Farm Types Research Articles

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.

Growth indices and drymatter production of groundnut as influenced by various farming types and cropping system under Southern transition Zone of Karnataka

Growth indices and drymatter production of groundnut as influenced by various farming types and cropping system under Southern transition Zone of Karnataka

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.

Trade‐offs and synergies between dimensions of well‐being among smallholder farmers in Savannakhet province, Lao PDR

AbstractAgrarian transition is often seen as a pathway towards sustainable development and increasing well‐being for rural households. However, empirical evidence on trade‐offs and synergies between different dimensions of well‐being as a result of agrarian transitions is lacking. We conducted a cross‐sectional survey of 360 households across 12 villages in Savannakhet province, Lao PDR. We find evidence of synergies across different farmer types and between all included well‐being dimensions; economic, food security, health, and gender equality. However, for intensive paddy rice farmers, synergies are predominantly positive, while for non‐intensive cash crop farmers synergies are mostly negative. These findings indicate that development in one well‐being dimension may provide improvements in other dimensions, but that benefits can be difficult to achieve for some types of farmers. Our results further suggest that rural development policies focussing on a single well‐being aspect, for example supporting non‐farm incomes, may have co‐benefits beyond the immediate development targets.

Current Framework of Italian Agriculture and Changes between the 2010 and 2020 Censuses

This study aims to describe the current framework of the Italian agricultural sector and the changes that occurred in the decade between the two general censuses of agriculture of 2010 and 2020, and the EU Common Agricultural Policy (CAP) programming period 2014–2020. The General Census of Agriculture is an economic census carried out to fulfill international and EU legislation requirements, but also to meet national information needs. It consists in counting farms and identifying their characteristics. For this study, the official data of the 7th Italian General Census of Agriculture (GCA) of 2020 were collected, analyzed, and compared to those of the previous 6th GCA of 2010. Farms’ type of activities, structure, digitalization/computerization, innovation, and workforces’ characteristics were analyzed. Correlations between farms with investments in innovation and other variables like the age and the educational qualification of entrepreneurs and the farm’s size (agricultural used area) were calculated. Groups of similar Italian regions for types of farm and types of farming (segmenting the sector into subsets of regions that share common characteristics), and groups of similar farming characteristics in the entire agricultural sector, were highlighted. The results showed a notable positive correlation between farms’ investment in innovation and farms’ size, and a medium but positive correlation also with other two variables, the entrepreneur’s range of age and educational qualification. Results found groups of regions that are similar in terms of types of farm and farming types, highlighting that the agricultural sector in Italy is not homogeneous among all the regions of north, center, and south. Moreover, the discovered different groups of farming characteristics highlighted the Italian “farm profiles”, i.e., descriptions of key information about different specific types of farm. The overall analysis of all the results of this study provided the current situation of the Italian agricultural sector and discussion about its characteristics and changes during the last ten years. Based on our knowledge, this study is the first one with such a level of comprehensiveness. Findings are of high interest to academics in agriculture economics and policy maker, because they contribute to identifying the farms’ and territories’ strategic elements that require strengthening to foster economic and social development. Moreover these findings may provide food for thought on the effectiveness of the development strategy of the EU CAP 2023–2027 (through greening and digitization) at the regional and European levels, starting from the baseline situation of this country, which is certainly one, but which is among the most relevant ones in the European agri-food system and also globally.

Applying equineRSU and seasonal livestock correction to wider equine stud farm types

ABSTRACT To adjust for potential overestimations in the nitrogen excretion by horses within Overseer®, a revised stock unit system has been proposed (equineRSU). These equineRSU were generated and validated using a medium-sized equine farm as a model farm. The aim of this study was to test the application of the equineRSU and seasonal stock number adjustment on a more complex farming model. Livestock numbers and management data were captured prospectively for the base property (128.8 ha) of a large multi-property commercial breeding stud (3 support properties, 556 ha total area) between June 2022 and May 2023. The monthly on-farm metabolisable energy (ME) requirement and pasture demand were deterministically modelled with both a customised feed budget using livestock class and weight or using the equineRSU and monthly adjusted stock numbers. There were multiple complex movements of horses on and off the property in the different stock classes across the year, with stock management reflecting seasonal periods of high stocking density. There was good agreement (6% variance) between actual ME demand (complex feed budget) and estimated feed demand (simplistic equineRSU model) of 4,387,187 MJ vs 4,102,770 MJ. This suggests that the equineRSU could be used on complex equine farm systems within Overseer®.

Selected farm-level crop protection practices in Europe and Argentina: Opportunities for moving toward sustainable use of pesticides

Extensive use of plant protection products (PPP) in the last decades contributes to negative impacts on ecosystems, animals and humans. For the strategies of PPP reduction and replacement of hazardous pesticides, farm-level data on agronomic management practices and crop protection applications are crucial. In this study, we strategically collected data for the 2021 season at the SPRINT project case study sites (CSS) in 10 European countries and Argentina, on perennial, arable and vegetable crops. Data collection included strategically selected farm and field data, pesticide records and farming practices. Results involved more than 1700 recorded PPP applications across various crops with more than 170 different active substances from PPP in organic, integrated pest management and conventional farming practices. We explored differences in application patterns (fungicides, insecticides, herbicides and non-PPP, e.g. adjuvants, growth regulators, and fertilizers) between and within crops, countries and farming systems and calculated the costs of PPP use. The pesticide dosages applied during the crop season varied up to a factor of 20 around recommended doses. Regarding the costs of PPPs use perennial crops had the highest costs per ha crop production area. Finally, we analysed the active substances applied in different farming systems in terms of their hazard statements. Our results shed light on how PPPs are used across different crop and farming types and will help elucidate how pesticide application patterns can be changed in the future. Finally, we highlighted non-PPP use practices which help to reduce dependency on PPP use. This might be used to support decision-making and policies within agricultural advisory/support systems.

AD|ARC (Administrative Data | Agricultural Research Collection): Characteristics of farm households participating in agri-environment schemes in Wales, UK.

Objectives Describe the sociodemographic and farm business characteristics of farming households in Wales that have agri-environment contracts (voluntarily opting-in) without primary farm subsidies (voluntarily opting-out). Investigate the sociodemographic and farm business characteristics of farming households in Wales by the number and type of farming subsidies received. ApproachWe utilised the AD|ARC dataset comprising of Census 2011 variables, linked to agricultural and business variables for all farming households in Wales. We analysed variables relating to the individual (e.g. age, gender), household (e.g. household size, structure), farm business (e.g. farm type, diversification activities) and rural payments data (subsidy type, amount paid). We conducted comparative analyses between three groups of farming households: households engaged in agri-environmental schemes but not primary subsidies, households engaged with both subsidy types, and households claiming primary subsidies only. ResultsWe will present a detailed description of the sociodemographic and business characteristics of farming households by the number and type of subsidies claimed and engagement with agri-environmental schemes. Using business, personal, and household characteristics, we will discuss different farming household typologies in relation to participation in agri-environmental schemes, and outline the relationship between farming households and positive environmental action. Full findings will be presented at the conference but are currently subject to information governance restrictions. With an increasing interest in climate change and supporting the natural environment, our findings provide insight into the characteristics of farming households and their relationship to engagement with agri-environmental schemes. Our results will inform policy-makers seeking to support farming and the rural environment.

Investigation of the differences in characteristics of Welsh farming households with and without off-farm income

ObjectiveTo examine the characteristics of farming households that have no off-farm income, and how they compare to farming households containing at least one person employed in a non-farming occupation. ApproachThis research uses the AD|ARC dataset for Wales held in the SAIL databank at Swansea University. This Research Ready Dataset, created by the research team, is comprised of population census data and existing agricultural datasets. Individuals were split into two groups, those in households where all individuals were primarily employed in farming or unemployed, and those in households where at least one individual was in a non-farming occupation. ResultsComparing these groups, our findings show: There are 8135 farming households with at least one person in a non-farming occupation, and 5415 households with no off-farm income. Households with off-farm income are on average 65% larger than households with no off-farm income. 33% of farming only households consist of a single person; 73% of these farmers are male, and the average age is 62. The average age for farming-only households is 45, and the average age of households with non-farming occupations is 36. We will present detailed findings on the socio-economic and farm business characteristics of these groups. ConclusionUnderstanding differences between households with and without off-farm income provides insights on farm types and households most impacted by changes in agricultural policies and subsidies. This can inform policy design and help authorities deliver commitments on just transitions in a targeted and efficient manner.

Sustainability of the Different Rice Cultivation Practices in Yogyakarta, Indonesia

The current food crisis has become a serious threat to humanity. Other issues such as climate change, farmer regeneration, and excessive use of chemical inputs at the producer level threaten sustainability in agriculture. The sustainability of agricultural practices among farmers remains questionable due to the small number of organic farmers in Indonesia. The purpose of this study was to determine the level of sustainability of rice cultivation and the factors that influence the sustainability of rice cultivation in various types of cultivation in Yogyakarta. Research on farm sustainability that is analyzed in a multidimensional (5 dimensions) and compares 3 types of cultivation has not been widely carried out in Indonesia. This research was conducted in Bantul and Sleman with 90 respondents. The analysis method used Multidimensional Scaling-RAPFISH and Tobit regression. The results showed interesting findings where the 3 types of rice cultivation are in the sufficient (moderately sustainable) category even though the 3 have differences in the use of inputs, especially in the ecological dimension. The factors of education, frequency of attending extension and activity in farmer groups, the use of good agricultural practices, land ownership, and type of cultivation had a positive effect on increasing the sustainability of rice cultivation in various types of cultivation in Yogyakarta. The results of this research have an impact on agricultural extension field education provided by the government to increase the sustainability of rice cultivation in Yogyakarta. It is recommended that the 3 types of rice farmers to pay more attention to the use of Good Agricultural Practices (GAP) to increase sustainability.

Typologies of South African small-scale farmers and their risk perceptions: an unsupervised machine learning approach

PurposeSmall-scale farmers are highly heterogeneous with regard to their types of farming, levels of technology adoption, degree of commercialization and many other factors. Such heterogeneous types, respectively groups of small-scale farming systems require different forms of government interventions. This paper applies a machine learning approach to analyze the typologies of small-scale farmers in South Africa based on a wide range of objective variables regarding their personal, farm and context characteristics, which support an effective, target-group-specific design and communication of policies.Design/methodology/approachA cluster analysis is performed based on a comprehensive quantitative and qualitative survey among 212 small-scale farmers, which was conducted in 2019 in the Limpopo Province of South Africa. An unsupervised machine learning approach, namely Partitioning Around Medoids (PAM), is applied to the survey data. Subsequently, the farmers' risk perceptions between the different clusters are analyzed and compared.FindingsAccording to the results of the cluster analysis, the small-scale farmers of the investigated sample can be grouped into four types: subsistence-oriented farmers, semi-subsistence livestock-oriented farmers, semi-subsistence crop-oriented farmers and market-oriented farmers. The subsequently analyzed risk perceptions and attitudes differ considerably between these types.Originality/valueThis is the first typologisation of small-scale farmers based on a comprehensive collection of quantitative and qualitative variables, which can all be considered in the analysis through the application of an unsupervised machine learning approach, namely PAM. Such typologisation is a pre-requisite for the design of more target-group-specific and suitable policy interventions.

Seroprevalence of infectious bursal disease and its associated risk factors in Ethiopia: a systematic review and meta-analysis

ABSTRACT The poultry population is an integral part of Ethiopia’s Gross Domestic Product (GDP) but, due to various infectious diseases such as infectious bursal disease (IBD), the expected economic impact in the country remains limited. The status of the disease in Ethiopia is obscured; thus, a systematic review and meta-analysis were employed to estimate the overall pooled prevalence of IBD in Ethiopia. Meta-analysis was conducted to determine the effects of each identified risk factor, while meta-regression and sub-group analysis were employed to assess the relationship between study-level covariates and effect size. The pooled prevalence of IBD in Ethiopia was 69.4% (95% CI 30.7–96.2), while the pooled logit prevalence was 0.94 (95% CI: 0.68–1.20) with significant inter-study variance (Q test = 948.28, df = 43, P < 0.001; τ 2 = 0.71, I 2 = 95.47%). A small-study effect was detected in the regression-based Egger test (Prob > |z| < 0.0001). Significant variation was observed among different groups such as sex, age, breed, and type of farm of the chickens. The effect size for the study period from 2018 to 2021 was significantly lower by −0.204 compared to the study period from 2009 to 2015 (P < 0.0001. In conclusion, the IBD pooled prevalence estimate is high, even though the number of studies in the country is insufficient. The high prevalence of the disease requires prompt attention from all stakeholders in the sector to bring it under control through comprehensive disease prevention and control intervention strategies.