Search

Digitalization appears as a lever to enhance agriculture sustainability. However, existing works on digital agriculture's own sustainability remain scarce, disregarding the environmental effects of deploying digital devices on a large scale. We propose a bottom‐up method to estimate the carbon footprint of digital agriculture scenarios considering deployment of devices over a diversity of farm sizes. It is applied to two use‐cases and demonstrates that digital agriculture encompasses a diversity of devices with heterogeneous carbon footprints and that more complex devices yield higher footprints not always compensated by better performances or scaling gains. By emphasizing the necessity of considering the multiplicity of devices, and the territorial distribution of farm sizes when modeling digital agriculture deployments, this study highlights the need for further exploration of the first‐order effects of digital technologies in agriculture. [ABSTRACT FROM AUTHOR]

Soil quality is pivotal for crop productivity and the environmental quality of agricultural ecosystems. Achieving sufficient yearly income and long-term farm continuity are key goals for farmers, making sustainable soil management an economic challenge. Existing bio-economic models often inadequately address soil quality. In this study, we apply the novel FARManalytics model, which integrates chemical, physical, and biological indicators of soil quality indicator, quantitative rules on how these indicators respond to farmers' production management over time, and an economic calculation framework that accurately calculates the contribution of production management decisions towards farm income. This is the first study applying this model on existing arable farms. FARManalytics optimizes crop rotation design, cover crops, manure and fertilizer application and crop residue management. Nine Dutch arable farms were analyzed with a high variation in farm size, soil type, and cultivated crops. First, we assessed farm differences in soil quality and farm economics. Second, we optimized production management to maximize farm income while meeting soil quality targets using farm-specific scenarios. Third, we explored the impact of recent policy measures to preserve water quality and to increase the contribution of local protein production. The results show that the case farms already perform well regarding soil quality, with 75% of the soil quality indicators above critical levels. The main soil quality bottlenecks are subsoil compaction and soil organic matter input. We show that even in front-runner farms, bio-economic modeling with FARManalytics substantially improves economic performance while increasing soil quality. We found that farm income could be increased by up to €704 ha−1 year−1 while meeting soil quality targets. Additionally, we show that to anticipate on stricter water quality regulation and market shift for protein crops, FARManalytics is able to provide alternative production management strategies that ensure the highest farm income while preserving soil quality for a set of heterogenous farms. [ABSTRACT FROM AUTHOR]

The distribution of farm locations and sizes is paramount to characterize patterns of disease spread. With some regions undergoing rapid intensification of livestock production, resulting in increased clustering of farms in peri-urban areas, measuring changes in the spatial distribution of farms is crucial to design effective interventions. However, those data are not available in many countries, their generation being resource-intensive. Here, we develop a farm distribution model (FDM), which allows the prediction of locations and sizes of poultry farms in countries with scarce data. The model combines (i) a Log-Gaussian Cox process model to simulate the farm distribution as a spatial Poisson point process, and (ii) a random forest model to simulate farm sizes (i.e. the number of animals per farm). Spatial predictors were used to calibrate the FDM on intensive broiler and layer farm distributions in Bangladesh, Gujarat (Indian state) and Thailand. The FDM yielded realistic farm distributions in terms of spatial clustering, farm locations and sizes, while providing insights on the factors influencing these distributions. Finally, we illustrate the relevance of modelling realistic farm distributions in the context of epidemic spread by simulating pathogen transmission on an array of spatial distributions of farms. We found that farm distributions generated from the FDM yielded spreading patterns consistent with simulations using observed data, while random point patterns underestimated the probability of large outbreaks. Indeed, spatial clustering increases vulnerability to epidemics, highlighting the need to account for it in epidemiological modelling studies. As the FDM maintains a realistic distribution of farm location and sizes, its use to inform mathematical models of disease transmission is particularly relevant for regions where these data are not available. Author summary: We have developed a model to predict the location and size of poultry farms in countries or regions with limited data. This is important because knowing the distribution of farms helps in understanding how diseases spread, especially in areas with rapidly growing farm populations. Our model uses advanced statistical methods and is calibrated with environmental and human activity data to simulate farm locations and sizes, which we tested on farms in Bangladesh, Gujarat (India), and Thailand. We found that our model creates realistic patterns of farm locations and sizes, which are crucial for predicting disease outbreaks. When we simulated disease spread, our model showed that farms clustered together are more vulnerable to large outbreaks. This highlights the need for realistic farm data in disease prevention efforts. Our model can help public health officials in regions without detailed farm information to better plan and respond to potential disease threats. This work is a step towards better protecting both animal and human health from the spread of diseases. [ABSTRACT FROM AUTHOR]

The inclusion of rural smallholder farmers in the export of horticultural products has two major implications: increased household income through a promising global market, which is a catalyst for productivity, cumulatively growing Gross Domestic Product (GDP) and foreign exchange. So far, there are an estimated 2500 smallholder farmers who participate in the export of horticulture in Kenya. As a result, the current study sought to establish the nexus between quality control practices by the small holder farmers and the growth of the horticultural export market in Kenya. The study collected quantitative data using a structured questionnaire from a sample of 334 smallscale horticultural farmers who were randomly selected. Validity and reliability tests were performed before the main study. Then, descriptive and simple linear regression was used to analyze the data. Quality control practices can be measured through the Pre-production measures, Production and post-production control measures. Findings indicated that there was a statistically significant relationship between quality control practices and the growth of horticultural export markets. It was however observed that, there are weak quality control practices among the farmers which lead to non-conformities of products. This implies that the exports from Kenya become less attractive and make the smallholder farmers less competitive. [ABSTRACT FROM AUTHOR]

Using primary data from 180 cocoa farmers in Osun State, Nigeria, the study defined the externalities associated with cocoa production, evaluated farmers' willingness to pay for externalities and identified the determinants impacting farmers' willingness to pay for externalities in cocoa production. To analyze the demographic traits of the sampled farmers in the research area, descriptive statistics were used. Farmers' willingness to pay for externalities and the price they are willing to pay for them were estimated using the double-hurdle model. The findings showed that the majority of the examined farmers were able to name externalities brought on by pesticide leaching and bad odor, but very few of them could name externalities brought on by fermentation. For pesticides leaking, offensive odor and fermentation externalities, the average projected amount farmers were willing to pay per kg of cocoa is 60, 81 and 54 k, respectively. The findings also indicated that a variety of explanatory factors, including age, household size, years of schooling, farming experience, participation in farmers' associations, farm size and income from cocoa farms, had an impact on farmers' decisions to pay for the identified externalities. According to the study's findings, producers were willing to spend an estimated average of 140.54 k per kilogram of cocoa produced in order to compensate for the externalities. Therefore, if conveyed through market mechanisms, the hidden costs and benefits resulting from identified externalities could lead to efficiency in the price of cocoa. [ABSTRACT FROM AUTHOR]

Digital technology holds significant potential for enhancing business efficiency in agricultural marketing. However, empirical research on the use of digital technology among smallholder farmers engaged in staple crop marketing in Sub-Saharan Africa remains limited. Recognizing the pivotal role of digital technology in agriculture, this study aims to analyse and synthesize existing knowledge regarding the impact of mobile phones on market participation among smallholder farmers. Through a comprehensive analysis, we seek to provide a robust understanding that can inform policies and programs aimed at enhancing smallholder market integration. To achieve this objective, we collected cross-sectional data from 360 farmers in southeast Nigeria and implemented a double hurdle model to analyse market participation decisions and the extent of farmers' involvement in staple crop markets. In addition to traditional econometric methods, we employed propensity score matching to further investigate the impact of mobile phone ownership on market participation. Our analysis revealed that ICT tools, particularly mobile phones and radios, significantly influence both the decision and intensity of market participation among smallholder farmers. Specifically, mobile phones were found to play a crucial role in facilitating access to market pricing information and disseminating knowledge on improved production methods. Given the volatility of farm prices, the timely dissemination of market information through mobile phones is essential for farmers to make informed decisions. With a high percentage of mobile phone ownership and substantial investments in mobile networks in Nigeria, the digitalization of extension services and marketing information delivery systems could catalyse rapid improvements in agribusiness and marketing. This shift towards digital platforms has the potential to address information asymmetry, particularly among smallholder farmers, thereby fostering greater market integration and economic empowerment within rural communities. [ABSTRACT FROM AUTHOR]

The application of the resilience concept within socioecological systems has recently received much attention. Assessing the characteristics of cocoa agroecosystems in the dry and moist semi-deciduous ecological zones has become critical for resilience analysis in this era of climate change and the constant shrinking of cocoa suitability areas. Previous studies have used one of the dimensions of resilience to analyse complex adaptive systems, excluding critical factors and variables. This study applied a multi-criteria decision-making process, the Analytic Hierarchy Process (AHP) that accommodates the three dimensions of resilience, i.e., buffer capacity, adaptive capacity and self-organisation. The AHP is a multi-criteria decision-making tool that proceeds with the design of a hierarchy system for the goal, criteria, attributes and variables. Selected cocoa farmers were assigned weights related to criteria, attributes and variables in a comparison matrix. The resilience of the cocoa agroecosystems in Offinso Municipal and Adansi North Districts was 2.75 ± 0.06 (mean ± SD) and 3.23 ± 0.10 (mean ± SD), respectively. Buffer capacity contributed the highest proportion (44.3%) in the Offinso Municipal District, followed by adaptive capacity (38.7%) and self-organisation (17%). A similar trend was recorded for the Adansi North District: buffer capacity (42.9%), adaptive capacity (42.9%) and self-organisation (14.3%). Across the two study areas, shade trees, crop diversification, soil quality, cocoa variety, farm size, farm age, alternative livelihood, annual income and co-operative membership contributed prominently to the construction of cocoa agroecosystem resilience. The assessment of agroecosystem resilience is location-specific, and the study provides a simplified methodology for evaluating resilience. The paper aims to understand the importance of the components of the cocoa agroecosystem, and a simplified methodology for evaluating its resilience to perturbations. It presents a conceptual and methodological framework for the analysis and measurement of agroecosystem resilience in a participatory manner. [ABSTRACT FROM AUTHOR]

In Ethiopia rice crop is considered as a strategic food security crop which is expected to contribute to ensuring food security in the country. Bennch Sheko Zone is one of the major rice growing areas in the South Western Regional State. The study was conducted with specific objectives to investigate factors affecting smallholder farmers' market supply of rice and identify constraints related to rice production in the study area. Two-stage sampling technique was employed to select 119 representative rice-producer households. Descriptive statistics and appropriate econometric models were used to analyze the collected data. Multiple linear regression model used to analyze factors affecting rice market supply. Descriptive result of the study showed, the average annual rice production at the household level was 2.8 tons, of which 70% was supplied to the market. Econometric result showed farm size owned, credit use, annual income, number of oxen owned, and quantity of rice produced were found to be significantly affecting the market supply of rice in a district. Major constraints related to rice production in the district were a lack of proper weed management practices, improved seed, proper method and time of fertilizer application, weak institutional support, disease, and post-harvest handling problems were also important. The research findings suggest that attention should be given to rice production constraints through generation and wide demonstration of demand-driven rice production and post-harvest handling technologies for increased production and productivity to have a better market supply of rice to the market and benefit smallholder farmers. [ABSTRACT FROM AUTHOR]

This article aims to highlight the importance of climate and environmental challenges for agricultural economics and policy. Empirical research based on the Data Envelopment Analysis (DEA) method determined the average technical efficiency and scale efficiency of farms in the European Union in total and in economic size classes in the period 2004–2020. The results indicate that agriculture is generally characterised by high technical efficiency and scale efficiency. Analysis by economic size classes of farms, defined by the standard sum of their agricultural output, shows that the relationship between the scale of production and technical efficiency of farms is U-shaped. The highest technical efficiency and scale efficiency are characterised by small, large and very large farms economic classes. Economies of scale shift the burden of food production to large farms, which provide food security and are technically efficient but excessively burdensome for the climate and the environment. Small farms produce environmentally friendly food but on a small scale. Therefore, increasing the technical efficiency of medium-sized farms can contribute to more sustainable food production that meets both food security and climate and environmental objectives. The Common Agricultural Policy 2023–2027 provides greater access to financial support for moderate-scale farms and farms undertaking ecosystem restoration activities. This may affect the strength and direction of the relationship between farm scale and productivity, including technical efficiency. [ABSTRACT FROM AUTHOR]

Weather variations have posed enormous barriers to water resources, availability of food, human health, infrastructure, and natural environment. These phenomena underscore the need for climate smart practices in South Africa. The study examined in context, the socio-economic determinants, and acceptance of climate smart agriculture practices in Mzinti, Nkomazi Local Municipality South Africa. From a known population of 455 farmers, 212 samples were selected for the survey and considered realistic for the study. This survey comprised questions that were clear, unbiased, and relevant to the research questions. Enumerators were further briefed on the study objectives and the importance of consistent and ethical data collection. The team comprised of four primary data enumerators. A pilot survey with 20 randomly selected smallholder farmers was undertaken to identify and address any questionnaire that may be ambiguous. Based on this pilot, minor revisions were made to improve the questionnaire and ensure accurate reflection of intended variables, thus enhancing the reliability of the data collection instrument. A randomized sampling method was employed to select respondents who participated in the study. This allowed every participant to have a fair chance of being chosen. The study used the structured questionnaire, and the field survey was done between the month of April 2023 and July 2023. Descriptive statistics: frequency count, tables, and percentages, were used to explain the socio-economic determinants for acceptance of climate smart agriculture practices. The hypothesized variables were assessed using the binary logistic regression to determine the correlation between the socio-demographic characteristics and dependent variables. The result revealed that age (p< 0.007), crop yield (p<0.001), farm income (p<0.047) farm size (p<0.020, and food shortages (p<0.001) were correlated and statistically significant in determining the acceptance of climate smart agriculture practices. The study concluded that climate smart agriculture practices enhance farmer productivity, and it is influenced by factors such as age, farm size, and scarcity of food, crop yield, and farm income. The adoption of climate smart agriculture enables farmers to have increased crop yields, have access to food, increased income of the farm. Thus, it can be concluded that CSA practices effectively enhance the productivity of vegetable farming and food security. [ABSTRACT FROM AUTHOR]

This paper revisits the debate on the relationship between farm size and utilisation of agricultural land. Since the 1960s, a large number of studies have been examining this relationship and suggesting possible explanations supporting their thoughts. Three significant hypotheses exist in the literature forwarded by different scholars in this regard: an inverse relationship, a positive and a U-shaped one. Using the recent data from the Agriculture Census of India, this paper attempts to analyse the spatio-temporal trends of the relationship between farm size and land utilisation and examine the hypotheses and explanations already advanced, taking a state-level analysis in India. We found an inverse relationship where smaller farms are more fully and intensively used compared to the larger farms; however, the increasing share of unutilised land among the small and medium farms in the recent decade of 2005–2006 to 2015–2016 indicates a losing ground of small farmers because of ongoing agrarian distress. [ABSTRACT FROM AUTHOR]

The study examined the impact of agricultural cooperatives on poverty depth of cocoa farmers' poverty levels in Southwestern Nigeria. A multistage sampling technique was used in selecting 362 cocoa farmers in the study area. The results of a two-step control function quasi-maximum likelihood revealed that age, household size, farm size, and farming experience positively influenced the poverty depth while cooperative membership negatively influenced the depth of poverty among cocoa farmers. This study concludes that cooperative organizations have the potential to reduce poverty effectively, provided their values and principles are respected. Hence, an advocate for continued policy incentives targeted at encouraging farmers to form as well as participate in agricultural cooperatives. [ABSTRACT FROM AUTHOR]

A study was conducted on honey production in Imo state of Nigeria, with a focus on the health and economic dimensions of the industry. The research was carried out using a multi-stage sampling procedure, and a sample size of 80 honey-producer respondents was selected. Data was collected through a well-structured questionnaire and analyzed using descriptive and inferential statistics. The study found that honey producers in the area had a mean age of 51 years, 11 years of education, 21 years of farming/beekeeping experience, and a household size of 6 persons. The average annual household income was €709.10, with a farm size/number of hives kept of 72 hives per farmer and a quantity of honey produced per annum of 145 litres. The cost and returns analysis showed that the cost of production of honey per litre and profit per litre were €0.40 and €2.40, respectively. The study also determined the nutritional uses and health benefits of honey (e.g. healing wounds, treating ulcers, controlling sore throats and colds, boosting immunity, and as an antibacterial agent). Several factors, including uncontrolled bush burning, bee forage shortage, deforestation, theft of beehives, colony absconding, and poor agricultural practices which strongly constrain honey production has been observed. It is concluded that honey production is a very profitable venture with numerous uses and health benefits and venturing youths into honey production as a source of livelihood should be encouraged, and extension education should be tailored to technologies in beekeeping and the identification of genuine honey to minimize the success of adulteration, among others. [ABSTRACT FROM AUTHOR]

We investigated the determinants of changes in agricultural technology in Vietnamese rice-growing households. The double-hurdle estimation developed in this study proved to be an efficient method for determining how and to what extent changes in agricultural technology had been influenced by various factors while also allowing correlation between farmers' choices. We found evidence of a persistent increase in the use of improved seeds and machinery. In contrast, the previous upward trend in the use of fertilisers and pesticides was recently reversed. Farmers' decisions to adopt and use these four agricultural technologies are highly correlated with farm size, input and output prices, and macroeconomic conditions. Our findings also confirm a simultaneous relationship between the decisions to apply agricultural practices. When promoting new agricultural technologies, follow-up policy interventions should account for these characteristics of individual smallholders' decisions. [ABSTRACT FROM AUTHOR]

This paper analyzed farmers' willingness to accept (WTA) payment and uncertainties toward carbon market through a 2021 U.S. Midwest farmer survey. The findings showed that farmer carbon supply was elastic at intermediate prices ($20–50/Mg), but inelastic at low ($10–20/Mg) and high ($50–70/Mg) price levels. While perceived co‐benefits play significant roles in promoting participation at low‐price levels, variables such as age, education, farm size, and soil quality are more likely to influence producers' choices at intermediate‐ and high‐price levels. To enhance farmers' support for carbon programs, measures should be taken to improve benefit, while reducing cost and uncertainty. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Antimicrobial resistance (AMR) is a significant global health concern, necessitating the monitoring of antimicrobial usage (AMU). However, there is a lack of consensus on the standardized collection and reporting of AMU data in the veterinary field. In Denmark, the Danish Cattle Database (DCDB) contains treatment information on animal level, which allows counting of number of treatments carried out, used daily doses (UDD). The Danish VetStat database (VetStat) contains information on veterinary medicinal prescriptions at farm level and uses fixed standard doses of each product to calculate number of daily treatments, animal daily doses (ADD). This study aimed to compare two different numerators, UDD and ADD, used to describe AMU on Danish cattle farms, and estimate their correlation. Results: Routinely collected registry data from conventional dairy farms in Denmark for 2019 were used, including a total of 2,197 conventional dairy farms. The data from VetStat and the DCDB were aggregated and analysed, and treatment frequencies (TF) were calculated for both UDD and ADD, adjusting for farm size. Spearman correlation analysis and Bland–Altman plots were employed to assess the relationship and agreement between TF for ADD and UDD, respectively. The results showed a high correlation between TF for ADD and UDD for most prescription groups, i.e., groups used to categorise antibiotics based on target organs. An exception is found for the Udder prescription group, where a systematic underreporting of UDD compared to ADD was observed. This discrepancy may be due to combination treatments, and potential missing or grouped registrations in the DCDB. Conclusions: Our UDD and ADD comparison yields valuable insights on farm-level AMU. We observe strong correlations between UDD and ADD, except for udder treatments, where some farms report only 1/3 UDD compared to ADD, indicating potential underreporting. Further investigations are needed to understand the factors contributing to these patterns and to ensure the accuracy and completeness of recorded information. Standardizing AMU data collection and reporting remains crucial to tackle the global challenge of AMR effectively. [ABSTRACT FROM AUTHOR]

Accurate and timely information on farmland size is crucial for agricultural development, resource management, and other related fields. However, there is currently no mature method for estimating farmland size in smallholder farming areas. This is due to the small size of farmland plots in these areas, which have unclear boundaries in medium and high-resolution satellite imagery, and irregular shapes that make it difficult to extract complete boundaries using morphological rules. Automatic farmland mapping algorithms using remote sensing data also perform poorly in small-scale farming areas. To address this issue, this study proposes a farmland size evaluation index based on edge frequency (ECR). The algorithm utilizes the high temporal resolution of Sentinel-2 satellite imagery to compensate for its spatial resolution limitations. First, all Sentinel-2 images from one year are used to calculate edge frequencies, which can divide farmland areas into low-value farmland interior regions, medium-value non-permanent edges, and high-value permanent edges (PE). Next, the Otsu's thresholding algorithm is iteratively applied twice to the edge frequencies to first extract edges and then permanent edges. The ratio of PE to cropland (ECR) is then calculated. Using the North China Plain and Northeast China Plain as study areas, and comparing with existing farmland size datasets, the appropriate estimation radius for ECR was determined to be 1600 m. The study found that the peak ECR value for the Northeast China Plain was 0.085, and the peak value for the North China Plain was 0.105. The overall distribution was consistent with the reference dataset. [ABSTRACT FROM AUTHOR]

This study evaluated growth, yield and olive oil quality of mature pedestrian olive orchards. Trees of three Sicilian cultivars Calatina, Nocellara del Belice and Abunara were planted at four combinations of planting densities and training forms. Trees at 2 × 5 m were trained to central leader (CLx2), those at 3 × 5 m to free palmette (FPx3), those at 4 x 5 to globe vase (GVx4), and those at 5 x 5 to poly-conic vase (PVx5). 'Calatina' had the smallest trees in terms of trunk size in all growing systems, while canopy size of trees at higher densities was similar for all three cultivars. 'Calatina' was also the most growth efficient (m3 of canopy per cm2 of TCSA) and produced the least amount of pruning wood in the hedgerow systems (CLx2 and FPx3). Fruit yield per tree tended to be higher in more vigorous cultivars (Abunara and Nocellara) grown to 3D systems (GVx4 and PVx5), while 'Calatina' was the most yield efficient (kg of fruit per cm2 of TCSA) especially in the hedgerow growing systems. Fruit and oil yield per ha and average production value tended to be highest in CLx2 trees and lowest in GVx4 trees, with 'Calatina' showing the sharpest changes and 'Nocellara' the smallest changes among growing systems. According to the Jaen index, CLx2 tended to induce earlier fruit maturation, followed by PVx5, GVx4, and FPx3. The growing system did not affect oil fatty acid composition, while 'Calatina' had the highest amount of mono-unsaturated fatty acids and the lowest amount of saturated fatty acids. 'Abunara' oils exhibited the highest amount of total phenols in CLx2, while 'Calatina' and 'Nocellara' oils exhibited the highest amount in FPx3 and PVx5. Both, trans-2-hexenal ("cut grass" sensory note) and hexenyl acetate ("floral" sensory note) tended to be lowest in oils from trees grown at CLx2 and highest in those from trees grown at GVx4, showing a somewhat inverse relationship with fruit ripening degree. The outcome of the present study on mature pedestrian orchards shows that proper combinations of cultivars, planting densities, and training forms (canopy shape) may result in efficient intensive systems for growing olive in areas where super-high density systems cannot be profitable due to agronomic and environmental limitations (water shortage, steep sloping sites, small farm size, etc.). Pedestrian growing systems can also be used to exploit olive biodiversity by allowing the use of available local genotypes. For this reason, they may represent an effective and sustainable solution against unexpected climate changes and associated emerging diseases. [ABSTRACT FROM AUTHOR]

Lake Urmia in the northwest of Iran is one of the largest vanishing lakes in the world. Several water-saving strategies have been implemented in the lake basin over the last decade, but they are not producing efficient results. This study employed a modified version of the Soil and Water Assessment Tool (SWAT), an agrohydrological model, to investigate the basin-scale effectiveness of some water-saving plans implemented at the farm scale. Data collected from 301 monitoring sites in the Lake Urmia basin were applied to the modified SWAT model. The modified SWAT model was used to estimate water balance components and was coupled with the Water Accounting Plus framework (WA+). Six discharge stations, crop yields, evapotranspiration, and groundwater level tables were calibrated and validated from 1987 to 2015 within the Zarrineh Rud Basin (ZRB), the most crucial subbasin in the Lake Urmia basin. Next, four individual water-saving plans—changes in irrigation management and developments in irrigation systems, changes in fertilizer type and regime, changes in the type and method of cultivation, and farm size and shape adjustments—as well as seven combinations of the water-saving plans, were applied to the agrohydrological model. The results reveal that assessing restoration plans for Lake Urmia without considering both farm and basin scales provides no reliable results. With changes in management and the development of irrigation systems, considerable differences in water withdrawal were observed. Developing irrigation systems leads to enhanced water consumption and evapotranspiration, which is expected to improve water yield and crop productivity. However, individual plans such as developments in irrigation systems cannot increase the inflow to Urmia Lake, and combined water-saving strategies can help restore the lake only to a limited extent, because the changes in inflow are not substantial. [ABSTRACT FROM AUTHOR]

The global push for renewable energy must overcome the local challenge of convincing neighboring landowners to lease their properties for wind power. Is this challenge more or less pronounced in rural landscapes with small landholdings? Our theoretical model combines ideas from literatures on the commons, anticommons, and spatial externalities to explain conditions when small landholdings could promote or inhibit voluntary leasing. Empirically, we estimate the effects of landholding size and landscape fragmentation on wind farm uptake across rural areas of the United States over the past 20 years. Evidence from three spatial levels of analysis (counties, square‐mile sections, and individual parcels) indicates that areas with more landowners have less installed wind capacity after controlling for windiness, access to transmission lines, and other relevant factors that vary across and within counties. The findings imply that fragmented ownership, which is an overlooked factor in studies of the feasibility of decarbonization, will pose an impediment to future wind expansion on private land as remaining areas without wind development become disproportionately fragmented. [ABSTRACT FROM AUTHOR]

Copyright of European Journal of Wildlife Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Brazilian agriculture is characterized by the prevalence of small farms and regions with a high degree of rurality and dominance of the agricultural sector in the economy. These two characteristics affect the diversity of agricultural production in the country. Specifically, the article aims to analyze the effects of size farm and farmland use on agricultural diversification and the effects of demand and technology adopted by farmers. The database encompasses 4298 Brazilian municipalities from 1996 to 2017 (the last three agricultural censuses). Empirically, we consider spillover effects by estimating spatial models at the municipal level using panel data, highlighting the importance of location and neighborhood. The study's findings indicate a tendency toward local concentration of agricultural production in the country, despite the balance between municipalities with diversified and concentrated production. The results showed a significant effect of small farms and the municipalities' rurality degree on the agricultural output diversification. The study provides insights into the discussion on measures to strengthen support for small properties and regions that diversify crops to ensure economic efficiency and food security. [ABSTRACT FROM AUTHOR]

In the north-western part of India, especially in Punjab and Haryana plains, the groundwater overdraft increases the cost of its withdrawal for irrigation and causes inequality in its access to farmers. As a result, groundwater markets are gradually emerging as pervasive agrarian institutions. In this research, the groundwater market structure has been studied in Haryana state and Karnal district has been chosen as the study area. For the survey, three villages are selected by the purposive sampling technique. The 300 households (100 households from each village) are selected by the simple random sampling technique. The primary data are collected by close-ended structured scheduled, interviews, and focus group discussions methods from the selected villages between the periods of May to September 2019. The study reveals that groundwater markets help to mitigate the increasing inequalities in groundwater access. The results show that almost 50% of the farming households have participated in the groundwater markets. There is a positive correlation (R2 = 0.6176) between water selling and farm size and a negative correlation (R2 = − 0.9828) between water buying and farm size. Groundwater scarcity, land fragmentation, and no tubewell on their own land have been observed as primary factors for the participation of farmers in groundwater markets. The most popular mode of water transactions is cash-based (hourly), which shows the mature stage of groundwater markets in the study area. Groundwater trade for irrigation is maximum under two crops, rice (45%) and wheat (46%), which significantly puts pressure on the groundwater resources. The study is suggested to change the cropping pattern and moving to two crops combination (rice and wheat) to crop diversification. A community-based approach is essential for efficient groundwater resource use in a water-scarce environment via effective institutional arrangements. [ABSTRACT FROM AUTHOR]

This study estimates the relative contribution of different factors to the wide variation in agricultural economic water productivity (EWP) across Colorado River Basin counties. It updates EWP measures for Basin counties using more detailed, localized data for the Colorado River mainstem. Using the Schwarz Bayesian Information Criterion for variable selection, regression analysis and productivity accounting methods identified factors contributing to EWP differences. The EWP was USD 1033 (USD 2023)/acre foot (af) for Lower Basin Counties on the U.S.–Mexico Border, USD 729 (USD 2023)/af for other Lower Basin Counties, and USD 168 (USD 2023)/af for Upper Basin Counties. Adoption rates for improved irrigation technologies showed little inter-county variation and so did not have a statistically significant impact on EWP. Counties with the lowest EWP consumed 25% of the Basin's agricultural water (>2.3 million af) to generate 3% of the Basin's crop revenue. Low populations/remoteness and more irrigated acreage per farm were negatively associated with EWP. Warmer winter temperatures and greater July humidity were positively associated with EWP. When controlling for other factors, being on the Border increased a county's EWP by USD 570 (2023 USD)/af. Border Counties have greater access to labor from Mexico, enabling greater production of high-value, labor-intensive specialty crops. [ABSTRACT FROM AUTHOR]

Policies regulating common-pool resources (CPR), such as wetlands, should take into account community socio-economic realities and community perceptions. The study aims to examine whether policies regulating common-pool resources, such as wetlands, should take into account community socio-economic realities and community perceptions. Specifically, it characterized Ethiopian farm households in the Amhara Region and household-head perceptions of six factors related to sustainable wetland management. Surveys were given to 385 respondents from five administrative units or kebeles (kebele is the smallest administrative unit). Focus-group discussions followed. All respondents were Orthodox Christians, and men constituted 93% of household heads. Kebeles differed significantly for household-head age and education, but overall education level was low. Most households had three or four children. Overall, the mean farm area was 0.89 ha, but within kebeles, mean areas ranged from 1.35 to 0.80 ha. Kidest Hana was the most successful kebele for farm size and yield. Significant differences existed among kebele farms for percentages of harvested crops sold, suggesting some were less food-secure. Data suggested male household-head farms had twice the area of female-head farms, older household heads had more land than younger ones, heads with more education had more children, and married heads had more land than divorced or unmarried heads. None felt that people outside their kebele should access their natural resources. Overall, 85% thought land ownership was communal, and 15% thought it was private. A plurality (44%) did not know who oversaw land management. None knew of any organizations working on sustainable wetland management, but most (75%) wanted to attend meetings on the subject. No farm used mechanized agriculture. Most (87%) had not abandoned alternative crops to produce more rice. Therefore, as a conclusion, every effort needs to be taken to address this socio-ecological and development challenge that faces Fogera wetlands and larger national and international impacts to achieve balanced and sustainable development. Hence, our study highlights the need for better education, leadership, and policies regarding sustainable wetland management. [ABSTRACT FROM AUTHOR]

Farmers can counteract global warming by drawing carbon dioxide from the air into agricultural soils by building up humus. Humus programs were developed to motivate farmers for even more humus formation (= carbon sequestration) through an additional financial incentive. These programs are still at an early stage of development, which is why the number of participating farmers and research work is still low. This study is the first to analyze the willingness of German farmers to participate in hypothetical humus programs. The results of a discrete choice experiment show that a (higher) threshold for the payout of the premium, regional (rather than field-specific) reference values, and the risk of repayment clearly discourage farmers from participating. Program providers must more than double the premium (set at around 240 € per hectare and 0.1% humus increase) to maintain farmers' willingness to participate despite a payout threshold. Regional reference values and an additional premium/repayment system would lead to an increase in the premium of around 20 € per hectare in order to keep the willingness to participate at the same level. The motivation to build up humus, the desire to maximize subsidies, and a higher livestock density have a positive influence on farmers' decision to participate. Farm size and risk attitude have an impact on farmers' preferences for program design. The study is relevant for policymakers and non-governmental organizations concerned with carbon management, as our findings highlight pathways for efficient, targeted designs of humus programs and carbon sequestration policies. [ABSTRACT FROM AUTHOR]

Abstract This article looks at the key factors affecting the connection between peasant family size and farm size in Italy in 1930–1931. The association between farm size and family size was analyzed using a new dataset merging data drawn from both the Population Census of 1931 and the Census of Agriculture of 1930. We found a strict association between peasant family size, here considered as a production unit, and the surface area of the farm. The results seem to correspond to different causal relationship between family size and farm size according to access to land, and form of tenure. In some contexts, where sharecropping was widespread, farm size defines the size of the family. In others where small land ownership prevailed, it seems that family size shapes the size of the farm. In this study we propose a new explanation for peasant family size in the Fascist period. This is done adopting a cross-sectional perspective, providing a geographical analysis based on the 786 agrarian areas that formed the national territory in that period.

The constant changes experienced in agricultural activities due to climate change pose a great challenge to melon production. Hence, this research examined the determinants of melon farmers' adaptation strategies to cope with climate change hazards in southern–southern Nigeria. The research ultimately depended on primary data collected by using a set of questionnaires and interviews. The data were obtained from 260 samples retrieved from melon farmers by using multistage sampling techniques. The data were analyzed using the multivariate probit (MVP) model and partial eta squared test. The results of the MVP model showed that age (− 0.009), marital status (0.200), access to information on climate change (0.567) and crop insurance (0.214) were significant at the 0.01 level, while household size (− 0.030) was significant at the 0.05 level and determined the adoption of crop diversification. Educational level (0.012), extension contact (0.138) and access to credit (0.122) were significant at the 0.05 level, while access to information on climate change (0.415) was significant at the 0.01 level and determined the adoption of change in planting dates. Age (− 0.010) and access to information on climate change (0.381) were significant at the 0.01 level, while sex (− 0.139), marital status (0.158) and off-farm income (− 2.3E-7) were significant at the 0.05 level and determined the adoption of mixed farming. Farming experience (0.005) is significant at the 0.05 level, while access to information on climate change (0.529) and crop insurance (0.272) are significant at the 0.01 level and determine the adoption of drought-tolerant crop species. Access to information on climate change (0.536) is significant at the 0.01 level, indicating the adoption of improved crop species. Age (− 0.010), farm size (− 0.085) and crop insurance (0.206) were significant at the 0.05 level, while access to information on climate change (0.353) was significant at the 0.01 level and determined the adoption of off-farm job opportunities. The study recommends the availability and accessibility of credit, climate-smart agricultural practices, and the establishment of public‒private partnerships, among others. [ABSTRACT FROM AUTHOR]

The layout optimization of wind turbines seeks to improve wind power conversion efficiency by minimizing the wake effect in wind farm. However, the existing optimization methods cannot provide a layout with high output power due to their inability to weaken the energy losses caused by the wake effect between turbines. In this paper, an equilibrium optimizer with local perturbation and adaptive escape strategies, termed adaptive equilibrium optimizer (AEO), is proposed to tackle the wind farm layout optimization problem (WFLOP). To be specific, the worst turbines in the layout are re-located to better locations to reduce wind losses by enhancing the exploitation capacity of AEO with a local perturbation strategy. Then, an adaptive escape strategy supports the particles to get out of the local optimum and to search toward more promising areas, which facilitates the adjustment of the layout to reduce the wake effect. Besides, an adaptive repair operator adaptively reconfigures infeasible layouts to augment the proportion of feasible solutions in the population; thus, AEO can sufficiently explore the layout space to optimize the output power of wind farms. Twelve prohibited area constraints, three turbine scales, and three wind farm sizes are utilized to evaluate the performance of AEO in two cases with various wind speeds and directions. The experimental results demonstrate that the AEO performs excellently in terms of efficiency, robustness, and generalization for the layout optimization of turbines with different constraints, scales, and wind farm sizes in comparison with the state-of-the-art metaheuristics and other methods reported in the literature. [ABSTRACT FROM AUTHOR]

This study developed a theoretical model to explain the consolidation of farmland and specialization in agriculture. In the model, farmers are assumed to be endowed with knowledge regarding the production of each crop, which evolves through learning. Knowledge across crops is substitutable to various degrees. The farm size distribution and specialization are shown to be equilibrium outcomes determined by the distribution of knowledge. A simulation example based on farm‐level acreage data from California is presented to show the relevance of learning mechanisms and test model implications. [ABSTRACT FROM AUTHOR]

This research aims to measuring the efficiency of investment in Moringa farms in New Lands, quantifying the potential impacts of changes in major technical and economic variables on efficiency, and determining the Switching Value for the most affecting variables. A sample of 15 farms, located in Wadi El-Natroun in Alexandria Governorate, was Surveyed and post-stratified into small size farms (5 faddan and less) and large size farms (more than 5 faddan) to generate technical coefficients. Cash flow was prepared per faddan for each scale and IRR and NPV were calculated. Major results and conclusions can be summarized as follows: (1) Investment efficiency was achieved for Moringa production in the Wadi El-Natroun region, where the average internal rate of return was estimated at about 57%. The net present value is about 125.13 thousand pounds. (2) The decrease in the number of trees produced per faddan by 10% led to a decrease in the internal rate of return and the net present value with an average decrease of 19.98% and 22.22%, but it is still good and achieves investment efficiency. The Switching Value for the number of trees was estimated at 540 trees/faddan, 440 trees/faddan, i.e. 71% and 58.67% of the current situation for the small and large capacities, respectively. (3) The prevailing agricultural pattern is (80% moringa leaf production: 20% moringa seed production), and specialization in agriculture for the purpose of producing moringa seeds is the best in terms of the values of the investment efficiency standards used, followed by diversification between seed and leaf production. (4) The Switching Value for the productivity of an faddan of moringa seeds was estimated at approximately 10%, 0% of the current productivity for the small and large capacities, respectively, while the productivity of an faddan of moringa leaves at approximately 54%, 39% of the current productivity for the two capacities, respectively. (5) The Switching Value for the selling prices of seeds was estimated at approximately 88% and 0% of the current prices for the small and large containers, respectively, while for the selling prices of leaves at approximately 62.67% and 53.75% of the current prices for the two capacities, respectively. (6) The change in human labor costs is the most influential item in outflows on the internal rate of return. (7) There are many production and marketing problems facing Moringa producers in the Wadi El Natroun region. The research ended with Some recommendations and mechanisms for achieving them that can help the producer and take more efforts to overcome the problems and encourage growth and production of moringa in Egypt. [ABSTRACT FROM AUTHOR]

In the face of a changing climate and a rising number of "food deserts" in both rural and urban areas, there is a demand to supply fresh produce year-round to communities at the end of the traditional agriculture supply chain. Vertical indoor farming is a promising mode of next-generation agriculture that boasts reduced water and pesticide usage, improved yields, more consistent quality, year-round cultivation, and cheaper transportation and harvesting costs. Indoor farms can rival industrial greenhouses in size, but small-scale "pod farms" can be deployed to smaller communities and areas where large swaths of land are either unavailable or too costly. These pods are often the size of shipping containers with their temperature, humidity, and plant nutrient supply carefully controlled. Plants inside the pods are grown hydroponically with light supplied by panels of LEDs and, thus, this mode of farming is fundamentally different from greenhouse farming. Many indoor farming pods have recently become commercially available claiming high energy efficiency, but little analysis and optimization work has been done to prove these claims. To drive innovation in the design of these physical systems, we have developed a digital-twin and genomic optimization framework for the optical design of vertical indoor farming pods. We model a completely enclosed indoor farming pod with plants in the three mutually-orthogonal planes and illuminated by LED "walls." We employ ray-tracing methods and a genetic algorithm to determine the LED source tube area size, beam aperture spread, and power requirements for maximal power absorption by the plants. [ABSTRACT FROM AUTHOR]

Achieving sustainable agricultural development is a vital concern as soil degradation poses a growing threat to the livelihoods of smallholder farmers in the developing world. Previous literature has highlighted the potential for rural population growth to exacerbate this concern by leading to smaller farm sizes and crop production on marginal land. This paper uses a theoretical model to demonstrate a countervailing effect consistent with the work of Esther Boserup: Smaller farm sizes can encourage greater intensification and investment in the soil. Using panel data from the Tanzania National Panel Survey, I test the model and find some evidence consistent with this effect. Smaller farms are associated with greater organic, but not inorganic, fertilizer application, and higher levels of some soil quality proxies. These results suggest that if key resource and information constraints are overcome, population growth need not be an obstacle, and can be a boon, to sustainable agricultural development. [ABSTRACT FROM AUTHOR]

In Punjab, Pakistan, the "Warabandi" principle guides the distribution of surface water in tertiary canal networks to each farm. The allocated amount is proportional to farm size and provided according to a predetermined schedules in a 7-day fixed rotation. Limited canal water and rigid rotations of the Warabandi-guided water allocation led to unsustainable pumping of groundwater and relatively low field application efficiency. Using both site monitoring and modelling, we assessed cotton irrigation scheduling under current practices and the planning options in the context of the Warabandi principle. The farming practices of two raised-bed furrow cotton fields were intensively monitored at the Mungi distributary canal command area in Punjab. The AquaCrop model was parameterized and validated using 2019 and 2020 datasets and then applied to assess four irrigation scheduling scenarios. Scenario 1 reflects the current irrigation practice under canal water and groundwater use, while for scenarios 2, 3, and 4, solely canal water was considered and irrigation followed a fixed rotation of 7-days, 14-days, and targeted intervals, respectively. According to simulations' outputs, scenarios 2, 3, and 4 resulted in better performance compared to the current practices in both fields by reducing percolation substantially up to 90% below the root zone and lowered soil evaporation by up to 27% enebling similar yields ∼2.2 ton/ha raw cotton and higher water productivity. Under the frame conditions of Warabandi, scenario 4 was a promising option for introducing more flexible and demand-oriented irrigation at the farm level targeting cotton's water-stress sensitive growth stages by adapting irrigation application to rainfall events and refilling the soil slightly below field capacity level during each irrigation event to reduce percolation. The study delivered detailed information about cotton irrigation scheduling for on-farm water management, considering a bottom-up approach in Punjab. [ABSTRACT FROM AUTHOR]

Farm businesses often use debt to finance the purchase inputs and meet operational costs. Selected studies have investigated the impact of debt use on farm performance as measured using technical efficiency. However, no prior studies in agriculture have considered treating the debt repayment obligation created as a by‐product of production when benchmarking farm performance. This study employs nonparametric directional distance function models to quantify the impact of debt repayment as a by‐product of input use purchased on credit on farm‐level partial inefficiency using a panel data of 54 mixed enterprise broadacre farms in Western Australia from 2002 to 2011. The study finds that omitting repayment obligations created in the production process in analysis results in underestimating partial inefficiency scores. Farm size, production diversification and rainfall zone are significant drivers of partial inefficiency. The implication of the study's findings is that failure to account for repayment obligations created in the production process may result in erroneous policy suggestions that undermine the efforts of farm businesses to minimise or avoid financial stress. [ABSTRACT FROM AUTHOR]

Short-term estimates are not suitable for monitoring and comparing fluctuating pesticide use in EU agricultural land. A discriminative and comparable (HI) herbicide index was evaluated to elucidate herbicide use in the 21st century. The HI was 0.66 kg of active substances per hectare of conventional agricultural land across the EU. However, the HI varied between the 27 EU Member States. The highest mean values of HI were observed in Belgium, the Netherlands, Cyprus, Germany, France, and Denmark, with the lowest in Romania, Greece, Bulgaria, and Latvia. The results showed that the distribution of the HI variable was independent of the geographical location of each country, such as from North to South or from West to East in the EU. It seems that country-level agri-environmental parameters ultimately influenced the herbicide use. To assess the causes of this variability, 31 agri-environmental parameters (formatted into indices to be comparable) were investigated, emphasizing the structural characteristics of the agricultural sector in each EU Member State. Using only the significant independent variables (13 out of 31), linear discriminant analysis (LDA) was applied to explore the differentiation potential of EU27 by creating a discrimination model. The assessment of each one variable in the HI could contribute to the reduction in environmental impacts and the faultless implementation of the European agricultural policy in the near future. [ABSTRACT FROM AUTHOR]

The dairy sector is the second largest agricultural sector in the EU and Lithuania. It faces economic challenges (price volatility, farm consolidation and downsizing, etc.), but its importance outstrips other agricultural sectors (combining agro-systems and providing valuable food products for people). The aim of the study is to identify the vulnerabilities of dairy farms and to consider how to improve their performance after analysis of dairy farms in dairy exporting EU countries. As the problem of the study is complex, a set of indicators was analysed, including farm size, milk yield per cow, number of cows per annual work unit (AWU), milk production per fodder area, feed autonomy, milk price, total operating costs, depreciation, farm net value added per AWU, milk production per capita, and GDP at current prices per capita. The analysis was carried out using data from the Farm Accountancy Data Network (FADN) for 2017–2019. As Lithuania's dairy sector is export-oriented, EU countries with more than 100% milk self–sufficiency (18 countries in total) were chosen for the comparison. The multi-criteria decision-making methods (MCDM) were used for the study. The multi-criteria evaluation revealed that countries that are leaders in dairy exports obtained the best values of dairy farm performance. These countries (Denmark, Netherlands, Ireland, and Belgium) have the highest farm size, production scale, productivity, and income indicators. While Slovenian, Latvian, and Lithuanian dairy farms performed poorly in terms of productivity and economic indicators, these countries achieve competitiveness in the dairy sector through lower milk prices, higher utilisation of own resources, and higher levels of public support. [ABSTRACT FROM AUTHOR]

Climate change, changes in the natural environment, changing markets, price volatility, etc. pose tension and threats to the future of European Union farms. The uncertain future of family farms requires farm resilience—the ability to survive, adapt, and grow in the face of turbulent change. The limited resilience of family farms has become an important concern for rural and agricultural policy. The main goal of this work is to identify disturbances affecting Lithuanian family farms, assess their influence, investigate the general resilience of Lithuanian family farms, propose measures to reduce the vulnerability of farms, and increase the general resilience and sustainability. We used a combination of qualitative and quantitative research methods to conduct the research. Survey research was conducted using a semi-structured expert interview in which various types of variables were collected. The survey questionnaire, consisting of 38 groups of questions, was sent by email to 500 randomly selected family farmers in January 2024 and collected in the same month. The statistical analysis of the data from the 205 duly filled-out questionnaires was carried out using correlation analysis. In this article, we apply the concept of general resilience of the family farm in the direction of robustness, adaptability, and transformability. We identify the main factors influencing the general resilience of the family farm and study the main attributes of the resilience of family farms. We find some links between family farm characteristics, vulnerability factors, and general resilience capabilities, and we make several proposals to increase family farms' resilience. The obtained results prove that higher education, larger farm sizes, higher agricultural sales, and employment of permanent workers are associated with better resilience. Furthermore, increasing environmentally friendly practices positively impacts resilience. Older farms and farmers, longer durations of farming activity, and risk-averse behaviors tend to decrease resilience. Due to local and global circumstances, economic and social changes have occurred very quickly in recent years, so the results obtained in the study may not be valid in the long term. Similar surveys after several years will be necessary to study the resilience of Lithuanian farms, including deeper economic analyses that evaluate factors such as price sensitivity, the level of farm debt, and market access. [ABSTRACT FROM AUTHOR]

This study applies data envelopment analysis (DEA) to gauge technical efficiency and allocative efficiency in China's beef cattle-fattening industry using survey data. The Tobit model considers the salient determinants that drive these efficiencies. The results indicate that (1) large-scale farms exhibit robust TE and pure technical efficiencies (PTE), whereas scale efficiencies (SE) diverge significantly between large and medium-sized operations. The cost efficiency (CE) of smaller farms lags behind their larger counterparts, with the latter displaying greater revenue efficiencies (RE) and profit efficiency (PE). (2) The influence of identical factors on the efficiency of beef cattle fattening production can vary, sometimes antithetically, across different scales. Local policy interventions must be differentiated according to farm type and size. (3) The unique context of China's national conditions and the status quo of livestock farming render the dual implementation of environmental regulations and technological subsidies less viable for Chinese beef cattle farms. These entities should prioritize production over technological innovation and advancement. Policymakers should adopt strategies such as targeted skill/technological training for farm managers at particular scales of operation. This could represent a critical trajectory to augment the efficiency of beef cattle production and increase beef yield in China. [ABSTRACT FROM AUTHOR]

Seaweed farming in Maine, USA has grown exponentially over the last 5 years. Our work builds upon a prior Maine aquaculture sector benchmarking study to assess changes between the 2017 and 2022 harvest seasons. We interviewed 16 farmers who collectively harvested over 1 million lbs. (wet weight) of seaweed, ∼22 times the harvest volume from the 2017 season. We observed three notable improvements on kelp farms in Maine between 2017 and 2022: (1) median seaweed yield grew by 28%, from 3.3 to 4.24 lbs./ft.; (2) labor efficiency improved by 1,275%, from a median of 7.55 to 103.8 lbs. harvested per hour of labor and management input; and (3) median net margin per pound harvested increased from −$6.41 to $0.16/lb. These gains can likely be attributed to increased farmer knowledge, "learning by doing," extension support, improved seed production, and increases in scale. When benchmarks were recalculated according to three size groupings, we found that net margins ($/lb.) increased and breakeven price decreased with farm size (total lbs. harvested), indicating economies of scale. We found that fishermen, shellfish farmers, and other members of the working waterfront continue to leverage seaweed farming as a worthwhile source of supplementary income. [ABSTRACT FROM AUTHOR]

Purpose: The aim of the study was to identify practical challenges, best practices, and solutions used during the deployment of agricultural machinery depending on the size of the farm Design/methodology/approach: The method of observation and risk analysis was utilized in the operation of agricultural machinery using the FMEA method to identify potential threats and develop strategies for their mitigation. Findings: Research conducted on farms has revealed significant issues such as improper maintenance, lack of safety guards, and outdated equipment. To enhance farm safety, it is recommended to adhere to maintenance schedules, replace old machinery with newer models, and use Failure Mode and Effects Analysis (FMEA) to identify and mitigate potential hazards. Research limitations/implications: Further large-scale research is needed to develop effective strategies for improving farm safety. Implementing structured safety management systems like FMEA is recommended to systematically assess and minimize risks in both individual and large-scale farms. Practical implications: Implementing recommended measures such as regular inspections and maintenance, replacing or modernizing outdated machinery, using appropriate safety guards, and participating in training sessions will help reduce the risk of machinery failures and the number of accidents. Originality/value: This article presents new research findings on agricultural machinery safety in individual and large-scale farms, identifying significant issues and proposing specific improvement measures for farmers and agricultural safety experts. These insights help farmers understand risks better and implement safety enhancements when operating machinery. [ABSTRACT FROM AUTHOR]

The relationship between farm size expansion and efficiency is a key topic in agricultural economics, especially for achieving sustainable land use and food security. While existing literature focuses on land productivity, technical efficiency, and total factor productivity, the link between farm size and cost efficiency remains less explored. Cost efficiency is a critical indicator of production effectiveness and directly impacts agricultural sustainability and food security. This paper analyzes how farm size expansion affects the cost efficiency of Chinese rapeseed production, with a particular emphasis on sustainable agricultural production and food security. Our findings indicate an average cost efficiency of 0.740 for rapeseed in China, suggesting potential for improvement. We observe an inverted U-shaped relationship between farm size and rapeseed cost efficiency, with variations based on regional and topographic conditions. Optimal rapeseed farm size is between 10 and 30 mu in eastern and central China, and smaller than 10 mu in western China. Interestingly, in central China and plains regions, larger farm sizes have a less negative impact on cost efficiency. Finally, increasing plot size positively moderates the relationship between farm size and rapeseed cost efficiency, suggesting benefits from expanding both plot and farm sizes simultaneously. These findings provide empirical evidence to inform policy decisions related to sustainable land use, cost-efficient agriculture, and food security. [ABSTRACT FROM AUTHOR]

The article focuses on the question of optimal farm size in the context of contemporary agricultural challenges such as rapid population growth, climate change, and limited natural resources. The analysis shows that farm economic size can have a significant impact on financial performance indicators including productivity, profitability, liquidity, solvency, and sustainability. The article provides a detailed overview of the pros and cons of different farm economic sizes and their impact on financial sustainability, drawing on academic literature, available data, and statistical methods. The results indicate that larger farms have lower factor productivity but higher solvency. Smaller farms on the other hand have higher profitability and productivity. Medium-sized farms are characterized by high liquidity and financial autonomy. [ABSTRACT FROM AUTHOR]

Context: Managing people outside the farm family unit is a new issue for many Irish dairy farmers. In the context of rapid growth, the demand for employees has increased, creating the need for Irish dairy farmers to have human resource management (HRM) skills. Aims: This paper explores the extent and type of HRM practices adopted by Irish dairy farmers and the factors that influence their adoption. Methods: A questionnaire was developed, piloted, and issued to farmers on the basis of herd size and location. Data from 203 dairy farmers who employ people were analysed to examine the adoption of different HRM practices and the influence of farm characteristics, farmer demographics and farmer attitudes on their adoption. HRM practices included compliance with employment legislation, health and safety, different approaches to recruitment, workforce management and retention. The questionnaire included one or more variables for each of these HRM practices. Where more than one variable was included, an aggregate variable was developed for that practice. Key results: Whereas, overall, there was a low level of adoption of best HRM practices, farm characteristics such as herd size and number of employees had a significant influence on farmers' adoption of compliance with employment legislation, health and safety, recruitment, workforce management and retention practices. Demographic factors such as age, level of education, and average hours worked influenced farmers compliance with employment law legislation, workforce management practices and retention practices. Conclusions: The study highlighted an overall low compliance with employment legislation and low adoption of best practices in managing staff among dairy farmers in Ireland. Implications: This study highlighted that improvement is needed in all areas of HRM on Irish dairy farms. The findings of this study would be useful to farm advisors who support dairy farmers in improving their management of their businesses. Overall, this study has contributed to a greater understanding of the challenges in managing people in agriculture and how certain factors influences the adoption of HRM practices on dairy farms. The dairy industry's recent growth in Ireland has resulted in a high demand for additional workers, increasing the requirement for farmers to be skilled in Human Resource Management (HRM). This study identified that the adoption of HRM practices is influenced by farm characteristics, in particular herd size, the number of employees on the farm. This study has contributed insights into the prevalence of specific HRM practices on Irish dairy farms, and indicated that there is a significant scope for improvement. A novel aspect of this study was the focus on the potential factors that influence the adoption of HRM practices on Irish dairy farms. The findings of this study could be used by agricultural advisors and those working in HRM to provide tailored advice to support dairy farmers and other small business owners in managing their employees. [ABSTRACT FROM AUTHOR]

Making a living from a small farm is difficult in sub-Saharan Africa. In this paper, we quantify how difficult, using a simple, robust, relation between per capita daily income from farming (FPDI), land per capita and whole-farm net profitability per hectare. This relation allows the calculation of the land area required to generate various levels of household income as a function of farm performance. We use nationally representative household data for Tanzania to investigate the range of whole-farm profitability and to estimate an upper limit for it. For 6818 cases where households with land reported figures for gross crop and livestock revenues and for costs in any of the three years 2009, 2011 or 2013, actual median whole-farm net profitability was only $454/ha/y even without including the opportunity cost of family labour. When those were considered, median net profitability was negative $238/ha/y, i.e. a net loss. The maximum whole-farm profitability achieved was $4485/ha/y without family labour costs and $2742/ha/y with it. We evaluated actual and potential farm performance for their ability to generate a range of values of FPDI up to $10 per person per day. Most farms are not very profitable, particularly when household labour costs are considered, and few would be considered economically prosperous. Our analysis underscores the fact that improving their operations or adopting new technologies alone is unlikely to lift many smallholder farmers out of poverty in developing countries, given typical farm size distributions and reasonable assumptions about the realized economic returns to adoption of currently available agricultural technologies. While continued agricultural R&D investments are certainly worthwhile, such efforts alone will be insufficient to meaningfully address welfare needs of the world's rural poor. This suggests that agricultural development programs should expand their attention to incorporate off-farm and non-farm components of the rural economy. [ABSTRACT FROM AUTHOR]

Coffee is the foundation of Ethiopia’s economy with a quarter of the population dependent on coffee production and exports for livelihood. However, most empirical research in coffee production focuses on the productivity factors like yields rather than socio-economic factors that can significantly influence the level of coffee production. Thus, this essay explores the determinants of smallholders’ coffee production in Wolaita zone, Ethiopia by applying the ordered logistic regression model. This model estimates the coffee production status of smallholders by combining the effect of multiple productivity related biophysical and socio-economic factors. Using a multistage sample procedure, two farmers associations from each district were chosen for the research. Overall sample sizes of 250 households were interviewed door-to-door to generate quantitative data. Data was analyzed by using SPSS software and descriptive statistical techniques were applied in order to determine the coffee production status of the farm households. The results indicated that about 88.8% of the smallholder farm households fell under the yield category of ‘low producer’, which is an indicator that numerous variables provide challenges to the smallholder coffee production in the studied area. The results of the regression study showed that of the eighteen variables in the model, seven variables including irrigation access, pruning practice, household farm land size, training access, pesticide utilization, manure application, and cultivated land allocation were discovered to be the important predictors of farm families' coffee production status in the research region. It can be recommended that establishment of government sponsored irrigation systems, empowerment on utilization of appropriate coffee farm technologies and inputs for the areas, enhancing extension services to improve farmers’ skill and knowledge on coffee production system and risk alleviating mechanisms, developing soil fertility mechanisms, establishment of farmers training centers in the vicinities of producers, building capacity of institutions are vital to motivate coffee producers and increase productivity and coffee output in the research area and areas with similar situations. [ABSTRACT FROM AUTHOR]

Despite silvopastoral systems' environmental and production benefits, their adoption in forest ecosystems has been moderated. Identifying a silvopastoral farm typology combining farm size and management practices can help explore the constraints to their adoption and guide technical support initiatives. We investigated farms adopting silvopastoral systems in the Upper Atlantic Forest of Argentina and whether their management practices are related to the farms structural characteristics. We analysed 60 surveys that covered 3428 ha under silvopastoral management. First, we group the farms according to size and land use using the factor analysis mixed data and group with hierarchical clustering. Second, we performed two correspondence analyses with variables related to management practices in the silvopastoral area to explore the relationship between the practice management adopted and the cluster farm. Our results summarised the variability of farms and management practices in three groups: Specialist silvopastoral farms, Agricultural farms with silvopastoral management and forest plantation, and Livestock farms with silvopastoral management sectors. Specialist silvopastoral farms adopted most of the technical recommendations for this land use. Despite this work contributions, some information gaps still need to be addressed to have an integrated vision of how silvopastoral systems in the Upper Atlantic Forest of Argentina can be adopted in an extended manner. [ABSTRACT FROM AUTHOR]

Farm-level decision-making by resource-constrained smallholder farmers, such as investment in improved farm management practices and technologies may considerably be influenced by the age of farm operators. However, evidence of the effect of farm operators' age on farm efficiency and technological endowment, and consequently on agricultural productivity in sub-Saharan Africa has been inexact. To contribute to an improved understanding of the age-efficiency-productivity nexus, this study investigates the impacts of farm operators' age on agricultural productivity by evaluating the managerial performance and technological endowment of the operators, disaggregated across three age cohorts, viz. the youth, middle-aged and the aged. We fit the meta-stochastic frontier statistical framework to a country-wide sample of 24,596 farm households, spanning three decades of data collection in Ghana. The results show that relative to the potentials of each age cohort, more output can be generated using currently allocated inputs, but under improved farm management practices. Whereas we did not find evidence for possible age-related technological differences in agricultural production in Ghana, we did find strong support for possible age-induced managerial differences in farm production, with youth operators being more efficient than their middle-aged and aged peers. Consequently, the age of farm operators significantly affects agricultural productivity in Ghana through their efficiency of resource allocation. We find these results relevant for policy attention, in terms of the targeting of support to farm operators in the various age cohorts and in the country's quest to achieve greater agricultural productivity. [ABSTRACT FROM AUTHOR]