Leverages for on-farm innovation from farm typologies? An illustration for family-based dairy farms in north-west Michoacán, Mexico

Resúmen

Knowledge on farm diversity provides insight into differences among farms, enables scaling from individual farm to farm population level and vice versa, and has been used in the definition of recommendation domains for introduction of novel technologies. Farm diversity can be broadly described in terms of resource endowment and resource use strategy, or in other words, in terms of scale and intensity of production. Measuring intensity of production requires much greater monitoring effort than measuring scale of production, and often only proxies of production intensity are used. Using data from a regional farm survey and from intensive on-farm monitoring the question addressed in this paper is to which extent results of farm surveys that measure primarily scale of production can inform on-farm interventions aimed at improving farm performance. The survey included a random sample of 97 out of 664 smallholder dairy farmers in a community in north-west Michoacán, Mexico. Farm types were identified by a combination of Principal Component Analysis to reduce the dimensionality of the dataset, followed by Cluster Analysis. The survey was complemented with detailed analyses of costs, revenues and productivity on 6 farms over the course of one year. Survey results revealed considerable variation among the dairy farms in land area, livestock units, amount of hired labour, and infrastructure and equipment, which led to the distinction of 4 farm types. Indicators for animal health management and feeding strategies were uniform across the 4 types. The farm types matched the distinction of family-based and semi-intensive farm types used in Mexico. The detailed analyses of the individual farms belonging to the different types, however, revealed differences in resource use strategies reflected in differences in animal productivity, labour productivity and return to labour. Differences in animal productivity and labour productivity were explained by stocking rate, albeit in different ways. Return to labour was strongly related to cost of feed. Profitability was negative for all farms and was on most farms related to high external feedstuff costs, which constituted 59–89% of the feed cost of the animal ration. The results indicate that in addition to variables reflecting resource endowment or scale of production, typologies that aim to inform on-farm interventions need to consider farm characteristics that reflect intensity of production. Which variables should be selected will need to be determined in a preliminary assessment. To enhance internal resource use efficiency as was the purpose in the current study, candidate variables expressing intensity could include the share of external feed in the ration and proxies of internal resource use, e.g. reflected in crop and milk yields. Opportunities for on-farm innovation arising from the analyses are discussed from the perspective of labour flexibility, low costs and use of internal resources.