors or with high VOCs release.

Organoleptic Evaluation of Amomi Fructus and Its Further Background Verified via Morphological Measurement and GC Coupled with E-Nose

The present study investigated the maneuverability and reasonability of sensory analysis, which has been applied in TCM identification for a long time. Ten assessors were trained and generated the human panel to carry out the organoleptic evaluation of twenty-five batches of Sha-Ren samples. Accordingly, samples were scored from 0 (lowest) to 10 (highest) for sensory attributes. Based on this, samples were divided into three classes: high class (Yang-Chun-Sha from Guang-Dong), moderate class (Yang-Chun-Sha samples from Yun-Nan and Guang-Xi), and low class (Lv-Qiao-Sha from marketplaces). For further background, three instrumental approaches were employed: morphological measurement with three indices (longitudinal diameter, transverse diameter, and 100-fruit weight), GC for determination of bornyl acetate contents, and E-nose for aromatic fingerprint. It is demonstrated in the results that GC and E-nose analyses were in great agreement with organoleptic evaluation. It gives insights into further studies on searching better morphological indicators and improving discriminant model of E-nose.

Optimization of microwave roasting of peanuts and evaluation of its physicochemical and sensory attributes

In this study, the microwave (MW) roasting (MWR) of peanuts (Arachis hypogaea L.) is attempted, optimized and compared with conventional drum roasting. A two factor/three level face centered composite design based MWR experiments was conducted at different roasting time (60, 180 and 300 s) and MW power levels (180, 540 and 900 W). The roasting quality was analyzed by physicochemical and sensory attributes of roasted peanuts and extracted oil viz., moisture loss, hardness, browning index (BI), induction period (IP) based on Rancimat, peroxide value (PV) and overall acceptability (OA), respectively. A roasting time and MW power dependent improvement in the desired quality of roasted peanuts and extracted oil was observed attributable to the formation of antioxidant Maillard reaction compounds. A second order polynomial model adequately described the roasting experimental data (p < 0.0001, R² > 0.90) with an insignificant lack of fit (p > 0.05). Using response surface methodology, the MWR was optimized at roasting time of 201 s and MW power level of 900 W which yielded favorable values of quality attributes (moisture loss, 3.06%; hardness, 4528.34 g; BI, 58.89; IP, 8.12 h; PV, 8.80 milliequivalents O₂/kg; OA, 6.40). Furthermore, the quality assessment of ground peanuts for selected time-power combinations (low, optimum and high roasts) was attempted using scanning electron microscopy, electronic nose and Fourier transform infrared spectroscopy which revealed better quality of optimized MWR peanuts.