Success rate, genetic improvement and economic analysis of artificial insemination delivery models for smallholder pig production systems
Kadirvel Govindasamy
A B , Mokidur Rahman A , Tukheswar Chutia A and L. Anandakumar Singh A
A Division of Animal Production, ICAR Research Complex for NEH Region, Umiam, Meghalaya 793 103, India.
B Corresponding author. Email: velvet.2007@rediffmail.com
Animal Production Science 61(15) 1606-1612 https://doi.org/10.1071/AN19192
Submitted: 26 April 2019 Accepted: 7 June 2021 Published: 17 August 2021
Abstract
Context: Smallholder pig production systems in the north-eastern region of India are characterised by inefficiency due to use of unselected local pigs, and multiple breeding constraints such as paucity of superior germplasm, high mating costs, and poor access to artificial insemination (AI). Effective AI is the most viable option for genetic improvement and enhancing pig productivity.
Aim: The study was designed to assess the success rate and economic efficacy of four AI delivery models (Models I–IV): (I) AI at farmer’s doorstep through direct linkage to tribal farmers; (II) AI at farmer’s doorstep through trained, educated youth; (III) oestrus synchronisation and fixed-time AI; and (IV) mobile van-based AI delivery system. The study also sought to ascertain the benefits of adopting a crossbreeding program through AI over the existing use of local pigs for smallholder systems.
Methods: Semen collected from nine Hampshire boars was routinely utilised for AI after processing as per standard protocols. For Models I–IV, respectively, 259, 154, 183 and 284 sows from 75 villages/clusters were inseminated. Reproductive and litter performance as well as insemination cost were evaluated for each model. Growth performance of crossbred pigs obtained through AI was compared with that of local pigs in the smallholder production system.
Key results: Farrowing rate and mean litter size at birth were 74.90% and 8.57 ± 0.52 for Model I, 68.83% and 8.08 ± 0.37 for Model II, 80.87% and 9.31 ± 0.41 for Model III, 75.00% and 8.54 ± 0.64 for Model IV, and 81.58% and 6.81 ± 0.29 for natural service. Farrowing rate, litter size at birth and at weaning, and litter weight at weaning were significantly (P < 0.05) affected by AI delivery model in the order: Model III > Model I = Model IV > Model II. Litter weight at birth was significantly (P < 0.05) affected by AI delivery model in the order: Model III > Model I = Model II = Model IV. Lowest cost per insemination was found for Model IV (INR 319.00) followed by Model II (INR 449.00), Model III (INR 629) and Model I (INR 899). All models had lower cost than the natural service system (INR 2200). The growth performance of crossbred pigs obtained through AI was significantly (P < 0.01) higher than of the local pigs reared in the same production system.
Conclusion: The present study justifies the accessibility, feasibility and potential benefit of AI delivery models in smallholder/backyard pig production systems in the north-eastern region of India. Use of these AI delivery models will overcome the breeding constraints and reward farmers with more rapid genetic improvement in productivity with lower production costs. Model III (oestrus synchronisation and fixed time AI) shows best productivity and Model IV (mobile van-based AI delivery system) has lowest cost.
Implications: These AI delivery models will be effective for sustainable and economic piggery development and improve the socioeconomic livelihood of pig farmers in South Asian countries.
Keywords: artificial insemination (AI), delivery models, smallholder, backyard, pig production system, farrowing rate, economic analysis.
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