Innovation adoption and farm management practices in the Canterbury dairy industry

Abstract

This research examined technology adoption behaviours of Canterbury (New Zealand) dairy farmers and the socio-demographic, farm and information seeking characteristics (ISCs) associated with adoption. Ten farm management practices (FMPs) were selected based on their adoption and promotion by the Lincoln University Dairy Farm (LUDF) which is a commercially orientated demonstration farm. An email-based electronic questionnaire collected quantitative and qualitative data from Canterbury dairy farmers identified as holders of dairy effluent discharge consents. The questionnaire was distributed to 647 farmers for whom valid email addresses were available (64% of all consent holders). The response rate was 22%. Data was analysed using SPSS20. Respondent ages ranged from less than 30 years to greater than 70 years and averaged 47 years. This compares to average farmer ages of 50 and 58 reported in 2012 media. Nearly half of respondents had greater than 20 years of industry experience and 52% had multiple farm interests compared with a New Zealand wide estimate of 20% reported by van Bysterveldt in 2012. Sixty six per cent of respondents had post-school education compared to 38% of Canterbury adults reported by Statistics New Zealand. Seventy nine per cent of respondents were farm owners/owner-operators and 12% were equity managers. Average farm size was 231 effective hectares compared to an average Canterbury dairy farm of 226 hectares reported by LIC and DairyNZ in 2012. Average milksolids production of 433 kg per cow and 1538 kg per effective hectare were 9% and 13% higher respectively than Canterbury averages reported by LIC and DairyNZ in 2012. Seventy five per cent of respondent farmers were producing more than 1400 kg milksolids per hectare compared to average Canterbury production of 1360kg. Ninety two per cent of respondents operate a moderate input farming system (DairyNZ System 2-4). Eighty five per cent of respondents visited the SIDDC/LUDF website and 51% attended LUDF focus days at least once in 2012. DairyNZ events were attended by 80% of respondents and 65% employed a private consultant/advisor. Respondents ranked the LUDF website, dairy newspapers and LUDF focus days as the most important information sources for learning about the LUDF’s results, and ranked demonstration farms, DairyNZ events and other farmers as the most useful information sources for learning about new agricultural innovations. The adoption level for individual FMPs ranged from 21-83% per cent. Adoption levels in descending order were: low and consistent grazing residuals (83%), re-grassing based on measurement of poor performing paddocks (81%), regular monitoring of cow body condition and responding with alternative management to achieve targets (71%), monitoring of soil moisture to drive irrigation practice (64%), creating a separate herd of young cows to enable preferential stock management to achieve targets (57%), pre-grazing mowing to lift animal intake (42%), a zero induction policy (40%), frequent small applications of nitrogen fertiliser and gibberellic acid simultaneously to promote production of high quality pasture (39%), use of Eco-nTM to mitigate urine nitrogen loss (33%), and synchronising of heifers to calve two weeks before the herd (21%). In general, adoption behaviour in relation to specific FMPs correlated poorly with other FMPs, indicating that each adoption is a specific decision rather than as part of an adoption package. Respondents’ comments indicated that non-adoption was typically a considered decision in relation to their specific FMPs and farming systems, rather than being the result of barriers such as unawareness, poor information or low education. A measure of innovativeness was constructed using the number of innovations adopted by each farmer. The level of explanation provided by socio-economic characteristics was weak, as was the association with ISCs. There was some evidence of farm size and higher production per cow and per hectare being associated with the number of innovations adopted. It is concluded that for this group of farmers, with generally high education and typically above average production per hectare, that the high variation in innovation adoption practices is very weakly associated with socio-demographics and ISCs, but is instead influenced by the relevance of an innovation based on its compatibility with farmers’ needs, their capacity to adopt, and their existing FMPs. This has implications for extension professionals, policy makers, and innovation adoption theory.