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Genetic parameters were estimated for objective and subjective traits assessed after 3 and 29 days aging in meat samples of 1154 commercial beef cattle. Meat attributes [Warner-Bratzler shear force (WBSF), intramuscular fat (IMF), and pH] and sensory traits [flavor intensity (FI), off-flavor (OF), connective tissue (CT), overall tenderness (OT), sustained juiciness (SJ), and overall palatability (OP)] were available. The animal mixed model used included additive genetic and residual effects as random effects, contemporary group as fixed effect and genomic breed composition and slaughter age as covariates. Genetic parameters were estimated using airemlf90 software and single-step genomic BLUP. Heritability estimates for OT (3 and 29 d), OP (3 d) and OF (29 d) were of moderate magnitude ranging from 0.18 ± 0.07 to 0.31 ± 0.07. Heritabilities were negligible or of low magnitude for all other sensory traits with values ranging from 0.03 ± 0.05 to 0.14 ± 0.07. Among objectively measured traits, the estimate of heritability for meat pH was moderate at day 3 (0.20 ± 0.08) and negligible at 29 (0.00 ± 0.05). For IMF and WBSF the heritability estimates were 0.43 ± 0.09 and 0.54 ± 0.09, and 0.22 ± 0.07 and 0.19 ± 0.07 for day 3 and 29, respectively. Genetic correlations between days for each sensory trait tended to be of high and positive magnitude ranging from 0.54 ± 0.60 to 0.99 ± 0.28. Genetic and phenotypic correlations of subjectively assessed traits were consistent in direction and magnitude with WBSF (negative) and IMF (positive) suggesting that genetic selection based on objectively measured traits can be used for meat quality improvement and to increase consumer satisfaction. In addition, selection can be implemented using sensory traits collected after 3 days of aging., Competing Interests: Declaration of Competing Interest All authors declare no conflicts of interest related to this study, and there has been no significant financial support for this work that could have influenced its outcome., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Methane emission is not included in the current breeding goals for dairy cattle mainly due to the expense and difficulty in obtaining sufficient data to generate accurate estimates of the relevant traits. While several models have been developed to predict methane emission from milk spectra using reference methane data obtained by the respiration chamber, SF6 and sniffer methods, the prediction of methane emission from milk mid-infrared (MIR) spectra using reference methane data collected by the GreenFeed system has not yet been explored. Methane emission was monitored for 151 cows using the GreenFeed system. Prediction models were developed for daily and average (for the trial period of 12 or 14 days) methane production (g/d), yield (g/kg DM intake (DMI)) and intensity (g/kg of fat- and protein-corrected milk) using partial least squares regression. The predictions were evaluated in 100 repeated validation cycles, where animals were randomly partitioned into training (80%) and testing (20%) populations for each cycle. The best performing model was observed for average methane intensity using MIR, parity and DMI with validation coefficient of determination (R 2 ) and RMSE of prediction of 0.66 and 4.7 g/kg of fat- and protein-corrected milk, respectively. The accuracy of the best models for average methane production and average methane yield were poor (R val ) and RMSE of prediction of 0.66 and 4.7 g/kg of fat- and protein-corrected milk, respectively. The accuracy of the best models for average methane production and average methane yield were poor (R 2 val  = 0.28 and 0.12, respectively). A lower accuracy of prediction was observed for methane intensity and production (R 2 val  = 0.42 and 0.17) when daily records were used while prediction for methane yield was comparable to that for average methane yield (R 2 val  = 0.16). Our results suggest the potential to predict methane intensity with moderate accuracy. In this case, prediction models for average methane values were generally better than for daily measures when using the GreenFeed system to obtain reference methane emission measurements., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

The objective of this study was to compare the economic performance of an ear tag automated activity monitor system (AAM) versus a timed-AI (TAI) protocol in Holstein heifers. In total, 340 heifers were enrolled onto the study at 13.5 mo of age and randomly assigned to receive either an AAM (n = 170) or TAI (n = 170) protocol before breeding eligibility (D 0). Heifers in the AAM group were fitted with an ear tag AAM and bred based on high activity alert from the system. Heifers in the TAI group received a progesterone releasing intravaginal device on D -8, followed by device removal and prostaglandin on D -3 and gonadotropin-releasing hormone with TAI on D 0. In both treatments, the majority of heifers received sex-sorted semen for the first AI and conventional semen for subsequent AIs, with three opportunities to become pregnant. All heifers were diagnosed for pregnancy approximately 25 d post AI using transrectal ultrasonography, with confirmation at 30 and 45 d. Non-pregnant heifers in the TAI group, were resynchronized using the same TAI protocol. A partial budget was used to compare the costs and benefits of switching from a TAI to an AAM protocol in heifers, including protocol, labour, and rearing costs for each treatment, as well as estimated calf and milk value. Sensitivity analyses were also conducted to determine the effect of pregnancy per AI (P/AI), outsourcing AI, AAM tag cost and herd size on the net outcome. There was no difference in overall P/AI or days to pregnancy between treatments. However, number of AI was greater in the TAI than the AAM group. For the first AI, the P/AI was less in the TAI compared to the AAM group; however, the interval to first AI was less in TAI. There was minimal difference in performance for the second and third AI. There was a net gain of $11.97 per heifer when switching from a TAI to AAM protocol, due to the increased P/AI to the first AI and reduced cost of hormones. Several variables in the sensitivity analyses affected the net outcome. Considering only the first AI, switching to an AAM collar and a larger herd size all increased the net gain. Considering a greater P/AI to the first AI in the TAI group, outsourcing AI, using more AAM ear tags, and smaller herd sizes resulted in a net loss when switching from TAI to AAM. The AAM system resulted in exceptional P/AI and may be an economically viable alternative to improve heifer reproductive efficiency in herds with suboptimal P/AI to TAI., (Crown Copyright © 2021. Published by Elsevier Inc. All rights reserved.)

The objectives of this study were to evaluate the performance of the SCR eSense ear tag automated activity monitor (AAM) to detect estrus behavior in Holstein heifers and to determine the optimal time from estrus alert to artificial insemination (AI) using sex-sorted or conventional semen. In total, 281 heifers were fitted with the AAM once eligible for breeding (>13.5 m of age). For the first AI, estrus was synchronized using 500 μg of cloprostenol (PGF), given 14 d apart, and heifers were given estrus detection patches (Estrotect™) after the second PGF. Heifers were inseminated at randomly attributed times after high activity alert from the AAM system or if the estrus patch had ≥ 50% colour change. Most heifers received sex-sorted semen for the first AI and conventional semen for subsequent inseminations. Pregnancy diagnosis was performed at 30 d post AI and heifers had four opportunities to become pregnant. In a subset of heifers (n = 149), ovaries were scanned every 12 h from the time of AI until ovulation (OV). The system recorded a heat index (measure of estrus strength), maximum activity change, maximum rumination change and duration of high activity. The sensitivity was 91.0%, with a false positive and false negative rate of 8.0%, and the positive predictive value to detect true estrus events was 83.5%. Pregnancy per AI to first AI was 67.6% and 97.9% of heifers become pregnant after four inseminations. Most false positive estrus events had a heat index < 45 and a rumination change < -20, while false negative events had a rumination change ≥ -20. Odds of pregnancy was not associated with any estrus characteristics measured by the system. However, pre-ovulatory follicle diameter had a weak correlation (r < 0.25) with all estrus characteristics. The average (range) interval of onset of high activity, peak activity and end of high activity to OV was 28 h (16-46 h), 22 h (10-40 h) and 16 h (0-36 h), respectively. For conventional semen, each hour increase in interval from activity onset or peak activity to AI reduced the predicted probability of pregnancy by 3.8 and 4.2%, respectively. For sex-sorted semen, the relationship between activity onset or peak activity to AI and predicted probability of pregnancy was quadratic, but not significant. Overall, the SCR eSense ear tag AAM performed well and strategies to identify false positive and false negative estrus events, along with optimization of timing of AI, should further improve performance in Holstein heifers., (Crown Copyright © 2020. Published by Elsevier Inc. All rights reserved.)

Animal's feed efficiency in growing cattle (i.e. the animal ability to reach a market or adult BW with the least amount of feed intake), is a key factor in the beef cattle industry. Feeding systems have made huge progress to understand dietary factors influencing the average animal feed efficiency. However, there exists a considerable amount of animal-to-animal variation around the average feed efficiency observed in beef cattle reared in similar conditions, which is still far from being understood. This review aims to identify biological determinants and molecular pathways involved in the between-animal variation in feed efficiency with particular reference to growing beef cattle phenotyped for residual feed intake (RFI). Moreover, the review attempts to distinguish true potential determinants from those revealed through simple associations or indirectly linked to RFI through their association with feed intake. Most representative and studied biological processes which seem to be connected to feed efficiency were reviewed, such as feeding behaviour, digestion and methane production, rumen microbiome structure and functioning, energy metabolism at the whole body and cellular levels, protein turnover, hormone regulation and body composition. In addition, an overall molecular network analysis was conducted for unravelling networks and their linked functions involved in between-animal variation in feed efficiency. The results from this review suggest that feeding and digestive-related mechanisms could be associated with RFI mainly because they co-vary with feed intake. Although much more research is warranted, especially with high-forage diets, the role of feeding and digestive related mechanisms as true determinants of animal variability in feed efficiency could be minor. Concerning the metabolic-related mechanisms, despite the scarcity of studies using reference methods it seems that feed efficient animals have a significantly lower energy metabolic rate independent of the associated intake reduction. This lower heat production in feed efficient animals may result from a decreased protein turnover and a higher efficiency of ATP production in mitochondria, both mechanisms also identified in the molecular network analysis. In contrast, hormones and body composition could not be conclusively related to animal-to-animal variation in feed efficiency. The analysis of potential biological networks underlying RFI variations highlighted other significant pathways such as lipid metabolism and immunity and stress response. Finally, emerging knowledge suggests that metabolic functions underlying genetic variation in feed efficiency could be associated with other important traits in animal production. This emphasizes the relevance of understanding the biological basis of relevant animal traits to better define future balanced breeding programmes.

Quality of pork from pigs raised either traditionally (outdoor access or bedded settings with no sub-therapeutic antibiotics or growth promotants in feed) or conventionally (commercial indoor) was evaluated. Pork loins (m. longissimus thoracis et lumborum, LTL) from four hundred pigs from either traditional or conventional production systems (n=200) fed commercially formulated diets ad libitum were harvested at slaughter. Intramuscular crude fat content and lean color (L* and b*) values were significantly decreased in conventional pork loins. LTL from conventionally-raised pig carcasses showed increased (P<0.05) mean pH, moisture content and reduced cooking loss and shear force values and had increased tenderness and juiciness scores compared to those from traditionally-raised pig carcasses. Results indicated that pork from conventionally raised pigs was superior to that from traditionally raised pigs in terms of tenderness and juiciness, suggesting that consumers may value pork from traditionally raised pigs on the basis of factors other than eating quality and appearance., (© 2013.)

The chicken MHC-B locus affects the response to several strains of Rous sarcoma virus (RSV). We evaluated the association between haplotypes of the MHC-B locus and responses to the J strain of RSV by using an F(2) experimental resource family constructed with tumor-regressive (White Leghorn) and tumor-progressive (Rhode Island Red) chickens. The MHC-B haplotypes were determined by genotyping of the microsatellite marker LEI0258 and MHC-B locus class I alpha chain 2 (BF2). Two haplotypes in the resource family, one associated with tumor regression and one with progression, were defined by these 2 markers. To discriminate more precisely the regressive haplotype in this family, we further developed 35 SNP markers at the MHC-B locus. Information on the haplotypes revealed here should be useful for identifying chickens with regression and progression phenotypes of J-strain RSV-induced tumors.

It is important for the meat industry, including pig farmers and breeding companies, to know the composition of the carcass including the proportions of the different commercial cuts when making decisions on the type of pigs to be produced and marketed. Carcass composition is influenced significantly by the genotype of the animals. The aim of this work was to characterise carcasses from five different pig genotypes, by means of the quantification and comparison of their physical composition. Carcasses from 500 gilts from five different genetic types were studied. These lines were based on the following breeds: Large White, Landrace, Duroc, Piétrain and a Meishan synthetic population developed from a cross with a Large White based line. Measurements were taken in the carcasses directly with a ruler and with the Fat-O-Meat'er. The carcasses were cut following the European reference method and the four main joints were dissected. Carcasses from the Piétrain based line, which was halothane negative, presented the highest killing-out (83.34%) and were the shortest (81.81cm). The Piétrain based line was also the leanest and the Meishan based line the fattest. The highest proportion of ham (270.9g/kg) and the lowest proportion of belly (97.97g/kg) were found in the Piétrain line. The proportion of lean in all of the dissected cuts was higher in carcasses from this line while the Meishan line presented the highest proportions of intermuscular fat in all of the pieces. Carcasses came from the Piétrain line received the highest conformation scores and they were leaner and with better ham yield.

Stress neuroendocrine systems (hypothalamic-pituitary-adrenal axis and sympathetic nervous system) were studied in 100 female pigs from each of the five main genetic lines used in Europe for pork production: Piétrain, Large White, Landrace, Duroc and Meishan. Levels of cortisol and catecholamines were measured in urine collected at the farm, after transportation to the slaughterhouse and the next morning before slaughter. With the exception of the Piétrain line that showed intermediate levels of cortisol despite its extreme leanness, a significant positive relationship was found between basal cortisol levels and fatness, both across and within (except in Piétrain and Duroc) lines. Basal cortisol levels were 2.46-fold higher in Meishan (20.46 ng/mg creatinine) than in Large White pigs (8.30 ng/mg creatinine), the two extreme breeds. Post-transportation levels were highest but proportional to basal levels, suggesting that the adrenal reactivity to adrenocorticotropic hormone is a major source of variability between lines. Levels of catecholamines were less variable between lines but correlated also with fatness, partlyviapartial correlations with cortisol levels. In serum collected at exsanguination, creatine kinase activity was correlated with muscularity across the five breeds. However, this was due to a much larger activity than expected in Piétrain pigs, although all animals were negative for the allele of the ryanodine receptor gene responsible for stress sensitivity. Serum glucose levels were inversely related to fatness. These data show that the differences between breeds or lines can be utilised by cross-breeding and that this can lead to changes in stress hormones and in turn to some degree of changes in carcass traits.

Phenotypic information on 1155 market pigs for several pig meat quality traits, was collected. Genotypes on 12 DNA markers, including RYR1 and PRKAG3 I199V, were also obtained on all pigs to investigate the relationship between genetic markers and meat quality. The RYR1 gene had the highest impact on meat quality, however, several other markers showed significant effects on one or more traits. Animals heterozygous at the RYR1 locus were significantly inferior in almost all meat quality traits, except ultimate pH value, initial conductivity and redness of the meat. Drip loss from case-ready meat (measured from 1 to 7 days post-mortem) was 43% higher for heterozygotes than animals of the stress resistant genotype. The homozygous genotype II at position I199V of the PRKAG3 locus also resulted in less drip loss than genotypes IV and VV, regardless of the method and time of measurement. Furthermore, the favourable genotype related to higher ultimate pH and darker meat. Both loci significantly affected the intercept, linear and quadratic terms of fitted drip loss development curves. The favourable genotypes showed a lower drip loss after one day of measurement and a slower increase and a more linear development over time. Whilst the RYR1 and PRKAG3 markers influenced numerous meat quality traits, some of the other markers were also found to have significant effects on one or two meat quality traits. Markers at MC4R and HMGA1 loci significantly affected drip loss, whereas LDHA, CAST (Hpy188I) and ATP2A1 influenced pH value. In addition, the marker ATP2A1 was associated with variation in intramuscular fat content in M. longissimus dorsi. GLUT4 affected temperature 45min post-mortem and several markers (MC4R, LDHA, GLUT4, HMGA1, CAST (Hpy188I and PvuII)) influenced one or two of the different colour measurements. The markers at MC4R, CKM, AGRP, PRKAG3, and HMGA1 loci were tested for their interactions with RYR1 regarding drip loss. Only AGRP showed a significant interaction, but this was based on only a few animals with the homozygous genotype for one allele. Our results suggest that genetic markers provide a useful tool to improve meat quality in pigs independently from RYR1, especially the mutation I199V in the PRKAG3 gene.

Drip loss of 374 samples taken from porcine M. longissimus dorsi and M. semimembranosus was measured by using the "bag method" (BM), EZ-DripLoss (EZ-DL) from premium cuts (PC) and in retail tray (case-ready meat; CRM). This provided a comparison between these methods and their relationships to other meat quality and carcass traits. Samples were prepared at 24h post-mortem (pm) and were measured 24 and 48h after preparation (at 48 and 72h pm) using the BM and after 48h (at 72h pm) with the EZ-DL and PC. Drip loss of meat kept in retail trays was measured after 7 days (CRM(7)) and daily within a week (CRM(1-7)). Average drip loss was 1.80% and 3.10% using the BM after 24 and 48h, respectively. EZ-DL and CRM(7) showed higher drip losses of 4.71% and 4.00%. Daily loss of CRM(1-7) showed a concavely shaped curve and increased from 1.57% to 5.64% after 7 days. High correlations were obtained between drip loss of CRM(7) and BM (r=0.88) or the EZ-DL (r=0.91). The development of drip loss in case-ready meat fitted by linear-quadratic regression (y=0.439+1.245x-0.072x(2)) showed that high drip loss measured earlier by bag and EZ-DripLoss methods was highly associated with a high intercept (r=0.63-0.72), a high linear increase (r=0.77-0.81), but larger decrease in increments (r=-0.82 to -0.86) during weekly stored meat in retail trays as supplied at consumer level. Because the positive linear regression coefficient was substantially higher than the negative quadratic regression coefficient, the development of drip loss is mainly dependent on the initial drip loss. Therefore, animals with high drip loss within 72h post-mortem also showed undesirable high drip loss curves over the entire retail period. Relationships between drip loss and other meat quality traits were similar for BM, EZ-DL and CRM(7). Of these the correlation between pH(24) and drip loss was highest with r=-0.54, -0.49 and -0.47 for BM, EZ-DL and CRMH(7), respectively. Interestingly, a correlation of r=-0.35 between blood pH value and CRML(7) was obtained. Carcass traits such as loin, ham, shoulder, belly weight or loin eye area showed only marginal correlations to drip loss. In conclusion, EZ-DL was the most appropriate method to predict drip loss of case-ready meat in retail trays and its development during a 7 day storage period.

Development of body composition of 440 growing pigs from a three generation full-sib design to identify quantitative trait loci (QTL) was determined by three different methods. Firstly, the non-invasive method deuterium dilution technique (DT), was applied to all pigs in the experiment at six weights 20, 30, 60, 90, 120 and 140kg. Secondly, at each weight class, eight pigs were slaughtered and their entire body chemically analysed (CA). Thirdly, magnetic resonance imaging (MRI) was applied on 16 live pigs at different weights. For the entire empty body (without content of the gastrointestinal tract and bladder), allometric prediction equations to predict body composition from empty body water content measured by DT were derived from chemically analysed serial slaughtered pigs. These equations showed high correlations of 0.92, 0.90 and 0.85 for the contents of body water, fat-free substance as well as protein in fat-free substance, respectively. For the soft tissue (empty body without bones and viscera), allometric prediction equation of body composition based on DT and CA showed correlations of 0.91, 0.88 and 0.82 for water content, fat-free substance, and protein content of fat free substance, respectively. Fat tissue content, fat tissue mass, and lean tissue mass measured by MRI showed allometric relationships to lipid content, lipid mass, and protein mass determined by DT with correlations of 0.98, 0.87, and 0.98, respectively. Lean (measured by MRI) and protein (determined by DT) content of soft tissue was best fitted by a linear-quadratic polynomial and resulted in a correlation of 0.86. Allometric coefficients for change of percentages of chemical components, water (b=-0.036) and protein (b=0.106) in fat-free substance of empty body during growth were similar to those in the literature indicating the consistency of accretion rates of chemical components of the fat-free substance in different studies. Means for protein- and lipid-deposition rates (determined by DT) as well as lean tissue- and fat tissue-deposition rates (measured by MRI) ranged from 95 to 154, 147 to 328, 373 to 420 and 129 to 254g in the different weight ranges. Variation between animals in protein (lean tissue) and lipid (fat tissue) deposition rate was large which can be exploited in order to identify QTL of these traits.

Functional genomics, including analysis of the transcriptome and proteome, provides new opportunities for understanding the molecular processes in muscle and how these influence its conversion to meat. The Quality Pork Genes project was established to identify genes associated with variation in different aspects of raw material (muscle) quality and to then develop genetic tools that could be utilized to improve this quality. DNA polymorphisms identified in the porcine PRKAG3 and CAST genes illustrate the impact that such tools can have in improving meat quality. The resources developed in Quality Pork Genes provide the basis for identifying more of these tools.

A study in 192 entire male pigs examined the effects of breed, diet and muscle on growth, fatness, sensory traits and fatty acid composition. There were four breeds: two modern breeds, Duroc and Large White and two traditional breeds, Berkshire and Tamworth. The diets differed in energy:protein ratio, being conventional (C) and low protein (LP) diets, respectively. Muscles investigated were the `white' longissimus dorsi (LD) and the `red' psoas major (PS). Breed influenced growth rate and fatness, the modern breeds being faster-growing with leaner carcasses. However, the concentrations of neutral lipid fatty acids and marbling fat (neutral lipid+phosopholipid fatty acids) were higher in Berkshire and Duroc, in both LD and PS. Relationships between marbling fat and P2 fat thickness showed clear breed effects, with Duroc having high marbling fat at low P2 and Tamworth low marbling fat at high P2. Breed effects on sensory scores given by the trained taste panel to griddled LD and PS steaks were relatively small. Breed affected the fatty acid composition of intramuscular neutral lipid, with high % values for the saturated fatty acids, 14:0 and 16:0 in Berkshire and Tamworth (fat carcasses) and high values for polyunsaturated fatty acids in Duroc and Large White (lean carcasses). Duroc had particularly high concentrations of the long-chain polyunsaturated fatty acids, 20:5n-3 and 22:6n-3 in phospholipid of both muscles. Diet influenced growth rate and fatness, the LP diet slowing growth and producing fatter meat, more so in the two modern breeds, and particularly in intramuscular rather than subcutaneous fat. This diet produced more tender and juicy meat, although pork flavour and flavour liking were reduced. The PS muscle had higher tenderness, juiciness, pork flavour, flavour liking and overall liking scores than LD. The concentration of phospholipid fatty acids was higher in PS than LD but neutral lipid fatty acid content and marbling fat were higher in LD.

Porcine skeletal muscle fibres were molecularly classified, using in situ hybridisation and immunocytochemistry, into four types, according to the isoform of myosin heavy chain (MyHC) that was present in each fibre (MyHC slow/I, MyHC 2a, MyHC 2x and MyHC 2b). The relationship between MyHC fibre types and meat quality traits between two phenotypically divergent muscles [longissimus dorsi (LD) and psoas], and between the same muscles of different breeds (traditional Berkshire and Tamworth, and modern Duroc-based and Large White-based) were examined. We found that the greater abundance of fast oxidative-glycolytic MyHC 2a and 2x fibres in the psoas was associated with superior meat quality traits, and that the greater presence of fast glycolytic MyHC 2b fibres in the LD could account for less favourable quality traits, both in terms of pH, drip loss, grain, colour, yield force and work done. Although significant correlations were found between specific fibre types and quality traits, within either the psoas or LD muscle of some breeds, no consistent correlation was found across both muscles and all breeds. This finding was in line with the view that a given fibre type could have considerable differences in phenotype between breeds, and between muscles. The observed inverse compositional and functional-meat quality relationship between MyHC 2b and 2x fibres, and MyHC 2b and 2a fibres could form a basis of fibre type manipulation to improve meat quality.

After 30 years of selection, breeding of the pig breed sus scrofa Piétrain has resulted in reduced backfat thickness (from 3.2 to 1.9 mm) and increased loin muscle area (40 to 60 cm2) which indicates high genetic determination of these body composition traits. The use of sophisticated quantitative genetic methods that include all genetic relationships of large populations has led to a high response to selection of these traits. Selection on feed intake, lean and fat tissue growth using nonlinear functions to optimise these traits during the entire growth period in a biological model offers the opportunity to further improve total genetic potential. Protein and lipid deposition rates during the entire growth period have to be known for this biological model to be applied; thus knowledge of the genetic background of these traits is of high economic value. With the use of molecular genetic methods, such as candidate gene and genome scan approaches, the identification of genes for obesity and growth can be obtained. In sus scrofa, candidate genes associated with obesity and growth include Leptin Receptor, Melanocortin-4 Receptor, Agouti related protein, Heart fatty acid binding protein 3, and Insulin-like growth factor 2. Some of these candidate genes also explain variation in obesity levels in humans. Initial genome-wide scans have identified quantitative trait loci (QTL) on chromosomes 1, 4, 5, 7 and X for obesity and on chromosomes 1, 4, 7, 8, 13 and 18 for growth. Physiological candidate genes and predispositional QTL for obesity are not always located on the same chromosome; this is known the "polygenic paradox". Use of a nonlinear growth function is recommended in order to give more insight into the physiological regulation of obesity traits. Sus scrofa is an excellent model organism to examine the genetic regulation of obesity. The conservation of DNA sequence and chromosomal segments between sus scrofa and homo sapiens will permit easy transfer of results to human studies.

Progress in animal nutrition, reproduction, quantitative genetics, and the development of molecular genetics, proteomics, and functional genomics open new perspectives for the meat sector. The most promising developments include a wider utilisation of molecular markers, the possibilities of semen sexing and the targeted use of nutrition to modify the composition of meat. The increased use of biotechnology will have a considerable impact on the economics of production of meat and further processed products. New technologies will increase the possibilities for product differentiation and improve homogeneity of live animals. The consumer and society in general will influence the direction of these developments. This review will focus on the long-term impact of new technologies for the meat production chain.

The aim of this paper is to discuss the role of major genes and DNA technology in selection for meat quality in modern breeding schemes. An overview of major genes, including genes that affect water-binding, colour, marbling, boar taint and tenderness, is given. Two different approaches for the development of DNA tests as selection tools are described: (1) localization of relevant genes on the genome map using DNA markers, and (2) research on mutations in targeted functional genes (candidate genes). It is concluded that major genes for meat quality provide excellent opportunities, not only for increasing the level of meat quality, but also for decreasing variability. Furthermore, major genes can be exploited for differentiation for specific markets. It is stressed that phenotypic data on culled nucleus animals provide an important basis for the development of DNA tests for selection for meat quality. More fundamental research is recommended to understand the interactions of genes with each other and with environmental factors.