The development of a model for artificial insemination by backyard pig farmers in Thailand

Abstract

The aim of this study was to develop and evaluate a model of artificial insemination (AI) technology transferable to backyard pig farmers for strengthening pig productivity in rural areas in Thailand. An AI center, criteria and process for farmer selection, an AI training program, AI practice in pigs, and a backyard farmer network were created as a model. Five hundred and thirty-one farrowing records from 307 sows were analyzed. Farrowing rates (FR), total number of piglets born (TB), and number of piglets born alive (BA) were studied. AI has led to better results in FR, TB, and BA than natural mating (P < 0.05). Demographic factors such as sex and age of farmers only had significant effects on FR (P < 0.05), while educational levels and farmers' AI experience had significant effects on TB and BA (P < 0.05). Model factors such as type of training, semen delivery systems, and semen storage time did not have significant effects on FR, TB, and BA. In conclusion, using this model, we found that backyard farmers could be trained in AI techniques in order to achieve equally good results as experienced technicians. Male farmers within working age or older, with a high school education or higher are the recommended target groups for implementing this model. Strong cooperation with clear responsibilities of all stakeholders could create a good network of backyard pig farmers. Therefore, the implementation of AI techniques in pig production can be applied to the target group with an aim towards a sustainable, self-sufficient community.

Factors influencing success of artificial insemination of pigs using extended fresh semen in rural smallholder pig farms of Rwanda

“…The poor performances in young farmers could be explained by the fact that the young have fewer financial resources and are more interested in other activities compared to the other groups of age. Contrary, Visalvethaya et al (2011) in Thailand reported that old farmers have better performances than young farmers. This difference between findings could be explained by the context specificity of the two areas.…”

“…In fact, Mbuza et al (2016) reported that, in Rwanda, a large proportion of males is more involved in pig management activities such as feeding, cleaning, treating and record keeping compared to females; and good farm management is among the factors influencing fertility of pigs (Merks et al, 2000). Moreover, Visalvethaya et al (2011) argue that the male farmers have better management skills than female ones, especially in oestrus detection, where the males detect heat better than their female counterparts. Similarly, Visalvethaya et al (2011) reported that male managed farms present better fertility than female headed ones in Thailand.…”

“…Moreover, Visalvethaya et al (2011) argue that the male farmers have better management skills than female ones, especially in oestrus detection, where the males detect heat better than their female counterparts. Similarly, Visalvethaya et al (2011) reported that male managed farms present better fertility than female headed ones in Thailand.…”

“…Zanu et al (2012) in Ghana reported that adoptions of improved technologies are associated with farming experience. Indeed, Visalvethaya et al (2011) suggest that experience is crucial for pig reproduction particularly in heat detection.…”

“…Moreover, the conception rates in AI and natural mating in pigs are the same (Kadirvel et al, 2013). Indeed, the fertility rates of 80 to 90%, using AI, are common in many pig farms (Roca et al, 2006) and artificial insemination can lead to better results in farrowing rate and litter size than natural mating (Visalvethaya et al, 2011;Am-in et al, 2010;Kadirvel et al, 2013).…”