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The purpose of this paper is to ascertain if practising healthy lifestyles improves the technical efficiency of farms in Kwara state, Nigeria. In theory, all deviations from the optimum level of output are due to random effects and inefficiency of producers in which their health plays a key part and is dependent on the kind of lifestyle practiced whether healthy or unhealthy.

Cross-sectional data were employed through a three-staged sampling technique to pick 320 arable crop farmers across the state using a well-defined questionnaire. Data analysis was carried out using descriptive statistics, healthy lifestyles index (HLI), stochastic production frontier (SPF) and propensity score matching (PSM).

First, the analysis showed that about one-third of the sampled arable crop farmers practised healthy lifestyles. Second, the average technical efficiency of arable crop production for farmers who practised a healthy lifestyle was 0.893, and the level of technical inefficiency of the farms was determined by health-related lifestyle status, number of day's illness and educational level. Third, technical efficiency was improved by 0.00431067 for farms whose farmers practised a healthy lifestyle.

Rather than seeing that technical efficiencies of farms are attributed to farm characteristics, inputs used and socioeconomic characteristics alone, the findings suggest that technical inefficiencies of arable crop farmers were also due to the kind of lifestyle practised, which was evidenced in the increased efficiency for farmers who practised healthy lifestyle.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0353

The purpose of this paper is to empirically analyze the determinants of arable crop farmers’ awareness to causes and effects of climate change in south western Nigeria.

Using primary data, 150 arable crop farmers in Ogun State were selected through a multi stage sampling technique. Survey method was used to elicit information on farmers’ socioeconomic, production characteristics, and their level of awareness to causes and effects of climate change. The data collected were analyzed using descriptive statistics, environmental awareness index (EAI), and Tobit regression analysis.

Most (81.08 percent) of the arable crop farmers were males with an average household size of eight persons, farming experience of 24 years and farm size of approximately 1 ha. The computed climate change EAI showed that only 47 percent of the respondents were aware of causes of climate change, while 68 percent were aware of its effects. Results further revealed that age, income from secondary occupation (p < 0.10), marital status, household size (p < 0.05), years of farming experience, frequency of extension contact, land size in hectare, and farm revenue (p < 0.01) were the determinants of respondents awareness to causes and effects of climate change.

The study recommended among others that, awareness should be created among arable crop farmers on climate change causes and effects for appropriate mitigation actions to be taken for improved agricultural productivity.

The study provided new empirical evidence on the awareness level of respondents to causes and effects of climate change on their production activities and livelihood in general. Implications for policy will be to provide a public education program that will target females, the poor, the illiterate, and the people in the economically active age group among others in order to create awareness and provide information and adequate knowledge on the causes and effects of climate change for proper mitigation and adaptation options.

This paper evaluates the impact of socio and demographic factors on the multidimensional poverty of smallholder arable crop farming households in Nigeria.

Data were drawn from the second wave of the LSMS-Integrated Surveys on Agriculture General Household Survey Panel 2012/2013. The methods adopted in analysing the data were descriptive statistics, Alkire and Foster Method (AFM) and logit regression model.

The result shows that 84.34% of the households were headed by a male while 80.26% of the respondents were married with a mean household size of seven persons. The multidimensional poverty of arable crop farm households in Nigeria is 0.60, while the adjusted headcount ratio (MPI) is 0.27, with an average intensity of 0.45. We found that deprivation in the dimension of living standard accounted for 45.5% of the overall multidimensional poverty index (MPI). The result of the logistic regression indicates that household location, gender, household size and non-farm income are negatively correlated to poverty. The factors that increase poverty among households are the age of the household head and access to extension services.

The study presents an alternative means of assessing poverty among smallholder arable crop farming households in Nigeria. This study recommends that policymakers should focus more on improving the living standard of arable crop farming households to reduce poverty in rural areas. Similarly, concerted efforts should be made towards providing adequate health care and improved sanitation, supply of electricity and educational training that goes beyond primary education for farming household members.

The purpose of this paper is to examine the effect of the Ministry of Food and Agriculture (MoFA) Block Farm Credit Programme (BFCP) participation on crop output in four districts in the Northern region of Ghana.

Structured questionnaires were used to collect data from 240 beneficiary and non-beneficiary farmers of BFCP. The treatment effect model that accounts for selectivity bias was employed to examine the socioeconomic determinants of farmers’ decision to participate in the BFCP and the effect of BFCP participation on crop output.

Even though the BFCP participation increases output, inadequacy and late delivery of BFCP inputs, low publicity about the programme and difficulty in accessing the inputs from the districts agricultural officers are factors that prevent the full realization of the benefits of the programme. Improving extension services to create more awareness and a re-introduction of the BFCP to make inputs available and affordable to farmers can help boost farm productivity.

The positive effect of the BFCP means that the provision of low-cost production credit has the potential to increase productivity and improve incomes. Hence, MoFA should endeavour up scaling and properly managing the scheme.

This study is the first to evaluate the BFCP in Northern region of Ghana, particularly in relation to its contribution to crop value. The findings are very useful to advise policy by taking account of the programme deficiencies and enhance effectiveness.

The purpose of this paper is to analyze smallholder farmers’ perceptions of climate change and its adverse effects, identify major adaptation strategies used by farmers and analyze the factors that influence the choice of adaptation strategy by smallholder farmers in eastern Ethiopia.

The study was based on a cross-sectional survey of 296 sample households selected from three districts in east Ethiopia. Data were collected with the aid of a semi-structured questionnaire and review of literature, documents and databases.

The study provides empirical evidence that majority of farmers in the study area are aware of climate change patterns and their adverse effect on income, food security, diversity, forest resources, food prices and crop and livestock diseases. In response to these adverse effects, major adaptation strategies used by farmers include cultivating different crops, planting different crop varieties, changing planting dates, use of soil and water conservation techniques, conservation agriculture practices and engaging in non-farm income activities. Choice of adaptation strategies are influenced by gender of household head, household size, farm size, distance from market and number of farm plots.

The study suggests that developing more effective climate change adaptation strategies need support from the government. Such an effort needs provision of the necessary resources such as credit, information and extension services on climate change adaptation strategies and technologies, and investing in climate smart and resilient projects.

The study adopts multivariate probit model that models farmers’ simultaneous adaptation choice behavior which has been rarely addressed by previous researches.

This paper aims to analyze the effects of crop specialization on agricultural productivity and commercialization for farmers who produce high-value crops in the Northern Savannah Ecological Zone of Ghana.

The study used the USAID/Ghana Feed the Future (FTF) survey, which collected data on high-value crops (i.e. maize, rice and soya). Data for the analysis consists of 2,903 farm households. The study utilized the three-stage generalized method of moment estimation technique to deal with the potential endogeneity of crop specialization within the context of productivity and commercialization and heteroscedasticity issues in the data.

The study found that crop specialization positively relates to agricultural productivity and commercialization, suggesting that increased crop specialization in the production of high-value stimulates productivity and opens market opportunities for farm households. These findings imply that crop specialization seems more beneficial to farmers as it significantly improves productivity and commercialization.

The study was conducted in the Northern Savannah Ecological Zone of Ghana and not the entire country.

To the best of the authors' knowledge, this study is the first to have jointly modeled crop specialization, agricultural productivity and commercialization. The main advantage of using this system approach is that it uses more information, thereby providing more precise parameter estimates.

Understanding farmers’ perceptions of how the climate is changing is vital to anticipating its impacts. Farmers are known to take appropriate steps to adapt only when they perceive change to be taking place. This study aims to analyse how African indigenous vegetable (AIV) farmers perceive climate change in three different agro-climatic zones (ACZs) in Kenya, identify the main differences in historical seasonal and annual rainfall and temperature trends between the zones, discuss differences in farmers’ perceptions and historical trends and analyse the impact of these perceived changes and trends on yields, weeds, pests and disease infestation of AIVs.

Data collection was undertaken in focus group discussions (FGD) (N = 211) and during interviews with individual farmers (N = 269). The Mann–Kendall test and regression were applied for trend analysis of time series data (1980-2014). Analysis of variance and least significant difference were used to test for differences in mean rainfall data, while a chi-square test examined the association between farmer perceptions and ACZs. Coefficient of variation expressed as a percentage was used to show variability in mean annual and seasonal rainfall between the zones.

Farmers perceived that higher temperatures, decreased rainfall, late onset and early retreat of rain, erratic rainfall patterns and frequent dry spells were increasing the incidences of droughts and floods. The chi-square results showed a significant relationship between some of these perceptions and ACZs. Meteorological data provided some evidence to support farmers’ perceptions of changing rainfall. No trend was detected in mean annual rainfall, but a significant increase was recorded in the semi-humid zone. A decreasing maximum temperature was noted in the semi-humid zone, but otherwise, an overall increase was detected. There were highly significant differences in mean annual rainfall between the zones. Farmers perceived reduced yields and changes in pest infestation and diseases in some AIVs to be prevalent in the dry season. This study’s findings provide a basis for local and timely institutional changes, which could certainly help in reducing the adverse effects of climate change.

This is an original research paper and the historical trends, farmers’ perceptions and effects of climate change on AIV production documented in this paper may also be representative of other ACZs in Kenya.

The purpose of this paper is to investigate factors affecting the adoption of agricultural technologies in Sub-Saharan Africa, specifically the role of credit market inefficiency in adoption of agricultural technologies in the region.

Most importantly, the paper applies a 2SLS model on a unique data set on nine agrarian countries from Sub-Saharan Africa’s intensification of food crops agriculture (Afrint) to provide evidence on how credit market inefficiency affects adoption of technologies in the sub region.

The study finds that the relationship between credit and technology adoption is one-way causal relation (i.e. credit access leads to technology adoption) as opposed to a two-way relation (i.e. mutual dependent relation). Further, the results indicate that credit market inefficiency can be a major barrier to the adoption of yield enhancing technologies in Sub-Saharan Africa. Further, the study showed mixed results for household variables. The results give credence to studies that highlight the importance of infrastructure and risk control in the adoption of new technologies.

The study is limited to only nine countries in Sub-Saharan Africa. Thus, the findings and interpretations should be considered as such. Further, there is the need for further research that considers all the region so as to establish whether or not there is a relationship between credit market inefficiencies and technology adoption in the region.

The policy implication is that microfinance institutions should consider scaling up their credit services to ensure that more households benefit from it, and in so doing technology adoption will be enhanced.

The main contribution of the study lies in its use of a unique data set from Sub-Saharan Africa’s intensification of food crops agriculture (Afrint) to investigation relationship between credit market inefficiency and technology adoption.

This study aims to analyze the perceptions of smallholder farmers on climate change and events and further explores climate change adaptation strategies and associated challenges. The findings provide useful information for enhancing the adaptive capacity of smallholder farmers to adjust to climate-related hazards and improve their resilience and disaster preparedness in northern Ghana.

This study uses a multistage sampling procedure and sample size of 150 farmers, the Binary Probit Model (BPM), to identify and examine the determinants of climate change adaptation strategies adopted by smallholder farmers. Also, the constraints of adaptation were analyzed using Kendall’s coefficient of concordance.

The results from the BPM and statistics of Kendall’s coefficient revealed that the farm risk level, ability to adapt, farmer’s income, age, farming experience, climate change awareness and extension visits were factors that significantly influenced the adaptation strategies of smallholder farmers (in order of importance). The majority (60%) of the farmers ranked farm risk level as the major constraint to adopting climate change strategies.

The findings of this study enhance understanding on access to relevant and timely climate change adaptation information such as an early warning to farmers during the start of the farming/rainy season to support their adaptive responses to climate change.

The purpose of this paper is to identify factors that affect farm acceptance of the new seeds. This paper develops a Bivariate Probit model with adjusted sample selection bias to analyze Chinese farmers' sequential decision‐making process in their adoption of plant new varieties (new seeds) under the new Variety Property Right Protection System.

Face‐to‐face interviews with farm households in 22 provinces were used to gather questionnaire information. A total of 341 surveys were collected and analyzed using a Bivariate Probit model adjusted for sample selection bias problems. Descriptive statistics for each selected variable used in the model are also presented.

This study concluded that farm location, land size, farm perceived dealer reputation, and farmer‐to‐farmer word‐of‐mouth information were found to be important factors that affect farm adoption of new seeds.

This study is based on first‐hand survey information collected by the researchers. Thus, the results are original and were not published elsewhere.