Search

The combined effects of different storage temperatures (0, 4, 10 °C) and days (3, 8, 16, 25, 35, 46 and 58 days), and the use of modified casings on sausages cooled by immersion vacuum cooling (IVC) were investigated. Sausages were firstly cooked at 72 °C and cooled to 4 °C by IVC. Texture profile, colour, pH, moisture and volatile composition of samples were measured during 58-d storage. Hardness of samples with modified casings stored at 4 °C (MIVC-4 oC) at d8 (75.28 ± 6.05 N) was significantly higher than that at d3 (38.09 ± 8.89 N) (P

In the current research, the potential of a novel method based on the artificial neural network was investigated to diagnose the freshness of common carp (Cyprinus carpio) during ice storage. Fish as an aquaculture product has high nutrients and low-fat content. So, people have consumed it as a safe and high-value foodstuff in their daily diet. Investigation of fish freshness is proposed as a significant issue in the aquaculture industry since fish spoils rapidly. The applied system of this study is comprised of the following steps: First, images of samples were captured and the pre-processing operation was done on the images. Then, particular channels including R, G, B, H, S, I, L*, a*, and b* were computed. Next, feature extraction was performed to obtain 6 types of texture features from each channel. Afterward, the hybrid Artificial Bee Colony-Artificial Neural Network (ABC-ANN) algorithm was applied to select the best features. Finally, the Support Vector Machine (SVM), K-Nearest Neighbor (K-NN) and Artificial Neural Network (ANN) algorithms as the most common methods were used to classify fish images. The best performance of the K-NN classifier was calculated in the k = 8 neighborhood size with the accuracy of 90.48. The best kernel function for the SVM algorithm was polynomial with C, sigma, and accuracy of 1, 2 and 91.52 percent, respectively. In this system, the input layer has consisted of 22 neurons based on the feature selection operation and 4 classes including most fresh, fresh, fairly fresh and spoiled have been used as the number of output layer. At the end, the best results of the MLP networks were achieved by LM learning algorithm and 6 neurons in the hidden layer with the 22–10–4 topology and accuracy of 93.01 percent. The achieved results demonstrate the high performance of the ANN classifier for evaluation of common carp freshness during ice storage as a rapid, accurate, non-destructive, real-time and automated method. It shows the potential of computer vision method in combination with artificial neural networks as an intelligent technique for evaluation of fish freshness.

Harvested tomatoes were stored under atmospheres that were normoxic, anoxic, or modified (altered O2 and CO2 concentrations). Each atmosphere was created by storing the tomatoes at 25°C for up to 8 days in different kinds of pouches. During storage, metabolites of the tomatoes were measured using metabolomics. We obtained score plots of the metabolites on eighth day of storage by principal component analysis. There was a tendency for groups to be divided on the basis of score plot according to the composition of each gas. PC1 and PC2 seemed to correspond to the influence of O2 and CO2 concentrations, respectively, and the total contribution rate of the two axes was 72%, so that we concluded that the metabolites were affected mainly by O2 and CO2 concentrations. The results indicate that metabolomics may be an effective tool to reveal the relationship between metabolic state of harvested fruits and the atmosphere.

Variable selection is a critical step for designing a dedicated multispectral real-time system from multicollinearity spectral data. It improves the prediction ability of the calibration model and provides faster prediction by reducing the curse of dimensionality. The main objective of this study was to compare the effect of variables selection algorithms on model performance for predicting moisture content in red meat using visible and near-infrared (VNIR) hyperspectral imaging in the spectral range of 400-1000 nm and corn using near-infrared (NIR) spectroscopy in the spectral range of 1100-2498 nm. Six variable selection algorithms including the size of the regression coefficient (RC), variable importance in projection (VIP), genetic algorithm (GA), competitive adaptive reweighted sampling (CARS), successive projection algorithm (SPA), and stepwise regression (SWR) were tested and compared to realize their effects on the model performance for predicting moisture content in red meat and corn. The model based on competitive adaptive reweighted sampling-partial least squares regression (CARS-PLSR) was the best model to predict moisture content in red meat and corn. The results indicated the effectiveness of variable selection for providing the feature wavelengths to design a low-cost, real-time multispectral system.

Yellowing of green vegetables due to chlorophyll decomposition is a phenomenon indicating serious deterioration of freshness, and it is evaluated by measuring color space values. In contrast, mass reduction due to water loss is a deterioration of freshness observed in all horticultural crops. Therefore, in this study, we propose a novel freshness evaluation index for green vegetables that combines the degree of greenness and mass loss. The green color retention rate was measured using a computer vision system, and the mass retention rate was measured by weighing. Linear discriminant analysis (LDA) was performed using both variables (greenness and mass) as covariates to obtain a single freshness evaluation value (first canonical variable). The correct classification of storage period length by LDA was 96%. Green color retention alone allowed for classification of storage durations between 0 day and 10 days, whereas LDA could classify storage durations between 0 day and 12 days. The novel freshness evaluation index proposed by this research, which integrates greenness and mass, has been shown to be more accurate than the conventional evaluation index that uses only greenness.

A hyperspectral imaging system was for the first time exploited to estimate the core colour of sausages stuffed in natural hog casings or in two hog casings treated with solutions containing surfactants and lactic acid in slush salt. Yellowness of sausages stuffed in natural hog casings (control group, 20.26 &plusmn, 4.81) was significantly higher than that of sausages stuffed in casings modified by submersion for 90 min in a solution containing 1:30 (w/w) soy lecithin:distilled water, 2.5% wt. soy oil, and 21 mL lactic acid per kg NaCl (17.66 &plusmn, 2.89) (p &lt, 0.05). When predicting the lightness and redness of the sausage core, a partial least squares regression model developed from spectra pre-treated with a second derivative showed calibration coefficients of determination (Rc2) of 0.73 and 0.76, respectively. Ten, ten, and seven wavelengths were selected as the important optimal wavelengths for lightness, redness, and yellowness, respectively. Those wavelengths provide meaningful information for developing a simple, cost-effective multispectral system to rapidly differentiate sausages based on their core colour. According to the canonical discriminant analysis, lightness possessed the highest discriminant power with which to differentiate sausages stuffed in different casings.

Developing a noninvasive technique to estimate the degreening (loss of green color) velocity of harvested broccoli was attempted. Loss of green color on a harvested broccoli head occurs heterogeneously. Therefore, hyperspectral imaging technique that stores spectral reflectance with spatial information was used in the present research. Using artificial neural networks (ANNs), we demonstrated that the reduction velocity of chlorophyll at a site on a broccoli head was related to the second derivative of spectral reflectance data at 15 wavelengths from 405 to 960 nm. The reduction velocity was predicted using the ANNs model with a correlative coefficient of 0.995 and a standard error of prediction of 5.37 &times, 10&minus, 5 mg&middot, g&minus, 1&middot, d&minus, 1. The estimated reduction velocity was effective for predicting the chlorophyll concentration of broccoli buds until 7 d of storage, which was established as the maximum time for maintaining marketability. This technique may be useful for nondestructive prediction of the shelf life of broccoli heads.

Controlled atmosphere (CA) storage, that is, at low O2 and high CO2 concentrations, effectively extends the shelf life of horticultural products. The influence of CA storage (O2/CO2: 2.5%/6.0% or 2.5%/0.0%) and in normal air (both at 1 &deg, C for 21 d) on the physicochemical (O2 uptake, mass loss and L-ascorbate) and biological properties of broccoli (Brassica oleracea var. italica, Plenck, 1794) via amounts and activities of terminal oxidases of the electron transport chain was investigated. Mass loss, a sensitive index of freshness for broccoli heads under CA, was significantly lower under CA than under normoxia (p &lt, 0.05). Mass loss was depressed 7 d earlier under CA, including 6.0% CO2 than under CA without CO2. High CO2 effectively depressed the degradation of L-ascorbate. During storage, the activity of the alternative oxidase (AOX) was lower under CA than in normal air (p &lt, 0.05), while the amount of cytochrome c oxidase (COX), and the AOX/COX activity ratio (based on oxygen isotope discrimination), were not affected during storage. Our results indicate that CA storage effectively retained the freshness of broccoli heads by depressing the induction of AOX. However, depression of AOX amount was not associated with CO2 around broccoli heads.

The effectiveness of a simulated microgravity environment as a novel method for preserving the freshness of vegetables was investigated. Three types of vegetables were selected: vegetable soybean, mung bean sprouts, and white radish sprouts. These selected vegetables were fixed on a three-dimensional rotary gravity controller, rotated slowly. The selected vegetables were stored at 25°C and 66% of relative humidity for 9, 6, or 5 d while undergoing this process. The simulated microgravity was controlled utilizing a gravity controller around 0 m s−2. The mung bean sprouts stored for 6 d under simulated microgravity conditions maintained higher thickness levels than the vegetable samples stored under normal gravity conditions (9.8 m s−2) for the same duration. The mass of all three items decreased with time without regard to the gravity environment, though the samples stored within the simulated microgravity environment displayed significant mass retention on and after 3 d for mung bean sprout samples and 1 d for white radish sprout samples. In contrast, the mass retention effect was not observed in the vegetable soybean samples. Hence, it was confirmed that the mass retention effect of microgravity was limited to sprout vegetables. As a result of analysis harnessing a mathematical model, assuming that the majority of the mass loss is due to moisture loss, a significant difference in mass reduction coefficient occurs among mung bean sprouts and white radish sprouts due to the microgravity environment, and the mass retention effect of simulated microgravity is quantitatively evaluated utilizing mathematical models. Simulated microgravity, which varies significantly from conventional refrigeration, ethylene control, and modified atmosphere, was demonstrated effective as a novel method for preserving and maintaining the freshness of sprout vegetables. This founding will support long-term space flight missions by prolonging shelf life of sprout vegetables.

A hyperspectral imaging (HSI) system (380–1000 nm) was investigated for non-invasively estimating adenosine triphosphate (ATP) content in ready-to-eat sausages during 5 days storage at 35 °C. A set of pretreated combinations were carried out on preprocessing the spectra to improve the performance of partial least squares regression (PLSR). According to the regression coefficient values, ten important wavelengths (385, 390, 395, 505, 580, 670, 745, 780, 855, and 955 nm) were selected in this study. PLSR models developed using full wavelengths and optimal wavelengths showed the prediction coefficient of determination (rp2) up to 0.8324 and 0.8606, respectively. The concentration and location of the ATP content in sausages were for the first time displayed via chemical imaging developed by R statistics. Combining HSI and multivariate analysis can quantify and visualize ATP dynamic changes during storage and a great potential in the processed meat industry for real-time inspection.

In order to achieve rapid detection of defects and to increase the industrial operating efficiency of products without compromising their quality attributes, hyperspectral imaging (HSI) and multispectral imaging (MSI), as the technologies that simultaneously provides spectral and spatial information of foodstuffs, are now widely applied for inspecting both raw and processed meat items. This review first discusses the principles of HSI and MSI. Recent developments and applications of HSI and MSI directed at the raw and processed meat industry are then discussed. The advantages and disadvantages of hyperspectral imaging and its future prospects are also covered. This review provides a detailed overview of the recent efforts devoted to HSI and MSI technologies for evaluating the quality and safety of different meat products and the probability of its widespread application. Hyperspectral imaging, as a promising tool in developing rapid and non-invasive, is capable to detect defects in raw and processed meat products.

The potential of hyperspectral imaging with wavelengths of 380 to 1000 nm was used to determine the pH of cooked sausages after different storage conditions (4 °C for 1 d, 35 °C for 1, 3, and 5 d). The mean spectra of the sausages were extracted from the hyperspectral images and partial least squares regression (PLSR) model was developed to relate spectral profiles with the pH of the cooked sausages. Eleven important wavelengths were selected based on the regression coefficient values. The PLSR model established using the optimal wavelengths showed good precision being the prediction coefficient of determination (Rp2) 0.909 and the root mean square error of prediction 0.035. The prediction map for illustrating pH indices in sausages was for the first time developed by R statistics. The overall results suggested that hyperspectral imaging combined with PLSR and R statistics are capable to quantify and visualize the sausages pH evolution under different storage conditions. In this paper, hyperspectral imaging is for the first time used to detect pH in cooked sausages using R statistics, which provides another useful information for the researchers who do not have the access to Matlab. Eleven optimal wavelengths were successfully selected, which were used for simplifying the PLSR model established based on the full wavelengths. This simplified model achieved a high Rp2(0.909) and a low root mean square error of prediction (0.035), which can be useful for the design of multispectral imaging systems.

Redness can greatly influence the freshness of sausages. A precise, rapid and noncontact analytical method or tool is needed to quantify the color. Hyperspectral imaging (HSI) is an emerging technique that integrates spectroscopy and imaging to obtain the spectral and spatial information simultaneously. In the present study, the redness of cooked sausages stored up to 57 days was predicted using HSI in tandem with multivariate data analysis. The mean spectra of the sausages were extracted from the hyperspectral images. Partial least squares regression (PLSR) and forward stepwise multiple regression (FSMR) models were used to develop the relavent spectral profiles with the redness of the cooked sausages.; Results: Ten important wavelengths were selected based on the regression coefficient values from the PLSR model. The PLSR model established using the full wavelengths presented a good performance, with Rc of 0.934 and a root mean square error of calibration of 0.642 (redness ranged between 14.99 and 21.48). The prediction maps for demonstrating evolution of redness in sausages were developed for the first time using R statistics (R Foundation for Statistical Computing) and Matlab (MathWorks Inc., Natick, MA, USA).; Conclusion: HSI combined with PLSR and FSMR can be used to quantify and visualize evolution of sausage redness under different storage days. © 2017 Society of Chemical Industry.; © 2017 Society of Chemical Industry.

Modified atmosphere packaging and controlled atmosphere storage (hypoxia conditions) extend shelf lives of horticultural products by depressing the O2 uptake rate. We investigated the relationship between atmospheres and alternative oxidase (AOX) to cytochrome c oxidase (COX) activities (on the basis of oxygen isotope discrimination) and the relative amounts of two respiratory enzymes, AOX and COX, during the early stage of storage. Broccoli florets, with high O2 uptake rates, were stored under hypoxia and normoxia at 25 °C. O2 uptake rates, weight loss, and yellowing of broccoli florets were significantly lower when stored under hypoxia than when stored under normoxia. Significantly more AOX proteins were produced during storage under normoxia, but COX proteins were more consistent than those of AOX proteins. Hypoxia may depress the expression of AOX and prolong the shelf life. Oxygen isotope discrimination was elevated under hypoxia after 50.5 h. AOX production in broccoli was controlled more by changing atmospheres than by COX.

Summary The effects of a modified casing and chitosan-poly-vinyl alcohol antimicrobial packaging (CP packaging) on sausage colour, texture, microbial spoilage and volatile compounds after 29-days storage were investigated. Casings were modified by surfactant solution (composed of soy lecithin and soy oil) and lactic acid. For samples stored in CP packaging, there were no significant differences between day 1 and day 29 in relation to sausage hardness and springiness (P > 0.05). Redness increased over storage time regardless of treatments and packagings. Total plate counts of samples packaged by CP packaging were lower than 1 log cfu g−1 during 29-days storage. Cyclohexene, 1-methyl-4-(1-methylethylidene)- and α-copaene were found in samples with control casings and CP packaging after 15-days storage. The improved characteristics of the natural casing will enable meat processors or manufactures to enhance sausage production with a low sausage burst incidence, while the CP packaging will inhibit the intensive microbial growth.

Influence of atmosphere and storage period on the physicochemical and biological properties of harvested vegetable soybeans stored for 10 d at 25 °C was investigated. Storing vegetable soybeans under modified atmosphere (low O

Nowadays people tend to include more meat in their diet thanks to the improvement in standards of living as well as an increase in awareness of meat nutritive values. To ensure public health, therefore, there is a need for a rise in worldwide meat production and consumption. Further attention is also required as to how the safety and the quality of meat production process should be assessed. Classical methods of meat quality assessment, however, have some disadvantages; expensive and time-consuming. This study intends to introduce an alternative method known as Computer Vision (CV) for the assessment of various quality parameters of muscle foods. CV has several advantages over the traditional methods. It is non-destructive, easy, and quick, hence, more efficient in meat quality assessments. This study aims to investigate different quality characteristics of some muscle foods using CV. It closes with a discussion on the future challenges and expected opportunities of the practical application of CV in the meat industry.

This chapter discusses the detection of fish freshness, evaluation of physical properties and chemical composition and inspection of microbial spoilage in fish by Hyperspectral imaging (HSI). Fish has been one of the most important components of several and nutritious diets in the world. Its contribution to human health is well documented, being an essential topic for researchers. Compared with traditional methods, HSI is a environmental friendly, toxic-free, noninvasive, time-saving technique. Fillets of cod under different programs of freezing, thawing, and storage were investigated by HSI. The blood in whitefish fillets was detected by HSI with a range of 430–1,000 nm. Significant efforts have been made by the industries to enhance the quality and safety of the aquatic and seafood products by using new technologies such as novel cooling. However, high-quality and safe fish products are also closely related to human health and dietary benefits.

A hyperspectral imaging system in the spectral range of 400-1000 nm was investigated to develop a multispectral real-time imaging system allowing the meat industry to determine moisture content in red meat including beef, lamb, and pork. Multivariate calibration models were developed using partial least-squares regression (PLSR) and least-squares support vector machines (LS-SVM) in the full spectral range. Instead of selection of different sets of feature wavelengths for beef, lamb, and pork, a set of 10 feature wavelengths was selected for convenient industrial application for the determination of moisture content in red meat. A quantitative linear function was then established using MLR based on these key feature wavelengths for predicting moisture content of red meat in an online system and creating moisture distribution maps. The results reveal that the combination of hyperspectral imaging and multivariate has great potential in the meat industry for real-time determination of moisture content.

A hyperspectral imaging system was investigated for determination of feature wavelengths to be used in a design of a multispectral system for real-time monitoring of water holding capacity (WHC) in red meat. Hyperspectral images of different red meat samples were acquired in the spectral range of 400–1000 nm and partial least-squares regression (PLSR) and least square support vector machine (LS-SVM) models were developed. Feature wavelengths were selected using regression coefficients (RCs) and competitive adaptive reweighted sampling (CARS). The best set of feature wavelengths was determined using RCs and the best calibration model obtained was based on RCs-LS-SVM. The model obtained an R2p of 0.93 and RPD of 4.09, indicating that the model is adequate for analytical purposes. An image processing algorithm was developed to transfer this model to each pixel in the image. The results showed that instead of selecting different sets of wavelengths for beef, lamb, and pork, a subset of feature wavelengths can be used for convenient industrial application for the determination of WHC in red meat. The pixel wise visualization of WHC obtained with the aid of image processing was another advantage of using hyperspectral imaging that cannot be obtained with either imaging or conventional spectroscopy.

The main objective of this study was to evaluate the potential of visible near-infrared (VNIR) hyperspectral imaging (400–1000 nm) and machine learning to detect adulteration in fresh minced beef with chicken. Minced beef samples were adulterated with minced chicken in the range 0–50% (w/w) at approximately 2% intervals. Hyperspectral images were acquired in the reflectance (R) mode and then transformed into absorbance (A) and Kubelka–Munck (KM) units. Partial least squares regression (PLSR) models were developed to relate the three spectral profiles with the adulteration levels of the tested samples. These models were then validated using different independent data sets, and obtained the coefficient of determination (R2p) of 0.97, 0.97, and 0.96 with root mean square error in prediction (RMSEP) of 2.62, 2.45, and 3.18% (w/w) for R, A and KM spectra, respectively. To reduce the high dimensionality of the hyperspectral data, some important wavelengths were selected using stepwise regression. PLSR models were again created using these important wavelengths and the best model was then transferred in each pixel in the image to obtain prediction map. The results clearly ascertain that hyperspectral imaging coupled with machine learning can be used to detect, quantify and visualize the amount of chicken adulterant added to the minced beef.

We investigated the potential application of excitation–emission matrix (EEM) spectroscopy in the rapid, non-destructive evaluation of cleanliness in meat processing plants. ATP can be an indicator of microbial contamination. Thus, the fluorescent signal of ATP was detected at Ex = 286 nm and Em = 386 and 412 nm by applying two-dimensional Savitzky–Golay second-order differentiation of EEM obtained from the pork meat surface. The second derivative of the fluorescence intensity at Ex = 284 nm and Em = 412 nm, i.e., the wavelengths assigned to ATP, decreased with the ATP content. The ATP content and plate count were quantified using the second derivatives of EEMs by partial least squares regression in good agreement [coefficient correlation, 0.87; RMSEP, log10 (0.70, mol cm−2) for the predicted ATP content]. The model directly reflected the ATP fluorescent signal changes.

An objective grading method using a Computer Vision System (CVS) for mangoes is proposed. Red peel was selected using two types of color space values at chroma = 22 and hue angle = 52°. Eighteen out of 25 fully-ripened fruits were graded as “excellent,” determined by the share of red area per fruit being in the range of 80% - 100%. In contrast, all green-mature fruits were graded as “fair,” where the share of red area per fruit was - 0.0542x + 7.83), with a correlation coefficient accuracy of 0.94 and root mean square error of 1.31 mg·kg-1. This result may be effective for the visualization of anthocyanin distribution on mango skin. The threshold for red peel can be in the range of 131 - 186 mg·kg-1. This suggests that the pigment concentration is usable as a universal threshold. This value is unaffected by conditions for image acquisition or color measurement (e.g., light source, sensor, filter, and optical geometry), unlike color space values as hue angle.

Nanobubbles (NBs) have been reported to be effective at accelerating the metabolism of living organisms, but the mechanism is not yet well understood. In this study, the production of reactive oxygen species (ROS) by NBs and its effect on seed germinations were investigated. The fluorescence response of APF to NB water was measured. It changed depending on the NB number density which decreased with storage time. This indicated that NBs could produce ROS and the amount of ROS had positive correlation with the NB number density. The fluorescence intensity of APF increases linearly with the concentration of H2O2 in the range of 0–1 mM. Just after the NB generation, the oxidative capacities represented by amount of ROS of oxygen NB water and gas-mixture (air + nitrogen) NB water were estimated to be equivalent to 0.5 and 0.3 mM H2O2 respectively. The seed germination tests were performed in the NB water, distilled water and H2O2 solutions. The germination rate at each observation times of seeds submerged in g...

Freezing clearly damages plant cells and tissues when ice crystals form, and these affect the quality and speed up the deterioration of frozen agricultural products. This study attempted to use a combined method of both xenon hydrate formation and the freezing process (CXF) to lengthen the preservation of barley coleoptile cells, as opposed to using the freezing alone process (FAP). Barley coleoptile cells were used in this study as the sample simulated food, and xenon hydrate formation was encouraged in samples at 1.0 MPa and 1 °C for 0.5, 1, 2, 3, 4 and 5 h, respectively. The results showed that the amount of xenon hydrate in barley coleoptile cells increased with storage time, and that their cellular structure could be destroyed when increasing the amounts of xenon hydrate. Therefore, conditions under a xenon pressure of 1.0 MPa at 1 °C for 1 h were used to control the amounts of implemented xenon hydrate. The process of CXF, including the introduction of xenon gas under a pressure of 1.0 MPa at 1 °C for 1 h frozen to −20 °C, was studied. Typical restricted diffusion phenomenon were determined using a nuclear magnetic resonance method, and it was found that CXF barley coleoptile cells were similar to those of fresh barley. In contrast, the FAP barley coleoptile cells showed unrestricted diffusion phenomenon. The results from X-ray radiographic images also suggested that the CXF process can preserve the shape of barley coleoptile tissues and, additionally, it was found that xenon hydrate formation occurred inside the cells and intercellular spacing of such cells. It can therefore be suggested that the assumed process of xenon hydrate formation in plant cells results in CXF being more effective for the preservation of plant cells and their tissues than the FAP process.

Influence of atmosphere and storage period on the physicochemical and biological properties of harvested vegetable soybeans stored for 10 d at 25 °C was investigated. Storing vegetable soybeans under modified atmosphere (low O2 and high CO2), was more effective in maintaining its green color and mass than storing them under normoxia. Principal component 1 (PC1; contribution rate: 25%) was related to the atmospheres, whereas PC2 (contribution rate: 19%) was related to storage period. Cluster analysis showed that some types of sugars decreased, whereas some types of organic and amino acids increased with deterioration. Alanine, an indicator of low O2 stress, was maintained for 3 d under modified atmospheres, whereas alanine significantly decreased under normoxia. The concentrations of inositol and niacinamide (functional ingredients) under the modified atmospheres were significantly higher than those under normoxia. Thus, storage under modified atmospheres was effective in maintaining freshness and increasing the nutritional content of vegetable soybeans.

Colour evolution for sausage stuffed in casings modified by different concentrations of surfactant solution and slush salt with lactic acid was for the first time investigated during 68 days with 4 °C storage using a hyperspectral imaging system in the range of 380–1000 nm. Pre-treatments (normalization, standard normal variate (SNV), multiplicative scatter correction (MSC), first and second derivative) were conducted and performance after the pre-treatments was improved. No interactive effects between casing treatments and storage days were observed in accordance with two-way ANOVA. Partial least squares regression (PLSR) was developed from spectra with reflectance and absorbance modes and important wavelengths were selected with regard to each colour parameters. When predicted redness (a*), PLSR model derived from absorbance pre-treated by MSC for modified casing with treatment 1 showed the prediction coefficient of determination (Rp2) up to 0.78 while 0.61 for control casing using reflectance. This study innovatively showed a great potential in a cylinder shape sausage for real-time inspection and is competent to quantify and visualise the colour dynamic change of the sausages stuffed in modified casings.

Perforation-mediated modified atmosphere packaging of soft kale (Brassica oleracea L. convar. acephala (DC) Alef. var. sabellica L.) was investigated to maintain freshness at 10 °C for 12 d. Kale was sealed in micro-perforated pouches with different oxygen transmission rates (OTRs: mL m–2 d–1 atm–1) at 1.66 × 106, 3.0 × 103 or 64. Headspace atmospheres (O2/CO2) of pouches at OTR 1.66 × 106, 3.0 × 103 and 64 were 21 %/0 % (normoxia), 1.9∼7.4 %/8.5∼9.6 % (modified atmosphere) and 0 %/> 20 % (hypoxia), respectively. Hue angles (degree of green color) of leaves in the OTR 3.0 × 103 and 64 pouches were significantly higher than that in the OTR 1.66 × 106 pouch. However, carotenoid and ascorbic acid concentrations in the leaf in the OTR 3.0 × 103 pouch was significantly higher than that in the OTR 64 pouch. The modified atmosphere created in the OTR 3.0 × 103 pouch was suitable for maintaining external (green color) and internal (bioactive compounds) qualities of soft kale.

Harvested tomatoes were stored under atmospheres that were normoxic, anoxic, or modified (altered O2 and CO2 concentrations). Each atmosphere was created by storing the tomatoes at 25°C for up to 8 days in different kinds of pouches. During storage, metabolites of the tomatoes were measured using metabolomics. We obtained score plots of the metabolites on eighth day of storage by principal component analysis. There was a tendency for groups to be divided on the basis of score plot according to the composition of each gas. PC1 and PC2 seemed to correspond to the influence of O2 and CO2 concentrations, respectively, and the total contribution rate of the two axes was 72%, so that we concluded that the metabolites were affected mainly by O2 and CO2 concentrations. The results indicate that metabolomics may be an effective tool to reveal the relationship between metabolic state of harvested fruits and the atmosphere.

A simultaneous evaluation of various quality attributes of packaged bratwurst using hyperspectral imaging (HSI) was developed. Changes in physicochemical (L*, a*, b* color values, pH and thiobarbituric acid (TBA)), microbiological (total viable counts (TVC) and lactic acid bacteria (LAB)) and sensory (color, odor and overall acceptability) characteristics of the packaged sausages were monitored during storage at 4 ± 1 °C. Reflectance spectra covering a wavelength range of 400–1000 nm of the samples were acquired using HSI. The relationships between the quality attributes and the spectroscopic reflectance were investigated using canonical correlation analysis. Among all quality attributes, L* color value, TBA, TVC, LAB, odor and overall acceptability appeared to be highly associated with the reflectance. To facilitate the HSI for rapid image acquisition and data processing, partial least squares regression (PLSR) analysis was employed for selection of optimal wavelengths. The selected wavelengths were then assembled into multispectral data and used as input variables to optimize the PLSR and artificial neural network models for the prediction of quality attributes of the sausage samples. The HSI technique can be used for rapid and nondestructive evaluation of the product's quality and shelf life.

This study proposed the use of nuclear magnetic resonance (NMR) technique based on proton spin–spin relaxation time (T2) of water to indicate freezing damage in frozen fruit and vegetable. T2 value can be used to indicate water content in the cells of samples. The results showed that T2 values of frozen-thawed samples were lower than those of fresh (undamaged) samples. This is because of the cell membrane damage due to the formation of ice crystals, leading to leakage of water. The microstructural changes of frozen-thawed barley coleoptile tissue and apple parenchyma tissue were evident when observed using a high-resolution three-dimensional X-ray microscope and an optical microscope, respectively. Changes in the T2 value could be related directly to the microstructural changes of barley coleoptile tissue and apple parenchyma tissue. T2 value can be measured in far less time than conventional methods and is considered a rapid and effective method to indicate freezing damage in frozen foods. Practical Applications Freezing damage (e.g., cell shrinkage, membrane damage and loss of water holding capacity) caused by ice crystal formation affects the quality of frozen food products after thawing. This study proposed an alternative nuclear magnetic resonance (NMR) technique based on proton spin–spin relaxation time (T2) of water to indicate freezing damage in frozen fruit and vegetable. NMR measurement of T2 value can be performed in far less time than conventional freezing damage measurements (e.g., electrical conductivity and microscopy) and thus can be used as a rapid and reliable technique for determination of water in food samples and subsequently can be used to indicate freezing damage caused by ice crystal formation.

This research aimed to develop a rapid, non-destructive, and accurate method based on hyperspectral imaging (HSI) for monitoring spoilage fungal growth on stored brown rice. Brown rice was inoculated with a non-pathogenic strain of Aspergillus oryzae and stored at 30 °C and 85% RH. Growth of A. oryzae on rice was monitored using viable colony counts, expressed as colony forming units per gram (CFU/g). The fungal development was observed using scanning electron microscopy. The HSI system was used to acquire reflectance images of the samples covering the visible and near-infrared (NIR) wavelength range of 400-1000 nm. Unsupervised self-organizing map (SOM) was used to visualize data classification of different levels of fungal infection. Partial least squares (PLS) regression was used to predict fungal growth on rice grains from the HSI reflectance spectra. The HSI spectral signals decreased with increasing colony counts, while conserving similar spectral pattern during the fungal growth. When integrated with SOM, the proposed HSI method could be used to classify rice samples with different levels of fungal infection without sample manipulation. Moreover, HSI was able to rapidly identify infected rice although the samples showed no symptoms of fungal infection. Based on PLS regression, the coefficient of determination was 0.97 and root mean square error of prediction was 0.39 log (CFU/g), demonstrating that the HSI technique was effective for prediction of fungal infection in rice grains. The ability of HSI to detect fungal infection at early stage would help to prevent contaminated rice grains from entering the food chain. This research provides scientific information on the rapid, non-destructive, and effective fungal detection system for rice grains.

For the first time, a visible near-infrared (Vis-NIR) hyperspectral imaging system (400–1000 nm) was investigated for rapid and non-destructive detection of adulteration in minced beef meat. Minced beef meat samples were adulterated with horsemeat at levels ranging from 2 to 50 % (w/w), at approximately 2 % increments. Calibration model was developed and optimized using partial least-squares regression (PLSR) with internal full cross-validation and then validated by external validation using an independent validation set. Several spectral pre-treatment techniques including derivatives, standard normal variate (SNV), and multiplicative scatter correction (MSC) were applied to examine the influence of spectral variations for predicting adulteration in minced beef. The established PLSR models based on raw spectra had coefficients of determination (R2) of 0.99, 0.99, and 0.98, and standard errors of 1.14, 1.56, and 2.23 % for calibration, cross-validation, and prediction, respectively. Four important wavelengths (515, 595, 650, and 880 nm) were selected using regression coefficients resulting from the best PLSR model. By using these important wavelengths, an image processing algorithm was developed to predict the adulteration level in each pixel in whole surface of the samples. The results demonstrate that hyperspectral imaging coupled with multivariate analysis can be successfully applied as a rapid screening technique for adulterate detection in minced meat.

) and 0.73 (RMSECV 0.98%), respectively, using partial least squares regression (PLSR) models. The proposed nondestructive method may be effective for evaluating internal and external qualities of mangoes simultaneously.

The requirement of real-time monitoring of food products has encouraged the development of non-destructive measurement systems. Hyperspectral imaging is a rapid, reagentless, non-destructive analytical technique that integrates traditional spectroscopic and imaging techniques into one system to attain both spectral and spatial information from an object that cannot be achieved with either digital imaging or conventional spectroscopic techniques. Recently, this technique has emerged as one of the most powerful and inspiring techniques for assessing different meat species and building chemical images to show the distribution maps of constituents in a direct and easy manner. After presenting a brief description of the fundamentals of hyperspectral imaging, this paper reviews the potential applications of hyperspectral imaging for detecting the adulteration, contamination, and authenticity of meat, poultry, and fish. These applications envisage that hyperspectral imaging can be considered as a promising non-invasive analytical technique for predicting the contamination, adulteration, and authenticity of meat, poultry, and fish in a real-time mode.

Pork adulteration in minced beef was detected for the first time using a hyperspectral imaging (HIS) technique. Minced beef samples were adulterated with minced pork in the range of 2–50% (w/w) at approximately 2% intervals. Images were acquired using a visible near-infrared hyperspectral imaging (VNIR-HSI) system and their spectral data were extracted. Several data pre-treatments and different linear multivariate analyses, namely partial least squares regression (PLSR), principal component regression (PCR), and multiple linear regression (MLR), were investigated to determine the predictive ability of VNIR-HSI in detecting pork meat adulteration in minced beef. PLSR had a better performance than PCR for predicting pork adulteration in minced beef. Only four wavelengths centered at 430, 605, 665, and 705 nm were selected as the important wavelengths to build the MLR model for visualizing the distribution of adulteration. The results confirm that HSI can be used to provide a rapid, low cost, and nondestructive testing technique for detection of adulteration in minced meat.

Freezing usually causes cell and tissue damage in frozen fruits. This study attempted to use a combined method of xenon hydrate formation and freezing (CXF) for the preservation of apple parenchyma tissue and to compare it with the freezing alone process (FAP). CXF included two steps. The first step was to initiate a certain amount of xenon hydrate by introducing the apple parenchyma tissue to the xenon gas at 1.0 MPa and 1 °C for 0, 1, 2, 3, 4, 5, 6 and 7 d. It was found that the amount of xenon hydrate in apple parenchyma tissue increased with storage time and 2 d was optimum to obtain the certain amount of xenon hydrate. In the second step, the sample with optimum xenon hydrate formation was frozen at − 20 °C. The results showed that CXF was more effective in maintaining firmness, turgor pressure, and cell membrane integrity of the apple parenchyma tissue than FAP. A typical restricted diffusion phenomenon which indicates that water molecules are maintained in the apple parenchyma cells was found in the CXF samples, while the FAP samples showed an unrestricted diffusion phenomenon. In addition, firmness, turgor pressure, cell membrane integrity, and restricted diffusion phenomenon of the CXF samples were similar to those of the fresh samples. The CXF could preserve the apple parenchyma tissue because of the bulk water inside the cells and the water surrounding the cells which transformed to ice crystals is limited. Thus, cell and tissue damage due to the formation of ice crystals was reduced. The obtained results indicated that the CXF is effective for the preservation of the apple parenchyma tissue. Industrial relevance There has been an attempt to improve the quality of frozen fruit by using innovative techniques, in opposition to simply freezing. This present work proposed xenon hydrate formation for the reduction of bulk water before freezing in order to reduce freezing damage due to a large amount of ice crystal formation. The combined method of xenon hydrate formation and freezing has been proved to be able to reduce cell membrane damage usually occurring in frozen fruit. Thus this new technique has potential to be used for improving the quality of frozen fruit. The xenon hydrate formation is considered as an innovative technique for the preservation of fruit, which is expected to be useful for the frozen food industry.