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Vertebrate reproductive science and technology
RESEARCH ARTICLE

13 Evaluating reproductive performance benchmarks and determining factors influencing reproductive performance in smallholder beef cattle farms

M. Nkadimeng A B , E. van Marle-Köster B , M. L. Mphaphathi A , F. V. Ramukhithi A and M. L. Makgahlela A C
+ Author Affiliations
- Author Affiliations

A Agricultural Research Council, Animal Production Institute, Germplasm Conservation, and Reproductive Biotechnologies, Private Bag X2, Irene 0062, South Africa

B Department of Animal and Wildlife Sciences, University of Pretoria, Hatfield 0002, South Africa

C Department of Animal, Wildlife and Grassland Sciences, University of the Free State, Bloemfontein 9301, South Africa

Reproduction, Fertility and Development 36(2) 156 https://doi.org/10.1071/RDv36n2Ab13

© 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of the IETS

Smallholder beef farming plays a vital role in driving rural economies in South Africa (SA) and has the potential to alleviate poverty among livelihoods. However, reproductive performance in this sector is poor, which affects herd growth and profitability. The study aims to benchmark smallholder reproductive performance as measured by fertility indicators: pregnancy rate (PR), fetal and calf loss (FC), calving interval (CI), and days open (DO). The study further assesses the influence of animal and management factors on these indicators. A total of 3694 cow records from 40 smallholder beef cattle herds were sampled from five province of SA between 2018 and 2019 over two seasons: in Autumn (March–May) for pregnancy diagnosis and in Spring (September–November) for monitoring confirmed pregnancies (recording FC). The percentage of both abortions and calf mortality defined FC indicator. Calf mortality was recorded from birth to 21 days of life. The age of the last calf and gestation length for each participating cow were used to calculate DO and CI in days. Data on animal and herd management factors such as body condition score (BCS), cow age class, breed type, lactation status, culling old or nonproductive cows, record-keeping, and breeding and calving months were recorded. The preferred 25th quartile was used to describe the performance benchmark and the GLIMMIX procedure of SAS was utilised to determine animal and management factors influencing performance. The SAS frequency procedure was used to show average reproductive performance levels. Reproductive performance recorded an average of 50% pregnancy, 12% loss, extended CI (608) and DO (304). However, smallholder farms recorded benchmarks of 54% pregnancy, 1.4% loss, 152 DO, and 425 CI. The study revealed that management practices such as culling old/nonproductive cows, record-keeping, and calving and breeding seasons had a significant influence on reproductive performance (P < 0.05). Cow age class, breed type, BCS also significantly influenced performance indicators (P < 0.05). Cows with BSC 3 had higher odds of pregnancy rate [OR = 3.81], while cows in BCS 1 [OR = 3.254] and BCS 2 [OR = 3.775] experienced extended CI. Autumn-calving cows had longer CI [OR = 1.03] compared to summer-calving cows [OR = 0.34]. Furthermore, second calvers had higher odds of PR. However, both first calvers [OR = 2.218] and aged cows [OR = 3.827] recorded higher odds of FC. The recorded performance benchmarks suggest that improving management practises in smallholder beef cattle herds can optimise reproductive performance.