Genetic parameters and predicted response to selection for lean growth in an Australian commercial nucleus pig herd

Genetic parameters for performance traits in a pig population were estimated using a multi-trait derivative-free REML algorithm. The 2590 total data included 922 restrictively fed male and 1668 ad libitum fed female records. Estimates of heritability (standard error in parentheses) were 0.25 (0.03), 0.15 (0.03), and 0.30 (0.05) for lifetime daily gain, test daily gain, and P2-fat depth in males, respectively; and 0.27 (0.04) and 0.38 (0.05) for average daily gain and P2-fat depth in females, respectively. The genetic correlation between P2-fat depth and test daily gain in males was -0.17 (0.06) and between P2-fat and lifetime average daily gain in females 0.44 (0.09). Genetic correlations between sexes were 0.71 (0.11) for average daily gain and -0.30 (0.10) for P2-fat depth. Genetic response per standard deviation of selection on an index combining all traits was predicted at $AU120 per sow per year. Responses in daily gain and backfat were expected to be higher when using only male selection than when using only female selection. Selection for growth rate in males will improve growth rate and carcass leanness simultaneously.

Part 1. Growth, carcass and meat quality parameters of male goats: effects of genotype and liveweight at slaughter

Male kids (110) from six goat genotypes, i.e. Boer x Angora (BA), Boer x Feral (1317), Boer x Saanen (BS), Feral x Feral (FF), Saanen x Angora (SA) and Saanen x Feral (SF) and two slaughter weight groups, i.e. Capretto and Chevon (liveweight at slaughter 14-22 and 30-35 kg, respectively) were compared for growth, carcass and meat quality characteristics. Due to their better growth rate, kids from BS and SF genotypes reached the required liveweight for slaughter earlier than kids from other Genotypes used in the study. Chevon kids had a significantly (P < 0.05) lower average daily gain (119 g per day) compared to Capretto kids (171 g per day). SA, SF and FF kids deposited more internal fat in comparison to kids from other genotypes. The dressing percentage of kids ranged from 51 to 54%, with significant differences between genotypes. BS and SF kids had longer carcasses. while BF kids had larger eye muscle area compared to other genotypes. Goat carcasses had a thin subcutaneous fat cover (1.6-2.2 mm). Genotype had a significant (P < 0.05) influence on cooking loss, pigment concentration and muscle colour parameters (CIE L*, a* and b* values). As denoted by the higher V and fibre optic probe values and lower subjective muscle score, the longissimus muscle colour was lighter for BS kids than other genotypes. Cooked meat from the BF kids had lower shear force values and better sensory scores compared to other genotypes. A significant (P < 0.05) decrease in muscle tenderness was observed from Capretto to Chevon carcasses, whereas cooked meat from these two slaughter weight groups was equally accepted (P > 0.05) by the panellists. (C) 2003 Elsevier Science B.V. All rights reserved.

Part 2. Carcass composition and fatty acid profiles of adipose tissue of male goats: effects of genotype and liveweight at slaughter

The dissected carcass composition and fatty acid profiles of intermuscular fat from 110 male goat kids from six genotypes i.e. Boer x Angora (BA), Boer x Feral (BF), Boer x Saanen (BS), Feral x Feral (1717), Saanen x Angora (SA) and Saanen x Feral (SF) and two slaughter weight groups i.e. Capretto and Chevon (liveweight at slaughter 14-22 and 30-35 kg, respectively) were compared. Carcass tissue distribution for various genotypes was: muscle (63-66%), fat (10-13%) and bone (21-24%). Genotype significantly (P < 0.05) influenced the carcass composition; BA and FF carcasses had significantly higher muscle to bone ratio, while carcasses from BS kids were leaner compared to other genotypes. However, the two slaughter weight groups did not differ significantly (P > 0.05) in terms of carcass composition, when compared at the same carcass weight. In the present study, significant (P < 0.01) correlations were observed between percentage of muscle, fat and bone in most of the primal cuts and that in the carcass side. The main saturated fatty acids (SFAs) identified were palmitic (16:0) and stearic acid (18:0), while oleic acid (18: 1, omega9) was the main unsaturated fatty acid (UFA) in the intermuscular fat from goat kids. There were significant (P < 0.05) differences between genotypes in the proportions of individual fatty acids. Adipose tissue from BS kids had significantly higher UFAs (mainly oleic acid) and thus had a significantly lower melting point compared to other genotypes. There were significantly higher proportions of palmitic acid (35%) in the adipose tissue from Capretto kids compared to that from Chevon kids (22%). The concentration of UFAs increased in the adipose tissue from Capretto to Chevon carcasses. (C) 2003 Elsevier Science B.V. All rights reserved.

Responses in carcass lean pH at 24 hours post-mortem in lines of Large White pigs selected for growth rate on a fixed ration over a set time

A restricted maximum likelihood analysis applied to an animal model showed no significant differences (P > 0.05) in pH value of the longissimus dorsi measured at 24 h post-mortem (pH24) between high and low lines of Large White pigs selected over 4 years for post-weaning growth rate on restricted feeding. Genetic and phenotypic correlations between pH24 and production and carcass traits were estimated using all performance testing records combined with the pH24 measurements (5.05–7.02) on slaughtered animals. The estimate of heritability for pH24 was moderate (0.29 ± 0.18). Genetic correlations between pH24 and production or carcass composition traits, except for ultrasonic backfat (UBF), were not significantly different from zero. UBF had a moderate, positive genetic correlation with pH24 (0.24 ± 0.33). These estimates of genetic correlations affirmed that selection for increased growth rate on restricted feeding is likely to result in limited changes in pH24 and pork quality since the selection does not put a high emphasis on reduced fatness.

Evaluation of multifrequency bioelectrical impedance data for predicting lean tissue mass in beef cattle

Multifrequency bioimpedance analysis has the potential to provide a non-invasive technique for determining body composition in live cattle. A bioimpedance meter developed for use in clinical medicine was adapted and evaluated in 2 experiments using a total of 31 cattle. Prediction equations were obtained for total body water, extracellular body water, intracellular body water, carcass water and carcass protein. There were strong correlations between the results obtained through chemical markers and bioimpedance analysis when determined in cattle that had a wide range of liveweights and conditions. The r(2) values obtained were 0.87 and 0.91 for total body water and extracellular body water respectively. Bioimpedance also correlated with carcass water, measured by chemical analysis (r(2) = 0.72), but less well with carcass protein (r(2) = 0.46). These correlations were improved by inclusion of liveweight and sex as variables in multiple regression analysis. However, the resultant equations were poor predictors of protein and water content in the carcasses of a group of small underfed beef cattle, that had a narrow range of liveweights. In this case, although there was no statistical difference between the predicted and measured values overall, bioimpedance analysis did not detect the differences in carcass protein between the 2 groups that were apparent following chemical analysis. Further work is required to determine the sensitivity of the technique in small underfed cattle, and its potential use in heavier well fed cattle close to slaughter weight.

Prediction of the chemical composition of lamb carcasses from multi-frequency impedance data

Multi-frequency bioimpedance analysis (MFBIA) was used to determine the impedance, reactance and resistance of 103 lamb carcasses (17.1-34.2 kg) immediately after slaughter and evisceration. Carcasses were halved, frozen and one half subsequently homogenized and analysed for water, crude protein and fat content. Three measures of carcass length were obtained. Diagonal length between the electrodes (right side biceps femoris to left side of neck) explained a greater proportion of the variance in water mass than did estimates of spinal length and was selected for use in the index L-2/Z to predict the mass of chemical components in the carcass. Use of impedance (Z) measured at the characteristic frequency (Z(c)) instead of 50 kHz (Z(50)) did not improve the power of the model to predict the mass of water, protein or fat in the carcass. While L-2/Z(50) explained a significant proportion of variation in the masses of body water (r(2) 0.64), protein (r(2) 0.34) and fat (r(2) 0.35), its inclusion in multi-variate indices offered small or no increases in predictive capacity when hot carcass weight (HCW) and a measure of rib fat-depth (GR) were present in the model. Optimized equations were able to account for 65-90 % of the variance observed in the weight of chemical components in the carcass. It is concluded that single frequency impedance data do not provide better prediction of carcass composition than can be obtained from measures of HCW and GR. Indices of intracellular water mass derived from impedance at zero frequency and the characteristic frequency explained a similar proportion of the variance in carcass protein mass as did the index L-2/Z(50).

What is a healthy weight for middle aged women?

OBJECTIVE: To explore associations between body mass index (BMI) and selected indicators of health and well-being and to suggest a healthy weight range (based on BMI) for middle aged Australian women. DESIGN: population based longitudinal study (cross-sectional baseline data). SUBJECTS: 13431 women aged 45-49 y who participated in the baseline survey for the Australian Longitudinal Study on Women's Health. RESULTS: Forty-eight percent of women had a BMI>25kg/m(2). Prevalence of medical problems (for example, hypertension, diabetes), surgical procedures (cholescystectomy, hysterectomy) and symptoms (for example, back pain) increased monotonically with BMI, while indicators of health care use (for example, visits to doctors) showed a 'J' shaped relationship with BMI. Scores for several sub-scales of the MOS short form health survey (SF36) (for example, general health, role limitations due to emotional difficulties, social function, mental health and vitality) were optimal when BMI was around 19-24 kg/m(2). After adjustment for area of residence, education, smoking, exercise and menopausal status, low BMI was associated with fewer physical health problems than mid-level or higher BMI, and the nationally recommended BMI range of 20-25 was associated with optimum mental health, lower prevalence of tiredness and lowest use of health services. CONCLUSIONS: Acknowledging the limitations of the cross-sectional nature of these data, the results firmly support the benefits of leanness in terms of reducing the risk of cardiovascular disease, diabetes and gall bladder disease. The findings are moderated, however, by the observation that both low and high BMI are associated with decreased vitality and poorer mental health. The optimal range for BMI appears to be about 19-24 kg/m(2). From a public health perspective this study provides strong support for the recommended BMI range of 20-25 as an appropriate target for the promotion of healthy weight in middle aged Australian women.

Smoking and relative body weight: An international perspective from the WHO MONICA project

Study objective-To investigate the magnitude and consistency of the associations between smoking and body mass index (BMI) in different populations. Design-A cross sectional study. Setting and participants-About 69000 men and women aged 35-64 years from 42 populations participating in the first WHO MONICA survey in the early and mid 1980s. Main restults-Compared to never smokers, regular smokers had significantly (p < 0.05) lower median BMI in 20 (men) and 30 (women) out of 42 populations (range -2.9 to 0.5kg/m(2)). There was no population in which smokers had a significantly higher BMI than never smokers. Among men, the association between leanness and smoking was less apparent in populations with relatively low proportions of regular smokers and high proportions of ex-smokers. Ex-smokers had significantly higher BMI than never smokers in 10 of the male populations but in women no consistent pattern was observed. Adjustment for socioeconomic status did not affect these results. Conclusions-Although in most populations the association between smoking and BMI is similar, the magnitude of this association may be affected by the proportions of smokers and ex-smokers in these populations.