Agricultural Risk Research Articles

Analisis Risiko Usahatani Wortel Di Kelurahan Rurukan Kecamatan Tomohon Timur Kota Tomohon

The purpose of the study was to analyze the priority risks in carrot farming in Rurukan Village, East Tomohon District, Tomohon City. This research was conducted for four months from October 2023 to January 2024, located in Rurukan Village, East Tomohon District, Tomohon City. The data collection method used in this study was the survey method. Data were obtained from direct interviews with carrot farmers, by asking questions in the form of a prepared questionnaire. Supported by data obtained from the Tomohon City Agriculture Office, Tomohon City Central Bureau of Statistics, and Rurukan Village Office. The sampling method used is purposive sampling method to farmers who grow carrots until the last planting season in 2023. The sample in this study were carrot farmers in Rurukan Village with a total of 10 respondents (farmers). The analysis used in this research is descriptive qualitative analysis. The data obtained were identified and then processed with FMEA (Failure Mode and Effect Analysis) analysis tools to assess the risks that could potentially arise. The results showed that the risk analysis of carrot farming in Rurukan Village, East Tomohon Subdistrict, Tomohon City showed that there were four potential failures that became risk priorities, namely the long dry season, pest attacks, high rainfall, price fluctuations. The results of the assessment based on FMEA (Failure Mode and Effect Analysis) analysis show that farmers are not maximizing their efforts in handling the risks that occur in carrot farming.

From drought hazard to risk: A spring wheat vulnerability assessment in the Canadian Prairies

The Canadian drought monitor (CDM) provides monthly assessments of drought severity but does not provide guidance on the potential agricultural impacts. This study extends the CDM to a comprehensive risk assessment framework by assessing the vulnerability of spring wheat to drought timing and severity in the Canadian Prairies. To achieve this, a bayesian neural network (BNN) model was developed that predicts high-resolution wheat yields and uncertainties using the CDM and normalized difference vegetation index (NDVI) data from 2010 to 2021. Model performance is comparable to previous studies, with errors ranging from 13% to 18% of mean yields and R2 values from 0.43 to 0.70 that peak in early August. The model was then applied under various drought conditions to evaluate how different drought timings and severities affect yield vulnerability. The results demonstrate that drought exposure from June to August reduces wheat yields in proportion to drought severity while abnormally dry conditions may have a positive impact of yield, particularly in August. Yield uncertainty decreases substantially from June to July while yield prediction accuracy increases, suggesting that mitigation efforts are most effective prior to July. The final component of the research involved creating operational risk maps that integrate the yield vulnerability assessment with the CDM. These maps were applied in a case study to demonstrate their utility in providing actionable, real-time information for agricultural stakeholders. Overall, this study contributes to the body of knowledge regarding crop sensitivities to varying drought conditions and represents a methodological advancement by enabling high-resolution, operational agricultural risk assessments at scale. By integrating detailed vulnerability data with drought hazard monitoring from the CDM, the information provided by these risk maps can be leveraged by agricultural stakeholders in near real-time to make well-informed decisions that mitigate the impacts of drought on wheat production, enhancing the resilience of agricultural systems to climatic variability.

Exploring Climate-Induced Agricultural Risk in Saudi Arabia: Evidence from Farming Communities of Medina Region

Agriculture is vital to the Saudi Arabian economy since it provides food and other necessities to people living in rural areas, as well as those living in adjacent cities. Notwithstanding its considerable economic importance, the agricultural sector is confronted with formidable obstacles due to climate change, such as elevated temperatures, floods, extreme droughts, and decreased agricultural yields. Building a farming system capable of being climate resilient requires the comprehension of the vulnerabilities of farm households and related systems. This paper deals with the potential agricultural risks resulting from climate change in Saudi Arabia. In addition to concentrating on precipitation and temperature, the present research incorporates the three main components of the Climate Change Vulnerability Index (CCVI): sensitivity, exposure, and adaptive capability. The results of this research reveal a notable challenge that farmers in Saudi Arabia encounter, as they are very susceptible to the impacts of climate change. The Climate Change Vulnerability Index (CCVI) has a score of 0.730, signifying a substantial degree of vulnerability. The farmers in this region are very susceptible to uncertainties caused by climate change, as indicated by the significant exposure score of 0.725. This exposure comprises a wide range of concerns resulting from fluctuations in temperature, patterns of rainfall, and occurrences of severe weather, all of which have an immediate and negative effect on agriculture. Farmers in that region are more susceptible to the effects of climate change, which could jeopardize their livelihoods and agricultural operations, as shown by the susceptibility component (SVI) of 0.559. Moreover, the adaptive capacity (AVI) score of 0.567 highlights the fact that farmers have limited access to resources, skills, and experience, hindering their ability to tackle the challenges that have been caused by climate change in this region successfully. The results emphasize the immediate necessity for specific policies and assistance to enhance the resilience of agricultural communities in the area, as well as to mitigate the potential adverse effects of climate change on their livelihoods.

A new analytical wind turbine wake model considering the effects of coriolis force and yawed conditions

Wind turbine wakes significantly affect power production and impose higher loads on downstream turbines. Therefore, the development of accurate and efficient wake models is important for optimizing wind farm layouts and predicting wind turbine performance. This study introduces a novel analytical wake model for yawed wind turbines that incorporates the effects of the Coriolis force. The wake deflection in the far wake region is derived through the application of the principles of mass and momentum conservation. In the near wake, the deflection is assumed to be linear with distance. A Gaussian distribution is assumed for the velocity deficit within the wind turbine wake. Two approaches have been proposed to estimate the onset of the far wake region. While the first approach employs a simplified empirical formula, the second approach utilizes an iteration-based method. The proposed analytical wake model has been validated against computational fluid dynamics (CFD) results. Subsequently, the effects of several important parameters on the wake deflection have been systematically investigated. Overall, the simulation results showed a satisfactory agreement between the CFD results and those obtained from the proposed model. Furthermore, the study concluded that the Coriolis force can exert significant effects on wake deflection, particularly in the far wake region, confirming previous findings from numerical simulations. Due to its simplicity and computational efficiency, the proposed model can be readily used in several applications, including wind farm layout optimization, control and risk assessment.

The Value Chain and Sustainable Efficiency of Industrial Potatoes Through an Entrepreneur

This research was driven by the need for sustainable and efficient farming, productivity, and market expansion. This study mapped the industrial potato value chain, identified key stakeholders and their responsibilities, and assessed value chain linkages. This case study employed purposive sampling. The industrial potato value chain includes input suppliers, producers, processors, traders, and consumers, according to the research. Agricultural entrepreneurs are vital to the industrial potato value chain. He chose the Sharazur Plain, Kalar City, and Penjwin districts of Sulaimani Governorate in Iraq's Kurdistan Region for industrial potato production. Additionally, the entrepreneur has entered into agreements with Green Iraq Company as a processor, input supplier, and a chain supporter of the industrial potato value chain. The company has a significant role in enhancing producers to produce industrial potatoes, Lay's Chips is manufactured by a company in Sulaimani governorate/Bazian region. The study demonstrates that the implementation of contractual agreements may lead to a win-win situation for all parties involved. This reduces the farmer's risk by promoting cultivation and guaranteeing the firm has enough raw materials for processing. According to this study, universities, research centers, and agricultural departments have no role in the industrial potato value chain.

European Integration, Opportunities and Risks of Business and Agriculture in Albania

The Integration Process of Albania in the European Union started in 1993 and is considered a long road with many challenges. The signing of the Stabilization-Association Agreement in 2006 is the most important moment of this process, including the harmonization of legislation, to prepare the final EU membership process. This article analyses business opportunities and risks, mainly those of the agri-food sector on its way to the EU. In this framework, trade agreements with the EU and Free Trade Agreements (CEFTA) have influenced the liberalization of trade for agri-food products, intensifying and increasing the level of trade with Europe and the countries of the region. This article also deals with the identification of comparative advantages for the agri-industry sector, where facing the regulated European market, not only challenges are analyzed, but also serious limitations, increasing the need for a structural change in trade relations. In the focus of this paper, are the economic and regional strategies, as well as the progress of the business and agri-food processes, also addressing the trade flows of Albania with the countries of the region and the EU. The analysis of this paper consists of three main premises: 1) in the framework of European integration, costs and benefits in terms of economy and business are more visible in the medium and long term; 2) the integration in the medium term brings a higher economic growth for the countries that aspire to join the EU; and 3) the European integration makes the economy more efficient, bringing about an increase in the ratio of investments, in relation to income, through the reduction of risk with a tendency to increase capital and income per capita (European Commission Report, 2023). The analysis of empirical data shows that the results are not as convincing as expected, thus confirming other previous studies by experts in the field. The main conclusion of this paper is that the integration process has influenced reforms and economic policies in terms of formal and content, both in terms of costs and benefits. In substantive terms, the data analysis shows that the process of European integration has served as a strong impetus for the development of institutions in the country, inter-institutional coordination, the establishment of new institutions, the improvement of human resources, local markets, and the increase of absorptive capacities of funds from the EU. On the other hand, it is concluded that in specific areas of domestic business, such as agri-industry, the effects of EU integration are either not felt yet or are minimal.

Heterogeneous impact of crop diversification on farm net returns and risk exposure: Empirical evidence from Ghana

AbstractIncreasing frequency of extreme weather events threatens the livelihoods of low‐income farm households due to the heavy dependence on rain‐fed agriculture coupled with the under‐developed formal markets for risk management products. Thus, crop diversification is one of the widely used ex ante adaptation strategies to hedge against weather risk exposure. In this study, we use survey data from the northern Savanna zone of Ghana merged with historical weather data to shed light on the heterogeneous impact of crop diversification on farm net returns and risk exposure. We employ the dose response function and instrumental variable techniques to address potential endogeneity concerns. Overall, our findings show that crop diversification is a welfare‐enhancing strategy that significantly increases farm net returns, lowers the probability of crop failure, and thus decreases downside risk exposure. Notably, our dose‐response function analysis demonstrates that the positive benefits of crop diversification are particularly pronounced at lower intensities, reaching an optimal threshold. Beyond this point, the incremental advantages tend to diminish, suggesting the importance of carefully considering the optimal level of diversification for maximum benefits. The results further underscore the significant impact of both access to agricultural extension services and fertilizer usage on the adoption of crop diversification.

Impact of climate services on the operational decision and economic outcome of wheat (Triticum aestivum) and rice (Oryza sativa) cultivation in Haryana

The management of weather and climate risks in agriculture has become an important issue. Application of weather forecast and related advisories offer a great potential to make better-informed decisions and help farmers in adapting climate change. In the present study, weekly forecast-based crop advisories were prepared and disseminated among the farmers of Jind, Rothak and Hisar districts of Haryana. From each block, three experimental villages i.e., one each village receiving weather based advisory services through either of Whatsapp, Text SMS and Mobile Application and one control village (not receiving weekly advisory services) were chosen and thus resulting in 18 experimental villages and 6 control villages. Difference in Difference (DiD) research design was used to study the impact of advisories on farm operational decision making as well as economic outcome of the wheat (Triticum aestivum L.) and paddy A(Oryza sativa L.) cultivation. Average treatment effect of advisories in both crops was found to be significant in all the farm operational decisions except weed management. Reduced seed rate of 3.47, 3.99 and 3.84 kg/acre, reduction in 14.93, 16.92 and 20.23 kg/acre of fertilizer application and saving 0.25, 0.31, 0.34 number of sprays in wheat crop and similarly reduced seed rate of 1.05, 1.15 and 1.27 kg/acre, reduction in fertilizer usage by 18.52, 20.00 and 20.91 kg/acre, and also saving 0.96, 1.02 and 1.15 number of sprays in paddy crop was observed from Text SMS, WhatsApp and Mobile App treatment groups, respectively. The study has also indicated reduced input cost of ₹943.45, 1026.05 and 1168.33/acre in wheat and similarly ₹1439.98, 1566.86 and 1670.22/acre in paddy from Text SMS, WhatsApp and Mobile App treatment groups, respectively. The provision of seamless weather-based advisories for agriculture need to become a national adaptation priority in adapting to changing climate of today and of the future.

Automated system for the detection of risk in agricultural sugarcane harvesting using digital image processing and deep learning

In recent years, significant changes have been presented in the climatological trends due to climatic change, originating negative impacts on the agricultural production, diminishing mainly the harvest efficiency. The following research proposes the optimization of the agricultural risk identification method for the prediction of the variables: temperature and precipitation; the risk identification method was developed through the Digital Image Processing technique (DIP) and Deep Learning (DL); Subsequently, with the processed images, Convolutional Neural Networks (CNN's) were developed for the detection of areas where there is a potential risk in the sugar cane crop harvest in the southeast of Veracruz in Mexico. The efficiency of CNN detects temperatures over 38ºC and the levels of precipitation under 70 millimeters. The efficiency of network detection is 0.9716 and 0.9948 for predicting the temperatures and precipitation variables, which represent a solid basis for detecting zones that depict a risk for the sugarcane harvest.

Agromet Advisories to Mitigate the Effects of Aberrant Weather in Himachal Pradesh

Weather is a pivotal factor in agricultural production, influencing crop growth, disease and pest occurrences, water and fertilizer needs, and the effectiveness of cultural and preventive measures. Extreme weather events can cause physiological stress, physical damage, soil erosion, and crop quality degradation. In India, agriculture's vulnerability to adverse weather is a significant concern, with natural disasters like floods, droughts, and cyclones leading to crop failure, food insecurity, and economic impacts. To mitigate these challenges, Agrometeorological Advisory Services (AAS) play a crucial role in providing farmers with weather-based advisories to manage agricultural risks. The Integrated Agro-Meteorological Advisory Service (IAAS), run by the Indian Ministry of Earth Sciences and the India Meteorological Department (IMD), offers district-level weather forecasts and agromet advisories to support farmers in adapting to weather fluctuations. These advisories cover various weather-related risks, including cold injury and frost, high temperatures, wind damage, hailstorms, and floods. Sample advisories suggest measures like irrigation for frost protection, mulching to reduce heat stress, and shelter belts to mitigate wind damage. Effective dissemination of advisories involves communication through electronic media, Krishi Vigyan Kendras (Agriculture Science Centres), and Kisan (Farmer) Call Centres. Thrust areas for enhancing AAS include improved scientific understanding, advanced monitoring and prediction of severe weather events, satellite-based communication technologies, and real-time forecasting. By integrating these strategies, farmers can better prepare for extreme weather and mitigate its impact on agriculture.

Crop insurance, factor allocation, and farmers’ income: evidence from Chinese pear farmers

Crop insurance, as a crucial tool for agricultural risk management, holds significant importance in increasing farmers’ income. This study analyzed the intrinsic relationship and mechanism between crop insurance, factor allocation, and pear farmers’ income. Using field survey data from 1,337 pear farmers in Xixian and Weixian counties in China, we employed OLS regression models and mediation effect models to empirically investigate the direct and indirect impacts of crop insurance on pear farmers’ income. Additionally, we examined the moderating role of agricultural cooperatives and group heterogeneity. The research findings revealed the following: (1) Although crop insurance increases agricultural expenses, it mitigates income losses due to disasters, ultimately leading to a net increase in pear farmers’ income. (2) Crop insurance enhances agricultural labor and machinery inputs, and encourages pear farmers to adopt green production techniques, thereby boosting their income. (3) The beneficial impact of crop insurance on pear farmers’ income is even more pronounced when farmers are members of cooperatives. (4) Heterogeneity analysis showed that for pear farmers who make individual decisions and have smaller land areas, crop insurance can increase their income, while its impact on farmers who make group decisions or have larger land areas is not significant. In conclusion, this study proposes to promote the development of crop insurance, deepen factor market-oriented reforms, support and guide the development of cooperatives, and pay attention to the heterogeneity among different groups of farmers.

Credit constraints and risk exposure in scaled farming: insights from East China

Credit constraints and risk exposure in scaled farming: insights from East China

Determinants of Smallholder Farmers' Awareness of Crop Insurance in Kedah, Malaysia

Agriculture is a major source of income for humans and has become an agro-food commodity. However, this industry is vulnerable to a wide range of dangers, including climate change, natural disasters, illnesses, and pests. Crop insurance is not a new concept in advanced economies since it has been recognized as an efficient instrument for mitigating agricultural risks and encouraging farmers to employ modern technology and innovation. This research investigates the determinants of smallholder farmers' awareness of crop insurance in the agricultural landscape of Kedah, Malaysia. Therefore, this study examines the relationship between knowledge, risk attitude and farm size on the farmers' awareness of crop insurance. The study, based on a sample of 100 farmers, utilizes a non-probability sampling technique to collect data through structured questionnaires. The research employs reliability analysis, correlation analysis, and regression analysis to evaluate the raw data and uncover the factors influencing farmers' awareness of crop insurance. The study conclusion shows a strong correlation between farmers' knowledge levels and farm size as important indicators of crop insurance awareness. The analysis emphasizes how crucial it is to increase farmers' understanding through focused educational programs and customized awareness campaigns that take farm size dynamics into account. Policymakers and agricultural extension services can enable smallholder farmers to make well-informed decisions about using crop insurance as a strategy to manage agricultural risks and guarantee financial stability by making information and resources easily accessible.

Methodology for forming a digital farming management system

The paper presents methodological approaches for the creation of a digital farming management system (DFMS). A convergent approach, based on cognitive (conceptual) analysis methods, is employed in the research and applied to the formation of adaptive landscape farming systems. The fundamental principles of organizing DFMS include crop and environmental monitoring (in situ, remote sensing); the formation of farming system archetypes based on the analysis of long-term field experiments; spatial object modeling and land typology using GIS; planning and support for agrotechnologies to adapt to natural and economic conditions; modeling ecosystem services and biodiversity; assessing the impact on the sustainability and economics of crop production. The system is implemented using geoinformation models in a specific geographic coordinate. DFMS involves conducting a "inventory" of natural and production resources, as well as identifying limits of climatic, soil, and agrolandscape parameters at different levels of land use intensity. At each stage of organizing system blocks, methods of intelligent data analysis and machine learning are used, with the core of the system relying on the use of knowledge bases and logical rules of the subject area. A key element of the system is the scaling of the results of long-term field experiments and accumulated knowledge in different management areas based on the parameterization of the multi-level variability of farming systems and the formation of their archetypes. The practical implementation of the main provisions of DFMS allows approaching the solution of key issues related to reducing the level of uncertainty and associated risks in agriculture. This is achieved through scientifically justified organization of rational land use, increasing the resilience of crop production in different land use conditions, and providing information support to rural producers.

Land–atmosphere coupling exacerbates the moisture-associated heterogeneous impacts of compound extreme events on maize yield in China

Compound climate events are major threats to crop production under climate change. However, the heterogeneity in the impact of compound events on crop yield and its drivers remain poorly understood. Herein, we used empirical approach to evaluate the impact of compound hot–dry (HD) and cold–wet (CW) events on maize yield in China at the county level from 1990 to 2016, with a special focus on the spatial heterogeneity. Our findings indicate comparable impact of extremely compound CW events (−12.8 ± 3.6%) on maize yield loss to extremely compound HD events (−11.3 ± 2.1%). The spatial pattern of compound HD and CW events impacts on maize yield was dominantly associated with moisture regime, followed by management practices and soil properties. Specifically, drier counties and counties with less fraction of clay soil and organic carbon tend to experience greater yield loss due to compound HD events, and wet condition, excessive fertilizer, clay soil and rich organic carbon aggravate the maize yield loss due to compound CW events. Moreover, the land–atmosphere coupling exacerbated the heterogeneous yield impact through divergent heat transfer. In drier regions, the greater proportion of sensible heat creates a positive feedback between drier land and hotter atmosphere. In contrast, the greater proportion of latent heat in wetter regions results in a positive feedback between wetter land and colder atmosphere. Our results highlighted a critical element to explore in further studies focused on the land–atmosphere coupling in agricultural risk under climate change.

Land Ownership Security, Farm Investment, and Investment Risk in Indian Agriculture: Evidence from Nationally Representative Survey

AbstractThis paper examines the impact of land ownership on farm-level investment and investment risk (variability) in Indian agriculture using nationally representative survey data. The study adopts a flexible moment approach with White’s heteroscedasticity consistent standard error method. Results reveal that land ownership intensity significantly augments on-farm investment and reduces its variability. Other variables like family head’s education, access to irrigation, technical advice, credit and nonfarm income have significant inducement effects on-farm investment. We also observe that farmers’ education, age, irrigation, technical advice, MSP awareness and commercialization reduce farm investment risk. Findings have important policy implications for Indian land tenancy

Spatiotemporal variations, health risk assessment, and sources of potentially toxic elements in potamic water of the Anday Stream Basin (Türkiye), Black Sea Region.

Monitoring and protecting freshwater habitats are paramount for a sustainable water management perspective. This study investigated potentially toxic elements (PTEs) in the potamic water of the Anday Stream Basin (Türkiye), Black Sea Region, for a hydrological year (from May 2020 to April 2021). Among PTEs, the highest average values were recorded for sodium (Na) at 41.3mg/L and the lowest for mercury (Hg) at 0.009μg/L and noted under quality guidelines. The stream was found to be at the level of "Low Heavy Metal Pollution" and "Low Contamination" based on the ecotoxicological risk indices. The highest calculated hazard quotient (HQ) value of 1.21E-02 for Cd was noted in the children via the dermal pathway and the lowest of 6.91E-06 for Fe in adults via the ingestion pathway. Results revealed a higher hazard index (HI) value of 1.50E-02 for Cd to children and the lowest of 1.98E-05 for Fe to adults. As a result of applying agricultural risk indices, the stream showed sodium adsorption ratio values less than 6 and was found to be "Excellent" for agriculture. However, the sodium percentage values were less than 20 and found "Permissible" and the magnesium hazard > 50 and noted as "Unsuitable" for agriculture. Statistical analysis revealed that natural factors mainly attributed to PTE contamination of the Anday Stream Basin.

Peningkatan Kinerja Usahatani Hortikultura Melalui Pengembangan Pola Kemitraan Agribisnis: Studi Kasus Kelompok Tani Sidoluhur, Desa Cabeyan, Kabupaten Sukoharjo

The development of horticultural farming through agribusiness partnerships can serve as a solution to farmers' limitations in managing agricultural risks. Partnerships have the potential to improve farming productivity and ensure price certainty. However, in some instances, partnership practices may give rise to issues such as dependency and weakened bargaining power for farmers. This research aims to investigate and analyze the potential for enhancing the performance of horticultural farming through the development of agribusiness partnership models in the Sidoluhur Farmers' Group, Cabeyan Village, Sukoharjo District. The research methodology employed is a descriptive case study involving five key respondents, including a lecturer from Universitas Sebelas Maret, the owner of Spesial Sambal, and farmers engaged in cultivation or responsible for the Sidoluhur Farmers' Group. The case study method allows for in-depth investigation into specific cases and facilitates the development of narratives or stories. The research findings indicate that the established partnership model is a subcontracting pattern involving three parties: the Sidoluhur Farmers' Group, PT Waroeng Spesial Sambal, and Universitas Sebelas Maret. The partnership provides market certainty for the farmers with a stable selling price. Importantly, this partnership does not create dependency on PT Waroeng Spesial Sambal, as farmers are free to market their harvests independently.

Smallholder farmers’ perceived motivations for the adoption and implementation of climate information services in the Atwima Nwabiagya District, Ghana

This study investigated smallholder farmers’ perceived motivations for the adoption and implementation of climate information services (CIS) in the Atwima Nwabiagya District, Ghana. Specifically, the study answered the following research questions. (i) What is the perception of smallholder farmers on climate change and variability in the Atwima Nwabiagya District?; (ii) What are the CIS accessed and used by the smallholder farmers for farm management decisions?; (iii) What are the perceived motivations for the adoption and implementation of CIS by smallholder farmers?; and; (iv) What are the barriers confronting smallholder farmers in adopting and implementing CIS? Primary data was collected through questionnaire surveys with 200 farming households and four key informant interviews in four selected communities (Kobeng, Seidi, Wioso, and Nkawie Panin) in the study district. Results showed that smallholder farmers perceived climate change and variability through increased windstorms and thunderstorms, variable rainfall, and increased temperature patterns. The surveyed farmers also perceived that the climatic changes affect their agricultural activities adversely. However, the smallholder farmers accessed and used CIS including weather warnings (86%), daily weather forecasts (70%), and seasonal forecasts (60%) to manage climatic risks on the farm. Results also showed that the smallholder farmers were motivated by critical factors including improvement in the acquisition of proactive measures (92%), increased knowledge of climatic patterns that affect food stock (91%), and a reduction in loss of stock produced (88%) to access and use CIS. Despite this, the smallholder farmers were confronted with key barriers in their uptake and utilization of CIS. These were the timeliness of CIS (73%), a lack of weather symbols in the forecasts (65%), and inadequate information on seasonal forecasts for long-term planning (61%). The study concluded that the motivations for smallholder farmers using CIS in the study district may vary depending on their context, goals, and challenges. However, the general motivation is to enhance smallholder farmers’ farm planning and risk management by using weather and climate forecasts to make better decisions on crop selection, planting dates, input use, pest and disease control, irrigation, harvesting, and marketing.

First record of Zaprionus tuberculatus (Diptera: Drosophilidae) in mainland France

AbstractAs most drosophilid species are not considered as primary pest, studies of their communities in natura, with standardized surveys, are relatively sparse. However, Drosophila suzukii and its rapid expansion through the world led to the implementation of many monitoring programs. As part of a research project on D. suzukii, we set up in 2022 an annual fly monitoring in 16 fruits plantations in France to understand population's dynamics of D. suzukii and to broadly survey drosophilid communities. The captures led to the first observation of Zaprionus tuberculatus in mainland France. Over the whole monitoring, we trapped a total of 111 specimens in a fig orchard located in southern France (Salses‐le‐Château), both in fig trees and nearby hedgerow. The first detection of Zaprionus tuberculatus occurred in July 2022 in the hedgerow, and captures continued until January 2023 with an interruption in November and December. In addition, in this orchard we collected overripe figs in September 2023 from which over 20 Z. tuberculatus have emerged in the following 2 weeks, confirming the establishment of a permanent population. The pest status of Z. tuberculatus and its potential risk for agriculture is not yet clear, but the pest behavior of the close‐relative species Zaprionus indianus, especially on figs, should be a warning point for the entry of Z. tuberculatus into the EU and France, as they may have similar polyphagous habit. The pest status and range expansion of Z. tuberculatus should be assessed to estimate risk to fruit's production.