Factors influencing farmers' adoption of precision dairy technology

Modern dairy industry has an urgent need to promote a sustainable development strategy in China. Among them, precision dairy technology can be one of the most important ways to realize the modern dairy industry. Farm management can be transformed from the group to the individual for high efficiency and production level. However, the current adoption of precision dairy technology was still lacking so far. Most research was focused on the influencing factors of technology application and development. Only a few explored the current adoption of precision dairy technology. This study aims to investigate the adoption behavior of precision dairy technology by dairy farmers. The research areas were selected as the dairy-producing bases in North China (Hebei Province, Henan Province, Shandong Province, and Shanxi Province). 345 valid samples were firstly collected for the latter use. A binary Logit regression was then used to construct the theoretical framework for the farmers' adoption of precision dairy technology, according to the farmers' behavior and innovation diffusion theory. The results showed that: 1) The adoption rates of automatic cup stripping, identification, milk recording, and estrus monitoring technology by dairy farmers were 64.9%, 57.7%, 56.2%, and 37.7%, respectively. 2) The non-adoption of new technologies was ever more costly for dairy farmers, particularly for the unaffordable investment in the early stage of technology. 3) All technology popularization levels, breeding scales, and average daily milk production presented a significant positive correlation on the adoption of four technologies. By contrast, there was a significant correlation with the other factors on the adoption of at least two technologies. Among the four technologies, the automatic cup stripping technology was the least affected by the breeding scale, policy subsidies, and technical training. The automatic identification technology was the most affected by the satisfaction of breeding income and education level. The automatic milk recording technology was the most affected by the average daily milk production, and policy subsidies without technical training. The automatic estrus monitoring technology was the least affected by the education level and average daily milk production without the policy subsidies, particularly the most influence from the breeding scale and technical training. Therefore, it is recommended to implement the different promotion measures for the four technologies. Specifically, the automatic cup stripping technology can be focused on small-scale farms, due to the least influence from the farming scale. The automatic estrus monitoring technology can be focused on large-scale breeding farms, technical popularization, and training for the strong skills of data management for the dairy farmers.