Assessing the effects of Sello Manos Campesinas (Peasant-Hands Seal) on smallholders participating in the programme

The Sello Manos Campesinas programme aims to make peasant farming visible by certifying four attributes that consumers recognise as proper from peasant farmers: i.e. originated from peasant farmers, artisanal production, healthy, and fostering local development. Two years after beginning operations, we collected information from focus groups in regards to the motivations of farmers for participating in the programme. With this information, we constructed a survey to evaluate those motivations and assess the effects and changes brought about by the seal on farmers businesses. This survey was applied to 100 farmers throughout the country. We identified three motivations for applying to be certified under the programme: improving sales, valuing the product and the production process, and receiving a personal recognition. However, for all practical purposes, their motivations were mainly for trading: raising product value, access new sales channels, and selling more products at a better price. Our results show that farmers actually use and promote the seal and that sales figures are promising, in spite of the scarce promotion of this seal to consumers. This situation could be explained as this seal makes customers trust the product, hence transforming their purchasing intentions. Acknowledgement : This research was financed by FIDA MERCOSUR CLAEH programme

Typification of farming systems for constructing representative farm models: two illustrations of the application of multi-variate analyses in Chile and Pakistan

If the fundamental precepts of Farming Systems Research were to be taken literally then it would imply that for each farm 'unique' solutions should be sought. This is an unrealistic expectation, but it has led to the idea of a recommendation domain, implying creating a taxonomy of farms, in order to increase the general applicability of recommendations. Mathematical programming models are an established means of generating recommended solutions, but for such models to be effective they have to be constructed for 'truly' typical or representative situations. The multi-variate statistical techniques provide a means of creating the required typologies, particularly when an exhaustive database is available. This paper illustrates the application of this methodology in two different studies that shared the common purpose of identifying types of farming systems in their respective study areas. The issues related with the use of factor and cluster analyses for farm typification prior to building representative mathematical programming models for Chile and Pakistan are highlighted. (C) 2003 Elsevier Science Ltd. All rights reserved