Pigs were raised on six isotopically controlled diets to examine the dietary macronutrients used in the synthesis of bulk bone biochemical components (apatite, collagen and lipids) and individual compounds (bone fatty acids, cholesterol and amino acids from collagen). δ 13 C values of apatite and bulk bone lipids reflected those of the whole diet, with 13 C apatite-whole diet = 10.2 ± 1.3‰ and 13 C bone lipids-whole diet = −2.4 ± 0.7‰. A wide variation observed in the 13 C collagen-whole diet values (0.5 to 6.1‰) was hypothesized to reflect the relative importance of (i) the direct incorporation of essential amino acids, and (ii) the balance between direct incorporation and de novo synthesis of non-essential amino acids. Linear regression (n = 6) was used to assess the relationship between the δ 13 C values of whole diet and bulk bone components and individual compounds. Whole diet δ 13 C values showed a strong correlation with those of bone cholesterol (R 2 = 0.81) and non-essential fatty acids (0.97 ≤ R 2 ≤ 0.99). Not surprisingly, bone linoleic acid δ 13 C values correlated well with dietary linoleic acid (R 2 = 0.95). Mass balance calculations using the δ 13 C values of single amino acids accurately predicted the δ 13 C value of whole collagen. The δ 13 C values of whole diet were well correlated with those of the non-essential amino acids, alanine (R 2 = 0.85) and glutamate (R 2 = 0.96) in collagen. The essential amino acids leucine ( 13 C collagen leu-diet leu = 0.5 ± 1.2‰) and phenylalanine ( 13 C collagen phe-diet phe = −0.6 ± 0.6‰) showed little isotopic fractionation between diet and bone collagen.

The ability to accurately measure body or carcass composition is important for performance testing, grading and finally selection or payment of meat-producing animals. Advances especially in non-invasive techniques are mainly based on the development of electronic and computer-driven methods in order to provide objective phenotypic data. The preference for a specific technique depends on the target animal species or carcass, combined with technical and practical aspects such as accuracy, reliability, cost, portability, speed, ease of use, safety and for in vivo measurements the need for fixation or sedation. The techniques rely on specific device-driven signals, which interact with tissues in the body or carcass at the atomic or molecular level, resulting in secondary or attenuated signals detected by the instruments and analyzed quantitatively. The electromagnetic signal produced by the instrument may originate from mechanical energy such as sound waves (ultrasound – US), ‘photon’ radiation (X-ray-computed tomography – CT, dual-energy X-ray absorptiometry – DXA) or radio frequency waves (magnetic resonance imaging – MRI). The signals detected by the corresponding instruments are processed to measure, for example, tissue depths, areas, volumes or distributions of fat, muscle (water, protein) and partly bone or bone mineral. Among the above techniques, CT is the most accurate one followed by MRI and DXA, whereas US can be used for all sizes of farm animal species even under field conditions. CT, MRI and US can provide volume data, whereas only DXA delivers immediate whole-body composition results without (2D) image manipulation. A combination of simple US and more expensive CT, MRI or DXA might be applied for farm animal selection programs in a stepwise approach.

Molecular genetic selection on individual genes is a promising method to genetically improve economically important traits in chickens. A resource population was developed to study the genetics of growth, body composition, skeletal integrity, and metabolism traits. Broiler sires were crossed to dams of 2 diverse, highly inbred lines (Leghorn and Fayoumi), and the F1 birds were intermated by dam line to produce broiler-Leghorn and broiler-Fayoumi F2 offspring. Growth, body composition, skeletal integrity, and hormonal and metabolic factors were measured in 713 F2 individuals. Insulin-like growth factor-I (IGF1) was selected for study as a biological and positional candidate gene. A single nucleotide polymorphism (SNP) was identified between the founder lines in the IGF1 promoter region, and a PCR-RFLP assay was developed. A mixed model was used to statistically analyze associations of IGF1-SNP1 with phenotypic traits. The IGF1-SNP1 had significant associations with most recorded traits, except metabolic traits. Strong interactions between the IGF1 gene and genetic background on growth traits in the 2 F2 populations suggest that genetic interaction is an important aspect for consideration before using the IGF1-SNP1 in marker-assisted selection programs. Several beneficial effects (improved growth, increased breast muscle weight, decreased abdominal fat, and enhanced skeletal integrity) associated with 1 allele indicate the presence of 1 or more loci near IGF1-SNP1 controlling biologically diverse and economically important traits in chickens.