Green hams electrical impedance spectroscopy (EIS) measures and pastiness prediction of dry cured hams

Explainable Feature Engineering for Multi-Modal Tissue State Monitoring Based on Impedance Spectroscopy

One of the most promising approaches to food quality assessments is the use of impedance spectroscopy combined with machine learning. Thereby, feature selection is decisive for a high classification accuracy. Physically based features have particularly significant advantages because they are able to consider prior knowledge and to concentrate the data into pertinent understandable information, building a solid basis for classification. In this study, we aim to identify physically based measurable features for muscle type and freshness classifications of bovine meat based on impedance spectroscopy measurements. We carry out a combined study where features are ranked based on their F1-score, cumulative feature selection, and t-distributed Stochastic Neighbor Embedding (t-SNE). In terms of features, we analyze the characteristic points (CPs) of the impedance spectrum and the model parameters (MPs) obtained by fitting a physical model to the measurements. The results show that either MPs or CPs alone are sufficient for detecting muscle type. Combining capacitance (C) and extracellular resistance (Rex) or the modulus of the characteristic point Z1 and the phase at the characteristic frequency of the beta dispersion (Phi2) leads to accurate separation. In contrast, the detection of freshness is more challenging. It requires more distinct features. We achieved a 90% freshness separation using the MPs describing intracellular resistance (Rin) and capacitance (C). A 95.5% freshness separation was achieved by considering the phase at the end of the beta dispersion (Phi3) and Rin. Including additional features related to muscle type improves the separability of samples; ultimately, a 99.6% separation can be achieved by selecting the appropriate features.

Quality Control of Jinhua Ham from the Influence between Proteases Activities and Processing Parameters: A Review

Endogenous proteases are significant for Jinhua ham quality. Protein degradation affects the chemical traits, texture and the formation of flavor substances. Protease activities are affected by different process parameters, such as processing temperature, maturation time, salt content and the drying rate. They affect ham quality, which can be controlled by process parameters. The influences of key factors on Jinhua ham quality are briefly summarized, which can provide a theoretical basis for the selection of specific parameters in dry-cured ham processing. Furthermore, some suggestions are proposed for correcting and improving the flavor and textural defects of ham, yet the effectiveness depends on the operating conditions. The determination of enzyme activity is not real-time and unsupervised at the moment. Future research will focus on the determination of the actual endogenous protease activity and the quantitative relationship between the enzyme activity and main processing parameters.

Instrumental texture analysis on the surface of dry-cured ham to define the end of the process

The end of the elaboration process of dry-cured ham is currently decided by product weight loss and/or by an expert who carries out an evaluation of the tactile texture on the surface. The objective of this study was to define the optimal measurement conditions of an instrumental texture analysis on the surface of the dry-cured ham (ITAS), to define the end of process. 120 dry-cured hams were classified by experts into Hard (appropriate) or Soft (non-appropriate) texture groups and used to perform compression tests using different probes on three anatomical positions. Results showed that the small probe in position 2 gave the most discriminant conditions, providing representative information of the internal texture. Although classification using only weight loss was possible with an accuracy rate of 80.4% or 66.7% depending on the weight loss, the maximum classification accuracy was obtained when using ITAS in combination with weight loss. Further studies at industrial level are needed.

Evaluation of fish freshness using impedance spectroscopy based on the characteristic parameter of orthogonal direction difference

BACKGROUND

As a nondestructive testing technology, electrochemical impedance spectroscopy (EIS) has been applied to evaluate food quality because of its features of rapidity, low cost, nondestructiveness and portability. However, fish freshness evaluation based on existing EIS technology is affected by the differences of individual biological samples. In this study, the difference of electrical properties between two orthogonal directions was extracted to develop a new freshness indicator. A real part orthogonal direction difference parameter set (RODDS) was used to establish a prediction model for total volatile basic nitrogen (TVB-N).

RESULTS

Compared with the traditional parameter of EIS, coefficient of determination between RODDS and TVB-N increased from 0.55 to 0.71 for the calibration group, and root mean squared error between predicted and measured values of TVB-N decreased from 5.46 to 3.81 for the test group.

CONCLUSIONS

The results implied that RODDS could effectively offset individual differences in basic electrical properties and improve the TVB-N prediction accuracy in practical application scenarios with samples from multiple origins. The proposed method may provide a new idea for the development and improvement of EIS-based portable testing devices for fish and meat. © 2020 Society of Chemical Industry.

Application of Novel Techniques for Monitoring Quality Changes in Meat and Fish Products during Traditional Processing Processes: Reconciling Novelty and Tradition

In this review, we summarize the most recent advances in monitoring changes induced in fish and other seafood, and meat and meat products, following the application of traditional processing processes by means of conventional and emerging advanced techniques. Selected examples from the literature covering relevant applications of spectroscopic methods (i.e., visible and near infrared (VIS/NIR), mid-infrared (MIR), Raman, nuclear magnetic resonance (NMR), and fluorescence) will be used to illustrate the topics covered in this review. Although a general reluctance toward using and adopting new technologies in traditional production sectors causes a relatively low interest in spectroscopic techniques, the recently published studies have pointed out that these techniques could be a powerful tool for the non-destructive monitoring and process optimization during the production of muscle food products.

Utilization of Bioelectrical Impedance to Predict Intramuscular Fat and Physicochemical Traits of the Beef Longissimus Thoracis et Lumborum Muscle

The bioelectrical impedance analysis (BIA) is a non-destructive technique that has been successfully used to assess the body and carcass composition of farm species. This study aimed to predict intramuscular fat (IMF) and physicochemical traits in the longissimus thoracis et lumborum muscle (LM) of beef, using BIA. These traits were evaluated in LM samples of 52 crossbred heifer carcasses. The BIA was performed in LM, using a 50 Hz frequency high precision impedance converter system. A correlation analysis of the studied variables was performed. Then a stepwise with a k-folds cross validation procedure was used to modelling the prediction of IMF and physicochemical traits from BIA parameters (24.5% ≤ CV ≤ 47.3%). Wide variation was found for IMF and BIA parameters. In general, correlations of BIA parameters with IMF and physicochemical traits were moderate to high and were similar for all BIA parameters (−0.50 ≤ r ≤ 0.50 only for total pigments, a* and pH48). It was possible to predict IMF and physicochemical traits from BIA. The best fit explained 79.3% of the variation in IMF, while for physicochemical traits the best fits were for sarcomere length and shear force (64.4% and 60.5%, respectively). The results confirmed the potential of BIA for objective measurement of meat quality.

Assessing heat treatment of chicken breast cuts by impedance spectroscopy

The aim of this work was to develop a new system based on impedance spectroscopy to assess the heat treatment of previously cooked chicken meat by two experiments; in the first, samples were cooked at different temperatures (from 60 to 90 ℃) until core temperature of the meat reached the water bath temperature. In the second approach, temperature was 80 ℃ and the samples were cooked for different times (from 5 to 55 min). Impedance was measured once samples had cooled. The examined processing parameters were the maximum temperature reached in thermal centre of the samples, weight loss, moisture and the integral of the temperature profile during the cooking–cooling process. The correlation between the processing parameters and impedance was studied by partial least square regressions. The models were able to predict the studied parameters. Our results are essential for developing a new system to control the technological, sensory and safety aspects of cooked meat products on the whole meat processing line.

Innovative nondestructive measurements of water activity and the content of salts in low-salt hake minces

Impedance spectroscopy (IS), low-field proton nuclear magnetic resonance (LF (1)H NMR), chloride titration, ion chromatography, and an ion selective electrode were used to investigate the physicochemical parameters and measure sodium and potassium contents in low-salt brines and fish. Salt solutions (0-3 w/w, %) and model products of minced hake with added NaCl (0.5-3.0 w/w, %), or a mixture of NaCl and KCl (50/50 w/w, %), were analyzed. Good correlation was observed between the sodium content determined by using the ion selective electrode method and ion chromatography (R(2) = 0.97). In both salt solutions and fish minces, the impedance spectroscopy measurements could detect the difference in salt contents in mince with salt contents down to 0.5%. The NMR transversal relaxation time T2 measurements clearly distinguished samples with 0, 0.5, and 1.0-3.0% salt, based on principal component analysis (PCA). Therefore, LF (1)H NMR seems to be a suitable technique for studies of low-salt products.

Meat quality assessment using biophysical methods related to meat structure

This paper overviews the biophysical methods developed to gain access to meat structure information. The meat industry needs reliable meat quality information throughout the production process in order to guarantee high-quality meat products for consumers. Fast and non-invasive sensors will shortly be deployed, based on the development of biophysical methods for assessing meat structure. Reliable meat quality information (tenderness, flavour, juiciness, colour) can be provided by a number of different meat structure assessment either by means of mechanical (i.e., Warner-Bratzler shear force), optical (colour measurements, fluorescence) electrical probing or using ultrasonic measurements, electromagnetic waves, NMR, NIR, and so on. These measurements are often used to construct meat structure images that are fusioned and then processed via multi-image analysis, which needs appropriate processing methods. Quality traits related to mechanical properties are often better assessed by methods that take into account the natural anisotropy of meat due to its relatively linear myofibrillar structure. Biophysical methods of assessment can either measure meat component properties directly, or calculate them indirectly by using obvious correlations between one or several biophysical measurements and meat component properties. Taking these calculations and modelling the main relevant biophysical properties involved can help to improve our understanding of meat properties and thus of eating quality.