A Review of Characterization Approaches for Smallholder Farmers: Towards Predictive Farm Typologies

Abstract

Characterization of smallholder farmers has been conducted in various researches by using machine learning algorithms, participatory and expert-based methods. All approaches used end up with the development of some subgroups known as farm typologies. The main purpose of this paper is to highlight the main approaches used to characterize smallholder farmers, presenting the pros and cons of the approaches. By understanding the nature and key advantages of the reviewed approaches, the paper recommends a hybrid approach towards having predictive farm typologies. Search of relevant research articles published between 2007 and 2018 was done on ScienceDirect and Google Scholar. By using a generated search query, 20 research articles related to characterization of smallholder farmers were retained. Cluster-based algorithms appeared to be the mostly used in characterizing smallholder farmers. However, being highly unpredictable and inconsistent, use of clustering methods calls in for a discussion on how well the developed farm typologies can be used to predict future trends of the farmers. A thorough discussion is presented and recommends use of supervised models to validate unsupervised models. In order to achieve predictive farm typologies, three stages in characterization are recommended as tested in smallholder dairy farmers datasets: (a) develop farm types from a comparative analysis of more than two unsupervised learning algorithms by using training models, (b) assess the training models’ robustness in predicting farm types for a testing dataset, and (c) assess the predictive power of the developed farm types from each algorithm by predicting the trend of several response variables.

Research Progress and Conceptual Insights on Drought Impacts and Responses among Smallholder Farmers in South Africa: A Review

“…However, the contribution of smallholder farmers to food security cannot be underestimated. In sub-Saharan Africa, it is estimated that smallholder farmers produce about 75-80% of the food [26,27], which contributes tremendously to food security [28] and household welfare [29]. Despite the key role of smallholder farmers in enhancing food security, it is estimated that they use about 12% of the world's agricultural land [30], indicating high levels of marginalisation.…”

Potential Use of Beneficial Microorganisms for Soil Amelioration, Phytopathogen Biocontrol, and Sustainable Crop Production in Smallholder Agroecosystems

“…Currently, it is estimated that smallholder agroecosystems account for more than 50% of the food produced globally (Herrero et al, 2017). In Africa, they contribute about 75% of the total crop production and 50% of the animal products (Nyambo et al, 2019) and, thus, are significantly involved in rural poverty reduction, economic development, and food security. However, compared to largescale profit-driven systems, smallholder agroecosystems have limited land size, stringent financial resources, low market sharing, and product range, thus, are faced with more risks and vulnerabilities (Kuivanen et al, 2016;Herrero et al, 2017).…”

Towards sustainable agroforestry management: Harnessing the nutritional soil value through cocoa mix waste

“…These are farmers involved in farming a small piece of land (<5 acre) with farm operations largely managed by family labour and cocoa production serves as a primary source of direct income (70-100% of their yearly income) and livelihood (Nyambo et al, 2019;Ameyaw et al, 2018). Thus, for the majority of cocoa farmers in Ghana, fertility of soils under cocoa plantations is maintained through the recycling of nutrients through leaf biomass and decomposition of leaf litter (ISSER, 2004;Dawoe et al, 2010).…”