Farm Typology Research Articles

Multivariate Typology of Osmanabadi Goat Farming in its Home Tract: A Cluster Analysis

The study was conducted to identify the typology of the Osmanabadi goat-keeping households and farms in a home tract of the breed during 2020-21. Hierarchical and K mean clustering techniques were used to classify 107 households into three homogenous clusters. In extensively large flock keeping households with large landholdings (C1, n=25, 23%), the respondents were using scientific practices to a great extent than the households with extensively keeping small flock with small landholdings (C3, n=59, 55%). Goat rearing was being the sole farm activity of relatively more households in C3, where primarily women had control over farm decisions and returns than the households who semi-intensively kept medium flock with medium landholding (C2, n=23, 22%). Households in C3 were mostly using open sheds, had lower goat income than the rest of the clusters. Households in C2 were higher in employment generation than households in C3. The typologies of Osmanabadi goat-keeping households showed significant heterogeneity in clusters and critical points which need to be considered to find sustainable solutions. Government policies and extension approaches are likely to be more effective if they consider the heterogeneity in the planning and delivery of extension interventions.

Understanding Farm Diversity through Typology for Technological Interventions in Western Plain Zone of Uttar Pradesh, India

The farming systems having diverse characteristics need to be understand for tailoredtechnological interventions. Farm typology designates the heterogeneous farmers’characteristics in to homogenous groups to understand the factual situation in the region.The multivariate analysis viz. PCA and Cluster analysis performed to minimize data andgroup them into homogenous characteristics by various farm variables. A cross sectionsurvey of 120 farmers in WPZ of Uttar Pradesh was carried out and identified 9 significantvariables and generated 4 PCs from PCA. Hierarchical clustering of PCs leads to groupingfarms into homogenous class. The predominant farm types based are type-1 (22.5%)livestock based intensive farms, type-2 (23.3%) are resource endowed large farms, type-3(10.8%) are crop based marginal farms and type-4 (43.3%) are small farmers with highprofit margin. Large farms are integrated with crop and animal components earning higherincome. The results show that the diversified farms with both livestock and crop sectorsare reaping better income and technology adoption capacities.

Finding the ecological farmer: A farmer typology to understand ecological practice adoption within Europe

Agricultural policies are now orientated towards sustainable food production which integrate climate and biodiversity targets. Increasing the uptake of ecological approaches is intrinsic to the success of these policies. but this is contingent on farmer acceptability of these practices. We employ a cross-European farmer survey to explore the perspectives of producers and to derive a typology based on their ecological self-identities.Using a one stage latent class model we find four types and examine common factors which may correlate to farmer membership of a particular group. We find two types which are positive towards uptake of ecological approaches but are mainly differentiated by their responses to social pressure and the acceptance of ecological practices within their supply chains. A further group reveals a multifunctional identity, which balances ecological with food productivity goals, whereas a final group show indifference towards ecological approaches and may align with previous work identifying productivist farming identities. As Governments are seeking to promote transition within the industry we argue for clear policy intent inmessaging, as well as approaches which support supply chain dialogue to target particular groups of farmers for real behavioural change.

Characterizing cassava farmer typologies and their seed sourcing practices to explore opportunities for economically sustainable seed business models in Rwanda.

The overdependency on local cassava varieties and informal seed sources by farmers in Rwanda has contributed to the spread of cassava viral diseases. The use of improved planting materials made available through formal seed sources, that assure seed quality, is one way to prevent future disease outbreaks. In order to increase the availability of, and farmers access to, such materials there is increasing interest to develop seed business models. This study aims to understand seed sourcing practices of different farm typologies to inform the development of tailored seed business models. A total of 390 farmers were interviewed and the collected data was analyzed into clusters, resulting in seven farm typologies. Seed sourcing strategies, seed replacement dynamics and purchasing behavior of these typologies were explored via a seed tracing study. We find that more commercial oriented farmers have better access to formal seed sources. Nevertheless, the majority of farmers in all typologies accessed new varieties and quality cassava seed via informal channels. At both formal and informal sources, cash investments in seed were mainly made by the categories of better-off farmers, and were one-time investments to acquire a new variety. Based on farmers current seed sourcing practices, clarifications on the differences between farmers and their willingness-to-pay, the roles of seed degeneration, cost-benefit analysis, value propositions and profit formulas seem important requirements for the further development of viable cassava seed business models. We conclude that tailoring seed business models can have a high potential as it acknowledges differences among farmers, but that careful coordination is needed to ensure that one approach or intervention does not contrast with and/or undermine the others.

Utilizing a farm typology for the development of rubber-based farming: a case from Moneragala district, Sri Lanka

Utilizing a farm typology for the development of rubber-based farming: a case from Moneragala district, Sri Lanka

US farm typology from agricultural census: labor resource analysis

This article analyzes the labor resources by farm type in the United States based on the 2017 Agricultural Census. The subject of the research is the system of statistical indicators of the availability and composition of labor resources, the object is the population of farms in the United States. Based on the study of the US experience, it is proposed to expand the program of the agricultural census of the Russian Federation under the section “Labor resources” and the system of groupings of observation units, including typological ones, when publishing the results. The analysis of labor resources by types of farms in the United States showed that there are significant differences in the availability and composition of labor resources.

Profiling Goat Farm Enterprises Under The Prism Of Sustainability: The Role Of Financial Ratios, Socio-Demographic Characteristics And The Waste Management In Goat Enterprises

Sustainable livestock farming is a hot issue worldwide. Last decade there is an intense transformation that affect all aspects of the sector like economic, social and environmental. This transformation has to deal with the increasing market globalization, the changes in Common Agriculture Policy and the new social awareness in environmental issues. The aim of this study is to profile and classify goat farms according to their performance using farm-level data that concerns economic, social and environmental sustainability. A combination of multivariate analysis techniques, such as Principal Component Analysis and Cluster Analysis were developed for the aggregation of synthetic indicators and for the creation of farm typologies. According to results, Greek goat farming achieves a low performance in almost all pillars of sustainability, but if the sector adopt sustainable practices there is the margin to become more elastic and competitive.

Typology of red maradi dairy goat farms in the north east of Benin

1 ABSTRACT The characterization of livestock systems enables to identify the diversity of livestock farms in order to define development actions. The aim of this study is to characterize the different farming practices observed in the Red Maradi goat farms located in the North East of Benin. Data collection took place between August and December 2019, in 90 goat farms with at least one breeding nucleus of the Red Maradi breed. Using the Multiple Correspondence Factor Analysis (AFCM) and Ascending Hierarchical Classification (CAH) methods, a typology of Red Maradi goat farms in the region was developed. Thus, four types of breeding of Red Maradi goats were identified. Agro-pastoralists, traders (27.59%) and craftsmen (17.24%) mostly from the Bariba socio-cultural ethnic group (38.72%) characterize wandering peasant farms (type 1). They are responsible for herds of modest numbers (15 ± 8 heads) made up by purchase. The mode of rearing goat straying is practiced in 93.1% of these farms against 6.9% of semi-straying. The animals hardly have a sheepfold. The farms (type 2), semi-scavenging peasant herds, are mainly characterized by breeders and agro-breeders of the Fulani and Gando socio-cultural ethnic group (56%). They are responsible for small herds (16 ± 8 heads) and practice the seasonal straying of goats (88%). The animals are housed on these farms (58.07%) in a basic sheepfold and receive crop residues as a supplement. The breeders of type 3, semi-improved peasant breeding are from a very diverse socio-cultural ethnic group Dendi (23%), Yorouba (19%), Fon (11.5%), Bariba (12.5%) with a relatively higher level of education. Over 75% of type breeders have reached secondary level. They combine their main activity, public service, commerce and crafts, the breeding of goats with herds of relatively larger size (20 ± 15 heads). The animals are housed in more improved sheepfolds built in roughcast or hard earth and in 75% of these farms receive food and water in the pen. Type 4, semi-intensive dairy farming of Red Maradi goats, brings together farm farms producing and upgrading goat's milk. Fon (51.25%) and Bariba (48.75%) mostly own these farms. They are responsible for larger herds (57 ± 7 heads) so 35% is made up of the Red Maradi goat and the rest of the Saanen breed. The animals have a permanent sheepfold and, in addition to the basic ration consisting of fodder, a production supplement consisting of concentrate.

Farm typology for planning targeted farming systems interventions for smallholders in Indo-Gangetic Plains of India

Due to complexity of smallholder farms, many times technologies with great potential fail to achieve the desired impact in leveraging productivity and profitability of the farming community. In the Indo-Gangetic Plains there is an urgent need to understand the diversity of farm households, identifying the main drivers deciding their system thus, classifying them into homogenous groups. In the present study, the diversity of smallholder farms was assessed using crop, livestock and income related characteristics and associated farm mechanization. Using principal component analysis and cluster analysis for 252 farm households, 4 farm types were identified i.e. Type 1. Small Farm households with cereal-based cropping system and subsistence livestock (39%), Type 2. Small Farm households with diversified cropping system dominated by cereal and fodder crops with only cattle herd (9%), Type 3. Marginal Farm household with diversified cropping system dominated by cash crop and herd comprising of only cattle (39%), Type 4. Marginal Farm household with diversified cropping system dominated by cereal crops and herd dominated by small ruminants (12%). Based on the constraints identified for different components of farming systems, low-cost interventions were planned for each farm type. These interventions have resulted in 84.8–103.2 per cent increase in the income of the farm HH under study suggesting usefulness of typology-based intervention planning in increasing income of small farm holders.

Assessing the economic impact of diseases in Mediterranean grow-out farms culturing European sea bass

The aim of this work is to propose a novel and formal approach to evaluate the direct costs of diseases caused by different pathogens as well as their economic impact on typical Mediterranean grow-out farms culturing European sea bass under different scenarios of production related to the biomass produced (farm size) and the size of the fish produced (production strategy). We employ a deterministic static model to simulate the annual income statement of those facilities to evaluate the direct costs caused by different diseases as well as, through a partial budget and sensitivity analyses, the economic impact of them. An important conclusion of this work is that the profitability and economic viability of sea bass grow-out farms suffering recurrent outbreaks of diseases caused by different pathogens depend on the farm typology (farm size) as well as the decisions taken by owners/investors about the size of the fish produced and sold in the market. Our estimations show that as the larger is the farm and the size of the fish produced, the larger are the direct cost of a disease outbreak. However, the economic impact on the net operating profit is significantly worse as smaller is the farm and smaller the fish produced. The conclusions of this research stress the need for small producers to pay attention and devote resources to prevent and treat disease outbreaks.

Analysis of Smallholders’ Livelihood Vulnerability to Drought across Agroecology and Farm Typology in the Upper Awash Sub-Basin, Ethiopia

Assessing the magnitude of smallholder farmers’ livelihood vulnerability to drought is an initial step in identifying the causal factors and proposing interventions that mitigate the impacts of drought. This study aimed to assess smallholders’ livelihood vulnerability to the drought in the upper Awash sub-basin, Ethiopia. Household (HH) and climate data were used for indicators related to sensitivity, exposure, and adaptive capacity that define vulnerability to drought. The vulnerability of farmers’ livelihood to drought was compared among the studies agroecological zone (AEZ) and farm typologies. The result illustrated a diverse magnitude of vulnerability index (VI) ranging from −1.956 to −4.253 for AEZ. The highest magnitude of VI was estimated for livelihood in the lowland AEZ, while the lowest magnitude of VI was estimated in midland AEZ. This could be accounted for by the fact that lowland farmers shown the highest exposure (0.432) and sensitivity (0.420) and the lowest adaptive capacity (0.288). A closer look at farmers’ livelihood typology, in each of the AEZ, showed substantial diversity of farmers’ livelihood vulnerability to drought, implying potential aggregations at AEZ. Accordingly, the vulnerability index for livestock and on-farm-income-based livelihood and marginal and off-farm-income-based livelihood typologies were higher than the intensive-irrigation-farming-based smallholders’ livelihood typology. Based on the result, we concluded that procedures for smallholders’ livelihood resilience-building efforts should better target AEZ to prioritize the focus region and farmers’ livelihood typology to tailor technologies to farms. Although the result emphasizes the importance of irrigation-based livelihood strategy, the overall enhancement of farmers adaptive capacity needs to focus on action areas such as reducing the sensitivity and exposure of the households, improving farmers usage of technologies, diversify farmers’ livelihood options, and, hence, long-term wealth accumulation to strengthen farmers’ adaptive capacity toward drought impacts.

Context Specificity and Time Dependency in Classifying Sub-Saharan Africa Dairy Cattle Farmers for Targeted Extension Farm Advice: The Case of Uganda

Despite the huge potential for milk production, interventions to improve productivity in sub-Saharan Africa (SSA) are barely based on specified farm classifications. This study aimed to develop robust and context-specific farm typologies to guide content of extension farm advice/services in Uganda. From a sample of 482 dairy farmers, we collected data on farmer socio-demographics, farm management practices, ownership of farm tools and facilities, willingness to pay for extension services, milk production, and marketing. Farm typologies were obtained based on principal component and cluster analyses. Thereby, of the three dairy production systems that emerged, small-scale, largely subsistence yet extensive and low productive farms were more prominent (82.6%). Farms that were classified as large-scale, less commercialized yet extensive with modest productive systems were more than the medium-scale commercial farms with intensive and highly productive systems. However, the later were considered to potentially transform dairy farming in Uganda. It was also predicted that the validity of our farm classification may persist until half of the farms have moved between clusters. The study gives new insights on dairy production systems in Uganda, which can be used to organize more targeted research on farmers’ extension needs for facilitating delivery of relevant and effective extension services and designing appropriate extension policies.

The potential for aflatoxin predictive risk modelling in sub-Saharan Africa: a review

This review presents the current state of aflatoxin risk prediction models and their potential for value actors throughout the food chain in sub-Saharan Africa, with a specific focus on improving smallholder farmer management practices. Several empirical and mechanistic models have been developed either in academic research or by private sector aggregators and processors in high-income countries including Australia, the USA, and Southern Europe, but these models have been only minimally applied in sub-Saharan Africa, where there is significant potential and increasing need due to climate variability. Predictions can be made based on historic occurrence data using either a mechanistic microbiological framework for aflatoxin accumulation or an empirical model based on statistical correlations with climate conditions and local agronomic factors. Model results can then be distributed to smallholders through private, public, or mobile extension services, used by policymakers for strategy or policy, or utilised by private sector institutions for management decisions. Specific agricultural advice can be given during the three most critical points in the phenological cycle: preseason insight including sowing timing and crop varieties, preharvest advice about management and harvest timing, and postharvest optimal practices including storage, drying, and market information. Model development for sub-Saharan Africa is limited by a dearth of georeferenced aflatoxin occurrence data and real-time high resolution climate data; the wide diversity of farm typologies each with significant information and technology gaps; a prevalence of informal market structures and lack of economic incentives systems; and general lack of awareness around aflatoxins and best management practices to mitigate risk. Given advancements towards solving these challenges, predictive aflatoxin models can be integrated into decision support platforms to focus on optimisation of value for smallholders by minimising yield and nutritional losses, which can propagate value throughout the production and postharvest phases.

Targeting Irrigation Expansion to Address Sustainable Development Objectives: A Regional Farm Typology Approach

Sustainable water management is a core sustainable development goal (SDG) that also contributes to other SDGs, including food and water security, ecosystem health, and climate adaptation. To achieve these synergies, policies must target efforts to regions that best correspond with development objectives. This study designs a targeting strategy for irrigation expansion in southern Mexico—a region long considered to have strong potential for sustainable irrigation development. We use an integrated farm typology and decision tree approach to identify priority municipalities for irrigation expansion. We use multivariate statistics to examine the relationships among farm characteristics in 933 municipalities, classifying each according to four farm types: lowland, midland, midland-irrigated, and highland. We then partition municipalities into 11 farm-type subgroups, each ranked by priority level for receiving irrigation interventions following Mexico’s National Water Program guidelines. Results identify a ‘highest-priority’ subgroup of 73 municipalities comprised mostly of midland and highland farm types. These types are characterized by low irrigation use, small farmland areas, high vulnerability to climate, high marginalization (poverty), strong representation from indigenous communities, low maize yield, and high rates of subsistence production. Findings provide a crucial first approximation of where irrigation expansion would best address water policy priorities and sustainable development objectives in southern Mexico. This study also provides a useful framework for scaling organizations tasked with targeting development efforts across large spatial scales.

Organic Nutrient Source Allocation and Use in Smallholder Farming Communities: What Are We Missing?

Organic nutrient sources (ONS) are managed as a key resource by smallholder farmers to maintain the productivity of soils. Recycling of ONS by applying them to soils is a globally dominant strategy of ecological nutrient management. Understanding how ONS produced on-farm are allocated and what drives farmer decision making around their use is critical for sustainable nutrient management in smallholder agroecosystems. Using focus group discussions and a survey of 184 farming households, we studied socio-economic, socio-cultural, and environmental drivers of ONS allocation and use at the farm scale in three contrasting agroecological zones of western Kenya. Farm typologies of ONS management were also developed using cluster analysis based on resource endowment and the connectedness of farmers, management norms, and interaction with extension. Our findings suggest that the more resource endowed a farmer is, the more ONS are allocated to the main plot within the farm. We also observed that farmers preferred allocating more resources to plots that were considered more fertile. Land tenure had an important influence, in that main plots not owned by farmers were more likely to retain ONS such as crop residues. Management of residues is dependent on farmer gender, for instance, female farmers tended to burn legume residues in particular, which is notable since these higher quality residues are often considered key to sustainable soil nutrient management. Farm typologies featured different allocation patterns of ONS and were associated with resource endowment and farmer networks, including external ties to extension agents and internal ties to other farmers. Finally, there was a strong overarching influence of agroecological zone that often escapes characterization on the allocation of ONS. As research and development organizations continue to engage with smallholder farmers to reduce the burden of global food insecurity, the insights gained by this research will allow better anticipation of drivers and obstacles to improved nutrient management in these farming landscapes and communities.

Factors associated with grain feeding in dairy farms located in the central-western region of Paraná State, Brazil

This study aimed to investigate factors associated with grain feeding and determine the typology of dairy farms that use high-grain diets. Twenty-two farm operators were interviewed in three municipalities located in the central-western region of Paraná state, Brazil. Information on reproductive and nutritional management practices, sociodemographic characteristics, and farm performance was collected. Data were analyzed using exploratory factor analysis, hierarchical cluster analysis, and multiple linear regression. Three factors (F1, F2, and F3) were extracted, which together explained 82.61% of the total variance. F1 comprised diet quality, technology, and breeding composition. F2 comprised labor and size. F3 comprised feed quality and schooling. Farms were classified into four groups and compared in terms of factor scores and performance parameters. Group 1 had the highest mean score on F1 (0.715), group 4 on F2 (1.642), and group 2 on F3 (1.116). Groups 4 and 1 had the highest milk productivity (2043.50 and 399.52 L day−1, respectively) and labor efficiency (418.16 and 148.63 L worker−1 day−1, respectively). Group 4 also had the highest mean number of cows per worker (25.52 cows worker−1). Regression analysis revealed that diet quality, technology, and breeding composition (F1) explained the variance in cow productivity. Labor and size, (F2) explained the variance in number of cows per worker. Daily productivity and labor efficiency were explained by both F1 and F2. Feed quality and farm operator’s level of schooling did not explain the variation in any of the variables. We found that roughage quality, breeding technology, and herd breed composition are the major factors associated with grain feeding. Farmers who feed cows high-quality roughage throughout the year and invest in genetic improvement and selective breeding strategies are more likely to adopt high-grain feeding and have high milk productivity.

Application of Geographic Information System and Multivariate Techniques for the Delineation of Farm Typologies

Application of Geographic Information System and Multivariate Techniques for the Delineation of Farm Typologies

Identifying farm-type specific entry points for innovations in weed management in smallholder inland-valley rice-based systems in West Africa

In West Africa, weeds are major production constraints in rain-fed lowland rice systems—often located in the inland valleys. Weed management technologies have been developed and promoted in such rice systems, but adoption by farmers lags behind, probably because of insufficient considerations of the system diversity or the farm-specific characteristics during technology development or promotion. This study aimed to identify farm-type specific entry points for innovations in weed management practices of smallholders in rice-based systems in inland valleys. We conducted farm surveys in the Mono Couffo region of Benin in 66 fields in 2010 and 2011 in a range of socio-economic settings typical for smallholder farms. A combination of multivariate analyses using Principal Component Analysis and Agglomerative Hierarchical Cluster is helpful in constructing farm typologies. This categorization, in turn, enables the assessment of farm-type specific weed management strategies and consequently the identification of entry points for innovation. Specific entry points for innovations in weed management include: (i) complementing the existing range of curative options by more preventive measures, (ii) diversifying the existing range of curative measures (mainly hand weeding and herbicide application) by measures that are both non-chemical and labor-saving, and (iii) improving women farmers’ access to information and inputs by targeted training endeavors and conducive credit systems.

The Role of Education in the Transition towards Sustainable Agriculture: A Family Farm Learning Perspective

This paper deals with the analysis of decision-making processes at the family-farm level with reference to the transition towards sustainable agriculture. Despite literature that has underlined the relevance of education in strategic decision making, less attention has been devoted to the (family) collective decision-making process by taking into account the maximum level of education of the family members regardless of the position and whether they are the manager of the family farm or not. Therefore, this paper tries to fill a gap in literature by emphasizing the family farm’s collective decision-making process. In order to empirically measure this relevance, an econometric model was carried out that allowed us to evidence clear differences in the transition paths among various typologies of family farms on the basis of the level of education. Our results confirm the impact of education at the collective family level on transition towards more sustainable agricultural practices. This is particularly true in remote rural areas, where the transition is realized with higher intensity with respect to other territorial contexts. This brings about policy implications on enskilling farmers and upgrading their level of human capital.

Combining the best of two methodological worlds? Integrating Q methodology-based farmer archetypes in a quantitative model of agri-environmental scheme uptake

Increasing farmers’ acceptance and adoption of environmentally beneficial farming practices is essential for mitigating negative impacts of agriculture. To support adoption through policy, it is necessary to understand which types of farms or farmers do or do not (yet) apply such practices. However, farmers are not a homogeneous group and their behavior is subject to a complex array of structural, socioeconomic, and socio-psychological influences. Reducing this complexity, farmer typologies or archetypes are useful tools for understanding differing motivations for the uptake of sustainable farming practices. Previous investigations of the role of farmer archetypes in the adoption of such practices rely on either purely qualitative or purely quantitative methods in data collection, typology creation, and hypothesis testing. Our study combines both approaches by classifying survey respondents into farmer types based on a previous Q methodological study. We then use these types in a two-part regression model that aims to explain participation in agri-environmental schemes (AES) and the level of scheme participation. To control for farm structural factors, we additionally link our questionnaire data to secondary data from the farm accountancy data network. Results indicate that in Austria, AES are attractive to all types of farmers, but the level of participation (AES income per hectare) in these schemes differs between archetypes: Profitability-oriented farmers participate less, and nature-oriented farmers participate more than other types. This suggests that monetary compensations for sustainable farming practices are not perceived as sufficient by certain groups of farmers, and policy makers need to consider additional kinds of incentives.