Next Article in Journal
An Investigation of University Students’ Perceptions of Learning Management Systems: Insights for Enhancing Usability and Engagement
Previous Article in Journal
Advances, Hotspots, and Trends in Outdoor Education Research: A Bibliometric Analysis
Previous Article in Special Issue
Economic Sustainability Foraging Scenarios for Ruminant Meat Production—A Climate Change Adapting Alternative
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 16
Issue 22
10.3390/su162210035
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

From Conventional to Organic Agriculture: Influencing Factors and Reasons for Tea Farmers’ Adoption of Organic Farming in Pu’er City

by
Hao Li
1,2,
Shuqi Yang
1,
Juping Yan
1,
Wangsheng Gao
1,
Jixiao Cui
2,* and
Yuanquan Chen
1,*
1
College of Agronomy and Biotechnology, China Agricultural University, Beijing 100107, China
2
Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100875, China
*
Authors to whom correspondence should be addressed.
Sustainability 2024, 16(22), 10035; https://doi.org/10.3390/su162210035
Submission received: 12 September 2024 / Revised: 28 October 2024 / Accepted: 14 November 2024 / Published: 18 November 2024
(This article belongs to the Special Issue Agricultural Economic Transformation and Sustainable Development)
Browse Figures
Versions Notes

Abstract

:
As the global pursuit of sustainable agricultural practices continues, organic farming is gaining increasing attention. In Pu’er, one of China’s major tea-producing regions, the factors influencing tea farmers’ willingness to adopt organic agriculture have not yet been fully studied. This study integrates the diffusion of innovations theory and the theory of planned behavior, using field surveys to thoroughly analyze the key factors and reasons affecting tea farmers in Pu’er in adopting organic farming practices. The findings indicate that perceptions of the economic benefits of organic farming are the primary drivers of farmers’ willingness to adopt. Experience with organic agriculture training and positive views on environmental and health benefits also significantly enhance the willingness to adopt organic farming. Contrary to common assumptions, education level, age, and household income have minimal influence on adoption willingness. However, low-income families that rely on tea cultivation are more inclined to adopt organic farming. Policymakers should prioritize economic incentives, strengthen training support, and enhance the promotion of the benefits of organic agriculture, while simplifying certification processes and expanding market channels to facilitate the transition of tea farmers to organic agriculture. This study offers insights into the sustainable tea industry and organic farming promotion.

1. Introduction

Amid the persistent challenges of environmental crises, population growth, and the limitations of traditional food systems, it has become increasingly vital to identify sustainable pathways for economic development, particularly within the agricultural sector. In this context, alternative farming practices and changes in traditional food consumption patterns have attracted growing scholarly attention [1,2]. Organic agriculture, in particular, is regarded as a viable strategy, as it addresses both environmental sustainability and consumer health concerns [3,4]. However, to support the continued expansion of the organic sector, especially in the global tea market, there is a critical need for more in-depth studies that examine the factors influencing farmers’ adoption of organic practices. This research seeks to contribute to this field of study by examining the adoption of organic farming practices among tea farmers in Pu’er City, Yunnan Province, a region central to China’s tea industry.
Many studies have explored the environmental and social impacts of organic versus conventional production methods [5,6,7]. Compared with traditional agriculture, organic agriculture has shown significant advantages in reducing agricultural greenhouse gas emissions, improving soil fertility, and ensuring public food safety [8]. However, organic agriculture is often accompanied by higher labor input requirements, and yields are on average 25% lower than conventional agriculture [9]. Increases in labor inputs and declining yields can pose significant barriers to farmers’ adoption of organic production methods. Nonetheless, studies have shown that organic farming yields are relatively more stable, and organic products often command a higher market premium, meaning that organic farmers may enjoy higher incomes. While these advantages and challenges have been widely discussed, there is still a lack of systematic research influencing farmers’ willingness to adopt organic production methods. In developing countries, socio-economic and institutional factors determine whether farmers adopt organic farming practices, with economic constraints often cited as the main obstacle. The transition to organic farming often requires a significant upfront investment, both in terms of capital and time, which can be overwhelming for many smallholder farmers [10,11]. In addition, these concerns are further exacerbated by potential yield reductions within organic farming converters and uncertain economic returns to future markets for organic products [12]. Therefore, financial incentives such as government subsidies will play an important role in encouraging farmers to adopt organic farming [13]. The level of education of farmers and the ease of access to effective information are also key factors influencing the adoption of organic farming by farmers. Some studies have shown that farmers with higher levels of education are more likely to adopt organic farming methods because they are better equipped to understand the complexities of organic farming practices and the long-term benefits that organic agriculture offers [14]. In addition, access to information, e.g., formal training programs, extension services, or peer access to information, can have a significant impact on a farmer’s decision making regarding their willingness to adopt organic farming practices [15]. Cultural and psychological factors are equally important in influencing farmers’ adoption behavior. In areas where conventional farming practices are deeply entrenched, farmers may be reluctant to adopt new methods due to potential crop failures and concerns about unknown risks [16,17].
Pu’er, located in Yunnan Province in southwestern China, is one of the country’s most significant tea-producing regions, accounting for a substantial share of China’s high-quality tea exports [18]. According to the Pu’er Tea and Coffee Industry Development Center, as of 2021, tea plantations in Pu’er cover an area of 1.75 million mu, generating an output value of approximately CNY 33.8 billion, with the primary tea industry contributing about CNY 6.8 billion [19]. The tea sector constitutes 32% of Pu’er’s GDP and directly benefits more than 1.2 million residents. As such, the promotion of organic tea farming in Pu’er has the potential to profoundly impact both the local economy and the global tea market. However, the intense competition in the tea industry, coupled with the deep-rooted traditional business model of tea farming, makes it challenging for farmers to perceive the short-term economic benefits of transitioning to organic methods [15]. Additionally, the shift to organic production requires significant investments in time and resources to make adjustments and optimize practices, which adds to the complexity of the transition process [2,20,21]. Socio-economic factors, such as tea farmers’ economic returns, market demand for tea, and policy support, play a crucial role in their decision-making processes [22]. Equally important, however, are the psychological factors such as risk perception, traditional attitudes, and trust in new technologies that influence farmers’ willingness to adopt organic farming practices [23]. Despite the rapid global expansion of the organic agricultural sector, existing research on the willingness of tea farmers to adopt organic methods tends to focus narrowly on technical or policy factors [24,25], often neglecting the broader socio-economic and psychological drivers. This gap limits a comprehensive understanding of farmers’ decision-making processes and poses challenges for designing effective organic agriculture extension policies. This study seeks to bridge these gaps by investigating not only the specific drivers that influence the adoption of organic farming but also the role of external factors, such as government policies, market incentives, and social influences, in shaping farmers’ choices. Addressing these challenges is critical for enhancing production methods, optimizing resource utilization, and strengthening the agricultural trading system, all of which are essential for stimulating exports and fostering regional development.
To fill the gaps in existing research, diffusion of innovations theory (DIT) and theory of planned behavior (TPB) provide valuable theoretical frameworks for understanding the complexities of the adoption of organic farming practices by tea farmers. DIT explains the adoption process of innovations through five key attributes: comparative advantage, compatibility, complexity, trialability, and observability [26]. These attributes help to understand the acceptance of organic farming practices by tea farmers. For example, the relative advantages of organic farming in reducing environmental pollution and improving tea quality may be an important incentive to attract tea farmers to make the transition [27]. However, if organic farming is due to high technological complexity, tea farmers may feel intimidated and thus take a wait-and-see attitude towards the transition. In addition, trialability and observability in DIT directly affect the decision-making process of tea farmers to adopt organic farming practices. For example, tea farmers verify the possible risks associated with organic transition through small-scale trials or visualize cases of a successful adoption of organic methods by other farmers to observe farmers’ willingness to adopt organic farming [28]. The TPB can further dissect the decision-making process of tea farmers adopting organic farming. TBP explores how three core factors, including attitudes, subjective norms, and perceived behaviors, influence behavioral intentions [29]. This is reflected in the following aspects. First, in the context of the willingness to adopt organic methods of production, tea farmers’ attitude of whether they believe that organic farming can bring higher economic benefits, or a better ecological environment, will directly affect their willingness to adopt organic farming [30]. Secondly, tea farmers may be more inclined to switch to organic farming if they feel pressure from their peers or the market that organic farming is a more socially desirable option. This also suggests that subjective normative pressure from the family, community, or society may also have an impact on tea farmers’ decision-making process to adopt organic farming [31]. Finally, if tea farmers perceive that they lack the necessary resources, technology, or market support, they may abandon or delay their plans to convert. This reflects the influence of perceived behavioral control on behavioral intention in TPB theory, i.e., tea farmers’ confidence in their own ability and awareness of the difficulty of organic farming may be important influences [32]. In the context of tea cultivation in Pu’er, DIT is employed to ascertain which of the advantages of organic agriculture (for example, increased income and reduced environmental impact) are most likely to motivate the adoption of such practices. Concurrently, TPB provides a supplementary viewpoint that emphasizes the influence of attitudes, subjective norms, and perceived behavioral control in shaping adoption decisions. Thus, by combining DIT with TPB, a more comprehensive understanding of the psychological and behavioral dynamics of tea farmers in Pu’er City in the face of organic farming practices can be achieved.
This study aims to explore the multiple influencing factors affecting tea farmers’ willingness to adopt organic farming practices in Pu’er City, Yunnan Province. To this end, the diffusion of innovations theory and the theory of planned behavior are employed to conduct a multi-dimensional systematic analysis. The primary objectives of this study are as follows: (1) to analyze the complex relationship between tea farmers’ socio-economic backgrounds and their attitudes and behavioral willingness to adopt organic farming practices through field surveys, and to explore the key factors affecting the adoption of organic production methods by farmers with different characteristics; (2) to study how tea farmers’ perceptions of organic agriculture affect their willingness to adopt organic farming from the cognitive and psychological perspectives, and reveal the role of these perceptions in decision-making processes. The findings of this study will provide a theoretical basis and practical reference for the development of sustainable agriculture policies in Pu’er and other tea-producing regions.

2. Materials and Methods

2.1. Study Area

Pu’er is located in the southwest of Yunnan Province (Figure 1) and is one of the major tea-producing areas in China. In 2021, Pu’er had a tea plantation area of 116,700 hectares, with an output of 136,700 tons, and the city’s organic tea plantation area reached 28,027 hectares, making the tea plantation area the largest in the country among prefecture-level cities. The area’s varied elevations, ranging from lowlands to high mountains, create microclimates that are conducive to growing high-quality tea. These conditions make Pu’er an important site for examining the factors that influence tea farmers’ willingness to adopt organic farming practices.

2.2. Data Collection

In this study, data were collected through a survey of 162 tea farmers in Pu’er City. The tea farmers surveyed represented a diverse range of age groups, educational backgrounds, income levels, and years of agricultural experience. The survey instrument consisted of structured questions distributed in collaboration with local agricultural offices and tea associations to ensure a representative sample of tea farmers. The use of questionnaires facilitated the establishment of a rapport with the tea farmers, which was essential for acquiring reliable and candid responses.
The questionnaire comprised three principal sections. The initial section encompassed inquiries pertaining to the respondents’ age, gender, educational background, household size, number of agricultural laborers, annual household income, percentage of agricultural income, duration of tea cultivation, and size of the tea plantation. The second section pertains to awareness of organic farming, encompassing farmers’ familiarity with organic standards, knowledge of organic certification systems, and perceptions of potential income, environmental impacts, and health-related benefits associated with adopting organic farming practices. Additionally, the objective conditions of tea farmers’ willingness to adopt organic practices are examined, including their awareness of government subsidies for organic agriculture and the influence of successful examples in their vicinity on their decision to adopt organic farming.

2.3. Theoretical Framework

In this study, the diffusion of innovations theory and the theory of planned behavior were combined to understand the decision-making process of tea farmers adopting organic farming practices in Pu’er. The theoretical framework (see Figure 2) demonstrates how external and internal factors interact with each other to influence tea farmers’ decisions. DIT explains the process of the diffusion of organic agriculture as an innovation in communities by emphasizing five key attributes: comparative advantage, compatibility, complexity, testability, and observability. In this study, these five factors were captured in the questionnaire through the design of specific questions. For example, the questionnaire measures the impact of ‘comparative advantage’ by assessing farmers’ perceptions of the economic benefits and environmental advantages of organic agriculture; ‘compatibility’ by assessing farmers’ perceptions of organic agriculture in relation to existing farming methods; and ‘complexity’ by assessing farmers’ perceptions of the technical and technological advantages they may encounter during the conversion process. “Complexity” was measured by investigating the technical and economic barriers that farmers may encounter during the conversion process. In addition, the questionnaire included a survey on the feasibility of organic agriculture in small-scale trials and the visibility of success stories to assess ‘testability’ and ‘observability’. At the same time, the TPB was used to analyze farmers’ decision-making factors at the psychological level. In the design of the questionnaire, questions were developed to address three key elements of the TPB: attitude, subjective norms, and perceived behavioral control. Some of the questions in the questionnaire were designed to understand farmers’ perceptions of the economic benefits of organic farming and environmental protection to assess their attitudes; other questions focused on community expectations and social pressures to measure the impact of subjective norms on farmers; and we also investigated whether farmers had received training and technical support to understand their perceptions of the difficulty of transitioning to organic farming to assess perceived behavioral control. To better understand the relationship between external and internal factors, the theoretical frameworks of DIT and TPB were tightly integrated in the study. The five attributes of DIT are driven by government support and market incentives; e.g., through government-funded pilot projects and demonstration cases, farmers can more easily observe and experiment with the effects of organic agriculture, thus enhancing “observability”. The three psychological components of TPB are driven by market incentives and social influences; e.g., market incentives and the demonstration of success stories enhance farmers’ positive attitudes, while positive social expectations from the community reinforce subjective norms. In addition, government support and market conditions boosted farmers’ confidence in overcoming barriers, thus strengthening their perceived behavioral control. By integrating DIT and TPB, we designed a theoretical framework to capture the multiple considerations of tea farmers in Pu’er City when adopting organic agriculture. This approach not only helped us to clarify the influence of economic and technical factors, but also revealed the critical role of social and psychological factors in farmers’ decision-making process.

2.4. Analytical Methods

2.4.1. Descriptive Analysis

In order to more accurately describe the basic situation of tea farmers in Pu’er City, this study summarized and analyzed the socio-demographic and socio-economic characteristics of the respondents using frequency distribution statistics. The use of frequency distribution statistics enabled the description of the various characteristics of the respondents, including gender, age, literacy, income level, and land ownership, in order to demonstrate the distribution of different characteristics within the tea farmers’ group. This included the presentation of the gender ratio, the distribution of tea farmers across different age groups, the structure of the literacy levels of the tea farmers, and the distribution of their incomes. Furthermore, frequency distribution can elucidate the extent of the concentration of respondents on specific characteristics. For instance, it can reveal whether a particular income level or literacy level is dominant among tea farmers, which in turn reflects certain commonalities or differences in the socio-economic conditions of tea farmers.

2.4.2. Correlation Analysis

To gain a more comprehensive understanding of the relationship between different variables, this study employed a correlation matrix to examine the correlation between socio-demographic factors and respondents’ perceptions of organic farming, as well as their willingness to adopt organic farming practices. The correlation matrix not only demonstrated the linear relationship between the variables but also facilitated the identification of potentially significant associations. The analysis enabled the researchers to elucidate the extent to which different socio-demographic characteristics influence tea farmers’ willingness to adopt organic farming practices. This included investigating whether farmers with higher levels of education are more inclined to adopt organic farming or whether there are significant differences in perceptions of organic farming among different age groups. To illustrate the strength and direction of the correlation coefficients, heat maps were employed for visualization purposes. The findings of this analysis can provide robust data support for the development of more precise policies and interventions, which can more effectively promote the promotion and application of organic agriculture among tea farmers in Pu’er City.

2.4.3. Regression Analysis

In order to explore in more depth which factors significantly influence tea farmers’ willingness to adopt organic farming practices, this study constructed a multiple regression analysis model. Through the use of a regression analysis, the study was able to determine the extent to which each of the independent variables influenced tea farmers’ willingness to adopt. This analysis helped to identify key factors that should be prioritized when promoting organic agriculture. Regression modeling allows policymakers to implement more precise interventions based on data-driven results, thus promoting the effective promotion of organic agriculture. The specific steps of the regression analysis are as follows:
(1) Variable definition: Several independent variables were selected for the purpose of predicting tea farmers’ willingness to adopt organic agriculture, which was defined as the dependent variable. The independent variables included the respondents’ level of education, age, annual income, experience with tea planting, training in organic agriculture, and perceptions regarding the potential for organic agriculture to increase income and improve the environment. The dependent variable was the willingness of tea farmers to adopt organic agriculture.
(2) Data standardization: Prior to conducting the regression analysis, all independent variables were standardized to eliminate discrepancies in magnitude across variables of varying scales. This guarantees that the regression coefficients accurately represent the degree of influence exerted by each factor on the dependent variable.
(3) Regression model: A multiple linear regression model was employed, formulated as follows:
Y = β 0 + β 1 X 1 + β 2 X 2 + ⋯ + β n X n + ε
where Y represents the willingness to adopt organic farming; β0 is the intercept of the regression model; β1, β2, …, βn are the coefficients for each independent variable X1, X2, …, Xn; and ε is the error term.
(4) Estimation of coefficients: In this study, the least squares method was used to estimate the regression coefficients. The least squares method determines the best-fit line by minimizing the squared error between the predicted and actual values to calculate the regression coefficients for each independent variable.
(5) Interpretation of regression results: By analyzing the positivity, negativity, and magnitude of the regression coefficients, we derived the direction and strength of the influence of each independent variable on the tea farmers’ willingness to adopt organic farming.

3. Results

3.1. Statistical Characteristics of Tea Farmers in Pu’er City

The demographic characteristics of the tea farmers in Pu’er City reveal that the majority of respondents are middle-aged, with 59.3% of them aged between 40 and 59 years. Specifically, 30.4% are aged 50–59 years, and 28.9% are aged 40–49 years. Gender distribution shows that 59.9% of the respondents are male, while 40.1% are female. In terms of education level, more than half of the tea farmers (53.5%) have only completed elementary education or less, with 30.6% having completed junior high school, and only 7.0% possessing a college degree or higher. Regarding land ownership, the majority of tea farmers (42.0%) manage tea plantations ranging from 0.33 to 0.67 ha, while 19.1% have less than 0.33 ha, and 17.3% operate plantations larger than 1.33 ha. The annual household income of most respondents (46.3%) falls within the USD 2600–6700 range, with 23.8% earning less than USD 2600, and only 4.3% earning more than USD 20,200. Additionally, 37.0% of the tea farmers have 11–20 years of experience in tea cultivation, indicating a relatively experienced farming community, while 25.3% have 5–10 years of experience, and 21.0% have 21–30 years of experience. These results indicate that the tea farming community in Pu’er City is predominantly composed of middle-aged, male farmers with relatively low levels of formal education. Most farmers manage small- to medium-sized tea plantations and have moderate income levels, with a significant portion having substantial experience in tea cultivation (Figure 3).

3.2. Willingness to Adopt Organic Farming Practices Among Tea Farmers

Figure 4 shows the willingness of tea farmers in Pu’er to adopt organic farming practices and analyzes different demographic and socio-economic factors. The data show that all age groups below 60 years old are more willing to adopt organic farming, while older farmers (>60 years old) are less willing to adopt organic farming (Figure 4a). In total, 76.76% of farmers with university education or higher education expressed willingness to adopt organic farming, while 72.94% of farmers with only primary education were also willing to adopt organic farming (Figure 4b). In terms of tea garden size, farmers managing medium-sized plots (0.33–0.67 ha) expressed the greatest willingness, accounting for about 64.71% of this group (Figure 4c). In terms of experience in tea cultivation, farmers with 11–20 years of cultivation experience showed the most neutral willingness to adopt organic production, while farmers with less than 5 years and 5–10 years of cultivation experience were more willing to adopt organic agriculture (Figure 4d). Farmers with an annual income of less than USD 2600 had the highest willingness to adopt organic farming, which was about 83.78% (Figure 4e). In addition, the share of income from tea cultivation in household income also had a strong impact on willingness; farmers who relied on tea cultivation for a larger share of their income were more likely to adopt organic farming practices (Figure 4f). Training in organic farming was a strong determinant, with 84.27% of trained farmers willing to adopt organic farming practices, while only about 58.90% of untrained farmers were willing to adopt organic farming practices (Figure 4g). In addition, farmers who perceived organic tea production to be beneficial to the environment and health were more likely to adopt organic production practices, with more than 70% of farmers indicating a willingness to adopt these practices (Figure 4h). Finally, management style also influences adoption; independent operations or those with a more rigid management structure are more likely to adopt organic production practices than those individual farmers with more flexible management (Figure 4i).

3.3. Income and Education and Willingness to Adopt Organic Agriculture

The distribution of income by education level demonstrates that farmers with higher education levels possess higher income levels in comparison to those with lower education levels (Figure 5). Additionally, approximately 76.76% of farmers in this group are inclined to adopt organic production methods, in contrast to 72.94% of low-income farmers (Figure 4e). This indicates that farmers with higher levels of education may possess a greater capacity to comprehend the long-term advantages of organic agriculture. Additionally, they often have more resources (financial and informational) at their disposal, which can facilitate the adoption of organic practices. Consequently, the rate of adoption is higher among this group. Conversely, farmers with low levels of education and lower incomes may be more inclined to adopt organic production methods as a means of enhancing their income. These findings indicate that to enhance the overall adoption rate, it is essential to customize policy support or policy guidance to encompass diverse income and education levels. For instance, targeted assistance, such as subsidies and training programs, is crucial for farmers with lower incomes or lower education levels. Conversely, for those with higher incomes or more advanced education, it is vital to disseminate information about the long-term benefits of organic tea to promote the active adoption and implementation of organic tea production methods within this demographic.

3.4. Analysis of Regression Coefficients for Willingness to Adopt Organic Farming

Figure 6 illustrates the coefficients of a regression analysis of the various predictors that affect the willingness of tea farmers to adopt organic farming practices. The regression coefficients indicate the direction and magnitude of the effect of each predictor variable on the willingness to adopt organic farming. Positive values indicate an increase in willingness, while negative values indicate a decrease in willingness. The results demonstrated that the belief held by tea farmers that organic farming can increase their income exerts the greatest influence on their willingness to adopt, with a regression coefficient of 1.63. This indicates that economic gain is the most significant factor driving the adoption of organic farming by tea farmers. Tea farmers who had received organic agriculture training also exhibited a stronger willingness to adopt, with a regression coefficient of 0.99. This suggests that training in organic farming methods can increase tea farmers’ awareness of organic agriculture and play an important role in increasing their willingness to adopt organic agriculture. Furthermore, tea farmers who believe that organic farming can improve the environment are also more likely to adopt the method, with a regression coefficient of 0.88. However, the regression coefficient of the education level is −0.32, which suggests that tea farmers with higher education levels may be more risk-averse with regard to the economic viability of organic farming or the challenges associated with its implementation. This may potentially lead to a reduced inclination towards adopting this approach. The regression coefficients for age and annual household income were 0.01 and 0.00, respectively, which were close to zero, indicating that these factors did not have a significant effect on the intention to adopt. The regression coefficient for tea-growing experience was −0.06, indicating that experienced tea farmers may be more inclined to adhere to their established conventional growing methods rather than transitioning to organic farming practices. These findings elucidate the multifaceted factors influencing tea farmers’ adoption of organic agriculture, with financial gain and training support identified as the primary drivers, while education level and traditional experience may act as inhibitors to some extent.

3.5. Analysis of Relevance of Willingness to Adopt Organic Agriculture

Figure 7 presents a correlation analysis of the demographic factors of tea farmers in Pu’er City, their awareness of organic agriculture, and their willingness to adopt organic farming. This analysis provides further insight into the key factors influencing tea farmers’ adoption of organic agriculture. The results indicate that knowledge of organic standards shows a strong positive correlation with the willingness to adopt organic farming (0.47), suggesting that the deeper the farmers’ understanding of organic standards, the stronger their willingness to adopt organic practices. This finding highlights the importance of access to information and knowledge in promoting adoption decisions. Additionally, the correlation between receiving training and the willingness to adopt organic farming practices is 0.28, further demonstrating the role of training in enhancing farmers’ awareness and willingness to adopt organic agriculture. In contrast, tea farmers’ perceptions of organic agriculture’s environmental benefits (0.42) and the belief that organic tea is healthier (0.29) also exhibit positive correlations with their willingness to adopt organic agriculture, indicating that awareness of environmental protection and health factors influences farmers’ decision making. Traditional socio-economic factors such as age (0.01) and annual income (0.0014) show very weak correlations, consistent with the findings in Figure 6, further suggesting that these factors have little relationship with the willingness to adopt organic farming. Overall, the awareness of organic agriculture, training, and perceptions of environmental and health benefits are positively associated with the adoption of organic farming practices among tea farmers. Therefore, increasing the promotion of organic agriculture and enhancing training efforts may be key approaches to encouraging the widespread adoption of organic farming among tea farmers in Pu’er City.

4. Discussion

4.1. Comparison with Previous Studies

In this study, the factors influencing tea farmers’ willingness to adopt organic farming share similarities with, but also differ from, existing research on farmers’ adoption of organic farming practices. Previous studies have consistently emphasized that education and income are significant factors influencing the adoption of organic agriculture. The regression analysis in this study revealed a negative relationship between education level and the willingness to adopt organic farming, a finding that initially appears to be counterintuitive [16,21,30]. This trend may be attributed to the fact that more highly educated tea farmers tend to have a heightened awareness of the potential risks and uncertainties associated with organic farming. Prior research indicates that individuals with higher education levels often engage in more comprehensive cost–benefit analyses, which can lead them to adopt a more cautious stance toward economically volatile practices [33,34]. In the specific context of Pu’er’s tea farmers, those with higher educational backgrounds may be more cognizant of the challenges related to organic certification standards and the substantial initial investments required, thereby reducing their inclination to transition to organic methods. This observation contrasts with the findings of numerous studies that suggest farmers with higher levels of education are generally more likely to adopt organic farming, as they are better equipped to navigate the complexities of organic certification [35,36]. In Pu’er City, while tea farmers with higher education backgrounds showed a greater willingness to adopt organic practices (Figure 4), the overall educational level in the region remains relatively low (Figure 3). Consequently, the frequency analysis indicates that the presence of highly educated farmers does not necessarily establish education as a decisive factor for adoption. Instead, our regression analysis suggests that the challenges perceived by well-educated farmers in terms of meeting stringent certification criteria may deter them from fully embracing organic agriculture (Figure 6). The relationship between income and the adoption of organic farming is similarly complex. Traditional perspectives posit that higher-income farmers are more inclined to adopt organic practices, as they possess the financial resilience to absorb potential short-term losses [37]. However, this study found no significant correlation between household annual income and tea farmers’ willingness to adopt organic farming (Figure 6). Interestingly, farmers with an annual household income below USD 2600, who rely heavily on tea farming, comprising 36–50% of their total household income, were 24.81% more likely to transition to organic farming. This suggests that low-income farmers might perceive organic agriculture as an economic strategy to alleviate financial pressures associated with conventional farming. These findings are consistent with other studies in developing regions, where small-scale farmers often view organic production as an opportunity to differentiate their products and tap into premium markets [26,37,38]. Overall, these findings provide a deeper understanding of the socio-economic factors influencing the adoption of organic farming, particularly within the distinct cultural and market context of Pu’er’s tea industry. The results suggest that variables such as education and income do not function independently; rather, they are shaped by local challenges and perceptions of economic feasibility. This study offers a novel perspective by integrating DIT and TPB, allowing for an analysis that encompasses both socio-economic and psychological influences on tea farmers’ decision-making processes. Unlike earlier studies that tend to examine broader determinants, this research employs a dual-theoretical framework combining DIT and TPB to offer a comprehensive perspective. This integrated approach enables a more thorough examination of not only the socio-economic factors but also the psychological dynamics influencing the willingness of tea farmers to adopt organic practices. The insights generated from this study, particularly in the unique context of Yunnan’s tea sector, provide a valuable contribution to the discourse on sustainable agriculture.

4.2. Policy Implications

A significant correlation was observed between farmers’ knowledge of organic agriculture and their awareness of organic certification standards and traceability systems, as well as their willingness to adopt organic practices (the highest correlation was at 47%). Additionally, a 36% correlation was identified between annual income and willingness to adopt organic practices (Figure 7). However, these correlations reflect a more complex reality in the specific context of this study. Due to the generally low education levels and limited financial capital among tea farmers in Pu’er (Figure 3), they face challenges in understanding and implementing organic farming practices. As a result, relying solely on the willingness of highly educated tea farmers in Pu’er to adopt organic production may not lead to significant effects [39,40,41]. Policymakers should simplify the organic certification process or provide more intuitive, easily implementable technical support. Tailored training programs that combine local context with the needs of farmers with lower education levels are essential to help them overcome knowledge and cognitive barriers, ensuring that training effectively translates into a willingness to adopt organic farming practices [42,43]. Furthermore, the study reveals that households with an annual income below USD 2600 are more likely to adopt organic agriculture, especially when tea income accounts for 36–50% of total household income (Figure 6). This finding contrasts with previous studies, which have suggested that higher-income farmers are better equipped to bear the initial costs of transitioning to organic agriculture. However, in this study, low-income tea farmers in Pu’er may view organic agriculture as an economic strategy to mitigate the pressure of low prices in traditional agricultural markets by producing differentiated, high-value-added products. This implies that policymakers should focus on the needs of these farmers and provide direct economic support, such as subsidies or loans, while creating stable market channels (e.g., ensuring consistent market access or price guarantees for organic products) to offer long-term economic incentives for low-income farmers [44,45]. Such a policy framework should not only offset the economic costs of transitioning to organic farming but also ensure that farmers can achieve sustainable income through the price premium of organic products [46,47]. Finally, the study finds a significant positive correlation between farmers’ perceptions of the environmental benefits of organic agriculture and the health benefits of organic tea, and their willingness to adopt organic farming practices. Given Pu’er’s tea-centric industrial structure and the increasing consumer awareness of health and environmental issues, policymakers could further promote and publicize the ecological and public health benefits of organic agriculture [44,46]. This would also provide new opportunities for Pu’er to develop a more sustainable organic tea supply chain.
In conclusion, policymakers aiming to encourage the adoption of organic agriculture among tea farmers in Pu’er City must consider a variety of factors, avoiding a one-size-fits-all approach that fails to address the unique circumstances of different farmer groups. First and foremost, policies should account for the economic conditions and educational levels of various groups of tea farmers, as well as their perceptions of the environmental and health benefits of organic agriculture. Training and support programs must be flexible and targeted, effectively addressing the specific barriers faced by tea farmers during the transition to organic production [48,49,50]. Additionally, guidance on organic farming techniques and organic certification requirements should be actively promoted to assist farmers in connecting with the organic market and to boost their confidence in making the transition [51,52]. Implementing such comprehensive policies and services can more effectively promote the development of organic tea cultivation in Pu’er, establishing a mutually beneficial model for both farmers and the environment. To further enhance the adoption of organic farming among low-income tea farmers, policymakers should consider optimizing the organic certification process by reducing costs and simplifying requirements, making it more accessible to small-scale farmers. Additionally, targeted subsidies could be introduced to cover initial transition costs, such as purchasing organic inputs or compensating for yield reductions during the conversion period. This could involve creating a tiered certification system, where basic organic standards are recognized initially, with incremental incentives for more advanced certification levels as farmers gain experience. By implementing these tailored strategies, the development of organic agriculture in Pu’er City will become more sustainable, offering a successful model for other tea-producing regions.

4.3. Limitations

This study aimed to explore the factors influencing tea farmers’ willingness to adopt organic farming from multiple perspectives. However, it is acknowledged that the study was not without limitations. Firstly, the questionnaire utilized in this study solely collected data regarding the current attitudes and behaviors of tea farmers, which may restrict the ability to draw conclusions regarding the causal relationship between the factors influencing the adoption of organic farming and subsequent actual behaviors [53]. Future research could employ longitudinal methods to track farmers’ behavioral and psychological changes, thereby gaining a deeper understanding of how farmers’ willingness to adopt organic farming practices may change in response to changes in market conditions or government policies [54,55]. Secondly, it is possible that farmers may overstate their willingness to adopt organic farming practices due to social pressures or due to an inaccurate recollection of past experiences associated with organic farming [56]. Future research could address the limitations of this study by increasing the scale and number of studies and introducing third-party observations [57]. Additionally, this study focused on the influence of socio-economic and psychological factors on tea farmers’ willingness to adopt organic methods. Future research could further examine the influence of market dynamics on organic adoption intentions by analyzing fluctuations in tea prices, changes in demand for organic products, and competition in the tea industry [58].

5. Conclusions

This study combines the diffusion of innovations theory and the theory of planned behavior to explore the influencing factors and their underlying reasons for tea farmers’ adoption of organic agricultural production methods in Pu’er City, Yunnan Province. The results of the study showed that tea farmers’ perception of the economic benefits of organic agriculture was the most important factor influencing their willingness to adopt. In the regression analysis, the perception that organic agriculture can increase income was 0.99, indicating that technical training plays an important role in increasing the adoption rate. The regression coefficient of 0.88 for farmers who had a positive perception of organic farming in improving the environment and health showed the significant influence of environmental and health benefits in enhancing adoption intentions. Contrary to the conventional view, the effect of the education level was not significant in this study. The data showed that tea farmers with a higher education level showed more caution in adopting organic farming with a regression coefficient of −0.32. In contrast, low-income households with an annual income of less than USD 2600 and whose main source of income was tea were 24.81% more likely to use organic farming practices than in other scenarios. The novelty of this study lies in the first application of the integration of DIT and TPB theories to the study of tea farmers’ adoption of organic agriculture in Pu’er City, revealing the complex relationship among economic, environmental, and psychosocial factors. Through an in-depth analysis of tea farmers’ behaviors in this specific context in Pu’er City, we not only provide new insights on organic agriculture adoption, but also suggest specific policy recommendations. In order to promote organic agriculture more effectively, policymakers should pay attention to tea farmers’ economic status, educational background, and level of awareness of environmental and health benefits. This study suggests streamlining the organic certification process, providing technical training and economic support, and promoting successful organic farming practices in order to develop flexible and targeted policies. In addition, the government and relevant stakeholders should actively develop stable market channels and provide price guarantees to reduce the economic risks faced by tea farmers during the transition process. Overall, this study not only provides a theoretical basis and policy recommendations for the development of organic agriculture in Pu’er, but also provides useful references for the promotion of organic agriculture in other tea-producing regions.

Author Contributions

Conceptualization, H.L. and S.Y.; methodology, H.L.; validation, H.L., J.C. and Y.C.; formal analysis, H.L.; investigation, H.L. and J.Y.; resources, W.G.; data curation, H.L. and J.Y.; writing—original draft preparation, H.L.; writing—review and editing, J.C. and Y.C.; visualization, H.L.; supervision, J.C. and Y.C.; project administration, W.G.; funding acquisition, J.C. and Y.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Major Science and Technology Project of Yunnan Province, grant number 202202AE090029.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The datasets used during the current study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Çakmakçi, R.; Salik, M.A.; Çakmakçi, S. Assessment and Principles of Environmentally Sustainable Food and Agriculture Systems. Agriculture 2023, 13, 1073. [Google Scholar] [CrossRef]
  2. Arhin, I.; Li, J.J.; Mei, H.L.; Amoah, M.; Chen, X.; Jeyaraj, A.; Li, X.H.; Liu, A.J. Looking into the future of organic tea production and sustainable farming: A systematic review. Int. J. Agric. Sustain. 2022, 20, 942–954. [Google Scholar] [CrossRef]
  3. Carrié, R.; Smith, H.G.; Ekroos, J. Sensitivity to agricultural inputs and dispersal limitation determine the response of arable plants to time since transition to organic farming. J. Appl. Ecol. 2024, 61, 1227–1242. [Google Scholar] [CrossRef]
  4. Panday, D.; Bhusal, N.; Das, S.; Ghalehgolabbehbahani, A. Rooted in Nature: The Rise, Challenges, and Potential of Organic Farming and Fertilizers in Agroecosystems. Sustainability 2024, 16, 1530. [Google Scholar] [CrossRef]
  5. Cobb, D.; Feber, R.; Hopkins, A.; Stockdale, L.; O’Riordan, T.; Clements, B.; Firbank, L.; Goulding, K.; Jarvis, S.; Macdonald, D. Integrating the environmental and economic consequences of converting to organic agriculture: Evidence from a case study. Land Use Pol. 1999, 16, 207–221. [Google Scholar] [CrossRef]
  6. Meng, F.Q.; Qiao, Y.H.; Wu, W.L.; Smith, P.; Scott, S. Environmental impacts and production performances of organic agriculture in China: A monetary valuation. J. Environ. Manag. 2017, 188, 49–57. [Google Scholar] [CrossRef]
  7. Shin, E.; Shin, Y.; Lee, S.W.; An, K. Evaluating the Environmental Factors of Organic Farming Areas Using the Analytic Hierarchy Process. Sustainability 2024, 16, 2395. [Google Scholar] [CrossRef]
  8. Misselbrook, T.H.; Menzi, H.; Cordovil, C. Preface—Recycling of organic residues to agriculture: Agronomic and environmental impacts. Agric. Ecosyst. Environ. 2012, 160, 1–2. [Google Scholar] [CrossRef]
  9. Wang, P.C.; Liu, F.C.; Lee, D.C.; Lin, M.Y. Environmental Knowledge, Values, and Responsibilities Help to Enhance Organic Farming Intentions: A Case Study of Yunlin County, Taiwan. Agriculture 2023, 13, 1476. [Google Scholar] [CrossRef]
  10. Feledyn-Szewczyk, B.; Kopinski, J. Productive, Environmental and Economic Effects of Organic and Conventional Farms-Case Study from Poland. Agronomy 2024, 14, 793. [Google Scholar] [CrossRef]
  11. Heinrichs, J.; Kuhn, T.; Pahmeyer, C.; Britz, W. Economic effects of plot sizes and farm-plot distances in organic and conventional farming systems: A farm-level analysis for Germany. Agric. Syst. 2021, 187, 102992. [Google Scholar] [CrossRef]
  12. Martín-García, J.; Gómez-Limón, J.A.; Arriaza, M. Conversion to organic farming: Does it change the economic and environmental performance of fruit farms? Ecol. Econ. 2024, 220, 108178. [Google Scholar] [CrossRef]
  13. Liang, H.Z.; Meng, Y. Impact of direct payments and non-financial support on smallholder income from environmentally friendly agriculture in Tohoku region, Japan. J. Environ. Manag. 2024, 351, 119698. [Google Scholar] [CrossRef] [PubMed]
  14. Karipidis, P.; Karypidou, S. Factors that Impact Farmers’ Organic Conversion Decisions. Sustainability 2021, 13, 4715. [Google Scholar] [CrossRef]
  15. Rust, N.A.; Stankovics, P.; Jarvis, R.M.; Morris-Trainor, Z.; de Vries, J.R.; Ingram, J.; Mills, J.; Glikman, J.A.; Parkinson, J.; Toth, Z.; et al. Have farmers had enough of experts? Environ. Manag. 2022, 69, 31–44. [Google Scholar] [CrossRef]
  16. Quoc, T.N.; Tiet, T. The role of peer influence and norms in organic farming adoption: Accounting for farmers’ heterogeneity. J. Environ. Manag. 2022, 320, 115909. [Google Scholar] [CrossRef]
  17. David, L.; Streith, M.; Michaud, A.; Dambrun, M. Organic and Conventional Farmers’ Mental Health: A Preliminary Study on the Role of Social Psychological Mediators. Sustainability 2024, 16, 1926. [Google Scholar] [CrossRef]
  18. Liu, H.C.; Jiang, M.M.; Li, Q.W. Nonstereoselective dissipation of sulfoxaflor in different Puer tea processing. Food Sci. Nutr. 2020, 8, 4929–4935. [Google Scholar] [CrossRef]
  19. Wang, S.A.; Qiu, Y.; Gan, R.Y.; Zhu, F. Chemical constituents and biological properties of Pu-erh tea. Food Res. Int. 2022, 154, 110899. [Google Scholar] [CrossRef]
  20. Qiao, Y.H.; Halberg, N.; Vaheesan, S.; Scott, S. Assessing the social and economic benefits of organic and fair trade tea production for small-scale farmers in Asia: A comparative case study of China and Sri Lanka. Renew. Agric. Food Syst. 2016, 31, 246–257. [Google Scholar] [CrossRef]
  21. Zhen, H.Y.; Qiao, Y.H.; Ju, X.H.; Hashemi, F.; Knudsen, M.T. Organic conversion tea farms can have comparable economic benefits and less environmental impacts than conventional ones-A case study in China. Sci. Total Environ. 2023, 877, 162698. [Google Scholar] [CrossRef] [PubMed]
  22. Doanh, N.K.; Thuong, N.T.T.; Heo, Y. Impact of Conversion to Organic Tea Cultivation on Household Income in the Mountainous Areas of Northern Vietnam. Sustainability 2018, 10, 4475. [Google Scholar] [CrossRef]
  23. Zheng, R.R.; Ma, Y.L.; Liu, L.X.; Jiang, B.Y.; Ke, R.M.; Guo, S.S.; He, D.C.; Zhan, J.S. Synergistic Improvement of Production, Economic Return and Sustainability in the Tea Industry through Ecological Pest Management. Horticulturae 2022, 8, 1155. [Google Scholar] [CrossRef]
  24. Deka, N.; Goswami, K. Economic sustainability of organic cultivation of Assam tea produced by small-scale growers. Sustain. Prod. Consum. 2021, 26, 111–125. [Google Scholar] [CrossRef]
  25. Karki, L.; Schleenbecker, R.; Hamm, U. Factors influencing a conversion to organic farming in Nepalese tea farms. J. Agric. Rural Dev. Trop. Subtrop. 2011, 112, 113–123.26. [Google Scholar]
  26. Martens, B.V.D.; Goodrum, A.A. The diffusion of theories: A functional approach. J. Am. Soc. Inf. Sci. Technol. 2006, 57, 330–341. [Google Scholar] [CrossRef]
  27. Parra-Lopez, C.; De-Haro-Giménez, T.; Calatrava-Requena, J. Diffusion and adoption of organic farming in the southern Spanish olive groves. J. Sustain. Agric. 2007, 30, 105–151. [Google Scholar] [CrossRef]
  28. Li, J.; Jiang, R.; Tang, X.Y. Assessing psychological factors on farmers’ intention to apply organic manure: An application of extended theory of planned behavior. Environ. Dev. Sustain. 2024, 26, 2467–2491. [Google Scholar] [CrossRef]
  29. Issa, I.; Hamm, U. Adoption of Organic Farming as an Opportunity for Syrian Farmers of Fresh Fruit and Vegetables: An Application of the Theory of Planned Behaviour and Structural Equation Modelling. Sustainability 2017, 9, 2024. [Google Scholar] [CrossRef]
  30. Jiang, Y.H.; Arafat, Y.; Letuma, P.L.; Ali, L.; Tayyab, M.; Waqas, M.; Li, Y.C.; Lin, W.W.; Lin, S.; Lin, W.X. Restoration of Long-Term Monoculture Degraded Tea Orchard by Green and Goat Manures Applications System. Sustainability 2019, 11, 1011. [Google Scholar] [CrossRef]
  31. Badgley, C.; Moghtader, J.; Quintero, E.; Zakem, E.; Chappell, M.J.; Avilés-Vázquez, K.; Samulon, A.; Perfecto, I. Organic agriculture and the global food supply. Renew. Agric. Food Syst. 2007, 22, 86–108. [Google Scholar] [CrossRef]
  32. Wang, Y.C.; Chen, C.T.; Li, R.Y.; Lu, Y.H.; Chiang, L.C. Climate risk analysis of low-altitude tea gardens in central Taiwan using a Bayesian network. Environ. Monit. Assess. 2024, 196, 809. [Google Scholar] [CrossRef] [PubMed]
  33. Xie, S.W.; Feng, H.X.; Yang, F.; Zhao, Z.D.; Hu, X.D.; Wei, C.Y.; Liang, T.; Li, H.T.; Geng, Y.B. Does dual reduction in chemical fertilizer and pesticides improve nutrient loss and tea yield and quality? A pilot study in a green tea garden in Shaoxing, Zhejiang Province, China. Environ. Sci. Pollut. Res. 2019, 26, 2464–2476. [Google Scholar] [CrossRef] [PubMed]
  34. Yang, X.K.; Chen, Q.H.; Lin, N.M.; Han, M.Z.; Chen, Q.; Zheng, Q.Q.; Bin, G.; Liu, F.B.; Xu, Z.Y. Chinese consumer preferences for organic labels on Oolong tea: Evidence from a choice experiment. Int. Food Agribus. Manag. Rev. 2021, 24, 545–561. [Google Scholar] [CrossRef]
  35. Qiao, Y.H.; Martin, F.; Cook, S.; He, X.Q.; Halberg, N.; Scott, S.; Pan, X.H. Certified Organic Agriculture as an Alternative Livelihood Strategy for Small-scale Farmers in China: A Case Study in Wanzai County, Jiangxi Province. Ecol. Econ. 2018, 145, 301–307. [Google Scholar] [CrossRef]
  36. Phromthep, P.; Torut, B. Comparing the Collaboration of Smallholder Farmers through Participatory Guarantee System Practices in Northeastern Thailand. Sustainability 2024, 16, 4186. [Google Scholar] [CrossRef]
  37. Tshotsho; Lippert, C.; Zikeli, S.; Krimly, T.; Barissoul, A.; Feuerbacher, A. The role of management and farming practices, yield gaps, nutrient balance, and institutional settings in the context of large-scale organic conversion in Bhutan. Agric. Syst. 2024, 220, 104057. [Google Scholar] [CrossRef]
  38. Wu, S.; Li, S.W. Collaboration to Address the Challenges Faced by Smallholders in Practicing Organic Agriculture: A Case Study of the Organic Sorghum Industry in Zunyi City, China. Agriculture 2024, 14, 726. [Google Scholar] [CrossRef]
  39. Bloom, S.M.; Duram, L.A. A framework to assess state support of organic agriculture. J. Sustain. Agric. 2007, 30, 105–123. [Google Scholar] [CrossRef]
  40. Sano, D.; Prabhakar, S. Some Policy Suggestions for Promoting Organic Agriculture in Asia. J. Sustain. Agric. 2010, 34, 80–98. [Google Scholar] [CrossRef]
  41. Youngberg, G.; DeMuth, S.P. Organic agriculture in the United States: A 30-year retrospective. Renew. Agric. Food Syst. 2013, 28, 294–328. [Google Scholar] [CrossRef]
  42. Barbosa, M.W. Government Support Mechanisms for Sustainable Agriculture: A Systematic Literature Review and Future Research Agenda. Sustainability 2024, 16, 2185. [Google Scholar] [CrossRef]
  43. Martínez-Moreno, M.M.; Buitrago, E.M.; Yñiquez, R.; Puig-Cabrera, M. Circular economy and agriculture: Mapping circular practices, drivers, and barriers for traditional table-olive groves. Sustain. Prod. Consum. 2024, 46, 430–441. [Google Scholar] [CrossRef]
  44. Aznar-Sánchez, J.A.; Velasco-Muñoz, J.F.; López-Felices, B.; del Moral-Torres, F. Barriers and Facilitators for Adopting Sustainable Soil Management Practices in Mediterranean Olive Groves. Agronomy 2020, 10, 506. [Google Scholar] [CrossRef]
  45. Miah, M.A.M.; Bell, R.W.; Haque, E.; Rahman, M.W.; Sarkar, M.A.R.; Rashid, M.A. Conservation agriculture practices improve crop productivity and farm profitability when adopted by Bangladeshi smallholders in the Eastern Gangetic Plain. Outlook Agric. 2023, 52, 11–21. [Google Scholar] [CrossRef]
  46. Simin, M.T.; Glavas-Trbic, D.; Petrovic, M.; Komaromi, B.; Vukelic, N.; Radojevic, V. Can organic agriculture be competitive? Custos Agron. Line 2020, 16, 429–444. [Google Scholar]
  47. Zander, K.; Nieberg, H.; Offermann, F. Financial relevance of organic farming payments for Western and Eastern European organic farms. Renew. Agric. Food Syst. 2008, 23, 53–61. [Google Scholar] [CrossRef]
  48. Breustedt, G.; Latacz-Lohmann, U.; Tiedemann, T. Organic or conventional? Optimal dairy farming technology under the EU milk quota system and organic subsidies. Food Policy 2011, 36, 223–229. [Google Scholar] [CrossRef]
  49. Zhang, Y.N.; Gao, X.P.; Sun, B.W.; Liu, X.B. Hydrodynamics, Diagenesis and Hypoxia Variably Drive Benthic Oxygen Flux in a River-Reservoir System. Water Resour. Res. 2024, 60, e2023WR035449. [Google Scholar] [CrossRef]
  50. Pawlewicz, A. Change of Price Premiums Trend for Organic Food Products: The Example of the Polish Egg Market. Agriculture 2020, 10, 35. [Google Scholar] [CrossRef]
  51. Emeana, E.M.; Trenchard, L.; Dehnen-Schmutz, K.; Shaikh, S. Evaluating the role of public agricultural extension and advisory services in promoting agro-ecology transition in Southeast Nigeria. Agroecol. Sustain. Food Syst. 2019, 43, 123–144. [Google Scholar] [CrossRef]
  52. Jin, G.Q.; Chen, H.X.; Zhang, Z.T.; Jiang, Q.H.; Liu, Z.Y.; Tang, H.W. Transport of Phosphorus in the Hyporheic Zone. Water Resour. Res. 2022, 58, e2021WR031292. [Google Scholar] [CrossRef]
  53. McCann, E.; Sullivan, S.; Erickson, D.; DeYoung, R. Environmental awareness, economic orientation, and farming practices: A comparison of organic and conventional farmers. Environ. Manag. 1997, 21, 747–758. [Google Scholar] [CrossRef] [PubMed]
  54. Sooriyakumar, K.; Sivashankar, S.; Sireeranhan, A. Farmers’ willingness to pay for the ecosystem services of organic farming: A locality study in Valikamam area of Sri Lanka. Appl. Ecol. Environ. Res. 2019, 17, 13803–13815. [Google Scholar] [CrossRef]
  55. Kondylis, F.; Mueller, V.; Zhu, S. Measuring agricultural knowledge and adoption. Agric. Econ. 2015, 46, 449–462. [Google Scholar] [CrossRef]
  56. Wu, J.P.; Qiu, G.Q.; Wu, C.M.; Jiang, W.W.; Jin, J.H. Federated learning for network attack detection using attention-based graph neural networks. Sci. Rep. 2024, 14, 19088. [Google Scholar] [CrossRef]
  57. Qiao, D.; Li, N.J.; Cao, L.; Zhang, D.S.; Zheng, Y.A.; Xu, T. How Agricultural Extension Services Improve Farmers’ Organic Fertilizer Use in China? The Perspective of Neighborhood Effect and Ecological Cognition. Sustainability 2022, 14, 7166. [Google Scholar] [CrossRef]
  58. Koppenberg, M. Markups, organic agriculture and downstream concentration at the example of European dairy farmers. Agric. Econ. 2023, 54, 161–178. [Google Scholar] [CrossRef]
Sustainability 16 10035 g001
Figure 1. Geographic location of surveyed areas in China.
Figure 1. Geographic location of surveyed areas in China.
Sustainability 16 10035 g001
Sustainability 16 10035 g002
Figure 2. Theoretical framework.
Figure 2. Theoretical framework.
Sustainability 16 10035 g002
Sustainability 16 10035 g003
Figure 3. Demographic characteristics of tea farmers in Pu’er City, Yunnan Province. (a) Age distribution; (b) gender distribution; (c) education level; (d) area of tea plantations; (e) distribution of annual household income; and (f) number of years of tea cultivation.
Figure 3. Demographic characteristics of tea farmers in Pu’er City, Yunnan Province. (a) Age distribution; (b) gender distribution; (c) education level; (d) area of tea plantations; (e) distribution of annual household income; and (f) number of years of tea cultivation.
Sustainability 16 10035 g003
Sustainability 16 10035 g004
Figure 4. The willingness of tea farmers to adopt organic farming practices. (a) Age distribution; (b) education level; (c) size of tea plantation; (d) tea-growing experience; (e) annual household income; (f) proportion of income from tea cultivation; (g) training in organic agriculture; (h) perception of organic tea production; (i) management practices. Willingness (1 = Yes, 0 = No).
Figure 4. The willingness of tea farmers to adopt organic farming practices. (a) Age distribution; (b) education level; (c) size of tea plantation; (d) tea-growing experience; (e) annual household income; (f) proportion of income from tea cultivation; (g) training in organic agriculture; (h) perception of organic tea production; (i) management practices. Willingness (1 = Yes, 0 = No).
Sustainability 16 10035 g004
Sustainability 16 10035 g005
Figure 5. Distribution of annual income across different education levels.
Figure 5. Distribution of annual income across different education levels.
Sustainability 16 10035 g005
Sustainability 16 10035 g006
Figure 6. Regression coefficients for willingness to adopt organic farming.
Figure 6. Regression coefficients for willingness to adopt organic farming.
Sustainability 16 10035 g006
Sustainability 16 10035 g007
Figure 7. Correlation analysis of tea farmers’ willingness to adopt organic farming.
Figure 7. Correlation analysis of tea farmers’ willingness to adopt organic farming.
Sustainability 16 10035 g007
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Li, H.; Yang, S.; Yan, J.; Gao, W.; Cui, J.; Chen, Y. From Conventional to Organic Agriculture: Influencing Factors and Reasons for Tea Farmers’ Adoption of Organic Farming in Pu’er City. Sustainability 2024, 16, 10035. https://doi.org/10.3390/su162210035

AMA Style

Li H, Yang S, Yan J, Gao W, Cui J, Chen Y. From Conventional to Organic Agriculture: Influencing Factors and Reasons for Tea Farmers’ Adoption of Organic Farming in Pu’er City. Sustainability. 2024; 16(22):10035. https://doi.org/10.3390/su162210035

Chicago/Turabian Style

Li, Hao, Shuqi Yang, Juping Yan, Wangsheng Gao, Jixiao Cui, and Yuanquan Chen. 2024. "From Conventional to Organic Agriculture: Influencing Factors and Reasons for Tea Farmers’ Adoption of Organic Farming in Pu’er City" Sustainability 16, no. 22: 10035. https://doi.org/10.3390/su162210035

APA Style

Li, H., Yang, S., Yan, J., Gao, W., Cui, J., & Chen, Y. (2024). From Conventional to Organic Agriculture: Influencing Factors and Reasons for Tea Farmers’ Adoption of Organic Farming in Pu’er City. Sustainability, 16(22), 10035. https://doi.org/10.3390/su162210035

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop