Agricultural Risk Research Articles

Author Correction: Uniting remote sensing, crop modelling and economics for agricultural risk management

Author Correction: Uniting remote sensing, crop modelling and economics for agricultural risk management

Fostering dialogue on health risks of intensive livestock farming in the Netherlands: Combining insights from conversation analysis with the mental model approach of risk communication

Fostering dialogue on health risks of intensive livestock farming in the Netherlands: Combining insights from conversation analysis with the mental model approach of risk communication

Evaluation of pesticide contamination risks and sustainable practices in Ecuadorian agriculture

Pesticide use is crucial in global agriculture to control pests and increase crop yields. In Ecuador, the use of pesticides, including fungicides and insecticides, is common in crops such as potatoes and tomatoes. However, the indiscriminate use of these products has proven to have negative consequences for human health and the environment. This study investigates these risks in Ecuadorian agriculture, specifically in the Paute canton, where inadequate data exacerbates these issues. Employing a descriptive research design, data were collected through validated surveys administered to 30 farmers (9 women and 21 men) residing in various rural communities. The study also included observational methods to complement survey data. Findings reveal that farmer, predominantly with primary education, face health risks from inappropriate pesticide use. Symptoms reported include eye irritation, headaches, and nasal irritation, which vary based on education level and safety practices. The research highlights the urgent need for improved pesticide management through targeted training and sustainable practices. This study’s insights into the extent of health issues and variability in safety measures provide a basis for developing effective interventions to mitigate the health and environmental impacts of pesticide use in Paute and similar regions.

The Impact of the WTO Agricultural Agreement on Developing Countries

Abstract: Agricultural insurance, as an agricultural risk management tool to disperse agricultural risks, compensate farmers' losses and safeguard agricultural production, has become an indispensable part of the agricultural security system in various countries. However, due to the high cost of agricultural insurance, many countries provide financial subsidies for agricultural insurance. This paper introduces the help of agricultural insurance subsidies to countries in World Trade Organization (WTO), summarizes the main features and inadequacies of relevant WTO rules, and analyzes the existing problems of agricultural insurance subsidies from four aspects based on the practice of American agricultural insurance subsidies. The main conclusions of this paper include: first, the rules of agricultural insurance subsidy are limited and the classification is not clear, which seriously harms the agricultural development of developing countries; second, income insurance and natural disaster insurance in premium subsidies are regarded as "green box" tools, which need to meet certain conditions, otherwise there is still the possibility of being regarded as "amber box" tools; third, the current WTO rules on agricultural insurance subsidies are more conducive to the development of developed countries, but the agricultural insurance subsidies in developing countries lag behind and are difficult to implement, and the rules on agricultural insurance subsidies urgently need to be improved. Fourth, the double standards of developed countries and developing countries have caused differences in the classification of agricultural insurance subsidies. Finally, the thesis puts forward some suggestions on the compliance development of China's agricultural insurance subsidies under the framework of WTO rules.

Utilizing large‐scale insurance data sets to calibrate sub‐county level crop yields

AbstractCrop yields are crucial for research on agricultural risk and productivity but are typically only available at highly aggregated levels. Yield data at more granular levels of observation have the potential to enhance econometric identification and improve statistical power but are typically inaccessible. Crop insurance contracts offered via the US Federal Crop Insurance Program (FCIP) are priced, in part, based on past yields of the farm meaning year‐to‐year variation in premium rates has the potential to provide insight into how yields vary over time. This paper introduces methods to use observed FCIP rating parameters to calibrate yields for insurance transactions lacking such data. These methods are validated with 148,243 farm‐level observations from Kansas for which yields are known. The calibrated yields are applied empirically to examine the impact of asymmetric information in the FCIP via choice of insurance unit structure and the extent to which legislative changes mitigated this effect.

Sizing Up the Farm Bill Safety Net

Lower commodity prices and higher production costs over the past couple of years have crop producers concerned about tighter margins and cash flow for their operations. The federal farm income safety net provides substantial support to producers through commodity programs, crop insurance programs, and disaster assistance. Crop insurance has been the primary safety net tool for producers in recent years as commodity prices generally fluctuated at levels above commodity program support levels. Even declining markets in the past couple years left prices that remained above Price Loss Coverage (PLC) support levels and revenue calculations above Agriculture Risk Coverage (ARC) guarantees unless there were significant yield losses at the county level for ARC-CO or the individual farm level for ARC-IC. The outlook is changing however as declining prices run into support levels that are increasing based on the past few years of higher prices. The ARC program provides a revenue guarantee tied to 86% of a benchmark revenue calculated from a five-year moving average price and a five-year moving average trend-adjusted yield. The PLC program provides support if prices fall below the higher of a legislated reference price or 85% of a five-year moving average price. With the higher prices experienced during the past few years, the five-year moving average price has increased and both ARC and PLC support levels have gotten stronger. A look at ARC and PLC protection and payment levels provides a picture of what current support and cash flow may look like and what future support could be under current or future farm legislation.

Sustainable dairy farming and fipronil risk in circular feeds: insights from an Italian case study

Circular feeds, such as grain dry distillers, citrus pulp, cane molasses, and potatoes peels, are co-products of biomass processes. They are currently proposed in animal nutrition to improve the environmental and economic sustainability of the food production chain. In this paper, we report a case study involving fipronil, a pesticide currently not authorized for agriculture within the EU, but used in the Americas, Eastern Europe, and Asia. Fipronil was found at a mean level of 0.49 mg/kg, in a grain dry distiller batch administered to dairy cows. This finding, along with other evidence of potential fipronil presence in feed materials, prompted us to evaluate the risk to food safety and food security from 12 different conventional and sustainable feeding regimens. To this purpose, we considered a fipronil feed-to-milk carry-over rate of 0.52, the tolerance levels in fodders and food from The EU, Codex Alimentarius, and US-EPA, and the Acceptable Daily Intake (ADI) of 0.0002 mg/kg body weight for adverse effects on thyroid function in dairy cows. Under a conservative scenario, fipronil-contaminated potato peels and grain distillers in the feeding regimens may play a pivotal role in exceeding the EU Maximum Residue Level (MRL) in bovine milk and fat (0.005 and 0.030 mg/kg, respectively). Hay-based diets with soybean hulls and cane molasses show negligible risks (Hazard Index ∼ 1). In all cases, the ADI exceedance suggests the need to evaluate thyroid function in dairy cows exposed to fipronil as a food security factor.

Analyzing the Relationship between Agricultural AI Adoption and Government-Subsidized Insurance

Due to the increased unpredictability and severity of weather patterns caused by climate change, traditional farming practices and risk management strategies are becoming increasingly inadequate. In this paper, we explore the literature to understand the potential of artificial intelligence (AI) in mitigating climate-related agricultural risks and the pivotal role that public institutions play in encouraging farmers to adopt such technologies. We propose a framework to integrate AI into government-subsidized insurance structures, focusing on reduced premiums through government intervention. We argue that AI’s potential to reduce the uncertainty and severity of climate-induced damages could lower the overall risk profile of insured farmers, thereby justifying lower premiums in the long run. We further discuss the implications of such policies on insurance markets, agricultural sustainability, and global food security. Our initial exploration contributes to the literature by addressing a relatively underexplored intersection of two critical fields—agricultural insurance and artificial intelligence—suggesting directions for future research.

Perceptions of The Health Risks of Local Poultry Farming and The Behaviour Of Urban and Peri-Urban Populations in The Town of Korhogo (Côte d'Ivoire).

Poultry farming plays an important nutritional, economic and socio-cultural role in developing countries. The aim of this study is to analyse the perceptions of health risks associated with poultry farming activities in the vicinity of dwellings and the behaviour of the population of the town of Korhogo. To achieve this, a qualitative socio-anthropological approach was used. The data collected came from 97 semi-structured interviews and direct observation from 15 April to 27 May 2024 in the town of Korhogo. The main results show that local residents living near poultry farms are aware of the health risks to which they are exposed, but the balance of power between gains and risks explains their practices. Poultry farming close to homes has had an impact on local residents and their environment. Residents often suffer from respiratory ailments, allergies, soiling of their surroundings, odour nuisance and other noises. As for the environment, it has suffered pollution of its air and water quality, as well as soil degradation. The reasons why these poultry farmers decide to carry out their activities close to homes are environmental, economic, social and ethical. Hence the need to train young farmers to manage the nuisances generated by these poultry farming activities.

Multiple agricultural risks and insurance—issues, perspectives, and illustration for wine-growing

Multiple agricultural risks and insurance—issues, perspectives, and illustration for wine-growing

An Empirical and Deep Learning Investigation of Working Conditions and Musculoskeletal Outcomes in Wheat Farmers

Background: In developing countries, various farming activities are performed manually with the help of traditional hand tools. Therefore, agriculture is recognized as one of the risky occupations Objective: This research study aims to identify the critical working conditions of wheat farmers in Rajasthan state, India. Method: Data were collected through the survey conducted on 75 randomly selected wheat farmers of Rajasthan. The survey questionnaire gathered information related to demographic, occupational, and musculoskeletal discomfort faced by the farmers. In addition, a deep learning-based posture detection study of the workers was performed to assess the postural risks through a rapid upper limb assessment score. Result: The collected data were analyzed further for fruitful insights. The survey outcomes showed that awkward posture (41%) and repetitive movement (35%) were the most reported reasons for the severe risks of musculoskeletal disorders among farmers. The posture evaluationbased study outcomes showed that approximately 51% of subjects lie in the action category 4, which shows the higher level of risks in the activities performed by farmers. Conclusion: It is suggested to apply the principles of physical ergonomics in the agriculture sector and spread awareness among the farmers about the agriculture risks associated with farming activities.

The interplay of geopolitics and agricultural commodity prices

AbstractThis article uses the time‐varying parameter vector autoregressive model to assess the impact of geopolitical risk and shocks on agricultural commodity markets, accounting for demand—exports; supply—input prices; inventory; speculation; and economic fluctuations. The results show that geopolitical risks significantly impact corn and soybean futures prices and market behaviors with context‐specific implications in the short to medium term. In addition, heightened geopolitical risk during the Russia–Ukraine war increased oil prices and indirectly elevated agricultural commodity prices. These insights are crucial for agricultural risk management, informing federal policies and forecasting future price trends in an increasingly uncertain global market environment.

Manajemen Risiko Usahatani Cabai Rawit: Studi Kasus Di Kawasan Gunung Merapi

Cayenne pepper (Capsicum frutescens L) is a common horticultural commodity cultivated by farmers in the Mount Merapi area. Farmers in this region face the risk of fluctuating productivity due to unpredictable volcanic eruption activities. This study aims to describe the types, sources, and levels of risk, analyze and examine risk management in bird's eye chili farming based on risk levels, risk mapping, and the total household income analysis of bird's eye chili farmers in Mount Merapi. The sample consists of 100 farmers selected through simple random sampling, with the criteria being residents who have been farming cayenne pepper for 10 years in the Mount Merapi area, growing cayenne pepper as the main commodity on their farmland, and farmers with and without additional income sources outside of farming. Data analysis includes risk analysis, total household income analysis, and descriptive quantitative analysis. In Pakem Subdistrict, the coefficient of variation values for production, price, and profit risks are 0.67, 0.08, and 1.20, respectively. In Dukun Subdistrict, these values are 0.55, 0.14, and 2.40, respectively. Lastly, in Selo Subdistrict, the values are 0.45, 0.07, and 0.84, respectively. Household income analysis is divided into two categories: farmers with additional income sources outside of farming and those without additional income sources in each district. The highest average total household income of cayenne pepper farmers is found in Selo Subdistrict. Important considerations in agricultural risk management include providing insurance for cayenne pepperi, market development, and land diversification.

Conceptualising climate change vulnerability across the agrarian transition: The example of Egypt

In this study, we explore the relationship between Egypt's agrarian transition and farmers’ perceptions of environmental risks and opportunities for climate change adaptation. Drawing from agrarian studies and rural development pathways in Egypt, we highlight structural challenges in addressing vulnerabilities of households in agrarian communities to environmental change. Our evidence comes from 350 landholders and agricultural labourers in rural Damietta, a governorate in the northeast of the Egyptian Nile Delta Region. We categorize households into three groups based on their reliance on agriculture for income, corresponding to different agrarian transition models. We find that vulnerabilities and capacities for climate change adaptation vary among these groups, with those heavily dependent on agriculture being the most vulnerable, despite having greater awareness of agricultural risks. They exhibit limited capacity to respond effectively – both in and ex situ, indicating a need for targeted support as environmental pressures increase due to climate change.

COVID-19 pandemic, household welfare and diversification strategies of smallholder farmers in Uganda

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.

Utilizing machine learning and hemagglutinin sequences to identify likely hosts of influenza H3Nx viruses

Influenza is a disease that represents both a public health and agricultural risk with pandemic potential. Among the subtypes of influenza A virus, H3 influenza virus can infect many avian and mammalian species and is therefore a virus of interest to human and veterinary public health. The primary goal of this study was to train and validate classifiers for the identification of the most likely host species using the hemagglutinin gene segment of H3 viruses. A five-step process was implemented, which included training four machine learning classifiers, testing the classifiers on the validation dataset, and further exploration of the best-performing model on three additional datasets. The gradient boosting machine classifier showed the highest host-classification accuracy with a 98.0 % (95 % CI [97.01, 98.73]) correct classification rate on an independent validation dataset. The classifications were further analyzed using the predicted probability score which highlighted sequences of particular interest. These sequences were both correctly and incorrectly classified sequences that showed considerable predicted probability for multiple hosts. This showed the potential of using these classifiers for rapid sequence classification and highlighting sequences of interest. Additionally, the classifiers were tested on a separate swine dataset composed of H3N2 sequences from 1998 to 2003 from the United States of America, and a separate canine dataset composed of canine H3N2 sequences of avian origin. These two datasets were utilized to look at the applications of predicted probability and host convergence over time. Lastly, the classifiers were used on an independent dataset of environmental sequences to explore the host identification of environmental sequences. The results of these classifiers show the potential for machine learning to be used as a host identification technique for viruses of unknown origin on a species-specific level.

Impacts of policy-related agricultural insurance on farmers’ earnings in China's major grain-producing regions

Policy-related agricultural insurance can diversify farming risks and compensate damaged farmers’ losses. This study examined the impact of policy-related agricultural insurance on farmers’ earnings in China's primary grain-producing regions. The findings indicate that policy-related agricultural insurance significantly improved farmers’ earnings. Agricultural operational scale, technological advancements, and agricultural credit played an intermediary role in policy-related agricultural insurance on farmers’ earnings. This study provides suggestions including increasing support, guiding the modernization and transformation of policy-related agricultural insurance, promoting coordinated development of agricultural insurance and agricultural credit in order to promote the high-quality development of policy-based agricultural insurance and improve farmers' income.

Agricultural Insurance Adoption in the Context of Climate Change: Influencing Factors in Benin (West Africa)

Background: Agricultural insurance has emerged as an effective climate risk management strategy in many African countries, but its adoption is still low in Benin. This study seeks to understand farmers¢access and perception of agricultural insurance, while analyzing the factors that affect its adoption in the municipality of Ouèssè in Benin. Methods: Using the method of snowball sampling, the research team collected data from 112 household heads, from six major maize-producing villages. With the data from focus group discussions and a structured questionnaire, we performed descriptive statistics and used the logistic regression model to analyze the factors influencing farmers' agricultural insurance adoption. Result: Our investigations revealed that almost all (95%) of the respondents have received agricultural insurance information at least once and about 94% of them found insurance useful for effective agricultural risk management. However, most of respondents (66.5%) lacked knowledge of loss assessment methods and 52% of them said that the insurance premium was too high for farmers. Most (95%) of the respondents who subscribed to agricultural insurance also received agricultural credit. The binomial logistic regression analysis revealed that adopting agricultural insurance is positively influenced by the farmers' perception of the insurance, educational level, household size andaccess to agricultural credit. Implementing strategies that consider these influencing factors andpromote awareness, while building capacity and trust, could facilitate farmers' adoption of agricultural insurance, especially in countries like Benin, where agricultural insurance is relatively new.

Climate variability through the lens of applied weather index insurance in Senegal-a novel perspective on the implications of decadal variation

IntroductionWeather-based index insurance is a financial instrument which allows smallholder farmers to protect themselves against climate shocks such as droughts and floods. In many cases, insurance indices are based on one or more earth observation datasets (e.g., rainfall, soil moisture, vegetative health) which are partly covering periods of more than 40 years. While remote sensing products and their associated data have improved over this time, understanding the historical climate variability and trends remains an essential piece in ensuring the development of indexes that best represent farmers’ risks. From a practical perspective, shortening time series to limit the risk of understudied climate variability, such as the Atlantic Multidecadal Variability, sometimes seems to be a quick solution. However, shorter time series jeopardize the overall robustness of the index. Therefore, understanding the links between climate variability, index design, and implications for farmers is key. Weather-based index insurance products in Sahelian West Africa usually face a challenge in robustly quantify underlying climatic decadal variation in seasonal rainfall.MethodsThis study analyzes the influence of decadal shifts in rainfall patterns in Sahelian West Africa, in particular Senegal, on index insurance calibration and design, concluding with practical recommendations for the next generation of drought risk finance instruments in the region.ResultsOur findings indicate that decadal variability has not led to a clear decrease in payouts in recent years compared to earlier years, despite an overall increase in seasonal rainfall. Rather, we find that interannual variability has increased which may be a more critical factor for assessing farmers’ agricultural risk than the increase in total rainfall.DiscussionFocusing on key moments of the cropping calendar in the design of an index shows that an increase in the total average rainfall per season does not result in fewer payouts.

Does cooperative membership facilitate access to credit for women farmers in rural Kenya?

Potential borrowers' demand for credit is restrained by agricultural risk, while microfinance institutions favor male over female farmers because the latter have no collateral. We investigate whether women's membership in cooperatives facilitates access to credit. Primary data from Kenya were used. Descriptive statistics, propensity score matching, and probit regression methods were applied. The results show that 78 % of the respondents did not apply for credit mostly because of high interest rates and being risk-averse; while 60 % of those denied credit were due to lack of collateral. The estimates indicate that joining cooperatives increases the probability of female farmers' access to credit; transparency in cooperatives' financial activities increases the probability of accessing credit by 72 %. Given the core role of cooperatives, there is a need for a favorable environment in which cooperatives can form, develop, and thrive. Cooperatives need support from the government and development agencies to buffer their financial and management capacities and skills training. Subsequently bolstering women farmers' participation in cooperatives.