Estimates of Phenotypic and Genetic Parameters for Traits of Reproductive Efficiency in Kajli Sheep in Punjab, Pakistan

Asad Ali1*, Khalid Javed1, Imran Zahoor1, Khalid Mahmood Anjum2,

Numan Sharif1, Imtiaz Ahmad3 and Aftab Hussain Aftab3

1Department of Animal Breeding and Genetics, University of Veterinary and Animal Sciences, Lahore 54000, Pakistan

2Department of Wildlife and Ecology, University of Veterinary and Animal Sciences, Lahore 54000, Pakistan

3Livestock Experiment Station Khushab, Punjab, Pakistan

ABSTRACT

The objectives of this study were to evaluate non-genetic and genetic effects as well as heritabilities and repeatabilities for seven reproductive traits using phenotypic records from an experimental Kajli flock in Punjab, Pakistan. Phenotypic data comprised 2501 records of litter size at birth (LSB), cumulative litter weight at birth (LWB), and mean litter weight at birth/ lamb born (LMWB), 1657 records of litter size at weaning (LSW), cumulative litter weight at weaning (LWW), and mean litter weight at weaning/ lamb weaned (LMWW), and 1674 records of lambing interval (LI) from Kajli sheep housed at the Livestock experiment station Khushab from 2007 to 2018. Least squares procedures (SAS, 9.1) were used to assess the effect year of service (YOS), season of service (SOS), parity of dam, and breeding ram on the expression of all reproductive traits. A derivative free REML algorithm was used to estimate heritabilities and repeatabilities with software WOMBAT®. The overall least squares means ± standard error for LSB, LWB, LMWB, LSW, LWW, LMWW and LI were 1.19±0.03, 5.75±0.17 kg, 4.88±0.06 kg, 1.17±0.05, 20.77±0.91 kg, 17.87±0.57 kg, 330.69±20.48 days, respectively. The YOS had significant (p≤0.01) impact on LSB, LWB, LMWB, LWW and LMWW. However, SOS did not affect any reproductive trait except for LI (p≤0.01). Parity significantly affected LMWB (p<0.05) as well as LSB, LWB, LSW and LWW (p≤0.01), but not LMWW and LI. Breeding ram influenced LSB, LSW and LWW significantly (p≤0.01). Genetic parameter estimates were very low due to large values of environmental variances for all reproductive traits. Estimates of heritability were low for all traits (0.08±0.05, 0.01±0.02, 0.02±0.02, 0.01±0.01, 0.04±0.03, 0.07±0.05 for LSB, LWB, LMWB, LSW, LWW and LMWW, respectively). The heritability for LI was zero. Repeatability estimates were also low for all traits (0.09±0.05, 0.02±0.02, 0.06±0.03, 0.02±0.01, 0.04±0.02, 0.09±0.06, 0.01±0.01 for LSB, LWB, LMWB, LSW, LWW, LMWW and LI, respectively). Regression of estimated breeding values for all reproductive traits on year of breeding yielded no significant genetic trends during the 12 years of the study.

Article Information

Received 02 March 2022

Revised 05 November 2022

Accepted 22 November 2022

Available online 23 February 2023

(early access)

Published 17 April 2024

Authors’ Contribution

Concept, design, proof reading and submission, KJ, AA. Data collection and analysis, AA, KJ. Data maintenance and animal management, IA, AHA. Drafting and formatting of manuscript, AA, NS, IZ, KMA.

Key words

Breeding value, Environment, Genetic trend, Kajli, Reproduction

DOI: https://dx.doi.org/10.17582/journal.pjz/20220302060325

* Corresponding author: asad@uvas.edu.pk

0030-9923/2024/0003-1285 $ 9.00/0

Copyright 2024 by the authors. Licensee Zoological Society of Pakistan.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Introduction

Mediterranean and Asian wild sheep are both the ancestors of present-day sheep breeds (Waheed et al., 2016). The ancestors of Pakistani sheep breeds are most likely Urial (Ovis vignei), Argali (Ovis ammon) and Marco Polo sheep of China. Pakistan is endowed with a diverse small ruminant genetic pool. There are 30.9 million sheep in Pakistan that produce 46.8 metric tons of wool and contribute significantly to the 732 metric tons of lamb and chevon along with a goat population of 76.1 million (GOP, 2019). Kajli sheep are well recognized for their juicy mutton; rams are particularly nurtured for trade on Eid-ul-Adha as sacrificial animals (Qureshi et al., 2010). Kajli has become the most promising sheep breed of Pakistan due to its huge market acceptance. Kajli lambs are very popular for their growth rate and aesthetic traits (roman nose, black circle around eyes, and white colored wool). Autochthonous breeds of livestock species have a high biological value because they have developed an optimal set of adaptive characteristics over time in response to environmental pressures (Waheed et al., 2016).

The overall genetic progress of a breeding program largely depends on amounts of genetic variation associated with selection traits and on genetic correlations among these traits. Understanding of non-genetic factors underlying reproductive traits included in a genetic improvement scheme is crucial to devise a suitable management strategy. Similarly, knowledge of genetic parameters for composite traits in selection indexes helps to predict direct and indirect selection responses as well as determine optimal trait weights in multiple-trait selection programs.

Previous research with Kajli sheep has involved non-genetic and genetic sources of variation underlying performance characteristics (Qureshi et al., 2010), change in physiological and blood parameters in new born lambs (Saddiqi et al., 2011), morphometric measurements (Iqbal et al., 2014), pathophysiology of peste des petitis (Khan et al., 2018) and polymorphism of Calpastatin (Khan et al., 2012), Leptin (Qureshi et al., 2015), Callipyge (Shah et al., 2018), Myostatin and Beta-3 Adrenergic Receptor genes (Ali et al., 2021). However, detailed and comprehensive information about environmental effects, genetic effects, and variance components for composite reproductive traits in Kajli sheep is lacking.

Genetic variation for reproductive traits does exist among individuals but large environmental differences make the assessment of such genetic differences very challenging (Abegaz et al., 2002). Moreover, phenotypic selection of large sized ewe lambs is a common practice in most sheep production systems. Therefore, the estimation of environmental and genetic influences underlying ewe performance becomes unavoidable to make unbiased breeding decisions (Borg et al., 2009). The success of a sheep enterprise depends largely on the reproductive efficiency of the flock. Thus, enhancement of reproductive performance is a vital objective in sheep breeding. This can be achieved through a selection program for reproductive traits such as number of lambs born and weaned per ewe per year. Implementation of a selection program requires comprehensive information on genetic and environmental factors influencing reproductive traits as well as genetic parameters associated with these traits. Thus, the objectives of this study were to evaluate nongenetic and genetic effects as well as heritabilities and repeatabilities for seven reproductive traits i.e., litter size at birth (LSB), cumulative litter weight at birth (LWB), mean litter weight at birth/lamb born (LMWB), litter size at weaning (LSW), cumulative litter weight at weaning (LWW), mean litter weight at weaning/lamb weaned (LMWW) and lambing interval (LI) using phenotypic records from an experimental Kajli flock.

Materials and Methods

Resource flock and site

The resource flock consisted of 652 Kajli ewes housed at the Livestock Experiment Station, Khushab (LES Khushab), Pakistan (coordinates: 32.296667, 72.3525). The climate in Khushab is classified as BSh (Steppe climate; Köppen-Geiger classification), commonly known as semi-arid, with an average temperature of 24.3°C and an annual rainfall of about 400 mm. Kajli sheep is native to Khushab; it was brought into LES Khushab in the 1980s (Ali et al., 2020a). The LES Khushab spans 971 acres of land, 930 acres of canal irrigated, 10 acres of forest, and 30 acres of roads and buildings. Selection of Kajli ewes in LES Khushab was based on growth performance and breed characteristics. Rams selected for breeding were either produced within LES Khushab or purchased from other flocks to provide genetic heterogeneity. Mature male and female sheep were housed in separate open type buildings except during breeding days. Generally, breeding occurred in the fall (August-October) and spring (February-April) seasons. However, to meet the high demand for male lambs, ewes which did not breed in the fall and spring were bred in the summer (May-July) and winter (November-January) months, respectively. Breeding was practiced in small groups of 25 to 30 ewes/ram (Ali et al., 2020b). Lambs were ear tagged and weighed at birth, and allowed to stay with their dams until weaning (90 to 120 days of age). Animals at LES Khushab were weighed on an electronic scale at the end of each month. Monthly body weight records were maintained in registers (Ali et al., 2020b). The feeding and housing conditions at LES Khushab have remained the same since the start of the Kajli flock. Feeding consisted of 7 to 8 h/day of grazing on seasonal crop remains in the canal irrigated plains or similar number of hours of grazing on naturally grown wild trees in the forested areas. Clean drinking water was provided ad libitum in cement troughs. In addition, a concentrate supplement (300 to 500 g/day/female and 500 to 750 g/day/male) was provided during breeding, lambing, and seasons of scarcity. Kajli sheep were vaccinated against pleura-pneumonia, enterotoxaemia, sheep pox, foot and mouth disease, and peste des petits. Drenching with anthelmintic medicines to avoid internal parasites was given every four months, and dipping to prevent external parasites was practiced twice a year.

Data description

Data used in this study included pedigree, birth date, birth type, sex and weight records at different ages collected at LES Khushab during a period of 12 years (2007 to 2018). Data consisted of 2501 lambing from 652 dams and 25 rams. Lambs were 51.61% male, 48.39% female, 71.96% single-born, 27.14% twins, and 0.89% triplets. The pedigree structure of selected animals is laid out in Table I. The reproductive traits were litter size at birth (LSB), cumulative litter weight at birth (LWB), mean litter weight at birth/lamb born (LMWB), litter size at weaning (LSW), cumulative litter weight at weaning (LWW), mean litter weight at weaning/lamb weaned (LMWW) and lambing interval (LI). The overall data description is provided in Table II. Lambs were allowed to stay with their dams until they were four months of age. The age of 120 days was adopted as weaning age. Weaning weights were adjusted to 120 days of age using the following equation (Akhtar et al., 2012).

Body weight adjusted to 120 days (LWWT) = X+[(Y-X)/Z]*120

Where X is birth weight; Y is actual weight; Z is actual age (days).

 

Table I. Pedigree structure of Kajli sheep at LES Khushab.

Category	N
No. of base animals	361
No. of animals with records	859
No. of animals with unknown sire	328
No. of animals with unknown dam	326
No. of sires with progeny records	25
No. of dams with progeny records	354
No. of grand sires with progeny records	25
No. of grand dams with progeny records	171

 

N, number of individuals.

 

Statistical analysis

Least squares analyses were used to evaluate the fixed effects of year of service (YOS), season of service (SOS), parity, and breeding ram using linear model procedures from the statistical analysis software (Cody, 2015). The fixed effect model was as follows:

Yijklm = μ + YOSi + SOSj + Pk+ Rl + eijklm (Model 1)

Where Yijklm is phenotypic value of each trait, µ is population mean; YOSi is year of service (i=1,2,3...12; 1 to 12); SOSj is season of service {j=S1, S2, S3, S4; S1 (February, March, April), S2 (May, June, July), S3 (August, September, October), S4 (November, December, January)}, Pk is parity (k=1,2,3...7; 1 to 7), Rl is breeding ram (l=1,2,3...25; 1 to 25), εijklm is random residual associated with Yijklm assumed to be NID ~ mean zero, variance σ2ε.

 

Table II. Descriptive statistics for reproductive traits in Kajli sheep.

Trait	N	Mean±SE (Range)	h2	R
LSB (No.)	2501	1.16±0.007 (1-3)	0.08±0.05	0.09±0.05
LWB (kg)	2501	5.57±0.031 (1.50-12.00)	0.01±0.02	0.02±0.02
LMWB (kg)	2501	4.84±0.017 (1.50-07.40)	0.02±0.02	0.06±0.03
LSW (kg)	1657	1.13±0.008 (1-3)	0.01±0.01	0.02±0.01
LWW (kg)	1657	20.13±0.167 (7.48-56.55)	0.04±0.03	0.04±0.02
LMWW (kg)	1657	18.04±0.101 (7.48-32.23)	0.07±0.05	0.09±0.06
LI (days)	1674	342.80±160.91 (164-1661)	0.00±0.00	0.01±0.01

 

LSB, litter size at birth; LWB, cumulative litter weight at birth; LMWB, mean litter weight at birth/ lamb born; LSW, litter size at weaning; LWW, cumulative litter weight at weaning; LMWW, mean litter weight at weaning/ lamb weaned; LI, lambing interval; N, number of animals; SE, standard error; h2, heritability; R, repeatability.

 

Variance components were estimated with restricted maximum likelihood (REML) procedures (Gilmour et al., 1995) by fitting an animal mixed linear model in software WOMBAT® (Meyer, 2007). Pedigree information was traced as back as possible and was included in the additive relationship matrix to minimize biases due to selection and non-random mating. The values of the convergence criteria (-2 log likelihood) for genetic parameters were 1 x 10-8.

Univariate analyses were run to estimate heritabilities for performance traits. Only those fixed effects found to be significant in the initial analyses (Model-1) were included in the animal mixed linear model. The following model was used to compute variance components and heritabilities:

Yijk = μ + Fi + Aj + eijk (Model 2)

Where Yijk is the actual value of a particular trait, μ is the population mean, Fi represents fixed effects found significant in model 1 (Table III), Aj is the random additive genetic effect of the jth animal with mean zero and variance σ2A, and eijk is the random residual assumed to be NID (0, σ2e).

Estimates of repeatabilities for reproductive traits were obtained with the following model:

Yijkl = μ + Fi + Aj + Ek + eijkl (Model 3)

Where Yijkl is the observation for a particular trait, μ is the population mean, Fi is the ith fixed effect considered in Model 2 (Table III), Aj is the random additive genetic effect of the jth animal with mean zero and variance σ2A, Ek is the random permanent environmental effect of the kth ewe, eijkl is the random error associated with Yijkl, assumed to be NID (0, σ2e). However, estimates of the common environment ratio (c2) were obtained as follows:

c2 = σ2PE/ σ2P

where σ2PE is permanent environment variance, σ2P is phenotypic variance.

Repeatability estimates were obtained as follows:

Repeatability = (σ2A + σ2PE) / σ2P

where σ2A is additive genetic variance, σ2PE is permanent environment variance, and σ2P is phenotypic variance.

 

Table III. Fixed effects fitted for the estimation of heritability (Model-2) and repeatability (Model-3).

Trait	Fixed effects
	Year of service	Season of service	Parity	Serving ram
LSB (No.)	X		X	X
LWB (kg)	X		X
LMWB (kg)	X		X
LSW (kg)			X	X
LWW (kg)	X		X	X
LMWW (kg)	X
LI (days)		X

 

For abbreviation, see Table II.

 

Results

The least squares means (LSM) for year of service (YOS), season of service (SOS), parity of dam, and breeding ram on LSB, LWB, LMWB, LSW, LWW, LMWW, and LI revealed significant differences among YOS for all observed traits (p≤0.01), except for LSW and LI (p>0.05). Higher LSM for LSB (1.43±0.03) and LWB (6.97±0.15 kg) and lower LSM for LI (266.07±9.16 days) were obtained in 2017. The LSM values revealed near linear improvement in LSB of Kajli across years. The SOS only affected LI (p≤0.01). Higher LSM for LWB (5.84±0.05 kg) and lower LSM for LSB (1.17±0.01 kg) were observed in S1 (spring). Dam parity number affected LSB, LWB, LMWB, LSW (p≤0.01) and LWW (p≤0.05), but not LMWW and LI. Analysis showed a gradual increase in LSM values for LSB from the 1st (1.09±0.01) to the 6th parity (1.27±0.04). The number of individuals, least squares means (LSM), and standard errors (SE) for YOS, SOS and parity computed for each of the reproductive traits (LSB, LWB, LMWB, LSW, LWW, LMWW, and LI) are presented in Table IV. Table V shows the breeding ram LSM for LSB, LWB, LMWB, LSW, LWW, LMWW, and LI. LSM for LSB differed across years (p≤0.01); differences of up to 0.56 lambs per breeding ram were observed over the years. Similarly, differences among breeding rams (p≤0.01) existed for LSW (up to 0.36 lambs) and LWW (up to 8.99 kg).

Heritability and repeatability estimates for LSB, LWB, LMWB, LSW, LWW, LMWW, and LI are presented in Table II. Estimates were low for all observed traits. Heritability estimates ranged from 0 (LI) to 0.08±0.05 (LSB). Repeatability estimates ranged from 0.01±0.01 for LI to 0.09±0.06 for LMWW. Trends for estimated breeding values (EBV) of Kajli sheep for LSB, LWB, LMWB, LSW, LWW, LMWW, and LI from 1999 to 2018 are plotted in Figure 1. Genetic trends for LSB, LWB, LMWB, LSW, LMWW, and LI were essentially flat, although LSW and LWW exhibited improvement and decline in different years of production.

 

Table IV. Least squares means (LSM±SE) for non-genetic effects affecting reproductive traits in Kajli sheep.

Effect	No.	LSB (No.)	LWB (kg)	LMWB (kg)	No.	LSW (No.)	LWW (kg)	LMWW (kg)	No.	LI (days)
Year of service
2007	58	1.11± 0.03e	5.67± 0.09e	5.17±0.09bc	21	1.18±0.05	20.43± 0.82e	17.24±0.64d	44	352.81±34.23
2008	196	1.16± 0.02cde	5.70± 0.06de	5.01±0.06bc	104	1.21±0.02	20.31± 0.50e	16.68±0.30d	151	344.21±13.37
2009	215	1.10± 0.02de	5.41± 0.05e	4.97±0.05bc	107	1.12±0.01	18.71± 0.30e	16.44±0.25d	160	316.59±12.66
2010	225	1.06± 0.02de	4.53± 0.08f	4.26±0.08e	127	1.17±0.01	18.54± 0.34e	15.65±0.28d	171	319.52±11.68
2011	212	1.05± 0.02de	5.37± 0.09e	5.09±0.09bc	135	1.16±0.02	20.78± 0.43d	17.87±0.30c	170	312.37±12.47
2012	251	1.15± 0.02bcd	5.80± 0.08c	5.07±0.08b	178	1.19±0.02	21.54± 0.41d	18.30±0.32c	210	331.20±12.66
2013	257	1.21± 0.03b	5.88± 0.09c	4.94±0.09bc	199	1.16±0.02	21.96± 0.44cd	18.89±0.26bc	201	378.95±12.63
2014	261	1.13± 0.02bcde	5.37± 0.06e	4.77±0.06d	205	1.19±0.02	21.29± 0.43d	18.09±0.31c	164	405.72±13.22
2015	195	1.21± 0.03bc	5.68± 0.10cd	4.75±0.10cd	147	1.17±0.03	22.46± 0.60bc	19.31±0.33ab	126	330.31±7.19
2016	349	1.31± 0.02b	6.03± 0.09c	4.68±0.09bc	230	1.19±0.02	22.15± 0.50bc	19.05±0.26ab	219	293.44±7.72
2017	191	1.43± 0.03a	6.97± 0.15a	4.90±0.15a	134	1.09±0.04	19.84± 0.77ab	18.41±0.37a	58	266.07±9.16
2018	91	1.36± 0.05a	6.59± 0.21b	4.93±0.21a	70	1.17±0.06	21.27± 1.05a	18.50±0.54a	--	--
Season of service
S1 (Spring)	836	1.17± 0.01	5.84± 0.05	4.98±0.03	569	1.18±0.01	21.18± 0.30	18.30±0.16	546	332.76±7.69ab
S2 (Summer)	72	1.18± 0.03	5.70± 0.05	4.83±0.11	50	1.16±0.05	20.79± 1.17	17.70±0.52	46	359.63±25.55a
S3 (Fall)	1427	1.21± 0.01	5.68± 0.05	4.77±0.02	920	1.17±0.01	20.93± 0.23	18.03±0.14	974	336.14±4.78ab
S4 (Winter)	166	1.18± 0.02	5.78± 0.05	4.84±0.08	118	1.16±0.02	20.21± 0.53	17.45±0.40	108	319.17±15.00b
Parity
1	789	1.09± 0.01d	5.29± 0.04d	4.88±0.03a	502	1.11±0.01b	19.51± 0.30c	17.70±0.17	580	357.63±6.65
2	613	1.14± 0.01cd	5.63± 1.04c	4.98±0.03a	397	1.12±0.01b	20.24± 0.31bc	18.15±0.20	443	245.31±7.77
3	441	1.20± 0.02bc	5.83± 2.04bc	4.93±0.04a	291	1.18±0.02ab	21.26± 0.44ab	18.08±0.26	302	327.20±8.01
4	306	1.19± 0.02bc	5.78± 1.04bc	4.92±0.05a	203	1.13±0.02ab	20.75± 0.50ab	18.32±0.28	184	328.50±13.26
5	183	1.24± 0.03ab	6.03± 2.04a	4.89±0.06a	132	1.21±0.03a	21.47± 0.69a	17.80±0.37	97	314.40±16.46
6	99	1.27± 0.04a	5.95± 2.04ab	4.73±0.08b	79	1.21±0.05a	20.79± 0.78a	17.24±0.41	45	337.72±25.99
7	70	1.20± 0.05abc	5.74± 2.04c	4.81±0.10ab	53	1.21±0.05a	21.40± 0.99a	17.80±0.58	23	312.74±29.33

 

LSB, litter size at birth; LWB, cumulative litter weight at birth; LMWB, mean litter weight at birth/ lamb born; LSW, litter size at weaning; LWW, cumulative litter weight at weaning; LMWW, mean litter weight at weaning/ lamb weaned; LI, lambing interval; SE, standard error; LSM, least squares mean (LSM values for each trait with different superscripts within columns differ significantly (P<0.05) from each other; LSM values without superscripts do not differ significantly (p≥0.05); SE, standard error; S1, (February, March, April); S2, (May, June, July); S3, (August, September, October); S4, (November, December, January), --, no record.

 

Discussion

Year of service

The LSM for LSB (1.16) in Kajli was lower than the values of 1.77 in Polypay (Hanford et al., 2006), 1.56 in Pelibuey (Tec-Canché et al., 2015), 1.50 in Abera (Marufa et al., 2017), 1.43 in Bonga sheep (Tera et al., 2021) 1.28 in Baluchi (Yadollahi et al., 2019), 1.29 in Baluchi (Jafaroghli et al., 2019) and 1.45±0.010 in Bonga sheep (Areb et al., 2021). Further, the LSM for LSB (1.14) in Menz and Horro sheep was lower than the LSB in Kajli (Mukasa-Mugerwa et al., 2002). The significant effect of YOS on LSB in Kajli was contrary to the non-significant impact of year on LSB in Santa Inês (Riofrio et al., 2016). However, the LSB in Pelibuey sheep was significantly associated with year (Tec-Canché et al., 2015). The LSM for LWB in Kajli was higher than values reported in Baluchi (5.39kg) (Yadollahi et al., 2019) and Awassi (5.32kg) (Haile et al., 2019) but lower than the value in Lori Bakhtiari (5.70kg) (Vatankhah et al., 2008) sheep. The significant influence of year on LWB in Kajli was similar to earlier findings by Tec-Canché et al. (2015) in Pelibuey but dissimilar to the report on Saint Croix sheep (Sánchez-Dávila et al., 2015). Moreover, the significant impact of year on LSB and LWB was similar to

 

Table V. Least squares means (LSM±SE) for breeding ram effects on reproductive traits in Kajli sheep.

Ram ID	No.	LSB (No.)	LWB (kg)	LMWB (kg)	No.	LSW (No.)	LWW (kg)	LMWW (kg)	No.	LI (days)
200411005	92	1.22± 0.02bc	5.57± 0.13	4.60±0.10	63	1.05±0.01f	18.66± 0.51ijk	17.88± 0.43	69	334.05±17.74
200510002	35	1.58± 0.06a	5.78± 0.13	4.58±0.14	17	1.09±0.06ef	18.74± 1.27ijk	17.25± 0.77	30	348.61±37.79
200510003	88	1.20± 0.03bc	5.67± 0.07	4.78±0.08	46	1.14±0.04def	19.06± 0.70jk	16.92± 0.44	66	375.39±25.36
200510005	193	1.22± 0.02bc	5.72± 0.09	4.77±0.06	105	1.08±0.02ef	18.26± 0.50hijk	16.92± 0.36	150	328.48±12.47
200510007	61	1.25± 0.04bc	5.67± 0.11	4.59±0.10	29	1.05±0.03f	17.26± 0.60k	16.53± 0.52	50	344.49±23.23
200510008	237	1.17± 0.02cd	5.57± 0.07	4.83±0.05	149	1.08±0.02ef	18.06± 0.39ghijk	16.99± 0.35	182	337.98±12.49
200510009	296	1.31± 0.02b	5.67± 0.07	4.78±0.05	201	1.15±0.02cdef	19.27± 0.42fghij	16.91± 0.28	226	330.50±12.74
200611008	112	1.27± 0.03b	5.72± 0.14	4.54±0.10	75	1.08±0.03f	18.58± 0.50ijk	17.37± 0.40	89	359.28±15.93
200611009	87	1.25± 0.03bc	5.88± 0.14	4.81±0.12	55	1.11±0.04def	18.98± 0.83ghijk	17.19± 0.40	64	368.01±22.81
200710063	15	1.17± 0.00cd	5.53± 0.23	4.70±0.23	10	1.39±0.16a	25.73± 1.44a	19.76± 1.49	12	360.53±47.14
200710064	79	1.18± 0.02cd	5.43± 0.13	4.68±0.12	45	1.03±0.00f	18.65± 0.47ijk	18.19± 0.47	65	354.63±18.86
200710066	93	1.21± 0.03bc	5.78± 0.15	4.78±0.10	49	1.02±0.00f	17.36± 0.48k	17.05± 0.48	73	352.74±19.46
201110588	203	1.28± 0.03b	5.65± 0.09	4.86±0.05	158	1.16±0.03bcdef	19.69± 0.53efgh	17.15± 0.34	123	299.39±13.22
201110594	159	1.24± 0.03bc	5.76± 0.10	4.72±0.07	127	1.16±0.03bcdef	20.08± 0.56efg	17.55± 0.34	113	319.05±16.15
201310761	72	1.17± 0.05cd	5.79± 0.20	4.99±0.09	46	1.10±0.04def	19.30± 1.04efghi	17.28± 0.60	49	332.43±21.99
201310775	84	1.19± 0.05cd	5.87± 0.19	4.94±0.07	58	1.16±0.05bcdef	20.52± 0.96cdef	17.55± 0.55	62	298.68±12.49
201310862	48	1.24± 0.06bc	5.91± 0.22	4.83±0.10	33	1.30±0.08abc	22.60± 1.39abcd	17.54± 0.77	27	325.99±12.98
201310864	101	1.12± 0.04d	5.62± 0.16	5.00±0.06	75	1.10±0.03def	20.20± 0.70def	18.29± 0.42	71	298.27±13.36
201411001	51	1.05± 0.04de	5.45± 0.19	5.10±0.08	38	1.15±0.05cdef	19.91± 1.12efgh	16.94± 0.61	29	301.33±16.01
201411002	109	1.09± 0.04de	5.70± 0.18	5.21±0.07	79	1.20±0.05bcdef	22.04± 0.83bcdef	18.38± 0.45	44	322.02±14.52
201411003	88	1.02± 0.04de	5.42± 0.21	5.22±0.04	54	1.24±0.05bcdef	23.34± 1.19abcde	18.64± 0.58	33	322.50±12.86
201411004	97	1.13± 0.05cd	6.13± 0.21	5.37±0.08	59	1.38±0.06abc	25.38± 1.26ab	18.39± 0.48	44	289.47±8.85
201411007	49	1.22± 0.07bc	6.09± 0.29	5.04±0.12	41	1.38±0.07ab	26.25± 1.44a	19.38± 0.81	--	--
201411008	31	1.23± 0.10bc	6.06± 0.40	5.04±0.20	27	1.32±0.09abcd	25.49± 1.66abc	19.75± 0.77	--	--
201411009	21	1.22± 0.11bc	6.29± 0.45	5.19±0.20	18	1.27±0.10bcde	25.96± 1.84a	20.90± 1.24	3	330.44±62.60

 

For abbreviations and statistical details, see Table IV.

 

the significant (p≤0.01) effect of year of lambing on litter size and birth weight in Kermani (Mokhtari et al., 2010) and Rambouillet (Khan et al., 2017) sheep. Differences observed among studies may be attributed to intra-breed and interbreed genetic differences among animals as well as differences in climatic conditions, availability of fodder/feed, and managerial skills of farm staff.

The effect of year of service was significant (p≤0.01) for all observed traits of Kajli sheep except LSW and LI. The LSM for LSW (1.13) and LWW (20.13kg) in Kajli were lower than 1.24 (LSW), 29.11kg (LWW) in Baluchi sheep (Yadollahi et al., 2019). Similar to this study, the effects of year were significant (p≤0.01) for weight at weaning in Baluchi sheep (Yadollahi et al., 2019). The significant effect of year on LWW (p≤0.01) is supported by Piwczynski et al. (2011) and Sanchez-Davila et al. (2015).

The LSM for LI (330.69±20.48 days) in Kajli was higher than 242.62 days in Djallonke sheep (Gbangboche et al., 2006), 253.5 in Bonga sheep (Tera et al., 2021), 259.4 days in Pelibuey sheep (Tec-Canché et al., 2015), 283 days in Bonga sheep (Areb et al., 2021), 288 days in Abera sheep (Marufa et al., 2017), 307.41 days in Brazillian Santa Ines sheep (Aguirre et al., 2017), 264 days in Pakistani Harnai sheep (Zaborski et al., 2019) and lower than 363 days in Santa Ines (Riofrio et al., 2016). The substantial influence of service year on reproductive efficiency traits in this study (p≤0.01) may be linked to climatic conditions, particularly annual rainfall in different years of production.

Season of service

Season of service was inconsequential for all reproductive traits (LSB, LWB, LMWB, LSW, LWW and LMWW), except for LI (p≤0.05). Analysis revealed that dams bred in S3 (fall) had larger litter sizes than of dams bred in S1 (spring) but LMWB of dams bred in spring were higher than LMWB from ewes bred in fall. These results indicated that LMWB decreased as LSB increased in Kajli sheep, in agreement with reports on Mexican Saint Croix hair (Sanchez-Davilla et al., 2015), Iranian Mehraban (Yavarifard et al., 2015), and Chinese small tail han (Lv et al., 2016) breeds of sheep. The overall non-significant differences in LSB due to SOS were contrary to significant (p≤0.05) differences in litter sizes of fat tailed sheep (Ferda et al., 2009) and Bonga sheep (Tera et al., 2021), but in accordance (p> 0.05) to Mukasa-Mugerwa et al. (2002) for Menz and Horro sheep.

LSM differences for LWB, LMWB, LSW, LWW and LMWW among dams bred in different seasons were statistically non-significant. Availability of good quality fodder throughout the gestation period of dams bred in spring (S1) yielded high LSM values for LWB, LMWB, LSW, LWW and LMWW. Seasons were non-significantly associated with LWB, but significantly associated with LWW in Saint Croix hair sheep (Sanchez-Davilla et al., 2015). The significant impact of lambing season on LI in Djallonke (p≤0.01; Gbangboche et al., 2006) and Pelibuey (p≤0.05; Tec-Canché et al., 2015) support the findings on Kajli sheep. The absence of reproductive seasonality in Kajli may be due to the tropical climate of the region, because seasonality of reproduction is mostly observed in sheep of temperate climates (Ortavant et al., 1988). Furthermore, reproduction is primarily influenced by non-genetic factors (feeding, housing, management of breeding and lambing ewes), thus a uniform year-round reproductive management of Kajli at LES Khushab may be one of the reasons for the non-seasonality of reproductive traits in this breed.

Parity

The LSM for litter size at birth in Kajli varied with parity (p≤0.01); minimum value (1.09±0.01) in the 1st parity and maximum value (1.27±0.04) in the 6th parity. The gradual increase in litter size after each parity can be related to the fact that during early parities dams were still growing in size, increase in uterine capacity, multiple ovulations, and maternal behavior traits associated with reproductive efficiency (Fogarty et al., 2000; Abegaz et al., 2002; Benyi et al., 2006; Gbangboche et al., 2006). Tec-Canché et al., (2015) reported a similar increase in litter size from the 1st to the 6th parity in Pelibuey sheep to the one observed in Kajli sheep here. Litter size of 3rd-parity dams was higher (P<0.05) than that of 1st-parity dams, congruent with reports for various sheep breeds (Red karaman and Tuj sheep; Koycegiz et al. (2009), Pelibuey sheep; Macías-Cruz et al. (2009), and Saint Croix sheep; Sanchez-Davila et al. (2015)). Differences among LSM for LWB, LWW and LSW due to parity in Kajli were significant (p≤0.01). The differences (p≤0.01) in LWB and LWW for ewes of different parity were likely due to differences in body sizes at different ages, maternal care, and experience of lamb grooming. The impact of parity or maternal uterine environment on LMWB decreased until weaning and parity did not significantly (p>0.05) affect LMWW (Sanchez-Davila et al., 2015). These results agree with reports on Marwadi sheep (Nirban et al., 2015), Small tail han sheep (Lv et al., 2016) and Avikalin sheep (Mahala et al., 2019), establishing the significant impact of parity on LWB. However, in Avikalin sheep the differences (p<0.05) in body weight of lambs due to parity continued until 6 months of age (Mahala et al., 2019). Parity did not affect (p>0.05) LI in Kajli sheep, contrary to the significant impact of parity on LI found in Djallonke (Gbangboche et al., 2006), Moghani (Rashidi et al., 2011), Shall (Posht-e-Masari et al., 2013), Ghezel (Nabavi et al., 2014), Lori (Mohammadi et al., 2015) and Santa Ines (Aguirre et al., 2017) sheep.

Breeding ram

The goal to evaluate the influence of the breeding ram on LSB, LWB, LMWB, LSW, LWW, LMWW and LI in Kajli was to document its effect on these reproductive traits as it had never been evaluated in Kajli. There is some evidence in the literature on the influence of breeding ram on LSB (Sanchez-Davila et al., 2015). The influence of serving ram was significant on LSB, LSW and LWW (p≤0.01) but non-significant (p>0.05) on LWB, LMWB, LMWW and LI. The LSM for LSB by breeding ram ranged from 1.02±0.04 to 1.58±0.06 lambs born per parturition. Breeding plans to improve fertility rely on ram estimated breeding values for litter size (Afolayan et al., 2008; Sanchez-Davila et al., 2015). Intense selection of rams with high genetic merit for litter size can bring from 8 to 10% progress in reproductive efficiency of flocks (Aguirre et al., 2007; Vanimisetti et al., 2007; Sanchez-Davila et al., 2015). Breeding of prolific rams with genetically unrelated females results in a quick increase in litter size in a flock of sheep (Sanchez-Davila et al., 2015). Breeding Romanov rams exhibited detectable (p<0.05) differences for LSB (Schmidova et al., 2016). However, Mohammadi et al. (2012) reported significant (p<0.05) association of ram with LWB and non-significant (p>0.05) with LSB.

Genetic parameters

The estimates of heritability and repeatability for LSB in Kajli were 0.08±0.05 and 0.09±0.05, respectively. The heritability estimate for LSB in Kajli was in conformity with values from 0.078 to 0.092 in Romanov sheep (Schmidova et al., 2016) and 0.08 (Tera et al., 2021) but lower than the 0.09 (Yadollahi et al., 2019) and 0.10 (Jafaroghli et al., 2019) values in Baluchi sheep and the 0.1 value in five different sheep breeds (Rosati et al., 2002). The estimates of heritability in Kajli for all reproductive traits were very low, ranging from 0 (LI) to 0.08±0.05 (LSB). Heritability estimates for reproductive traits here were lower than estimates for lambing interval (0.06), litter weight at birth (0.15), and litter weight at weaning (0.11) in meat type sheep (Lobo et al., 2009). Yadollahi et al. (2019) estimated heritability (0.12) for litter mean weight per lamb born (LMB) and (0.05) for litter mean weight per lamb weaned (LMW), while very high values for LMB (0.47) and LMW (0.40) were obtained in Shall sheep (Posht-e-Masari et al., 2013). Estimated repeatability values for all reproductive traits in Kajli were lower than values for litter size (0.34), LMB (0.25), and LMW (0.21) in Baluchi sheep (Yadollahi et al., 2019). The heritability estimate for LSB was higher than the estimate for LWW, in agreement with published reports (Bromley et al., 2000; Olivier et al., 2001; Piwczynski et al., 2011). If repeatability is the upper level of heritability, then the low repeatability values for reproductive traits in Kajli indicate that little improvement can be achieved through direct selection for these traits.

Mean yearly estimated breeding values for reproductive traits in Kajli showed minor changes across years, except for LSW and LWW which oscillated around the horizontal axis, indicating no significant genetic changes for reproductive traits over time. Studies on additive genetic trends for composite reproductive traits in sheep are scanty. However, significantly positive additive genetic trends for LSB and LSW were reported in Polypay sheep (Hanford et al., 2006). No significant improvement in genetic worth indicates little focus on reproductive traits in breeding programs of Kajli. Improvement in husbandry practices (environmental conditions) may be an option to increase reproductive efficiency in Kajli sheep.

Conclusion

Season of breeding had little impact on reproductive performance of Kajli sheep, thus year-round breeding plans can be implemented to obtain a higher number of lambs per ewe per year. Litter size is usually considered as a dam trait. However, a significant effect of breeding ram on litter size existed in Kajli sheep. Thus, selection for prolific rams may also be effective to enhance reproductive efficiency in Kajli sheep at LES Khushab, Pakistan.

Acknowledgement

Authors are thankful to the farm staff at Livestock Experiment Station Khushab for their support in data collection.

Funding

This research received no external funding.

IRB approval

This study was approved by Advanced Studies and Research Board (ASRB) of University of Veterinary and Animal Sciences in its 48th meeting held on 11-05-2018.

Ethical statement

The study was approved by Ethical Review Committee of University of Veterinary and Animal Sciences, Lahore.

Statement of conflict of interest

The authors have declared no conflict of interest.

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