Effect of visual marbling on sensory properties and quality traits of pork loin

Pork loins (N = 53) were selected from a commercial packing plant to determine the influence of subjective marbling score on sensory attributes and eating quality properties. The pork loins were obtained from commercially raised hybrid barrows (average carcass weight = 67.7 kg), originating from nine cooperating herds, and fed similar diets throughout the finishing period. Carcass quality measurements, trained sensory panel analyses, fatty acid composition, thiobarbituric acid-reactive substance (TBARS) index, and cholesterol content were assessed and analyzed on the individual pork loins. With an increase in marbling level, there was a corresponding decrease in drip loss (P = 0.049) and observed increases in pH (P = 0.001), sensory tenderness (P = 0.001), and sensory juiciness scores (P = 0.017). The most notable results demonstrated that protein concentrations were reduced as marbling levels amplified (P = 0.012). The increase in marbling score was observed to be a significant source of variation in polyunsaturated fatty acid (PUFA) concentrations. Linoleic and arachidonic acids decreased in both raw and cooked samples as marbling score increased. The data demonstrated that visual marbling score does have an influence on sensory properties and pork quality.     

Rapid determination of pork sensory quality using Raman spectroscopy

Existing objective methods to predict sensory attributes of pork in general do not yield satisfactory correlation to panel evaluations, and their applications in meat industry are limited. In this study, a Raman spectroscopic method was developed to evaluate and predict tenderness, juiciness and chewiness of fresh, uncooked pork loins from 169 pigs. Partial Least Square Regression models were developed based on Raman spectroscopic characteristics of the pork loins to predict the values of the sensory attributes. Furthermore, binary barcodes were created based on spectroscopic characteristics of the pork loins, and subjected to multivariate statistical discriminant analysis (i.e., Support Vector Machine) to differentiate and classify pork loins into quality grades ("good" and "bad" in terms of tenderness and chewiness). Good agreement (>83% correct predictions) with sensory panel results was obtained. The method developed in this report has the potential to become a rapid objective assay for tenderness and chewiness of pork products that may find practical applications in pork industry.     

On-line prediction of fresh pork quality using visible/near-infrared reflectance spectroscopy

Visible/near-infrared (Vis/NIR) spectroscopy was tested to predict the quality attributes of fresh pork (content of intramuscular fat, protein and water, pH and shear force value) on-line. Vis/NIR spectra (350–1100 nm) were obtained from 211 samples using a prototype. Partial least-squares regression (PLSR) models were developed by external validation with wavelet de-noising and several pre-processing methods. The 6th order Daubechies wavelet with 6 decomposition levels (db6–6) showed high de-noising ability with good information preservation. The first derivative of db6–6 de-noised spectra combined with multiplicative scatter correction yielded the prediction models with the highest coefficient of determination (R²) for all traits in both calibration and validation periods, which were all above 0.757 except for the prediction of shear force value. The results indicate that Vis/NIR spectroscopy is a promising technique to roughly predict the quality attributes of intact fresh pork on-line.     

Simultaneous determination of tenderness and Escherichia coli contamination of pork using hyperspectral scattering technique

A rapid nondestructive method based on hyperspectral scattering technique for simultaneous determination of pork tenderness and Escherichia coli (E. coli) contamination was studied in the research. The hyperspectral scattering images of thirty-one pork samples were collected in 400-1100 nm, and the scattering profiles were then fitted by Lorentzian distribution function to give three parameters a (asymptotic value), b (peak value) and c (full width at b/2). The combined parameters of (b-a), (b-a) × c, (b-a)/c and “a&b&c” were used to develop multi-linear regression (MLR) models for prediction of pork tenderness and E. coli contamination. It was shown that MLR models developed using parameters a, b, (b-a) and (b-a)/c can give high correlation coefficients of 0.831, 0.860, 0.856 and 0.930 respectively for pork tenderness prediction. For E. coli contamination of pork, MLR models based on parameters a and “a&b&c” can give high R_CV of 0.877 and 0.841 respectively.     

蒸发光散射检测器和示差检测器应用于食品中三氯蔗糖测定的比较

目的比较高效液相色谱示差检测法和高效液相色谱法蒸发光散射检测法检测多种食品中三氯蔗糖含量的分析方法。方法样品经甲醇溶液提取后,除蛋白、脂肪后,经亲脂性二乙烯苯和亲水性N-乙烯基吡咯烷酮固相萃取小柱净化,富集后采用高效液相色谱仪进行检测。仪器条件如下:示差检测器:等度洗脱,检测池温度35℃;灵敏度:16;蒸发光散射检测器:梯度洗脱,雾化器温度:30℃;雾化器压力:1 psi;蒸发室温度:80℃;增益:1; N_2流量:1.0 L/min。结果三氯蔗糖在5、10和50 mg/kg添加水平的示差检测器回收率的结果为84.3%～99.6%,相对标准偏差小于6.9%(n=6);蒸发光散射检测器:回收率的结果为85.6%～98.9%,相对标准偏差小于8.1%(n=6);方法检出限为2 mg/kg,定量限为5 mg/kg。结论 2种方法均可有效检出食品中的三氯蔗糖,蒸发光散射检测器采用双对数线性回归。     

The influence of pork quality traits and muscle fiber characteristics on the eating quality of pork from various breeds

The purpose of this study was to compare parameters associated with pork quality, muscle fiber, and eating quality among various breeds, and to examine if differences in eating quality were associated to pork quality and muscle fiber characteristics. For carcass and pork quality, although there were significant differences among breeds, the values of parameters in all pigs were assigned a normal quality class, a likely outcome of the similarity in the area percentage of type I and IIB fibers. For eating quality, pork loins from Berkshire pigs were more tender and full of pork flavor than Landrace and Yorkshire pigs. Except juiciness and mouth coating, over 20% of the variability in the eating quality parameters can be explained by pork quality traits and muscle fiber characteristics using multiple regression analysis. Furthermore, differences in muscle pH_24 h, cooking loss, shear force, and NPPC marbling score could explain a large proportion of variation in eating quality parameters associated with the texture of pork.     

Predicting intramuscular fat content and marbling score of pork along the longissimus muscle based on the last rib

The possibility of using IMF content/MS at the last rib to predict the corresponding fat attribute of loin chops at the 2nd last to the 7th last thoracic ribs and the mean of IMF content/MS of the whole loin joint was investigated. Linear and quadratic regression, cross‐validation analysis and analysis of variance were employed for the study. For either IMF or MS, linear and quadratic regression models had similar performance. The best mean correlation coefficients of calibration (R_c) of 0.91 and cross‐validation (R_v) of 0.88 were obtained for linear regression model of IMF content of the whole loin, while R_c of 0.90 and R_v of 0.88 were obtained for quadratic regression model of MS of the whole loin. The results indicated that IMF content and MS at the last rib had great potential for the prediction of IMF content and MS at the other ribs.     

Prediction of lean meat content in pork carcasses using the Hennessy Grading Probe and the Fat-O-Meater in Argentina

Rapid evolution of pork production in Argentina requires new calibrations for predicting carcass lean meat percentage with the Fat-O-Meater (FOM) and Hennessy Grading Probe (HGP), first adopted in 1995. The second objective was to unify the lean percentage units with those applied by the European Union. Carcasses of 59 gilts and 56 barrows from different environments and breeds were tested. Carcass weights were from 65 to 117kg, and lean content was from 38% to 62%. Predicting lean content by multiple regression equations, the coefficients of determination R(2) were 0.801 and 0.794 for the FOM and HGP equations, and the residual standard deviations (RSD) were 2.40% and 2.45%, respectively. Both instruments had the same precision and were accurate enough to be adopted in national carcass grading classification. Hot carcass weight was not selected as a significant variable. The same prediction equations could be used for gilts and barrows. Quadratic terms did not improve predictions.     

Rapid identification of pork for halal authentication using the electronic nose and gas chromatography mass spectrometer with headspace analyzer

The volatile compounds of pork, other meats and meat products were studied using an electronic nose and gas chromatography mass spectrometer with headspace analyzer (GCMS-HS) for halal verification. The zNose™ was successfully employed for identification and differentiation of pork and pork sausages from beef, mutton and chicken meats and sausages which were achieved using a visual odor pattern called VaporPrint™, derived from the frequency of the surface acoustic wave (SAW) detector of the electronic nose. GCMS-HS was employed to separate and analyze the headspace gasses from samples into peaks corresponding to individual compounds for the purpose of identification. Principal component analysis (PCA) was applied for data interpretation. Analysis by PCA was able to cluster and discriminate pork from other types of meats and sausages. It was shown that PCA could provide a good separation of the samples with 67% of the total variance accounted by PC1.     

Monitoring of warmed-over flavour in pork using the electronic nose - correlation to sensory attributes and secondary lipid oxidation products

Sensory analysis of meatballs was carried out to monitor the warmed-over flavour (WOF) development in cooked, cold-stored (at 4 °C for 0, 2 and 4 days) and reheated meatballs derived from M. longissimus dorsi (LD) and M. semimembranosus (SM) of pigs fed a standard diet supplemented with either 3% of rapeseed oil or 3% of palm oil. This was performed in combination with measurement of volatile compounds using a solid-state-based gas sensor array system (electronic nose) and gas chromatography/mass spectrometry together with measurement of thiobarbitoric acid reactive substances (TBARS). Subsequently, to elucidate the relations and predictability between the obtained data, the gas sensor responses were correlated with chemical (volatile and non-volatile secondary lipid oxidation products) and sensory data (flavour and odour attributes), using partial least squares regression modelling (PLSR). The TBARS, hexanal, pentanal, pentanol and nonanal all correlated to the sensory attributes associated to WOF formation. Moreover, the responses from eight of the MOS (metal oxide semiconductor) sensors within the electronic nose proved to be significantly related to WOF characteristics detected by both sensory and chemical analysis, while six of the MOSFET (metal oxide semiconductor field effect transistor) sensors were related to freshly cooked meat attributes determined by sensory analysis. The obtained results show the potential of the present gas sensor technology to monitor WOF formation in pork.     

高效液相色谱串联二级管阵列检测器和荧光检测器测定金属包装彩印面3种光引发剂迁移量的不确定度评定

目的评定高效液相色谱串联二级管阵列检测器和荧光检测器(high performance liquid chromatographydiode array detector-fluorescence detector,HPLC-DAD-FLD)测定金属包装彩印面3种光引发剂迁移量的不确定度。方法依据JJF 1059.1-2012《测量不确定度评定与表示》,对光引发剂迁移量测定过程中的不确定度来源进行分析和量化评定。结果本研究测得的某金属包装彩印面中光引发剂的迁移量分别为二苯甲酮(benzophenone,BP)为(0.3211±0.0226)mg/L(k=2)、4-甲基二苯甲酮(4-methyl benzophenone,4-MBP)为(0.3210±0.0244)mg/L(k=2)和2-异丙基硫杂蒽酮(2-isopropyl thioxanthone,2-ITX)为(0.0377±0.0067)mg/L(k=2)。不确定度主要来源于标准曲线拟合、标准物质称量和样本估计总体。结论本研究可为HPLC-DAD-FLD法测定金属包装彩印面中3种光引发剂迁移量的测量准确性提供参考。     

Simultaneous determination of nine lignans using pressurized liquid extraction and HPLC-DAD in the fruits of Schisandra chinensis

The pressurized liquid extraction and HPLC-DAD was developed for extraction and determination of bioactive lignans in Schisandra chinensis. The efficient PLE conditions employed methanol as extraction solvent, 125 °C of extraction temperature, 5 min of static extraction time and only one cycle. A rapid HPLC-DAD method was described for simultaneous determination of nine lignans, including schisandrol A, gomisin J, schisandrol B, tigloylgomisin H, angeloylgomisin H, schisandrin A, γ-schisandrin, gomisin N and schisandrin C. The extraction efficiency of PLE was observed to be comparable with reflux and sonication. In addition, the contents of nine lignans in S. chinensis from different regions were analysed by PLE and HPLC-DAD method.