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This study seeks to address factors affecting food availability in South Carolina counties. Using available U.S. Census data for 2002, 2007, 2012, and 2017, the study analyzes demographic and socioeconomic variables affecting food availability. Cross-section linear models are specified and estimated for each year using the heteroskedasticity consistent estimators developed by White (1980) and available in RATS (2020). The results reveal that a county’s farm income, harvested acres, agricultural productivity, and geographical location are major factors affecting food availability. The findings highlight the impact of geographical disparities in food availability and show that counties located further north in South Carolina have less food availability than counties situated in the southernmost part of the State. The results have implications for charity assistance and government food aid distribution. [ABSTRACT FROM AUTHOR]

Purpose: Agricultural production in Ethiopia is largely dependent on seasonal rainfall. This has made the agriculture-based economy of the country extremely vulnerable to the impacts of climatic change. To reduce this risk, the government has introduced strategies that promote irrigation as a key policy priority. Despite this, there has been limited empirical evidence on the impact of practicing small-scale irrigation on household income. This study was, therefore, conducted to examine the impact of access to small-scale irrigation on farm-household income in GannaBossa district, Ethiopia. Design/methodology/approach: A multistage stratified random sampling technique was adopted to select 289 study participants. The data were analysed using both descriptive and inferential data analysis techniques. Propensity score matching (PSM) and logit regression were applied to analyse the impact of irrigation utilization on farm households' income and identify factors influencing farm households' decisions about irrigation-utilization, respectively. Findings: The results of the study indicated that access to irrigation has a positive and significant impact on farm-household income. Estimates of the PSM model also confirmed that the mean income of irrigating households is significantly higher than that of non-irritating households. Further analysis of the results of the regression model revealed that amongst the hypothesized predictors of irrigation utilization, family size, soil fertility status, access to credit, access to extension services and access to the market were found to be positive and significant determinants of irrigation utilization, while distance to a water source was found to be a negative and significant predictor of irrigation utilization. Practical implications: The results of the study can inform development practitioners on how expanding access to irrigation can serve as one key driver in enhancing growth in agricultural productivity, increasing household income and contributing to the alleviation of rural poverty in areas with irregular rainfall and a high risk of drought. Originality/value: Given the country's irrigation potential and policy priorities, such empirical evidence informs decision-makers to make informed decisions regarding prioritizing irrigation interventions and expanding access and management in Ethiopia. [ABSTRACT FROM AUTHOR]

Climate-smart agriculture (CSA) addresses food security issues under climate change. The research examined the effect of adopting CSA practices on food and nutrition security by small-scale urban crop (SSUC) farmers in the eThekwini (ETH) Municipalityusing purposive sampling from 412 SSUC farmers. Results suggest that socio-demographic and institutional factors influence household consumption patterns and dietary status of SSUC farmers. The probit selection model show that the farmer's age, education, household size, off-farm income, monthly expenditure on food, agricultural training, group membership, and credit access significantly influenced CSA practices adoption decisions. The endogenous switching regression using marginal treatment effects shows that farm income, off-farm income, monthly expenditure on food, group membership, hired labour and distance to the farming site significantly affected household food consumption patterns. Gender, marital status, employment status, age, household size, farm and off-farm income, monthly expenditure on food, group membership, hired labour and number of part-time labourers from households significantly influenced the household dietary diversity status of SSUC farmers. The findings confirm heterogeneity in the effects of adopting CSA practices. Unobserved benefits are prevalent through a positive selection of CSA practices depicted by the Household Food Consumption Score (HFCS) and Household Dietary Diversity Score (HDDS). Adopting CSA practices enhanced the food and nutrition of SSCU farmers, shown by the average treatment effects (ATT) when farmers adopt CSA practices. Adopting CSA practices correlated positively with the food and nutrition security of SSUC farmers, with adopters being 16 and 31 percent more food secure concerning HFCS and HDDS, respectively. Hence, SSUC farmers in ETH Municipality adopting CSA practices were likely better off regarding food consumption patterns and dietary diversity. In light of this, a nexus between SSUC farmers, researchers, and extension services must consider suitable sets of CSA practices of relevant scale chosen and directed toward the welfare of localised contexts. [ABSTRACT FROM AUTHOR]

This study examines the impact of farm households' decision to adopt crop insurance and its effect on food security. Using the National Sample Survey Office's 77th round of data (2019–2020) from Indian farming households, the endogenous switching regression results confirm that insuring crops against production risks increases food security (as measured by higher consumption expenditures and net farm income). Specifically, findings show that farming households would decrease consumption expenditures by 15% and net farm income by 26% if they had not adopted crop insurance. Similarly, the noninsured families would have 23% higher consumption expenditures and 31% higher net farm income if they had insured crops. However, we find heterogeneity in welfare impacts because large farmers reap more benefits than smallholders. Policy implications from this study call for increased awareness of insurance programs, educating farmers about crop insurance schemes, and an effective institutional framework to reduce heterogeneity in insurance benefits. [EconLit Citations: Q13, Q18, O53]. [ABSTRACT FROM AUTHOR]

Even though small-scale irrigation (SSI) is a practical solution to address issues like poverty, food insecurity, and low farm production, its promise is often overlooked in Ethiopia. In the Demba Gofa District of southern Ethiopia, many rural households continued to rely primarily on rain-fed agriculture despite the possibility of irrigation. Therefore, the purpose of this study was to determine the factors that influence the adoption of SSI in Demba Gofa and its effect on farm income. A cross-sectional explanatory research design with a mixed-methods approach was employed on a total of 369 households selected through a multistage sampling procedure. An econometric data analysis using the propensity score matching model was employed to evaluate the effect of small-scale participation on households' farm income. The analysis revealed that the gender of the household head, cultivated land area, market accessibility, livestock ownership, and credit service accessibility positively affect irrigation adoption. Households' irrigation adoption was negatively and significantly associated with the age of the household head and the distance of the farm from the irrigation site. Furthermore, households that did not adopt small-scale irrigation schemes lost 4831.77 ETB in farm revenue compared to those that did. Thus, the study advises the government to support the establishment of adequate, long canals and government-guaranteed credit services for smallholder farmers in order to boost household income and, consequently, food security. Agricultural agents ought to conduct routine evaluations of the canals' operation and offer farmers training to enhance their skills in the sustainable use of irrigation systems. [ABSTRACT FROM AUTHOR]

This paper explore the impacts and mechanisms of digital literacy of farm households on income. The baseline regression of the impact of digital literacy of farm households on household income uses a fixed effects regression model, and the 2SLS regression model is used to address the endogeneity problem present in the model. The findings reveal that improving digital literacy among rural households significantly increases their family income, a result that remains robust even after considering endogeneity issues. Further examination of the mechanisms shows that enhancing digital literacy among rural households significantly improves their information acquisition capabilities and cognitive skills. It also deepens financial services, boosting the usage and engagement of rural households in digital financial activities, thereby enhancing family income levels. Facilitating rural residents' access to digital skills and tools to ride the digital economic wave, ensuring fair access, and achieving sustainable family income are of paramount significance for rural revitalization. It is also a crucial step in bridging the digital divide and promoting shared prosperity. [ABSTRACT FROM AUTHOR]

Background: Little gourd is important vegetable crop that provide a considerable amount of income to farm families in Central Gujarat. The present investigation was undertaken with the goal to study the cost and return in cultivation of little gourd in central Gujarat. Methods: For this purpose, primary data was collected from 120 little guard farmers from three districts namely Anand, Kheda and Vadodara and categorized according to size of holding as marginal, small, medium and large farms. To arrive at conclusion the data was analyzed with cost concepts and relevant income measures. Result: The study found that the average per hectare cost of cultivation, gross income and net income of little gourd followed an increasing pattern from marginal to large farm sizes. The input output ratio was found decreasing as the farm size increased. The study suggested that there is enough scope of enhancing net returns through increasing the scale of operations at farm level that may be achieved by organizing small and medium farmers into producer organizations. Over and above this, the farmers should be encouraged for production of export-oriented quality to further increase the farm income. [ABSTRACT FROM AUTHOR]

(a) Introduction: Zambia's poultry industry comprises commercial chickens and small-scale producers of indigenous chickens (Gallus domesticus) (ICs). Large, integrated entities run the commercial chicken sector, while the indigenous chicken sector (IC sector) is predominantly run by small-scale farmers (SSFs). Increased costs and low access to formal markets for commercial chickens have motivated SSFs to enter the IC sector under the free-range system (FRS) and semi-intensive system (SIS). (b) Objective: This study aimed to highlight the price changes in poultry inputs and outputs and demonstrate that the IC sector has more potential to contribute to farm income than commercial chickens under family poultry production systems. (c) Method: We analysed the prices for inputs and outputs for Zambia's poultry industry for the first quarter of 2016 to 2023 using data from the Poultry Association of Zambia (PAZ). We also analysed data from the 2021 Qualtrics survey to investigate the crops grown and crops used as feed and feed ingredients, the sources of feed, and the use of minerals and vitamins by SSFs for chickens. The gross profit (GP) and benefit–cost ratio (BCR) were analysed to compare the viability and profitability of ICs and broilers under SSFs. (d) Results: Our study shows that prices for day-old chicks (DOCs) and point-of-lay (POL) pullets increased by 57–125%, broiler and layer feeds increased by 67–96%, and soybean meal (SBM) and fishmeal rose by 143–229%. Prices for live ICs, commercial broilers, and ex-layers increased by 150%, 79%, and 71%, respectively. Egg prices rose by 100–124%. Farmers tried to look for local feed sources. Over 21% of the crops grown was maize, and nearly 43% was used for feed. (e) Conclusion: Our analysis and comparison between the ICs and broilers demonstrated that SSFs could achieve more farm income by producing ICs than commercial broilers. [ABSTRACT FROM AUTHOR]

The paper aims to determine which factors influenced the level of farm income for small-scale farmers in Gauteng Province during the lockdown period. Simple random sampling was used to collect data from 132 small-scale farmers using an online survey between January and February 2023. The Ordinary Least Square model (OLS) was used to analyse the data. The results showed that the farmer's age, level of education, non-farm income, number of farm workers employed, farming experience and lockdown influenced the level of farm income. In contrast, lack of funding negatively influenced the level of farm income. By improving the level of education and providing specialised training on modern farming techniques and farm management, farmers can enhance their productivity and efficiency. In addition, to enhance the overall farm income, it is recommended that non-farm income opportunities be promoted and supported as they have been shown to positively influence the level of farm income. Governments and financial institutions should also work together to create and expand funding opportunities for small-scale farmers, such as low-interest loans, grants, and subsidies. [ABSTRACT FROM AUTHOR]

The study assesses the profitability of Karoo farms. It develops an enterprise wool and mutton production budget from eight years of survey data collected from 73 farms. Costs are presented in constant 2019 Rand so that data from various years can be pooled. According to income composition, farms were classified into mutton, wool or mixed mutton-wool operations. Mutton and mixed farms run similar-sized flocks on similar-sized properties, while wool farms operate larger flocks on more land. Mutton producers stock their land 15% less densely than wool or mixed farms, which use the same stocking density. At R80.89 per hectare, the small stock enterprise on mixed farms is approximately 40% more expensive to operate than the unit cost of production on mutton or wool farms, which are similar. Wool farms generate the best perhectare incomes, 48% higher than the unit income of livestock on mixed farms and 62% higher than the per-hectare income on mutton farms. Net farm income is presented and discussed, and profitability is related to rainfall. [ABSTRACT FROM AUTHOR]

Italy is divided into 773 Agricultural Regions (ARs) based on shared physical and agronomic characteristics. These regions offer a valuable tool for analyzing various geographical, socio-economic, and environmental aspects of agriculture, including the climate. However, the ARs have lacked geospatial data, limiting their analytical potential. This study introduces the "Italian ARs Dataset", a georeferenced shapefile defining the boundaries of each AR. This dataset facilitates geographical assessments of Italy's complex agricultural sector. It also unlocks the potential for integrating AR data with other datasets like the Farm Accounting Data Network (FADN) dataset, in Italy represented by the Rete di Informazione Contabile Agricola (RICA), which samples hundreds of thousands of farms annually. To demonstrate the dataset's utility, a large sample of RICA data encompassing 179 irrigated crops from 2011 to 2021, covering all of Italy, was retrieved. Validation confirmed successful assignment of all ARs present in the RICA sample to the corresponding shapefile. Additionally, to encourage the use of the ARs Dataset with gridded data, different spatial-scale resolutions are tested to identify a suitable threshold. The minimal spatial scale identified is 0.11 degrees, a commonly adopted scale by several climate datasets within the EURO-CORDEX and COPERNICUS programs. Dataset: The Italian ARs Dataset— https://doi.org/10.5281/zenodo.11446949. Dataset License: Creative Commons Attribution 4.0 International license (CC BY 4.0). [ABSTRACT FROM AUTHOR]

The main aim of the article is to determine the level and variability of income obtained on EU farms, classified according to the FADN methodology into eight agricultural types, and the share of subsidies for operational activities in the income obtained. The analysis covers the variability of the total number of farms in the EU keeping FADN accounting, their structure, and the level of income obtained in individual types of farming from 2004 to 2022. Absolute and relative increases were used to determine changes in the total number of farms. They showed that from 2004 to 2022, number of farms under FADN observation field decreased by 36%. The next step was to analyze the level of income obtained from the farm. The highest level of income in the examined period was recorded by farms specialized in the breeding of granivores. Then, the average value for a given year, standard deviation, and coefficient of variation were used to assess the level and variability of income in individual agricultural types. From 2004 to 2022, farms specialized in rearing and breeding granivores and mixed farms were characterized by strong variability in the income obtained from a family farm between 2004 and 2022. Average variability in the level of income was observed on farms specialized in rearing and breeding other grazing livestock, which also had the highest share of subsidies for operating activities. [ABSTRACT FROM AUTHOR]

This study analyzed the impact of income diversification on agricultural output in Indonesia. We specifically focused on the effects of the cultivation of multiple crops, household heads’ employment in non-agricultural sectors, and regional differences in paddy rice productivity per area. We assessed cross-sectional data from the 2013 Census of Agriculture in Indonesia. Indonesian farmers actively channeled wage income into spending on agricultural inputs to improve yields. However, agricultural production continued to depend on human labor, and labor force loss due to wage labor employment was observed. In terms of magnitude, the effect of productivity gains due to labor force loss was larger and was not compensated for by the impact of wage income. Also, while the Indonesian government has been focusing on policies for subsidizing fertilizer use, the data show that less than 30 percent of households receive government subsidies for seeds, fertilizers, and machinery. These utilization rates should be improved. [ABSTRACT FROM AUTHOR]

The main aim of the article is to determine the level and variability of income obtained on EU farms, classified according to the FADN methodology into eight agricultural types, and the share of subsidies for operational activities in the income obtained. The analysis covers the variability of the total number of farms in the EU keeping FADN accounting, their structure, and the level of income obtained in individual types of farming from 2004 to 2022. Absolute and relative increases were used to determine changes in the total number of farms. They showed that from 2004 to 2022, number of farms under FADN observation field decreased by 36%. The next step was to analyze the level of income obtained from the farm. The highest level of income in the examined period was recorded by farms specialized in the breeding of granivores. Then, the average value for a given year, standard deviation, and coefficient of variation were used to assess the level and variability of income in individual agricultural types. From 2004 to 2022, farms specialized in rearing and breeding granivores and mixed farms were characterized by strong variability in the income obtained from a family farm between 2004 and 2022. Average variability in the level of income was observed on farms specialized in rearing and breeding other grazing livestock, which also had the highest share of subsidies for operating activities.

Purpose: Fish farmers in Africa often operate on small-scale culture units, primarily due to poor access to funding and low technology adoption. Digital innovation platforms seek to enhance farmers' access to finance, production and farmers' income. However, there is a lack of empirical evidence to support these claims. Therefore, this study investigated the factors influencing fish farmers' access to microcredit from digital innovation platforms and the impact of this microcredit on fish farms' yield and income in Nigeria. Design/methodology/approach: A mixed-methods approach was adopted, and data were gathered from 387 fish farmers through a well-structured questionnaire and focus group discussion. The data were analyzed using probit regression and instrumental variable two-stage least squares regression. Findings: The results revealed that ownership of smartphones, awareness of digital agricultural innovation platforms, farmers' education, income, fish farming as a primary occupation, cooperative society and extension contacts positively influenced farmers' access to microcredit from digital innovation platforms. The age of farmers and household size negatively influenced their access to digital microcredit. Digital microcredit positively and significantly impacted fish farms' yield and farmers' income. Practical implications: Digital microcredit significantly increased fish farm yield and income. Therefore, digital innovation platforms should be encouraged and promoted through the creation of awareness about their ability to solve inadequate financing in agriculture by agricultural extension agents. Originality/value: This study contributes to our understanding of the influencing factors for farmers accessing digital microcredit and how digital microcredit enhances farm yield and income. [ABSTRACT FROM AUTHOR]

The issue of ensuring food and nutrition security has become a prominent item on the global agenda, particularly for low-income countries with high population growth rates. Despite the implementation of numerous policies and programs with the objective of enhancing household calorie intake, food insecurity is worsening in Ethiopia. It is crucial to comprehend the principal factors influencing food security, as this knowledge is essential for implementing effective interventions to enhance food security. Therefore, this study aimed to estimate the food security status of households, measure the extent and severity of food insecurity, and identify the determinants of food security in Northeastern Ethiopia. The data for this study were collected through key informant interviews, focus group discussions, and a multi-stage sampling method, which involved the selection of 300 households. Descriptive and inferential statistics, the Foster–Greer–Thorbecke (FGT) index, and a probit model were employed to analyze the collected data. The results indicate that 41.67% of the sample households were food secure. By decomposing the results to the two land use systems, 34.62% and 50.69% of the pastoral and agro-pastoral households were food secure, respectively, indicating that agro-pastoral households were relatively more food secure than pastoral counterparts. Furthermore, the gap and severity of food insecurity among the sample households were calculated using FGT indices, resulting in a value of 15.02% and 5.31%, respectively. The probit model revealed that educational attainment, the number of milking cows, cultivated farm size, annual farm income, and participation in off-farm activities were significant predictors of improved household food security status. The findings of this study suggest that policies aimed at addressing food insecurity should consider livelihood diversification, the promotion of education and training, and the strengthening of institutional and technological environments. [ABSTRACT FROM AUTHOR]

The United Nations Sustainable Development Goals emphasize the dangers of inequality and initiatives on how to reduce it. Income inequality is an important part of this and can cause many social problems. This study aims to investigate the impact of land transfer on income inequality of Chinese farm households and its mechanism of action. This study empirically analyzes the impact of land transfer on farm household income inequality based on the OLS model using 27,134 samples from the 2018–2020 China Family Panel Study (CFPS) data. The study finds that land transfer can effectively reduce income inequality among farm households. However, only land transfers out affect income inequality; the effect of land transfers in is not significant. At the same time, there is some heterogeneity in the impact of land transfers on farm household income inequality. The effect is greater in the east and west than in the center. The effect is greater in the north than in the south. The role is greater in food-producing areas than in non-food-producing areas. Mechanism testing shows that land transfer impacts income inequality among farm households by promoting entrepreneurship. Farm households who use the Internet and have stronger social capital gain more from the impact of land transfer on income inequality. [ABSTRACT FROM AUTHOR]

Using farm machinery plays a significant role in easing the issue of slowing growth of operating income among farm households in China. Drawing data from CFPS2018, this study adopts a multinomial endogenous switching regression (MESR) to analyze the factors influencing farm households' choices regarding self-owned farm machinery and outsourced machinery services, as well as their subsequent impact on operating income. The results of the study show that the characteristics of the head of household, family, village, and region have a significant impact on the farm households' selection of whether to use self-owned machinery or outsourced services. Furthermore, the exclusive use of self-owned farm machinery and the combined use of both self-owned and outsourced machinery substantially enhance farm households' operating income. An additional analysis indicates that these two types of machinery are complementary, and their combined use generates a superimposed effect that further boosts income. These findings suggest that the combined use of self-owned and outsourced machinery is optimal for farm households who wish to expand their operating income. [ABSTRACT FROM AUTHOR]

Spatial modelling approaches to aid land‐use decisions which benefit both wildlife and humans are often limited to the comparison of pre‐determined landscape scenarios, which may not reflect the true optimum landscape for any end‐user. Furthermore, the needs of wildlife are often under‐represented when considered alongside human financial interests in these approaches.We develop a method of addressing these gaps using a case‐study of wild bees in the UK, an important group whose declines may adversely affect both human economies and surrounding ecosystems. By combining the genetic algorithm NSGA‐II with a process‐based pollinator model which simulates bee foraging and population dynamics, Poll4pop, we 'evolve' a typical UK agricultural landscape to identify optimum land cover configurations for three different guilds of wild bee. These configurations are compared to those resulting from optimisations for farm income alone, as well as optimisations that seek a compromise between bee populations and farm income objectives.We find that the land cover proportions in landscapes optimised for each bee guild reflect their nesting habitat preferences rather than foraging preferences, highlighting a limiting resource within the study landscape. The spatially explicit nature of these optimised landscapes illustrates how improvement for a given target species may be limited by differences between their movement range and the scale of the units being improved. Land cover composition and configuration differ significantly in landscapes optimised for farm income and bee population growth simultaneously and illustrate how human agents are required to compromise much more when the multifaceted nature of biodiversity is recognised and represented by multiple objectives within an optimisation framework. Our methods provide a way to quantify the extent to which real‐life landscapes promote or compromise objectives for different landscape end‐users.Our investigation suggests that optimisation set‐up (decision‐unit scales, traditional choice of a single biodiversity metric) can bias outcomes towards human‐centric solutions. It also demonstrates the importance of representing the individual requirements of different actors with different landscape‐level needs when using genetic algorithms to support biodiversity‐inclusive decision‐making in multi‐functional landscapes. [ABSTRACT FROM AUTHOR]

Farmland transfer-out is essentially a process of the rural land resource allocation, and it is also of great importance to farmers' poverty alleviation. The practice of farmland transfer-out in China is generally manifested as farmland expropriation and farmland lease. Based on the survey data of 832 poverty counties in China, this paper empirically analyzed the effects of farmland lease and expropriation on poverty alleviation. The results showed that farmland expropriation and lease in poverty areas could increase farmers' household income and poverty alleviation, and this conclusion was still valid after instrumental variable estimation and robustness test. Moreover, farmland expropriation significantly promoted the growth of entrepreneurship income and the decrease of farm income, but did not significantly impact non-farm income. However, farmland lease significantly promoted the growth of entrepreneurial income and non-farm income, but was negatively correlated with farm income. It should be noted that farmers' entrepreneurship strengthened the positive role of farmland expropriation on poverty alleviation, while it did not play a significant role in the relationship between farmland lease and poverty alleviation. Further research showed that the farmland expropriation and lease in poverty areas improved individual well-being through poverty alleviation, and the farmers' entrepreneurship in poverty areas strengthened this positive effect. This study provides empirical evidence for farmers in poverty areas to achieve poverty alleviation and improve individual subjective well-being through farmland transfer-out. [ABSTRACT FROM AUTHOR]

A three-year multi-location trial on the farmer's field was conducted in West Bengal, India to evaluate the impact of integrated nutrient management (INM) on the performance of kharif rice cv. Swarna Sub 1. The experiment employed a randomized block design (RBD) across eleven farmers' fields with similar soil properties, texture, topography, and historical fertilizer application patterns. Three treatments were tested: T1 – common practice of applying N:P:K @ 55:32:27 kg ha−1, T2 – soil test-based application (STA) of ∼75% recommended N dose through chemical fertilizer + ∼ 25% through Azolla, and T3 – soil test-based application of ∼ 75% recommended N dose through chemical fertilizer + 20% N from vermi-compost + 5% N through Azolla. The result of the experiment revealed that the T3 exhibited significant improvements in plant height, leaf area index (LAI), effective tillers meter−2, number of panicles plant−1, and 1000-grain weight compared to T2 and T1. Among the different nutrient management practices, the T3 recorded maximum rice grain productivity than the T1, and T2, Further, the benefit-cost ratio was noticed significantly higher under T3 (1.29) followed by T2 (1.27) and T1 (1.23). The soil organic carbon (SOC), available nutrient was enhanced by the soil test-based application of ∼75% recommended N dose through chemical fertilizer + 20% N from vermicompost + 5% N through Azolla. Thus, our study indicated that the balanced nutrient application through combined sources (T3) could improve crop growth; and sustain rice productivity, besides enhancing the farm income, and soil different soil properties. [ABSTRACT FROM AUTHOR]

Livelihood diversification (LD) is crucial for rural households due to increasing climate variability and declining farm incomes in the global south. Literature has extensively documented the benefits of LD in emerging economies. However, there is still a gap in the econometric evidence of LD on the food security of rural households in Ghana. This study addresses this gap by examining the factors that influence LD using the Ghana Living Standards Survey (GLSS 7) data collected from 133 rural households in Northern Ghana. Results from the censored Tobit regression model, multiple linear regression, and Simpson Diversification Index (SDI) indicated that diversification averaged 0.313 and ranged from 0.000 to 0.709 (zero to 70.9%). Total food expenditures (TFE) measured as a proxy of food security declined at low levels of diversification. Beyond the diversification level of 0.480, total food expenditure increased steadily. The findings revealed that only 24.6% of the households had diversification scores higher than the turning point of 0.480. The Tobit model also showed that remittance income, technical education, household size, marital status, access to extension services, and ownership of mobile phones were significant drivers of LD. The findings have demonstrated that LD improves food security in rural Ghana. [ABSTRACT FROM AUTHOR]

The study focused on investment, profitability, and input–output specific technical and scale efficiencies and suggested appropriately for its sustainable development in Andhra Pradesh. Farmers (n = 60) were interviewed, and data were analyzed using descriptive statistics, B-C ratio, C-D production function, and DEA techniques. The results depicted that majority of the farmers' primary occupation was aquaculture and 53% of them were farming on leased land. Yield (kg/ha) was highest for large farmers (5247 kg) followed by medium (5200 kg) and small farmers (4800 kg) which resulted the net incomes of $8771 for large farmers, medium ($7377), and small farmers ($6186). The share of feed cost and medicine cost was higher for large farmers, while feed and other costs were highest for medium and small farmers. Net returns were found to be proportional to the land holdings, while labor days have a negative effect. Inefficiency scores given by the DEA model suggest farmers were able to produce the same level of output with combination of inputs corresponding to the minimum cost of production. Adoption of scientific farming practices and CAA guidelines may ensure sustainable farm income. The DoF, AP has to frame policies for the promotion and monitoring of inland low-saline shrimp culture for the mutual benefit of all stakeholders. [ABSTRACT FROM AUTHOR]

The payment for ecosystem services (PES) scheme shows great poverty alleviation potential and recognizing this connection contributes to enhancing the development of residents in ecologically endowed areas. However, the literature has not clarified the extent of the promotion and moderating factors of PES on income yet. This study pursues the goal of identifying the effect of PES on household income in rural China from the income structure perspective. Methodologically, this research conducts a literature review of 28 papers to outline the effect of PES on agricultural production, off-farm, and total income, and it applies a meta-analysis and meta-regression analysis of 13 papers to identify the influencing degree and interference factors. The findings reveal four issues. Overall, the effect of PES on agricultural production income was negative, while the effect on off-farm and total income was positive. Second, the PES schemes boosted farm household income by 0.15 weighted average effect size. Third, farm household participation area, subsidized unit prices, and urbanization level played positive moderating effects, while farm household age was a negative moderating variable. Lastly, PES risk exacerbated income inequality among farm households. The study also integrates the PES and the SDGs, proposing that advancing climate action involves the assistance of sustainable communities, decent work, and protection from conflict with social equity. Finally, the paper provides recommendations in terms of government-led PES projects that should be inclusive of economic, social, and ecological objectives, provide job security for smallholders, and quality urbanization. Plain language summary: A systematic review of empirical research on PES and farm household income in China The purpose is that clarifying the extent of the promotion and moderating factors of PES on income well. The methods are that literature search plus meta-analysis. The findings reveal four issues. Overall, the effect of PES on agricultural production income was negative, while the effect on off-farm and total income was positive. Second, the PES schemes boosted farm household income by 0.15 weighted average effect size. Third, farm household participation area, subsidized unit prices, and urbanization level played positive moderating effects, while farm household age was a negative moderating variable. Lastly, PES risk exacerbated income inequality among farm households. Moreover, the study discusses the role of PES in SDGs. Finally, this paper provides advice for balancing the eco-social objectives of the PES project and promoting high quality urbanization. [ABSTRACT FROM AUTHOR]

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The paper applies the farm accountancy data network (FADN) approach to conduct a comparison analysis of the revenue of EU fruit producers. The study constitutes a significant contribution to the requisite development of more accurate metrics and appropriate approaches, which are necessary for assessing the economic success of EU fruit production in the principal sector of EU agriculture. The metrics used to measure the economic success in fruit production include farm net value added (FNVA), farm net income (FNI), annual working unit (AWU) of FNVA, and farm family income (FFI/FWU). An agricultural farm's overall productivity can be determined by dividing its entire output (production) by the inputs employed in its operations, such as specific expenses and intermediate consumption. The FADN approach, which tracks the increase in agricultural revenue and assesses the effects of European policies on the agricultural sector, improves monitoring and meeting of performance goals. Finding economic, technological, and other aspects that will improve agricultural farms' businesses and, by extension, agriculture as a whole will require applying an appropriate methodological approach to portray the actual situation and results of these farms. [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]

The Purdue Improved Crop Storage (PICS) bag, a sustainable post‐harvest storage technology, can address the high postharvest losses that are a major threat to economic development, food security and the environment in Africa. However, there is limited empirical research on this technology. This study therefore aims to fill this knowledge gap by analysing the factors influencing the diffusion and adoption rates of PICS bags and estimates the impact of the technology adoption on postharvest losses, farm income and income inequality in the Ashanti region of Ghana. The results show that less than 20% of farmers adopt the PICS bag, suggesting low adoption despite the widespread exposure of 51.75%. The technology adoption rate could be increased by 20% if all the farmers were exposed to it. It reduces postharvest losses by 14.2%–19.1%, increases farm income by 89.7%–91.2% and reduces income inequality by 51.33%. These findings suggest that promoting the technology can stimulate sustainable rural development by improving farmers' welfare. [ABSTRACT FROM AUTHOR]

Context: The reduced utilisation of inputs in milk production holds significant importance from both sustainability and profitability perspectives. Aim: This study examines the efficiencies of each input separately utilised in specialised milk farms across the European Union (EU) countries and explores the factors that influence input efficiencies by using non-radial data envelopment analysis (DEA) model with Russell measure method. Methods: Data from the dairy report of the EU milk-specialised farms compiled by the European Commission (EC) and the Farm Accountancy Data Network (FADN) covering the period from 2013 to 2020 were analysed. The study employed a DEA model to assess efficiency, with a focus on energy, labour, dairy cows, homegrown feed, purchased feed, and operating costs. Key results: Ireland, Italy, Malta, and the Netherlands demonstrated full efficiency across various aspects of milk production, highlighting their exemplary performance in resource utilisation within the EU. Furthermore, the study identified significant potential for efficiency improvements across the EU countries, with potential reductions ranging from 48.8% to 65.616% in various input usage categories. Conclusions: The analysis underscored the importance of improving input efficiency to enhance competitiveness in the dairy sector. Implications: As milk prices and economic performance improve, specialised milk farms tend to become more efficient in managing operating expenses. However, expanding the land area for forage may lead to diminishing returns in resource efficiency, indicating complex interactions and trade-offs affecting input efficiency. Understanding input efficiency in specialised milk farming is crucial for enhancing sustainability and productivity in the European Union (EU) dairy sector. This study addressed the problem of inefficient resource utilisation in EU milk farming, discovering that countries such as Ireland and the Netherlands achieve full efficiency, whereas others have significant potential for improvement. The findings indicated that improving resource efficiency can lead to significant cost savings, environmental benefits, and increased competitiveness within the dairy industry. [ABSTRACT FROM AUTHOR]

Using primary data collected from 389 sample households in Dangla district, Amhara region of Ethiopia, this study examined smallholder farmers' willingness to pay for ZM-GrowTM foliar fertiliser. The study employed the Tobit model to estimate the determinants of the maximum willingness to pay and a seemingly unrelated bivariate probit model to estimate the mean willingness to pay for foliar fertiliser. The results of the Tobit regression model showed that the education level of the farm household, total annual income, access to credit service, access to agricultural extension service, perception about fertiliser, and cost of the existing fertiliser have a positive and significant effect on farm households' willingness to pay. On the other hand, the age of farm households, availability of labour, and initial bid price have negative and significant effect on farm households' willingness to pay for ZM-GrowTM foliar fertiliser. The mean willingness to pay for ZM-GrowTM foliar fertiliser, estimated using the seemingly unrelated bivariate probit model, was 121.16 birr/litre (2.75 USD/litre). The corresponding mean willingness to pay amount estimated from an open-ended format was 161.105 Birr/litre (3.65 USD/litre). The results suggest that foliar fertilisers could be good alternatives to the existing fertilisers and its adoption can be further facilitated through improved access to knowledge and finance/credit. [ABSTRACT FROM AUTHOR]

The water use practices in Menz Mama Midir woreda are very traditional and inefficient. To lessen this problem, water pricing (valuation) has been considered to be a promising tool. This study, therefore, examined smallholder farmers' willingness to pay and determinants affecting their decisions to pay for improved irrigation water use in Menz Mama woreda, North Shewa zone, Amhara national regional state of Ethiopia. Cross-sectional data collected from 215 randomly sampled irrigation beneficiaries were used for analysis. The mean WTP from double bounded dichotomous elicitation method ranges from 164.027 Birr (4.17 USD) to 221.059 Birr (5.62 USD) per year per hectare of irrigable land. The result from the seemingly unrelated bivariate probit model estimation revealed that the sex of the household head, total annual farm income, size of irrigable landholdings of the household, frequency of extension contacts, amount of credit, and dissatisfaction with the existing irrigation service positively and significantly influenced farmers' WTP decisions. In contrast, off-farm income and bid values were negatively related to WTP decisions. Therefore, the aforementioned factors affecting farmers' decisions to pay should be taken into consideration when constructing irrigation schemes in the study area and areas with similar economic and socio-cultural settings. [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]

The high rice prices of 2023 have highlighted the need for increasing rice productivity. But improving productivity, especially in low‐performing rice‐producing regions, should also improve incomes for the numerous smallholder cultivators. This article examines what we can learn from the experience of high‐performing rice‐growing regions, which have both high rice yields and incomes. We focus on two best‐performing villages from Kerala, southern India and Mekong Delta, Vietnam. Using a detailed case study approach combining farm budget analysis, counterfactual simulations using agricultural household models, and qualitative insights, our analysis shows the contribution of price support, irrigation, and agricultural research in these two regions to the current situation. While price support was the prominent factor in Keralaʼs village, irrigation and extending the cropping intensity was important for farm incomes in the Mekong Delta village. This comparative analysis demonstrates the need for an ongoing evaluation of price and non‐price factors and supplementing farm incomes through specific interventions for developing low‐performing rice‐producing regions. [ABSTRACT FROM AUTHOR]

Many farming households in Nigeria are deprived, and poor, hence, the need for economic empowerment intervention. Sweetpotato production, due to its short cycle and low input requirement could be projected on a larger scale for farming households' economic empowerment. However, data regarding ability of sweetpotato farming for farming households' economic empowerment is scarce. Therefore, farming households' sweetpotato production and economic empowerment in Nigeria's Niger-Delta Area was investigated. 364 sweetpotato farming households were chosen through a five-stage sample process. Descriptive statistics, Pearson Product Moment Correlation, T-test, and multiple regression were used to analyze the data that interview schedule was used to collect. Most respondents were female and aged 42.7±11.9 years. Farm size; farming experience; and income from sweetpotato, other crops, and non-crop livelihood activities were 2.6±3.4 hectares; 17.2±12.4 years; and N1,327,723.0±1,639,414.0 yearly, N2,385,815.0±2,615,273.0 yearly, and N1,828,004.0±2,336,270.0 yearly, respectively. The sweetpotato production and economic empowerment were low and high amongst farming households, respectively. Age, farm size and income from sweet potato were significantly related to economic empowerment. The economic empowerment status of high and low sweetpotato producers differed significantly. Between farming households with low and high income from sweetpotato production, their economic empowerment status significantly differed. Farming households' economic empowerment was mostly predicted by farming experience; and income from sweetpotato, and non-crop livelihood activities. Sweetpotato production influenced farming households' ability to prosper economically. Agricultural policies oriented towards improving economic empowerment should be promoted to emphasize increased sweetpotato production. [ABSTRACT FROM AUTHOR]

This paper explores the contribution of wage income to the overall earnings of agricultural households in India. Utilising data from the 2019 "Land and Livestock Holding of Households and Situation Assessment of Agricultural Households" conducted by the Ministry of Statistics and Programme Implementation (MoSPI) in 2018–19, the study offers an in-depth analysis of the proportion of income derived from wages by farmers across various states and landholding sizes. Additionally, the paper investigates the impact of public employment programmes, such as the Mahatma Gandhi National Rural Employment Guarantee Scheme (MGNREGS), on rural wages and the income of agricultural households. Findings from the paper point towards increasing landlessness among small and marginal farmers, as they increasingly rely on wages to supplement their livelihood. While a focus on increasing agricultural growth rate by the policymakers may contribute towards farmers' welfare, policies need to be focused towards increase in non-farm employment. Rural employment programmes help to address the issue of chronic unemployment and alleviate rural poverty. Public investments in the form of irrigation facilities and other rural infrastructure are also required to promote sustained agricultural growth and thereby foster well-being among the rural agricultural households. [ABSTRACT FROM AUTHOR]

The proposed reductions in farm input uses foreseen in the European Green Deal may penalize European farm production while increasing environmental leakages to foreign countries where production may expand. These expected impacts have led to calls for a more restrictive trade policy based on mirror clauses. This paper considers as a case study a potential ban on glyphosate in vegetable and fruits production. We develop an original computable general equilibrium model with endogenous adoption of new European production standards by foreign producers on currently latent markets. We find in our case study that adding mirror clauses to the Green Deal marginally improves European farm income and the global environmental footprint of food. We find that foreign producers as a whole can gain from these clauses and not lose as in a standard analysis. European households support these clauses by paying higher food bills while consuming vegetables and fruits produced without glyphosate. [ABSTRACT FROM AUTHOR]

Background: Agriculture is a hazardous industry but the frequency and severity of agricultural injuries are not well documented as nonfatal injuries to self‐employed farmers are excluded from national surveillance. The aim of this study was to provide new injury rate and cost estimates in US agriculture. Methods: Injury data were obtained from 2018 to 2020 Farm and Ranch Health and Safety Surveys. Responses from 7,195 farm/ranch operators included injury frequency, medical expense, and lost work time data. These injury rate and cost data were used to estimate national injury costs for self‐employed farmers using Census of Agriculture operator count, injury costs for hired agricultural workers using Bureau of Labor Statistics (BLS) nonfatal injury count, and fatal injury costs using BLS count of fatal injuries. Results: The injury rate for self‐employed farmers and ranchers was 15.25 injuries per 100 operators or 11.9 "recordable" injuries per 100 full time equivalent operators (FTE). Average costs for nonfatal injuries were: $10,878 for medical care, $4735 for lost work time, and $15,613 in total per injury case. The total national agricultural injury cost estimate was $11.31 billion per year; 11.3% higher than the earlier benchmark using 1992 data; both in March 2024 dollars. The cost burden was 2.1% of the US national gross farm income and 13.4% of the net farm income in 2019. Conclusions: Injuries result in significant economic losses to farm and ranch operators, their family members, workers, and society. Preventive efforts should be scaled up to reduce the frequency and costs of agricultural injuries. [ABSTRACT FROM AUTHOR]

Traditionally, mixed cropping (MxC) has been Rwanda's smallholder farming technology used to sustainably manage farmlands for family subsistence while forming dynamic and climate-resilient agroecosystems. Yet, its significance is overlooked over monocropping (MnC) adopted at dissent since the inception of Crop Intensification Program (CIP) in Rwanda. Thus, this study sought to analyze and compare MnC and MxC systems based on farmers' perceptions and farm profitability in drought-prone areas of Kayonza district in Eastern Province of Rwanda. The farmers' perceptions were assessed using questionnaires, focus group discussions (FGDs), and in-depth group interviews (IDGIs). The farm profitability was assessed using revenue-cost ratio (RCR) analysis. Purposive and multi-stage random sampling techniques were used for selecting sample households (n = 196). The data were analyzed using IBM SPSS software (version 25). Thematic content analysis method and Pearson correlations were used to analyze farmers' perceptions. The binomial logit model was used to determine the effect of the selected determinants on adopting either MxC or MnC. The results show that the majority of the respondents were more involved in MxC during short-rainy and dry seasons (98%) than MnC. Household heads' sex, family size, access to credit services, access to weather and climate information, access to extension services, social group membership, and farm income were highlighted to motivate farmers to adopt MxC systems. The latter was, therefore, shown to be more socio-economically and ecologically beneficial to farmers than MnC under drought conditions as it was chosen and adopted by most smallholder farmers and provided higher on-farm benefits (RCR>4).

This research aims to analyze the income of coffee farmers in Bengkulu province based on the poverty level as per Sajogyo’s 1996 theory, in the form of the “rice exchange rate”, and analyze the causal factors. Primary data was obtained from 326 farmers, interviewed using a purposive questionnaire. To identify factors causing poverty, it was analyzed using a logit function approach. As many as 19.33% of farmers are in the poor category, 21.78% are in a very poor condition, and 40.49% are in the poorest condition. Land ownership status and education are the keys for farmers to be able to have a decent life and socialize in society, this goes back to the role of the government. [ABSTRACT FROM AUTHOR]

Many countries of the world have implemented subsidy programs to maintain a minimum amount of farm production especially for rice. Agricultural support programs usually cause significant fiscal burdens on government budgets. These programs can be generally categorized into decoupled and coupled programs, and one longstanding research interest of previous literature is whether these programs are decoupled or coupled with farm production practices. In Taiwan, a unique land direct payment (LDP) program to rice farms was implemented to ease severe financial burden of the price support program with government purchase. In contrast to production control programs imposing quantity restrictions on farm production, this program is voluntary for rice farms, and participants are paid at a fixed rate per hectare of farmland. This paper examines the impacts of this program on farm income and farm production practices in Taiwan. The causal effect of the program is identified based on the exogenous rollout of the policy across multiple times and areas. We construct a dataset linking nationally representative rice farm surveys over several years and administrative records on program recipients to estimate the local average treatment effect of the program. We find that the effect is 4% of farm income. In addition, program participants rely less on price support programs and produce less rice and use less fertilizer, pesticide, and machinery. Although the LDP reduces rice production, we find that it causes overall government spending on the price support and direct payment programs to increase by 8.7% after the LDP. [ABSTRACT FROM AUTHOR]

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Agroforestry practices play a vital role in improving rural income and livelihoods, yet quantifying their contributions in Ethiopia remains limited. This study investigated the contribution of agroforestry practices to rural income and livelihoods, along with factors influencing income derived from these practices. A two-stage sampling method was employed to select 160 rural households engaged in home garden and woodlot agroforestry practices. Data were collected through semi-structured questionnaires, key informant interviews, and focus group discussions. Descriptive statistics, content analysis, generalized linear model, Mann–Whitney U test, and financial analysis tools were used to analyze and interpret the data. The results demonstrated that agroforestry practices provide numerous benefits to rural households, including fuelwood, charcoal, poles, construction materials, fodder, perennial crops, food crops, and fruits for both consumption and income generation. Agroforestry practices significantly increased farm income, contributing 18.2% of the total household income. This income significantly supported annual household expenditures across various livelihood capitals. Income from woodlots was significantly higher than that from home gardens, while home gardens showed a better overall capability to improve livelihoods. Household size, agroforestry size, gender, crop income, access to seedlings, and farm elevation positively and significantly (p < 0.05) impacted agroforestry income. Overall, agroforestry practices significantly contribute to annual income and improve the human, social, natural, physical, and financial capital of rural households in the Tarmaber district. Policymakers and practitioners should consider the socioeconomic, ecological, and institutional factors influencing agroforestry income when developing policies and strategies to improve rural income and livelihoods. [ABSTRACT FROM AUTHOR]