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Abstract Agricultural activities in many sub-Saharan African (SSA) countries are subject to various risk factors that the COVID-19 compounds. Earlier studies on the effect of COVID-19 on smallholders neglect the issue of comparison with non-farm households. The study uses micro-level household datasets to explore the impact of the COVID-19 pandemic on household welfare, with a focus on farm households relative to their non-farm counterparts. We employed a binary probit model and Propensity Score Matching (PSM) approach and demonstrated that farm households witnessed important income reductions during the COVID-19 pandemic in Uganda. The study contributes to the design of evidence-based approaches to reducing farmers’ vulnerabilities to agricultural risks and pandemic-related shocks.

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This study explores the challenges faced by farmers in the cauvery delta zone of Tamil Nadu, an area highly vulnerable to drought and flooding. The traditional reliance on mono-cropping, especially paddy, has made farmers more susceptible to risks posed by uncertain water availability and climate variability. The study aims to develop a risk-optimized, crop-diversified alternative cropping system using the Minimization of Total Absolute Deviation (MOTAD) model. Through a stratified random sampling, 600 farmers were selected across five agronomically and socio-economically homogeneous village clusters, to capture the diversity of cropping patterns and irrigation sources. The results revealed that, the degree of farm-level crop diversification was much low in the study area. The MOTAD model integrates risk considerations into farm planning by balancing profit maximization and risk minimization. The findings suggest alternative cropping systems, which include combinations of Paddy, Banana, Coconut-Pepper and low-water-intensive crops such as Brinjal, Bhendi, Maize, Cotton, Marigold and Tuberose. The findings emphasize the need for awareness among farmers about crop diversification as a risk mitigation strategy and suggest that agricultural extension agencies should promote the adoption of these diversified cropping systems. By evolving cluster-specific cropping plans, the study proposes a sustainable approach to enhance the resilience of farming in the Cauvery delta zone. [ABSTRACT FROM AUTHOR]

Agricultural activities in many sub-Saharan African (SSA) countries are subject to various risk factors that the COVID-19 compounds. Earlier studies on the effect of COVID-19 on smallholders neglect the issue of comparison with non-farm households. The study uses micro-level household datasets to explore the impact of the COVID-19 pandemic on household welfare, with a focus on farm households relative to their non-farm counterparts. We employed a binary probit model and Propensity Score Matching (PSM) approach and demonstrated that farm households witnessed important income reductions during the COVID-19 pandemic in Uganda. The study contributes to the design of evidence-based approaches to reducing farmers' vulnerabilities to agricultural risks and pandemic-related shocks. Article highlights: Farm households witnessed significant income reductions during the COVID-19 period in Uganda. Most common coping strategies adopted by households amid the COVID-19 crisis were reliance on savings, and reducing food consumption. The study offers suggestions in designing evidence-based approaches to reducing farmers' vulnerabilities to agricultural or pandemic-related shocks. [ABSTRACT FROM AUTHOR]

The Ghanaian cocoa sector faces numerous challenges which contributes to lower yields, forcing farmers to depend on traditional coping strategies due to the absence of institutionalized cocoa crop insurance. The effectiveness of these traditional risk-coping strategies remains uncertain. This study aims to identify the influential factors shaping cocoa farmers' decisions to participate in insurance schemes and the premium amounts they can afford. Using multi-stage random sampling, a semi-structured questionnaire was used to illicit responses from 240 cocoa farmers in the Western North region. A binary logistic and a multinomial logistic models were used for data analysis. Age, education, experience, credit access, and off-farm income were identified as statistically significant factors influencing farmers' decisions to participate in the insurance scheme. Moreover, among the 3 price contracts, multinomial results indicate that the majority of farmers (50.4%) favoured a premium/acre of GH¢250 for a minimum price insurance contract of GH¢1300 per annum. The multinomial log-odds determining the amount farmers are willing to pay are influenced by age, education, and off-farm income. Despite the sector's inherent challenges, there should be opportunities for collaboration between government agencies, insurance companies, and agricultural stakeholders aimed at improving insurance accessibility and affordability for cocoa farmers, thereby enhancing the sector's resilience against various risks.

Copyright of International Journal of Professional Business Review (JPBReview) is the property of Open Access Publications LLC 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.)

Copyright of Revista de Ciências Agrárias is the property of Sociedade de Ciencias Agrarias de Portugal 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.)

Copyright of Revista de Ciências Agrárias is the property of Sociedade de Ciencias Agrarias de Portugal 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.)

Agriculture plays a pivotal role in Africa's development and is essential for achieving the Sustainable Development Goals (SDGs). However, the agricultural sector is inherently exposed to production risks, and many farmers in the developing world lack access to reliable agricultural insurance coverage. This situation arises due to limited data and knowledge about farmers' insurance needs and the high costs associated with insuring against severe agricultural risks. Promoting agricultural insurance as an instrument can have several significant impacts, aligning with multiple SDGs. It can help stabilize farmers' income, thereby contributing to the goal of reducing poverty (SDG 1). Moreover, agricultural insurance can provide a safety net for food producers, helping them manage the impacts of climate-related risks and aligning with SDG 13, which addresses climate action. Additionally, by enhancing the resilience of farmers and ensuring more predictable income, agricultural insurance can contribute to addressing hunger (SDG 2) and ultimately create a more sustainable and prosperous agricultural sector in Africa. Therefore, this study evaluated agricultural insurance as an instrument for sustainable food supply systems in Nigeria. This study adopted a survey design. This study captured thoughts, experiences, and observations of selected agricultural underwriters in the Nigerian insurance industry through structured questionnaire. A descriptive statistic was employed in the data analysis. This study results indicated that aside from farmers’ awareness which showed some level of yardstick with respect to farmers behavioural metrics, all other metrics played no significant roles. It was also recorded that why farmers’ age, gender, family size and farming experience have no significant roles in the uptake of agricultural insurance, all other participatory factors have major effects. The study contributed significantly to knowledge with the graphical representations of the challenges confronting the agricultural insurers in Nigeria. The study provided suitable recommendations that endear achievable SDGs in Nigeria.

Food security is of great importance to all countries. Correspondingly, agricultural price insurance is an important tool to maintain food security. This study adopts the traditional spider web model to establish a mathematical framework for exploring the internal mechanism of agricultural price insurance, which can ease the volatility of the agricultural market. Then, the influence of agricultural price insurance on the supply of agricultural products is examined. The findings show that the supply elasticity of most agricultural products is greater than the demand elasticity, with agricultural product markets presenting a natural divergence. Agricultural price insurance changes the supply curve of agricultural products by reducing their supply elasticity, subsequently positively affecting the reduction of price fluctuation and the stabilisation of outputs. Agricultural price insurance can even change agricultural product markets under certain conditions, allowing a shift from divergence to convergence. Moreover, by adjusting the insurance parameters of agricultural prices, the equilibrium yield and price can be changed, and the planting area and income of farmers can be maximised. The mathematical basis for agricultural insurance derived in this study can support food security strategies at the national level and further provide a theoretical basis to formulate policies and departmental measures.

Scientists and policymakers are concerned about the effects of climate change on agricultural productivity and the well-being of farmers around the world. Alterations in the amount of precipitation and temperature have a direct influence on crop yields, although a rise in the prevalence of diseases and pests has a secondary but nevertheless important influence. The degree to which farmers believe climate change poses a threat to their agricultural operations is a decisive factor in determining whether or not they will make adjustments to their practices. This study assesses the impact of climate change on agricultural risks among cotton farmers in rural Zimbabwe. Thirteen (13) cotton farmers and employees of a company that buys and sells cotton were interviewed using a qualitative methodology. The study found that the cotton-growing industry has significantly incurred losses due to both the effects of climate change and the broader economic downturn. Several reasons related to Zimbabwe's economic collapse have contributed to the problem facing the nation's rural cotton farmers.

Agriculture plays a pivotal role in Africa's development and is essential for achieving the Sustainable Development Goals (SDGs). However, the agricultural sector is inherently exposed to production risks, and many farmers in the developing world lack access to reliable agricultural insurance coverage. This situation arises due to limited data and knowledge about farmers' insurance needs and the high costs associated with insuring against severe agricultural risks. Promoting agricultural insurance as an instrument can have several significant impacts, aligning with multiple SDGs. It can help stabilize farmers' income, thereby contributing to the goal of reducing poverty (SDG 1). Moreover, agricultural insurance can provide a safety net for food producers, helping them manage the impacts of climate-related risks and aligning with SDG 13, which addresses climate action. Additionally, by enhancing the resilience of farmers and ensuring more predictable income, agricultural insurance can contribute to addressing hunger (SDG 2) and ultimately create a more sustainable and prosperous agricultural sector in Africa. Therefore, this study evaluated agricultural insurance as an instrument for sustainable food supply systems in Nigeria. This study adopted a survey design. This study captured thoughts, experiences, and observations of selected agricultural underwriters in the Nigerian insurance industry through structured questionnaire. A descriptive statistic was employed in the data analysis. This study results indicated that aside from farmers' awareness which showed some level of yardstick with respect to farmers behavioural metrics, all other metrics played no significant roles. It was also recorded that why farmers' age, gender, family size and farming experience have no significant roles in the uptake of agricultural insurance, all other participatory factors have major effects. The study contributed significantly to knowledge with the graphical representations of the challenges confronting the agricultural insurers in Nigeria. The study provided suitable recommendations that endear achievable SDGs in Nigeria. [ABSTRACT FROM AUTHOR]

Farmers' inability to successfully participate in the maize value chain due to the threats of some risk factors is one of the key reasons for rising food insecurity. This study analyses farmers' responses to risks involved in maize production in Cameroon. Data on maize production risks were collected from smallholder maize farmers operating in selected communities along the River Sanaga. The Criticality Risk Matrix model was employed to determine the severity of these risks based on their criticality and likelihood of occurrence. After deriving farmers' risk preferences from the categorization of their farm decisions, a Multinomial Logit Regression model was then used to investigate the extent to which risk severity influences farm decisions. Additionally, a Graded Response Model was utilized to predict farmers' risk responses by categorizing their probable patterns of action. The results revealed that production risks with fatal consequences such as pest invasion had a negative significant influence on-farm decisions and their perceived threats were more likely to provoke risk-averse responses. Less fatal risk threats such as fertilizer unavailability, poor farm infrastructure, labour shortage, and health risks were all significant and induced risk-averse responses from farmers. Furthermore, gender, experience and employment status also significantly influence farm decision-making. The farmers’ response patterns presented on the Graded Response Model Characteristic Curves further indicated the willingness of farmers to continue farm activities despite perceived risks and the probability of engaging in diversification as an added measure to mitigate risks. We recommended that more effective measures for information dissemination on production risks as well as sustained Extension Service support to mitigate these risks be made available to farmers.

This study examines the impact of the row planting method on maize productivity and risk exposure using panel datasets from Ethiopia. A flexible moment-based production function is fitted to capture the expected yield, yield variance, and exposure to downside risk. A Mundlak–Chamberlain approach is combined with a switching regression treatment effects model to account for unobserved heterogeneity and endogeneity. The study shows that adopters of the row planting method significantly reduced exposure to downside risk while increasing expected yield. The analysis also identified some household and environmental conditions that affect the gain from the row planting method. [ABSTRACT FROM AUTHOR]

Copyright of Acta Universitaria is the property of Universidad de Guanajuato/Acta Universitaria 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.)

Assessing the risk to the agricultural system is important for agricultural sustainability. The present study analyses agricultural drought risk with respect to different drought severities. Different drought indices – namely, Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Soil moisture Index (SSI), Vegetation Condition Index (VCI), and Temperature Condition Index (TCI) – are used to evaluate the conditional probability. Non-stationary analysis is carried out for SPEI and SSI to incorporate the impact of large-scale oscillations and regional hydrological variability. Copula analysis is performed between drought conditions and various crop yield anomalies over Maharashtra, India, during 1998–2015. The outcomes suggest that SPEI is a significant drought indicator over the maximum number of districts in all the crops. Sea Surface Temperature (SST) and Indian Summer Monsoon Index (ISMI) are selected as suitable covariates to model the non-stationarity in the SPEI time series. The drought risk is estimated to increase with drought severity for all of the selected crops. It is observed that the exclusion of non-stationarity will underestimate the agricultural risk. [ABSTRACT FROM AUTHOR]

The effects of climate change are likely to increase the frequency of flood, drought, and salinity events in the coastal areas of Bangladesh, posing many challenges for agrarian communities. Sustainable intensification in the form of improved agricultural management practices and new technologies may help farmers cope with stress and adapt to changing conditions. In this study, we explore how climate change perceptions of agricultural risk affect adaptation to climate change through technology adoption in a unique landscape: the polders of Bangladesh. In 2016, a survey was conducted in 1003 households living on these artificial, leveed islands facing the Bay of Bengal. We analyzed the responses from polder residents to construct a climate risk index which quantifies climate risk perception in this highly vulnerable agrarian landscape. We analyzed how polder demographics influence their perceptions about climatic change using seemingly unrelated regression (SUR). Further, by using three bivariate probit regression models, we estimated how the perception of climate risk drives the differential adoption of new agricultural technologies. Our findings show that farmers perceive polder agriculture as highly vulnerable to four environmental change factors: flooding, drought, salinity, and pest infestation. The SUR model suggests that farmer demographics, community group memberships, and access to different inputs and services strongly influence climatic risk perceptions. Findings also suggest that polder farmers with higher risk perceptions have a higher propensity to adopt both chemical and mechanical adaptation strategies. Cost, however, limits the ability of farmers to adopt improved technologies, suggesting an opportunity for institution-led approaches. • Farmers perceive polder agriculture as highly vulnerable to four environmental change factors. • Polder farmers experience substantial yield losses from climatic events. • Perceptions of climate risk affect the adoption of chemical and mechanical agricultural technologies. • Community group participation increases the likelihood of adopting sustainable intensification practices. • Farmer networks play a strong role in climate change adaptation. [ABSTRACT FROM AUTHOR]

Agricultural risks associated with weather events, soil conditions, diseases, and pests have risen in recent years due to climate change. These risks have burdened farmers with the shock of financial stress and endangered the region's food security. Despite increasing risks, notable risk management tools like agricultural insurance have not effectively reached marginal farmers in developing economies. This can be attributed to the fact that existing centralized agricultural information systems lack trust factors in sharing and accessing agricultural risk data, which is accompanied by processing delays in insurance payouts. To this end, the emergence of promising technologies like blockchain helps establish trust and automates insurance-based payments with smart contracts. This work proposes a framework called AgriSSIOracle with two key contributions. The first is to have a trusted agricultural Internet of Things (IoT) data sharing that employs blockchain-based Self-Sovereign Identity (SSI) and provable credentials. Second is the decentralized oracle-based access control mechanism for smart contracts in agricultural insurance. A method for privacy-preserved authentication and data provenance for agricultural IoT devices is developed with SSI-based Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs). Next, the IoT data sharing scheme is illustrated using publish–subscribe and request–response communication patterns based on the device data credentials. Finally, the decentralized oracle mechanism for smart contracts is built based on multiparty computation for risk-related data access. The implementation of the framework is realized using a permissioned identity blockchain called Hyperledger Indy and Ethereum, which is a public blockchain for smart contracts. The security and privacy analysis confirms that the AgriSSIOracle framework ensures trust factors, particularly authenticity, privacy, data provenance, data integrity, and access control. The framework is evaluated with respect to the transaction throughput, latency, credential issue-verify-revoke time, and resource utilization metrics. The evaluation results prove that the AgriSSIOracle solution is scalable and efficient and meets the requirements of real-time deployment. [ABSTRACT FROM AUTHOR]

Compound droughts and hot events (or hot droughts) have attracted increasing attention due to their far-reaching impacts. Previous studies on these events mostly focused on the concurrence of meteorological droughts and hot extremes. The compound agricultural droughts and hot events (CADHEs), which have direct impacts on agricultural production, have received limited attention to their variability and driving factors. In this study, we defined CADHEs based on summer temperature and soil moisture from the Global Land Data Assimilation System (GLDAS) and investigated their changes and potentially driving factors for the period 1949–2014 in eastern China. Results showed increases in the frequency of CADHEs in Northeast China, North China, and South China (with increases of 125%, 160%, and 83%, respectively) except for Central China (with a decrease of 39%). Furthermore, we analyzed the contributions from individual variables (i.e., soil moisture and temperature) and their dependence on CADHEs changes in quantitative manners. For most regions, the increased temperature was the dominant driving factor of increased CADHEs. Strengthened soil moisture-temperature dependence was shown to play an important role in the increase of CADHEs in Northeast China, highlighting the contributions of dependence changes on the variability of compound events. This study can improve the understanding of changes in compound droughts and hot extremes and provide useful insights for mitigation measures of agricultural losses under global warming. • Compound agricultural droughts and hot events (CADHEs) have increased in eastern China. • Increased temperature dominates the changes in CADHEs for most regions. • Enhanced soil moisture-temperature dependence affects CADHEs changes in Northeast China. [ABSTRACT FROM AUTHOR]