Predictive Analysis of Linoleic Acid in Red Meat Employing Advanced Ensemble Models of Bayesian and CNN-Bi-LSTM Decision Layer Fusion Based Hyperspectral Imaging.

Rapid non-destructive testing technologies are effectively used to analyze and evaluate the linoleic acid content while processing fresh meat products. In current study, hyperspectral imaging (HSI) technology was combined with deep learning optimization algorithm to model and analyze the linoleic acid content in 252 mixed red meat samples. A comparative study was conducted by experimenting mixed sample data preprocessing methods and feature wavelength extraction methods depending on the distribution of linoleic acid content. Initially, convolutional neural network Bi-directional long short-term memory (CNN-Bi-LSTM) model was constructed to reduce the loss of the fully connected layer extracted feature information and optimize the prediction effect. In addition, the prediction process of overfitting phenomenon in the CNN-Bi-LSTM model was also targeted. The Bayesian-CNN-Bi-LSTM (Bayes-CNN-Bi-LSTM) model was proposed to improve the linoleic acid prediction in red meat through iterative optimization of Gaussian process acceleration function. Results showed that best preprocessing effect was achieved by using the detrending algorithm, while 11 feature wavelengths extracted by variable combination population analysis (VCPA) method effectively contained characteristic group information of linoleic acid. The Bi-directional LSTM (Bi-LSTM) model combined with the feature extraction data set of VCPA method predicted 0.860 Rp2 value of linoleic acid content in red meat. The CNN-Bi-LSTM model achieved an Rp2 of 0.889, and the optimized Bayes-CNN-Bi-LSTM model was constructed to achieve the best prediction with an Rp2 of 0.909. This study provided a reference for the rapid synchronous detection of mixed sample indicators, and a theoretical basis for the development of hyperspectral on-line detection equipment.

The impact of freezing methods on the quality, moisture distribution, microstructure, and flavor profile of hand-grabbed mutton during long-term frozen storage.

The aim of present study was to investigate the influence of conventional freezing (CF, -18 °C), low-temperaturefreezing (LF, -40 °C), and ultra-low-temperature freezing (ULF, -80 °C) on the quality, moisture distribution, microstructure, and flavor profile of hand-grabbed mutton (HGM) during frozen storage (0, 30, 60, 90, 120, 150 and 180 days). The TPC, TVB-N, and TBARS values increased significantly with prolonged storage, while the moisture content decreased (P < 0.05). Additionally, the concentrations of aldehydes, alcohols, ketones, acids, and alkenes decreased significantly as the storage duration increased. However, the concentrations of esters and heterocyclics increased (P < 0.05). Notably, at 30-180 days of storage, the TBARS and TVB-N values in ULF samples were significantly lower than those in CF and LF samples, while the moisture content was significantly higher (P < 0.05). Low field-nuclear magnetic resonance (LF-NMR) analysis showed that ULF decreased water migration and maintained the original texture characteristics of HGM during frozen storage. The ULF and LF groups had significantly higher levels of volatiles than the CF group (P < 0.05). The findings show that ULF, with its relatively rapid freezing rates, can still maintain the high quality of HGM after 180 days of frozen storage, contributing to quality control.

Dynamic changes in the water distribution and key aroma compounds of roasted chicken during roasting.

The effects of roasting times (0, 2, 4, 6, 8, 10, 12, and 14 min) on the dynamic changes of the water distribution and key aroma compounds in roasted chicken during the electric roasting process were studied. In total, 36 volatile compounds were further determined by GC-MS and 11 compounds, including 1-octen-3-ol, 1-heptanol, hexanal, decanal, (E)-2-octenal, acetic acid hexyl ester, nonanal, 2-pentylfuran, heptanal, (E, E)-2,4-decadienal and octanal, were confirmed as key aroma compounds. The relaxation time of T22 and T23 was increased first and then decreased, while the M22 and M23 in roasted chicken were decreased and increased with increasing roasting time, respectively. The fluidity of the water in the chicken during the roasting process was decreased, and the water with a high degree of freedom migrated to the water with a low degree of freedom. In addition, the L*, a*, b*, M23 and all amino acids were positively correlated with all the key aroma compounds, while T22, M22 and moisture content were negatively correlated with all the key aroma compounds.

Investigation Tracing the Origin of Tan Sheep Visceral Tissues through Mineral Elements.

The traceability of quality mineral fingerprints in the viscera of Tan sheep from northwest China was studied. Twenty-five mineral elements in the heart and liver samples of Tan sheep were determined using an inductively coupled plasma mass spectrometer (ICP-MS), and the characteristics of the mineral elements in the visceral tissues of the Tan sheep were further analyzed in combination with a principal component analysis (PCA), hierarchical cluster analysis (HCA), and linear discriminant analysis (LDA) to establish a discriminant model and verify it. The results show that 11 elements (137Ba, 43Ca, 63Cu, 56Fe, 39K, 31P, 60Ni, 78Se, 118Sn, 125Te, and 66Zn) in the Tan sheep heart samples had significant differences among different regions (p < 0.05), and the results of the LDA show that the accuracy rate of the return-generation examination was 85.70%, and the accuracy rate of the hand-over-fork examination was 87.50%; 10 elements (111Cd, 59Co, 52Cr, 56Fe, 39K, 55Mn, 95Mo, 23Na, 121Sb, and 78Se) in the Tan sheep liver samples had significant differences among different regions (p < 0.05), and the results of the LDA showed that the accuracy rate of the return-generation examination was 96.30%, and the accuracy rate of the hand-over-fork examination was 86.25%. This indicates that the multi-element analysis has potential for determining the origin of Tan sheep viscera in certain regions.

Electrochemical detection of enrofloxacin in meat using bimetallic organic framework-derived NiCo2O4@NiO.

A novel electrochemical aptasensor based on a bimetallic organic frame-derived carbide nanostructure of Co and Ni (NiCo2O4@NiO) was prepared for rapid and sensitive enrofloxacin (ENR) detection of sheep and pork liver meats. The composite was fabricated by solvothermal and direct pyrolysis methods and dropped onto a modified electrode to improve the electron transfer efficiency. Furthermore, different techniques such as scanning electron microscopy and X-ray photoelectron spectroscopy were used to characterize the morphology and structure of the materials. Electrochemical impedance spectroscopy and cyclic voltammetry were used to evaluate the performance of the electrochemical sensor. As a result, the electrochemical aptasensor based on NiCo2O4@NiO exhibited excellent sensing performances for ENR with an extremely low detection limit of 1.67 × 10-2 pg mL-1 and a broad linear range of 5 × 10-2 to 5 × 104 pg mL-1, as well as great selectivity, excellent reproducibility, high stability and applicability. In addition, the relative standard deviation for real samples was in the range of 93.83 to 100.09% and 94.95 to 100.01% for sheep and pork liver. The results showed that the composite can be expected to greatly facilitate ENR detection and practical applications in harmful food due to the advantages of simple fabrication, controllable, large-area uniformity, environmental friendliness, and trace detection.

Combination of hyperspectral imaging and entropy weight method for the comprehensive assessment of antioxidant enzyme activity in Tan mutton.

The antioxidant enzymes play the crucial role in inhibiting mutton spoilage. In this study, visible near-infrared (Vis-NIR) hyperspectral imaging (HSI) combined with entropy weight method (EWM) was developed for the first time to evaluate the antioxidant properties of Tan mutton. The comprehensive index of antioxidant enzymes (AECI) consisting of peroxidase (49.34%), catalase (37.97%) and superoxidase (12.69%) was constructed by the EWM. Partial least squares regression, least squares support vector machine and artificial neural networks (ANN) were developed based on characteristic wavelengths extracted by successful projections algorithm, uninformative variable selection, iteratively retains informative variables (IRIV), regression coefficient and competitive adaptive reweighted sampling (CARS). The textural features (TF) were extracted by the gray level co-occurrence matrix and fused with the spectral data to establish models. Visualization of the changes in antioxidant enzyme activity was constructed from the optimal model. In addition, two-dimensional correlation spectra (2D-COS) with AECI as a perturbation variable was used to identify spectral features, revealing chemical bond changes order under the characteristic peaks at 612-799-473-708-559 nm. The results showed that the IRIV-CARS-TF-ANN model performed the best, with prediction set coefficient of determination (RP2) of 0.8813, which improved 2.12%, 1.11% and 2.77% over the RP2 of full band, IRIV and IRIV-CARS, respectively. It was suggested that fusion data of HSI may effectively predict the activity of antioxidant enzymes in Tan mutton.

A new sensor for the rapid electrochemical detection of ractopamine in meats with high sensitivity.

In this research, g-C3N4/Cu@CoO/NC, which contained graphitic phase carbon nitride (g-C3N4) with a binary nanostructure and Cu@CoO/NC with a bimetallic MOF precursor, was constructed by a low-temperature pyrolysis process. The g-C3N4/Cu@CoO/NC was characterised by several techniques, including X-ray diffraction, scanning electron microscope, transmission electron microscope and X-ray photoelectron spectroscopy. Further, it was used to prepare an electrochemical sensor for the detection of ractopamine (RAC) in meat samples. The sensor showed excellent electrochemical oxidation characteristics for RAC detection, with a wide linear range (0.005 µmol/L to 32.73 µmol/L) and low detection limit (1.53 nmol/L). Meanwhile, the reproducibility, stability and interference of the g-C3N4/Cu@CoO/NC/GCE sensor were found to be excellent. Besides, the g-C3N4/Cu@CoO/NC/GCE sensor was well-used for the detection of RAC in pork, pig liver and lamb samples with recovery rates ranging from 96.5 % to 102.2 %.

Evaluation of key aroma compounds and protein secondary structure in the roasted Tan mutton during the traditional charcoal process.

The traditional charcoal technique was used to determine the changes in the key aroma compounds of Tan mutton during the roasting process. The results showed that the samples at the different roasting time were distinguished using GC-MS in combination with PLS-DA. A total of 26 volatile compounds were identified, among which 14 compounds, including (E)-2-octenal, 1-heptanol, hexanal, 1-hexanol, heptanal, 1-octen-3-ol, 1-pentanol, (E)-2-nonenal, octanal, 2-undecenal, nonanal, pentanal, 2-pentylfuran and 2-methypyrazine, were confirmed as key aroma compounds through the odor activity values (OAV) and aroma recombination experiments. The OAV and contribution rate of the 14 key aroma compounds were maintained at high levels, and nonanal had the highest OAV (322.34) and contribution rate (27.74%) in the samples after roasting for 10 min. The content of α-helix significantly decreased (P < 0.05), while the ß-sheet content significantly increased (P < 0.05) during the roasting process. The content of random coils significantly increased in the samples roasted for 0-8 min (P < 0.05), and then no obvious change was observed. At the same time, ß-turn content had no obvious change. Correlation analysis showed that the 14 key aroma compounds were all positively correlated with the content of α-helix and negatively correlated with the contents of ß-sheet and random coil, and also positively correlated with the content of ß-turn, except hexanal and 2-methypyrazine. The results are helpful to promoting the industrialization of roasted Tan mutton.

Preliminary Investigation on the Relationship between Raman Spectra of Beef and Metmyoglobin and Metmyoglobin Reductase Activity.

A hand-held Raman spectroscopic device was used as a rapid nondestructive testing device to predict the metmyoglobin (MetMb) and metmyoglobin reductase activity (MRA) values on the surface layer of fresh beef. Longissimus dorsi muscles were from 10 young bulls (Holstein-Friesian) from two different cattle farms (group A = 5 and B = 5). The Raman spectra of 100 samples were correlated with the MetMb and MRA values using partial least squares regression (PLSR). Two groups could be discriminated, and the separate correlation models were better than the joint correlation model for the fresh beef. The coefficients of determination are R 2 = 0.81 (group A) and R 2 = 0.87 (group B) for MetMb and R 2 = 0.80 (group A) and R 2 = 0.85 (group B) for MRA. The results show the usefulness of Raman spectra in predicting the inner traits such as MetMb and MRA during meat storage. In conclusion, it is feasible to determine the MetMb and MRA values by Raman spectroscopy. Color is an important indicator of beef freshness and can vary depending on the age, sex, and breed of the cow. They play a very important role in human nutrition. The color of meat is an important indicator of meat freshness, and many researchers are already investigating the causes of color changes. The research was conducted in this environment.

Water distribution and key aroma compounds in the process of beef roasting.

The key aroma compounds and water distribution of the beef at different roasting times (0, 3, 6, 9, 12, 15, and 18 min) were identified and analyzed. The results showed that the L * value increased considerably before peaking and then decreased. On average, a * values decreased significantly first and then kept stable, while b * values increased first and then decreased. A total of 47 odorants were identified in all samples, including 14 alcohols, 18 aldehydes, 6 ketones, 1 ester, 3 acids, 4 heterocyclic compounds, and 1 other compound. Among them, 11 key aroma compounds were selected and aldehydes and alcohols predominantly contributed to the key aroma compounds. The fluidity of the water in the beef during the roasting process was decreased, and the water with a high degree of freedom migrated to the water with a low degree of freedom. The correlation analysis showed that water content and L * were negatively correlated with key aroma compounds of the samples, while M 21 was positively correlated with key aroma compounds.

High freezing rate improves flavor fidelity effect of hand grab mutton after short-term frozen storage.

Taking the eutectic point as the final freezing temperature, the differences of flavor substances of in hand grab mutton (HGM) frozen at three rates of 0. 26 cm/h (-18°C), 0.56 cm/h (-40°C) and 2.00 cm/h (-80°C) were determined and analyzed. The results showed that the flavor of HGM decreased significantly after freezing. With the increase of freezing rate, the contents of aldehydes, alcohols, ketones, acids, esters, others, free amino acids and 5'-nucleotides were higher, and the content of specific substances was also generally increased. All samples from unfrozen and frozen HGM could be divided into four groups using an electronic nose based on different flavor characteristics. Seven common key aroma components were determined by relative odor activity value (ROAV), including hexanal, heptanal, octanal, nonanal, (E)-oct-2-enal, (2E,4E)-deca-2,4-dienal and oct-1-en-3-ol. The higher the freezing rate, the greater the ROAVs. Taste activity values calculated by all taste substances were far <1, and the direct contribution of the substances to the taste of HGM was not significant. The equivalent umami concentration of HGM frozen at -80°C was the highest. These findings indicated that higher freezing rate was more conducive to the retention of flavor substances in HGM, and the flavor fidelity effect of freezing at -80°C was particularly remarkable.

Formation of volatile flavor compounds, maillard reaction products and potentially hazard substance in China stir-frying beef sao zi.

The effects of stir-frying stages on the formation of flavor volatile compounds, Maillard reaction products (MRPs) and potentially hazardous substances with time in stir-fried beef sao zi were investigated. A total of 122 volatile compounds were identified in beef sao zi after stir-frying. Most of the volatile compounds were produced in the stir-frying fat (SFF) process of beef sao zi. Furosine, fluorescence intensity, Nε-(1-Carboxymethyl)-L-lysine (CML), Nε-(1-Carboxyethyl)-L-lysine (CEL) polyaromatic hydrocarbons (PAHs), heterocyclic aromatic amines (HAAs) and acrylamides (AA) are mainly presented in stir-fried beef sao zi. The furosine peaked at MSF 120 s as the Maillard reaction progressed. The fluorescent compound gradually increased with time during the stir-frying process. The CML and CEL peaked at MSF 120 s. AA reached its maximum in MSF 90 s and then decreased. The quantities and content of HAAs and PAHs were increased by prolonging the stir-frying time, but ended up far lower than the maximum permissible value specified by the Commission of the European Communities. The extended stir-frying promoted MRPs and some hazardous substances, but the content of potentially hazardous substances was still within the safety range for stir-frying beef sao zi.

Effect of Traditional Stir-Frying on the Characteristics and Quality of Mutton Sao Zi.

The effects of stir-frying stage and time on the formation of Maillard reaction products (MRP) and potentially hazardous substances with time in stir-fried mutton sao zi were investigated. Furosine, fluorescence intensity, Nε-(1-carboxymethyl)-L-lysine (CML), Nε-(1-carboxyethyl)-L-lysine (CEL), polyaromatic hydrocarbons PAHs), heterocyclic aromatic amines (HAAs), and acrylamides (AA) mainly presented were of stir-fried mutton sao zi. The furosine decreased after mixed stir-frying (MSF) 160 s due to its degradation as the Maillard reaction (MR) progressed. The fluorescent compound gradually increased with time during the stir-frying process. The CML and CEL peaked in MSF at 200 s. AA reached its maximum at MSF 120 s and then decreased. All the 5 HAAs were detected after MSF 200 s, suggesting that stir-frying mutton sao zi was at its best before MSF for 200 s. When stir-frying exceeded the optimal processing time of (MSF 160 s) 200 s, the benzo[a]pyrene peaked at 0.82 µg/kg, far lower than the maximum permissible value specified by the Commission of the European Communities. Extended stir-frying promoted MRP and some hazardous substances, but the content of potentially hazardous substances was still within the safety range for food.

Proteomics and metabolomics combined study on endopathic changes of water-soluble precursors in Tan lamb during postmortem aging.

Tan lamb is highly recommended breed in China. It is of great significance to understand the underlying mechanism of how water-soluble flavor precursors metabolize in Tan lamb muscles during the postmortem aging period. In this study, we investigated the muscle pH, lactate dehydrogenase (LDH) activity, and the variations in water-soluble flavor-related metabolites. The proteome changes were profiled to provide insights into the biochemical changes affecting accumulation of water-soluble flavor precursors in different aging stages (days 0, 4, and 8). The results indicated that pH value considerably decreased from day 0 to day 4, and increased from day 4 to day 8 (p < .05). The activity of LDH significantly increased from day 0 to day 4, and decreased from day 4 to day 8 (p < .05). Postmortem glycolysis was activated in 4 days, which directly affected the variations in metabolic enzymes and triggered the accumulation of flavor-related carbohydrates. The free amino acids accumulated due to hydrolysis of structural proteins, with 3-hydroxy-L-proline, aspartic acid, and methionine increasing from day 0 to day 4, and aspartic acid, serine, threonine, tyrosine, phenylalanine, and D-phenylalanine from day 4 to day 8. The inosine and hypoxanthine accumulated due to the degradation of ATP. The results of the present study provide insightful information, revealing the differences in biochemical attributes in Tan lamb muscles caused by postmortem aging.

Biological function, mediate cell death pathway and their potential regulated mechanisms for post-mortem muscle tenderization of PARP1: A review.

Tenderness is a key attribute of meat quality that affects consumers' willingness to purchase meat. Changes in the physiological environment of skeletal muscles following slaughter can disrupt the balance of redox homeostasis and may lead to cell death. Excessive accumulation of reactive oxygen species (ROS) in the myocytes causes DNA damage and activates poly ADP-ribose polymerase 1 (PARP1), which is involved in different intracellular metabolic pathways and is known to affect muscle tenderness during post-slaughter maturation. There is an urgent requirement to summarize the related research findings. Thus, this paper reviews the current research on the protein structure of PARP1 and its metabolism and activation, outlines the mechanisms underlying the function of PARP1 in regulating muscle tenderness through cysteine protease 3 (Caspase-3), oxidative stress, heat shock proteins (HSPs), and energy metabolism. In addition, we describe the mechanisms of PARP1 in apoptosis and necrosis pathways to provide a theoretical reference for enhancing the mature technology of post-mortem muscle tenderization.

Characterization of flavor volatile compounds in industrial stir-frying mutton sao zi by GC-MS, E-nose, and physicochemical analysis.

This study aims to investigate the flavor changes of industrial stir-frying mutton sao zi, a mutton product popular in the northwest of China, at different stir-frying stages. Electronic nose (E-nose) was used to recognize mutton sao zi odors at different processing time points, and the individual volatile compounds were further identified by the solid-phase microextraction (SPME) combined with gas chromatography-mass spectrometry (GC-MS). A total of 105 volatile compounds were detected by GC-MS, of which 51 were major volatile compounds. Additionally, GC-MS and E-nose data of the samples were also correlated with the fatty acids, crude composition (moisture, fat, protein), and amino acids. The stir-frying time and temperature may be the critical contributors to different flavors of industrial stir-frying mutton sao zi. The signal intensities of W1S, W1W, W2S, W2W, and W3S sensors positively correlate with protein, fat, and 18 amino acids, but negatively with SFA and moisture. Hence, this study explored the flavor changes of industrial stir-frying mutton sao zi by E-nose and SPME-GC-MS for the first time, providing an insight into the industrial production and flavor control stir-frying machine of stir-frying mutton products with household flavor.

A Low-Cost End-to-End sEMG-Based Gait Sub-Phase Recognition System.

As surface electromyogram (sEMG) signals have the ability to detect human movement intention, they are commonly used to be control inputs. However, gait sub-phase classification typically requires monotonous manual labeling process, and commercial sEMG acquisition devices are quite bulky and expensive, thus current sEMG-based gait sub-phase recognition systems are complex and have poor portability. This study presents a low-cost but effective end-to-end sEMG-based gait sub-phase recognition system, which contains a wireless multi-channel signal acquisition device simultaneously collecting sEMG of thigh muscles and plantar pressure signals, and a novel neural network-based sEMG signal classifier combining long-short term memory (LSTM) with multilayer perceptron (MLP). We evaluated the system with subjects walking under five conditions: flat terrain at 5 km/h, flat terrain at 3 km/h, 20 kg backpack at 5 km/h, 20 kg shoulder bag at 5 km/h and 15° slope at 5 km/h. Experimental results show that the proposed method achieved average classification accuracies of 94.10%, 87.25%, 90.71%, 94.02%, and 87.87%, respectively, which were significantly higher than existing recognition methods. Additionally, the proposed system had a good real-time performance with low average inference time in the range of 3.25 ~ 3.31 ms.

Preparation of 17ß-estradiol-imprinted material by surface-initiated atom transfer radical polymerization and its application.

A novel 17ß-estradiol molecularly imprinted polymer was grafted onto the surface of initiator-immobilized silica by surface-initiated atom transfer radical polymerization. The resulting molecularly imprinted polymer was characterized by elemental analysis and thermogravimetric analysis. The binding property of molecularly imprinted polymer for 17ß-estradiol was also studied with both static and dynamic methods. The results showed that the molecularly imprinted polymer possessed excellent recognition capacity for 17ß-estradiol (180.65 mg/g at 298 K), and also exhibited outstanding selectivity for 17ß-estradiol over the other competitive compounds (such as testosterone and progesterone). Then, the determination of trace 17ß-estradiol in beef samples was successfully developed by using molecularly imprinted polymer solid-phase extraction coupled with high-performance liquid chromatography. The limit of detection was 0.25 ng/mL, and the amount of 17ß-estradiol in beef samples was detected at 2.83 ng/g. This work proposed a sensitive, rapid, reliable, and convenient approach for the determination of trace 17ß-estradiol in complicated beef samples.

A robust boosting regression tree with applications in quantitative structure-activity relationship studies of organic compounds.

A regression tree (RT) was extensively utilized in quantitative structure-activity relationship studies (QSAR), due to its inherently promising attributes. The issues of instability and inclination to overfitting and suboptima, however, often occur in RT. In the present study, a robust version of boosting was invoked to simultaneously improve the stability and generalization ability of RT, forming a new method called robust boosting regression tree (RBRT). RBRT works by sequentially employing the RT method to model the robustly reweighted versions of the original training set and then aggregating these resultant predictors via weighted median. The designed RBRT was applied to predict the bioactivities of flavoniod derivatives and the anti-HIV activities of HIV-1 inhibitors, compared with boosting RT (BRT) and RT. The results of these two data sets demonstrated that the introduction of robust boosting drastically enhances the stability and generalization ability of RT, and RBRT is superior to BRT in QSAR studies.