This article reports on the effects of elastic (rubber) flooring compared with concrete flooring on claw health and milk yield in dairy cows. Milk yield and activity data of 53 complete lactations from 49 cows were recorded by an automatic milking system in the University of Munich Livestock Center dairy herd. Cows were kept in a loose housing system on concrete-slatted or rubber-matted slatted flooring. Claws were trimmed and measured linearly in combination with claw lesion diagnosis 3 times during one lactation period (including the transition phase). An automatic milking system recorded milk yield and activity. The net horn growth of the claws increased on elastic flooring. Therefore, correct and frequent claw trimming is at least as important for claw health in dairy herds kept on rubber flooring as for those on concrete-slatted flooring. Cows housed on rubber had an increased incidence of sole ulcers. Sole hemorrhages (except for hemorrhages associated with sole ulcers) occurred less frequently on rubber than on concrete. Results concerning digital dermatitis were difficult to assess, because manual manure scraping on rubber required sprinkling the flooring twice daily, which additionally moistened the digital skin of the cows. This might explain the greater incidence of digital dermatitis on elastic flooring. The incidence of clinically lame cows did not differ between flooring types. Cows showed greater activity on rubber, most likely caused by the more comfortable walking surface compared with the concrete-slatted flooring. The greater activity may indicate better overall health of high-yielding dairy cows on rubber flooring. Milk yield, however, did not differ between flooring types.

Since the pig is one of the most important livestock animals worldwide, mapping loci that are associated with economically important traits and/or traits that influence animal welfare is extremely relevant for efficient future pig breeding. Therefore, the purpose of this study was a genome-wide mapping of quantitative trait loci (QTL) associated with nine body composition and bone mineral traits: absolute (Fat, Lean) and percentage (FatPC, LeanPC) fat and lean mass, live weight (Weight), soft tissue X-ray attenuation coefficient (R), absolute (BMC) and percentage (BMCPC) bone mineral content and bone mineral density (BMD). Data on the nine traits investigated were obtained by Dual-energy X-ray absorptiometry for 551 pigs that were between 160 and 200 days old. In addition, all pigs were genotyped using Illumina’s PorcineSNP60 Genotyping BeadChip. Based on these data, a genome-wide combined linkage and linkage disequilibrium analysis was conducted. Thus, we used 44 611 sliding windows that each consisted of 20 adjacent single nucleotide polymorphisms (SNPs). For the middle of each sliding window a variance component analysis was carried out using ASReml. The underlying mixed linear model included random QTL and polygenic effects, with fixed effects of sex, housing, season and age. Using a Bonferroni-corrected genome-wide significance threshold of P < 0.001, significant peaks were identified for all traits except BMCPC. Overall, we identified 72 QTL on 16 chromosomes, of which 24 were significantly associated with one trait only and the remaining with more than one trait. For example, a QTL on chromosome 2 included the highest peak across the genome for four traits (Fat, FatPC, LeanPC and R). The nearby gene, ZNF608, is known to be associated with body mass index in humans and involved in starvation in Drosophila, which makes it an extremely good candidate gene for this QTL. Our QTL mapping approach identified 72 QTL, some of which confirmed results of previous studies in pigs. However, we also detected significant associations that have not been published before and were able to identify a number of new and promising candidate genes, such as ZNF608.

The objective of the study was to evaluate whether magnetic resonance imaging (MRI) offers the opportunity to reliably analyze body composition of pigs in vivo. Therefore, the relation between areas of loin eye muscle and its back fat based on MRI images were used to predict body composition values measured by dual energy X-ray absorptiometry (DXA). During the study, a total of 77 pigs were studied by MRI and DXA, with a BW ranging between 42 and 102 kg. The pigs originated from different extensive or conventional breeds or crossbreds such as Cerdo Iberico, Duroc, German Landrace, German Large White, Hampshire and Pietrain. A Siemens Magnetom Open was used for MRI in the thorax region between 13th and 14th vertebrae in order to measure the loin eye area (MRI-LA) and the above back fat area (MRI-FA) of both body sides, whereas a whole body scan was performed by DXA with a GE Lunar DPX-IQ in order to measure the amount and percentage of fat tissue (DXA-FM; DXA-%FM) and lean tissue mass (DXA-LM; DXA-%LM). A linear single regression analysis was performed to quantify the linear relationships between MRI- and DXA-derived traits. In addition, a stepwise regression procedure was carried out to calculate (multiple) regression equations between MRI and DXA variables (including BW). Single regression analyses showed high relationships between DXA-%FM and MRI-FA (R 2 = 0.89, √MSE = 2.39%), DXA-FM and MRI-FA (R 2 = 0.82, √MSE = 2757 g) and DXA-LM and MRI-LA (R 2 = 0.82, √MSE = 4018 g). Only DXA-%LM and MRI-LA did not show any relationship (R 2 = 0). As a result of the multiple regression analysis, DXA-LM and DXA-FM were both highly related to MRI-LA, MRI-FA and BW (R 2 = 0.96; √MSE = 1784 g, and R 2 = 0.95, √MSE = 1496 g). Therefore, it can be concluded that the use of MRI-derived images provides exact information about important 'carcass-traits' in pigs and may be used to reliably predict the body composition in vivo.

The objective of this study was to investigate non-invasive imaging methods to update the used regression equation for stationary tested boars. A total of 94 boars were examined. 20 boars were dissected to provide the reference LMP. Performance data (PD) from right carcasses were available from all groups. The left carcasses were studied by MRI & DXA. Based on the reference LMP and the MRI & DXA data, regression equations for LMP were developed. The estimates for LMP based on MRI & DXA data were used to calculate new regression equations for entire male carcass halves based on linear PD. Further 33 PD sets served as independent sample, which was included in a Monte Carlo simulation for imputing the missing reference LMPs (n=74) and discussing the accuracy of the results. The LMP regression equation based on the combined MRI & DXA data is as accurate as the former regression equation, but needs only three instead of seven variables.

The improvement of carcass quality is one of the main breeding goals in pig production. To select appropriate breeding animals, it is of major concern to exactly and reliably analyze the body composition in vivo. Therefore, the objective of the study was to examine whether the combination of dual-energy X-ray absorptiometry (DXA) and magnetic resonance imaging (MRI) offers the opportunity to reliably analyze quantitative and qualitative body composition characteristics of different pig breeding groups in vivo. In this study, a total of 77 pigs were studied by DXA and MRI at an average age of 154 days. The pigs originated from different autochthonous or conventional breeds or crossbreeds and were grouped into six breed types: Cerdo Ibérico (Ib); Duroc × Ib (Du_Ib); White Sow Lines (WSL, including German Landrace and German Large White); Hampshire/Pietrain (Pi_Ha, including Hampshire, Pietrain × Hampshire (PiHa) and Pietrain × PiHa); Pietrain/Duroc (Pi_Du, including Pietrain × Duroc (PiDu) and Pietrain × PiDu); crossbred WSL (PiDu_WSL, including Pietrain × WSL and PiDu × WSL). A whole-body scan was performed by DXA with a GE Lunar DPX-IQ in order to measure the amount and percentage of fat tissue (FM; %FM), lean tissue (LM; %LM) and bone mineral, whereas a Siemens Magnetom Open with a large body coil was used for MRI in the thorax region between 13th and 14th vertebrae in order to measure the area of the loin (LA) and the above back fat area (FA) of both body sides. A GLM procedure using SAS 9.2 was used to analyze the data. As expected, the native breed Ib followed by Du_Ib crossbreeds showed the highest %FM (27.2%, 25.0%) combined with the smallest LA (46.2 cm2, 73.6 cm2), whereas Ib had the lowest BW at an average age of 154 days. Pigs with Pi_Ha origin presented the least %FM (12.4%) and largest LA (99.5 cm2). The WSL and PiDu_WSL showed an intermediate body composition. Therefore, it could be concluded that DXA and MRI and especially their combination are very suitable methods to reliably identify differences in body composition and carcass traits among different pig lines in vivo.

The mirror carp (Cyprinus carpio) belongs to the cyprinids, the world's largest and most important fish family in aquaculture. The fat content and the fillet yield are important parameters in the marketing of carp. Although the influence of the environment on the body composition of the carp has been well studied, there is little research in the field of breeding. For this purpose, precise phenotyping is indispensable. Therefore, during this study a total of 33 mirror carps were examined using computed tomography (CT) technology. First, the fish were examined alive. Total body weight and linear measurements such as lengths, height and circumferences were measured, and ultrasound was used to determine the back-fat thickness. The fish were then slaughtered and whole body scans of all fish using CT were made. The carps were filleted and the fillets with skin were chemically analyzed. In order to predict the chemical fillet fat content, thickness measurements and volume calculations of the back fat were carried out using CT. Compared to the CT-based back-fat thickness measurement correlated with the results from the chemical analysis (R2=0.62), the CT-based volume measurement of the back fat leads to a higher coefficient of determination (R2=0.85). Prediction results can still be improved by adding linear measurements. The in vivo ultrasound (US) examination of the back-fat thickness was compared with the CT back-fat thickness results. The measurements of the back-fat thickness took place at similar positions in the fish. Coefficients of determination (R2) of 0.63 to 0.77 were obtained. The back fat in mirror carp proved to be an interesting area for determining the fillet fat content. The evaluation of the fillet yield resulted in a mean value of 42.89 % with a standard deviation of ±2.43. Fillet yield (%) correlated with CT-based fillet thickness measurement resulted in a moderate coefficient of determination (R2 of 0.45). A similar coefficient of determination was achieved with selected linear measurements.