The impact of genetic merit on ewe performance and efficiency parameters

Abstract

The aim of this study was to investigate the impact of ewe genetic merit on ewe performance and efficiency parameters. The study consisted of three genetic merit groups (New Zealand (NZ), High Irish and Low Irish) and ran from 2016 to 2019, inclusive. Each genetic merit group contained 30 purebred Suffolk and 30 purebred Texel ewes, that were selected based on their maternal genetic indexes in their country of origin namely Ireland (€uro-star Replacement index) or New Zealand (New Zealand Maternal worth). Ewe body condition score (BCS), ewe body weight (BW), milk yield, milk composition, dry matter intake (DMI) and efficiency parameters were all analysed using linear mixed models. Ewe BW was similar across all genetic merit groups at each time point (P>0.05). In comparison to both High and Low Irish ewes, NZ ewes had a higher BCS at mating, mid-pregnancy, lambing, wk 10 post-lambing (PL, P<0.05). Ewe BW change was similar across genetic merit groups, except between mating and mid-pregnancy where ewe BW loss was greater for NZ ewes than Irish ewes (P<0.05) and between wk 6 PL and wk 10 PL where NZ ewes gained BW and High and Low Irish ewes lost BW (P<0.01). Ewe milk yield, milk fat, total solids and gross energy content was superior for milk produced by NZ ewes at wk 6 PL in comparison to milk produced by High Irish and Low Irish ewes (P<0.01). New Zealand ewes produced a greater quantity of milk solids/kg of BW at wk 6 PL compared to High Irish ewes (P<0.01), while Low Irish ewes did not differ from either NZ or High Irish (P>0.05). Low Irish ewes had a greater daily DMI than High Irish ewes in late lactation (wk 10 PL, P<0.05) and had a greater DMI/kg of ewe BW compared to the High Irish ewes at the same time point (P<0.05). New Zealand ewes weaned a litter BW equivalent to 60.4 % of their mating BW, which was more than the Low Irish ewes who weaned 57.1 % of the ewe’s BW at mating (P<0.01), while the High Irish ewes did not differ from either the NZ or Low Irish ewes at 59.3 % of the ewe’s BW at mating (P>0.05). This paper presents a range parameters across ewes of high and low genetic merit, demonstrating the ability to achieve gains through selection of animals of high genetic merit. Sheep producers should consider genetic indexes as a tool to assist in the decision making process of selecting replacement ewes and/or breeding rams, once satisfied the animal is correct and meeting the breeding objectives of the system.

Validation of maternal and terminal sheep breeding objectives using Irish field data

“…However, a greater difference in age at slaughter was observed between animals of high and low genetic merit based on the terminal index (8.34 d) compared to the maternal index (4.45 d), suggesting that the terminal index is selected strongly for lamb postweaning growth potential. The magnitude of the differences between animals of high and low index in the present study was greater than those reported by Fetherstone et al (2021a) for traits including lamb survival and number of lambs born, but very similar in terms of lamb live weights pre and weaning to those reported previously by Márquez et al (2012) at both 5 (+0.3 kg) and 10 (+0.5 kg) weeks of age.…”

“…The use of selection index theory ( Hazel, 1943 ) to generate a single value of the genetic merit of an animal, is commonly used across farmed species including sheep ( Conington et al, 2004 ; Swan et al, 2007 ; Santos et al, 2015 ), goats ( Ziadi et al, 2021 ), beef ( Twomey et al, 2020 ), and dairy ( Miglior et al, 2005 ). Rates of genetic gain or response to selection are commonly modeled for individual traits for sheep ( Swan et al, 2007 ; Casellas et al, 2015 ; Santos et al, 2017 ), less commonly reported in the literature is the validation of breeding objectives ( Connolly et al, 2016 ; Twomey et al, 2020 ), this is especially true for sheep, where validation studies have tended to focus on specific traits ( Conington et al, 1998 ) or on controlled experiments ( Márquez et al, 2012 ; Fetherstone et al, 2021a , 2021b ). Access to a national database, such as was available in the present study allows, firstly large numbers of animals to be accessed per trait (range 9,197 to 47,169 in the present study) and secondly allows animals to be compared in a commercial environment.…”

“…Genetic gain, however, remains a function of how accurately the breeding objectives reflect differences in the phenotypic performance of animals. Although validation of sheep breeding objectives has been reported previously, these tended to be performed under controlled experiments both in Ireland ( Fetherstone et al, 2021a , 2021b ) and elsewhere ( Conington et al, 1998 ; Márquez et al, 2012 , 2013 ). Large-scale validation of breeding objectives using field data in sheep is not often described in the scientific literature.…”

Investigating How Genetic Merit and Country of Origin Impact the Profitability of Grass-Based Sheep Production Systems

“…The key performance indicators for each scenario, describing reproductive performance and lambing [4], lamb growth and performance [6], and ewe efficiency and performance [5] were retrieved and inputted to the TLPM, as outlined in Tables 1 and 2. Selection indices for this study were based on those used in the Irish national breeding objectives [1] and hosted by Sheep Ireland (https://www.sheep.ie; accessed on 10 January 2021).…”

“…The validation of genetic indexes is essential in order to increase farmers’ confidence in breeding programmes and to demonstrate that genetic progress can be achieved through the use of animals of superior genetic merit. Previous research on the impact of maternal genetic merit and country of origin on the productivity of sheep production systems has shown that differences exist in reproduction and lambing performance [ 4 ], lamb growth and performance [ 5 ], and ewe performance and efficiency [ 6 ]. Although differences were often biologically small between the three genetic-merit groups within the previously reported literature, the overall financial impact of the accumulation of these differences at the full farm-system level has not been investigated to date.…”