Food Quality Evaluation Research Articles

Determination of Biogenic Amines in Fish Meat and Fermented Foods Using Column-Switching High-Performance Liquid Chromatography with Fluorescence Detection

In this study, we developed a column-switching high-performance liquid chromatography method with fluorescence detection for the simultaneous analysis of biogenic amines (BAs). This method uses an isocratic solution using acetonitrile with water as the mobile phase. Column-switching is achieved by using a switching valve with a set time program to change flow direction. Using this method, seven BAs (tryptamine, 2-phenylethylamine, putrescine, cadaverine, histamine, tyramine, and spermidine) could be separated and impurities eliminated. Using fluorescence detection, BAs could be identified with high sensitivity. We employed this method to determine the BA contents of fish (mackerel, tuna, and cod) and fermented food (a soybean product and cheese). Our results are in line with previous reports, yielded highly reproducible and quantitative results, and enabled the quick and simultaneous analysis of multiple BAs. Therefore, the method developed here may be useful for the continuous analysis of BAs in different samples to evaluate food quality.

おから粉末を利用した高齢者向け食品"つみれ"の品質評価

おから粉末を利用した高齢者向け食品"つみれ"の品質評価

Editorial overview: Foodomics technologies

Background.The progress in the analytical methods in food science and technology brought about a novel and modern approach concerning human health and food quality and safety. Foodomics is a recently coined term and is an integration of relevant omics disciplines. The constituent omics approaches have extensively been applied in biology and medical domains so far. Recently, food and nutrition scientists have also been interested in these omics research.Scope and Approach.Foodomics is a powerful tool in determining the food constituents and nutrients at the molecular level. Lately, researches in the food area have been fuelled by using the analytical techniques through different omics disciplines like proteomics, metabolomics, lipidomics, nutrigenomics, metagenomics and transcriptomics. Numerous research papers address the use of different omics technologies separately or in combination not only in analysing the food constituents but also in food authentication and evaluation of food safety and quality. It is evident that using the advanced analytical techniques in omics research has empowered the scientists looking into food and nutrition science at a broad perspective.Key Findings and Conclusions.This review discusses the recent developments in the analytical methodologies used in each “omics” discipline and how foodomics approach elucidates the arguments concerning food quality, food safety, the origin of food, human nutrition and relatedly human well-being.

Rapid and non-destructive discrimination of special-grade flat green tea using Near-infrared spectroscopy

Special-grade green tea is a premium tea product with the best rank and high value. Special-grade green tea is normally classified by panel sensory evaluation which is time and sample costly. Near-infrared spectroscopy is considered as a promising rapid and non-destructive analytical technique for food quality evaluation and grading. This study established a discrimination method of special-grade flat green tea using Near-infrared spectroscopy. Full spectrum was used for partial least squares (PLS) modelling to predict the sensory scores of green tea, while specific spectral regions were used for synergy interval-partial least squares (siPLS) modelling. The best performance was achieved by the siPLS model of MSC + Mean Centering pretreatments and subintervals from 15 intervals. The optimal model was used to discriminate special-grade flat green tea with the prediction accuracy of 97% and 93% in the cross-validation and external validation respectively. The chemical compositions of green tea samples were also analyzed, including polyphenols (total polyphenols, catechins and flavonol glycosides), alkaloids and amino acids. Principal components analysis result showed that there is potential correlation between specific spectral regions and the presence of polyphenols and alkaloids. Thus, NIR technique is a practical method for rapid and non-destructive discrimination of special-grade flat green tea with chemical support.

The Oriental fruit fly Bactrocera dorsalis learns to avoid an odorant associated with a toxin in food

AbstractTo adapt to the environment, it is important for insects to learn and evaluate food quality to avoid toxins in food. Currently, attractants are widely used for pest control, as they are environmentally friendly pesticides. Learning to associate an attractive odor with a toxin in food may influence insect behaviour in response to the attractant, thus affecting its application. In this study, we found that Bactrocera dorsalis, a serious pest of fruits and vegetables, can learn to associate a male lure compound, methyl eugenol (ME), with a sucrose solution contaminated with N,N‐diethyl‐3‐methyl benzoyl amide (DEET), a common insect repellent and decrease its proboscis extension response (PER) elicited by ME. Learning with DEET depends on its concentration, and flies exhibited significant aversive memory formation when high concentrations were used. Aversive‐DEET memory formed with 0.6% DEET persisted for at least 24 hr. We also found that aversive memory formed during training could be transferred to a behavioural response in an operant context.

Electronic Noses as a Powerful Tool for Assessing Meat Quality: a Mini Review

Food quality is a fundamental requirement for consumers, and there is growing interest in food quality assessment. An electronic nose is a machine that is designed to mimic biological olfaction and detect and discriminate among complex odors using an array of chemical sensors. Electronic noses have been widely applied for food quality evaluations because they are rapid, sensitive, and non-destructive. In the present paper, we review important applications of electronic noses to meat analysis. First, we briefly describe the components, working principle, and data processing for an electronic nose. Then, we discuss the applications of electronic noses to meat freshness evaluations, quality classification, and authenticity assessments using different pattern recognition algorithms. Despite many successful results, sensor technology limitations still restrict electronic nose applications at the industrial scale. Finally, we discuss existing problems and prospects for electronic noses in food analysis.

Swedish Consumers' Perception of Food Quality and Sustainability in Relation to Organic Food Production.

Consumers’ demand for locally produced and organic foods has increased in Sweden. This paper presents the results obtained from the analysis of data acquired from 100 consumers in Sweden who participated in an online survey during March to June 2016. The objective was to identify consumers’ demand in relation to organic food and sustainable food production, and to understand how the consumers evaluate food quality and make buying decisions. Qualitative descriptions, descriptive statistics and Pearson’s Chi-square test (with alpha value of p < 0.05 as level of significance), and Pearson’s correlation coefficient were used for analysis. About 72% of participants have the perception that organic food production method is more sustainable than conventional methods. Female consumers have more positive attitudes than men towards organic food. However, age difference, household size and income level do not significantly influence the consumers’ perception of sustainable food production concepts. Regionality, sustainable methods of production and organic production are the most important parameters to characterize the food as high quality and make buying decisions. On the other hand, product uniformity, appearance, and price were found to be relatively less important parameters. Food buying decisions and food quality were found to be highly related with Pearson’s correlation coefficient of r = 0.99.

A 1064 nm Dispersive Raman Spectral Imaging System for Food Safety and Quality Evaluation

Raman spectral imaging is an effective method to analyze and evaluate the chemical composition and structure of a sample, and has many applications for food safety and quality research. This study developed a 1064 nm dispersive Raman spectral imaging system for surface and subsurface analysis of food samples. A 1064 nm laser module is used for sample excitation. A bifurcated optical fiber coupled with Raman probe is used to focus excitation laser on the sample and carry scattering signal to the spectrograph. A high throughput volume phase grating disperses the incoming Raman signal. A 512 pixels Indium-Gallium-Arsenide (InGaAs) detector receives the dispersed light signal. A motorized positioning table moves the sample in two-axis directions, accumulating hyperspectral image of the sample by the point-scan method. An interface software was developed in-house for parameterization, data acquisition, and data transfer. The system was spectrally calibrated using naphthalene and polystyrene. It has the Raman shift range of 142 to 1820 cm−1, the spectral resolution of 12 cm−1 at full width half maximum (FWHM). The spatial resolution of the system was evaluated using a standard resolution glass test chart. It has the spatial resolution of 0.1 mm. The application of the system was demonstrated by surface and subsurface detection of metanil yellow contamination in turmeric powder. Results indicate that the 1064 nm dispersive Raman spectral imaging system is a useful tool for food safety and quality evaluation.

Development and Quality Evaluation of High Value Pet Food (Pet Treat)

Local availability of dog feeds is less and quite a big volume of dog feeds are being imported to city regularly from outside. Because of&nbsp; the higher cost of commercial dog feeds, most of the dog owners cannot afford to provide these feed to their pets. With this intention&nbsp; in mind, a few pet treats were developed taking pork by products as basic protein ingredient and incorporating vegetable by products&nbsp; as secondary ingredient. Four different pet treats were prepared combining meat and non-meat by products using four different binder&nbsp; combinations viz. Treatment- 1(Maida), Treatment-2 (Rice bran), Treatment- 3 (Wheat bran) and Treatment- 4 (Maida, Rice bran, Wheat&nbsp; bran and molasses). The products were dried in hot air oven at about 80oC for 24 hours. The products were vacuum packed in high den sity polyethylene packaging material and kept at room temperature for quality assessment. No significant differences in moisture, crude&nbsp; protein, ether extract, carbohydrate and calorie content of the prepared pet treats were observed. However, significant difference could&nbsp; be observed in pet treats prepared with addition of maida (Treatment 1) and wheat bran (Treatment 3) with respect to the ash content of&nbsp; the samples. The pet treats were found to be highly acceptable by different breeds of dogs. The costs of production of per kg pet treats&nbsp; were found to be Rs. 245.00, Rs. 240.00, Rs. 240.00 and Rs. 250.00 for treatment 1, treatment 2, treatment 3 and treatment 4 respectively.&nbsp; The products can be commercially developed and may be marketed locally for dog owners of Guwahati city.&nbsp

A Subset of Brain Neurons Controls a Sexually Dimorphic Proboscis Holding Behavior in Adult Drosophilia Melanogaster

Taste is essential for humans and animals alike to evaluate food quality and make important decisionsabout food choice and intake. How complex brains process sensory information to produce behavioris an essential question in the field of sensory neurobiology. Currently, little is known about tastecircuits in the brain as compared to other sensory systems. Here, we used the common vinegar fly,Drosophila melanogaster, to explore the potential role of brain neurons labeled by a transgenic line(VT041723-GAL4) in producing “proboscis holding” behavior (extrusion of the mouthpart withoutwithdrawal). By utilizing the GAL4/UAS binary expression system, we expressed a heat-activatedcation channel (UAS-dTrpA1) in these brain neurons and artificially activated them by elevationof temperature, subsequently examining behavior in the heat-activated proboscis extension reflex(PER) assay. We found that activation of these neurons induced proboscis holding. Interestingly, theproboscis holding phenotype was sexually dimorphic. Male flies rarely showed proboscis holdingand those that did had shorter proboscis holding durations. On the other hand, both mated and virginfemales showed significantly more proboscis holding and had longer proboscis holding durationsthan male flies. Overall, we identified a subset of brain neurons labeled by the VT041723-GAL4 linethat controls a sexually dimorphic feeding response (proboscis holding) upon activation.

Multispectral Imaging for Plant Food Quality Analysis and Visualization

The multispectral imaging technique is considered a reformation of hyperspectral imaging. It can be employed to noninvasively and rapidly evaluate food quality. Even though several imaging or sensor-based techniques have been conducted for the quality assessment of various food products, the rise of multispectral imaging has been more promising. This paper presents a comprehensive review of the use of the multispectral sensor in the quality assessment of plant foods (such as cereals, legumes, tubers, fruits, and vegetables). Different quality parameters (such as physicochemical and microbiological aspects) of plant-based foods that were determined and visualized by the combination of modeling methods and feature wavelength selection approaches are summarized. Based on the literature, the most frequently used wavelength selection methods are the successive projection algorithm (SPA) and the regression coefficient (RC). The most effective models developed for analyzing plant food products are the partial least squares regression (PLSR), least square support vector machine (LS-SVM), support vector machine (SVM), partial least squares discriminant analysis (PLSDA), and multiple linear regression (MLR). This article concludes with a discussion of challenges, potential uses, and future trends of this flourishing technique that is now also being applied to plant foods.

Chemical fingerprint and quantitative analysis of flavonoids for quality control of Sea buckthorn leaves by HPLC and UHPLC-ESI-QTOF-MS

The fruits and leaves of Sea buckthorn (Hippophae rhamnoides L.) have been proved their important medicinal and nutritional values. In this study, a high-performance liquid chromatography (HPLC) fingerprinting method based on the distribution and relative amount of seven flavonoids was established for the food quality evaluation of Sea buckthorn leaves. The chromatographic peaks were identified using UHPLC-UV-ESI-QTOF-MS. The chemometrics procedure was applied to identify more useful chemical markers for improving the quality control standard. The results indicated that the HPLC fingerprint combining similarity evaluation and quantification analysis can be successfully used to assess the quality of Sea buckthorn leaves. Chemometrics analysis shown that the quality has a certain extent differences in recovery regions and harvest time, the best harvest time was May and June which the leaves in growing period. The factors influencing its quality were also suggested based on HCA.

Recent advances in time domain NMR &amp; MRI sensors and their food applications

Time domain nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) are well-known non-destructive characterization techniques that are used to evaluate food quality. Time domain NMR is primarily based on relaxation and diffusion measurements from the signal coming from the whole sample whereas MRI enables visualization of the interiors of intact foods on a macroscopic scale without disturbing the sample based on the differences on relaxation and diffusion. A common perception that using NMR/MRI for testing food is costly is no longer valid with the advances in low-field bench top NMR/MRI instruments. This short review paper discusses the most recent developments and examples of time domain NMR and MRI based sensors for different food applications.

Freshness assessment of intact fish via 2D 1H J-resolved NMR spectroscopy combined with pattern recognition methods

Freshness of intact zebrafish was evaluated by 2D 1H J-resolved NMR spectroscopy conjugated with pattern recognition methods Without complicated sample pretreatment and specialized hardware settings, the biochemical processes of intact zebrafish from fresh to decay state and the corresponding metabolite profiles were acquired. A total of 21 metabolites were identified and their concentration variations during the spoilage process were obtained. Pattern recognition models were established for discrimination of fish from freshness to decomposition status. The results show that the concentration of lipid declines, the concentration of lactate fluctuates, and the concentrations of glycerol, asparagine, sarcosine, tyrosine, acetate, glycine and serine increase over the storage time. The observed acetate accumulation and lactate consumption may be considered as indexes for fish freshness assessment. This study indicates that the combination of high-resolution 2D 1H J-resolved NMR spectroscopy and pattern recognition methods may provide an efficient way for quality evaluation of semisolid and viscous foods.

Fast auto-clean CNN model for online prediction of food materials

Online food image detection is a key issue for intelligent food materials receiving and food supply chain applications, how to efficiently, accurately and quickly detect the image of food materials is a challenging research topic. A fast auto-clean convolutional neural network (CNN) model for online prediction of food materials is proposed, which is aiming at problems of the complex characteristics of the food images such as the complexity of the food materials, the focus of the dislocation and the uniformity of illumination. Firstly, a new approach of the auto-clean CNN models is proposed for automatic image cleaning and classification, which starting from original images and ending with multi-class prediction of clean images. Given a vocabulary of K classes, and a Yes/No clean label, two CNN models will learn a class label and a clean label respectively. Secondly, after the forward pass of two CNN models, the joint features generated from the last convolutional layers will be fed into our two loss layers. Combined with multi-class classification method, it classifies and optimizes the image dataset intelligently. Finally, an online prediction algorithm is proposed to improve the image recognition efficiency. Experimental results show that the proposed model and algorithm have good efficiency and accuracy, and the results of this study have significance to optimize the efficiency of the food supply chain industry and food quality evaluation.

Live, Eat, Love: life equilibrium as a driver of organic food purchase

PurposeThe purpose of this paper is to disentangle the effect of life equilibrium on organic food purchase intentions through a consideration of the evaluation of intrinsic and extrinsic food quality attributes. Furthermore, the study examines the role of health consciousness in achieving life equilibrium.Design/methodology/approachThe conceptual framework was developed based on previous research and tested through a quantitative study with end consumers. The hypothesized relationships were tested using structural equation modelling.FindingsThe results obtained from this study show that the perceived quality associated with the intrinsic attributes of organic food mediates a positive influence of life equilibrium on consumers’ organic food purchase intentions. The study also confirms that life equilibrium mediates the effects of health consciousness on the evaluation of intrinsic and extrinsic food quality attributes.Research limitations/implicationsThe theoretical contributions of the paper lie in uncovering the complex relationships that exist among health consciousness, life equilibrium, perceived organic food quality dimensions and purchase intentions and providing new evidence showing which perceived intrinsic organic food quality dimensions are relevant in shaping consumers’ purchase intentions.Practical implicationsThe research results suggest that organic food managers should focus on developing stronger value propositions that are based more on intrinsic food quality characteristics and less on extrinsic ones.Originality/valueThis study recognizes the relevance of life equilibrium as a specific consumer lifestyle form, which drives organic food consumption through extrinsic and intrinsic food quality attributes.

Data Mining on Fluorescence Fingerprint Information for the Food Quality Evaluation

Data Mining on Fluorescence Fingerprint Information for the Food Quality Evaluation

Development and quality evaluation of infant food with oregano essential oil for children diagnosed with cerebral palsy

The development of a meat-based food, with a pasty texture, meets the need to improve the nutritional intake (mainly protein), in children diagnosed with cerebral palsy and dysphagia disorders. This study evaluated the use of oregano essential oil (EO) on the development of an infant food (IF) for children with cerebral palsy and dysphagia disorders, and the shelf-life (polyphenols content, antioxidant activity, lipid oxidation, color, pH, syneresis and adhesives) of the product during 28 days of storage. Four treatments were developed: Standard IF (STD), without EO; Control IF (CON), with BHT; IF with 0.01% EO (EO-0.01%), and IF with 0.05% EO (EO-0.05%). The results indicated that samples containing oregano EO presented higher antioxidant activity (p < 0.01) than CON and STD. Also, EO-0.05% presented the highest polyphenol content (p < 0.02). All samples showed an increase in malonaldehyde value during storage (p < 0.001), however, this increase was more accelerated for the STD and CON. Also, STD, CON and EO-0.01% showed a reduction in syneresis and all treatments showed a reduction in adhesiveness during storage. Sample EO-0.05% showed better results in most of the analyses compared to the other treatments, demonstrating that it is possible to use a natural compound in the development of this product.

A vitamin-B2-sensing mechanism that regulates gut protease activity to impact animal's food behavior and growth.

To survive challenging environments, animals acquired the ability to evaluate food quality in the intestine and respond to nutrient deficiencies with changes in food-response behavior, metabolism and development. However, the regulatory mechanisms underlying intestinal sensing of specific nutrients, especially micronutrients such as vitamins, and the connections to downstream physiological responses in animals remain underexplored. We have established a system to analyze the intestinal response to vitamin B2 (VB2) deficiency in Caenorhabditis elegans, and demonstrated that VB2 level critically impacts food uptake and foraging behavior by regulating specific protease gene expression and intestinal protease activity. We show that this impact is mediated by TORC1 signaling through reading the FAD-dependent ATP level. Thus, our study in live animals uncovers a VB2-sensing/response pathway that regulates food-uptake, a mechanism by which a common signaling pathway translates a specific nutrient signal into physiological activities, and the importance of gut microbiota in supplying micronutrients to animals.

Emotions elicited by local food consumption, memories, place attachment and behavioural intentions

This study examines the influence of food consumption emotions on tourist’s memories of a trip, place attachment, and behavioural intentions. A web-based post-holiday survey was conducted among tourists to Rovaniemi, Finland, and a valid sample of 241 tourists was used for data analysis. Structural equation modelling was applied and all the proposed hypotheses were supported. The findings demonstrate the role of food consumption emotions on the formation of memories that further influence behavioural intentions and place attachment. Memories also mediate in both of the relationships (i.e. between “food consumption emotions” and “place attachment” and between “food consumption emotions” and “behavioural intentions”. The managerial implications include that restaurant managers should formulate a local food quality evaluation system and programme to enable tourists to gain sensual enjoyment. They should also ensure food safety to avoid negative feelings among tourists. Finally, they should focus on the servicescape and storytelling, as well as offer food souvenirs that appeal to tourists’ emotions.