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Hamar, Norway

Wetten M.,NORSVIN | Odegard J.,Nofima Marin | Odegard J.,Norwegian University of Life Sciences | Vangen O.,Norwegian University of Life Sciences | Meuwissen Th.H.E.,Norwegian University of Life Sciences
Animal | Year: 2012

In this study, random regression models were used to estimate covariance functions between feed intake and BW in boars from the two breeds: the Norwegian Landrace and the Norwegian Duroc. In total, 1476 animals of the Norwegian Landrace breed and 1300 animals of the Norwegian Duroc breed had registrations on daily feed intake and growth from 54 to 180 days of age. Random regressions on the Legendre polynomials of age were used to describe genetic and permanent environmental curves in BW (up to the second order) and feed intake (up to the first order) for both the breeds. Heritabilities on BW increased over time for the Landrace (0.18 to 0.24), but were approximately constant for the Duroc (0.33 to 0.35). Average heritabilities for feed intake were approximately the same in both the breeds (0.09 to 0.11), and the estimates decreased over time, most pronounced in Duroc. On the basis of the current data, daily feed intake was seemingly controlled by the same genetic factors throughout the test period for Duroc; however, for Landrace, genetic correlations between test days decreased with increasing distance in time. For BW, the genetic correlations between test days were in general high, and did not go below 0.8 for any of the two breeds in this study. For both feed intake and BW, permanent environmental correlations between start and end of the test were reduced with increasing difference in days, most pronounced in Duroc. This study indicates that weight of the animal at the end of the test was more closely genetically correlated to feed intake of earlier periods compared with later periods of growth for both the breeds. This may be explained by the fact that BW is the cumulative growth of an individual, which is likely to be heavily affected by the feed intake during the most intense growth period. © Copyright The Animal Consortium 2011. Source

Gjerlaug-Enger E.,Norwegian University of Life Sciences | Kongsro J.,NORSVIN | Odegard J.,432 as | Aass L.,Norwegian University of Life Sciences | Vangen O.,Norwegian University of Life Sciences
Animal | Year: 2012

In this study, computed tomography (CT) technology was used to measure body composition on live pigs for breeding purposes. Norwegian Landrace (L; n = 3835) and Duroc (D; n = 3139) boars, selection candidates to be elite boars in a breeding programme, were CT-scanned between August 2008 and August 2010 as part of an ongoing testing programme at Norsvin's boar test station. Genetic parameters in the growth rate of muscle (MG), carcass fat (FG), bone (BG) and non-carcass tissue (NCG), from birth to ∼100 kg live weight, were calculated from CT data. Genetic correlations between growth of different body tissues scanned using CT, lean meat percentage (LMP) calculated from CT and more traditional production traits such as the average daily gain (ADG) from birth to 25 kg (ADG1), the ADG from 25 kg to 100 kg (ADG2) and the feed conversion ratio (FCR) from 25 kg to 100 kg were also estimated from data on the same boars. Genetic parameters were estimated based on multi-trait animal models using the average information-restricted maximum likelihood (AI-REML) methodology. The heritability estimates (s.e. = 0.04 to 0.05) for the various traits for Landrace and Duroc were as follows: MG (0.19 and 0.43), FG (0.53 and 0.59), BG (0.37 and 0.58), NCG (0.38 and 0.50), LMP (0.50 and 0.57), ADG1 (0.25 and 0.48), ADG2 (0.41 and 0.42) and FCR (0.29 and 0.42). Genetic correlations for MG with LMP were 0.55 and 0.68, and genetic correlations between MG and ADG2 were -0.06 and 0.07 for Landrace and Duroc, respectively. LMP and ADG2 were clearly unfavourably genetically correlated (L: -0.75 and D: -0.54). These results showed the difficulty in jointly improving LMP and ADG2. ADG2 was unfavourably correlated with FG (L: 0.84 and D: 0.72), thus indicating to a large extent that selection for increased growth implies selection for fatness under an ad libitum feeding regime. Selection for MG is not expected to increase ADG2, but will yield faster growth of the desired tissues and a better carcass quality. Hence, we consider MG to be a better biological trait in selection for improved productivity and carcass quality. CT is a powerful instrument in conjunction with breeding, as it combines the high accuracy of CT data with measurements taken from the selection candidates. CT also allows the selection of new traits such as real body composition, and in particular, the actual MG on living animals. © Copyright The Animal Consortium 2011. Source

Gjerlaug-Enger E.,Norwegian University of Life Sciences | Kongsro J.,NORSVIN | Aass L.,Norwegian University of Life Sciences | Odegard J.,Norwegian University of Life Sciences | And 2 more authors.
Animal | Year: 2011

This study was conducted to evaluate the potential of near-infrared (NIR) spectroscopy (NIRS) technology for prediction of the chemical composition (moisture content and fatty acid composition) of fat from fast-growing, lean slaughter pig samples coming from breeding programmes. NIRS method I: a total of 77 samples of intact subcutaneous fat from pigs were analysed with the FOSS FoodScan NIR spectrophotometer (850 to 1050 nm) and then used to predict the moisture content by using partial least squares (PLS) regression methods. The best equation obtained has a coefficient of determination for cross-validation (CV; Rcv 2) and a root mean square error of a CV (RMSECV) of 0.88 and 1.18%, respectively. The equation was further validated with(n=15) providing values of 0.83 and 0.42% for the coefficient of determination for validation (Rval 2) and root mean square error of prediction (RMSEP), respectively. NIRS method II: in this case, samples of melted subcutaneous fat were analysed in an FOSS XDS NIR rapid content analyser (400 to 2500 nm). Equations based on modified PLS regression methods showed that NIRS technology could predict the fatty acid groups, the main fatty acids and the iodine value accurately with Rcv 2, RMSECV, R val 2 and RMSEP of 0.98, 0.38%, 0.95 and 0.49%, respectively (saturated fatty acids), 0.94, 0.45%, 0.97 and 0.65%, respectively (monounsaturated fatty acids), 0.97, 0.28%, 0.99 and 0.34%, respectively (polyunsaturated fatty acids), 0.76, 0.61%, 0.84 and 0.87%, respectively (palmitic acid, C16:0), 0.75, 0.16%, 0.89 and 0.10%, respectively (palmitoleic acid, C16:1n-7), 0.93, 0.41%, 0.96 and 0.64%, respectively (steric acid, C18:0), 0.90, 0.51%, 0.94 and 0.44%, respectively (oleic acid, C18:1n-9), 0.97, 0.25%, 0.98 and 0.29% (linoleic acid, C18:2n-6), 0.68, 0.09%, 0.57 and 0.16% (α-linolenic acid, C18:3n-3) and 0.97, 0.57, 0.97 and 1.22, respectively (iodine value, calculated). The magnitude of this error showed quite good accuracy using these rapid methods in prediction of the moisture and fatty acid composition of fat from pigs involved in breeding schemes. © 2011 The Animal Consortium. Source

Gjerlaug-Enger E.,Norwegian University of Life Sciences | Aass L.,Norwegian University of Life Sciences | Odegard J.,Norwegian University of Life Sciences | Odegard J.,432 as | And 2 more authors.
Animal | Year: 2011

Subcutaneous fat from Norwegian Landrace (n = 3230) and Duroc (n = 1769) pigs was sampled to investigate the sources of variation and genetic parameters of various fatty acids, fat moisture percentage and fat colour, with the lean meat percentage (LMP) also included as a trait representing the leanness of the pig. The pigs were from half-sib groups of station-tested boars included in the Norwegian pig breeding scheme. They were fed ad libitum to obtain an average of 113 kg live weight. Near-infrared spectroscopy (NIRS) was applied for prediction of the fatty acids and fat moisture percentage, and Minolta was used for the fat colour measurements. Heritabilities and genetic correlations were estimated with a multi-trait animal model using average information-restricted maximum likelihood (AI-REML) methodology. Fat from Landrace pigs had considerably more monounsaturated fatty acids, polyunsaturated fatty acids (PUFAs) and fat moisture, as well as less saturated fatty acids (SFAs) than fat from Duroc pigs. The heritability estimates (s.e. 0.03 to 0.08) for the various fatty acids were as follows: Palmitic, C16:0 (0.39 and 0.51 for Landrace and Duroc pigs, respectively); Palmitoleic, C16:1n-7 (0.41 and 0.50); Steric, C18:0 (0.46 and 0.54); Oleic, C18:1n-9 (0.67 and 0.57); Linoleic, C18:2n-6 (0.44 and 0.46); α-linolenic, C18:3n-3 (0.37 and 0.25) and n-6/n-3 ratio (0.06 and 0.01). The other fat quality traits revealed the following heritabilities: fat moisture (0.28 and 0.33), colour values in subcutaneous fat: L* (whiteness; 0.22 and 0.21), a* (redness; 0.13 and 0.24) and b* (yellowness; 0.07 and 0.17) and LMP (0.46 and 0.47). LMP showed high positive genetic correlations to PUFA (C18:2n-6 and C18:3n-3), which implies that selecting leaner pigs changes the fatty acid composition and deteriorates the quality of fat. Higher concentrations of PUFA are not beneficial as the ratio of n-6 and n-3 fatty acids becomes unfavourably high. Owing to the high genetic correlation between C18:2n-6 and C18:3n-3 and a low heritability for this ratio, the latter is difficult to change through selection. However, a small reduction in the ratio should be expected if selection aims at reducing the level of C18:2n-6. Selection for more C18:1n-9 is possible in view of the genetic parameters, which are favourable for eating quality, technological quality and human nutrition. The NIRS technology and the high heritabilities found in this study make it possible to implement fat quality traits to achieve the breeding goal in the selection of a lean pig with better fat quality. © 2011 The Animal Consortium. Source

Kongsro J.,NORSVIN
Computers and Electronics in Agriculture | Year: 2014

The weight or mass of a pig is of great importance for farmers and stockmen to monitor performance, health and market weight of animals. The paper presents a prototype for pig weighing based on the Microsoft Kinect camera technology, utilizing the infrared depth map images. The system successfully estimated the weight of two different purebred breeds, landrace and duroc with an error estimate of 4-5% of mean weight. The depth map images require less calibration, are less prone to background (i.e. floor) noise compared to visible light camera systems and seem to be more robust between breeds due to additional information from height (depth map) of animals. © 2014 Elsevier B.V. Source

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