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A phenomenological study was undertaken to explore the lived experience of community based farmers using ecological farming practices. These farmers support and are supported by their local communities through marketing their products directly to eaters and use farming practices that mimic and seek to enhance the vitality of natural systems and cycles on their farms. Farmers’ experiences are characterised by hard work for little pay, engaging the fullness of human capacity, living in harmony, spirituality, and a socio-political awareness of food and farms in society. Farmers’ experiences contribute to the development of concepts of doing, being, belonging and becoming, and have implications for concepts of occupational justice and occupational ecology. Further study of other forms of occupation that promote engagement in dialogue with the natural world is encouraged in order to develop these concepts and help to integrate theories of justice, ecology, and occupation.

The goal of this research was to explore the use of machine learning to assist in the development of knowledge-based systems (KBS) in dairy farming. A framework was first developed which described the various types of management and control activities in dairy farming and the types of information flows among these activities. This framework provided a basis for the creation of computerized information systems and helped to identify the analysis of group-average lactation curves as a promising area of application. A case-acquisition and decision-support system was developed to assist a domain specialist in generating example cases for machine learning. The specialist classified data from 33 herds enrolled with the Quebec dairy herd analysis service, resulting in 1428 lactations and 7684 tests of individual cows, classified as outlier or non-outlier, and 99 interpretations of group-average lactation curves. To enable the performance analysis of classifiers, generated with machine learning from these small data sets, a method was established involving cross-validation runs, relative operating characteristic curves, and analysis of variance. In experiments to filter lactations and tests, classification performance was significantly affected by preprocessing of examples, creation of additional attributes, choice of machine-learning algorithm, and algorithm configuration. For the filtering of individual tests, naive-Bayes classification showed significantly better performance than decision-tree induction. However, the specialist considered the decision trees as more transparent than the knowledge generated with naive Bayes. The creation of a series of three classifiers with increased sensitivity at the expense of reduced specificity per classification task, allows users of a final KBS to choose the desired tendency of classifying new cases as abnormal. For the main interpretation tasks, satisfactory performance was achieved. For the filtering tasks, performance was fai

Thesis (Ph.D.) -- McGill University. / Written for the Dept. of Sociology. Typewritten MS.

Thesis (M. Com. (Agr.)) -- Lincoln University, 2009. / Also available via the World Wide Web.

Thesis (Ph.D.)--University of Alberta, 1997. / Submitted to the Faculty of Graduate Studies and Research in partial fulfilment of the requirements for the degree of Doctor of Philosophy, Department of Anthropology. Also available online.

Dissertação(mestrado)-Universidade Federal do Rio Grande, Programa de Pós-Graduação em Geografia, Instituto de Ciências Humanas e da Informação, 2010. / Submitted by Caroline Silva (krol_bilhar@hotmail.com) on 2012-07-16T12:47:30Z No. of bitstreams: 1 dissertao eder - final.pdf: 2015896 bytes, checksum: 7b2b44f5fe8af22f4d32bdaf311c0583 (MD5) / Approved for entry into archive by Bruna Vieira(bruninha_vieira@ibest.com.br) on 2012-07-31T19:16:57Z (GMT) No. of bitstreams: 1 dissertao eder - final.pdf: 2015896 bytes, checksum: 7b2b44f5fe8af22f4d32bdaf311c0583 (MD5) / Made available in DSpace on 2012-07-31T19:16:57Z (GMT). No. of bitstreams: 1 dissertao eder - final.pdf: 2015896 bytes, checksum: 7b2b44f5fe8af22f4d32bdaf311c0583 (MD5) Previous issue date: 2010 / A presente dissertação visa analisar a inserção da agricultura familiar no contexto de domínio do capital hegemônico, representado pela penetração de grandes grupos econômicos, que no caso específico dominam a fumicultura. Para estruturar o entendimento de como se expressa essa dominação nas pequenas propriedades, definiu-se a localidade Passo dos Oliveiras, 1º Distrito de Canguçu - RS. O Passo dos Oliveiras é uma das 120 localidades do município. É possível identificar as inúmeras variáveis presentes com o avanço da fumicultura, como cultura agrícola preponderante e suas conseqüências no que concerne à supressão da diversidade produtiva, uma das características típicas das pequenas propriedades. Presenciamos na área a atuação de grandes grupos empresariais fumageiros que dão suporte ao avanço da fumicultura, via sistema integrado de produção, possibilitando o aumento nas áreas plantadas bem como nos volumes produzidos. A partir do predomínio do capital em larga escala no campo brasileiro, temos modificações estruturais no perfil da agricultura familiar nacional que a inserem em uma nova dinâmica, a qual está submetida a agentes externos ligados diretamente às leis de mercado. Assim, o objetivo deste trabalho é diagnosticar os agentes que operam no contexto da agricultura familiar e delinear as conseqüências básicas de sua atuação, procurando evidenciar as matizes teóricas que embasam o desenvolvimento sustentável. / This research aims at analyzing the insertion of family farming in the domination of hegemonic capital context, represented by the penetration of large economic groups that, in this specific case, dominate the tobacco farming. For structuring the understanding on how the domination of these small properties works, this study has been done in Passo dos Oliveiras, First District of Canguçu, state of Rio Grande do Sul. Passo dos Oliveiras is one of the 120 localities of Canguçu. It is possible to identify numerous an integrated production system, enabling an increase in the planted areas, as well as, in the produced amounts. From the predominance of large-scale capital variables resulting from the tobacco farming progress, such as predominant agricultural crop and its consequences in the suppression of productive diversity. The production diversity is one of the typical features of small properties. It was feasible to observe in this study field, the influence of large business groups that support tobacco farming, through in Brazilian field, there are structural changes that insert the family farming profile in a new perspective, which is submitted to external agents that are directly connected to market laws. Therefore, the purpose of this study is to spot the agents that are involved in family farming and chart the consequences of this process. Moreover, the research intends to evidence the theoretical references that underlie the sustainable development.

To date, research on organic farming and certification has focused on the production and trade possibilities of the industry. Farmers‟ opinions are underrepresented and this study endeavours to capture their opinions. In this study, the economic problem is to investigate the low participation of farmers in certified organic farming, highlight the economic benefits which are normally not clearly defined, as well as study the often complicated and frustrating certification process. The main objective is to investigate the determinants, which affect the smallholder farmer‟s participation, and to analyse farmers‟ perceptions of certified organic farming in the Limpopo Province of South Africa. The specific focus was on the participation of smallholder farmers in certified organic farming. The dependent variable was participation as measured by a farmer‟s decision to either certify their farm or not. The independent variables included factors that make up farmer and farm characteristics, certification and market related characteristics. The study used a standard questionnaire to obtain information from farmers. The research methodology, analysis and the presentation of the study was quantitative. The study used descriptive statistics (percentages, means, standard deviations, Chi-squares and significance intervals) to evaluate the significance of the variables. These were analysed and described quantitatively by making use of EVIEWS and IBM AMOS software. In estimating the influential factors, a probit model was adopted, and in analysing farmer perception, structural equation modelling was used. v Descriptive statistics indicated that among farmers interviewed, the majority (61%) were female farmers and 39 per cent were male farmers. Among the female respondents, 46% participated in certified organic farming and 15 per cent of female farmers were not certified organic farmers. From the male group, 29 per cent were certified organic farmers and 7% were not. In determining factors influencing farmer participation, three of the variables were positively associated with the probability of participating in certified organic farming, these being: the age of the farmer, membership to a farmer organisation and market premium prices for certified commodities. The other five significant factors were negatively associated with the probability of participating in certified organic production. These factors were: the gender of the farmer, the farmers‟ income, farming experience, information access and certification costs. All these factors tended to decrease the likelihood of participating. With the exception of the farmers‟ income and farming experience, all the significant variables had the expected signs. Farmers‟ perceptions of certified organic farming were analysed and the results showed that a high percentage of farmers had a positive view of certified organic farming. In other words, the perceived benefits of certified organic farming meet farmers‟ expectations. The perceived premium price of certified organic products is the most important factor affecting farmer perception. This is not unusual because South Africa‟s organic production is mainly focused on exportation and targets high value markets. As hypothesized, the costs associated with the certification process, that is: inspection costs (-0.578) and annual certification costs (-0.719), negatively affect farmer perception. In conclusion, a combination of factors influence a farmer‟s decision as to whether or not to participate in certified organic farming. One cannot rely only on specific factors to determine farmers‟ participation in certified organic farming. Farmer perception of certified organic farming is also an important aspect. The more farmers positively perceive the farming enterprise, the higher the rate of participation will be. The same applies to the perceived costs, which have a negative impact on participation. The study finally recommends that government complete and put into practice the South African organic regulations, which may motivate farmers to get involved in certified organic farming and encourage local capacity building in certified organic farming. However, in the meantime, government should place an vi emphasis on self-regulation within farmer groups and cooperatives for organic production, and set up a regulator to monitor the current activities. This would enhance interest from potential farmers, and strengthen consumer confidence. The study further recommends that information on organic farming should be improved by encouraging more research in this area, which will enable farmers, consumers and regulators to access data on socio-economic, production and trade in the industry. Government should support or create a partnership between farmers and processors to establish cost effective processing of organic products and to increase the availability of processed products for market. Government should assist non-certified smallholder organic farmers to become certified, potentially resulting in a price premium for their products and enhancing export capabilities. / Dissertation (MSc Agric)--University of Pretoria, 2013. / gm2014 / Agricultural Economics, Extension and Rural Development / unrestricted

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