Use of Magnetic Resonance Imaging for monitoring Parma dry-cured ham processing

Modelling of salt uptake for salt content standardization in dry-cured ham

Salt content standardization in dry-cured ham production is complex as there are many factors that influence salt uptake. The aim of this work was to study and model salt uptake as a function of salting time and the characteristics of green ham in two different ham types using a large amount of data obtained from an inline non-invasive characterization technology. The usefulness of these models to standardize the salt content of the industrial production was also evaluated. Magnetic induction technology was used to characterize lean and fatty hams in order to further model the salt uptake using different statistical methods. Salt content increased with the salting time showing an asymptotic behaviour which was lower in fatty hams. The best models were those that considered the salting time, weight, and fat content of hams as model independent variables. These models are helpful for salt content standardization within the industry and can be used to simulate process modifications and avoid the time-consuming and costly trial and error tests.

Computed tomography and predictive microbiology for non-invasive evaluation of the impact of dry-cured ham production process conditions on the behaviour of Listeria monocytogenes and Clostridium botulinum

Variability of salt content in dry-cured ham production can pose microbiological food safety issues, especially in salt reduced and/or non-nitrified products. In this regard, computed tomography (CT) could help to non-invasively characterised the product to further adjust the production process and ensure its safety. The aim of this work was to study the application of CT to estimate a_w in dry-cured ham to be used by predictive microbiology to evaluate the impact of the production process on the behaviour of Listeria monocytogenes and Clostridium botulinum. Effect of nitrite elimination and fat content of hams was also evaluated. Thirty hams with two different fat content levels were characterised analytically and using CT at different key points in the process. The safety of the process was evaluated by applying predictive microbiology using both analytical and CT data as model inputs. Results showed that nitrite and fat content had an impact on the predicted growth potential of the pathogens evaluated. After the resting period, if no nitrite is added, the time needed for 1 log increase (t_inc) of L. monocytogenes would shorten by 26% and 22% in lean and fat hams, respectively. After week 12, important differences on t_inc values for C. botulinum were found between both groups of hams (ca. 40% shorter in fat hams). CT can provide reliable pixel-to-pixel information for predictive microbiology to evaluate the growth of relevant pathogens, but further studies are needed to validate this combination as a tool to evaluate the safety of the production process.

Formation of Zn-protoporphyrin during the elaboration process of non-nitrified serrano dry-cured hams and its relationship with lipolysis

This study assessed the ZnPP content, heme content, salt content, and instrumental color in the biceps femoris and semimembranosus muscles during the elaboration of Serrano dry-cured ham manufactured without the addition of nitrate and nitrite for 15 months. The effects of lipolysis and lipid oxidation on the content of Zn-protoporphyrin were also investigated in the biceps femoris. We found that the maximum formation of Zn-protoporphyrin occurred between end of resting and 6 months of processing, which coincides with temperature increase during processing and the end of salt equalization. Zn-protoporphyrin further increased in the biceps femoris until 9 months of processing but remained unchanged in the semimembranosus. Free fatty acid content increased till 6 months and then remained unchanged until the end of the process. These findings and those from an in vitro study reinforced the idea that the release of free fatty acids can promote the activity of the endogenous enzyme ferrochelatase and contribute to the formation of Zn-protoporphyrin from heme. However, the content of Zn-protoporphyrin decreased at the end of the processing, which may be due to the progression of lipid oxidation.

Optimization of the image acquisition procedure in low-field MRI for non-destructive analysis of loin using predictive models

The use of low-field magnetic resonance imaging (LF-MRI) scanners has increased in recent years. The low economic cost in comparison to high-field (HF-MRI) scanners and the ease of maintenance make this type of scanner the best choice for nonmedical purposes. However, LF-MRI scanners produce low-quality images, which encourages the identification of optimization procedures to generate the best possible images. In this paper, optimization of the image acquisition procedure for an LF-MRI scanner is presented, and predictive models are developed. The MRI acquisition procedure was optimized to determine the physicochemical characteristics of pork loin in a nondestructive way using MRI, feature extraction algorithms and data processing methods. The most critical parameters (relaxation times, repetition time, and echo time) of the LF-MRI scanner were optimized, presenting a procedure that could be easily reproduced in other environments or for other purposes. In addition, two feature extraction algorithms (gray level co-occurrence matrix (GLCM) and one point fractal texture algorithm (OPFTA)) were evaluated. The optimization procedure was validated by using several evaluation metrics, achieving reliable and accurate results (r > 0.85; weighted absolute percentage error (WAPE) lower than 0.1%; root mean square error of prediction (RMSEP) lower than 0.1%; true standard deviation (TSTD) lower than 2; and mean absolute error (MAE) lower than 2). These results support the high degree of feasibility and accuracy of the optimized procedure of LF-MRI acquisition. No other papers present a procedure to optimize the image acquisition process in LF-MRI. Eventually, the optimization procedure could be applied to other LF-MRI systems.

Ultrasonic characterization of salt, moisture and texture modifications in dry-cured ham during post-salting

For the first time, this study addresses the use of non-destructive ultrasound to monitor ham post-salting. For that purpose, the ultrasonic velocity (1 MHz) and the weight loss of hams were measured regularly every 2 days up to 8 weeks after salting. Additionally, for different post-salting times, internal salt and moisture content and hardness were measured at different locations from the ham surface. The experimental results reflected that the ultrasonic velocity increased as the ham weight decreased (26.1 m/s per kg), showing a satisfactory correlation between both variables (r = 0.95). The ultrasonic velocity was also correlated with the salt and moisture content. However, ham hardness remained fairly constant during post-salting, which confirmed that characteristic textural changes mainly occur during the salting and drying-maturation stages. Thus, the ultrasonic velocity could be a reliable parameter with which to monitor not only overall modifications in ham weight, but also internal changes of moisture and salt content during post-salting in a non-destructive way.

Use of MRI as a predictive tool for physicochemical and rheologycal features during cured ham manufacturing

Magnetic resonance imaging (MRI) was used to study the structural changes during dry-cured ham manufacturing. T₁, T₂ and apparent diffusion coefficient (ADC) were determined. Dry cured hams were analysed at different steps of the manufacturing process (raw, salted, post salted, half-cured and cured). Structural changes were linked with the rheological behaviour, estimated by texture profile analysis (TPA) performed in three different muscles of hams (semimembranosus, semitendinosus and biceps femoris). A decrease for T₁, T₂ and ADC parameters during the curing process was observed, connected to the dehydration kinetics and salt diffusion. Curing process increased hardness and chewiness and reduced elasticity and cohesiveness. Mathematical models were defined to obtain useful equations to monitor ripening. Multiple and simple linear regression models were performed to predict water and salt content and rheological features evolution through MRI parameters. Best settings were achieved with water and salt content for the three studied muscles (R² around 0.90). T₁, T₂ and ADC showed a negative correlation with hardness and a positive relation with springiness and cohesiveness.

Effect of Cooking Conditions on Quality Characteristics of Confit Cod: Prediction by MRI

This study evaluates the effect of low temperature (60, 64 and 68 °C) and different times (15 and 20 min) of cooking on physicochemical and sensory characteristics of confit cod and analyzes confit cod in a non-destructive way by means of magnetic resonance imaging (MRI) and computer vision techniques. Higher scores for acceptability and flavor in 60 °C–20 min and 64 °C–20 min samples and some physicochemical differences were found. These results allow distinguishing four groups of confit cods as a function of cooking conditions – 60 °C–15 min/68 °C–15 min/68 °C–20 min/60 °C–20 min, 64 °C–15 min, 64 °C–20 min – and proposing to cook confit cod at 60–64 °C during 20 min. Prediction by means of computational texture features from MRI gave moderate-to-good correlation (0.6–0.75) for six quality attributes and very good-to-excellent relationship (0.75–1) for other six. Thus, computational texture features seem to be appropriate to determine the quality attributes of confit cod in a non-destructive way.

Non-destructive analysis of sensory traits of dry-cured loins by MRI-computer vision techniques and data mining

BACKGROUND

Magnetic resonance imaging (MRI) combined with computer vision techniques have been proposed as an alternative or complementary technique to determine the quality parameters of food in a non-destructive way. The aim of this work was to analyze the sensory attributes of dry-cured loins using this technique. For that, different MRI acquisition sequences (spin echo, gradient echo and turbo 3D), algorithms for MRI analysis (GLCM, NGLDM, GLRLM and GLCM-NGLDM-GLRLM) and predictive data mining techniques (multiple linear regression and isotonic regression) were tested.

RESULTS

The correlation coefficient (R) and mean absolute error (MAE) were used to validate the prediction results. The combination of spin echo, GLCM and isotonic regression produced the most accurate results. In addition, the MRI data from dry-cured loins seems to be more suitable than the data from fresh loins.

CONCLUSIONS

The application of predictive data mining techniques on computational texture features from the MRI data of loins enables the determination of the sensory traits of dry-cured loins in a non-destructive way. © 2016 Society of Chemical Industry.

Prediction of pork quality parameters by applying fractals and data mining on MRI

This work firstly investigates the use of MRI, fractal algorithms and data mining techniques to determine pork quality parameters non-destructively. The main objective was to evaluate the capability of fractal algorithms (Classical Fractal algorithm, CFA; Fractal Texture Algorithm, FTA and One Point Fractal Texture Algorithm, OPFTA) to analyse MRI in order to predict quality parameters of loin. In addition, the effect of the sequence acquisition of MRI (Gradient echo, GE; Spin echo, SE and Turbo 3D, T3D) and the predictive technique of data mining (Isotonic regression, IR and Multiple linear regression, MLR) were analysed. Both fractal algorithm, FTA and OPFTA are appropriate to analyse MRI of loins. The sequence acquisition, the fractal algorithm and the data mining technique seems to influence on the prediction results. For most physico-chemical parameters, prediction equations with moderate to excellent correlation coefficients were achieved by using the following combinations of acquisition sequences of MRI, fractal algorithms and data mining techniques: SE-FTA-MLR, SE-OPFTA-IR, GE-OPFTA-MLR, SE-OPFTA-MLR, with the last one offering the best prediction results. Thus, SE-OPFTA-MLR could be proposed as an alternative technique to determine physico-chemical traits of fresh and dry-cured loins in a non-destructive way with high accuracy.

Dry-cured ham tissue characterization by fast field cycling NMR relaxometry and quantitative magnetization transfer

Fast field cycling (FFC) and quantitative magnetization transfer (qMT) NMR methods are two powerful tools in NMR analysis of biological tissues. The qMT method is well established in biomedical NMR applications, while the FFC method is often used in investigations of molecular dynamics on which longitudinal NMR relaxation times of the investigated material critically depend. Despite their proven analytical potential, these two methods were rarely used in NMR studies of food, especially when combined together. In our study, we demonstrate the feasibility of a combined FFC/qMT-NMR approach for the fast and nondestructive characterization of dry-curing ham tissues differing by protein content. The characterization is based on quantifying the pure quadrupolar peak area (area under the quadrupolar contribution of dispersion curve obtained by FFC-NMR) and the restricted magnetization pool size (obtained by qMT-NMR). Both quantities correlate well with concentration of partially immobilized, nitrogen-containing and proton magnetization exchanging muscle proteins. Therefore, these two quantities could serve as potential markers for dry-curing process monitoring. Copyright © 2016 John Wiley & Sons, Ltd.

Application of quantitative magnetization transfer magnetic resonance imaging for characterization of dry-cured hams

Quantitative magnetization transfer magnetic resonance imaging (qMT-MRI) was employed to characterize dry-cured ham tissues differing in anatomical positions and processing protocols. Experimentally obtained MR images of dry-cured ham sections were analyzed by the well-established binary-spin-bath (BSB) model. The model enabled an efficient discrimination between a free-water proton pool and a restricted-macromolecular proton pool. Significant differences in restricted pool sizes were found among different ham sections. Values of the restricted pool size obtained by the model were in a good agreement with chemically determined protein content. The study confirmed the feasibility of the applied qMT-MRI as a nondestructive tool for characterization of dry-cured ham tissues.

Use of multiparametric magnetic resonance microscopy for discrimination among different processing protocols and anatomical positions of Slovenian dry-cured hams

A novel multiparametric magnetic resonance microscopy (MRM) approach was applied to the Slovenian Kraški pršut dry-cured ham samples in order to evaluate its potential for discrimination among biceps femoris and semimembranosus muscle from two hams, differing in processing (salting duration) and thus in water and salt content. The approach is based on apparent diffusion coefficient (ADC) mapping as well as on longitudinal (T1) and transversal (T2) nuclear magnetic resonance relaxation time mapping. Three-dimensional maps were acquired and analyzed by one dimensional (1D) ADC, T1, and T2 distributions as well as by paired two-dimensional ADC-T1, ADC-T2 and T1-T2 distributions. The discriminating potential of the applied MRM approach was confirmed by differences among both 1D and 2D distributions of different ham samples. In addition, distribution peak positions highly correlated with the conventionally determined moisture content.

Effect of processing time on the quality of dry-cured ham obtained from a native pig breed (Chato Murciano)

The compositional and sensory parameters of Chato Murciano dry-cured ham at different ripening times (14, 18, 22 and 24 months of processing) were studied. A sensory consumer study of dry-cured ham with a short ripening stage (14 months of processing) and a similar ham with a long ripening stage (22 months of processing) was carried out. Dry-cured hams remained in the ripening stage at 18−20°C and 70–75% relative humidity. The different processing times studied had no effect on the ash, intramuscular fat, sodium chloride and protein contents of the final ham, but significantly affected the moisture (P < 0.05) and saturated (P < 0.01) and monounsaturated (P < 0.05) fatty acid contents. Sensory analysis showed that processing time enhanced redness, fat colour, all of the odour and flavour traits studied, and all the texture traits except juiciness. In the taste profile, only saltiness showed a significant increase. However, sensory changes were only significant up to 22 months of processing (for most of the parameters), the resulting ham showing higher level of consumer preference and acceptability than dry-cured ham with the shorter ripening. Based on these results, it is recommended that an appropriate processing time to obtain a high-quality Chato Murciano dry-cured ham is 22 months.

Monitoring dry-curing of S. Daniele ham by magnetic resonance imaging

S. Daniele hams were collected at different stages during dry-curing and submitted to magnetic resonance imaging (MRI) according to the acquisition Spin-Echo sequences T1 and T2. The intensity of the MR signals in the images of the Semimembranosus, Semitendinosus, Rectus femoris and Biceps femoris muscles of the hams was computed and expressed in grey levels. Muscles were also submitted to traditional analyses, including aw, soluble solids, sodium chloride, total and water soluble nitrogen. T1 and T2 MR signals well described the evolution of the phenomena occurring in the different muscles during dry-curing. MR signal acquired in T2 mode well correlated with traditional indicators in Semitendinosus, Rectus femoris and Biceps femoris muscles. Predictive models estimating the value of aw, moisture, salt content and proteolysis extent on the basis of the MR signal intensity were proposed.