This study examined the determinants and constraints of mobile phone-enabled agricultural extension services among small-ruminant farmers in Northern Ghana. Cross-sectional data were collected from 406 farmers through purposive and simple random sampling methods. The data is analysed using descriptive statistics, binary logistic regression, and Kendall’s coefficient of concordance. The results show that gender, household size, farmer-based organisation (FBO) membership, and small-ruminant-rearing experience significantly influenced access to mobile-enabled extension on small ruminant production. Male farmers had 16.20 times the odds of access compared with female farmers. Each additional household member was associated with 1.91 times the odds of access, while FBO members had 3.11 times the odds compared with non-members. Each additional year of small-ruminant-rearing experience was associated with 2.35 times the odds of access. Kendall’s ranking identified inadequate electricity coverage as the most important constraint, followed by high device costs, device management costs, difficulty understanding SMS messages, and limited knowledge of mobile phones. The study recommends gender-responsive digital extension, rural electrification, local-language voice services, and integration of mobile and conventional extension systems to enhance the knowledge of small ruminant farmers in the Northern Region of Ghana. Read more

Finite transitive groups could be extended through points, lines or block as such geometric constructions were motivated through the concept of the Steiner system. The transitive extension of finite groups indicated the degree of homogeneity either by the partitioning of the groups or observing the orbits. We employed a different approach to the previous work carried out. Read more

A study was conducted to assess the factors that limit rabbit production under an intensive production system in Zanzibar. A total of 390 farmers from three districts each has 130 respondents were interviewed in a cross-sectional survey. The results revealed that 48.2% of farmers had kept rabbits and 51.8% did not, while 53.2% of the farmers kept medium breeds and 46.8% of them kept small breeds of rabbits. In terms of management systems was significant (ρ≤ 0.038) in the feeding system was 60.2% of farmers used an intensive system and 39.8% employed semi-intensive systems, whereas a higher number of farmers 88.6% of main diets fed the rabbits with green grass than 11.4% utilized kitchen wastes. In the observed marketing of rabbits and their products, the proportion of respondents who had sold rabbit parts was significantly higher (ρ≤ 0.007), that is 73.0% had sold rabbits than 27.0% who did not sell any rabbit parts. However, it was not statistically significant concerning the types of rabbit products sold and marketing challenges at ρ≤ 0.836 and ρ≤ 0.475 respectively. The disease infection was reported by 58.9% of farmers their rabbits were affected by the disease and 41.1% of them did not. However, no statistical significance was associated with the causes of disease infection at ρ≤ 0.299. Likewise, rabbit production in Zanzibar is at an immaturity stage and is constrained with many drawbacks. Therefore, proper animal husbandry practices and extension service delivery are recommended. Read more

On the premise that stakeholders in rural farmers development must understand the appropriate means of passing relevant information to farmers, this study examined the main sources of market information among rural farmers in Ogun State. It uses questionnaires to obtain quantitative and qualitative information relating to sources of marketing information, means of selling produce, place for selling produce, place for buying input and whether rural farmers in Ogun State do have up-takers for their produce. The study made use of purposive sampling of Ifo block, Simawa block, Ala block and Ado-Odo block to represent farmers from Abeokuta, Ikenne, Ijebu-Ode and Ilaro zones respectively. The results on the sources of market information were that 27.3% get marketing information from other farmers, 24.7% get information through personal enquiry, 7.3% through radio, 7.5% through buyers, 0.4% from TV, 13.7% through extension agents, 17.5% from farmers meeting and 1.5% through social media. The study concludes that rural farmers in Ogun State get market information from multiple sources. The dominant sources are other farmers, personal enquiry, extension agents and farmers meeting. The study recommends that useful information to farmers by relevant stakeholders should be through multiple choices and should include the use of extension agents and farmers' meetings. Read more

COVID-19 vaccines were developed for the prevention and control of COVID-19 globally and strong immunity will be developed if most of the world’s population accept and get vaccinated with the COVID-19 vaccine. However, vaccine hesitancy is a major threat to the control and prevention of COVID-19 in most countries especially the developing countries. The study was carried out to determine COVID-19 knowledge, risk perception and vaccine hesitancy among extension agents in Katsina State, North Central Nigeria. Due to insecurity, 23 local government areas in the state were purposively sampled across the three agricultural zones in the state. Furthermore, all the five village extension agents and one block extension supervisor in each LGA selected was considered to give a total of one hundred and thirty-eight (138) respondents for the study. Descriptive statistics such as percentage and mean, risk perception score, COVID-19 knowledge scale and a Logit regression model were used to achieve the study objectives. Results show that extension agents in Katsina State have a good knowledge of the COVID-19 vaccine and a high-risk perception towards COVID-19. However, due to trust and safety concerns, majority of the extension workers (73.2%) are still hesitant and yet to get a shot of the vaccine. The major determinants of COVID-19 acceptance include age of the extension worker, years of work experience and knowing a person infected by the virus. It can be concluded from the study that the older and more experienced extension workers can be used as a good starting point for launching a program aimed at reducing COVID-19 vaccine hesitancy among extension workers in Katsina State. The electronic media such as the Radio and Television should be used to produce jingles and skits for educating extension workers on the COVID-19 vaccine. Community and religious leaders should be empowered by the government to help clarify the misconceptions about vaccines that have pervaded communities especially in Northern Nigeria. Read more

The Laplace distribution and its extensions have been widely utilized in statistical modelling due to their ability to capture real-world data characteristics such as skewness and heavy tails. This study evaluates the performance of the classical Laplace (L) distribution against three of its variants: the Transmuted Laplace (TL), Alternative Laplace (AL), and Asymmetric Laplace (ASL) distributions. While these extensions introduce additional parameters to enhance flexibility, their empirical performance remains a subject of interest. Using three datasets Rent prices, Voltage Drop, and Nigeria’s Unemployment Rate. This study assesses model fit based on the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and Mean Squared Error (MSE). Findings reveal that the standard Laplace (L) distribution consistently outperforms its counterparts. In the Rent dataset, it achieves the lowest AIC (613.636), BIC (609.2266), and a reasonable MSE (2343.761), whereas the TL and AL distributions yield significantly higher AIC and BIC values, and the ASL distribution demonstrates an extremely high MSE (9.34 × 10¹²), indicating poor fit. A similar trend is observed in the Voltage Drop dataset, where the L distribution records the lowest AIC (201.1564), BIC (197.7293), and MSE (132.7978), while TL and ASL show excessive model instability. In the Unemployment Rate dataset, the L distribution again provides the best fit, with an AIC of 349.7985, a BIC of 345.896, and a moderate MSE of 186.4666. On average, across all datasets, the L distribution remains the most robust model, with the lowest AIC (388.197), BIC (384.284), and MSE (887.6751). The AL distribution follows closely with an MSE of 888.9518 but exhibits significantly higher AIC (2426.027) and BIC (2424.071). The ASL distribution, while demonstrating moderate AIC (1443.016) and BIC (1448.885), suffers from poor predictive accuracy with an extremely high MSE (3.19E+12). The TL distribution performs the worst, with the highest AIC (34,686.77), BIC (20,112.08), and an MSE of 76,038.22, highlighting its instability. In conclusion, this study establishes that the standard Laplace (L) distribution provides the most reliable and accurate fit across diverse datasets. While alternative forms introduce additional flexibility, their increased complexity does not necessarily yield superior model performance. Future research should explore modifications to improve the parameter stability of Laplace extensions and investigate alternative estimation techniques to enhance predictive accuracy in real-world applications. Read more