Farm Types Research Articles

Effects of gender and agricultural cooperatives on biodiversity conservation farming practices: evidence from an emerging economy

PurposeThis study explores the effects of gender and participation in agricultural cooperatives on biodiversity conservation farming practices in vegetable production.Design/methodology/approachThis study used data collected from a survey of 627 vegetable farmers in Viet Nam and employed the Ordered Probit regression model to examine the effects of gender and participation in agricultural cooperatives on biodiversity conservation farming practices.FindingsWe find that female vegetable farmers are more likely to conduct biodiversity conservation farming practices than male farmers. This gender difference is, however, removed when participation in agricultural cooperatives is controlled, suggesting that agricultural cooperatives effectively facilitate biodiversity conservation farming practices.Research limitations/implicationsIt is noted that our study is not free from some limitations. First, we conducted our study on vegetable farmers only. The biodiversity conservation practices in vegetable cultivation might be different from other types of farming. Future studies should be conducted with other types of agricultural cultivation. Second, we do not have enough data to explain why female farmers are more likely to adopt biodiversity conservation practices than male farmers. Future studies should capture biological and social aspects of gender differences to address this limitation.Originality/valueThis study contributes to the literature on biodiversity conservation by presenting empirical evidence on the effects of gender and agricultural cooperatives. Participation in agricultural cooperatives is revealed to facilitate the adoption of biodiversity conservation practices. In addition, we find that the education of farmers, the number of years that farmers have been living in the local area and the quality of land and water are positively related to the adoption of biodiversity conservation practices in vegetable production.

Navigating Social, Environmental, and Economic Complexities of Insect Farming to Contribute to Sustainable Agrifood Systems

Abstract Insect farming is increasingly recognized as an important component of sustainable agrifood systems that provide a variety of social, environmental, and economic benefits. This text explores the complexities of insect farming which must be considered to maximize its potential and thereby contribute to global sustainability goals. It explores diverse strategies for evaluating and optimizing the socio-economic and environmental benefits of insect farming and addresses insects’ diverse roles in circular food systems and their potential contributions to achieving the UN Sustainable Development Goals. By exploring the particularities of insect farming which vary according to the particular context of each region, this text highlights the ways in which local ecological, socio-economic, and cultural factors influence the outcomes of insect farming initiatives. The case exercises included are aimed at providing readers with an understanding of the role of insect farming in sustainable agriculture. Combining theoretical insights with practical examples, it provides a framework for developing locally adapted insect farming practices that maximize the benefits while minimizing the risks of this type of farming. The case exercises presented are aimed at providing students with experience in developing plans for insect farming scenarios that consider key social, environmental, and economic aspects related to sustainable insect production. Information © The Author 2024

Metabolomic Fingerprints: Seasonal and Farm-Specific Differences in Heterotrigona itama Bee Bread

Stingless bees’ products such as honey and bee bread are beneficial to human health. However, the metabolite composition within the products may differ according to spatial and temporal factors. This study aims to investigate the impact of spatial and temporal factors on the significant metabolite composition present in Heterotrigona itama bee bread collected from different seasons and types of bee farms. Thus, tandem mass spectrometry (LCMS/MS) based metabolomics analysis was used to achieve the said goal, focusing on H. itama bee bread samples, followed by multivariate analysis using the MetaboAnalyst platform. Our findings revealed significant metabolites that set bee bread samples apart. In terms of temporal factors, the analysis highlights specific metabolites exclusive to the wet season, such as flavones and flavonoids. However, in contrast, during the wet season, there are no significant metabolites in herbal farm samples. The results also underscore the significance of phenolic compounds in wet season samples and as vital metabolites distinguishing the groups. This study highlights a total of 24 annotated significant metabolites identified in different bee bread samples, as well as their capacity to differentiate between seasons and bee farms. Notably, these results suggest a wide variety of potential plant families as a source of bee bread. These findings shed light on the impact of seasons and diverse plant families contributing to bee bread composition, which may impact the growing meliponiculture industry greatly.

Characterization of dairy goat production systems in coastal valleys of the Lima region

Goat farming in Peru is a husbandry activity that, although it is considered secondary in the country, has a great economic and social impact on the rural population, that is why government efforts to develop is so important. The objective of this study was to characterize dairy goat rearing systems in the coastal valleys of the Lima region to identify gaps and opportunities for improvement. This cross-sectional research was conducted in four provinces located in the Lima region, Peru. A total of 62 goat farmers participated in the trial. For data collection, a standard survey was prepared with open and closed questions distributed across two components (socioeconomic and productive). The surveys were processed for qualitative variables using a multiple correspondence analysis (MCA) followed by a hierarchical cluster analysis (HCA) to differentiate the types of farming systems prevalent based on the survey population. The hierarchical cluster analysis resulted in the formation of three separate groups of goat farmers, which can be classified as extensive systems differentiated by management practices and their production and marketing objectives. The test showed a significant difference; therefore, it can be affirmed that they are associated with the groups or clusters formed. These results will allow actors related to goat farming, such as state and regional entities, to focus efforts on addressing specific demands of the different types of goat farmers found in this study.

The dynamics of organic farming conversion in groundwater management

Abstract This article analyses the endogenous choice of farmers to be organic or conventional in a groundwater evolutionary model when a tax on fertiliser on conventional farmers is implemented by a regulatory agency. The analysis of the model shows that the coexistence of both type of farmers only occurs when the decrease in productivity due to organic production is relatively low and the price premium for organic products is relatively high. However, even if conversion is welfare improving, our results show that this conversion may be done at the expense of the water resource with a lower water table. An application to the Western la Mancha aquifer (Spain) illustrates the main results.

The Extent and Patterns of Digitalization in Proactive Land Acquisition Strategy (PLAS) Farms in South Africa

This study sought to develop an index for agricultural digitalization by applying composite confirmatory analysis (CCA). Another aim was to determine the factors that affect the development of digitalization in PLAS farms. Data on the indicators of the three dimensions of digitalization were collected from 300 Proactive Land Acquisition Strategy (PLAS) farms in South Africa using semi-structured questionnaires. Confirmatory composite analysis (CCA) was employed to reduce the items into three digitalization dimensions and ultimately to a digitalization index. Standardized digitalization index scores were extracted and fitted to a linear regression model to determine the factors affecting digitalization. The results revealed that the model shows practical validity and can be used to measure digitalization as measures of fit (geodesic distance, standardized root mean square residual, and squared Euclidean distance) were all below their respective 95%quantiles of bootstrap discrepancies (HI95 values). Therefore, digitalization is an emergent variable that can be measured using CCA. The average level of digitalization in PLAS farms was 0.02 and varied significantly across provinces. Although farmers have attempted to digitalise their farms, there are still minimal levels of digitalization in PLAS farms. The results further reveal different digitalization patterns. As judged by the estimated weights of various dimensions of digitalization, the use of digital technologies to collect, store, analyse, and disseminate (CSAD) farm-related data contributed more towards the digitalization index. The second most important component of digitalization was automation digitalization. In contrast, value chain digitalization was the least significant contributor. The factors that significantly influence digitalization were age, gender, farm type, network type, and cellular data type. Since PLAS farmers have not embraced much digitalization, it is important to focus on awareness and capacity building. A balanced approach to digitalization would benefit PLAS farms by ensuring that strategies to integrate digital solutions within the value chain are developed. To foster and support the digitalization in PLAS farms, policymakers and stakeholders should tailor their strategies to fit specific socioeconomic factors.

The Role of Agricultural Technology in Attaining Food Security among Small Farmers in Char Area in Mymensingh District

Farmers in the char areas of Bangladesh are frequently affected by food insecurity due to their low engagement in modern agriculture such as less use of modern agricultural technology. This study evaluates the socio-demographic characteristics of the sample farmers to assess their nutritional status and the factors influencing char dwellers' dietary diversity. Survey data were collected from 70 households, and focus group discussions were conducted using a semi-structured questionnaire from Nilokhiya char under the Mymensingh District of Bangladesh. An OLS regression model was used to estimate the influence of socioeconomic characteristics of sample households on the decision on factors influencing dietary diversity. The farming type of the farmers is another concern of this study where results show that 90% of farmers in the char areas rely on rice and vegetable farming, whereas more than 60% of the farmers are also involved in livestock and poultry farming at the same time. The nutritional status of char farmers shows that their diet includes a variety of foods but is deficient insufficient protein and healthy fats, which could have an impact on their overall nutrition. Cereals are a staple in the diet, as indicated by the high consumption rate (97.1%) and the substantial average intake (2.30 kg/day). Every household consumes fruits, though in smaller quantities (0.28 kg/day). Eggs are less frequently consumed (57.1%) despite a higher intake (2.64 kg/day). Dietary diversity has a strong positive correlation with supply (.913) at a 1 % significant level which means that efficient supply chains minimize delays, reduce spoilage, and ensure a continuous flow of food to markets to ensure food security. A positive correlation with total income (.373) leads to a higher total income also supports greater dietary diversity. Credit was significant at a 5% level (.267) indicating that a 1 % increase in credit leads to an increase in dietary diversity by 267%. On the contrary, Experience has a negative relationship with dietary diversity which means that experience does not influence food security. Lack of transport and communication, environmental hazards, and natural disasters are the most significant problems faced by the farmers in the char area.

Exploring Diversification Strategies among Italian Farms

The multifunctionality model is receiving more and more attention from policymakers as a result of recent initiatives to build more resilient and sustainable food systems as well as the potential for increased farm revenue. This paper explores the role of multifunctional farming in the Italian agriculture viewed through the lens of an entrepreneurial strategy grounded on-farm diversification. Farm diversification strategies, which broaden the farm’s traditional boundaries to include additional activities at the farm level, help the evolution towards multifunctionality. A policy-driven transition towards multifunctional farming has been noticed in Italy during the past few decades, which has prompted a strategic reconfiguration of the farm’s business models. Drawing on the identified activity of portfolio diversification, this study provides an overview of the analyzed 49,429 Italian farms, by articulating diversification strategies into four entrepreneurial activities, which are related to on/off-farm/farm-related or farm-diverse diversification strategies. This article has attempted to verify the presence of farm types that responded to portfolio diversification management strategies through the use of a cluster analysis on data from the general census of Italian agriculture. Supporting new patterns in the adoption of business models focused on multifunctionality should be considered in European rural development policies.

Strategic Categorization of Dairy Cow Farms in Croatia using Cluster Analysis

Abstract Background The milk processing sector in the Republic of Croatia faces numerous challenges. It is a distinctly bipolar structure, with some entities resembling the largest milk producers in the EU, while many small and medium-sized dairy farms struggle to remain competitive and achieve further progress. To formulate effective policy, it is important to differentiate between these types and address their key challenges. Objectives The aim is to find the most representative solution that will help us define typical dairy farms and upgrade a SiTFarm tool (Slovenian Typical Farm Model), enabling us to assess the situation in Croatia comprehensively. Methods/Approach Cluster analysis was conducted using empirical data obtained from the Croatian Agency for Agriculture and Food. The analysis involved applying both hierarchical and non-hierarchical clustering techniques. Results Two cluster analysis scenarios are presented, differing in the variables used. In each scenario, 16 relatively homogeneous clusters of farms were obtained. Diversity was minimized within these clusters, and they effectively explain the dairy business in Croatia. Conclusions The results of this analysis thus represent an important starting point for further analysis of the dairy sector in Croatia. These findings could help policymakers identify the types of farms that would benefit most from targeted investments to enhance efficiency, economic viability, and environmental sustainability.

Influence of an innovative IMTA system (Mediterranean Sea, Italy) on environmental and biological parameters: Seasonal analysis

The influence of benthic suspension feeders as bioremediating organisms on water column seston and their ability to mitigate fish farm waste was assessed by monthly analyses for one year. A monthly monitoring from July 2020 to October 2021 of physico-chemical and biochemical variables of the water column and the sediment was performed in an in-shore mariculture plant located in the Mar Grande of Taranto (Italy), comparing two adjacent areas that differ in type of farming. The first (reference site) is a fish monoculture, while the second consists of an innovative Integrated Multi-Trophic Aquaculture system (IMTA site). The annual cycle of chlorophyll-a concentration showed values corresponding to mesotrophic/eutrophic conditions, with peak production in early fall (4.64 μg L−1). During the spring and summer sampling times, when the amount of aquaculture waste is greater than during the rest of the year, the reference site showed the highest lipid (151.73 μg L−1) and organic matter (189.00 mg g−1) values with respect to those at the IMTA site. The IMTA bioremediating organisms possibly acted as underwater gardens changing the seston quality and availability and providing protection and food for the zooplankton community, which showed higher abundance of individuals for most sampling times at the IMTA site, peaking during September and October in both 2020 and 2021 (max 232,985.20 ind m−3). Our results demonstrate the effectiveness of the considered IMTA system in mitigating the negative impact of organic matter release into the environment due to fish farming activities. The influence of bioremediating organisms on seston composition and concentration opened up mitigation as well as restoration scenarios.

Switching costs in transient technology use: Panel evidence from Kenyan maize production

AbstractThe idea of switching costs and how they affect agricultural technology adoption has received little attention in the literature. We employ a dynamic switching model to show that switching costs generally discourage the adoption of new technologies by farmers, but the extent of the effect depends on the level of switching costs, as well as farmer perceptions and foresight. We provide an empirical strategy to identify switching costs and estimate their effects on adoption under different farmers’ perceptions about adoption uncertainty. An application to hybrid seed adoption in Kenya confirms the existence of switching costs. The correlated‐random‐effects probit results suggest there is heterogeneity in dominant farmer types across agro‐ecological zones in Kenya. Area‐specific policies are suggested to promote technology adoption in different environments.

Operational and production determinants contributing towards commercialization among female Agripreneurs in Vhembe district

This study investigates operational and production determinants that significantly influence small-scale transitioning to commercial farming among female agripreneurs, the implications for food security and gender equality with various elements impacting the commercialization of agricultural production in emerging economies. A quantitative research design was used in this research. This study was conducted in the emerging economic zone, the Vhembe district of Limpopo province where agricultural activities dominate. A purposive sampling was used to select 149 female agripreneurs. Structured questionnaires were handed to the participants during the in-person interview sessions. The study results reveal that the sample was dominated by elderly agripreneurs who primarily relied on permission to occupy arrangements for land security. The study findings exhibit that operation determinants such as type of farming and record keeping were positive contributors towards commercialization among female agripreneurs. Meanwhile, production elements such as commodity types regressed the commercialization effort among female agripreneurs. The study findings imply that policy tools should advocate for land security among female agripreneurs as they enhance the implementation of their long-term agricultural plans. The study findings suggest that emerging female agripreneurs should be made aware of various farming types that propel commercialization within a shorter period due to their lifecycle.

Different habitat condition proportions on farms affect the structure and diversity of dung beetle (Coleoptera, Scarabaeidae, Scarabaeinae) communities

The continuous changes and increase of land use into ranching and agriculture have caused shifts in the composition and structure of dung beetle communities due to the modification of vegetation structure. The impact of these changes can be approached using dung beetles as ecological indicators. Agricultural, ranching, and forestry are often integrated into the same farm in different proportions (landscape level), and their degree of integration with habitats changes over time and space. We assessed if different habitat proportions of crop, pasture, and forest land on three farms affect the structure and diversity of dung beetle (Coleoptera: Scarabaeinae) communities. Farms included from three to four habitat conditions each (plantations of timber species, banana-coffee plantation, living fences, pastures, secondary and riparian forest). Pitfall traps with dung and carrion as bait were placed across each habitat condition of each farm during three different sampling periods. Across all samplings, 1,198 dung beetle individuals belonging to 21 species were captured. Species diversity and composition vary according to the type of farm and the main factor that modifies this tendency is the proportion of pasture land composing the farm. Farms with a lower proportion of grazing land (11.96% for forestry farms and 32.19% for agricultural farms) and denser vegetation canopy, which cast more shadows, had greater beetle diversity. Conversely, farms having a greater proportion of grazing land had low diversity and a dominant tendency in the species abundance curve. Umbraphile species dominated the forest farm, indicating a strong affinity for shaded environments such as the one provided there, while species displaying no habitat preference exhibited higher abundance in the ranching farm. Additionally, a notable prevalence of small-sized species was observed in the ranching farm, contrasting with a relatively even distribution of sizes in the remaining landscapes. These tendencies suggest that shade positively influences biodiversity conservation. Riparian vegetation, living fences, and banana-coffee plantations are important connectivity elements in agricultural landscapes for shade-adapted dung beetle species.

One-size measures do not fit all areas: Evaluation of area-specific control of foot and mouth disease in Thailand using bioeconomic modelling

Information on the epidemiological and economic consequences of control measures is fundamental to design effective foot and mouth disease (FMD) control measures. One approach to obtaining this information is through bioeconomic modelling. In this study, a bioeconomic model was used to evaluate FMD control in two different study areas in Thailand: a high farm density area predominantly consisting of dairy farms and a low farm density area with mixed farm types. The bioeconomic model consists of an epidemiological part and an economic part. For the epidemiological part, a stochastic between-farm transmission model was constructed with transmission parameters estimated from FMD outbreaks in Thailand. The outputs from the epidemiological model, i.e. the number of infected farms, the number of affected farms and the outbreak duration, are used as inputs for economic model to calculate the economic consequences. We applied the simulation model with four FMD control measures: culling the animals of infected farms, ring vaccination, animal movement restrictions and isolation of infected farms. Furthermore, we included effect of farmers' compliance to asses its effect on control measures. The simulated FMD outbreaks in the low farm density area were small, thus control measures did not greatly affect the size of outbreaks and, therefore, did not have a positive economic return. In contrast, in the high farm density area, FMD outbreaks were large without control measures. All measures reduced the size of the outbreaks but resulted in different total costs. In terms of outbreak control, culling infectious farms was the best option, but its total cost was higher than ring vaccination or isolation of infected farms. In terms of cost-effectiveness, ring vaccination was the best measure. If farmers' compliance were low, all control measures would be ineffective, resulting in high total cost of the outbreak. The cost distribution between compliant and non-compliant farms showed that non-compliant farms paid more than compliant farms, except for the ring vaccination scenario. The results emphasize the economic significance to customize control measures specific to the area's conditions and highlight the importance of farmers' compliance when designing control measures.

Novel characterisation of sheep flocks in Wales: A description of principal flock typologies and antimicrobial use patterns

There is increasing pressure to reduce and refine antimicrobial use (AMU) in farmed livestock, to slow the development of antimicrobial resistance (AMR) and preserve the efficacy of antimicrobials (AMs) in both humans and animals. Developing strategies to help drive the prudent use of AMs requires an understanding of the direct and indirect factors influencing the between-farm variation in AMU typically observed. Given limited evidence of risk factors in sheep, this exploratory study aimed to investigate whether sheep flocks could be classified into farm types based on farm characteristics, health parameters and management practices, and whether important differences existed in AMU between these flock types. This study was conducted on 22 sheep flocks in Wales, United Kingdom as part of a wider longitudinal study on AMU and AMR. Comprehensive surveys were administered to flocks where 147 variables regarding farm characteristics, flock health parameters and management practices were captured. AMU data for each flock were also collated. A Multiple Correspondence Analysis (MCA), followed by a Hierarchical Clustering on Principal Components (HCPC) analysis, were used to classify the flocks. The top 10 dimensions yielded by MCA explained 67.4 % of the total variance. Nine partitions of relatively homogeneous flocks, derived from three typologies produced from the first three cut-points of the HCPC dendrogram, were visualised and described. These nine partitions were characterised by 70 variable categories, principally the implementation or neglect of best-practice lameness management practices. Partitions of flocks that neglected best-practice lameness managements – characterised by delayed treatments of lame sheep, footbathing and bleeding when foot trimming – reported higher lameness prevalence and fewer lame ewes recovering within five days of treatment. These flocks had higher total AMU (mg/PCU) and used a higher mass of injectable AMs than other partitions of flocks. Flock traits, lambing practices, disease challenges and other management factors also described partitions derived in later dendrogram cuts. Findings from this study confirm good AM stewardship in sheep flocks to be a complex picture, given the typologies of flocks described and the range of factors likely to influence AMU. Opportunities for targeted strategies for sustainable reductions in AMU can be directed towards specific flock types identified, specifically within the context of lameness treatment and control. We highlight the importance of understanding flock heterogeneity, through the construction of typologies, as a means to fine-tune appropriate interventions to specific flock types in order to help drive more prudent use of AMs.

Nitrogen use efficiencies, flows, and losses of typical dairy farming systems in Inner Mongolia

Dairy farming is a notable source of nitrogen (N) emissions, impacting both atmospheric and aquatic ecosystems, thus necessitating a detailed analysis of nutrient dynamics to curtail nutrient wastage. However, N flow variability and its environmental ramifications differ markedly among dairy farms, and a holistic understanding of these differences is lacking in Inner Mongolia, the biggest dairy production province in China. Utilizing data from 187 dairy farms and employing the NUFER-farm model, this study assessed N flows, N use efficiency (NUE), and N losses across four predominant dairy farming systems in Inner Mongolia. These systems include traditional pastoral dairy farms (PF), smallholder dairy farms with croplands (SF), industrial landless farms (IDF), and coupled dairy cattle and cropland-intensive farms (CDF). Our findings indicate considerable differences in N flows, NUE, and losses among the systems. On average, N deposition and N fertilizer were the primary N sources for PF and SF, respectively, whereas IDF and CDF derived over 90% of their N inputs from purchased feeds. PF and SF recycled all available manure N on-farm, whereas IDF and CDF recycled only approximately 36% of the total available manure N. N losses constituted 39–72% of total N outputs, with ammonia emissions accounting for 68–73% of total N losses across all farm types. In particular, PF had a higher N loss per kilogram of dairy product than other systems. Farm-level NUE ranged from 17 to 35%, with manure management practices showing significant variability, underscoring the potential for enhanced strategies to reduce N losses through improved manure treatment.

Gut Microbiota Diversity of Local Egyptian Cattle Managed in Different Ecosystems.

The animal gastrointestinal tract contains a complex microbiome whose composition ultimately reflects the co-evolution of microorganisms with their animal host and their host's environment. This study aimed to gain insights into the adaptation of the microbiota of local Egyptian cattle to three different ecosystems (Upper Egypt, Middle Egypt, and Lower Egypt) distributed across 11 governorates (with an average of 12 animals per governorate) using amplicon sequencing. We analyzed the microbiota from 136 fecal samples of local Egyptian cattle through a 16S rRNA gene sequencing approach to better understand the fecal microbial diversity of this breed which developed under different ecosystems. An alpha diversity analysis showed that the fecal microbiota of the Egyptian cattle was not significantly diverse across areas, seasons, sexes, or farm types. Meanwhile, microbiota data revealed significant differences in richness among age groups (p = 0.0018). The microbial community differed significantly in the distribution of its relative abundance rather than in richness across different ecosystems. The taxonomic analysis of the reads identified Firmicutes and Actinobacteriota as the dominant phyla, accounting for over 93% of the total bacterial community in Egyptian cattle. Middle Egypt exhibited a different microbial community composition compared to Upper and Lower Egypt, with a significantly higher abundance of Firmicutes and Euryarchaeota and a lower abundance of Actinobacteriota in this region than the other two ecosystems. Additionally, Middle Egypt had a significantly higher relative abundance of the Methanobacteriaceae family and the Methanobrevibacter genera than Lower and Upper Egypt. These results suggest a difference in the adaptation of the fecal microbial communities of Egyptian cattle raised in Middle Egypt. At the genus level, eleven genera were significantly different among the three ecosystems including Bacillus, DNF00809, Kandleria, Lachnospiraceae_NK3A20_group, Methanobrevibacter, Mogibacterium, Olsenella, Paeniclostridium, Romboutsia, Turicibacter, and UCG-005. These significant differences in microbiota composition may impact the animal's adaptation to varied environments.

Performance evaluation of Uruguayan dairy farming systems

In the last 20 years, the Uruguayan dairy sector has intensified and concentrated on higher cow productivity, maintaining the herd, smaller land, and fewer farms. The research aims are to identify, describe, and evaluate the economic performance of different types of dairy farms. A sample of 284 farms from the National Dairy Farm Survey 2019 was used (representing 2,021 dairies); using k-means Cluster analysis with the variables: cow productivity, stocking rate, land productivity, concentrate, roughage, and grass intake (per hectare). We identified six farm types, three with high participation of grass in the cows’ diets (HG, 60% or more of dry matter intake), and the other three focused on supplementation (HS); with three intensification levels (1-low, 2-intermediate and 3-high productivity per ha). For the 2018/19 season three types of farms presented the best economic performance (HS-3, HG-3, and HG-2), including those with the highest stocking rate and grass intake per hectare, and more than USD 225 Economic Farm Surplus (EFS) per hectare with the lower unitary cost. Other two types exhibited intermediate economic performance (HS-2 and HG-1) with EFS close to zero and unitary cost similar to price. And one type (HS-1) displayed the worst economic performance, with negative indicators and the largest number of farms with very low productivity.

Farmers’ Willingness and Adoption of Water-Saving Agriculture in Arid Areas: Evidence from China

Enhancing water resource utilization efficiency is crucial for achieving sustainable development in arid and semi-arid regions. In promoting water-saving agriculture technologies, there is often a phenomenon of “willingness without behavior”. Therefore, investigating how willingness translates into behavior is of significant importance for improving water resource utilization. This study utilized data from a survey of 494 households in Ulanqab City, Inner Mongolia Autonomous Region, China, and employed Probit models to analyze the factors influencing farmers’ willingness towards water-saving technologies and their adoption. Prospect theory and mental accounting theory were introduced to understand the mechanism of transformation from farmers’ willingness to adoption. The study found that farmers’ willingness is a crucial prerequisite for their adoption. Farmers’ income perception towards adopting water-saving technologies can facilitate the transformation from willingness to adoption, while cost perception can inhibit this transformation. Both small and large-scale farmers’ perception of the benefits of water-saving technologies significantly increased their likelihood of translating their willingness to adopt into actual action. Compared with large-scale farmers, small-scale farmers are more sensitive to the perception of economic costs in the decision-making process. For both types of farmers, the perception of learning cost inhibits their willingness to adopt water-saving technologies to a certain extent. Farmers’ perception of the prospects of adopting water-saving technologies leads to a psychological segmentation effect, and the ultimate adoption depends on the psychological game between farmers’ income and cost perception.

The Polish milky ways A socio-historical case of the human-nonhuman relationship

This article discusses the socio-historical case of the human – non-human networks of Polish farmers engaged in milk production and cow herding. “Milky ways” is a term referring to var­ious ways, networks and social constellations which determine the socio-political landscape of Polish milk and dairy production and cow herding. The analysis includes ways in which, in various timeframes (before the Second World War, during Socialism, in the present time), milk is remembered to have linked a farming community and served as ways of sustenance for various types of farmers and local inhabitants (e.g. Jews, townspeople). The article explores what actors (people, products, spaces, and politics) formed the milky-way network, bringing into question the well-being and coping strategies of present-day farmers. Data for this study was collected during ethnographic fieldwork in Eastern Poland in the summer of 2019, as well as between 2010 and 2014 in villages around a small Podlachian town.