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Indigenous chicken play an important role in the livelihoods of the rural poor in developing countries. They not only act as a source of nutrition but also supplement household incomes. Despite the tremendous market opportunities available for the farmers, there are still low levels of market participation for indigenous chicken farmers in Gulu district and other parts of Uganda. In light of this, a research study was motivated to ascertain the drivers of smallholder indigenous chicken farmers’ market participation in Gulu district. Using cross-sectional data from households in selected sub counties in Gulu district, a two-stage Heckman model was used to model the decision of the smallholder farmers to participate in the market and then determine the factors affecting the value of sales thereafter. Results from the descriptive statistics showed that there were 126 market participants and 24 non-participants. Both flock size and non-farm incomes differed significantly (5%) between market participants and non-participants. The participants had a larger flock size while non-participants had more income. The results of the probit model further revealed that the first stage of market participation was significantly affected by distance of the household to the market (1%), flock size (10%), and ownership of a bicycle (1%). In the second stage (outcome model), the OLS results revealed that flock size, distance to the market and market price of indigenous chicken significantly (1%) affected the indigenous chicken farmer’s value of sales. In conclusion, creation of effective marketing systems that would help reduce transaction costs of the indigenous chicken, provision of extension and veterinary services will not only increase the flock sizes kept by the smallholder farmers but also the value of sales of indigenous chicken for the farmers that participate in the market. Key words: Heckman model, smallholder farmers, indigenous chicken, market participation, Gulu district.

Characterization of indigenous chicken production and related constraints: Insights from smallholder households in rural Kenya

Most communal farmers in Chivi district of Zimbabwe rear indigenous chickens. However, the impact of interventions by government and non-government partners remains unknown. The purpose of this study is to assess impact of indigenous chicken production in semi-arid areas with a focus on Chivi district. The research focused on indigenous chickens as the enterprise has the potential to increase rural population income and in turn improve the nutrition for the rural population. A total of 160 indigenous chicken farmers were sampled from a population of 1240 who received past interventions in trainings, feed and chicks or pullets from development partners and government using a survey questionnaire. Variables such as age, farmer experience, education, type of dwelling, maize, cattle, goats, supplementary feed, type of housing, resting of fowl run, vaccinations and type of hatching method were found to be significantly affecting sales rate. Indigenous chicken production was found to be weakly profitable as a positive gross margin was obtained. The study also revealed that value chain actors in indigenous chicken production had no processors. It was concluded that though indigenous chicken production was profitable, the above stated factors affect impact of indigenous chickens. The value chain map had no processors. Capacitating farmers on poultry management and availing credit to finance production and marketing players is important to improve indigenous chickens among smallholder farmers.

Background: Improving the well-being of small holder farmers through the promotion of improved technologies has gained increased attention in recent times. Despite the high production potential and the crop's economic importance, adoption and diffusion of barley technologies are constrained by various factors. The purpose of the study is to identify determinants of adoption of agricultural technologies in the barley-based farming system of Ethiopia, with the specific objectives of identifying factors affecting Agricultural technology package choice and assessing the inter-dependency between the technologies. Methods: The study was carried out in highland areas of Ethiopia. The study used data from the Ethiopian socio-economic survey of 693 sample households. The descriptive and econometric analytical tools were applied. The research employed the Multivariate probit model to estimate the factors that influenced the adoption of agricultural technologies choice for barley production. Results: The descriptive result of the study identified that variables, like education, family size, credit access, farm size, farm income, and farmer's age play significant roles across barley technologies. The results showed that about 66.96%, 58.59%, 75.18%, 65.17%, and 75.99% of sample house hold adopted an improved variety of barley, by using urea, DAP, chemical, manure, and crop rotation, respectively. Multivariate probit model results showed that the age of the house hold head, soil fertility, farm size, training, and transportation cost affect the adoption of barley technologies negatively and significantly. Sex of the household head, education level of the house hold head, farm income, tropical livestock unit, and access to credit affect the adoption of barley technologies positively and significantly. Conclusion: Small holder farmers were more likely to succeed than fail in jointly adopting barley technologies. Consequently, government policy and other concerned parties should emphasize on the improvement of the institutional support system and decrease gender disparities in access to such institutions.

Globally, climate change is a significant development challenge. Sub-Saharan Africa is particularly vulnerable to the negative effects of climate change because of the region’s low adaptive capacity and its excessive reliance on rain-fed agriculture for food security and livelihood. Climate information accessibility is promoted to improve smallholder farmers’ adoption intensity of climate-smart adaptation practices. The object of this research is to examine climate information access as a driver of climate-smart adaptation practices. This study utilized primary data from 475 smallholder farmers in the Northern Region of Ghana. The Endogenous-Switching Poisson regression model was fitted to examine the determinants of access to climate information and the subsequent effect of access to climate information on climate-smart adaptation practices adoption intensity. According to the study, access to climate information is endogenous and is influenced positively by gender, farming experience, off-farm income and the number of times smallholder farmers listen to the radio. Age, farm income, access to extension, education, off-farm income, farm experience, perception of temperature and Access to climate information thus had a significant influence on the adoption intensity of smallholder farmers’ climate-smart adaptation practices. Based on these results, we suggest that climate change and agricultural programs should encourage smallholder farmers' subscription to access climate information in promoting the adoption of numerous climate-smart adaptation practices. To provide climate information to smallholder farmers in this situation, extension agents should be the main targets. The large effect of income that is both farm and off-farm income on the rate of climate-smart adaptation practices adoption is one of the study’s key findings. We contend that agricultural programmes should include ways to improve both farm and off-farm income of smallholder farmers to enable them to intensify their climate-smart adaptation practices adoption.

Intention to adopt improved indigenous chicken breeds among smallholder farmers in Machakos county, Kenya. Do socio-psychological factors matter?

PurposeThis study examines the impact of extension services in Indonesia on the technical efficiency of smallholder rice farming.Design/methodology/approachThe frontier production function approach and propensity score matching method are adopted to determine the technical efficiency and examine the impact of extension services on the technical efficiency.FindingsThis study shows significant variations in agricultural performance in Banten, Indonesia, with an average technical efficiency of 81.7 percent. The results show that farmers with extension access significantly increase in technical efficiency with margins of 3.5–4.6 percent compared to farmers who do not have extension access.Research limitations/implicationsThe consistent positive and significant effect of extension access implies that investment in agricultural extension programs can optimize the potential impact on smallholder farmers’ technical efficiency.Originality/valueThe estimation results clearly show that farm size, seeds, labor and fertilizer are significant determinants of rice yield. Every increase in production inputs such as farm size, seeds and fertilizer, accompanied by a decrease in the use of labor, can increase substantial profits in output. Variables such as extension access, credit access, training and mobile phone ownership have a positive and significant relationship to the technical efficiency of smallholder farmers.

Smallholder farmers are challenged by limited resources, finances, and access to complex production technologies, which hinder the implementation of good production practices such as good seed selection, knowing when to plant and harvest, pest and disease control, and access to lucrative markets. This paper used quantitative research methods to explore smallholder farmers’ perceptions, adoptions, and differences in agricultural incomes between adopting and non-adopting farmers. This study reveals that smallholder farmers perceive access to real-time information as important; however, adopting digital technologies as information sources is still considered low. Binary regression analysis further revealed that the access to extension services variable positively correlated with adopting the internet (web pages), YouTube and Farmers Weekly website as information sources. Digital technologies were generally perceived to be reliable, time-effective, and easy to use; however, adopting these technologies had no significant impact on the farmer’s agricultural income. This paper concludes that digital technology adoption is still considerably low; however, more and more farmers are not only open to adopting these technologies, but those who have adopted prefer incorporating them among sources they use to acquire farming information. Using digital technologies did not cause differences in agricultural income for these farmers. This study recommends public-private partnerships and community engagement through cooperatives to further drive technology adoption, fostering market access and improving livelihoods for smallholder farmers.

This study contributes to the literature on the impact of farmer contact with agricultural extension services on farm productivity, drawing on a unique panel sample of households residing in three resettlement areas of rural Zimbabwe. It pays particular attention to the potential confounding effects of the biases identified by Birkhaeuser, Evenson, and Feder. Specifically, we exploit the longitudinal nature of our data to estimate the impact of extension on the value of crop production per hectare, with and without controls for unobservable household fixed effects. The attraction of this estimator is that the differencing process rids the specification of the correlation between extension and the disturbance term. We find that after controlling for innate productivity characteristics and farmers' ability using household fixed- effects estimation, access to agricultural extension services, defined as receiving one or two visits per agricultural year, raises the value of crop production by about 15%. This parameter estimate is statistically significant. Another unique feature of these data are, for a subsample, extension worker assessments of farmers' ability. We find that farmers with above-average ability are indeed more productive, producing 40%-50% higher output per hectare of cropped area. Controlling for innate productivity using locality dummies, farm plot characteristics, and farmers' ability using these assessments of ability, we continue to obtain a positive association between access to extension and productivity, an association that is equal in magnitude to our fixed-effects results. However, we also find considerable variability in these parameter estimates across individual crop years.

Improved rice variety adoption and farm production efficiency: Accounting for unobservable selection bias and technology gaps among smallholder farmers in Ghana

PurposeChanging climate has increasingly become a challenge for smallholder farmers. Identification of technical, institutional and policy interventions as coping and adaptation strategies and exploring risks of their adoption for smallholder farms are the important areas to consider. The aim of the present study was to carry out an in-depth analysis of adaptation strategies followed and the associated risk premium in technology adoption.Design/methodology/approachThe study was carried out in the dryland systems of three Indian states – Andhra Pradesh, Karnataka and Rajasthan – and was based on a survey of 1,019 households in 2013. The flexible moment-based approach was used for estimating the stochastic production function, which allowed estimation of the relative risk premium that farmers are willing to pay while adopting the technologies to avoid crop production risks.FindingsIn all the three states, the risk premium (INR ha−1) was higher for farm mechanization compared to supplemental irrigation, except in the case of Andhra Pradesh. The higher the level of technology adoption, the higher the risk premium that households have to pay. This can be estimated by the higher investment needed to build infrastructure for farm mechanization and supplemental irrigation in the regions. The key determinants of technology adoption in the context of smallholder farmers were climatic shocks, investment in farm infrastructure, location of the farm, farm size, household health status, level of education, married years, expected profit and livestock ownership.Originality/valueQuantification of the risk premium in technology adoption and conducting associated awareness programs for farmers and decision-makers are important to strengthen evidence-based adoption decisions in the dryland systems of India.

The objective of this study was to analyzing factors that affect smallholder farmers’ choice of adaptation strategy and identifies adaptation measures to climate change in Ethiopia using Dale Woreda as a case study. The data was collected from 359 sample households using a survey questionnaire and was analyzed using both descriptive statistics and econometric methods. Multinomial logit model (MNL) was used to identify factors influencing smallholder farmers’ choice of adaptation strategies to climate change and variability. The adaptation strategies considered in the MNL model were crop diversification, growing drought tolerant crop, soil and water management, early and late planting and small scale irrigation practice. The result from the multinomial logit analysis showed that sex, education, farm experience, family size, farm income, farm size, distance to the market, soil fertility, access to credit, access to climate information, and extension access were significant factors influencing smallholder farmers’ adaptation strategies. a unit increases in number of years of education could increase 8.1% of the likelihood of adopting crop diversification ,1.8% of the likelihood of adopting growing drought tolerant crop and 1.2% of the likelihood of early and late planting as adaptation measures. The basic barriers to climate change adaptation on the farmers’ side are lack of credit access, lack of knowledge, lack of support from government, shortage of farm land, lack of climate information and lack of climate related problem. Therefore, expanding extension service, improving the availability of credit and enhancing research on use of new crop diversification and distributing drought tolerant crop varieties and encouraging continuous climate training center, disseminating climate information by local language through social media and providing modern tool for soil and water management and small scale irrigation by government are more suited in three agro-ecological zones.

Smallholder farmers are crucial in ensuring global food security and sustaining rural economies. However, these farmers face significant challenges, including low productivity and financial constraints. Thus, this study developed a comprehensive framework for smallholder farmers in adopting and effectively utilizing Cyber-Physical Agricultural Systems (CPAS) enabled technologies. This is achieved through a comprehensive literature review and synthesis to identify trends, opportunities, and gaps in CPAS applications, particularly for smallholders. Following this, three case studies were explored to examine the manufacturing costs of specific CPAS technologies: a robot arm, an intelligent irrigation system, and a smart IoT kit. These costs were assessed and compared to the average incomes of smallholder farmers globally. Finally, an integrated strategy addressing their financial constraints has been developed across policy, research, market environment, and service-oriented interventions. These strategies were synergized to establish product standards, understand societal demands, develop evidence-informed practices, and provide best practices and support. Future research should focus on further reducing technology utilization and adoption costs and conducting social research in terms of farmers' openness to this technology.

The study is conducted using a primary data which was collected from 252 randomly selected households found in two woredas (districts) of Gedeo zone with the objective of analysing determinants of smallholder farmers’ participation in the credit market from both demand and supply sides and its implication on agricultural technology adoption and intensity of adoption. Probit and double-hurdle models are employed to analyse the data. Being young, number of oxen and distance to credit market are found to reduce the probability of being credit constrained. Age, number of oxen, family size and technology adoption are found to increase credit demand while land size, tropical livestock unit and distance to credit market have negative (unexpected) signs. In the double-hurdle model estimation while credit market participation, being literate, being young and livestock holdings are found to determine the probability of technology adoption positively having oxen, being credit constrained and far from input market affected probability of technology adoption negatively. In the last estimation, education, land size and livestock holdings turned out to affect intensity of adoption positively while number of oxen and distance to input market are found to reduce expenditure of farm technology.

This study endeavors to construct a comprehensive conceptual framework elucidating the moderating influence of income on factors influencing the adoption of agricultural technology among cassava farmers in Nigeria. Agricultural technology, herein, refers to the innovative utilization of emerging Information and Communication Technologies tailored for agricultural applications within remote environments. The agricultural sector holds paramount significance within the Nigerian economy, engaging nearly 70% of the labor force and contributing over 40% to the gross domestic product. The adoption of technology in agriculture signifies potential enhancements in income, poverty alleviation, improved national nutrition and health, reduced food prices, and employment opportunities. However, the income of cassava farmers plays a pivotal role in ensuring their sustainability. Regrettably, their income streams are often unstable due to fluctuations in market prices, adversely impacting their ability to finance the adoption of technology to bolster productivity. Therefore, this research aims to develop a robust conceptual framework delineating the moderating role of income on the determinants of agricultural technology adoption behavior, particularly pertinent within the Nigerian context. It is imperative to tailor conceptual frameworks specifically for Nigeria, given that frameworks derived from other regions may not be directly applicable to the unique challenges and dynamics of the Nigerian agricultural landscape.