Effects of Various Non-genetic Factors on Fertility Traits in Murrah Bulls in an Organized Herd

The Indian livestock biodiversity is endowed with the finest buffalo breeds and houses the largest buffalo population in the world. Despite nearly half of the cattle population, buffaloes contribute more than cows to the country’s milk (Anonymous, 2019) which reflects the gravity of buffalo in the Indian dairy industry. Indian breeds of buffaloes have the remarkable genetic potential for production and adaptability to cater for the huge demand for milk in our country. Sire and dam, contribute equally to the inheritance of milk production; but sires contribute more genetic gain than a dam; since the higher intensity of selection can be realized for bulls, owing to frozen semen technique. Hence a faster genetic improvement in herd performance can be achieved through sire selection (Norman et al., 2003).
       
Keeping a record of service perconception, conception rate, non-return rate and calving, is necessary in order to properly evaluate the reproductive efficiency. Fertility of females, records of semen parameters as well as bull wise conception rates are also required to make a reproductive management decision. Ideally, with an 80% pregnancy rate on the first insemination, a maximum of 1.3 services per conception and an average service period of 85 days, optimum economic fertility could be achieved (Morrow, 1980). Conception is the first prerequisite of a buffalo entering into a productive life and greatly influences the lifetime productivity of the individual buffaloes. The conception rate directly determines the total profitability of a dairy farm enterprise. Specifically, among buffaloes, a large number of females remain barren or unproductive around the year and become a burden for the farmers (Cicek et al., 2017). On the other hand, many factors, both genetic and non-genetic, viz. genotypes, age, parity and reproductive health of females; genotype, libido and semen quality of bulls; heat detection, season and time of AI etc., have a direct influence onincreasing conception rate.
               
Meager buffalo population is contributing much in milk production as compare to cattle demands  adequate supply of excellent germplasm or frozen semen doses for their further genetic improvement. Selection of bulls for semen production considering the various factors (Age of bull, season and period at collection/ preservation) affecting post-thaw semen quality traits plays a great role as frozen semen samples have been used widely in the field resulting good conception rate (Nordin et al., 1990; Parmar et al., 2021). The information regarding the trends of these influences semen attibutes  would greatly help to  know the requirement of bulls to meet the demand of frozen semen and to provide any suitable additional managerial requirements time to time. Considering these, the present study was planned with the aim to evaluate the effects of concomitantfactors affecting conception rate and to recommend an optimum approach for achieving maximum conception rate among buffaloes.

The present investigation was conducted at Artificial Breeding Research Centre (ABRC) and Livestock Research Centre of ICAR-National Dairy Research Institute, Karnal; which is situated at an altitude of 250 meters above the mean sea level in the Indo-Gangetic alluvial plains on 29° 42' N latitude and 72°02' E longitude. The farm’s climate is subtropical and the temperature shows broad variation froma near freezing point in winter months to a maximum around 46°C in summer. The average relative humidity ranges from 41% to 85%. The locality of the farmgets an annual rainfall of about 760 to 960 mm, mostly during the monsoon (July to August). Thus it is obvious that the Murrah herd at the institute has been exposed to a wide range of meteorological factors.
       
Records on 5349 AI of Murrah bulls and their mates during the period 1980 to 2014 for estimation of conception rate were collected from Dairy Cattle Breeding Division, Livestock Research Centre and Artificial Breeding Research Centre at National Dairy Research Institute, Karnal, Haryana (India). Semen analysis was done by collecting frozen semen samples of 130 Murrah bulls. The data were analyzed to study the effects of various non-genetic factors on conception rate as well as sperm quality traits in Murrah bulls, classifying the data into four periods of AI/ semen freezing viz., Period-1 (1980-1996), Period-2 (1997-2002), Period-3 (2003-2008), Period-4 (2009-2014); four seasonsof AI and collection/freezing of semen viz. Summer (April-June), Rainy (July-September), Autumn (October-November) and Winter (December-March); five parity groups (Heifer, first, second, third and fourth and more parity) and five female AI number groups (first, second, third, fourth and five or more AI after calving), respectively. The age of the bull was divided into four age groups i.e. the first group with less than three years, next as 3-4 years, 4-5 years and last group as 5 years or more at the time of freezing of semen has been considered to see the effect on sperm quality parameters and shown significant effect on post-thaw semen parameters. A minimum of 3 semen straws from each bull per available season (total 3 replication) were used for estimation of seminal parameters and the average of three replications of seminal parameters was used for further analysis. Sperm quality traits like Post-thaw motility, sperm abnormality, sperm viability, acrosomal integrity and hypo osmotic swelling test (HOST) test were performed to assess the quality parameters in Murrah bulls semen using standard protocol performed in most of the semen processing laboratory. Further, the estimation of conception rate was done using the following formula:
   
Least-squares analysis was performedin SAS version 9.3 (SAS Institute, Cary, NC, USA) and the analysis of variance for the season of AI, period of AI, parity and female AI number affecting bull’s conception rate under model was computed. The difference of means between subclasses was tested for significance using Duncan’s multiple range test (DMRT) as modified by Kramer (1957). The following model was used for the present investigation;
   
Where,
Y_ijkn= Observation of nth bull in lth female AI no.
k^th=     Parity of cow.
j^th=      Period of AI and ith season of AI.
µ=      Overall mean.
S_i=     Fixed effect of ith season of AI (1-4).
P_j=     Fixed effect of jth period of AI (1-4).
Pa_k=   Fixed effect of kth parity of cow (1-5).
FAI_l= l^th female AI number and.
e_ijkn=    Random error ~ NID (0, σ²_e).
       
Similarly, Least-squares analysis was performed to see the effects of various non-genetic factors on semen quality traits of Murrah bulls using the following model:
   
Where,
Y_ijkn=  Observation of n^th bull in k^th period of freezing.
j^th= Season of freezing.
i^th= Bulls age group.
µ= Overall mean.
AG_i= Fixed effect of ith age of bulls at freezing (1-4),
S_j= Fixed effect of jth season of freezing (1-4). 
P_k= Fixed effect of kth period of freezing (1-4).
e^ijkl= Random error ~ NID (0, σ²_e).

Factors affecting conception rate
 
Overall conception rate was estimated by the total number of pregnancies in each female out of total numbers of AI and it was expressed in percentage. The overall conception rate (%) in the present study was 38.43±0.99% with individual bull’s conception rate ranging from 20.00% to 60.46%. The range of conception rate for Murrah bulls was reported as 20.51 to 52.77% by Jadhav (1998) and 22.66 and 54.54% by Taraphdar (1999), which is very close to the present observations. Taraphdar (1999) reported the overall CR as 40.75% and Mir et al., (2015) estimated the average overall conception rate (%) as 39.19±1.55 for Murrah bulls. Segura-Correa et al., (2017) concluded the overall conception rate to 44.6% at 120 days postpartum. It is noteworthy that, overall conception rate (OCR) varies depending on not only genetic factors but predominantly on the environmental and managemental factors. The effect of various factors on the conception rate of bulls were studied by taking the period of AI, the season of AI, parity of female and female AI number with a remark that all the animals belonged to the same breed and herd and thus were provided similar feeding and housing management. The analysis of variance revealed that the period of AI and season of AI had a significant (P<0.05) effect on conception rate while parity and female AI number was not found to affect the conception rate of bulls (Table 1). Segura-Correa et al., (2017) found breed, parity number, season and year of calving to have significant effects on conception rate. In the study of Mir et al., (2015), parity and stage of lactation were found to be non-significant while the same for period and season was significant.The conception rate was found to be maximum i.e. 39.63±0.22 percentage in the period 1997 to 2002 and the lowest CR i.e. 36.37±0.23 percentage was found in the period between 2003 and 2008. Mir et al., (2015) found a significant effect of the period on conception rate (higher 47.88±1.13 in July 2011-December 2012 and lower 27.13±0.96 in the January 2010- June 2011). Considering the season of AI, the rainy season (July-September) had the lowest conception rate i.e. 37.12±0.23%, while autumn, summer and winter had a conception rate between 38.25±0.23% and 38.75±0.20% (Table 2). Segura-Correa et al., (2017) similarly found that the least conception rates in cattle belong to the rainy season. Bhave et al., (2016) found the different distribution of inseminations in lean (Jan- June) and favourable (July-December); however, at the same time, they could not find a significant effect of season of insemination on conception rate. Ron and Bar-Anan (1984) suggested that insemination month accounted for most variation of conception rate of cows; with the lowest conception rate of heifers during summer. Liu et al., (2018) reported that to achieve a high CR, lactating cows should be bred in winter and spring (from December to May) from the start of the seasonal breeding program, whereas the heifer should be allowed to breed in summer under subtropical climatic conditions. The present study and Mir et al., (2015) found non-significant effects of parity, contradicting the study of Bhave et al., (2016) which revealed the significant effects of lactation order on conception rate in buffaloes reared under field conditions. Similarly, Correa et al., (2017) found to have a significantly lower conception in the first parity of the cows.
 

 

 
Factors affecting semen quality parameters
 
In the present study, the age of bull at freezing had a significant effect on acrosome integrity whereas seasons of freezing were found to significantly affect almost all the post-thaw seminal parameters. No significant changes over the period of semen collection/freezing on semen attributes were found; which is expected since no genetic selection for seminal parameters were performed. The overall least squares mean for different semen quality parameters viz. Post-thaw motility, sperm abnormality, sperm viability, acrosome integrity and HOST were found as 55.83±0.53%, 65.87±0.63%, 8.07±0.18%, 73.20±0.50% and 52.40±0.36%, respectively. Bulls with age at freezing between 4-5 years showed higher acrosome integrity whereas less than 3 years of age had a lower percentage of acrosome integrity. The average HOST percentage of frozen semen was found significantly higher i.e. 53.38±0.64 and 52.95±0.62 for the age of bulls at freezing 4-5 years and 3-4 years, respectively, while less than 3 years of age of bulls at freezing had the lowest percentage of HOST i.e. 50.23±0.88. More or less similar, slightly higher or lower estimates of average post-thaw motility (%) were reported between 55.0 and 76.3% by Shivahre (2013), as 64.14% by Bhosrekar et al., (1994), from 60.8±1.5 to 69±4.5% by Kumar et al., (1993) and as 46.44±1.74 by Kumar et al., (2014). Acrosome integrity and HOST were significantly affected by age of bull at freezing (P<0.05). Ramajayan et al., (2021) observed higher estimates for acrosome integrity for bulls with an age group between 4-5 years while lower estimates were found for less than 3 years of age. Bulls aged from 3.5 years to ≥11 years showed higher acrosome integrity between 68.74 and 71.89% and a lower estimate was found in bulls with 18 to 42 months of age. However, no significant impact of age on HOST was observed. Similar findings have been reported by Bhosrekar et al., (1991), Chowdhury et al., (2017), Bhakat et al., (2015) as 92.00%, 73.74% and 70.10%, respectively in Murrah and Surti buffalo bulls. Season of the semen collection/freezing had a significant effect (P<0.05) on all the post-thaw motility parameters of Murrah bulls. The average PTM was found to be maximum i.e. 59.74±1.05 percentage for the semen frozen in the autumn, while frozen in the rainy season had the lowest PTM as 50.88±1.02 percentage. The average sperm abnormality was found to be maximum i.e. 9.3±0.36 per cent for the semen frozen in the autumn and rainy season had lower sperm abnormality i.e. 7.53±0.35 per cent. The average live spermatozoa percent in frozen semen was found maximum i.e. 70.66±1.25 percentage in the autumn season, while the rainy season had a lower percentage of live spermatozoa i.e. 60.40±1.21 percent. The average acrosome integrity percentage from frozen semen was found higher i.e. 74.67±1.03 and 74.37±0.97 percent in autumn season and winter, while lower i.e. 70.32±1.00 in the rainy season. Maximum (54.88±0.70) percent of HOST reacted spermatozoa were in the autumn season whereas minimum (49.30±0.69) in the rainy season. Higher estimates of acrosome integrity had been reported by Bhosrekar et al., (1991) in the autumn season followed by Summer; whereas Bhakat et al., (2015) found a higher estimate in the Winter. Shahzad et al., (2021) reported the non-significant effect of two seasons viz. hot humid summer season (August-September) and the spring season (February-March) on semen kinematics including DNA integrity in Nili-Ravi buffalo bulls. Parmar et al., (2021) also found significant seasonal variations in extreme hot and cold weathers for the average percent of cryopreserved motility (58.85±0.56 and 56.35±0.43), sperm deformity (8.62±0.43 and 9.08±0.51), live and dead count (67.06±0.77 and 65.62±0.76), acrosomal integrity (75.22±0.27 and 74.29±0.22), HOST reactive sperm (58.52±0.67 and 55.43±0.60) and first AI conception rate (45.75±0.21 and 43.50±0.11) with better estimates for semen quality and first conception rate during cold as compare to hot season in buffalo bulls.

The study was carried out in Murrah bulls with the objectives to find out the effects of various factors on bulls’ conception rate. The results of the study indicated that period and season were having a significant effect on conception rate whereas no effect of parity and female AI number on CR. The selection of bulls in a breeding program may improve male fertility that may further result in a higher success rate of Artificial Inseminations leading to better reproductive efficiency of the herd. This study highlights that the bulls of age group between 3 and 5 years have shown good semen quality and thus this age must be preferred for good quality semen cryopreservation. Semen collection and freezing in summer and rainy season had low to poor semen quality which indicates seasonality in the semen quality and warrants that the frequency of semen collection should be reduced during adverse seasons. Semen quality had no significant fluctuations over the period, possibly indicating that seminal traits did not face sufficient selection pressure. The information may be used as an aid for the selection of animals with high fertility.The genetic evaluation of bulls considering the conception rate along with productivity and correction of data for significantly affecting factors would be highly useful for the economic success of the dairy sector.

The authors are highly thankful to Director, ICAR-NDRI and Head, AGB Division for providing all the necessary research facilities for the present study. Financial assistance received in terms of DST-INSPIRE for pursuing PhD to the first author is duly acknowledged.

None.