Research Article
Technical Efficiency of Rice Producers in Mali: A Comparative Analysis of the Office Niger Zone and the Baguinéda Irrigated Perimeter Office
Issue:
Volume 10, Issue 4, August 2025
Pages:
149-157
Received:
28 March 2025
Accepted:
9 June 2025
Published:
30 June 2025
Abstract: As in most sub-Saharan African countries, agriculture is the dominant economic sector in Mali, and the potential for rice production is also high but remains largely untapped. Although achieving potential production depends on many variables, farmers in the two production areas studied are generally below the global efficiency score. The objective of this comparative study is to evaluate the productive performance of rice farmers in the Office du Niger zone compared to those in the Baguinéda Irrigated Perimeter Office. To do this, using program 4.1, we used the maximum likelihood method to estimate both the production function and the inefficiency function. The analysis of production frontiers shows that the variables Area, Seed, Fertilizer, and Herbicide have a significant effect on the level of production. As for the analysis of rice farmers' technical efficiencies, it appears that farmers in the Office du Niger and those in the Baguinéda Irrigated Perimeter Office operate at 0.79 and 0.72 of their productive capacity, respectively. Furthermore, the analysis of determinants shows that membership in a farmers' organization, ownership of equipment, main activity, technical support, and marital status are major factors in improving the efficiency of these rice farmers. There is therefore potential for increasing production without any additional inputs. The authorities responsible for rice development should therefore place particular emphasis on supplying farmers with agricultural equipment and materials, encouraging the creation of farmers' organizations, and intensifying rice production.
Abstract: As in most sub-Saharan African countries, agriculture is the dominant economic sector in Mali, and the potential for rice production is also high but remains largely untapped. Although achieving potential production depends on many variables, farmers in the two production areas studied are generally below the global efficiency score. The objective ...
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Research Article
Factors Influencing the Choice of Aflatoxin-inhibiting Technologies Among Smallholder Groundnut Farmers in Elgeyo Marakwet and Baringo Counties in Kenya
Issue:
Volume 10, Issue 4, August 2025
Pages:
158-169
Received:
2 June 2025
Accepted:
16 June 2025
Published:
7 July 2025
DOI:
10.11648/j.ijae.20251004.12
Downloads:
Views:
Abstract: Access and use of Aflatoxin-inhibiting technologies among smallholder farmers can improve their livelihoods and reduce post-harvest losses due to Aflatoxin contamination. However, the use of technologies including drying technologies, shelling, hermetic storage, resistant seeds, Aflasafe, and Good Agricultural Practices (GAP) remains low among smallholder groundnut farmers. This study assesses the factors influencing the choice of Aflatoxin-inhibiting technologies for increased production and marketability of groundnuts in farming households. Data analysis was conducted using SPSS and STATA 18. Descriptive statistics were used to examined current practices, while a multi-stage sampling approach was used to select 384 smallholder farmers from Elgeyo Marakwet and Baringo Counties in Kenya. A multivariate probit model was used to determine the factors influencing the choice of Aflatoxin inhibiting technologies. The study highlights that farmers’ decision to adopt Aflatoxin-inhibiting technologies was significantly influenced by gender, sales price, group membership, fertiliser use, household size, land size, household income, extension access, use of improved groundnut varieties and distance to market. The study provides insights into the dynamics of adoption of Aflatoxin-inhibiting technology. It underscores the need for strengthening group membership, extension service delivery and social network programs for farmer information dissemination to promote adoption and enhance agricultural productivity to improve the livelihoods of smallholder farmers in Kenya.
Abstract: Access and use of Aflatoxin-inhibiting technologies among smallholder farmers can improve their livelihoods and reduce post-harvest losses due to Aflatoxin contamination. However, the use of technologies including drying technologies, shelling, hermetic storage, resistant seeds, Aflasafe, and Good Agricultural Practices (GAP) remains low among smal...
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Research Article
Forecasting the International Market Prices for Rice, Corn and Soybeans Using ARIMA Time Series Modelling
Issue:
Volume 10, Issue 4, August 2025
Pages:
170-182
Received:
4 June 2025
Accepted:
16 June 2025
Published:
7 July 2025
DOI:
10.11648/j.ijae.20251004.13
Downloads:
Views:
Abstract: Rice, corn, and soybeans are among the most widely cultivated crops, making them crucial for global food security and the economic well-being of many countries. Like many other crops, the global prices for these commodities are prone to fluctuations due to unfavorable weather conditions, natural disasters (like flooding), global demand, and economic crises. Consequently, their prices are subject to significant changes and volatility. Forecasting and modelling these prices offer valuable insights to policymakers and local growers within the agricultural sector. While there is a plethora of studies focusing on forecasting prices based on data obtained for a specific locality, country, or region, there is a paucity of publications that take on a more global outlook for rice, corn, and soybeans. The objective of this study is to use an Autoregressive Integrated Moving Average (ARIMA) process to model and forecast the international market prices of milled rice (5% broken), corn, and soybeans. We relied on World Bank data covering the period from 1988 to 2018 to construct several time series models. The average prices for milled rice, corn, and soybeans are $344.47, $144.48, and $334.72 (USD) per metric ton, respectively. The results of the model selection procedure indicate that the ARIMA (5,1,4), ARIMA (6,1,3), and ARIMA (6,1,1) models best fit the prices of milled rice, corn, and soybeans, respectively. Furthermore, these models offer the best in-sample and out-of-sample performances. The accuracy of the projected values, derived from the chosen models, was evaluated by calculating several metrics, including the mean absolute error (MAE), mean squared error (MSE), root mean square error (RMSE), and mean absolute percentage error (MAPE). This paper highlights the utility and applicability of the ARIMA model as a powerful tool for forecasting agricultural prices. Our modeling framework could enable governments and agribusinesses to (a) better anticipate global price fluctuations, (b) optimize trade decisions, (c) strengthen food security planning, and (d) engage in more sustainable agriculture.
Abstract: Rice, corn, and soybeans are among the most widely cultivated crops, making them crucial for global food security and the economic well-being of many countries. Like many other crops, the global prices for these commodities are prone to fluctuations due to unfavorable weather conditions, natural disasters (like flooding), global demand, and economi...
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,
George Owour
