Maize Farmers Research Articles

Integrating ICT for Enhanced Maize Market Access: A Business Model for Storage and e-Marketing in Char Land

Aims: This paper puts forth the idea of MaizeConnect—a business model centred on information and communication technology (ICT) to improve a lot of rural maize farmers in Bangladesh when it comes to accessing markets. Methodology: The research was conducted in the char areas of Jamalpur District, where the Making Markets Work for the Chars (M4C) project is being implemented. The research undertakes a mixed-methods approach of desk reviews, stakeholder consultations, and SWOT analysis to understand the model's viability and impact. A situation analysis was conducted in the selected research sites to understand the current marketing practices, identify gaps, and determine the specific needs of marginal farmers. Results: An innovative e-marketing model has been developed for ensuring better access to smallholders in Bangladesh. This model not only seeks to give farmers direct access to buyers but also aims to tackle the problem of postharvest maize losses. The rural farmers are mostly poor, producing maize on a small scale. They don't have much power to negotiate, which makes their situation look pretty grim. MaizeConnect focuses on transforming the maize sector by providing easy-to-use technology, with three main benefits: price stabilization, market connectivity, and payment system inclusion. The model relies on collaboration between government, NGOs, and the private sector, with continuous support essential for sustained impact. Conclusion: There is a unique opportunity to transform the rural agricultural landscape in Bangladesh through ICT integration in the maize value chain—specifically in improving market access and storage solutions. The MaizeConnect model can overcome key challenges including post-harvest losses, market inefficiencies, and the integration of smallholder farmers into a more profitable value chain.

The economic value of seasonal weather and climate services for maize farmers in Manicaland Province of Zimbabwe

Most rural areas in Zimbabwe are extremely vulnerable to changing climatic conditions, particularly droughts, which threaten smallholder farmers' livelihoods. Seasonal weather forecast services can help farmers adapt, optimise production, and implement risk reduction strategies. To support increased investment in these services, this study seeks to provide quantitative evidence on the economic value of locality-specific seasonal weather forecasts by eliciting maize producers' willingness to pay (WTP) through the contingent valuation approach. The results of the study show that among 502 farmers, 68 % would pay for seasonal weather forecasts, highlighting their perceived economic value and practical utility in agricultural decision-making. On average, farmers were willing to pay one (1) United States dollar (US$1) per month for seasonal weather forecast services. Extrapolating this demand nationally, we estimate an annual economic value of around US$ 53.2 million for these services. This valuation underscores the substantial economic benefits that weather and climate services could offer to Zimbabwe's agriculture sector, justifying the case for increased resource allocation towards the delivery of location-specific weather forecasts. Using the Heckman selection model, the study further identified that maize producers' climate change perceptions, radio ownership, and prior participation in agricultural policy development significantly increased their likelihood of paying for seasonal weather forecasts. These factors highlight the role of both access to information and engagement in policy processes in shaping farmers' valuation of seasonal weather forecasts. Establishing district-level climate change dialogue platforms can significantly enhance maize producers' awareness of climate change, deepen their understanding of the value of weather forecasts, and encourage their participation in policy-making processes. By creating spaces for knowledge exchange and farmer engagement, these platforms not only support informed farm decision-making but also help tailor climate services to farmers' needs. Nevertheless, farmers from the Ndau ethnic group and those in remote areas showed reluctance to pay for seasonal weather forecasts, indicating that factors like ethnicity and remoteness affect WTP. This reluctance highlights how social marginalisation and inadequate infrastructure in remote areas limit access to weather information, thereby reducing farmers' perceived value of these services. Enhanced telecommunication infrastructure and radio signals in rural areas, especially community radios, could help to expand the access and tailoring of forecast messages in local languages, making it understandable and thus supporting informed decision-making across diverse farming communities.

Spatial Spillover Effects of Smallholder Households’ Adoption Behaviour of Soil Management Practices Among Push–Pull Farmers in Rwanda

Push–pull technology (PPT) integrates maize with the legume fodder Desmodium sp. and the border crop Brachiaria sp., aiming to enhance maize production in Rwanda. Despite its potential, the adoption of complementary soil management practices (SMP), vital for PPT’s success, remains low. This study employs spatial econometric methods to evaluate the determinants of SMP adoption and the interdependencies in decision-making among PPT-practicing farmers. We constructed a spatial weight matrix based on a global Moran’s I index and identified optimal model parameters through principal component analysis. Utilizing a spatial Durbin probit model (SDPM), we assessed the spatial interdependence of SMP adoption decisions among maize farmers. Our findings reveal significant spatial dependence in SMP adoption within a 1.962 km radius, with improved seed usage, household income, yield, farmer group membership and size of land cultivated being key factors positively influencing adoption. We propose a “nonequilibrium promotion strategy” to enhance SMP adoption, emphasizing the establishment of pilot regions to broaden outreach. Additionally, fostering technical training and selecting farmers with adequate resources as demonstration leaders can enhance spatial spillover effects. This research provides insights for developing policies to scale up push–pull technology in Rwanda and across Sub-Saharan Africa.

Explicating the Role of Agricultural Socialized Services on Chemical Fertilizer Use Reduction: Evidence from China Using a Double Machine Learning Model

Reducing chemical usage, particularly chemical fertilizers, is a crucial measure for advancing sustainable agricultural development. This study utilized field survey data from 894 maize farmers across three northeastern provinces of China. A double machine learning modeling framework was established to empirically examine the impact and mechanism of agricultural socialized services on chemical fertilizer use of farm households. The model addresses numerous stringent constraints of conventional causal inference models and effectively mitigates the “curse of dimensionality” issue. Current research indicates that agricultural socialized services can substantially decrease chemical fertilizer use among farmers. Further investigation reveals that these services facilitate this reduction by enhancing the mechanization level, promoting the use of organic fertilizers, and providing a labor substitution effect. The region heterogeneity test indicates that the impact of agricultural socialized services is more pronounced in Liaoning and Heilongjiang provinces geographically. Regarding the heterogeneity analysis of food crop income levels, agricultural socialized services can decrease chemical fertilizer use among farmers more effectively with elevated food crop income levels. Consequently, the findings imply that the socialization of agricultural services has substantial potential to be an effective chemical fertilizer reduction strategy to support the agricultural green transition, which can be enhanced through promoting the degree of mechanization, organic fertilizer application, and labor division and specialization.

Keeping toxigenic Aspergillus section Flavi and aflatoxin contamination at bay by deploying atoxigenic-based biocontrol products during production of groundnut and maize in Mozambique.

Aflatoxins, produced by aflatoxigenic Aspergillus section Flavi fungi, commonly occur in groundnut and maize grown in Mozambique and have long been associated with high prevalence of liver cancer, stunting, and restricted access to lucrative international markets. Effective aflatoxin control options in the country are limited and not adequately explored. Biocontrol products based on atoxigenic strains of A. flavus provide viable aflatoxin mitigation measures but require development for Mozambique. Four hundred and sixty-eight (468) and 558 groundnut and maize farmers, respectively, voluntarily evaluated the effectiveness of two biocontrol products (Aflasafe MWMZ01 and Aflasafe MZ02), each containing as active ingredients four distinct atoxigenic isolates of A. flavus belonging to native vegetative compatibility groups (VCGs), at preventing aflatoxin contamination and displacement of aflatoxigenic fungi for 2 years in various agro-ecologies. Most groundnut and maize treated with the biocontrol products were below maximum levels for food in the European Union (EU; 85%; p < 0.01) and the United States (US; 99%; p < 0.01). In contrast, most non-treated maize and groundnut (ranging from 38 to 70%; p = 0.05) were above the EU and US maximum allowable levels for food. Aflatoxin reductions ranged from 78 to 98% (p < 0.01) in treated groundnut, and from 61 to 93% (p < 0.01) in treated maize. Toxigenic fungi were almost completely displaced from soils and crops by the applied atoxigenic active ingredients. This study revealed that the atoxigenic based biocontrol technology is effective in Mozambique at displacing aflatoxigenic fungi and reducing aflatoxin accumulation in both groundnut and maize but a combination with other management tools is encouraged for better retention of crop quality along the value chain.

Evaluation of Rabi Maize-based Intercropping System for Augmenting the Productivity and Profitability of Rabi Maize under Irrigated Conditions of Bihar

Background: A combination of maize and legume, cabbage and potato in intercropping benefits the agricultural production system due to different peak period of growth and synergistic effects, which reflected into yield advantage. In order to reduce nutritional competition and the yield gaps between actual production and production potential for both crops in the intercropping system, more information is required for the optimization of maize-based intercropping systems. So, keeping above fact in mind, the present study was undertaken to find out the suitable rabi maize based intercropping system for augmenting productivity and profitability of maize. Methods: A field experiment was conducted on the farmer’s field of selected villages of KVK Bhagalpur (on-farm trials) during the winter (rabi) season of 2020-21 and 2021-22 on rabi maize to validate, refine and popularize the technology developed at Bihar Agricultural University, Sabour, Bhagalpur (Bihar) and ICAR-Indian Institute of Maize Research (IIMR), Ludhiana, for enhancing the productivity and profitability of rabi maize. The experiment, comprising four treatments, viz., sole rabi maize (farmer’s practice), maize + potato (1:1 row ratio), maize + vegetable pea (1:2 row ratio) and maize + cabbage (1:1 row ratio), was arranged in a randomized block design (RBD) with five replications. All five farmers selected for experimentation were treated as replications. Result: Experimental results revealed that all three intercropping associations of maize + vegetable pea (1:2 row ratio), maize + potato (1:1 row ratio), maize + vegetable pea (1:2 row ratio) and maize + cabbage (1:1 row ratio) produced significantly higher maize equivalent yields than the sole crop of rabi maize. However, among the intercropping systems, maize + vegetable pea (1:2 row ratio) produced the highest maize equivalent yield (241.0 q/ha) and significantly incurred the highest net return (322093 ₹ /ha), as well as a higher B: C ratio (6.04) than the rest of the intercropping systems as well as sole crop of rabi maize.

Stochastic Frontier Analysis of Technical Efficiency of Smallholder Maize Farmers in Morogoro Municipality: A Reflection from RIPAT Program

This study looks into the elements that influence maize production and technical efficiency among households participating in the RIPAT SUA Project in Morogoro Municipality, using stochastic frontier analysis for the 2022 – 2023 season. The focus was on socio-economic characteristics, land size, seed usage, use of fertilizer extension services, training from the project, and education. The primary objective was to examine the factors influencing maize production and efficiency by evaluating socioeconomic aspects and specific agricultural techniques. A total of 110 households were surveyed with standardized questionnaires. Socioeconomic data was collected, key variables were evaluated and key variables were analyzed using descriptive statistics and stochastic frontier analysis. The results reveal that land size harms productivity (β = -0.436, p &lt; 0.001), whereas improved seed usage has a positive impact (β = 0.401, p = 0.016). Education level (β = -1.168, p = 0.002) and agriculture experience (β = -0.016, p = 0.049) considerably reduce technical inefficiency, insisting on the importance of education interventions. Additionally, 40% of households have access to VSLA, revealing financial problems. While 94.55% of households got training, only 18.18% received extension services which could hamper the best productivity. Every household reported owning land and using seeds highlighting that they had the necessary materials for maize production. Regarding technical efficiency, Magadu ward high score of 5%, while Kauzeni has the lowest at 1.9% suggesting significant disproportions in productivity among wards. These findings emphasize the importance of focused initiatives to improve agriculture productivity through enhancing farmer education and training, experience, and increased access to finance. These strategies are critical for improving maize productivity and addressing food security issues among households participating in programs like the RIPAT SUA initiative hence will increase agricultural efficiency and contribute to more farmer-sustainable farming methods throughout the region

SOCIO-ECONOMIC DETERMINANTS OF INTEGRATED SOIL FERTILITY MANAGEMENT (ISFM) PRACTICIES CHOICE AMONG MAIZE FARMERS IN ADAMAWA STATE, NIGERIA

This study was carried out to analyzed socio-economic determinants of Integrated Soil Fertility Management (ISFM) practices choice among maize farmers in Adamawa State, Nigeria. Using a multi-stage sampling procedure, 206 maize farmers were selected and interviewed using a structured questionnaire. Descriptive statistics and multinomial logit regression models were used to analyze the data collected. Findings revealed that majority of the farmers (about 60%) fell within the 20-40 years and they were predominantly male (62.1%), married (82.0%), and had a secondary education (40.3%). Farmers operated on an average farm size of 1.70 hectares. Majority of the maize farmers in the study area used intercropping with legumes (94%), organic manure (87%) and improved maize seed (79%) ISFM practices, the least practiced ISFM among the farmers were minimum tillage, crop residue retention and use of crop rotation. Socio-economic factors that were significant (P &lt; 0.05) and positively influenced ISFM practices used among maize farmers were annual income, education level, and household size. Meanwhile gender (sex) have negative and significant (P &lt; 0.05) influence on minimum tillage practice by the maize farmers. The study concludes on moderate use of ISFM practices among maize farmers in the study area. It was therefore be recommended that organized farmer’s programmes should be targeted toward educating the farmers on ISFM practices benefits and improving their income so as to facilitate adoption of ISFM practices for sustainable farm operation.

ANALYSIS OF SMALL-SCALE MAIZE FARMERS PARTICIPATION IN COMPREHENSIVE AGRICULTURAL REVOLUTION PROGRAMME (ZACAREP) IN ZAMFARA STATE, NIGERIA

The study analysed small-scale maize farmer’s participation in Zamfara comprehensive agricultural revolution programme (ZACAREP) in Zamfara State Nigeria. Multi-stage random sampling procedure was used to select 160 respondents for the study and data were collected using structured questionnaires. Descriptive statistics, Likert scale and Poisson regression model were used to analyse the data. The study revealed that, majority (75%) of the respondents were males and more than two third (61.9%) were not formally educated. Among the perceived factors that influence decision to participate in ZACAREP by farmers, refunding with products after harvest (

Assessing the Effectiveness of Climate-Smart Irrigation Practices in Improving Household Income Among Smallholder Maize Farmers in Botswana

Assessing the Effectiveness of Climate-Smart Irrigation Practices in Improving Household Income Among Smallholder Maize Farmers in Botswana

Assessment of Socio-Economic Determinants of Maize Production among Smallholder Farmers in Nassarawa State, Nigeria

The study focused on assessment of socioeconomic determinants of maize production among smallholder farmers in Nasarawa State. A multistage sampling technique was used for the selection of 171 small holder farmers for the study. A well-structured questionnaire containing both open and closed ended questions was used to collect the data for the study descriptive statistics such as percentage and frequencies and multiple regression analysis were used to achieve the objectives of the study. The socioeconomic result of the smallholder maize farmers in showed that the majority (36.3%) of the farmers were within the age range of 31-40 years of age and were mostly 76.6%) male farmers with the majority married and literate. Also, a greater number (66.1%) were members of association, 71.3% had farming experience between the range of 16-20 years with household size of 4-6, cultivating average farm size of 2-3 acres, had good contact with extension agents though only 4.1% had access to credit facility. The result of the multiple regression analysis showed that farm size, educational status and household size have positive significant effect on the output of maize at 1% and 10% level of significance respectively. The maize production technologies adopted by the majority (88.4%) of the farmers were herbicides and improved variety while the major constraints were high cost of labour, high cost of inputs and poor credit facility. The federal Government should create an enabling environment that guarantees available farmland to farmers since farm size is a critical determinant to maize production.

Impacting Arable Farmers’ Perception of Processed Organic Fertilizer Use through Farm Demonstration: Evidence from Maize Farmers in Ogun State, Nigeria

Fertilizer use supports productivity in arable farming. However, improper use of inorganic fertilizers can harm the environment, accelerate climate change and slow down the achievement of the 13th SDG. This study examined the use of farm demonstration in improving maize farmers’ perception of organic fertilizer use in the five major towns in Ikenne LGA of Ogun state. Sixty-five maize farmers were selected for the study using multistage sampling technique. Demonstration plots were established near the farmers to observe the agronomic impact of organic fertilizer use. Results showed that respondents’ average farm size was less than 1 hectare, 58% had undulating or sloppy lands which are vulnerable to degradation. Only 22% of the farmers mostly use organic fertilizers which they source from unprocessed animal waste. Only 32% of the farmers are aware of commercially processed organic fertilizers. Using the pair-sample t-test, the perception level of the farmers at the end of the demonstration was significantly higher than before the demonstration (t = 14.87, p &lt;0.05). The study recommended that perception enhancing intervention be introduced to farmers in order to increase the use of clean and safe commercially available fertilizers.

Impacts of multivalued interventions on maize farmers’ welfare: Evidence from SIPMA development project in Ghana

Recent research has highlighted the significance of agricultural development programmes in Sub-Saharan Africa for enhancing production, food security, and farmer welfare. However, these studies frequently investigate the effects of a single intervention rather than a combination of interventions. This study examines the impact of three interventions (credit access, structured market, and entrepreneurial training) on maize yield, food security, food expenditure and non-food expenditure in Ghana. We utilized multivalued inverse probability weighted regression correction, and propensity score matching with data from the Smallholder Inclusive Productivity and Market Access (SIPMA) agricultural development programme on 477 maize farmers. Participation in SIPMA interventions significantly increased maize yields, farm income, food spending, and non-food spending. For smallholder farmers, participation in a combination of input credit provision, structured market, and entrepreneurial training results in the highest yield, farm income, and non-food expenditures, while participation in entrepreneurial training alone results in a lower yield. Our empirical evidence suggests that the interventions should be expanded to other communities because the project's characteristics are distinctive in terms of fostering community engagement and collaboration with local/regional institutions.

PENGARUH MODAL SOSIAL TERHADAP KAPASITAS MANAJERIAL PETANI JAGUNG DI DESA UMBA KECAMATAN NAPANO KUSAMBI KABUPATEN MUNA BARAT

This study aims to ascertain the social capital and managerial capacity of farmers, as well as to determine the influence of the social model on the managerial capacity of corn farmers in Umba Village, Napano Kusambi Subdistrict, West Muna Regency. The research population comprises all individuals engaged in the cultivation of corn in Umba Village, amounting to a total of 32 individuals. The sample was selected using the census method, resulting in a sample size of 32 respondents for this study. Data were collected through observation, surveys, and structured interviews, with the use of a questionnaire. This study employed a quantitative approach. The variables under investigation are divided into two categories: social capital and managerial capacity among farmers. The data were subjected to two distinct forms of analysis. Initially, a quantitative descriptive analysis was conducted utilising the class interval formula to delineate the prevailing conditions pertaining to social capital and managerial capacity among maize farmers. Subsequently, a multiple linear regression analysis was employed to ascertain the influence of social capital on the managerial capacity of maize farmers. The multiple linear regression analysis is comprised of three tests: the T-test, F-test, and determination test. The findings indicate that the utilization of social capital among corn farmers in Umba Village is classified as favorable. This is evidenced by the presence of a robust level of trust, a commendable application of norms, and a relatively strong network of social connections. The managerial capacity of maize farmers is categorized as good, as evidenced by their effective maize farm planning and organization. However, there are areas for improvement, particularly in the dimensions of maize farming implementation and supervision, which remain in the poor category. Social capital has a significant positive effect on the managerial capacity of maize farmers, amounting to 29.1%, with 70.9% influenced by other factors.

PERAN KELOMPOK TANI DAN PENGGUNAAN SARANA PRODUKSI PADA KEGIATAN USAHATANI JAGUNG DI DESA KOMBA-KOMBA KECAMATAN KABANGKA KABUPATEN MUNA

The issues encountered in maize farming activities in Komba-Komba Village can be attributed to several factors. Firstly, the knowledge and expertise of farmers in this area remain limited. Secondly, the role of farmer groups is not yet fully realised. Thirdly, the utilisation of production resources, including seeds, fertilisers and pesticides, is not optimised. The objective of this study was to ascertain the utilisation of production facilities and the function of farmer groups in maize farming activities in Komba-Komba Village, Kabangka Subdistrict, Muna Regency. The research informants were selected purposefully, with specific criteria in mind. Consequently, the research informants totaled 13 individuals, comprising farmer group administrators, specifically two farmer group leaders, two secretaries, two treasurers, six farmer group members, and the village head. Data were collected through observation, in-depth interviews, and document analysis using interview guides. This study focuses on the utilization of production facilities and the role of farmer groups in maize farming. The research employs a qualitative descriptive analysis approach to data analysis, comprising three stages: data reduction, data presentation, and conclusion drawing. The findings indicate that farmer groups in Komba-Komba Village serve as a conduit for collaboration in maize farming activities. This is evidenced by the presence of groups that engage in joint efforts between the farmer group leaders and members during the farming process. Furthermore, the role of farmer groups has not been as effective as the function of farmer groups. In terms of production facilities, farmers in Komba-Komba Village provide these for maize farming activities, including seeds, fertilizers, and pesticides, using their own capital.

Determinants of profit among maize farmers in Osogbo ADP zone of Osun State, Nigeria

Maize output in Nigeria is declining and worsening economic situations continue to afflict rural households increasing the level of food insecurity. This study examined the determinants of profit among maize farmers in Osogbo ADP zone of Osun State, Nigeria. Primary data were sourced using a well-structured questionnaire from a total of 120 maize farmers. A two-stage sampling procedure was employed to select the farmers. The analytical tools used were descriptive statistics, farm budgetary techniques and regression analysis. The results showed that maize cultivation was dominated by male farmers with an average age of 50 ± 9.4 years. Additionally, less than 30.8% of the maize farmers had formal education above secondary school. The farming experience of the maize farmers was 14.7 ± 5.3 years and the average farm size was estimated at 7.85 ± 2.15 acres. The average farm income was N207 314.40 ± 23 290.95 with the Benefit-Cost Ratio (BCR) of 2.24. The major constraints of maize production, ranked based on their higher values of WMS, were the high labour costs, expenditures for pest and disease control, and the high costs of fertilizers The determinants of farm income that had positive relationship and were significant at 1% level of significance include years of formal education, expenditure on fertilizer while age of the framers negatively influenced the farm income. Also, the farm size and years of farming experience were positive and statistically significant to farm income at 5%. The study suggests a policy focus of training farmers in modern farming system and implement sustainable farm inputs subsidy programs. Keywords: determinants, profit, maize, farmers, Nigeria

MkulimaGPT: Equitable AI Use Via a Swahili Chatbot for Maize Farming System in Tanzania

The maize sector in Tanzania is crucial for the country's food security and economic stability. However, farmers face various challenges, including diseases that reduce yields and limited access to information. To address this, an innovative solution called MkulimaGPT has been developed, it is a text and voice chatbot that uses generative Artificial Intelligence (AI) technology and is accessible through WhatsApp. The platform offers real-time agricultural guidance in Swahili, overcoming language and literacy barriers. It is available through a local phone number and designed to cater to Tanzania's digital landscape by utilizing the widespread mobile network. MkulimaGPT blends generative AI's capabilities with the comprehensive agricultural knowledge base, ensuring its advisory services are contextually rich and technically astute. It is an example of inclusive AI and bridges the gap between farmers and extension services, fostering inclusivity for marginalised groups, particularly women, with a commitment to deliver real-time, and actionable insights for Tanzania's maize farming.

Does digital finance improve welfare effects of maize farmers’ productivity gains?

PurposeIn Burkina Faso, maize is a key component in farm households’ food security and welfare. However, maize productivity in the country is low and productivity improvements do not necessarily result in better living conditions. This paper aims to establish linkages between maize productivity and welfare by considering the context of digital finance adoption for farmers in Burkina Faso.Design/methodology/approachFor this purpose, we use an endogenous switching regression approach on the Burkina Faso’s Living Standard Measurement Survey of 2018.FindingsOur estimates show that digital finance adoption enhances the transmission of productivity gains to farm households’ welfare, with the welfare elasticity of maize productivity almost twice higher for digital finance adopters.Social implicationsOur findings highlight the importance of increasing the access to digital finance to improve farm household welfare.Originality/valueThis manuscript makes the valuable contribution of analysing the heterogeneity of the transmission of agricultural productivity to welfare, with a focus on the identification of the role of digital finance.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2024-0077

Economic Benefits and Uses of Indigenous Seasonal Weather Forecasts in Zimbabwe

This study presents a seminal contribution regarding the economic value of indigenous seasonal weather forecasts in Zimbabwe. Many farmers (58%) use indigenous seasonal weather forecasts to make maize farming decisions such as selecting suitable varieties. The main indicators used for indigenous seasonal weather forecasts are flowering and fruition of specific trees. Based on travel cost analysis, which incorporates a multi-purpose visit scenario, the study establishes the economic importance of indigenous seasonal weather forecasts with a consumer surplus of US$1,044 per year among the 290 farmers using the forecasts. There is therefore a need to integrate indigenous weather forecasts into national seasonal weather forecasting and disaster risk reduction systems to complement modern seasonal weather forecasts. Co-production of seasonal weather forecasts with farmers is proposed in this regard. This further calls for the need to digitally document, visualize, and disseminate indigenous seasonal weather forecast indicators to a wider audience to increase their use.

DETERMINANTS OF FARMER’S PERCEPTION OF PROSTEPHANUS TRUNCATUS (HORN) DAMAGES AND LOSSES ON STORED MAIZE IN TOGO AND BENIN (WEST AFRICA)

Prostephanus truncatus is one of the most damaging post-harvest pests of stored maize in Africa. Research Institutions disseminated Various control strategies during the 1990s in West Africa with significant results. What is farmers’ perception of this pest in decades after those control strategies? This study aimed to assess determinants of farmers’ perception of current damages and losses caused by Prostephanus truncatus on stored maize in southern of the two countries (Benin and Togo). 300 maize farmers (150 from Togo and 150 from Benin) were randomly selected from 10 villages per country. Descriptive statistics were used in addition to Logit and Tobit regression analysis. The results showed that 38% of farmers (35% in Togo and 41% in Benin) still perceive Prostephanus truncatus as the most damaging pest of stored maize. Logit's results showed that factors influencing farmers’ perception of Prostephanus truncatus were group membership, contact with extension agents, and period of maize harvesting. The results from the Tobit regression model showed that factors such as the maize variety, the form of maize storage (with husk), and the storage period influence the extent of damage and loss caused by Prostephanus truncatus. Farmers still perceive Prostephanus truncatus as the main post-harvest pest causing high damage and losses on maize. It is recommended that further dissemination of maize storage technology to reduce postharvest losses.