Search

Agriculture has a significant role in the wellbeing of the rural households of developing countries. Still, its productivity is very low in these countries due to the low use of mechanization at the farm level. In addition, extreme climate events and labor shortages at required intervals have made decisive pitch for the promotion and adoption of farm mechanization for ensuring sustainable farm performance and food security in developing countries. However, limited empirical evidence is available from Pakistan, about the adoption of farm mechanization and its impact on farm performance and food availability. Therefore, primary data were collected from 384 farmers from cotton–wheat cropping system of Punjab, Pakistan, by using a multi-stage sampling procedure. The endogenous switching regression (ESR) model was employed to estimate the determinants of farm mechanization adoption and their associated impacts on farmers' livelihood, measured by farm performance and food availability. The findings indicate that the adoption of full mechanization across all farming operations enhances overall farm performance and improves food availability. In addition, full mechanization leads to a substantial increase in farm performance by up to 55% and boosts food availability by approximately 125%. Our study demonstrates that the adoption of farm mechanization is strongly influenced by factors such as education, household size, landholding, off-farm employment, access to credit, and extension services. [ABSTRACT FROM AUTHOR]

Increasing farmers’ income is possible through high-value markets. Employment, access to financing, and technical support have favorable effects and a rise in income. This research seeks to establish the sustainability of organic cabbage farming through economic performance analysis. Quantitative research methods were conducted in this research. Descriptive quantitative analysis was performed with PLS-SEM software. The research data comprise primary data and secondary data. Of the 11 pathway coefficients in this study, only 9 were significant. The protection variable was positively related to the production optimization construct but did not significantly affect financial performance. The variable “healthy and safe” was positively associated with significant constructs of “financial performance” and “production optimization.” The variable “capacity development” was positively related to the constructs of “financial performance” and “production optimization.” The “technical” variable was significantly positively associated with the construct of “financial performance” but did not significantly affect the construct of “optimization of production.” The variable “production optimization” is positively related to the construct of “financial performance” and the construct of “farm performance” of farmers. Agricultural extension and training must be carried out to improve farmers’ technical knowledge. Government subsidies to support organic farming are also needed to ensure the sustainability of organic cabbage farming in the Semarang district.

The issue of productivity and performance in agriculture is significant because it affects a country's competitiveness, sustainability, and self-sufficiency in agricultural production and is reflected in European policy. This study aims to determine which country had the most efficient large farms compared to other V4 countries and whether efficiency in each country translates into the performance of large farms. The data were obtained from the EU FADN (Farm Accountancy Data Network) database from 2005 to 2019. These data were then evaluated using the statistical methods DEA: CCR-O (Data Envelopment Analysis: constant returns to scale), DEA: BCC-O (Data Envelopment Analysis: variable returns to scale), and Pearson correlation coefficient. Regarding international comparisons in achieving efficiency as measured by DEA, Hungary is the best performer among the countries compared, followed by Czechia, Poland, and Slovakia. The correlation between efficiency and performance measured by Farm Net Value Added was demonstrated only for Hungary. The international comparison provided information about which country had the most efficient large farms, what the ranking of countries was in terms of efficiency, and for which countries efficiency had / did not have a potential impact on performance. At the same time, the relationships regarding the efficiency and performance of farms with an economic size above EUR 500 000 of standard output were clarified.

The 2003 reform of the Common Agricultural Policy, which decoupled farm subsidies from production, was expected to increase farmers' market orientation and to positively impact farm productivity. This theoretical effect of decoupling on farm performance has been verified in a few ex-post analyses. However, these studies lack important aspects of farm-level policy impact evaluations. First, they do not use a well-defined counterfactual scenario, second they do not account for farm heterogeneity when measuring performance and third they do not assess farm performance in a comprehensive manner. We address these shortcomings by combining quasi-experimental empirical methods with a latent-class production function. Using UK and French farm-level data, we show that farms indeed operate with distinct production technologies and that decoupling had positive and significant effects on productivity. Our results further show that under decoupling, farmers tend to diversify their businesses while keeping environmental pressure at a similar level as with coupled support. [ABSTRACT FROM AUTHOR]

The issue of productivity and performance in agriculture is significant because it affects a country’s competitiveness, sustainability, and self-sufficiency in agricultural production and is reflected in European policy. This study aims to determine which country had the most efficient large farms compared to other V4 countries and whether efficiency in each country translates into the performance of large farms. The data were obtained from the EU FADN (Farm Accountancy Data Network) database from 2005 to 2019. These data were then evaluated using the statistical methods DEA: CCR-O (Data Envelopment Analysis: constant returns to scale), DEA: BCC-O (Data Envelopment Analysis: variable returns to scale), and Pearson correlation coefficient. Regarding international comparisons in achieving efficiency as measured by DEA, Hungary is the best performer among the countries compared, followed by Czechia, Poland, and Slovakia. The correlation between efficiency and performance measured by Farm Net Value Added was demonstrated only for Hungary. The international comparison provided information about which country had the most efficient large farms, what the ranking of countries was in terms of efficiency, and for which countries efficiency had / did not have a potential impact on performance. At the same time, the relationships regarding the efficiency and performance of farms with an economic size above EUR 500 000 of standard output were clarified. [ABSTRACT FROM AUTHOR]

Agriculture has a significant role in the wellbeing of the rural households of developing countries. Still, its productivity is very low in these countries due to the low use of mechanization at the farm level. In addition, extreme climate events and labor shortages at required intervals have made decisive pitch for the promotion and adoption of farm mechanization for ensuring sustainable farm performance and food security in developing countries. However, limited empirical evidence is available from Pakistan, about the adoption of farm mechanization and its impact on farm performance and food availability. Therefore, primary data were collected from 384 farmers from cotton–wheat cropping system of Punjab, Pakistan, by using a multi-stage sampling procedure. The endogenous switching regression (ESR) model was employed to estimate the determinants of farm mechanization adoption and their associated impacts on farmers’ livelihood, measured by farm performance and food availability. The findings indicate that the adoption of full mechanization across all farming operations enhances overall farm performance and improves food availability. In addition, full mechanization leads to a substantial increase in farm performance by up to 55% and boosts food availability by approximately 125%. Our study demonstrates that the adoption of farm mechanization is strongly influenced by factors such as education, household size, landholding, off-farm employment, access to credit, and extension services.

This study identified the determinants of cocoa farmers’ access to credit in Ghana and estimated the impact of credit access on yield, yield gap, gross income, cost of production, and net income using propensity score matching. A total of 384 cocoa-farming households were included in the analysis. Only 33.3% of cocoa farmers accessed credit for production and cooperative unions were the main source of credit accessed by the farmers. The study finds significant positive impacts of agricultural credit on yield, gross income, and net income, while yield gap decreases significantly (by 12.2–16.7%) with access to credit. Policy efforts to improve cocoa farmers’ access to credit could therefore enhance the productivity and profitability of cocoa production. It was found that male-headed households with access to credit derive greater benefits than their female counterparts. This may be attributed to differences in resource endowments and marginalization (between male and female heads). In addition, it was found that with access to credit, cultivating more than one cocoa farm could make cocoa production more productive and profitable. This indicates more efficient and profitable use of credit on fragmented farms, than on non-fragmented farms. However, under credit constraint, the practice of land fragmentation could be counterproductive.

The agricultural industry in Russia demonstrated a notable growth since 2010. Russian policymakers strive to further increase agricultural production and set new targets for the industry for the years ahead. While agroholdings are regarded as one of the main driving forces behind the recent success in the agricultural sector, they are also believed to be the main locomotive that will move agriculture towards the set goals. In spite of their growing importance, the literature on agroholdings is still relatively immature and fails to provide clear evidence of their financial efficiency as opposed to non-agroholding farms. The current study utilizes a manually sourced longitudinal dataset of 203 corporate farms in Russia and provides a new empirical evidence on the financial performance of agroholding farms through the prism of an agency problem. Our findings reveal a significant positive relationship between agroholding membership and financial performance, as indicated by two accounting indicators – return on assets (ROA) and return on sales (ROS). We further observe that agroholdings face lower agency costs, which to a certain extent, explain their higher financial performance compared to stand-alone farms. The study offers empirical recommendations for policymakers and corporate executives in the Russian agricultural sector.

Copyright of Journal of Indonesian Agribusiness / Jurnal Agribisnis Indonesia is the property of IPB University 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.)

ABSTRACT: Grass management technologies (grass measuring devices and grassland management decision support tools) have been identified as important tools to improve the performance of pasture-based dairy farms. They have the potential to significantly improve the efficiency and sustainability of dairy systems by increasing milk production through enhanced pasture growth and utilization, which would reduce the need for supplementary feeds, along with increased output, therefore increasing farm profitability and environmental sustainability. Despite the several potential benefits of grass management technologies, there is a lack of empirical research around the effects of these technologies on the performance of pasture-based dairy systems. The current study aimed to fill this knowledge gap by using a 2018 nationally representative survey of Irish dairy farms and a propensity score matching approach to determine the effects of adopting grass management technologies on the physical, environmental, and financial performance of Irish pasture-based dairy farms. The findings showed that dairy farms utilizing grass management technologies had, on average, higher farm physical, environmental, and financial performance (in terms of grazed pasture use, total pasture use, length of the grazing season, milk yield, milk solids, greenhouse gas emissions per kilogram of fat- and protein-corrected milk, gross output, and gross margin) compared with dairy farms not utilizing these technologies. However, when controlling for selection bias, we can only attribute a positive causal effect of grass management technology adoption on the use of grazed pasture per cow, grazing season length, milk yield per cow, and milk solids per cow. This might be due to dairy farmers not yet using the technologies to their full potential, 2018 being an unusual year in terms of weather (and therefore not being able to capture the full range of farm performance benefits), or because grass management technologies need to be adopted in association with other technologies and practices to achieve their expected performance outcomes. Future research should include updated farm-level data to capture the weather and learning effects and so be able to determine the impact of grass management technologies on a wider range of performance indicators.

This study identified the determinants of cocoa farmers' access to credit in Ghana and estimated the impact of credit access on yield, yield gap, gross income, cost of production, and net income using propensity score matching. A total of 384 cocoa-farming households were included in the analysis. Only 33.3% of cocoa farmers accessed credit for production and cooperative unions were the main source of credit accessed by the farmers. The study finds significant positive impacts of agricultural credit on yield, gross income, and net income, while yield gap decreases significantly (by 12.2–16.7%) with access to credit. Policy efforts to improve cocoa farmers' access to credit could therefore enhance the productivity and profitability of cocoa production. It was found that male-headed households with access to credit derive greater benefits than their female counterparts. This may be attributed to differences in resource endowments and marginalization (between male and female heads). In addition, it was found that with access to credit, cultivating more than one cocoa farm could make cocoa production more productive and profitable. This indicates more efficient and profitable use of credit on fragmented farms, than on non-fragmented farms. However, under credit constraint, the practice of land fragmentation could be counterproductive. Impact Statement: Through the generation of foreign exchange, creation of employment, and the provision of other environmental and health related benefits, cocoa can be classified as a gem among the major export commodities from Ghana. Despite the benefits the commodity offers to the Ghanaian economy, the cocoa subsector has been subjected to myriads of production related challenges (including aging trees, low soil fertility, low or limited adoption of productivity-enhancing inputs, challenges with post-harvest management, etc.), which have led to declining trend in cocoa production, rising production costs and decreasing farm income. Majority of these challenges have in recent research efforts been linked to credit constraints. While efforts have been made by previous and current governments to improve cocoa farmers access to credit and enhance the performance of the subsector, credit remains insufficient for cocoa farmers, and very little has so far been documented empirically on the impact of agricultural credit on cocoa production, especially in Ghana. This study addresses this gap by analyzing the determinants of cocoa farmers access to agricultural credit and the impact of agricultural credit on productivity (yield, yield gap, and gross income), cost and returns from cocoa production. The study also identifies and documents potential heterogeneity in impacts of agricultural credit on male and female headed households, and between farmers who operate on fragmented and non-fragmented lands, stressing on the need to consider the differences in impact between these two groups when implementing measures to enhance farmers access to credit and the impact on farm performance. Findings from this study could guide policy formulation, especially in targeting of farmers for agricultural credit and in the implementation of measures to address challenges in cocoa production. To farmers, this study could enlighten them on the benefits of operating on fragmented lands with improved access to credit, and the risk of operating on fragmented lands under credit constraint [ABSTRACT FROM AUTHOR]

This study aims to estimate eco-efficiency scores and identify determinants of Norwegian dairy farms using a parametric approach that accounts for methane emissions. The study incorporates an environmental output measure and draws on 30 years of panel data from 692 specialist dairy farms (1991-2020). The findings indicate that Norwegian dairy farms are inefficient, with room for improvement in the dairy production system and the environment. According to the average eco-efficiency score, conventional dairy farms could cut input use and CH4 emissions by 5% while maintaining output. Furthermore, the study found that land tenure, experience, and government subsidies all positively impact eco-efficiency. Policymakers should encourage the best-performing dairy farms to share information on increasing productivity while considering environmental concerns to achieve better social and agricultural development. It should be noted that the study only looks at livestock methane emissions; future research may investigate other environmental factors.

Agro-food quality certification has been gaining greater importance, because it contributes to both agricultural sustainability and food quality. However, small-scale farmers in developing countries have difficulties in obtaining certification and the economic benefits acquired from certification are unclear. This paper investigates the effects of agro-food quality certification on the farm performance which is indicated by profit, yield and price. The impacts of agricultural organizations, farmer cooperatives and agricultural companies in particular, on the adoption of certification by farmers are explored. We also investigate the effects of organizations on the farm performance of certified farmers. A dataset of 410 vegetable farmers in China is applied, and the propensity score matching (PSM) method is employed in the empirical analysis to address selection bias and reverse causality. Our study finds that, overall, the adoption of certification does not significantly influence farm performance. Cooperative membership positively influences the adoption of certification and the farm performance of certified farmers, while contract farming does not generate additional benefits for certified farmers.

In context of global challenges facing agriculture, our article addresses the extent to which the synergistic nature of agroecological innovations may reconcile environmental and technical efficiency of farms. We develop an empirical model, namely conditional efficiency framework, which explicitly accounts for context-dependent drivers like synergy and complementarity of innovations. Using a sample of 567 banana farms in the French West Indies, our estimates confirm the complementarity effect since the joint adoption of agroecological innovations increases the technical efficiency scores much more than other drivers and each of the innovations taken in isolation. We also show that advice and extension services as well as human capital variables are key adoption levers for public policy since they reduce the variability of production and thus the risk associated with the joint adoption of the agroecological innovations. [ABSTRACT FROM AUTHOR]

The Operational Groups (OGs) of the European Innovation Partnership for Agricultural Productivity and Sustainability (EIPAGRI) were introduced by the 2014-2020 Common Agricultural Policy to foster competitive and sustainable farming and forestry. The objective of this paper is to assess the economic and environmental impacts of participating in the EIP-AGRI OGs located in the Italian region of Emilia-Romagna. Performance of participants in OGs is compared with that of non-participants, who are selected by applying propensity score matching techniques to an Italian farm accountancy data network sample of 3204 farmers observed in the period 2017-2020. Logistic regressions are used to measure both propensity scores and the average treatment effect on the treated, while one-to-many optimal matching without replacement is adopted to form the control group. The resulting sample is composed of 270 observations, of which 45 are treated subjects. Results indicate that the OGs analysed might have contributed to improving fertiliser management and profitability levels in participating farms, but they failed to preserve biodiversity and reduce the consumption of pesticides and other inputs such as water, energy, and fuels. To increase the effectiveness of OGs, policy makers are advised to condition projects on the actual experimentation and implementation of agricultural innovations and apply a performance-based system of indicators for the assessment of the ex-ante and ex-post impacts of farm management. [ABSTRACT FROM AUTHOR]

The progress of agriculture is strongly influenced by the shortage of labor and land resources, leading to the transformation of modern agriculture into a highly mechanized and automated form. It has been observed that in recent years the use of intelligent agricultural machinery and agricultural robots has increased significantly in agricultural work. The research carried out aims to highlight the impact of farm equipment fleet monitoring systems on operational management on a farm. By analyzing the various monitoring systems available and evaluating them in terms of efficiency, productivity, and profitability, we can derive an appropriate strategy for the farm. Observation and analysis were the research methods applied to assess the impact of using monitoring systems. Thus, a series of data were monitored and interpreted concerning: agricultural work carried out by a machine, working time, area worked, fuel consumption, how the machine was operated by the mechaniser, etc. The results of the work showed that the implementation of a monitoring system can bring important benefits in cost and resource management, making this investment an efficient and sustainable solution for farmers. [ABSTRACT FROM AUTHOR]

This study aims to estimate eco-efficiency scores and identify determinants of Norwegian dairy farms using a parametric approach that accounts for methane emissions. The study incorporates an environmental output measure and draws on 30 years of panel data from 692 specialist dairy farms (1991–2020). The findings indicate that Norwegian dairy farms are inefficient, with room for improvement in the dairy production system and the environment. According to the average eco-efficiency score, conventional dairy farms could cut input use and CH4 emissions by 5% while maintaining output. Furthermore, the study found that land tenure, experience, and government subsidies all positively impact eco-efficiency. Policymakers should encourage the best-performing dairy farms to share information on increasing productivity while considering environmental concerns to achieve better social and agricultural development. It should be noted that the study only looks at livestock methane emissions; future research may investigate other environmental factors. [ABSTRACT FROM AUTHOR]

This study examines the impact of smartphone-based information acquisition on crop yields, net returns, return on investment (ROI), and production costs, using survey data collected from 558 wheat farmers in rural China. We employ a double-robust inverse probability weighted regression adjustment estimator to address the potential selection bias issue. The results reveal that information acquisition via smartphones significantly increases wheat yields, net returns, and ROI by 7%, 31%, and 39%, respectively, and it has a negative but insignificant impact on production costs. These results largely echo the results estimated from propensity score matching and endogenous switching regression models. In general, our findings suggest that policy interventions targeting to boost farm economic performance should consider distributing agricultural production and marketing information via smartphones. [ABSTRACT FROM AUTHOR]

This paper examines the role of improved sorghum variety adoption on smallholder farm performance and household welfare, measured by farm input expenditure, farm output, farm net returns, and household consumption expenditure per capita, using data from a household survey in Ghana's Upper East region. The study employed an endogenous treatment effects model, which addresses observable and unobservable selection biases associated with households' adoption decisions. The results reveal that improved sorghum variety adoption is significantly driven by government support, farm size, market distance, education, Farmer-Based Organization (FBO) membership, and household size. Moreover, gender, education, farm size, government support, FBO membership are the significant drivers of farm performance and household welfare among farm households. The results also show increased farm performance and better welfare associated with improved sorghum variety adoption. In particular, adopters incur 12.87% input expenditure, generate 6.95% farm output, 6.39% farm net returns, and 9.88% household consumption expenditure per capita, relative to non-adopters. Developing improved sorghum varieties and promoting uptake by farmers could enhance farm performance and improve rural livelihoods in Ghana.

Agro-food quality certification has been gaining greater importance, because it contributes to both agricultural sustainability and food quality. However, small-scale farmers in developing countries have difficulties in obtaining certification and the economic benefits acquired from certification are unclear. This paper investigates the effects of agro-food quality certification on the farm performance which is indicated by profit, yield and price. The impacts of agricultural organizations, farmer cooperatives and agricultural companies in particular, on the adoption of certification by farmers are explored. We also investigate the effects of organizations on the farm performance of certified farmers. A dataset of 410 vegetable farmers in China is applied, and the propensity score matching (PSM) method is employed in the empirical analysis to address selection bias and reverse causality. Our study finds that, overall, the adoption of certification does not significantly influence farm performance. Cooperative membership positively influences the adoption of certification and the farm performance of certified farmers, while contract farming does not generate additional benefits for certified farmers. [ABSTRACT FROM AUTHOR]

The focal point of this study was determining the effect of market orientation on farm performance as moderated by farmer resilience in the volatile dairy sector of an emerging country, Kenya. Using data from 682 respondents found in one of the vibrant dairy production counties in the country, Murang’a County, the study examined the interrelationships between market orientation, farmer resilience, and farm performance. Results from the analysis indicate a significant relationship between all the dimensions of market orientation (competitor orientation, customer orientation and inter-functional coordination) with both farmer resilience and farm performance with the exception of a non-significant relationship between customer orientation and farm performance. The significant relationship between inter-functional coordination and farm performance was the only one that displayed a negative correlation. The findings on the moderating effects of resilience on the market orientation-farm performance relationship report a positive significant effect. As this study represents the first effort to look into the linkages between the three concepts collectively, it provides important insight into the understanding the three concepts in the context of an emerging country.

Farm economic performance measuring is important for farm management purposes and for assessing the impact of agricultural policy measures. Efficiency studies enable assessment of farm performance since highly efficient farms are considered to have higher potential for operating in a changing economic and technological environment. The aim of this paper is to assess the technical efficiency of vegetable farms in North Macedonia, utilising Data Envelopment Analysis, as a non-parametric approach estimating the relative efficiency of decision making units producing multiple outputs and using multiple inputs. The analysis is based on Farm Monitoring System data including 75 vegetable farms in 2011 survey. Apart from baseline scenario, additional scenarios include available agricultural policy support in 2011 and 2016. The average technical efficiency of vegetable farms is 0.62 considering constant returns to scale, i.e. 0.71 and 0.75 considering variable returns to scale (in output and input oriented perspective, respectively). With better farm management, technical efficiency score can be improved on average by 25%. Technical efficiency increases slightly with subsidies, on average by 2 to 3%. Analyses based on farm level data, are valuable when estimating the effects of implementation of agricultural policy as well as when creating new policy interventions.

Most farms are struggling with aggravating economic, social and ecological conditions. If family farms want to survive in the long run, they need to develop innovation strategies. In line with the resource-based view, this paper argues that market orientation and multiple family generations in management are valuable resources of a family farm, which can contribute to innovation by facilitating the development of innovative ideas. This paper also explores the role of farm performance as a moderator. Since small- and medium-sized businesses in rural areas tend to lack growth orientation, it is assumed that family farms do not feel a strong urge to make use of their innovation potentials unless their performance falls to a critically low level. A regression analysis is conducted to test the relationships with a sample of 690 Austrian family farms. The results confirm the positive effect of both market orientation and multiple generations in management on innovation. As expected, farm performance moderates this relationship negatively. The findings are discussed against the backdrop of the family business, innovation and farming literature and suggestions are made how family farms can make best use of the market and the family as two important potential innovation sources. [ABSTRACT FROM AUTHOR]

South African government guided by the Restitution of Land Rights Act 22 of 1994, implemented land restitution as one of the pillars of land reform programme. The mandate was to promote land ownership and equality between white and black people. This study determined the extent to which farm beneficiaries are satisfied with the performance of the restituted farms in Waterberg District. Quantitative approach was used to examine closed-ended data using stratified random sampling procedure. Interviews, photo-voice and non-participatory observation methods were additionally used to collect data through qualitative approach. The Statistical Package for the Social Sciences (SPSS version 25) was used to compute descriptive statistics and cross-tabulations while content analysis was used for the qualitative data. The study revealed that participation in the restituted farms was dominated by males (73.0 %). About 77 % of the farm beneficiaries were not satisfied with the performance of the farms and 60.5 % of them confirmed that their livelihoods were not changed due to lack of farm income. Moreover, (90.3 %) reported that farms did not create job opportunities for beneficiaries. It is recommended that intervention strategy, be implemented to enhance farm performance that will satisfy farm beneficiaries.

The "Precoce MS" program, established by the Brazilian government in Mato Grosso do Sul in 2017, aims to encourage beef producers to harvest animals at younger ages to enhance carcass quality. About 40% of the beef produced in the state now comes from this program, which offers tax refunds ranging from 49% to 67% based on carcass classification and production system. Despite the program success, with participants delivering younger animals (with a maximum of 4 incisors), there remains significant variability in carcass quality. This paper investigates management practices and environmental factors affecting farm performance regarding carcass quality. Data from all animals harvested between the beginning of 2017 and the end of 2018 were analyzed, totaling 1,107 million animals from 1,470 farms. Farm performance was assessed based on the percentage of animals achieving grades "AAA" and "AA." Each batch of harvested cattle from each farm was categorized into two groups: high farm performance (HFP, with more than 50% of animals classified as "AAA" or "AA") and low farm performance (LFP, with less than 50% classified as such). A predictive logistic model was developed to forecast farm performance (FP) using 14 continuous and 15 discrete pre-selected variables. The most effective model, obtained through backward stepwise variable selection, had an R 2 of 0.18, accuracy of 71.5%, and AUC of 0.715. Key predictors included animal category, production system type, carcass weight, individual identification, traceability system, presence of a feed plant, location, and the Normalized Difference Vegetation Index (NDVI) from the 12-mo average before harvest. Developing predictive models of carcass quality by integrating data from commercial farms with other sources of information (animal, production system, and environment) can improve our understanding of production systems, optimize resource allocation, and advance sustainable animal production. Additionally, they offer valuable insights for designing and implementing better sectorial, social, and environmental policies by public administrations, not only in Brazil but also in other tropical and subtropical regions worldwide., Competing Interests: There are no potential conflicts of interest that may affect our ability to objectively present or review the research data here submitted., (Published by Oxford University Press for the American Society of Animal Science 2024.)

In this paper we utilize a nationwide dataset on plot-level rangeland health, which has not been used in previous studies on the economic impact of rangeland degradation in Mongolia. Taking account of typical reverse causality between grass condition and pastoralists' activities, we adopt a 2SLS instrumental variable approach to identify the impact of rangeland degradation on pastoralists' farm performance and welfare. We find that rangeland degradation causes a significant decrease in livestock product sales, farm income, and total paid-out costs. But we do not observe a significant decrease in farm profit and total income of the households. [ABSTRACT FROM AUTHOR]

A Bayesian non-neutral stochastic input distance function model is used to examine whether output specialization has an impact on the economic performance of vegetable producers in Benin. Specialization is assumed to have an effect on the production frontier itself, as well as on the distance of each producer's observed data to this frontier (technical efficiency). A derivative-based measure of economies of scope is obtained by exploiting the duality between the shadow cost and the input distance functions. In this study, we also control for spatial heterogeneity of vegetable production by including a soil fertility variable in the production function at the farm level. The technology is found to exhibit no economies of scope, indicating that vegetable producers have no incentive for specialization or diversification. However, the degree of specialization has a positive effect on technical efficiency. From a policy perspective, the findings imply that policies to encourage specialization may lead to higher performance.

Many previous studies that evaluated the impact of adaptation to climate change on poverty failed to assess how the gains from adaptation can be assessed from the multidimensional poverty perspective. In this study, survey data were used to examine the effect of adoption of adaptation strategies comprising irrigation, soil conservation, and enhanced cropping calendar management, on farm performance and multi-dimensional poverty index. Multinomial Endogenous Treatment Effect (METE) model which accounts for selectivity bias due to both observed and unobserved factors was employed. The results showed that a higher crop output and a greater reduction in downside risk exposure were associated with adoption of adaptation strategies as a package. The results further revealed that using all three strategies led to a significant reduction in multi-dimensional poverty among adapters. This suggests that adaptation is not only an ex-ante strategy against risk exposure, but an effective means of achieving the Sustainable Development Goals. It is therefore important for policy makers to consider the promotion of irrigation, soil conservation and cropping calendar management as effective strategies that could enhance farm performance and reduce household poverty. Intensifying extension and farmer education will also enhance adaptation to climate change. [ABSTRACT FROM AUTHOR]

Climate change is putting increasing pressure on agriculture, which might be reduced by paying more attention to risk management, production efficiency and farm investment. This paper describes the interrelationship between crop insurance take-up, technical efficiency and investment in Hungarian farming using a system of simultaneous equations. The empirical analysis is based on farm accountancy data for the period 2001-2019. Results suggest that both technical efficiency and investment have positive and significant effects on insurance take-up. Accordingly, higher technical efficiency and a higher investment rate both lead to increased insurance usage. In terms of its relationship with efficiency, insurance has a positive and significant coefficient, but investment does not have a significant influence on technical efficiency. Where investment is concerned, insurance usage has a positive and significant effect, but the role of technical efficiency is insignificant. Results suggest that policy interventions that stimulate any of the three factors can potentially have additional positive impacts through spill-over effects on other factors. These effects could be further enhanced if, for instance, interventions focusing primarily on insurance take-up also pay attention to investment by differentiating insurance premium subsidies, depending on whether there is an ongoing (or operating) investment that can be linked to weather-related risk management. [ABSTRACT FROM AUTHOR]

Land fragmentation (LF) is widespread worldwide and affects farmers' decision-making and, thus, farm performance. We used detailed household survey data at the crop level from ten provinces in China to construct four LF indicators and six farm performance indicators. We ran a set of regression models using OLS methods to analyse the relationship between LF and farm performance. The results showed that (1) LF increased the input of production material and labour costs; (2) LF reduced farmers' purchasing of mechanical services and the efficiency of ploughing; and (3) LF may increase technical efficiency (this result, however, was not sufficiently robust and had no effect on yield). Generally speaking, LF was negatively related to farm performance. To improve farm performance, it is recommended that decision-makers speed up land transfer and land consolidation, stabilise land property rights, establish land-transfer intermediary organisations and promote large-scale production. [ABSTRACT FROM AUTHOR]

This study aimed to analyze the glebagan system's effect on shallot farming performance in Central Java, Indonesia. The glebagan system is a yearly cropping rotation with plantation crops under the control of state-owned enterprises. This study employed economic production theory as the fundamental analysis. Brebes district was selected as the study site since the region is one of the centers of shallot production at the national level. Samples for the study were obtained from farmers who grew shallot in the glebagan and conventional systems, with a sample size of 100 for each group. The sample selection criteria include the farmers adopting the glebagan system for two years in technically irrigated lands in the peak season of shallot. The control group was selected based on the same seasons. Production function was employed to analyze the impact of the glebagan system. The results show that farmers growing shallots in the glebagan system gained many advantages. The production of shallot farming in the glebagan system was higher than that of its counterpart, and the system improved the productivity of the land. These findings imply that the glebagan system is functional and can be socialized with other farmers. The system can be modified to shallot and other horticultural crops. The study is novel regarding the analytical model that includes control variables to show the attributable impact of the glebagan system. [ABSTRACT FROM AUTHOR]

This paper compares the performance of conventional and organic fruit farms in Spain, using a set of base indicators to assess their economic and environmental performance on a per hectare basis. Composite indicators are also calculated to measure the overall economic and environmental performance of both production systems. Comparisons are made using propensity score matching to minimize the non-randomization biases caused by structural differences between the samples of conventional (n = 552) and organic (n = 127) fruit farms sourced from the Spanish Farm Accountancy Data Network (RECAN). The results based on per hectare metrics point to modest changes in the performance of farms that converted to organic farming. This is mainly because most converted farms were former conventional farms characterized by lower profitability and less intensive input use, consequently minimizing the effects of the conversion process. Nevertheless, the conversion outcomes exhibit a degree of variability depending on the specific type of fruit production. Economic gains are only discernible in the case of nut farms, whereas fruit and tropical fruit farms tend to yield the most favorable results per hectare from an environmental perspective. • Changes in per hectare performance are assessed when fruit farms convert to organic. • A complete set of economic and environmental base and composite indicators is used. • A matching procedure is implemented to obtain unbiased difference estimators. • Small changes are found in the per hectare performance of farms after conversion. • Mixed results depending on the type of fruit production subsector considered. [ABSTRACT FROM AUTHOR]

The effects of support policies on technical efficiency are not clear and are very complex because the results may be either positive or negative. The effects can be positive if the money received will serve as an incentive to innovate or to switch to new technologies or can have a negative effect if the money received increase the income of the farms and as a result prefer to have more leisure time. Given the theoretical uncertainty of the impact of supporting policies on efficiency, productivity and added value, the aim of this paper is to address this issue empirically. This paper contributes to the literature for the case of Kosovo by fulfilling the following objectives (i) to measure technical efficiency of farms in Kosovo and (ii) to identify the effect of subsidies by employing a stochastic output distance function and an inefficiency effect model as the one proposed by Battese and Coelli (1995). Parametric stochastic frontier approach was employed to estimate technical efficiency and to determine the effect of exogenous variables on technical efficiency through one-step approach. The share of total subsidies to total output (%) was used as proxy for policy variable and a set of farm characteristics as exogenous variables. We used FADN of Kosovo data provided by MAFRED for 2014. The results suggest that on average a farm in Kosovo produced 15.7% of the maximum output, while the rest of the potential output was lost due to technical inefficiency. Subsidies had negative effect on technical efficiency, however insignificant.

Farm economic performance measuring is important for farm management purposes and for assessing the impact of agricultural policy measures. Efficiency studies enable assessment of farm performance since highly efficient farms are considered to have higher potential for operating in a changing economic and technological environment. The aim of this paper is to assess the technical efficiency of vegetable farms in North Macedonia, utilising Data Envelopment Analysis, as a non-parametric approach estimating the relative efficiency of decision making units producing multiple outputs and using multiple inputs. The analysis is based on Farm Monitoring System data including 75 vegetable farms in 2011 survey. Apart from baseline scenario, additional scenarios include available agricultural policy support in 2011 and 2016. The average technical efficiency of vegetable farms is 0.62 considering constant returns to scale, i.e. 0.71 and 0.75 considering variable returns to scale (in output and input oriented perspective, respectively). With better farm management, technical efficiency score can be improved on average by 25%. Technical efficiency increases slightly with subsidies, on average by 2 to 3%. Analyses based on farm level data, are valuable when estimating the effects of implementation of agricultural policy as well as when creating new policy interventions. [ABSTRACT FROM AUTHOR]

Agroecological intensification (AEI) practices relying on on-farm diversity tend to close nutrient cycles and reduce dependency on external inputs in agricultural systems. These practices improve the productivity of banana-based systems in Uganda, but their extent of implementation differs between and within regions. However, the impact of AEI practices on a broader range of objectives including environmental and nutritional objectives, is hardly quantified. Additionally, recommendations to improve the farm performance, given these options, are lacking. We, therefore, analyzed the current farm performance for these broad range of objectives and explored optimal farm reconfigurations in two Ugandan districts, one in Central Uganda and one in Southwestern (SW) Uganda. Given the heterogeneity of smallholder farms, a farm typology based on the applied AEI practices was developed. It classified the subsistence farms in Central Uganda into two extreme groups with an average of 11.0 and 16.4 AEI practices applied per farm. Farms in SW Uganda were moderately intensified (i.e., 13.0 practices). The FarmDESIGN model revealed a higher species diversity, relatively higher profitability (2,039 – 3,270 $/ha/year) and nutritional yield on farms in Central Uganda. However, relatively high soil erosion levels (0.243 – 0.240) and negative nitrogen (N) balances (−72 to −50 kg N/ha/year) were indicative of unsustainable practices. In contrast, farms in SW Uganda were less diverse and more market oriented. Their commercial orientation allowed investments in soil fertility management, resulting in more sustainable [low soil erosion level (0.172) and positive N balance (5 kg/ha/year)], but less profitable (506 $/ha/year) systems. To improve farm performance, bananas and other perennials played a key role. Explorations with Calliandra calothyrsus (Calliandra) hedgerow or Mucuna pruriens (Mucuna) cover crop increased on-farm mulch production, improved sustainability indicators and profitability. We conclude that AEI practices can improve farm performance, and a more intensive use would be beneficial. In addition, the FarmDESIGN model provides a useful tool for redesigning these farms, proposing different redesigns depending on farmers' objectives (profitability, productivity or sustainability), and for evaluating ex ante the impact of new agricultural measures on farm performance.

The study investigates the perceptions of the effects and impacts on the performance of agricultural and livestock farms based on the view of obtaining dynamic capabilities by the adoption of enterprise resource planning (ERP) technology. The dimensions for measuring farmers' perceptions of ERP adoption were technological, organizational and environmental and their diffusion and the impacts measured on dynamic capabilities were on internal operations, costs, sales and natural resources. A total of 502 farmers directly involved in managing the production, located in the main agricultural areas of Brazil were interviewed. The results indicated that the perception of obtaining dynamic capabilities in the farms by adopting the ERP was significant, but with lower levels in costs and natural resources. The influence of farm size on ERP adoption and its perception on farm performance was not significant. The proposed model proved to be adequate and can be validated and compared with other producing regions. [ABSTRACT FROM AUTHOR]

Increased climate variability during the last four decades has made the agricultural environment in many developing countries more uncertain, resulting in increasing exposure to risk when producing crops. In this study, we use recent farm‐level data from Ghana to examine the drivers of individual and joint adoption of crop choice and soil and water conservation practices, and how adoption of these practices impacts on farm performance (crop revenue) and exposure to risks (skewness of crop yield). We employ a multinomial endogenous switching regression model to account for selectivity bias due to both observable and unobservable factors. The empirical results reveal that farmers' adoption of crop choice and soil and water conservation leads to higher crop revenues and reduced riskiness in crop production, with the largest impact on crop revenues coming from joint adoption. The findings also show that education of the household head, access to extension and weather information influence the likelihood of adopting these practices. Thus, enhancing extension services and access to climate information and irrigation can reduce gaps in adoption of soil and water conservation and crop choice, considered as climate‐smart practices that will eventually improve crop revenues and reduce farmers' exposure to climate‐related production risks. [ABSTRACT FROM AUTHOR]