Agriculture is the foundation of a country or region’s development and the guarantee for the continuous development and progress of the entire national economy. On the one hand, agriculture is the most basic sector of material production, providing humanity with a material foundation for survival, and is the source of a society’s clothing, food, and survival. On the other hand, agriculture provides raw materials for other sectors, such as industry, and is a necessary condition for the existence and development of other material and all non-material sectors of production. The economic and social development of a country or region cannot be separated from agriculture and its development of agriculture is the primary condition for all production. At the same time, agricultural development is closely related to climate change. On the one hand, agriculture is the fundamental industry most affected by climate change (Wang et al., 2023). Climate changes such as drought and high temperatures have actually led to a 3–8% decrease in global grain production of rice, wheat, corn, and other crops (Zou, 2021). China’s meteorological disasters caused by climate change events have reduced the production of major grain crops by about 10% while climate change has led to a decrease of about 5% in food protein and trace elements (Zou, 2021). On the other hand, agriculture has dual attributes, namely as carbon source and carbon sink. Agricultural production activities are not only an important source of greenhouse gas emissions, but also have a strong carbon sink effect. According to the fourth assessment report released by the IPCC in 2007, agricultural emissions of CH₄ and NO₂ account for 50 and 60% of total human activities respectively, while their greenhouse gas emissions account for 14% of the global total, making them the second largest source of greenhouse gas emissions in the world between electric heating production and exhaust emissions (Intergovernmental Panel on Climate Change, 2007). At the same time, agricultural production also has a strong carbon sequestration effect. It can achieve biological carbon sequestration through its own multiple channels and methods, including the photosynthesis of plants in various ecosystems such as farmland, forests, and grasslands. Through these methods, about 30% of global annual anthropogenic carbon emissions can be absorbed (Wang et al., 2023). In view of this, the green, low-carbon, sustainable, and high-quality development of agriculture has become a focus and concern for countries around the world.

China is a major agricultural country and issues related to agriculture, rural areas, and farmers are a global concern that affects the development of our party and people’s cause, as well as a fundamental dilemma that affects the national economy and people’s livelihoods. Currently, 500 million out of China’s 1.4 billion people still reside in rural areas. Farmers are the fundamental force behind China’s economic and social development as well as the main force driving the country’s modernization. Solving the problems of agriculture, rural areas, and farmers is a requirement for achieving China’s industrialization, urbanization, and socialist modernization, as well as an effective way to guarantee achieving the goal of the people’s common prosperity. Among the issues related to agriculture, rural areas, and farmers, increasing the income of farmers is the central task of rural work (State Council Office, 2016) and the key to solving rural issues.

At the same time, China has entered a new era of ecological civilization construction. Adhering to the concept of a community with a shared future for mankind and the belief that “green mountains and clear waters are invaluable assets,” China has actively participated in international carbon neutrality and climate change actions, and pledged to the world to achieve carbon peak by 2030 and carbon neutrality by 2060 (Zou, 2021). Guided by the “dual carbon” goal, green and low-carbon agriculture that continuously increases yield, reduces input, reduces pollution, and improves efficiency (Zhang, 2019) has become the development direction of China’s agriculture, hence the country’s agricultural development has begun a new stage.

At present, China has become a moderately prosperous society and is moving toward the second centenary goal. If China wants to be strong, agriculture must be strong; if China wants to be beautiful, rural areas must be beautiful; if China wants to be rich, farmers must be rich (Zhang and Cui, 2023). Therefore, in the new stage of development, the issue of “agriculture, rural areas and farmers” is of primary importance for China to enter the new era of building a socialist and modernized strong country, while the core issue of China’s agriculture and rural development is the growth of farmers’ income (Xiao, 2021). Thus, promoting the continuous growth of farmers’ income has become the core and key to solving the problems of agriculture, rural areas, and farmers. Family farming is the most important and stable basis of farmers’ income in China. In view of this, under the “dual carbon” goal, studying the impact of the green and low carbon agricultural production mode on farmers’ income has guiding significance for China in terms of solving the “three rural issues| while realizing the high-quality development and modernization of agriculture.

China is a united multi-ethnic country, therefore in order to achieve socialist modernization and common prosperity, “No one nation can be left behind” (Xi, 2021). Guizhou Province has a large number of ethnic minorities and is also an economically and socially underdeveloped province. It is a region that requires special attention to consolidate achievements concerning poverty alleviation while achieving the goal of common prosperity. Y Town is a remote township under the jurisdiction of Zhijin County, Guizhou Province. According to field research results, of the 41,055.43 mu of arable land in the town, about 80 per cent is mountainous, making it a mountain economy and agricultural town. By the end of 2021, the town had a total registered residence of 44,103, of which 28,924 are ethnic minorities such as Chuanqing, Miao, Bai, accounting for 65.58% of the town’s total population. It is a typical township where ethnic minorities gather and live. Hence, it is of great practical significance to study the influence of green and low-carbon agricultural development on farmers’ income in economically underdeveloped ethnic minority mountainous agricultural areas of China in order to solve the problems of agriculture, rural areas, and farmers, thereby comprehensively realizing agriculture’s modernization and a common prosperity.

At present, there is a wealth of research in domestic and foreign academic circles on the development of green and low-carbon agriculture and its impact on farmers’ income. These studies focus mainly on the concepts, influencing factors, low-carbon agriculture or agricultural green production policies, and the impact of low-carbon agriculture on farmers’ income.

Result Analysis and Discussion. In this section, the least square method (OLS) regression is used to estimate Equation (2) of household income determination and the results are shown in Table 3.

The regression results in Table 3 show that the “low-carbon” variable passes the significance test at the level of 1% and the coefficient is negative. It shows that the household income level of farmers who use plastic film is lower than that of farmers who do not use plastic film. There is a positive correlation between green and low-carbon agricultural production methods farmers’ and household income levels. The household income level of farmers who use low-carbon production methods for agricultural production is higher than that of farmers who use non low-carbon production methods for agricultural production. Low carbon agricultural production methods can promote the growth of household income for farmers. The research results of Ma et al. (2022) also prove this: the adoption of green agricultural production technologies by agricultural producers can reduce agricultural pollution emissions, increase agricultural output value, and thus improve farmers’ income and well-being. This is basically consistent with the research findings of Chi et al. (2021), which showed a clear “U” relationship between green and low-carbon agricultural production technologies and household agricultural income. The research conclusion of this article is also consistent with the actual production of farmers. Due to the need to save production costs, the plastic film used by the sample farmers is non-degradable. Due to the time-consuming and laborious removal of plastic films as well as the insufficient awareness of environmental hazards among farmers, most of the sample farmers choose to dispose of plastic residues in farmland, causing soil pollution (Koskei et al., 2021), which has adverse effects on the environment and human health (Rodrigues et al., 2019). Non low-carbon agricultural production methods will have negative externalities on society, thereby reducing the welfare and income levels of farmers. From the perspective of farmers, in the short term sample farmers improve agricultural yield and income by adopting a non-low carbon production method relying on agricultural plastic film for agricultural production, which can resist adverse environments and provide superior growth and development conditions for crops. However, in the long run, adopting non-low carbon agricultural production methods is irrational, as soil pollution can reduce agricultural yield and product quality, leading to a decrease in household income for farmers.

The age variable passes the significance test at the 5% level, and the coefficient is negative. It shows that the average disposable monthly income of rural households will decrease with an increase in age. This was also confirmed by the studies of Wang et al. (2021) and Xiang et al. (2022). This is because, compared to older farmers, young farmers have more energy, are more receptive to new things, can obtain modern agricultural production and management information more efficiently, and can learn and master modern agricultural knowledge and technology more quickly.

The marital status variable passed the significance test at the level of 1%, and the coefficient was positive, indicating that the income level of married farmer families was significantly higher than that of unmarried farmer families. This is consistent with the research conclusions of Agwu and Orji (2013), Fan (2020), Zhang (2021), and Wonder et al. (2022).

The variable of educational attainment passes the significance test at the level of 1% while the coefficient is positive. This indicates that education level plays a significant role in promoting the household income of farmers, that is, the longer the duration of education, the higher the education level, the higher the household income level of farmers. This was also confirmed by the studies of Liu and Zhao (2020), Wang et al. (2021), Xiang et al. (2022), and Mina et al. (2022).

The health status variable passed the significance test at the 1% level and had a positive coefficient. It shows that this variable has a positive promoting effect on the income of rural households, that is, the healthier the body, the higher the income level of rural households. Consistent conclusions have been drawn by Fan (2020), Zhang (2021), Xiang et al. (2022), and Mina et al. (2022).

The variable of “new rural social endowment insurance” also passed the significance test at the level of 1%, and the coefficient was positive. This shows that the new rural social endowment insurance has a significant role in promoting the household income of rural households, and the household income level of insured households is significantly higher than the total household income of non-insured households. This is consistent with the findings of Zhang et al. (2015) and Zhang (2021).

The gender variable did not pass the significance test, indicating that the gender of the household head of the surveyed rural households had no significant impact on the household income of rural households, which was consistent with the research results of Zhang (2021) and Xiang et al. (2022). This is because family decisions are collective, and although the head of the household plays a major role in family decision-making, it is not necessarily decisive. Ethnic variables did not pass the significance test, indicating that ethnic identity has no significant impact on rural household income, which is contrary to the research results of Tang and Huang (2017) and Fan (2020). The reasons are as follows: First, regional differences. The sample region involved in this study – Guizhou Province – is an area where ethnic minorities gather and has a high degree of ethnic integration. There is no difference between different ethnic identities in education, employment and other aspects. Second, China’s long-standing policy of ethnic equality has produced practical results. Political status variables did not pass the significance test, indicating that party membership has no significant impact on household income, which is contrary to Kung and Lee (2001), Knight and Yueh (2008), Cheng et al. (2016), and Li (2023). The reason is that, given the continuous improvement of the socialist market economy system with Chinese characteristics, the process of rural governance and decision-making in China is becoming more and more open and transparent, while the economic benefits of party membership are gradually disappearing. The “minimum living security” variable did not pass the significance test, indicating that the enjoyment of minimum living security did not significantly affect the household income of rural households. This is inconsistent with the views of Chen et al. (2020). The reasons are as follows: (1) The number of farmers in Y Town who enjoy the minimum living guarantee is very small, accounting for only 4.4% of the total sample, so it cannot significantly affect the total household income level of farmers; (2) The minimum living guarantee amount is relatively small, with an average of about 205 yuan per person per month (data obtained from field investigations), and this amount does not have a significant effect on increasing the total income of households. The above factors lead to the insight that enjoying the minimum living guarantee cannot have a significant impact on the total income of rural households.

The statistical regression results in Table 3 also show that in the agricultural production feature vector Y, which may affect the disposable income of farmers and households, the agricultural service outsourcing variable passes the significance test at the 1% level and the coefficient is negative. This indicates that in the process of agricultural production, agricultural service outsourcing reduces the household income level of farmers. This is contrary to the research conclusions of Machila (2015), Lyne et al. (2018), and Xiang and Xiaoqin (2023). The reason may be that it is difficult to establish trust between farmers and agricultural outsourcing service providers in the regions where the sample farmers are located. The distrust of such service providers by farmers leads to an increase in production costs and a waste of economic resources. For example, farmers may conduct real-time supervision when agricultural outsourcing service providers deliver services.

In the process of land circulation, land transfer (or land rental) has no significant impact on the income of rural households, which is inconsistent with the theoretical analysis and findings of Ying and Sihong (2022) and Congjia and Lingming (2021). Through in-depth investigation, it is found that the reasons why the conclusions drawn in this study are inconsistent with the theoretical analysis may mainly stem from the following three aspects:

Y Town, located in the Yunnan Guizhou Plateau with more mountains than flat dams, is a typical mountainous terrain. As a result, a large part of the cultivated land in the town is located in the mountains, with a large slope where production and operational costs are much higher than that of flat land. Thus, land demanders were more inclined to transfer land from the dam area with flat terrain, especially in the early stages of land transfer implementation. Indeed, by the end of 2021, the land transfer of Y Town was limited to the land in the dam area, and farmers whose land is not in the dam area could not participate in the transfer. The geographical conditions of Y town determined that the proportion of land in the dam area in the cultivated land of most farmers is relatively low, at an average of about 15%. This resulted in a relatively small scale of land transferred by most farmers even if they participated in land transfer. As shown in Table 4, of the 881 sample farmers, the number of farmers with land transfer area less than 1 mu is the highest, with a total of 704 households, accounting for about 80% of the sample farmers. There are 124 households with a land transfer area greater than 1 mu but less than 2 mu, accounting for approximately 14% of the total sample households. The number of farmers with land transfer areas between 3 and 5 mu is less than 2% of the total sample size. However, there is only one household with a land transfer area greater than 5 mu

The small scale of land transfer leads to the small amount of property income from land transfer behavior. As shown in Table 5, among the sample farmers, the maximum income from land transfer is 3,282 yuan a year while the minimum is 0 yuan. The average annual property income of each household from land transfer is about 299 yuan.

To sum up, the geographical conditions of Y Town restrict the scale of land transfer, leading to farmers in Y Town being unable transfer land or that the land area transferred is generally small at the present stage, so farmers derive less income from land transfer. As a result, the impact of land transfer on household income is not significant.

Due to geographical conditions and natural endowments, farmers in Y Town are currently unable to participate in land transfer or the scale of land transfer is generally small. As shown in Table 5, of the sample farmers, the smallest land area involved in land transfer is 0 mu, the largest is 5.47 mu, and the average land area of each household involved in land transfer is about 0.5 mu. By the end of 2021, the per capita cultivated land area of Y Town was about 1.27 mu, and the average total cultivated land area of each household was about 5 mu. As a result, even if they participated in land transfer, the proportion of the land area transferred by farmers is small, and the vast majority of farmers cannot transfer all the cultivated land owned by them. In fact, of the cultivated land transferred by the sample farmers, only the flat and high-quality land in the dam area was transferred by the land demand side, while the mountainous cultivated land was classified as “inferior goods” and still remained in the hands of farmers. This leads to the observation that even after participating in land transfer, sample farmers still needed to invest labor in the production and operation of mountainous farmland. As a result, this part of the labor force cannot be liberated from agricultural production, cannot be transferred to the non-agricultural sector for employment, and cannot obtain higher wage income compared to agricultural production (Fei and Weijuan, 2015; Zhonghao and Xingwen, 2016).

To sum up, the geographical conditions and natural endowments of Y Town limit the scale of land transfer, so that farmers are still tied to agricultural production after the transfer of some of the high-quality land, and the agricultural labor force cannot be fully released (Ruifen and Anlu, 2015; Zhang et al., 2018), resulting in an insignificant income increase effect of land transfer for farmers.

The unemployment of farmers caused by the transfer of land management rights is also one of the reasons why the impact of land transfer on the income growth of Y Town farmers is not significant. After in-depth investigation, it was found that about 41.57% of farmers whose main source of income is agricultural production and operations have lost their land management rights after transferring them, while their household labor force is basically in a state of “unemployment.” The reasons include: ① insufficient employment opportunities in surrounding towns. The transfer of land management rights has released some rural labor from agricultural production. However, due to the backward development of the local secondary and tertiary industries and the impact of the COVID-19 epidemic, the surrounding cities and towns have not been able to provide sufficient jobs for this surplus labor, resulting in “unemployment” and accompanying “land loss” for some rural surplus labor. ② Insufficient human capital accumulation. School education is the main way to achieve human capital accumulation. However, as can be seen from Table 2, the average education span of sample farmers is 6.35 years. This means that most of the peasants in Y Town do not receive school education after primary school. Most of the surplus rural labor force become low-skilled workers due to a lack of human capital accumulation and are at a disadvantage when they are transferred to non-agricultural sectors, especially when they are exported or transferred to such sectors in the developed eastern regions. The shortage of human capital accumulation leads to the lack of conditions and capital for rural surplus labor to transfer to non-agricultural sectors, which results in “unemployment” accompanying “land loss” for some rural surplus labor. ③ Local complex. Local complex is a unique cultural phenomenon of the Chinese nation. The influence of this culture on peasant household behavior is mainly reflected in the excessive dependence of rural surplus labor on the local geographical environment, living customs, etc. and an inadaptability to the natural and cultural environment of foreign villages. The results of field research show that most of the sample farmers have different degrees of local complex, and some of the rural surplus labor force cannot leave their hometown and follow to the non-agricultural sector as the result.

To sum up, the land transfer behavior in Y Town has no significant effect on increasing the income of farmers due to three reasons: the limitations of geographical conditions and natural endowments on the scale of land transfer, insufficient release of the agricultural labor force, and “unemployment” caused by land transfer.

Under the guidance of the “dual carbon” goals, the Chinese government has further increased its efforts to develop green and low-carbon agriculture, with the goal of continuously increasing production, reducing input, reducing pollution, and improving efficiency (Zhang, 2019), thereby effectively promoting the growth of farmers’ income, achieving the modernization of agriculture, while realizing the goal of common prosperity. This paper takes Y Town, Zhijin county as an example. Using the OLS regression method and based on field survey data of 881 farmers, the paper has empirically studied the impact of green and low-carbon agricultural production methods on the income of farmers in ethnic minority mountainous agricultural areas. The main contribution of this study is to expand the research scope of green and low-carbon agriculture to ethnic minorities and mountainous agricultural areas. The final results are as follows: (1) There is a positive correlation between green and low-carbon agricultural production methods and household income levels while adopting green and low-carbon agricultural production technologies can effectively promote the growth of household income for farmers; (2) Education level, health status, and new rural social pension insurance all have a significant promoting effect on the income of rural households; (3) Due to the difficulty in establishing trust relationships, agricultural service outsourcing has reduced the household income level of farmers; (4) The insignificant effect of land transfer behavior in Y Town on farmers’ income is due to three reasons: the limitations of geographical conditions and natural endowments on the scale of land transfer; insufficient release of agricultural labor; and “unemployment” caused by land transfer.

Based on the above research results, this study makes the following policy recommendations:

The limitations of our study are presented and also the directions for future research here. The present study is limited to ethnic minority areas and mountainous agricultural areas in China, therefore its research results and development suggestions may not be applicable to non-ethnic minority areas and non-mountainous agricultural areas. To that end, it is recommended to extend research frameworks to non-ethnic minority areas and non-mountainous agricultural areas.

The selected index for green and low-carbon agricultural production in this study is a single index, which does not provide a comprehensive measurement of the green and low-carbon agricultural production modes. Hence, it is suggested that future studies should adopt a more comprehensive index to measure various aspects of green and low-carbon agricultural production methods.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

YL: Conceptualization, Formal analysis, Funding acquisition, Methodology, Software, Writing – original draft. TP: Data curation, Investigation, Writing – review & editing. YC: Supervision, Writing – review & editing. JY: Supervision, Writing – review & editing. CL: Investigation, Writing – review & editing.