Genetic relationships between boar feed efficiency and sow piglet production, body condition score, and stayability in Norwegian Landrace pigs 1

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1 Publihed Augut 30, 2016 Genetic relationhip between boar feed efficiency and ow piglet production, body condition core, and tayability in Norwegian Landrace pig 1 K. H. Martinen,* 2 J. Ødegård,* T. Aamundtad, D. Olen, and T. H. E. Meuwien* *Department of Animal and Aquacultural Science, Norwegian Univerity of Life Science, NO-1432 Å, Norway; AquaGen AS, P.O. Box 1240 Sluppen, NO-7462 Trondheim, Norway; and Topig Norvin, Storhamargata 44, NO-2317 Hamar, Norway ABSTRACT: Both feed efficiency and ow production are economically important trait in pig breeding. One challenge in a maternal line uch a Norwegian Landrace i to breed for highly feed efficient fattening pig and, at the ame time, produce ow with high daily feed intake to maintain their BCS in multiple paritie. The aim of thi tudy wa to etimate genetic correlation among novel feed efficiency meaurement on Norwegian Landrace boar and piglet production, tayability, and body condition in Norwegian Landrace ow. The feed efficiency meaurement were lean meat and fat efficiency. Thee meaurement were calculated uing an extended reidual feed intake model where total feed intake in the tet period wa the repone variable and fat (kg) and lean meat (kg) on the carca were included a both fixed and random regreion. The random regreion coefficient that reulted from thi model were breeding value, which repreented the amount of feed ued to produce an extra kilogram of lean meat and fat. The ow trait were tayability of the ow from firt to econd parity, BCS at weaning, litter weight at 3 wk, and total number of piglet born. All trait were recorded on firt parity purebred Norwegian Landrace and analyzed uing multivariate animal model. All genetic correlation between fat efficiency and ow trait were low. Significant genetic correlation were found only between fat efficiency and tayability (0.21 ± 0.11) and between fat efficiency and total litter weight at 3 wk (0.21 ± 0.10). The reult indicate that election for efficient depoition of fat could give poor tayability and lower litter weight at 3 wk in firt parity ow. The genetic correlation between lean meat efficiency and ow trait were not ignificantly different from 0 and ignified no genetic relationhip between thee trait. Selection for efficient depoition of lean meat hould not affect the ow trait and i, therefore, beneficial. Key word: body condition core, feed efficiency, genetic parameter, maternal line, tayability 2016 American Society of Animal Science. All right reerved. J. Anim. Sci : doi: /ja INTRODUCTION In the late 1950, ytematic breeding of Norwegian Landrace pig began and the breeding goal conited mainly of growth and feed intake within a certain weight interval. Growth and feed intake are till economically important trait in pork production (Kani et al., 2005): a feed efficient pig with high growth rate i deired. Traditionally, election for lean 1 The author would like to thank Topig Norvin (Hamar, Å) for acce to data. 2 Correponding author: kritine.martinen@nmbu.no Received December 23, Accepted May 18, meat growth i accomplihed by including growth rate, reduced back fat, and feed intake per kg growth (FCR) in the breeding goal (Hermech, 2004). Cameron and Curran (1994) howed that intene election for lean food converion or lean growth rate may have reulted in reduced feed intake in ad libitum feeding ytem. Additionally, Kerr and Cameron (1996) howed that animal elected for low daily feed intake over 7 generation ate ignificantly le during lactation and had a poorer litter growth than animal elected for high daily feed intake. Thi uggeted that uch election trategie might give an undeired reduction in voluntary feed intake in the ow during the lactation period. Litter ize i an economically important production trait for maternal line; a the number of piglet

2 3160 Martinen et al. increae, the energy requirement for milk production increae (Rothchild, 1996; Rydhmer, 2000). Koltad et al. (1996) howed that Norwegian Landrace had a high ability to mobilize energy from body reerve. Hence, increaed litter ize and reduced appetite increae the rik of a negative energy balance of the ow. High mobilization of body reerve during lactation could lead to a poor body condition at weaning. Poor body condition and increaed weight lo in ow are aociated with lower reproductive performance (Yang et al., 1989; Thaker and Bilkei, 2005), and low reproductive ucce i a major reaon for culling of ow (Dagorn and Aumaitre, 1979; Stein et al., 1990; Lucia et al., 2000; de Jong et al., 2014). Stalder et al. (2003) found that ow needed at leat 3 paritie to become profitable. Therefore, one of the major challenge of pig breeding i to produce a highly feed efficient fattening pig with a low FCR intake and a high production level and at the ame time maintain the ow BCS to be able to produce multiple litter. Martinen et al. (2015) found genetic variation in new feed efficiency meaurement for Norwegian Landrace and Duroc, which gave the poibility to elect for animal that utilized their feed efficiently. The aim of thi current tudy wa, therefore, to etimate genetic relationhip between the new feed efficiency trait of Norwegian Landrace boar and BCS, tayability, and piglet production of Norwegian Landrace ow. MATERIAL AND METHODS Thi tudy wa baed on phenotypic record that exited in the databae of Topig Norvin (TN; Vught, the Netherland), and hence, the Animal Care and Ue Committee approval wa not needed for thi pecific tudy. Data material wa provided by TN and included purebred boar from TN boar teting tation and purebred Norwegian Landrace ow from TN breeding nucleu and multiplier herd. Data on piglet production, body condition, and tayability wa extracted from the Norwegian litter recording ytem (Ingri; Norwegian Meat and Poultry Reearch Centre, 2016), wherea feed intake data on the boar wa extracted from TN databae from the tet tation. The trait analyzed were total feed intake in the tet period (FI) meaured on boar on the tet tation and BCS after weaning of firt litter (BCSw), tayability up to inemination for a econd litter (STAY), total number of piglet born in firt litter (TNB), and total litter weight of firt litter at 3 wk (TLW) meaured on purebred Landrace ow and their litter in nucleu and multiplier herd. The feed efficiency meaure were predicted by a random regreion of FI on lean meat and fat production (Martinen et al., 2015). In total, data on all trait wa extracted from 197 herd within TN breeding nuclei in Norway and other countrie. Boar Tet Recording Total feed intake in the tet period meaured on boar originated from 40 nucleu herd in Norway and wa recorded at TN boar tation tet. The boar elected for the tet are from the bet third of all litter born in the active breeding population. At the tation tet, individual feed intake and weight were meaured daily on all boar by a Feed Intake Recording Equipment (FIRE) tation (Oborne Indutrie, Inc., Oborne, KS) in each pen of 12 pig. The average live weight of the boar at the tart of the tet wa approximately 40 kg and approximately 100 or 120 kg at the end of the tet. If the boar finihed the tet before March 1, 2012, they ended the tet to 100 kg live weight; all boar finihing after thi ended the tet at 120 kg live weight. In thi data et, FI wa recorded on boar born from 2008 to In total, 8,161 Norwegian Landrace boar had information on FI. At the end of the tet, all boar were canned by computed tomography (CT). A part of thi procedure, lean meat and fat content on the carca of each boar were calculated by a TN-developed MATLAB (The MathWork Inc., Natick, MA) program for image analyi of CT data (Gjerlaug- Enger et al., 2012). Martinen et al. (2015) provided a more detailed decription of the data. Stayability, BCS, and Piglet Production Information on the ow trait came from 194 nucleu and multiplier herd in the TN ytem, from Norway and other countrie. Due to trict animal welfare regulation, Norwegian pig production ha ome ditinct characteritic. It i enforced by law that the minimum length of lactation hall be 28 d and ow are looe houed through all tage of production (Thingne, 2013). Hence, the data are collected in herd that do not have identical management, a weaning take place earlier and the ow are crated during lactation in ome foreign countrie. In Norway, farmer routinely record BCSw, TLW, and TNB in nucleu and mot multiplier herd. In thi data et, TLW wa defined a the um of adjuted individual weight of all piglet at 3 wk of age in the firt litter. The piglet are weighed between 17 and 25 d of age, and their weight i adjuted to 3 wk of age (21 d). The total number of piglet born in the firt litter included both live-born and tillborn piglet. Body condition core after weaning of firt litter wa a categorical trait where ow were cored from 1 to 9, where 1 wa thin and 9 wa obee. The farmer follow national guideline for body condition coring of ow provided by TN and Norwegian Meat and Poultry Reearch Centre (Olo, Norway) to make the coring a objective a poible (Norwegian Meat and Poultry Reearch Centre and Topig Norvin, 2015). In thi data, STAY wa defined a a binary trait and tated whether a ow wa culled after firt litter (STAY = 0) or

3 Boar feed efficiency and ow performance 3161 if he wa ineminated for a econd litter (STAY = 1). Animal with an unucceful econd inemination were not captured in thi trait, a thee were alo regitered a 1. Only information from firt to econd parity wa ued, but tayability from firt to econd parity i found to be highly correlated with tayability from econd to third parity and later paritie (Tholen et al., 1996; Engblom et al., 2009; Aamundtad et al., 2014). Sow younger than 250 d or older than 730 d at farrowing, and ow weaning piglet older than 70 d were dicarded. Only ow with at leat 2 piglet in the litter were included in the analyi. The trait were recorded on firt parity ow born from 2002 to Table 1 how decriptive tatitic for the trait. Pedigree wa traced back 10 generation and included 117,638 animal. Table 1. Average (mean), SD, minimum (min), and maximum (max) value for total feed intake in the tet period (FI), lean meat, and fat regitered on boar in the tet tation and for BCS after weaning of firt litter (BCSw), tayability up to inemination for a econd litter (STAY), total litter weight of firt litter at 3 wk (TLW), and total number of piglet born in firt litter (TNB) regitered on ow off tet Parameter Mean SD Min Max FI, kg Lean meat, kg Fat, kg BCSw, point STAY, point TLW, kg TNB, no Statitical Analye The trait were analyzed uing multivariate animal model, and etimation of variance component and genetic correlation were performed uing the DMU oftware package (Maden and Jenen, 2013). The fixed effect ued in the model were determined baed on a GLM analyi of the trait in SAS (SAS Int. Inc., Cary, NC). For all trait, heritability wa defined a h 2 = σ a 2 /(σ a 2 + σ e 2 ), in which σ a 2 i the genetic variance and σ e 2 i the reidual variance of the trait. Total Feed Intake in the Tet Period. The trait and model are defined according to Martinen et al. (2015). For the trait FI in boar at the tet tation, the following model wa ued for analyi: FI ijknoqrt = HY i + BM j + ST k + SEC n + β lm LMEAT o + β fat FAT q + β amw AMW r + a + pen t + a lmeat p o + a fat f q + e ijknoqrt. [1] The fixed effect included in the model were birth herd year (HY), birth month (BM), canning time (ST), and ection in the tet tation (SEC). Number of level in HY (i) wa 207 and for BM (j), it wa 12. For ST (k), number of level wa 2 (finihing before or after March ) and SEC (n) had 132 level. The boar phenotype for carca lean meat (LMEAT), carca fat (FAT), and accumulated metabolic BW (AMW) were included a fixed regreion covariate. A a meaure of feed efficiency, random regreion on amount of lean meat (lmeat) and fat ( a p and a f, repectively) were included in the model a in Martinen et al. (2015). A each boar ha only 1 meaure each for lean meat and fat content (kg), the random regreion model i fitted through the genetic relationhip between boar with record of lean meat and fat. Therefore, the model can ue a ituation with only 1 record per animal. The animal additive genetic effect (a ) and pen were included a random effect. In thi model, a repreent the genetic effect of the animal on FI that cannot be explained by the difference in depoition of fat and lean meat and i from now on referred to a the (genetic effect on) reidual feed intake of the animal (RFI). In the reult, a p i referred to a lean meat efficiency (LME) and a f i referred to a fat efficiency (FE) of animal. Both LME and FE are random regreion coefficient, which indicate the individual deviation (from the population mean) with repect to amount of feed needed to produce 1 kg of lean meat or fat. It hould be noted that increaed level are unfavorable a thi indicate a greater demand for feed per kilogram fat or lean meat depoited. Hence, low LME and FE are deirable. Total feed intake in the tet period wa alo analyzed in a econd model [2], which wa identical to model [1] but excluded the effect of AMW and the fixed and random regreion on carca LMEAT and fat. FI ijklmn = HY i + BM j + ST k + SEC l + a m + pen n + e ijklmn. [2] The fixed effect are the ame a in model [1], wherea the random effect (a m ) i the genetic effect of the animal on FI. Model [2] wa, therefore, a traditional linear animal model ued to analyze FI, which did not correct for production. Model [2] wa ued to compare the reult from the new model developed in Martinen et al. (2015) with reult from a traditional linear animal model for FI. Body Condition Score. Body condition core after weaning of firt litter wa analyzed in the following model, which i ued by TN for their routinely genetic evaluation of the trait: BCSw ijklmnopq = M_LNO i + HY j + SEA k + BRYEAR l + WEAN m + β AGEM n + β AGEW o + animal p + litter q + e ijklmnopq. [3]

4 3162 Martinen et al. The fixed effect in the model wa dam litter number (M_LNO; i = 1 to 3, in which all M_LNO > 3 wa aigned a 3), HY (j = 1 to 593), eaon (SEA; k = 1 to 4), breed of the litter year of the record (BRYEAR; l = 1 to 65), and number of weaned piglet (WEAN; k = 1 to 19). Sow age at farrowing (AGEM) and litter age at weaning (AGEW) were both included a fixed regreion covariate in the model. The animal breeding value (animal), litter identity (litter) and the reidual (e) were included a random effect. Stayability. Baed on previou work by Aamundtad et al. (2014), STAY wa analyzed a STAY ijklmno = M_LNO i + BY j + HYS k + BR l + β AGEM m + animal n + litter o + e ijklmno. [4] In the model, M_LNO, birth year (BY), herd year eaon of the record (HYS), and breed of the litter (BR) were treated a fixed effect. Dam litter number had 3 level (M_LNO > 3 wa aigned 3), BY had 13 level, HYS had 4,936 level, and BR had 11 level. The AGEM wa included a a fixed covariate. The animal breeding value (animal) and their litter were included a random effect, and e wa the random reidual effect. Total Number of Piglet Born and Litter Weight at 3 wk. Total number of piglet born in firt litter wa analyzed by the model below, which i identical to TN model in the routine genetic evaluation of thi trait: TNB ijklmno = M_LNO i + HY j + SEA k + BRYEAR l + β AGEM m + litter n + animal o + e ijklmno. [5] The effect in model [5] were the ame a for BCSw (model [3]), without the fixed regreion covariate of age at weaning. The M_LNO (i = 1 to 3, in which i > 3 = 3), the HY (j = 1 to 1,406), the SEA (k = 1 to 4), and the BRYEAR (l = 1 to 93) were included a fixed effect. For TLW, the model wa the ame a model [5] but alo included the fixed effect of number of piglet weighed in the litter (weighed piglet = 1 to 27). Thi model wa referred to a model [6]. Decriptive Statitic RESULTS Table 1 how decriptive tatitic of the data. The average feed intake in the boar tet period FI wa kg with a high variation (97.2 to kg). Boar had, on average, 52.3 ± 3.6 kg carca LMEAT and 15.9 ± 4.3 kg carca fat FAT. For BCSw meaured on ow at weaning, the average wa 4.2 ± 0.9 point (cale from 1 to 9). Few ow with BCSw = 1 were preent, which indicated that ome ow were very thin at weaning. The maximum BCSw wa 8, which indicated that no obee ow were included in the data. For STAY, approximately 70% of the ow were ineminated for a econd parity, wherea the ret were culled after weaning their firt litter. For piglet production, TLW wa 66.8 ± 19.7 kg, on average, but with a high variation, from 1.5 to kg. Thi i mainly due to the ubtantial variation in number of piglet in the litter. Average TNB wa 13 piglet, ranging from 2 to 29. The TNB included both live-born and tillborn piglet. Table 2 contain the number of animal with phenotype for each trait combination. Regitration of BCSw did not tart until 2007, and therefore, the number of obervation wa ignificantly lower than the other trait. Variance Component and Heritabilitie Etimate of variance component and heritabilitie for all trait are preented in Table 3. All (genetic) variance were ignificantly larger than 0. Significance wa teted baed on the etimate ± 1.96 SE, which ignifie a 95% confidence interval for the etimate (P < 0.05). Low to moderate heritabilitie were found for TNB, STAY, BCSw, and TLW (0.07, 0.10, 0.13 and 0.16, repectively). The heritability for FI etimated with model [1] wa remarkably high (0.59), wherea model [2] gave a moderate heritability for FI (0.22). The additive genetic variance wa approximately the ame in both model, but the reidual variance wa coniderably lower with model [1]. Genetic Correlation The etimated genetic correlation from the multivariate analyi are preented in Table 4. Genetic correlation were etimated among RFI, LME, and FE meaured on boar and BCSw, STAY, TLW, and TNB were meaured on ow. Overall, the genetic correlation were relatively low and motly nonignificant. Significant correlation were found between RFI and both efficiency meaure (LME and FE), uggeting that animal with a high overall feed intake had a lower efficiency (higher feed intake per kilogram depoited lean meat and fat). The etimated genetic correlation between FE and LME wa lightly negative, albeit not ignificant. The genetic correlation between FI etimated with model [2] and the ow trait were cloe to 0 and nonignificant between all trait. The Sow Trait and Reidual Feed Intake of the Animal. The correlation between RFI and the ow trait were poitive but low and motly not ignificantly different from 0. Still, a poitive and ignificant correlation wa found between RFI and BCSw, which implie that animal with an overall high feed intake

5 Boar feed efficiency and ow performance 3163 Table 2. Ditribution of obervation between total feed intake in the tet period (FI), BCS after weaning of firt litter (BCSw), tayability up to inemination for a econd litter (STAY), total litter weight of firt litter at 3 wk (TLW), and total number of piglet born in firt litter (TNB) FI BCSw STAY TLW TNB FI 8,161 BCSw 38,251 STAY 36,257 88,453 TLW 34,128 68,319 70,321 TNB 38,251 88,453 70,321 90,945 (ued for other purpoe than fat and lean meat depoition) in the growth period would be expected to have a greater BCSw a firt parity ow. The Sow Trait and Fat Efficiency. The genetic correlation between FE and ow trait were poitive (i.e., unfavorable) but low. Significant poitive correlation were found between FE and STAY (0.21 ± 0.11) and between FE and TLW (0.21 ± 0.10). Thee reult uggeted that election for fat efficient pig might reult in animal with poorer STAY and reduce TLW. Overall, the correlation between FE and ow trait were nonignificant, except for the correlation between FE, TLW, and STAY in firt parity ow. The Sow Trait and Lean Meat Efficiency. The genetic correlation found between LME and the ow trait were nonignificant. All thee correlation were negative, except the one between LME and TNB, which wa poitive but alo nonignificant. DISCUSSION Thi genetic analyi howed nonexiting genetic correlation between LME and the ow trait, wherea FE had a low and unfavorable genetic correlation to both TLW and STAY. Selection for LME i, therefore, not expected to deteriorate the ow trait BCSw and STAY and piglet production in firt parity ow. Selection for FE i a poibility but may caue ome deterioration of TLW, unle the trait i actively elected for. Variance Component and Heritabilitie For the piglet production trait (TNB and TLW), the heritabilitie were in agreement with TN genetic parameter and lightly lower than thoe found by Aamundtad et al. (2014). Sevón-Aimonen and Uimari (2013) etimated a heritability of 0.08 for TNB in Finnih Landrace, which correpond to thi tudy and tudie of other breed (Hanenberg et al., 2001; Rydhmer et al., 2008). Bergma et al. (2008) etimated Table 3. Genetic variance component (σ a 2 ), reidual variance component (σ e 2 ), and heritability (h 2 ) for total feed intake in the tet period (FI) for boar, BCS after weaning of firt litter (BCSw), tayability up to inemination for a econd litter (STAY), total litter weight of firt litter at 3 wk (TLW), and total number of piglet born in firt litter (TNB) for model [1] and [2]. The variance component for FI were baed on genetic variance component for the animal (reidual feed intake of the animal [RFI]), lean meat efficiency (LME), and fat efficiency (FE). Model [1] Model [2] Trait σ 2 a σ 2 e h 2 σ 2 a σ 2 e h 2 FI (0.95) (3.26) (2.79) 0.22 RFI (a ) (1.47) LME ( a ) p 0.22 (0.04) FE ( a ) f 0.27 (0.04) BCSw 0.07 (0.00) 0.46 (0.00) (0.00) 0.46 (0.00) 0.13 STAY 0.02 (0.00) 0.14 (0.00) (0.00) 0.13 (0.00) 0.10 TLW (0.66) (0.59) (0.63) (0.59) 0.16 TNB 0.80 (0.06) (0.07) (0.06) (0.07) 0.07 a higher heritability but included more than firt litter in their analyi a well a data from crobred ow. A review article by Bidanel (2011) howed that average heritability for TNB wa Hanenberg et al. (2001) found an increae in heritability a parity increaed for TNB. Thi tudy included only firt parity ow; therefore, a lower heritability might be expected. Total number of piglet born in firt litter i influenced by embryo urvival, uteru capacity, and ovulation rate. Primipariou ow have a lower uteru capacity than multipariou ow, and Hermech et al. (2000) uggeted that thi might caue a retriction on the genetic variation. Thi mean that the genetic potential for the trait might not be fully expreed. Bidanel (2011) alo found an average heritability of 0.17 for TLW, in accordance with thi tudy. A correponding heritability wa found in Norwegian Landrace for mean BW at 3 wk (Canario et al., 2010). Lundgren et al. (2014) etimated a greater heritability for TLW in Norwegian Landrace, in accordance with Aamundtad et al. (2014). The data et in thi tudy conit of data from Norway and foreign countrie and therefore may include more noie and underetimate the heritabilitie. Heritability for BCSw wa in accordance with earlier reult found in Norwegian Landrace, analyzed a linear trait in multitrait animal model (Lundgren et al., 2012, 2014). Studie have alo invetigated the ow body condition through other continuou trait, uch a lo of live weight and lo of back fat from farrowing to weaning (Grandion et al., 2005; Bergma et al.,

6 3164 Martinen et al. Table 4. Genetic correlation (SE) between feed intake in the tet period not explained by genetic of lean meat and fat efficiency, named reidual feed intake of the animal (RFI), lean meat efficiency (LME), fat efficiency (FE), BCS after weaning of firt litter (BCSw), tayability up to inemination for a econd litter (STAY), total litter weight of firt litter at 3 wk (TLW) and total number of piglet born in firt litter (TNB). (Model [1]). Genetic correlation between total feed intake in the tet period (FI) and BCSw, STAY, TLW and TNB (Model [2]) Model [1] Model [2] Trait RFI LME FE FI 1 LME 0.25 (0.07) FE 0.71 (0.05) 0.19 (0.12) BCSw 0.16 (0.07) 0.03 (0.13) 0.13 (0.11) 0.13 (0.08) STAY 0.12 (0.07) 0.14 (0.12) 0.21 (0.11) 0.02 (0.08) TLW 0.09 (0.06) 0.16 (0.11) 0.21 (0.10) 0.04 (0.07) TNB 0.03 (0.08) 0.14 (0.14) 0.05 (0.12) 0.06 (0.09) 1 FI = total feed intake in the tet period. 2008). Heritabilitie in thee tudie were lightly greater for weight lo and lower for back fat lo. In the current tudy, STAY wa defined a a binary trait with ucce (1) if the ow wa ineminated again after firt litter and a failure (0) if he wa culled after firt litter. The etimated heritability of the current tudy wa 0.10, which wa lightly lower than etimate obtained by Aamundtad et al. (2014) for the ame breed (0.13). The trait were not identically defined, a Aamundtad et al. (2014) defined STAY a ability to give birth to a econd litter, rather than inemination for a new litter. Knauer et al. (2011) defined tayability in the ame way a Aamundtad et al. (2014), included only firt litter ow and analyzed the trait in a threhold model (0.14). The heritability of a threhold model i not directly comparable with that of a linear model. An ordinal threhold model may be beneficial for analyi of both BCSw and STAY, a imulation tudie have hown that threhold model are beneficial to ue for categorical trait and are expected to give better etimate of the underlying heritability and increaed genetic gain if higher accuracy i achieved (Meuwien et al., 1995; Abdel- Azim and Berger, 1999). Still, in real data tudie, the ue of threhold model i challenging becaue of an increaed computational burden when working with large data et, and extra gain have been limited (Varona et al., 1999; Ødegård et al., 2006). Ødegård et al. (2006) concluded that a longitudinal linear tet day model for urvival in Atlantic almon gave the highet predictive ability when compared with a threhold model and variou other model. However, thee method are rarely implemented in organized breeding program, a they are computationally challenging. Stayability up to inemination for a econd litter i a complex trait, influenced by everal trait uch a reproduction and lamene and alo environmental factor uch a herd management and temperature. A low heritability might be expected, a the genetic component of STAY may be difficult to depict. Thi might be becaue the binary outcome of the trait not only i a reult of ow biological capacity of coming into heat or producing a litter but alo becaue an inemination i an active deciion made by the farmer. Thi deciion i partly baed on ow biological capacity and partly a ubjective judgment from the farmer. The ow in the herd in thi data et were elected to be ineminated for a econd litter or not baed on their total merit index and phenotypical functionality. Hence, the oberved tayability i not only a reult of the ow biological capacity for a econd litter but alo an active deciion made by the farmer partly influenced by the aumed EBV at the time of inemination or culling. Thi mean that ow with poor EBV are not necearily ineminated with a econd litter, even though they are capable. Aamundtad et al. (2014) performed a genetic analyi of tayability, comparing model with and without the fixed covariate of the animal total merit index at time of culling. Incluion of the total merit index a a covariate actually increaed the etimated heritability for the tayability trait. Thi may be explained by everal major change in the breeding goal of Norwegian Landrace in the pat (and, therefore, in the compoition of the total merit index), and correcting for thi may have removed ome of the noie in the recorded phenotype (Aamundtad et al., 2014). Furthermore, Aamundtad et al. (2014) might have improved the model by comparing the EBV of the culled animal with the within-herd level at time of culling, intead of population average. The genetic variation in LME and FE wa rather low for both trait, and Martinen et al. (2015) found that LME and FE explained 12 and 20%, repectively, of the total genetic variation in FI. Thi uggeted that a rather mall part of FI wa explained by LME and FE. The trait FE rather than LME explained a bigger part of the genetic variation in FI, and the tudy propoed that thi might be caued by the election trategy for Norwegian Landrace. The etimated heritability for FI wa 0.59 and wa calculated with the ame formula a the ow trait, but the calculation of σ a 2 wa baed on the variance component for RFI, LME, and FE (Martinen et al., 2015). Lower heritability etimate have been found for total feed conumption in performance tet by earlier tudie (Kerr and Cameron, 1996; Holm et al., 2004). The model ued for analyi of FI in thi tudy wa very complex. The reidual variance decreaed ubtantially a lean meat and fat were included in the model and may be the reaon for the increaed heritability when model [1] wa ued in

7 Boar feed efficiency and ow performance 3165 contrat to model [2] (Table 3). Model [1] ha a heterogeneou genetic variance (due to difference in lean meat and fatne) and a contant error variance, which implie that the genetic variance i modeled with more flexibility than the error variance. Thi may have reulted in the genetic factor capturing ome of the reidual heterogeneity. Therefore, an extenion of model [1] would be to introduce alo heterogeneou error variance, which would be a function of the lean meat and fat content (kg). No ignificant change were oberved in the heritabilitie for the ow trait when model [2] wa ued for FI, a expected. Genetic Correlation In pork production, daily feed intake i a conflict of interet between the market hog producer and the piglet producer (Holm et al., 2004). For a market hog producer, low feed intake and high growth i important to maintain a good profit. For the piglet producer, a large appetite and high daily feed intake in the ow i crucial to produce large and heavy litter and to avoid high weight lo (Eien et al., 2003). No information wa available on the ow feed intake in thi tudy, but the ow production (TLW) and BCSw could give an indication whether their feed intake wa ufficient during lactation. To look at the genetic relationhip between the new feed efficiency trait and thee ow trait would be beneficial to ee if potential election for thee new trait would have a deleteriou effect on thee important ow trait. No ignificant correlation were etimated between any of the feed efficiency meaure and TNB. Other tudie have alo found low or nonignificant correlation between reproductive performance in ow and production trait in boar (Hermech et al., 2000; Holm et al., 2004; Imboonta et al., 2007). Kaufmann et al. (2000) tated that the maternal genetic effect of the ow wa a more important part of piglet weight at birth and weaning than the animal own direct genetic effect, and Grandion et al. (2002) upported thi concluion. An incluion of the maternal genetic effect in the model for analyzing piglet production might have been ueful to depict a genetic correlation between efficiency trait and piglet production trait. The carca of a pig conit of lean meat, fat, and bone. In Norwegian Landrace, there i minimal variation in the ize of bone compared with lean meat and fat (Norwegian Meat and Poultry Reearch Centre, 2012). Therefore, more fat at a given BW uually implie le lean meat and vice vera. Thi relationhip may explain the overall oppoite ign for the correlation between the ow trait and FE and between the ow trait and LME. If an animal conume a given amount of feed, it i ditributed to mucle or fat depoition. If the animal ha a high mucle growth, it mot likely depoit le fat tiue. Thi doe not necearily make the animal fat inefficient, a the energy cot of depoiting 1 kg fat may be imilar. The Sow Trait and Reidual Feed Intake of the Animal. The ow data material in thi tudy conited of record on firt parity ow. Firt parity ow have a greater rik of lo of body reerve during lactation compared with multiparou ow. Thi i due to not only their extra nutritional requirement for growth in addition to milk production and maintenance but alo their general lower feed intake capacity (Whittemore, 1996; Thingne et al., 2012). Boddicker et al. (2011) found that animal elected for low reidual feed intake ate le than a randomly elected group, epecially in the econd half of the growth period (after 50 kg). Thee biological retriction in firt parity ow might influence the genetic relationhip between RFI and BCSw. In a review article, Veerkamp (1998) howed tudie where poitive correlation were found between live weight and DMI in cow. Dunnington and Siegel (1996) howed that chicken line elected for high BW had a ignificantly greater feed intake than the line elected for low BW. In addition, animal elected for low reidual feed intake tended to have a higher BW lo from farrowing to weaning than animal elected for high reidual feed intake (Gilbert et al., 2012). Thee finding may upport the current tudy poitive genetic correlation between RFI and BCSw in ow, uggeting that animal with a high overall feed intake in the growth period had an increaed BCSw. The genetic relationhip between reidual feed intake and ow performance i not clearly etablihed in the literature. Thi tudy found no ignificant genetic correlation between RFI and piglet production (TNB and TLW), in accordance with Gilbert et al. (2012), who etimated weak and nonignificant correlation between reidual feed intake and total number of piglet born and litter weight at 3 wk. In contrat, Young et al. (2010) invetigated animal elected for reduced reidual feed intake over 6 generation and found that the line elected for low reidual feed intake had a greater number of piglet in the litter and the piglet were heavier at birth. However, the tudy concluded that the ow had a greater body reerve lo than the control line. Baed on the preent and earlier tudie, it might eem a if the genetic relationhip between the reidual feed intake in the growth period and ow performance i rather weak. However, election for reduced reidual feed intake in the growth period might improve ow ability to mobilize body reerve for piglet production. The Sow Trait and Fat Efficiency. The ignificant unfavorable genetic correlation between FE and STAY uggeted that animal that ued a high amount of feed to produce 1 kg of fat had a better chance of taying in

8 3166 Martinen et al. the herd. We found a poitive correlation between fat content on the carca (kg) and FE (unpublihed reult), implying that the animal with high fat content on the carca were le fat efficient. Poibly, animal that overeat would produce more fat and appear le fat efficient. In the end, thi overeating would reult in the converion of protein from feed to fat on the carca, which i a highly inefficient ue of feed. However, thi may be beneficial for the ow a an energy reource for piglet production, which affect STAY. Thi explanation i upported by the ignificant poitive correlation between FE and TLW (0.21), which ignifie that animal that are le fat efficient produce heavier litter. Koltad (2001) invetigated the fat depoition in Norwegian Landrace and Duroc. They argued that due to the election criteria, a relatively high proportion of total fat in Norwegian Landrace wa depoited a viceral fat. The tudy alo mentioned the importance of including depoition of viceral fat for the efficiency in pig production. When modeling FE in thi tudy, the amount of viceral fat wa not included in the analyi, only FAT etimated from the CT image. Viceral fat depoition wa, therefore, not directly corrected for in the model, although a poitive genetic correlation between viceral and FAT exit (D. Olen, Topig Norvin, Hamar, Norway, peronal communication). It i, therefore, poible that animal that eemed inefficient in fat depoition had depoited a high amount of viceral fat in their body, which i not included in the CT image analye. A correction for the laughter percentage (i.e., amount of viceral fat) in model [1] wa performed to invetigate whether FE wa dependent on where the fat wa depoited. The reult indicated that laughter percentage did not have an effect on FE. No change were oberved in the reult when laughter percentage wa included in the model. Thi uggeted that the finding of the current tudy are robut, even though viceral fat i not included in the analyi of FE. The Sow Trait and Lean Meat Efficiency. The amount of feed ued to produce 1 kg lean meat did not have any ignificant genetic relationhip with any of the ow trait. Hermech et al. (2000) etimated genetic correlation between FCR and reproduction trait in ow. They found a negative but low and favorable correlation between FCR and litter weight at birth. Lean meat efficiency in the current tudy decribe the feed needed for lean meat depoition and i a more pecific meaure of feed efficiency. The genetic correlation between LME and litter weight howed the ame relationhip a Hermech et al. (2000) but were not ignificant. Our reult uggeted that overall LME hardly affected the ow trait. Thi tudy found a ignificant correlation between RFI and BCSw, which ugget that election for RFI could reult in ow with poor BCSw. Becaue no genetic relationhip between LME and the ow trait were found, thi new trait could be le related to ow trait than traditional reidual feed intake. Implication The reult indicated that the genetic relationhip between the new feed efficiency meaurement and the ow trait in general were mall and not ignificantly different from 0 for Norwegian Landrace. Significant genetic correlation were found between FE and STAY and between FE and TLW (0.21 and 0.21, repectively), uggeting that election for better FE in boar may reduce TLW in firt parity ow and reult in poorer STAY. Lean meat efficiency had no ignificant genetic relationhip with the ow trait. To meet future challenge with the maternal line, LME make it poible to elect animal that have genetic potential to depoit lean meat efficiently at low feed cot, without affecting economically important ow trait uch a STAY, BCSw, TLW, and TNB. LITERATURE CITED Aamundtad, T., D. Olen, E. Seheted, and O. 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