Rural Farmers Research Articles

Does the livelihood capital of rural households in national parks affect intentions to participate in conservation? A model based on an expanded theory of planned behavior

The purpose of this research was to examine the motivations of rural farmers to participate in community conservation within national parks. An expanded version of the Theory of Planned Behavior was used to explore the impacts of economic and psychological factors on farmer willingness to engage in conservation efforts. In using the livelihood capital concept along with the TPB theory, structural equation modeling was applied to analyze survey data from rural residents within Nanling National Park, Guangdong, China. The attitudes of farmers about the development of the national park and subjective norms significantly affected willingness to participate in community conservation, and the willingness was directly influenced by financial, social, and institutional dimensions of livelihood capital. For certain dimensions of livelihood capital, attitudes and subjective norms mediated willingness to engage in conservation efforts, the affecting path being livelihood capital → subjective norms → attitudes → willingness to participate in community conservation. Perceived behavioral control had a positive moderating effect between attitudes and willingness. The findings help to explain the factors driving rural farmer willingness to engage in community conservation. Socio-psychological factors and institutional capital were particularly instrumental in affecting willingness. Overall, this research reveals how different types of livelihood capital influence community conservation among farmers and the importance of community conservation as a livelihood strategy option, as well as the psychological and economic factors of farmers in a changing institutional environment. Based on the findings, corresponding policy recommendations are presented to improve the effectiveness of community conservation policy, and also provide China's experience and reference for other developing countries to formulate targeted community conservation policies.

Are farmers willing to pay for low-carbon agriculture? Evidence from China

PurposeReducing carbon emissions in agriculture is vital for fostering sustainable agricultural growth and promoting ecological well-being in rural areas. The adoption of Low-Carbon Agriculture (LCA) by farmers holds great potential to accomplish substantial reductions in carbon emissions. The purpose of this study is to explore the farmers' preference and willingness to engage in LCA.Design/methodology/approachThis study employs the Choice Experiment (CE) method to examine farmers' preferences and willingness to adopt LCA, using field survey data of 544 rural farmers in the Weihe River Basin between June and July 2023. We further investigate differences in willingness to pay (WTP) and personal characteristics among different farmer categories.FindingsThe empirical results reveal that farmers prioritize government-led initiatives providing pertinent technical training as a key aspect of the LCA program. Farmers' decisions to participate in LCA are influenced by factors including age, gender, education and the proportion of farm income in household income, with their evaluations further shaped by subjective attitudes and habits. Notably, we discovered that nearly half of the farmers exhibit indifference towards LCA attributes.Originality/valueTo the best of the authors' knowledge, this study is the first to investigate farmers' attitudes toward LCA from their own perspectives and to analyze the factors influencing them from both subjective and objective standpoints. This study presents a fresh perspective for advocating LCA, bolstering rural ecology and nurturing sustainable development in developing nations.

Exploring the Influence of Export Environment on Market Standard Dimensions and Horticultural Market Growth in South Rift, Kenya

The inclusion of rural smallholder farmers in the export of horticultural products has two major implications: increased household income through a promising global market, which is a catalyst for productivity, cumulatively growing Gross Domestic Product (GDP) and foreign exchange. So far, there are an estimated 2500 smallholder farmers who participate in the export of horticulture in Kenya. As a result, the current study sought to establish the influence of export environment on the relationship between market standard dimensions and export market growth of the horticultural products from small scale farmers in south rift of Kenya. The study collected quantitative data using a structured questionnaire from a sample of 334 small-scale horticultural farmers who were randomly selected. Validity and reliability tests were performed before the main study. Then, descriptive and multiple regression was used to analyze the data. Export environment was measured through: government support and services for export, government regulations and certifications and trade agreements and market access. Findings indicated that there was a statistically significant influence relationship between market standard dimensions and the growth of horticultural export market, where export environment on each predictor variable had the highest influence on market dynamics, followed by quality control, traceability and post-harvest handling practices being the least. This implies that the export environment plays a critical role in making the smallholder farmers’ products more competitive in export market. The study concluded that, appropriate policies, regulations and trade agreements were critical in market standards compliance. The government should create a framework to effectively disseminate information on trade agreements so as to benefit farmers and in addition establish collaboration between farmers, the government and private sector in export intervention measures. Keywords: Export, Horticulture, quality, Post-harvest, Traceability, Market

Growth of Horticultural Export Market: The implication of Post-harvest Handling Practices among Small Scale Farmers in South Rift, Kenya

The inclusion of rural smallholder farmers in the export of horticultural products has two major implications: increased household income through access to a promising global market and enhanced productivity, cumulatively contributing to the growth of Gross Domestic Product (GDP) and foreign exchange. Currently, there are an estimated 2,500 smallholder farmers participating in horticultural exports South Rift of Kenya. Consequently, this study aimed to investigate the relationship between post-harvest handling practices by smallholder farmers and the growth of the horticultural export market. Quantitative data were collected using a structured questionnaire from a sample of 334 small-scale horticultural farmers, randomly selected for the study. Validity and reliability tests were conducted prior to the main study. Descriptive statistics and simple linear regression were employed to analyze the data. Post-harvest handling practices were assessed through the utilization of packaging materials, storage facilities, energy supply, hygiene, and transportation facilities. The findings indicated a statistically significant relationship between post-harvest handling practices and the growth of horticultural export markets. However, deficiencies were observed among small-scale farmers in South Rift, Kenya, in managing horticultural products after harvest. The study recommended for strategic interventions for the adoption of modern technologies in every stage of the supply chain and establishes collaborations with key stakeholders in order to minimize cost of investment per farmer and ultimately enhancing market standards compliance and competitiveness in the fruit and vegetable export market. Keywords: Post harvest, storage, packaging, Hygiene, Export, Markets

Determinants of poverty in rural cocoa farming communities in Ghana: unidimensional and multidimensional analysis

Determinants of poverty in rural cocoa farming communities in Ghana: unidimensional and multidimensional analysis

The Prevalence of Infection with Gastrointestinal Helminths in Free-Range Poultry of Zabol, Iran.

As an ecological and ethical method employed for poultry farming, free-range chicken keeping is growing and is important in fostering rural farmers' livelihoods and community prosperity. This study aimed to determine the nature and prevalence of helminth infections in native poultry in Zabol, Iran. Between 2022 and 2023, 160 chickens were acquired and slaughtered ethically, and then their gastrointestinal tracts were taken and formalin preserved in Zabol, Iran. The parasites were isolated from gastrointestinal mucus in the laboratory and characterized using a microscope and specific methods such as Acetocarmine staining. Among 160 dissected birds, 92 (57.5%) were presented with gastrointestinal parasites, with 64 (40%) containing cestodes, 16 (10%) containing nematodes, and 12 (7.5%) infected by both. Observations were made of seven different species. Ascaridia galli (A. galli) (10%), Subulura brumpti (7.5%), and Heterakis gallinarum (3.12%) represent the three main nematode species. While Raillietina tetragona (R. tetragona) (33.12%) was the most prevalent cestode, R. echinobothrida (6.25%), R. magninumida (5%), and Cotugnia digonopora (3.12%) were less common. The study revealed that free-range chickens in the arid Zabol region had a high prevalence of gastrointestinal parasites. There is a strong correlation between chicken foraging behavior and exposure to contaminated soil, with certain nematodes and cestodes constituting the most prevalent, negatively affecting bird growth, productivity, and health. Therefore, improving poultry welfare by applying parasite control measures and implementing appropriate management strategies is essential.

Gendered distributional impacts of ownership of mobile money account on farm input expenditures: A micro perspective from rural maize farmers in Ghana

AbstractThis article investigates the distributional impact of mobile money account ownership on farm input expenditures among maize farmers in southern Ghana. Using cross‐sectional data from 1044 farm households, we employed an instrumental variable quantile regression to account for endogeneity and selection bias. We find that socioeconomic, spatial location, and institutional factors significantly influence male and female‐headed household decisions to own mobile money accounts. The empirics show that male‐headed households spend more on fertilizer and pesticide relative to female‐headed households. Mobile money account ownership increases fertilizer expenditure in male‐headed households more than female‐headed households. Male‐headed families with mobile money accounts spend 13.9% and 6.5% more on fertilizer at the 40th and 60th quantiles. High 80th quantile female‐headed households spend 4.3% more on fertilizer. For male‐headed households, farming experience and education positively influence mobile money account ownership on fertilizer expenditure, while off‐farm activity at the 40th quantile positively influences female‐headed households. Our results distill useful policy implications that call for concerted efforts targeted at digital financial inclusion with an eye to bridging differential gender gaps.

It's not just about the sun, it's about a living: Rural older farmers' experience of skin cancer risk and prevention.

To understand rural older farmers' perspectives and attitudes toward skin cancer risk and prevention. This study used a grounded theory approach and semi-structured interviews with 12 rural older farmers (farm owners, farmworkers ages 50 years or older) in Washington. Participants' perspectives were explored relative to Health Belief Model constructs. Inductive and deductive analyses were used to generate relevant themes. COREQ guidelines were followed. The findings fit well and extended the Health Belief Model, which was used to arrange key themes identified in relation to skin cancer risk and prevention, specifically participants' perceived barriers to accessing primary care and protection when outdoors, perceived benefits of sun-protective behaviors, perceived hereditary susceptibility to skin cancer, perceived severity of the increased skin cancer risk, and cues to action for skin checks. A new construct of hope was identified to emphasize the importance of establishing emotional, instrumental, and informational support systems for promoting skin cancer prevention. Participants also indicated their hope of raising awareness of skin cancer prevention among all ages. Findings highlighted the importance of integrating skin cancer prevention services for rural older farmers and across the lifespan. Public health approaches are needed to enhance the awareness of and access to preventive care in these underserved populations.

Rural Inclusive Finance and Agricultural Carbon Reduction: Evidence from China

Rural Inclusive Finance and Agricultural Carbon Reduction: Evidence from China

Multidimensional Poverty Status in Rural Bangladesh and the Pathways of Sustainable Poverty Alleviation

Even though poverty is a social and economic phenomenon, it is nonetheless important to investigate the multidimensional character of poverty in the Global South. Hence, this study is an effort to determine the multidimensional poverty status in rural Bangladesh, decompose poverty, and investigate risk factors for poverty. To achieve the goal, primary data were collected from 350 rural farm households through the random sampling technique. The Alkire-Foster (A-F) method of multidimensional poverty estimation was applied considering four dimensions of deprivation. It was found that 11% of rural households were multidimensionally poor, whereas the multidimensional headcount of poor was 23% and their average intensity of poverty was 47%. When their poverty was decomposed, it was evidenced that the standard of living dimension has the highest contribution among the four dimensions to poverty. The result from ‘indicator-wise decomposition’ found that job seeking was the highest contributing indicator to poverty followed by school dropout and type of cooking fuel. A binomial logit regression model was used to explore the risk factors of poverty. Regression results revealed that larger household size has significantly increased the risk while, more income-earning persons, ownership of large livestock, and crop farming could significantly reduce the risk of poverty in rural farm households. The study findings could be used to implement a sustainable poverty reduction strategy. Also, the contextual factors need to be considered in poverty estimation and policy intervention should be implemented in such a way where the contribution of the dimensions and indicators of poverty get prime focus.

Evaluating food security and nutritional pathways of rural farm families: Empirical evidence from northeast India

The study aimed to ascertain a relationship between agricultural status, socioeconomic factors, and nutrition of farm families. The study was conducted in selected villages in the West Garo Hills district of Meghalaya, using Stratified Random Sampling (St. RS). Using pretested interview schedules, we collected primary data from respondents in 2020 and 2021, focusing on socioeconomic variables, body mass index, and income from agriculture and related sectors. The data was analysed using correlation analyses and separate combined regression estimates for each year and month were obtained. Results from the study indicate that agricultural income significantly influenced nutritional status (p < 0.05) and household income growth was also found significant. The region's agricultural production of cereals, pulses, and vegetables was insufficient, as was the production of meat and meat products, milk, and milk products. Hence, expenditure towards purchasing the above food groups from the market was found to be significant (p < 0.05). Therefore, the markets near the mainland especially in the hilly region play a crucial role in the nutritional pathway of rural farm families.

Solar empowerment in agriculture: investigating photovoltaic energy’s impact on efficiency among wheat farmers

Persistent electricity shortages in Pakistan, causing prolonged grid power load shedding, have adversely impacted various sectors, notably agriculture and the livelihoods of rural farmers. Literature suggests that adopting photovoltaic solar energy can mitigate these issues. This research aims to measure the impact of photovoltaic solar energy on the technical efficiency of food productivity in Khyber Pakhtunkhwa, Pakistan, applying data from 580 respondents. Addressing self-selective bias through ESR and stochastic frontier production function model is utilized to assess technical efficiency. The findings of this study reveal that farmers using solar energy experience a significant improvement in technical efficiency, with 15.8 percent of them achieving a 7.643 percent increase, after accounting for self-selection bias. Furthermore, the positive effects are more pronounced among larger farms and those with greater farming experience. This study underscores the importance of evidence-based approaches in implementing solar energy solutions, highlighting their potential to foster sustainability and equitable development at the grassroots level. The research culminates with policy recommendations that underscore the importance of promoting the photovoltaic solar energy use among farmers to improve food security and increase agricultural productivity.

Assessment of agricultural residue potential for electrification of off-grid communities in the Sawla-Tuna-Kalba District of Ghana

BackgroundThere is a close link between the lack of electricity access and poverty indicators such as illiteracy, high infant mortality, lack of access to health care and malnutrition among others. Most rural farming communities in Ghana lack access to electricity due to the high cost of extending the grid to these communities. This lack of access tends to worsen the gap between urban and rural inhabitants regarding access to education, healthcare and development.MethodsThis study assessed the technical and theoretical potential of agricultural residues in providing electricity to off-grid communities. The study used crop production figures of maize, cassava, millet and groundnut in the Soma and Goyiri farming communities in the Sawla-Tuna-Kalba District to conduct an assessment of the theoretical and technical potential of residues from the crops. The production figures of these crops were obtained from the District Office of the Ministry of Food and Agriculture. Expected electricity demand of households, schools and health centers in the study communities were collected and employed for the projected load demand estimates.ResultsThe study found that 312.23 MWh/day of electricity could be generated from the combined residues of maize, cassava, millet and groundnut from the two communities. This amount of electricity is capable of providing ~ 202 to 263 times the peak electricity demand of the studied communities. Out of the total electricity demand of the two communities, only about 91 kWh/day is needed for use in a school and Community Health Promotion and Services (CHPS) compound, implying that the electricity from crop residues can also help to improve education and health provision in the rural communities.ConclusionIt is concluded that the potential of crop residues in meeting the electricity demand of off-grid communities is enormous. Hence, it must be considered in Ghana’s energy development plans to achieve universal electricity access.

Study of Fall Army Worm (Spodoptera frugiperda) Risk Communication Sources and Information Needs of Rural Maize Farmers in Imo State, Nigeria

Study of Fall Army Worm (Spodoptera frugiperda) Risk Communication Sources and Information Needs of Rural Maize Farmers in Imo State, Nigeria

Analysis of smallholder farmers' dynamics of knowledge sharing, skill transfer, and participation in using biogas (application of social network analysis)

Air pollution, population growth, and the lack of fossil energy sources are critical factors that drive people toward clean and renewable energies in the current century. Biogas is suitable for rural farmers as a source of clean energy. Since there are many social interactions in knowledge exchange and sharing, the transfer of skills, and participation among individuals, various actors are involved in the network. The power and influence of actors and the social interactions between smallholder farmers and these actors fuel the development of biogas consumption in rural areas. Therefore, this study analyzes the social network structures and characteristics of various actors by social network analysis (SNA) in knowledge sharing, the transfer of skills, and participation networks among traditional smallholder farmers in Iran. The research sample consisted of some smallholder farmers in four provinces of Fars, Khorasan Razavi, Golestan, and Kermanshah (144 smallholder farmers). The research instrument was a questionnaire designed as a matrix. The findings showed that based on the betweenness centrality score, biogas-consuming smallholder farmers (34.56) and cooperatives of smallholder farmers (24.79) were the main actors in the network of knowledge sharing, respectively. Furthermore, biogas-consuming smallholder farmers (28.04) and pioneer smallholder farmers (27.11) were the main actors in the network of participation, respectively. The betweenness centrality score revealed that cooperatives of smallholder farmers (29.23) and opinion leaders (23.33) were the main actors in the network of skills transfer, respectively. It can be concluded that these actors had high social power and influence among smallholder farmers and can be the core of the smallholder farmers’ social networks. It means that they can influence the development of biogas consumption among Iranian smallholder farmers.

Development of a cloud-based IoT system for livestock health monitoring using AWS and python

The agriculture industry is currently facing significant challenges in effectively monitoring the health of livestock. Traditional methods of health monitoring are often labor-intensive, inefficient, and insufficiently responsive to the needs of modern farming. As the number of IoT devices in agriculture proliferates, issues of scalability and computational load have become prominent, necessitating efficient and scalable solutions. This research introduces a cloud-based architecture aimed at enhancing livestock health monitoring. This system is designed to track critical health indicators such as movement patterns, body temperature, and heart rate, utilizing AWS for robust data handling and Python for data processing and real-time analytics. The proposed system incorporates Narrow Band IoT (Nb IoT) technology, which is optimized for low-bandwidth, long-range communication, making it suitable for rural and remote farming locations. The architecture's scalability allows for the effective management of varying numbers of IoT devices, which is essential for adapting to changing herd sizes and farm scales. Preliminary experiments conducted to assess the system's performance have demonstrated its durability and effectiveness, indicating a successful integration of AWS IoT Cloud services with the deployed IoT devices. Furthermore, the study explores the implementation of predictive analytics to facilitate proactive health management in livestock. By predicting potential health issues before they become apparent, the system can offer significant improvements in animal welfare and farm efficiency. The integration of cloud computing and IoT not only meets the growing technological needs of modern agriculture but also sets a new benchmark in the development of sustainable farming practices. The findings from this research could have broad implications for the future of livestock management, potentially leading to widespread adoption of technology-driven health monitoring systems in agriculture. This would help in optimizing the health management of livestock globally, thereby enhancing productivity and sustainability in the agricultural sector.

Automated Detection of Plant Diseases and Pests Using Advanced Image Processing and Neural Networks

Pests and viral plant diseases have proliferated in agriculture. Rats spread plant diseases. Hard to detect viral infections or insect infestations that impair plant growth and yield. It decreases crop size, quality, and marketability, incurring major economic losses. Strong, disease-resistant crops are needed for agriculture. Bacterial, fungal, and insect/pest diseases destroy 70% and 15% of crops. Above 85% of disease severity destroys crops. Early detection systems track pests and diseases. High-definition equipment is costly for rural farmers. Correct diagnosis permits quick infection severity and type assessment and control. In precision agriculture, neural networks and image processing eliminate human error. Sustainable agriculture and organic agricultural cultivation must start early. The proposed system classifies diseases and pests for plant safety. A healthy, fast-growing plantation is our goal. Early detection of viral diseases and insect infestations boosts crop productivity. Plant disease diagnostics focuses on leaves and buds. Stem and insect infections are covered. The suggested method classifies plant health and disease automatically. Peanut leaves develop Bacterial Blight from contagious illnesses like Cercospora Leaf Peanut. Boll Weevils, European Corn Borers, and Fall Army Worms attack cotton. The conditions are categorised. Image accuracy depends on lighting, resolution, location, and backdrop complexity. Various low-resolution pictures are enriched to better classification. Complex leaf intensity variations cause the system to misdiagnose illness or insect infestation. To avoid misclassification, the system segments the sample image using various methods to find lesions. Multilevel Segmentation (MS) improves Deep neural network feature extraction using approximate outlines. This method protects important pixels, eliminates unneeded pixels, and amplifies the lesion to control segmentation and reduce insufficient and excessive segmentation.

Vertical Spatial Differentiation and Influencing Factors of Rural Livelihood Resilience: Evidence from the Mountainous Areas of Southwest China

Rural livelihood resilience (RLR) is significant for the sustainability of rural areas, farmers and agriculture. This research takes the mountainous areas of Southwest China as the study areas and integrates the buffer, adjustment and renewal capabilities to construct a RLR analysis framework and evaluation indicator system. The RLR of 234 sample counties was evaluated using set pair analysis, and the influencing factors of RLR were investigated using Geodetector. The aim is to scientifically analyze the vertical spatial differentiation and influencing factors of RLR and fully explore the risk-resistant potential of rural livelihood systems in mountainous areas. The results show that (1) From 2000 to 2020, RLR increases significantly, but the level is still low, and its structure shows a primary pattern of “buffer capability &gt; adjustment capability &gt; renewal capability”. (2) There is no significant negative correlation between RLR and terrain gradients, especially in the middle and low mountains. RLR in high mountainous areas is significantly lower than in low and medium mountainous areas, but the gap is narrowing. There are no significant gaps in RLR and various capabilities between low and medium mountain areas. (3) Economic development, non-agricultural industries and grassroots autonomous organizations are essential determinants for RLR. Economic development, grassroots autonomous organizations and transportation conditions are more important in low and medium mountain areas, while non-agricultural industries and medical conditions contribute more to high mountainous areas. (4) To enhance the RLR, policy recommendations should place a strong emphasis on extending the agricultural industry chain, improving rural production and living infrastructure and strengthening the supply of high-quality social public services. The findings can provide a scientific basis for governments to implement rural revitalization strategies and improve farmers’ well-being, as well as practical guidance for enhancing the risk resistance ability of underdeveloped mountainous rural areas.

Implementation Outline of Climate-Smart One Health: A System-Thinking Approach

The One Health (OH) concept has evolved significantly in recent decades, emerging as a key framework guiding international research and policy in managing new infectious diseases, chiefly zoonoses. While its initial conception revolved around managing zoonotic diseases as they traverse the interface between animals and humans through the environment, this concept has transformed beyond its origins as a collaboration solely between veterinary and public health stakeholders. Notably, the past decade has ushered in a new era of addressing complex issues in a novel manner. Emerging evidence has led to a fresh theoretical framework, highlighting interconnected terrestrial and aquatic ecosystems. Understanding these links is crucial in tackling emerging issues and resultant health challenges within these systems under what we call One Health 2.0. The current paper describes Climate-Smart One Health (CS-OH) and Climate-Smart Integrated Pest Management (CS-IPM) approaches, emphasizing holistic perspectives and practical tools. The One Health (OH) 2.0 concept applies to the agricultural sector and more specifically to agrifood systems exposed to climate change impacts. It is meant to address, in a comprehensive manner, soil, water, plant, animal, rural and urban farmers and farming communities, and consumer health issues. The One Health (OH) 2.0 concept is embodied in the Climate-Smart One Health (CS-OH) approach. The latter is designed for applications in agrifood systems. Pathways for the deployment of both CS-OH and CS-IPM interventions are proposed in this paper. A Ghanaian case is discussed.

Awareness of G2C services among rural farmers in Sagar, Madhya Pradesh: An analytical study

Awareness of G2C services among rural farmers in Sagar, Madhya Pradesh: An analytical study