Explore the vast range of titles available.

Marbling characteristics are important traits for the genetic improvement of pork quality. Accurate marbling segmentation is the prerequisite for the quantification of these traits. However, the marbling targets are small and thin with dissimilar sizes and shapes and scattered in pork, complicating the segmentation task. Here, we proposed a deep learning-based pipeline, a shallow context encoder network (Marbling-Net) with the usage of patch-based training strategy and image up-sampling to accurately segment marbling regions from images of pork longissimus dorsi (LD) collected by smartphones. A total of 173 images of pork LD were acquired from different pigs and released as a pixel-wise annotation marbling dataset, the pork marbling dataset 2023 (PMD2023). The proposed pipeline achieved an IoU of 76.8%, a precision of 87.8%, a recall of 86.0%, and an F1-score of 86.9% on PMD2023, outperforming the state-of-art counterparts. The marbling ratios in 100 images of pork LD are highly correlated with marbling scores and intramuscular fat content measured by the spectrometer method (R2 = 0.884 and 0.733, respectively), demonstrating the reliability of our method. The trained model could be deployed in mobile platforms to accurately quantify pork marbling characteristics, benefiting the pork quality breeding and meat industry.

Tenderness, juiciness, and flavor have been associated with consumer acceptance of beef, lamb, and pork. Drivers of consumer liking are interrelated across these species, but there are differences in consumer preferences. Animal age, animal diet, and subsequent marbling impact consumer liking across species. For beef, consumer research prior to the 1990s showed that tenderness was the main driver of liking. Consumer tenderness and juiciness liking are highly correlated. More recent research has shown that as overall tenderness improved and tenderness variation decreased, flavor has become a more important driver of beef consumer liking. Flavor is affected by consumer preparation methods, familiarity with different flavor presentations, and animal production systems. Animal diet impacts consumer perception of beef tenderness and flavor, especially when comparing forage-fed versus grain-fed beef. Flavor preferences vary across countries more so than preferences for beef based on consumer tenderness preferences and are most likely influenced by the consumption of locally produced beef and the flavor-derived type of beef traditionally consumed. Drivers of pork consumer liking have been shown to be affected by pH, color, water holding capacity, animal diet, and the presence of boar taint compounds. While tenderness and juiciness continue to be drivers of consumer liking for pork, flavor, as impacted by animal diet and the presence of boar taint compounds, continues to be a driver for consumer liking. For lamb, the flavor, as affected by diet, and animal age continue to be the main drivers of consumer liking. Lamb consumers vary across countries based on the level of consumption and preferences for flavor based on cultural effects and production practices.

Fat metabolism and intramuscular fat (IMF) are qualitative traits in pigs whose development are influenced by several genes and metabolic pathways. Nutrigenetics and nutrigenomics offer prospects in estimating nutrients required by a pig. Application of these emerging fields in nutritional science provides an opportunity for matching nutrients based on the genetic make-up of the pig for trait improvements. Today, integration of high throughput “omics” technologies into nutritional genomic research has revealed many quantitative trait loci (QTLs) and single nucleotide polymorphisms (SNPs) for the mutation(s) of key genes directly or indirectly involved in fat metabolism and IMF deposition in pigs. Nutrient–gene interaction and the underlying molecular mechanisms involved in fatty acid synthesis and marbling in pigs is difficult to unravel. While existing knowledge on QTLs and SNPs of genes related to fat metabolism and IMF development is yet to be harmonized, the scientific explanations behind the nature of the existing correlation between the nutrients, the genes and the environment remain unclear, being inconclusive or lacking precision. This paper aimed to: (1) discuss nutrigenetics, nutrigenomics and epigenetic mechanisms controlling fat metabolism and IMF accretion in pigs; (2) highlight the potentials of these concepts in pig nutritional programming and research.

This study assessed the effects of season on health, behaviour, physiological stress parameters, and carcass and meat quality in a total of 480 slaughter pigs. The following health indicators were recorded: pneumonia, pleurisy, milk spots, and pericarditis. Behaviour was monitored during unloading (slipping, falling, turning back, reluctance to move, panting, shivering) and lairaging (panting, shivering, huddling). Blood lactate and glucose concentrations were determined at exsanguination. Performance indices (live weight, daily weight gain), carcass (carcass weight, backfat and loin thickness, lean meat content, carcass lesion score), and meat quality (pH, temperature, drip, thawing and cooking losses, colour, marbling) traits were measured postmortem. Pigs slaughtered in winter had the highest live weight, carcass weight, loin thickness, and carcass lesion score, while the lowest live weight, carcass weight, and backfat thickness were recorded in pigs slaughtered in summer. The highest lactate and glucose concentrations were recorded in pigs slaughtered in summer. The highest prevalence of red, soft, and exudative meat was recorded in pigs slaughtered in winter. Pigs slaughtered in summer had the lowest pH, the highest thawing loss, L* value, b* value, and occurrence of pale, soft, and exudative meat. Pigs slaughtered in autumn had the lowest drip loss, cooking loss, L* value, b* value, and the greatest percentage of red, firm, and nonexudative meat. In conclusion, the summer and winter temperatures compromised health and welfare and reduced carcass and meat quality in slaughter pigs, indicating that protection against heat and cold stress is not yet effective.

The present study aimed to investigate the impacts of dietary standardized ileal digestible lysine to net energy (SID Lys:NE) ratio on lipid metabolism in pigs fed high-wheat diets. Thirty-six crossbred growing barrows (65.20 ± 0.38 kg) were blocked into two treatment groups, fed high-wheat diets with either a high SID Lys:NE ratio (HR) or a low SID Lys:NE ratio (LR). Each treatment group consisted of three replicates, with six pigs per pen in each replicate. The diminishing dietary SID Lys:NE ratio exhibited no adverse impacts on the carcass trait (p > 0.05) but increased the marbling score of the longissimus dorsi muscle (p < 0.05). Meanwhile, LR diets tended to increase the serum triglyceride concentration (p < 0.1). LR diets upregulated fatty acid transport protein 4 and acetyl-coA carboxylase α expression levels and downregulated the expression level of adipose triglyceride lipase (p < 0.05). LR diets improved energy metabolism via decreasing the expression levels of AMP-activated protein kinase (AMPK) α1, sirtuin 1 (SIRT1), and peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α) (p < 0.05). Additionally, LR diets stimulated hepatic bile acid synthesis via upregulating the expression levels of cytochrome P450 family 7 subfamily A member 1 and cytochrome P450 family 27 subfamily A member 1, and downregulating farnesol X receptor (FXR) and small heterodimer partner (SHP) expression levels (p < 0.05). A lowered SID Lys:NE ratio affected the colonic microbial composition, characterized by increased relative abundances of YRC22, Parabacteroides, Sphaerochaeta, and Bacteroides, alongside a decreased in the proportion of Roseburia, f_Lachnospiraceae_g_Clostridium, Enterococcus, Shuttleworthia, Exiguobacterium, Corynebacterium, Subdoligranulum, Sulfurospirillum, and Marinobacter (p < 0.05). The alterations in microbial composition were accompanied by a decrease in colonic butyrate concentration (p < 0.1). The metabolomic analysis revealed that LR diets affected primary bile acid synthesis and AMPK signaling pathway (p < 0.05). And the mantel analysis indicated that Parabacteroides, Sphaerochaeta, f_Lachnospiraceae_g_Clostridium, Shuttleworthia, and Marinobacter contributed to the alterations in body metabolism. A reduced dietary SID Lys:NE ratio improves energy metabolism, stimulates lipogenesis, and inhibits lipolysis in finishing pigs by regulating the AMPKα/SIRT1/PGC-1α pathway and the FXR/SHP pathway. Parabacteroides and Sphaerochaeta benefited bile acids synthesis, whereas f_Lachnospiraceae_g_Clostridium, Shuttleworthia, and Marinobacter may contribute to the activation of the AMPK signaling pathway. Overall, body metabolism and colonic microbiota collectively controlled the lipid metabolism in finishing pigs.

Abstract The objective was to determine the amount and variability of intramuscular fat (IMF) in a pork loin attributable to anatomical chop location, sex, and sire line. Pigs were sired by commercially available terminal Duroc boars selected for meat quality (MQ; n = 96) or lean growth (LG; n = 96) and equally split between barrows and gilts. After slaughter and fabrication, bone-in chops were removed from four locations of each left-side loin (A = 6th rib, B = 10th rib, C = last rib, and D = 4th lumbar vertebrae). An adjacent pair of chops from each location was collected and evaluated for visual color and marbling, subjective firmness, moisture and extractable lipid (IMF) (anterior chop), and Warner–Bratzler shear force (posterior chop). Data were analyzed using the MIXED procedure of SAS as a split-plot design. Homogeneity of variances was tested on raw data using Levene’s test of the GLM procedure and found to be heterogeneous. Thus, a two-variance model was fit using the REPEATED statement of the MIXED procedure, grouped by pig. The mivque(0) option of the VARCOMP procedure was used to calculate the proportion of variability that each factor contributed to the total variance. Barrows (3.64%) produced chops with greater (P < 0.01) IMF content than gilts (3.20%), and barrows (2.14) had greater (P < 0.01) IMF variability than gilts (1.23). Chops from MQ pigs (4.02%) exhibited greater (P < 0.01) IMF content than LG (2.82%), and MQ (1.76) had greater IMF variability (P < 0.01) than LG pigs (0.97). Chops from locations A (3.80%) and D (3.77%) had greater IMF than B (3.34%; P < 0.01), and A, B, and D had greater IMF than C (2.77%; P < 0.01). Variances of IMF also differed (A = 1.44, B = 1.59, C = 1.05, and D = 2.18; P = 0.01) across chop locations. Of the variability in IMF, 33.0% was attributed to sire line, 10.16% to chop location, and 4.01% to sex, with 52.83% not accounted for by these three factors. Location A chops were the most (P < 0.01) tender (2.57 kg) and C chops the least (P < 0.01) tender (2.93 kg), while B and D chops were intermediate and not different from each other. No differences in variability (P = 0.40) of tenderness were observed among chop locations (A = 0.31, kg B = 0.24 kg, C = 0.24 kg, and D = 0.23 kg). These results demonstrated that variability in tenderness values did not reflect the variability of IMF. In conclusion, chop location, sex, and sire line all contribute to the amount and variability of pork loin marbling.

[...]the role of flavor in the acceptability of muscles from primals other than the rib or loin is not entirely clear. [...]consumer acceptance of and preference for flavor potentially shifts when dealing with value-added or processed meats as opposed to fresh meats. Australian and Asian consumers differed in their perception of ‘premiumness’ of meat products, which could be related to the traditional meat preparation and presentation styles between those groups of consumers. [...]demographic factors, specifically age, influenced eating quality and willingness to pay for sheepmeat and beef. [...]Miller [12] reviewed the drivers of consumer liking for beef, pork, and lamb, suggesting the drivers are interrelated across species, but differences exist. In summary, the Special Issue “Consumer Preferences and Acceptance of Meat Products” demonstrates that the value of different palatability traits has evolved over time. [...]consumer acceptance and preference are not solely determined by the inputs of the meat itself, but can also be influenced by various demographic factors.

Background With increasing health awareness among consumers, the demand for healthier, tastier, higher quality and nutritional value pork is increasing. It has been shown that different dietary starch sources can alter the carcass traits and meat quality. However, research on the effects of different starch sources with clear different amylose/amylopectin ratio on the amino acid and fatty acid composition in Longissimus thoracis ( L . thoracis ) muscle of pigs is limited. This study aimed to investigate the effects of different dietary starch sources on carcass traits, meat quality, muscle amino acid and fatty acid composition, and the mRNA expression levels of genes involved in lipid metabolism and muscle fiber characteristics in finishing pigs. A total of 72 Duroc × Landrace × Large White barrows were randomly allocated to 3 different dietary treatment groups with 8 replicate pens/group and 3 pigs per pen. Tapioca starch (TS), corn starch (CS), and pea starch (PS), with amylose/amylopectin ratio of 0.11, 0.25, and 0.44, respectively, were used as their dietary starch sources for 40 days. Results Results showed that the PS diet significantly increased ( P  < 0.05) the final body weight, average daily gain, loin-eye area, and fat-free lean index compared with the TS diet, but significantly decreased ( P  < 0.05) the feed to gain ratio and backfat thickness. Compared with the TS diet, PS diet also increased ( P  < 0.05) the pH 45 min , marbling scores, the content of intramuscular fat and inosine monophosphate in the L . thoracis , and decreased ( P  < 0.05) the drip loss and shear force. In addition, compared with the TS diet, PS diet increased ( P  < 0.05) the proportions of flavor amino acids, DHA, EPA, and n-3 polyunsaturated fatty acid (PUFA) in the L . thoracis compared with TS diet, but decreased ( P  < 0.05) the ratio of n-6/n-3 PUFA. Furthermore, compared with the TS diet, PS diet also upregulated ( P  < 0.05) the lipogenic genes ( FAS , LPL , SCD , ACCα ) and myosin heavy-chain ( MyHC )- IIa mRNA expression levels compared with the TS diet, but downregulated ( P  < 0.05) the CPT1B and MyHC-IIb mRNA levels. Conclusions In conclusion, these results provided compelling evidence that the different dietary starch source altered the carcass traits, meat flavor and quality in finishing pigs, and consumption of a diet with higher amylose/amylopectin ratio results in the production of a healthy, higher quality, and nutritional value pork.

Background Pork quality can directly affect customer purchase tendency and meat quality traits have become valuable in modern pork production. However, genetic improvement has been slow due to high phenotyping costs. In this study, whole genome sequence (WGS) data was used to evaluate the prediction accuracy of genomic best linear unbiased prediction (GBLUP) for meat quality in large-scale crossbred commercial pigs. Results We produced WGS data (18,695,907 SNPs and 2,106,902 INDELs exceed quality control) from 1,469 sequenced Duroc × (Landrace × Yorkshire) pigs and developed a reference panel for meat quality including meat color score, marbling score, L* (lightness), a* (redness), and b* (yellowness) of genomic prediction. The prediction accuracy was defined as the Pearson correlation coefficient between adjusted phenotypes and genomic estimated breeding values in the validation population. Using different marker density panels derived from WGS data, accuracy differed substantially among meat quality traits, varied from 0.08 to 0.47. Results showed that MultiBLUP outperform GBLUP and yielded accuracy increases ranging from 17.39% to 75%. We optimized the marker density and found medium- and high-density marker panels are beneficial for the estimation of heritability for meat quality. Moreover, we conducted genotype imputation from 50K chip to WGS level in the same population and found average concordance rate to exceed 95% and r 2 = 0.81. Conclusions Overall, estimation of heritability for meat quality traits can benefit from the use of WGS data. This study showed the superiority of using WGS data to genetically improve pork quality in genomic prediction.