Casa based assessment of post-thaw sperm motion traits as fertility indicators in Mehsana buffalo bulls

Introduction

The Indian dairy industry relies predominantly on cows and buffaloes, with domestic buffaloes contributing 91.82 million tonnes of milk and providing meat and draft power, thereby supporting rural economies. The use of high genetic merit bulls through artificial insemination (AI) is essential for improving future buffalo production performance (Vishwanath and Shannon, 2000) [1] . AI is the oldest and most widely used assisted reproductive technology in cattle and buffaloes; however, its adoption in buffaloes remains lower than in cattle, largely due to poor conception rates with frozen semen (Kumaresan and Ansari, 2001) [2] . Failure to achieve pregnancy and the need for repeated inseminations cause substantial frustration and economic losses for dairy farmers. Buffalo spermatozoa exhibit lower cryotolerance than cattle spermatozoa and are more susceptible to cryopreservation-induced damage (Andrabi, 2009) [3] , which may contribute to reduced conception rates in buffaloes. Most laboratories still rely on subjective assessment of sperm motion, concentration and morphology, which is prone to bias and inaccuracy, necessitating more objective evaluation methods (Rijsselaere et al., 2012) [4] . Computer Assisted Semen Analysis (CASA) minimizes observer bias by providing reliable, standardized outputs for semen quality control and sample selection (Del Prete et al., 2022) [5] . CASA enables automated and precise analysis of individual sperm motility patterns (Amann and Waberski, 2014) [6] using dark-field or negative phase-contrast imaging, in which sperm heads appear bright against a dark background, allowing rapid evaluation of large numbers of cells (Kathiravan et al., 2011) [7] . Given the close association between sperm motility and fertility, CASA-based objective assessment of sperm motion and morphology supports reliable fertility prediction (Puglisi et al., 2012) [8] .

Materials and Methods

Twelve Mehsana buffalo bulls from the Dama semen production unit, Banas Dairy (Gujarat, India), were selected based on conception rates from the progeny testing program. Bulls were classified as high-fertile (CR ≥ 43%; n=6) or low-fertile (CR ≤ 35%; n=6) using mean ±1 SD of CR data from 98 bulls under NDP-I. Frozen semen straws (0.25 mL) from six batches per bull (72 samples) were randomly selected and stored in liquid nitrogen for semen analysis.

Computer Assisted Semen Analysis (CASA)

Frozen semen straws were thawed at 37 °C for 30 seconds in a water bath (Memmert WNE 45, Germany) for post-thaw evaluation, with only one straw per bull processed at a time to avoid overcrowding. After thawing, 200 µL of semen was transferred to a pre-warmed (37 °C) sterile 1.5 mL microcentrifuge tube and diluted with 800 µL of pre-warmed TRIS buffer (1:4). Immediately, 3 µL of diluted semen was loaded onto a pre-warmed 8-chamber Leja slide (45° angle) and using the Hamilton Thorne IVOS II CASA system. Ten microscopic fields per sample were examined to record total and progressive motility and kinematic parameters viz., average path velocity (VAP, µm/s), straightline velocity (VSL, µm/s), curvilinear velocity (VCL, µm/s), amplitude of lateral head displacement (ALH, µm), beat cross frequency (BCF, Hz), straightness (STR,%), linearity (LIN,%), and the wobble coefficient (WOB,%) using standard manufacturer-recommended settings. To assess timedependent changes, diluted semen samples were incubated at 37 °C for up to 120 min and re-evaluated at 10-, 60-and 120min intervals following the same procedure.

Statistical Analysis

Data were tested for normality using the Shapiro-Wilk test, and percentage values were arcsine-transformed prior to analysis. Repeated-measures ANOVA was used to evaluate the effects of fertility group, incubation time and their interaction. Group-wise Pearson correlation analysis was performed among sperm parameters. All analyses were conducted using SPSS software (IBM® SPSS® Statistics, version 20.0).

Results and Discussion

Sperm Motility Parameters

Mean total motility (TM,%) and progressive motility (PM,%) at different post-thaw incubation intervals in high-and lowfertile bulls are presented in Table 1. Total motility declined significantly (p<0.05) from 0 to 10, 60 and 120 min in both groups, in agreement with Kumar et al. (2015) [9] and Swami et al. (2017) [10] . Both fertility group and incubation time significantly affected TM, whereas their interaction was nonsignificant. Total motility remained consistently higher (p<0.05) in high-fertile bulls across all intervals, corroborating earlier reports (Kumar et al., 2014 [11] ; Singh et al., 2017 [12] ; El-Khawagah et al., 2020 [13] ; Turri et al., 2021 [14] ). Variations in TM values among studies have been reported, with higher values observed by Patel and Dhami (2016) [15] , Kumar et al. (2016c) [16] and Pathak et al. (2019) [17] , and lower values by Dalal et al. (2018) [18] . Higher TM in high-fertile bulls during early post-thaw incubation (10-15 min) has also been documented (Gliozzi et al., 2017 [19] ; Narud et al., 2020 [20] ), whereas Oliveira et al. (2012) [21] reported non-significant differences after 20 min. Compared with Swami et al. (2017) [10] , TM at 60 and 120 min was lower in the present study, while Kumar et al. (2015) [9] observed higher TM at 60 min but lower values at 120 min. Progressive motility (PM) was significantly influenced by fertility group, incubation time and their interaction. PM was significantly higher (p<0.05) in high-fertile bulls at 0 and 10 min, while differences at 60 and 120 min were non-significant (Table 1). The higher PM at 0 min and its subsequent decline during incubation are consistent with previous reports (Kumar et al., 2016a,b,c [22,23,16] ; Dalal et al., 2018 [18] ). Higher PM values have been reported by Patel and Dhami (2016) [15] and El-Khawagah et al. (2020) [13] , whereas lower values were observed by Pathak et al. (2019) [17] in Surti and Murrah bulls. The significantly higher PM at 0 min in high-fertile bulls agrees with Turri et al. (2021) [14] , while Kumar et al. (2014) [11] reported non-significant differences; Narud et al. (2020) [20] also observed higher PM after 15 min in high-fertile bulls. Compared with Swami et al. (2017) [10] , PM at 60 and 120 min was lower in the present study, whereas Kumar et al. (2015) [9] reported lower values at both intervals. As sperm motility is critical for transport and fertilization (Kumar et al., 2014) [11] , its decline likely reflects metabolic exhaustion (Vianna et al., 2009 [24] ) and mitochondrial dysfunction (O'Connell et al., 2002 [25] ) during incubation.

Sperm Kinematic Parameters

The mean values of sperm kinematic parameters of post-thaw Mehsana buffaloes of high and fertile groups at different time intervals of incubation are presented in Table 2.

Velocity parameters

The mean values of velocity parameters (VAP, VSL and VCL; µm/s) were significantly influenced by incubation time and the time × fertility group interaction, while the main effect of fertility group was non-significant. Velocity values were higher in high-fertile bulls up to 60 min and reversed at 120 min, with a significant difference (p<0.05) observed only at 0 min. All three parameters increased significantly at 10 min compared to 0 min and then declined progressively at 60 and 120 min. Similar trends, including higher velocity parameters in high-fertile bulls, have been reported previously (Kumar et [11,12,10] , whereas Turri et al. (2021) [14] and Gliozzi et al. (2017) [19] observed non-significant group differences. Oliveira et al. (2012) [21] reported lower values, while Narud et al. (2020) [20] found higher VAP and VSL after 15-20 min in high-fertile bulls. The overall mean velocity values in the present study were lower than those reported by Kumar et al. (2016a,b) [22,23] , but higher than those observed by Patel and Dhami (2016) [15] , Kumar et al. (2016c) [16] , Swami et al. (2017) [10] and Pathak et al. (2019) [17] . Compared with Swami et al. (2017) [10] , VSL and VAP at 60 and 120 min were lower, whereas Kumar et al. (2015) [9] reported lower VAP at 60 min and comparable values at 120 min. Variations in velocity traits may arise from intrinsic and extrinsic factors (Mortimer, 2000) [26] , and the transient increase at 10 min likely reflects capacitation-like changes induced by freezethawing.

Amplitude of lateral head displacement

Time and the time × group interaction had a significant effect on ALH (µm), whereas the main effect of fertility group was not significant. No significant differences in ALH were observed between fertility groups at 0, 10, or 60 min; however, at 120 min, ALH was significantly higher (p < 0.05) in the low-fertile group. Overall, ALH showed a tendency to be higher in the low-fertile group. Similar non-significant differences between fertility groups have been reported by Kumar et al. (2014) [11] , Turri et al. (2021) [14] , Oliveira et al. (2012) [21] , and Gliozzi et al. (2017) [19] , whereas Singh et al. (2017) [12] observed higher ALH values in high-fertile bulls. The ALH values at 0 min were comparable to those reported by Kumar et al. (2016a,b) [22,23] , while lower values were reported by Swami et al. (2017) [10] , Pathak et al. (2019) [17] and Abdelli et al. (2025) [27] . At 60 and 120 min, ALH values were lower than those reported by Swami et al. (2017) [10] , whereas Kumar et al. (2015) [9] reported higher ALH at 60 min and lower values at 120 min. In the present study, ALH peaked at 10 min, consistent with the fluctuating patterns described by Kumar et al. (2015) [9] and Swami et al. (2017) [10] .

Linearity, Straightness and Wobbling

LIN, STR and WOB (%) were significantly influenced by time, while the effects of fertility group and the time × group interaction were non-significant (Table 2). No group differences were observed up to 60 min; however, STR was significantly higher in the low-fertile group at 120 min. All three parameters declined significantly (p < 0.05) with incubation. The 0-min values were comparable to those reported by Kumar et al. (2016c) [16] , whereas higher values were reported by Kumar et al. (2016a) [22] and Swami et al. (2017) [10] , and lower LIN by Patel and Dhami (2016) [15] and Pathak et al. (2019) [17] . The 60-and 120-min values agreed with Swami et al. (2017) [10] , while Kumar et al. (2015) [9] reported higher values. Consistent with the present findings, Kumar et al. (2014) [11] and Turri et al. (2021) [14] observed non-significant group differences, whereas Singh et al. (2017) [12] reported higher values in low-fertile bulls. In contrast, Gliozzi et al. (2017) [19] observed higher LIN in high-fertile bulls after 10 min, Narud et al. (2020) [20] reported nonsignificant differences after 15 min, and Oliveira et al. (2012) [21] found higher values in low-conception bulls after 20 min.

Beat cross frequency

BCF (Hz) was significantly influenced by time and the time × fertility group interaction, while the main effect of fertility group was non-significant. BCF was significantly higher (p < 0.05) in the low-fertile group at 0 min, with the reverse trend at 120 min (Table 2), and declined progressively from 0 to 120 min in both groups. The overall mean values were comparable to those reported by Kumar et al. (2016a,b) [22,23] , whereas lower values were reported by Patel and Dhami (2016) [15] , Swami et al. (2017) [10] , Pathak et al. (2019) [17] and El-Khawagah et al. (2020) [13] . The 60-min value agreed with Swami et al. (2017) [10] , although they reported higher values at 120 min, while Kumar et al. (2015) [9] observed higher BCF at both 60 and 120 min. Higher BCF in low-fertile bulls was also reported by Singh et al. (2017) [12] , whereas Kumar et al. (2014) [11] and Turri et al. (2021) [14] found no group differences. Non-significant differences at later incubation times were reported by Gliozzi et al. (2017) [19] , Narud et al. (2020) [20] and Oliveira et al. (2012) [21] .

Correlation among CASA traits in high-and lowfertile Mehsana buffalo bulls

Pearson's correlation coefficients among CASA traits of frozen-thawed semen in high-and low-fertile Mehsana buffalo bulls are presented in Table 3. In both groups, progressive motility (PM) showed significant positive correlations with total motility (TM) and STR. VSL was positively correlated with VAP, and significant positive interrelationships were observed among VCL, VAP and ALH. In contrast, VCL showed significant negative correlations with LIN, STR and WOB, while VAP and ALH were negatively correlated with LIN; ALH was also negatively correlated with STR and WOB. LIN was positively correlated with STR and WOB, and STR with WOB, in both groups. Marked differences between fertility groups were evident: TM-VAP correlations were positive and non-significant in high-fertile bulls but negative and significant in low-fertile bulls; PM-VAP correlations were positive and significant in high-fertile bulls but negative and non-significant in lowfertile bulls; PM-ALH correlations were negative and significant in low-fertile bulls but positive and non-significant in high-fertile bulls; VSL-ALH correlations were positive and significant in high-fertile bulls but negative and nonsignificant in low-fertile bulls; and VSL-LIN correlations were positive and significant in low-fertile bulls but negative and non-significant in high-fertile bulls. Among sperm motility patterns, progressive motility represents the most linear and forward-moving trajectory, enabling spermatozoa to traverse the female reproductive tract efficiently and reach the site of fertilization earlier than nonprogressive sperm. The significant positive correlations of straight-line velocity, average path velocity and straightness with progressive motility in the present study suggest that these parameters may serve as reliable indicators of bull fertility.

Conclusion

High-fertile buffalo bulls showed superior early post-thaw motility and velocity traits compared to low-fertile bulls. Total and progressive motility and velocity parameters (VAP, VSL, VCL) declined significantly with incubation time in both groups, with a transient increase at 10 minutes. Linear motion traits (LIN, STR, WOB) and flagellar activity indicators (ALH, BCF) decreased over time with minimal group differences. Distinct correlation patterns among CASA traits between fertility groups indicate functional differences in sperm motion, suggesting that early post-thaw motility and velocity characteristics may serve as reliable indicators of buffalo bull fertility.

Acknowledgement

Authors are thankful to the Principal, College of Veterinary Science and AH, Kamdhenu University, Sardarkrushinagar; management, Banaskantha District Co-Operative Milk Producers' Union Ltd, Palanpur and staff members of Dama Semen Production Unit, Banas Dairy for providing necessary help and facilities.

References

1. Vishwanath R, Shannon P. Storage of bovine semen in liquid and frozen state. Anim Reprod Sci. 2000;62(13):23-53.
2. Kumaresan A, Ansari MR. Evaluation of conception rate in buffaloes (Bubalus bubalis) with reference to semen quality, stage of oestrus and inseminator. Indian J Anim Sci. 2001;71:144-145.
3. Andrabi SMH. Factors affecting the quality of cryopreserved buffalo (Bubalus bubalis) bull spermatozoa. Reprod Domest Anim. 2009;44(3):552-569.
4. Rijsselaere T, Van Soom A, Maes D, Nizanski W. Computer-assisted sperm analysis in dogs and cats: An update after 20 years. Reprod Domest Anim. 2012;47(Suppl 6):204-207.
5. Del Prete C, Prieto OB, Mislei B, Iacono E, Mari G, Cocchia N, et al. Assessment of an open-access CASA software for bovine and buffalo sperm motility analysis. Anim Reprod Sci. 2022;247:107089.
6. Amann RP, Waberski D. Computer-assisted sperm analysis (CASA): Capabilities and potential developments. Theriogenology. 2014;81(1):5-17.
7. Kathiravan P, Kalatharan J, Karthikeya G, Rengarajan K, Kadirvel G. Objective sperm motion analysis to assess dairy bull fertility using computer-aided system -a review. Reprod Domest Anim. 2011;46(1):165-172.
8. Puglisi R, Pozzi A, Foglio L, Spano M, Eleuteri P, Grollino MG, et al. The usefulness of combining traditional sperm assessments with in vitro heterospermic insemination to identify bulls of low fertility as estimated in vivo. Anim Reprod Sci. 2012;132(1-2):17-28.
9. Kumar P, Saini M, Kumar D, Balhara AK, Yadav SP, Singh P, et al. Liposome-based semen extender is suitable alternative to egg yolk-based extender for cryopreservation of buffalo (Bubalus bubalis) semen. Anim Reprod Sci. 2015;159:38-45.
10. Swami DS, Kumar P, Malik RK, Saini M, Kumar D, Jan MH. Cysteamine supplementation revealed detrimental effect on cryosurvival of buffalo sperm based on computer-assisted semen analysis and oxidative parameters. Anim Reprod Sci. 2017;177:56-64.
11. Kumar D, Kumar P, Singh P, Yadav SP, Sarkar SK, Bhardwaj A, et al. Characteristics of frozen thawed semen in predicting the fertility of buffalo bulls. Indian J Anim Sci. 2014;84(4):389-392.
12. Singh RK, Kumaresan A, Mir MA, Kumar P, Chhillar S, Tripathi UK, et al. Computer assisted sperm analysis: Relationship between the movement characteristics of buffalo spermatozoa and sire fertility. Indian J Anim Res. 2017;51(4):660-664.
13. El-Khawagah AR, Kandiel MM, Samir H. Effect of quercetin supplementation in extender on sperm kinematics, extracellular enzymes release, and oxidative stress of Egyptian buffalo bulls frozen-thawed semen. Front Vet Sci. 2020;7:604460.
14. Turri F, Capra E, Lazzari B, Cremonesi P, Stella A, Pizzi F. A combined flow cytometric semen analysis and miRNA profiling as a tool to discriminate between highand low-fertility bulls. Front Vet Sci. 2021;8:703101.
15. Patel JB, Dhami AJ. Computer assisted sperm analysis of fresh and frozen-thawed buffalo semen and their interrelationship. Indian J Anim Res. 2016;50(1):8-13.
16. Kumar D, Kumar P, Yadav PS. Quantitative evaluation of buffalo semen by CASA during cryopreservation process. Indian J Anim Reprod. 2016;37(1):1-3.
17. Pathak PK, Dhami AJ, Chaudhari DV, Patel JA. Motion and kinematics parameters of frozen-thawed bovine spermatozoa assessed by Biovis CASA. Indian J Dairy Sci. 2019;72(3):302-306.
18. Dalal J, Kumar A, Kumar P, Honparkhe M, Malik VS, Singhal S, et al. Improvement in cryosurvival of buffalo bull (Bubalus bubalis) sperm by altering freezing rate within critical temperature range. Asian Pac J Reprod. 2018;7(2):72.
19. Gliozzi TM, Turri F, Manes S, Cassinelli C, Pizzi F. The combination of kinetic and flow cytometric semen parameters as a tool to predict fertility in cryopreserved bull semen. Animal. 2017;11(11):1975-1982.
20. Narud B, Klinkenberg G, Khezri A, Zeremichael TT, Stenseth EB, Nordborg A, et al. Differences in sperm functionality and intracellular metabolites in Norwegian Red bulls of contrasting fertility. Theriogenology. 2020;157:24-32.
21. Oliveira LZ, de Arruda RP, de Andrade AFC, Celeghini ECC, dos Santos RM, Beletti ME, et al. Assessment of field fertility and several in vitro sperm characteristics following the use of different Angus sires in a timed-AI program with suckled Nelore cows. Livest Sci. 2012;146(1):38-46.
22. Kumar A, Singh J, Kumar R, Cheema RS, Pandey AK, Singh P, et al. Prediction of buffalo bull fertility on the basis of sperm motion traits, viability, membrane integrity, heat shock protein (HSP70) expression and fertility associated antigen (FAA). Indian J Anim Sci. 2016;86(6):648-654.
23. Kumar A, Singh J, Singh P, Singh H, Brar PS. Computer assisted semen analysis based sperm motion traits, viability, membrane integrity of frozen buffalo sperms and their relationship with fertility rates. Indian Vet J. 2016;93(3):32-34.
24. Vianna FP, Papa FO, Zahn FS, Melo CM, Dell'Aqua JA Jr. Thermoresistance sperm tests are not predictive of potential fertility for cryopreserved bull semen. Anim Reprod Sci. 2009;113(1-4):279-282.
25. O'Connell M, McClure N, Lewis SEM. The effects of cryopreservation on sperm morphology, motility and mitochondrial function. Hum Reprod. 2002;17(3):704709.
26. Mortimer ST. CASA -Practical aspects. J Androl. 2000;21(4):515-524.
27. Abdelli A, Besbaci M, Al-Kass Z, Iguer-Ouada M, Morrell JM. In vitro effect of elevated ammonia and urea levels on post-thawed bull semen sperm characteristics. Vet Sci. 2025;12(10):997.