Non-genetic Factors Influencing Conception Rate of Vechur Breed of Cattle from Kerala

According to the 20^th Livestock Census (2019), the cattle population in the country stands at 192.49 million, including indigenous cattle (both identified/descript and non-identified/non-descript) as well as exotic and crossbred animals. Climate change has a significant impact on livestock, influencing growth, production and reproductive efficiency (Lees et al., 2019; Mitchell et al., 2018). Dwarfing serves as an adaptive response to high heat and humidity (Elayadeth-Meethal  et al., 2018). Cattle that have evolved in hot and humid environments tend to exhibit reduced growth (Pauler et al., 2020; Elayadeth-Meethal  et al., 2018). A smaller body size, as observed in breeds like the dwarf Vechur, is regarded as an adaptation to rising temperatures. Evidence suggests that smaller animals possess greater metabolic efficiency and improved heat tolerance (Elayadeth-Meethal  et al., 2021). Vechur cow rearing is well-suited for a low-input, eco-friendly system, as these cattle require minimal amounts of grass and other feed materials. Additionally, they can be sustained on agricultural by-products, making them an efficient and sustainable choice for farming (Anjali and Senthilkumar, 2020). Given the significant contribution of livestock to India’s GDP and rural livelihood systems (Gupta et al., 2022), the conservation and reproductive improvement of breeds like Vechur are essential. As highlighted by Rai et al., (2023), an integrated approach combining genetic improvement with conservation is vital for sustaining these native breeds.
 
Repeat breeding and anoestrus are major challenges in dairy animal breeding, resulting in prolonged calving intervals, higher culling rates and reduced farm profitability (Bartlett et al., 1986; Lafi et al., 1992). Reproductive performance in animals is influenced by various non-genetic factors. The changing climate underscores the importance of conserving locally adapted cattle breeds. Characterising these native breeds for thermo-tolerance is essential to uncover their inherent ability to thrive under challenging climatic conditions (Manoj et al., 2017). Non-genetic factors play a crucial role in determining the reproductive and productive efficiency of indigenous cattle breeds. Patel  et al. (2022) demonstrated this in Tharparkar cattle, where long-term data revealed that herd management practices and selection influenced reproductive traits. These insights emphasize the need to understand such influences in other native breeds like Vechur, especially under tropical conditions. Therefore, this study was conducted to assess the impact of these factors on conception rate in an organized herd of indigenous cattle raised under tropical climatic conditions.

The present study was conducted at the Vechur Cattle Conservation Project, Centre for Advanced Studies in Animal Genetics and Breeding, Mannuthy, Kerala, to assess the influence of non-genetic factors on the conception rate of Vechur cattle. A total of 868 breeding records spanning from 2011 to 2024 were analysed. The dataset included information on the date of service, conception outcome and environmental factors such as time of service, month and year of breeding. The cattle were maintained under a uniform management system, with natural service as the predominant breeding method. Bulls used for breeding were periodically evaluated for seminal parameters to ensure optimal fertility levels.
       
The objective of the study was to analyse monthly variations in conception rates in order to identify trends potentially influenced by climatic conditions, availability of green fodder and other management-related factors. The year-wise analysis was carried out to assess long-term variations in reproductive performance over the 14 years.
       
The statistical analysis was performed using SPSS v27.0 software. The chi-square (c²) test was used to determine the association between non-genetic factors and conception success. The chi-square statistic was calculated using the formula,
 

  

 
Where,
O_i = Observed frequency. 
E_i = Expected frequency.
       
In addition, logistic regression analysis was employed to assess the probability of conception based on the non-genetic factors considered. The logistic regression model was defined as:
 

                                           log (p/p-1) = β₀​+β₁​X₁​+β₂​X₂​

                                         
Where,
p = Represents the probability of conception.
β₀ =  Intercept.
β₁ and β₂ = Regression coefficients.
C₁ and C₂ = Represent the independent variables (month and year).
The significance of each variable in predicting conception success was evaluated and odds ratios were calculated to interpret the likelihood of conception under different conditions.

To ensure data integrity, records of repeat breeders and cows subjected to artificial insemination were excluded, retaining only natural service conception records. After refinement, 868 valid breeding records from 2011 to 2024 were analysed. It is important to note that data from 2024 was only available up to August, which may have introduced bias in year-wise comparisons.
       
Table 1 shows that the time of breeding-whether in the forenoon or afternoon-had no significant impact on conception rates, as indicated by the chi-square analysis (p>0.05). This lack of variation could be attributed to the controlled management conditions under which the breeding bulls were maintained. Regular health monitoring and reproductive evaluations ensured optimal fertility, while shade management and housing conditions helped mitigate the effects of diurnal temperature fluctuations.


       
A significant difference in conception rates was observed across months (p<0.05), with the lowest rate recorded in August (32.10%) and the highest in March (61.7%) (Table 2). This decline coincides with peak monsoon conditions in Kerala, where high humidity, reduced sunlight exposure and lower-quality fodder availability may negatively impact reproductive performance. No significant variations were found among the remaining months, suggesting that apart from August, monthly fluctuations do not play a major role in conception success.


       
Year-wise analysis showed significant variation (p<0.05) in conception rates across different years (Table 3). The highest rates were observed in 2012 and 2021, while 2013 and 2024 recorded the lowest. Favourable climatic conditions, improved herd management and optimized nutritional strategies could explain the higher conception rates in 2012 and 2021. Additionally, the lack of a consistently increasing trend in conception rates across years can be explained by the average inter-calving period of 514 days, meaning that cows do not calve every year, leading to natural fluctuations in breeding data. Moreover, nearly 30% of the recorded data corresponds to the last four months of the previous calving cycle, meaning that a significant proportion of animals from the later part of one year would not conceive again in the immediately following year. This pattern results in inherent variations in annual conception rates rather than a steady increasing trend.


       
To ensure statistical reliability, bulls with fewer than five recorded breeding were excluded and only those with more than five breeding records were analysed (Table 4). The chi-square test showed no significant variation in conception rates across different bulls (p>0.05). This uniformity is likely due to the rigorous semen quality evaluations, which ensured that only bulls with optimal fertility parameters were selected and maintained for breeding.


       
Logistic regression was used to quantify the influence of non-genetic factors on conception probability. Using 2024 as the baseline year, the model estimated whether conception rates in previous years significantly increased or decreased (Table 5). Similarly, with December as the baseline month, the likelihood of significant variation in conception across different months was assessed (Table 6).




       
Heat stress negatively affects fertility by disrupting oestrous cycles, reducing oocyte quality, increasing embryonic loss, altering the uterine environment and lowering semen quality (Dash et al., 2016; Hansen, 2020; Roth, 2021). High temperatures suppress GnRH secretion, impair follicular development and increase oxidative stress, leading to lower conception rates (Wolfenson and Roth, 2019; Schüller  et al., 2017). Bulls also experience reduced sperm motility and viability during heat stress (Yeste, 2016).

To mitigate these effects, breeding programmes should aim mating during cooler months and provide shade, ventilation, misting and electrolyte supplementation to reduce heat stress. Nutritional adjustments, improved oestrus detection methods and genetic selection for heat resilience are essential strategies. Regular monitoring of semen quality and rotational use of bulls can further optimise fertility outcomes (Dash et al., 2016; Hansen, 2020).

The study revealed that the overall conception rate in Vechur cattle over a 14-year period was 51.40%. Among the non-genetic factors evaluated, significant variations were observed across months and years. The lowest conception rate was recorded in August, coinciding with the peak monsoon period in Kerala, suggesting that high humidity and associated climatic stress may adversely affect fertility. In contrast, no significant effect was observed for the time of breeding (forenoon vs. afternoon) and conception rates remained consistent across different breeding bulls, likely due to rigorous selection and regular evaluation of semen quality. These findings reveal the critical role of non-genetic factors in determining reproductive efficiency in dwarf indigenous cattle breeds. Aligning breeding schedules with favourable climatic windows and minimising heat and humidity stress through improved management practices can enhance fertility outcomes. Furthermore, the uniformity observed across bulls highlights the effectiveness of proper sire selection and monitoring programs. The insights from this study helps in formulating breeding strategies for Vechur cattle, supporting their sustainable conservation and improved productivity under tropical conditions.

The present study was supported by funding from Kerala Veterinary and Animal Sciences University.
 
Disclaimers
 
The views and conclusions expressed in this article are solely those of the authors and do not necessarily represent the views of their affiliated institutions. The authors are responsible for the accuracy and completeness of the information provided, but do not accept any liability for any direct or indirect losses resulting from the use of this content.
 
Informed consent
 
All animal procedures for experiments were approved by the Committee of Experimental Animal Care and handling techniques were approved by the University Animal Care Committee.

The authors declare that there is no conflicts of interest regarding the publication of this article. No funding or sponsorship influenced the design of the study, data collection, analysis, decision to publish, or preparation of the manuscript.