Introduction
Goats have significant social and economic importance in many parts of the world (Castel et al., Reference Castel, Ruiz, Mena and Sanchez-rodríguez2010). They are known for their ability to adapt to various production systems and environments that may be unsuitable for other livestock species (Oliveira et al., Reference Oliveira, Brasil, Delgado, Peguezuelos, León, Guedes, Arandas and Ribeiro2016). The Murciano-Granadina goat breed is a well-known dairy breed in Spain with international importance, having been exported to several countries (Martinez et al., Reference Martinez, Vega-Pla, Leon, Camacho, Delgado and Ribeiro2010). The Murciano-Granadina goat breed was synthesized in 1975 from the Murciana and Granadina goat breeds in the semi-arid areas in southeastern Spain. The main phenotypic characteristics of the Murciano-Granadina goat breed include a straight or sub-concave profile, a medium-sized body with a tendency to lengthen with black or brown uniform coat colour, and 77 cm and 70 cm high at the withers in males and females, respectively (Delgado et al., Reference Delgado, Landi, Barba, Fernández, Gomez, Camacho, Martínez, Navas, Leon, Simoes and Gutierrez2017). Factors such as the globalization of the economy are putting pressure on the profitability of dairy goat farms and related activities, including meat production (Zurita-Herrera et al., Reference Zurita-Herrera, Delgado, Arguello and Camacho2011).
The body weight of domestic animals at different ages has an important effect on the profitability of flock holders. Thus, these characteristics may be regarded as important selection criteria in any production system (Tosh and Kemp, Reference Tosh and Kemp1994). Improving the growth performance of domestic animals requires knowledge on both genetic and non-genetic effects which are necessary for developing efficient breeding programmes. From a genetic point of view, the implementation of an appropriate breeding programme requires accurate estimates of breeding values for animals and genetic parameters for important traits (Zishiri et al., Reference Zishiri, Cloete, Olivier and Dzama2013). Estimates of genetic parameters for growth traits in several goat breeds have been reported, including Naeini (Baneh et al., Reference Baneh, Najafi and Rahimi2012), Raeini Cashmere (Mohammadi et al., Reference Mohammadi, Moradi Shahrebabak and Moradi Shahrebabak2012; Mokhtari et al., Reference Mokhtari, Razmkabir, Ghiasi and Mohammadi2019), Markhoz (Rashidi et al., Reference Rashidi, Bishop and Matika2011; Hosseinzadeh Shirzeyli et al., Reference Hosseinzadeh Shirzeyli, Joezy-Shekalgorabi, Aminafshar and Razmkabir2023), Beetal (Magotra et al., Reference Magotra, Bangar, Chauhan, Malik and Malik2021) and Inner Mongolia White Arbas Cashmere (Wang et al., Reference Wang, Liu, Shi, Qi, Li, Wang, Zhang, Zhao, Su and Li2023) breeds.
In livestock, growth-related traits of animals are influenced not only by their genetic potential but also by maternal effects (Wilson and Reale, Reference Wilson and Reale2006). Any effects the female parent exerts on the phenotype of its progeny can be considered maternal effects (Falconer and Mackay, Reference Falconer and Mackay1996). The genotype of the dam and related environmental factors can influence the dam's ability for milk production, health status, intrauterine conditions and mothering ability (Maniatis and Pollott, Reference Maniatis and Pollott2003). Therefore, maternal effects can be divided into genetic and environmental components. The contribution of maternal effects to phenotypic variation among offspring is considered a criterion in selection programmes in various species (Magotra et al., Reference Magotra, Bangar, Chauhan, Malik and Malik2021).
In multiparous species such as goats, maternal environmental effects can be partitioned into permanent and temporary components. However, the latter has been ignored in most genetic studies on the growth traits of goat breeds (Tesema et al., Reference Tesema, Alemayehu, Getachew, Kebede, Deribe, Taye, Tilahun, Lakew, Kefale, Belayneh, Zegeye and Yizengaw2020; Singh et al., Reference Singh, Dige, Pourouchottamane, Kumar and Gowane2022; Hosseinzadeh Shirzeyli et al., Reference Hosseinzadeh Shirzeyli, Joezy-Shekalgorabi, Aminafshar and Razmkabir2023). In species having several progenies per parturition, progenies (full sibs) share a common environment that contributes to their similarity, which is a further source of variation among families (Falconer and Mackay, Reference Falconer and Mackay1996). This similarity refers to common factors such as nutrition, maternal common care and climatic conditions (Abbasi et al., Reference Abbasi, Abdollahi-Arpanahib, Maghsoudi, Vaez Torshizi and Nejati-Javaremi2012). In general, the effects arised from these common factors are called maternal temporary environmental or common litter effects. They are common among the litters of a specific dam within each birth year of offspring. The importance of including litter effects in models used for genetic evaluation of growth traits of goats well documented (Rashidi et al., Reference Rashidi, Bishop and Matika2011; Menezes et al., Reference Menezes, Sousab, Cavalcanti-Filhoc and Gamad2016; Rout et al., Reference Rout, Matika, Kaushik, Dige, Dass, Singh and Bhusan2018). Ghafouri-Kesbi et al. (Reference Ghafouri-Kesbi, Zaman and Mokhtari2022) remembered that including the litter effects in model, fitted the data substantially better than corresponding model which excluded this effect.
In 2015, the private sector imported 3000 Murciano-Granadina goats from Spain to the southern region of Iran. This initiative aimed to improve the production efficiency of low-input and low-output local goat breeding farms and enhance the livelihoods of rural flock holders in the southern areas of the country. To achieve this goal, purebred Murciano-Granadina does and bucks were distributed to local flocks or considered for crossbreeding with local goat breeds. In Iran, local farmers often keep goat breeds for their multi-purpose applications, including fibre, meat and milk production. Although the Murciano-Granadina goat breed is primarily considered for dairy production purposes, understanding the genetic and phenotypic aspects of growth performance in this breed can provide the required information for designing appropriate breeding strategies that incorporate both Murciano-Granadina and local goat breeds in the future. In a recently published study, Mokhtari et al. (Reference Mokhtari, Esmailizadeh, Mirmahmoudi, Gutierrez and Modebbinejad2023) compared non-linear models describing growth trajectory and estimated genetic parameters for growth curve traits in the Murciano-Granadina goats.
The main objective of the present investigation was to estimate the genetic and phenotypic parameters of the early growth performance of the Murciano-Granadina goat breed by quantifying the importance of maternal effects on early growth traits.
Materials and methods
Flock management
The Murciano-Granadina goat flock studied herein has been managed under an intensive production system on a private dairy farm in Ghale-Ganj city, the southern region of Kerman province, Iran. Newborn kids were weighed and ear-tagged at birth, and information on their sex and birth type, as well as the identities of their dam and sire, were recorded. Weaning was at approximately 80 days of age. Kids were kept indoors and manually fed. Maiden does were exposed to the fertile bucks at about 11 months of age and 25 kg live body weights in separate groups with a ratio of 15 does per fertile buck (Mokhtari et al., Reference Mokhtari, Esmailizadeh, Mirmahmoudi, Gutierrez and Modebbinejad2023). Health care and veterinary practices including vaccination and antiparasitic drugs administration were performed according to the flock's routine protocols.
Data collection and evaluated traits
In this study, pedigree information and data on body weights of Murciano-Granadina kids from birth to weaning were collected from multiple parities of does between the years 2016 and 2022. The data and pedigree were carefully screened and edited several times, and lambs with incorrect information were removed from the dataset. The ENDOG v4.8 program was applied for checking errors in the pedigree and preparing it for subsequent analyses (Gutierrez and Goyache, Reference Gutierrez and Goyache2005). The pedigree structure of the investigated population is shown in Table 1. Among the registered goats, those with both sire and dam were known (complete recorded pedigree), with both sire and dam were unknown (no recorded pedigree), and with one of the sire and/or dam was known (incomplete recorded pedigree) represented 0.88, 0.11 and 0.01 of all kids, respectively. In the studied population, animals without offspring and animals with offspring were 0.69 and 0.31 of the total registered animals, respectively.
Pedigree structure of the population of the Murciano-Granadina goat breed
Individuals with body weights outside the range of overall means ± 3 × standard deviations (SD) were excluded from the dataset. The investigated traits included birth weight (BW), weaning weight (WW), pre-weaning average daily gain (ADG) calculated as ((WW-BW)/weaning age) × 1000, pre-weaning Kleiber Ratio (KR) calculated as ADG/WW0.75 and pre-weaning growth efficiency (GE) calculated as ((WW-BW)/BW) × 100. Table 2 presents the descriptive statistics for the growth traits analysed in this study.
Descriptive statistics for the studied growth traits in the Murciano-Granadina goat breed
S.D., standard deviation; C.V., coefficient of variation; Min., Minimum; Max., Maximum; BW, birth weight; WW, weaning weight; ADG, average daily gain from birth to weaning; KR, Kleiber ratio from birth to weaning; GE, growth efficiency from birth to weaning.
a KR values are multiplied by 1000.
Statistical analyses
The general linear model (GLM) procedure of SAS 9.1 software (SAS, 2004) was used to determine significant fixed effects in the models considered for genetic analyses. Tukey-Kramer test was applied to compare the mean of the traits of interest across different levels of the considered fixed effects. Fixed factors considered in the models for the investigated growth traits were the sex of kids in 2 levels (males and females), birth type in 2 levels (single, multiple births), age of dam at kidding in 5 levels (1–5 years old), birth year in 7 levels (2016–2022) and birth month in 12 levels. The ages of kids at weaning weight (in days) were fitted as a linear covariate for WW.
Initially, the impact of maternal effects on the variance components of the traits was evaluated. Models incorporating combinations of direct additive genetic, maternal additive genetic, maternal permanent environmental and maternal temporary environmental or litter (dam within a year) effects (models 1–9) were fit to the growth traits under investigation. The tested models were as follows:
where, y represents the vector of records for the investigated traits; b, a, m, pe, l and e stand for vectors of fixed, direct additive genetic, maternal additive genetic, maternal permanent environmental, maternal temporary environmental (litter) and the residual effects, respectively. The matrices of X, Z1, Z2, Z3 and Z4 are design matrices associating corresponding effects to vector y. It was assumed a ~ N(0, A$\sigma _a^2$
), m ~ N(0, A$\sigma _m^2$
), pe ~ N(0, ${\boldsymbol I}_{{\boldsymbol pe}}\sigma _{pe}^2$
), l ~ N(0, ${\boldsymbol I}_{\boldsymbol l}\sigma _l^2$
) and e ~ N(0, ${\boldsymbol I}_{\boldsymbol n}\sigma _e^2$
). A is the numerator relationship matrix, σ am shows covariance between direct additive and maternal additive genetic effects. Ipe, Il and In are identity matrices of appropriate dimensions. Furthermore, $\sigma _a^2$
, $\sigma _m^2$
, $\sigma _{pe}^2$
, $\sigma _l^2 \;$
and $\sigma _e^2$
are direct additive genetic, maternal additive genetic, maternal permanent environmental, maternal temporary environmental (litter) and residual variances, respectively. The best model for each trait was determined by applying the Akaike information criterion (AIC) (Akaike, Reference Akaike1974), which was computed as follows:
where Log L is the maximized Log of likelihood and p is the number of parameters to be estimated by the model. For each trait, the model with the lowest AIC was considered the most appropriate. The estimates of genetic, phenotypic and residual correlations between the studied traits were obtained by applying bi-variate animal models, by using the best univariate animal model determined for each trait. Genetic analyses were performed using the WOMBAT program (Meyer, Reference Meyer2013).
Results
The coefficient of variation was lowest for WW (13.11%) and highest for GE (26.66%). Male and female kids accounted for approximately 0.48 and 0.52 of the newborn kids, respectively. A similar trend was observed for the proportion of male and female kids at weaning. Single-born and multiple births kids comprised around 0.42 and 0.58 of the newborn kids, respectively.
Non-genetic effects influencing the studied growth traits
The least squares means of the investigated growth traits of the Murciano-Granadina goat across the levels of the considered fixed effects are presented in Table 3. The birth year and birth month of kids significantly affected all the studied growth traits (P < 0.01). The sex of kids significantly affected all the studied growth traits (P < 0.01). Male kids have significantly higher pre-weaning growth rates, Kleiber ratios and growth efficiency than female kids (P < 0.01). Furthermore, they were generally heavier than the females at birth and at weaning time. The birth type of Murciano-Granadina kids had a significant effect on all the studied growth traits (P < 0.01). The single-born Murciano-Granadina kids were superior to multiple births for all the studied growth traits. Dam age significantly affected on all the studied growth traits of the Murciano-Granadina kids (P < 0.01).
Least squares means (± S.E.) for the studied growth traits of the Murciano-Granadina goat breed
BW, birth weight; WW, weaning weight; ADG, average daily gain from birth to weaning; KR, Kleiber ratio from birth to weaning; GE, growth efficiency from birth to weaning.
n, number of records.
a KR values are multiplied by 1000.
Genetic parameter estimates
Model comparisons
The results of model comparisons by using AIC (Table 4) revealed that the maternal effects influenced all the studied early growth traits in the Murciano-Granadina kids. Among the tested models, the best model of genetic analysis determined for BW, included direct additive, maternal additive, maternal permanent and litter effects, without considering covariance between direct and maternal additive genetic effects (Model 8), while the best model detected for ADG, KR and GE included direct additive, maternal permanent and litter effects (Model 5). The model including direct additive and maternal additive genetic effects, ignoring covariance between these effects, was determined as the best model for WW (Model 3).
Akaike information criterion (AIC) values for the studied traits in the Murciano-Granadina goat breed under different models
BW, birth weight; WW, weaning weight; ADG, average daily gain from birth to weaning; KR, Kleiber ratio from birth to weaning; GE, growth efficiency from birth to weaning.
Univariate analyses
The estimates of variance components and genetic parameters for the studied early growth traits in the Murciano-Granadina goats under the best univariate model are given in Table 5. The estimated direct heritabilities for BW, ADG, KR, GE and WW were low, with values of 0.04, 0.07, 0.08, 0.05 and 0.07, respectively. In the present study, maternal additive genetic effects were only important for the genetic analysis of BW and WW. Maternal heritability estimates for BW and WW were 0.03 and 0.04, respectively. Except for WW, all the studied traits were affected by maternal permanent environmental and maternal temporary environmental (litter) effects. The ratios of maternal permanent environmental variance to phenotypic variance (pe2) were 0.08, 0.04, 0.04 and 0.06 for BW, ADG, KR and GE, respectively. The ratios of maternal temporary environmental or litter variance to phenotypic variance (l2) were 0.26, 0.17, 0.16 and 0.19 for BW, ADG, KR and GE, respectively.
Estimates of variance components and genetic parameters for the studied early growth traits in the Murciano-Granadina goat breed under the best univariate model
BW, birth weight; WW, weaning weight; ADG, average daily gain from birth to weaning; KR, Kleiber ratio from birth to weaning; GE, growth efficiency from birth to weaning.
$\sigma _e^2$
: residual variance, $\sigma _p^2$
: phenotypic variance,$\;h_a^2$
: direct heritability,$h_m^2$
: maternal heritability, pe 2: ratio of maternal permanent environmental variance to phenotypic variance, l 2: ratio of litter variance to phenotypic variance.
Multivariate analyses
The estimates of genetic, phenotypic and environmental correlations among the studied growth traits of the Murciano-Granadina goat are shown in Table 6. The estimates of genetic correlations among the studied traits were positive and low to high in magnitude, which ranged from 0.11 for BW-KR to 0.91 for BW-GE. The phenotypic correlations ranged from 0.03 for KR-WW to 0.87 for ADG-KR. In the present study, the maternal genetic correlation estimate between BW and WW was obtained at 0.47. Maternal permanent environmental correlations were also positive and ranged from a low estimate of 0.08 for BW-KR to a high estimate of 0.82 for BW-GE. In the present study, correlations related to litter effects were positive and ranged from low (0.07 for BW-ADG) to high (0.92 for ADG-KR) estimates.
The estimates of genetic, phenotypic and environmental correlations among the studied traits of the Murciano-Granadina goat breed
BW, birth weight; WW, weaning weight; ADG, average daily gain from birth to weaning; KR, Kleiber ratio from birth to weaning; GE, growth efficiency from birth to weaning; ra, direct genetic correlation; rpe, maternal permanent environmental correlation; rl, maternal temporary environmental (litter) correlation; re, residual correlation; rp, phenotypic correlation.
Discussion
The considered fixed effects were significant sources of variation for all the studied growth traits of Murciano-Granadina kids. Therefore, these effects should be included in the models used for the genetic evaluation of the Murciano-Granadina kids for early growth performance traits. The significant influences of these fixed effects on the growth traits of several goat breeds have been well documented (Baneh et al., Reference Baneh, Najafi and Rahimi2012; Barazandeh et al., Reference Barazandeh, Moghbeli, Vatankhah and Mohammadabadi2012; Mokhtari et al., Reference Mokhtari, Razmkabir, Ghiasi and Mohammadi2019; Singh et al., Reference Singh, Dige, Pourouchottamane, Kumar and Gowane2022; Hosseinzadeh Shirzeyli et al., Reference Hosseinzadeh Shirzeyli, Joezy-Shekalgorabi, Aminafshar and Razmkabir2023). The significant effects of birth year and birth month of kids on the studied traits may be explained partly by variations in annual weather conditions and flock management practices during the period of study (Hosseinzadeh Shirzeyli et al., Reference Hosseinzadeh Shirzeyli, Joezy-Shekalgorabi, Aminafshar and Razmkabir2023; Wang et al., Reference Wang, Liu, Shi, Qi, Li, Wang, Zhang, Zhao, Su and Li2023). Sexual differences were found between the male and female Murciano-Granadina kids for the studied growth traits. The sexual-related differences in growth performance of kids may be the result of different physiological characteristics, and also different hormone types and hormone secretion, especially sexual hormones such as Oestrogen (Aguirre et al., Reference Aguirre, Mattos, Eler, Barreto Neto and Ferraz2016). The superiority of the single-born Murciano-Granadina kids over multiple births kids in early growth performance may be justified to some extent by the fact that the single-born kids can benefit more from the whole uterine and maternal environment than multiple births kids. Therefore, the kids with multiple births will receive less nutrition from the dam (Boujenane and Diallo, Reference Boujenane and Diallo2017). The effect of dam age on the studied traits may be ascribed to several factors such as the growth stage, higher mothering ability, reproductive performance and the higher milk yield of does at older ages (Hosseinzadeh Shirzeyli et al., Reference Hosseinzadeh Shirzeyli, Joezy-Shekalgorabi, Aminafshar and Razmkabir2023). Mothering ability may lead to a better uterus capacity and maternal behaviour of the dams.
The low estimates of direct heritability for the studied growth traits in the Murciano-Granadina breed in this study indicated that direct genetic selection for these traits may not result in significant genetic progress, due to the low levels of direct additive genetic variation. Such lack of genetic variability in pre-weaning growth traits has also been reported by Bangar et al. (Reference Bangar, Magotra and Yadav2020) in the Jakhrana goat breed. Menezes et al. (Reference Menezes, Sousab, Cavalcanti-Filhoc and Gamad2016) reported direct heritability estimates for BW, WW and ADG in Boer goats as 0.08, 0.23 and 0.31, respectively. These estimates were higher than the corresponding estimates in the present study. Higher direct heritability estimates of 0.22, 0.12 and 0.25 for BW, ADG and WW, respectively, were reported in Raeini Cashmere goats (Mohammadi et al., Reference Mohammadi, Moradi Shahrebabak and Moradi Shahrebabak2012). Mokhtari et al. (Reference Mokhtari, Razmkabir, Ghiasi and Mohammadi2019) reported direct heritability estimates of 0.08 and 0.07 for pre-weaning average daily gain and growth efficiency in Raeini Cashmere goats, which were in agreement with the corresponding estimated direct heritabilities of the Murciano-Granadina goat breed in the present study (0.07 for ADG and 0.05 for GE). They also reported a value of 0.19 for direct heritability of pre-weaning KR in Raeini Cashmere goat, which was higher than the estimated values for KR in the present study. There is limited information on genetic parameter estimates of growth efficiency-related traits of goat breeds in the literature. Direct heritability estimates of 0.07 and 0.06 for pre-weaning growth efficiency in Makooei (Ghafouri-Kesbi and Abbasi, Reference Ghafouri-Kesbi and Abbasi2019) and Baluchi (Ghafouri-Kesbi and Gholizadeh, Reference Ghafouri-Kesbi and Gholizadeh2017) sheep breeds were close to the direct heritability estimate of GE in the present study (0.05). Bangar et al. (Reference Bangar, Magotra and Yadav2020) reported estimates of 0.09, 0.21, 0.17 and 0.06 for direct heritabilities of birth weight, three-month weight, pre-weaning average daily gain and pre-weaning Kleiber ratio in the Jakhrana goat breed, respectively. Estimates on genetic parameters for growth efficiency traits in goat breeds are limited.
As expected, maternal effects constitute sizeable parts of the phenotypic variations for all the studied growth traits of the Murciano-Granadina kids. Maternal effects increase sibling resemblance and, if not included in models used for genetic evaluation animals, may bias estimates of direct heritability upward (Singh et al., Reference Singh, Dige, Pourouchottamane, Kumar and Gowane2022). In this study, maternal additive genetic effects were important for the genetic evaluation of the BW and WW of the Murciano-Granadina kids. Maternal permanent and also maternal temporary environmental effects were also important genetic evaluation of the Murciano-Granadina kids for all the studied traits except for WW. Therefore, it is recommended to account for the maternal effects and additive genetic and environmental factors for estimating genetic parameters of early growth traits in the Murciano-Granadina goat breed. The necessity of considering maternal additive genetic, maternal permanent and maternal temporary environmental effects for genetic evaluation of early growth traits in Markhoz goat remembered by Rashidi et al. (Reference Rashidi, Bishop and Matika2011). In general, the influence of maternal effects on the growth traits has been well-documented in various goat breeds, including Naeini (Baneh et al., Reference Baneh, Najafi and Rahimi2012), Raeini Cashmere (Barazandeh et al., Reference Barazandeh, Moghbeli, Vatankhah and Mohammadabadi2012; Mohammadi et al., Reference Mohammadi, Moradi Shahrebabak and Moradi Shahrebabak2012; Mokhtari et al., Reference Mokhtari, Razmkabir, Ghiasi and Mohammadi2019), Barbari goat (Singh et al., Reference Singh, Dige, Pourouchottamane, Kumar and Gowane2022), Markhoz (Rashidi et al., Reference Rashidi, Sheikhahmadi, Rostamzadeh and Shrestha2008; Hosseinzadeh Shirzeyli et al., Reference Hosseinzadeh Shirzeyli, Joezy-Shekalgorabi, Aminafshar and Razmkabir2023), Jamunapari (Dige et al., Reference Dige, Rout, Singh, Dass, Kaushik and Gowane2021) and Inner Mongolia White Arbas Cashmere (Wang et al., Reference Wang, Liu, Shi, Qi, Li, Wang, Zhang, Zhao, Su and Li2023).
Mohammadi et al. (Reference Mohammadi, Moradi Shahrebabak and Moradi Shahrebabak2012) estimated maternal heritabilities of 0.17 and 0.07 for BW and WW, in Raeini Cashmere goats, respectively. Dige et al. (Reference Dige, Rout, Singh, Dass, Kaushik and Gowane2021) reported the maternal heritability of BW and WW in Jamunapari goats to be 0.11 and 0.26, respectively. In a recently published study, maternal heritability estimates of BW and WW in inner Mongolia white Arbas Cashmere goats were reported at 0.0143 and 0.0246, respectively (Wang et al., Reference Wang, Liu, Shi, Qi, Li, Wang, Zhang, Zhao, Su and Li2023), which were similar to the corresponding estimated values in the present study. In this study, low maternal heritability but statistically significant estimates were obtained for BW (0.03) and WW (0.04) of the Murciano-Granadina kids. Although maternal additive genetic effects explained low proportions of the phenotypic variances for BW and WW in the Murciano-Granadina goat breed, their effects on phenotypic variance were statistically significant, and excluding them from models used for genetic evaluation of these traits may resulted in upward biased direct heritability estimates. Erdogan Atac et al. (Reference Erdogan Atac, Takma, Gevrekci, Ozi Altıncekic and Ayasan2023) estimated genetic parameters for direct and maternal effects on pre-weaning growth traits in Turkish Saanen kids and reported that maternal effects perform a significant role in the expression of pre-weaning growth traits in this breed and including them in models resulted in more realistic variance components.
Maternal permanent environmental effects refer to environmental factors that consistently impact the performance of dams across multiple kiddings. The maternal permanent environmental effects on birth weight are mainly characterized by the uterine capacity of the dam, feeding level at late gestation and maternal behaviour (Ghafouri-Kesbi and Eskandarinasab, Reference Ghafouri-Kesbi and Eskandarinasab2008). In the present study, maternal permanent environmental effects explained low proportions of the phenotypic variances for BW (8%), ADG (4%), KR (4%) and GE (6%) in the Murciano-Granadina goat breed, but their effects on phenotypic variance were statistically significant and including them in models used for genetic evaluation of these traits is necessary. Furthermore, improving the feeding of does at late stage of gestation is of great important for more accurate genetic evaluation of the Murciano-Granadina kids for BW, ADG, KR and GE. Snyman et al. (Reference Snyman, Erasmus, Van Wyk and Olivier1995) showed that excluding the maternal permanent environmental effects could cause maternal heritability to be overestimated.
Snyman et al. (Reference Snyman, Erasmus, Van Wyk and Olivier1995) demonstrated that eliminating the maternal permanent environmental effects could result in maternal heritability being over-estimated. Baneh et al. (Reference Baneh, Najafi and Rahimi2012) reported a pe2 estimate of 0.16 for ADG in the Naeini goat breed, which was higher than the estimated value for ADG of the Murciano-Granadina goat breed in the present study. Singh et al. (Reference Singh, Dige, Pourouchottamane, Kumar and Gowane2022) reported estimates of 0.10 and 0.09 for pe2 of pre-weaning average daily gain and Kleiber ration in Barbari goats, respectively. Mohammadi et al. (Reference Mohammadi, Moradi Shahrebabak and Moradi Shahrebabak2012) estimated a pe2 value of 0.05 for pre-weaning average daily gain in Raeini Cashmere goat, which is in agreement with that obtained for ADG in the present study. Hosseinzadeh Shirzeyli et al. (Reference Hosseinzadeh Shirzeyli, Joezy-Shekalgorabi, Aminafshar and Razmkabir2023) estimated pe2 of 0.09 for BW in Markhoz goat, which is in agreement with the corresponding estimated value for BW in the present study. Bangar et al. (Reference Bangar, Magotra and Yadav2020) estimated pe2 of 0.18 for BW in the Jakhrana goat breed, which was higher than the corresponding estimated value in the present study. In a recently published study, Wang et al. (Reference Wang, Liu, Shi, Qi, Li, Wang, Zhang, Zhao, Su and Li2023) estimated low magnitude values of 0.0567, 0.0246 and 0.0314 for pe2 of BW, pre-weaning average daily gain and pre-weaning KR in inner Mongolia white Arbas cashmere goats, respectively.
In all the examined traits, the maternal temporary environmental effects or litter effects contributed significantly more to the phenotypic variances than other known random sources of variation, such as direct additive genetic, maternal additive genetic (for BW and WW) and maternal permanent environmental effects (for BW, ADG, KR and GE). The maternal temporary environmental or litter effect refers to this fact that kids from the same litter are phenotypically more similar than kids from different litters. Litter effects together with maternal permanent environmental effects allow for greater resemblance between full sibs from the same litter v. similarly related individuals from different litters (Ghafouri-Kesbi et al., Reference Ghafouri-Kesbi, Zaman and Mokhtari2022). Similarly, Menezes et al. (Reference Menezes, Sousab, Cavalcanti-Filhoc and Gamad2016) obtained estimates of 0.32 and 0.15 for l2 of BW and ADG in the Boer goat breed, respectively. Rout et al. (Reference Rout, Matika, Kaushik, Dige, Dass, Singh and Bhusan2018) estimated values of 0.39, 0.29 and 0.29 for l2 of birth weight, average daily gain from birth to three-month body weight and three-month body weight in Jamunapari goats breed, respectively. The estimates of l2 for BW and pre-weaning KR of Markhoz goat were obtained at 0.46 and 0.16, respectively (Rashidi et al., Reference Rashidi, Bishop and Matika2011). Hagger (Reference Hagger1998) studied the influence of litter effects on the early growth rate of two Switzerland sheep breeds and showed that the importance of the litter effects was more pronounced than other direct and maternal effects.
The observed positive genetic and phenotypic correlations suggest that selecting any of the studied growth traits in the Murciano-Granadina goat breed would not result in unfavourable genetic or phenotypic changes in the other traits. In other words, all the studied traits can be improved simultaneously following selection for any of these traits. Positive genetic correlations among the studied traits of the Murciano-Granadina goat breed in the present study represent some degree of pleiotropic effects on these traits, which is more pronounced for BW and GE.
Baneh et al. (Reference Baneh, Najafi and Rahimi2012) estimated values of 0.49, 0.61 and 0.94 for genetic correlations of BW-ADG, BW-WW and ADG-WW in the Naeini goat breed, respectively. They reported phenotypic correlation estimates of 0.03, 0.24 and 0.95 for BW-ADG, BW-WW and ADG-WW in the Naeini goat breed, respectively. These estimates in the Naeini goat breed were higher than the corresponding genetic and phenotypic correlation estimates in the present study. Rashidi et al. (Reference Rashidi, Bishop and Matika2011) reported positive and low to high phenotypic and genetic correlation estimates among the pre-weaning growth traits in Markhoz goats including BW, WW, ADG and KR; varied from 0.23 (BW-KR) to 0.98 (WW-ADG) for genetic correlations and from 0.07 (BW-KR) to 0.97 (WW-ADG) for phenotypic ones. These estimated values in the Markhoz goat were generally higher than those estimated in the present study. Wang et al. (Reference Wang, Liu, Shi, Qi, Li, Wang, Zhang, Zhao, Su and Li2023) reported direct genetic correlations of 0.012, −0.002 and −0.026 for BW-WW, BW-ADG and BW-KR in inner Mongolia white Arbas Cashmere goat, respectively. They reported phenotypic correlations of 0.062, −0.098 and −0.294 for BW-WW, BW-ADG and BW-KR in the inner Mongolia white Arbas Cashmere goat breed, respectively (Wang et al., Reference Wang, Liu, Shi, Qi, Li, Wang, Zhang, Zhao, Su and Li2023). Estimated values for the phenotypic and genetic correlations for BW-ADG and BW-KR in the present study were positive, but the corresponding estimated values by Wang et al. (Reference Wang, Liu, Shi, Qi, Li, Wang, Zhang, Zhao, Su and Li2023) in inner Mongolia white Arbas Cashmere goat breed were negative. These differences may be explained partly by differences in breed and data structure.
The variations in maternal permanent environmental effects may be explained by the differences in intrauterine conditions during pregnancy, nutrient availability during pregnancy and lactation, maternal behaviour and the mothering ability of the dam (Wang et al., Reference Wang, Liu, Shi, Qi, Li, Wang, Zhang, Zhao, Su and Li2023). Maternal permanent environmental correlations among pre-weaning growth traits in inner Mongolia white Arbas Cashmere goat breed ranged from −0.289 for BW-KR to 0.90 for WW-ADG (Wang et al., Reference Wang, Liu, Shi, Qi, Li, Wang, Zhang, Zhao, Su and Li2023). Maternal genetic correlations between BW and WW in Markhoz goat (Rashidi et al., Reference Rashidi, Sheikhahmadi, Rostamzadeh and Shrestha2008), Jamunapari goat (Dige et al., Reference Dige, Rout, Singh, Dass, Kaushik and Gowane2021) and inner Mongolia white Arbas Cashmere goat (Wang et al., Reference Wang, Liu, Shi, Qi, Li, Wang, Zhang, Zhao, Su and Li2023) breeds were reported as 0.43, 0.77 and 0.388, respectively.
Conclusion
The results of this study highlight the significant impact of environmental effects on the early growth performance of Murciano-Granadina kids. Furthermore, maternal effects had important influences on the early growth traits of the Murciano-Granadina goat breed. Therefore, accurate identification and recording of dams identities are necessary. Low estimates of direct heritability for the examined traits suggest limited genetic variability within the Murciano-Granadina goat breed population. As a result, genetic progress for these traits can not be achieved rapidly through mass selection. In addition to direct genetic effects, maternal genetic effects (for BW and WW), maternal permanent environmental effects and litter effects (for BW, ADG, KR and GE) were shown to be important for the genetic evaluation of the Murciano-Granadina kids. These effects should be included in the genetic analysis models for estimating more accurate breeding values of the selection candidates. In other words, the breeding programme should consider both improvement in environmental effects and maternal performance of dams into account for developing an efficient selection process in this breed. The moderate-to-high estimates of genetic correlation among the studied traits indicate that selection for any of these traits could lead to improvements in the other traits and could be useful for selecting kids at an early age.
Acknowledgements
The authors would like to express their gratitude to the staff of Ghale-Ganj dairy farm and Fajr Isfahan Agricultural and Livestock Company for their assistance in data collection and flock management.
Author contributions
Morteza Mokhtari, Ali Esmailizadeh and Juan Pablo Gutierrez developed the theoretical framework. Morteza Mokhtari, Zahra Roudbari and Arsalan Barazandeh analysed the data. Ehsan Mohebbinejad involved in data collection and processing. Morteza Mokhtari wrote the primary version of the manuscript. All authors have contributed to the manuscript revision and have read and approved the submitted version.
Funding statement
This research received no specific grant from any funding agency, commercial or not-for-profit sectors.
Competing interests
The authors certify that there are no conflicts of interest among authors and between authors and other people and organizations.
Ethical standards
Not applicable.
