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Adopting low-carbon agricultural technologies (LCATs) is fundamental to reducing carbon emissions in agriculture. Our study explores the factors influencing the adoption of LCATs and the roles of production outsourcing and specialised farming within the framework of off-farm employment. In this regard, survey data were collected from 1 040 farmers in the Yellow River region of China in 2020 to examine the effect of production outsourcing on the farmers' adoption of LCATs. Potential mechanisms associated with specialised farming and off-farm employment are considered to comprehend this relationship. We also investigate the heterogeneous effects of production outsourcing on adopting LCATs, taking different education levels and arable land areas into account. The results show a positive association between production outsourcing and farmers' LCATs adoption behaviour, even after considering self-selection bias. Specifically, outsourcing production can significantly increase the likelihood of farmers adopting low-carbon tillage, low-carbon irrigation, and low-carbon fertilisation technologies by 7.2%, 8.1%, and 7.3%, respectively. This effect is more pronounced among farmers with higher levels of education and smaller areas of arable land. Furthermore, production outsourcing increases the LCATs adoption by promoting specialised farming. The findings suggest that outsourcing is vital to alleviating the lack of LCATs adoption resulting from off-farm employment. [ABSTRACT FROM AUTHOR]

Industrial organizations play a crucial role in transforming the production and management practices of smallholder farmers, encouraging the adoption of environmentally friendly production methods. However, limited studies have conducted comprehensive research examining how these industrial organizations effectively encourage farmers to adopt green production technologies. To address this research gap, this study examines the influence of organizational support on the adoption of agricultural green production technologies among 645 kiwifruit farmers in Shaanxi Province, northwestern China, using cross-sectional survey data from 2022. In addition, this research explores the mechanisms and heterogeneity in this impact. In our analysis, we estimated Probit models and mediation effect models, which show a positive influence of organizational support on farmers' adoption of these technologies. Notably, both institutional support and tool support have a more pronounced positive effect on this adoption. The mechanism analysis shows that organizational support facilitates farmers' adoption of these agricultural green production technologies by expanding their access to high-value markets. Furthermore, when considering heterogeneity among farmers, the study finds that organizational support has the most significant impact on the adoption of these technologies among farmers operating at a moderate scale. Moreover, our research highlights a technology linkage effect in the adoption process. Specifically, organizational support has a positive and significant effect on the adoption of technologies like bagging, physical control, and soil testing formulas, while also having a positive but statistically insignificant impact on technologies such as pollution-free pesticides and organic fertilizer substitution. In conclusion, the study proposes to increase assistance to industrial organizations, to play an influential role in guiding and driving farmers. [ABSTRACT FROM AUTHOR]

[Display omitted] • Variation in willingness to pay for ecosystem services throughout the basin. • Water quality most valuable attribute for ecosystem services. • Spatial heterogeneity among people with higher WTP for agricultural production quality and lowest for oasis. • Complex pattern of heterogeneity among various groups. • Group III shows higher willingness to pay for enhanced ecosystem services. The importance of understanding people's preferences and the well-being of river systems cannot be overstated when it comes to the effective restoration and long-term management of these systems. This study aimed to determine the preferences of people in the Hei River Basin of China regarding the conservation, restoration, and development of ecological systems and their associated services. The research utilized a combination of random parameter logit models for distance decay. The study collected data using a choice experiment method and separated the study area into three distance-based groups: group I (within 25 km), group II (25 to 50 km), and group III (beyond 50 km). The findings showed that there was spatial heterogeneity among the people, with a higher willingness to pay for high-quality agricultural production and the lowest willingness to pay for oasis. The results revealed a complex pattern of spatial heterogeneity and indicated the need for increased awareness programs, environmental education, and the promotion of social responsibility towards environmental protection. It is essential to implement environmental policies, restore properties, and preserve ecological systems to achieve sustainable development and a sustainable environment. The findings highlight the importance of considering spatial heterogeneity and the need for increased environmental awareness, education, and policy implementation. This research can contribute to developing effective strategies for the preservation of river systems and ensuring sustainable development and a sustainable environment. [ABSTRACT FROM AUTHOR]

China is a major livestock producer confronting the dual challenges of rising demand for animal-based food consumption and decreasing carbon emissions. To effectively address these issues, it is crucial to understand the trends of carbon emissions from animal husbandry and the competitive advantages of carbon emission reduction in different regions. This study uses panel data from 31 provinces from 2004 to 2020 to investigate the contributing factors to carbon emissions and explore ways to reduce carbon intensity in animal husbandry. The analysis employs spatial shift-share analysis and the spatial Durbin model. Our findings indicate that life-cycle carbon emissions associated with animal husbandry in China decreased from 572.411 Mt CO 2 eq to 520.413 Mt CO 2 eq over time, with an average annual decline of 0.568 %. The annual contribution of output value and internal industry-mix adjustment to carbon emission growth is 22.639 MT CO 2 eq and 6.226 MT CO 2 eq, respectively. On the other hand, the annual contribution of carbon efficiency improvement to carbon emission reduction is much higher, at 36.316 MT CO 2 eq. However, there is significant regional heterogeneity in the spatial decomposition of the carbon efficiency change component. The Northeastern region, Northwest and along the Great Wall demonstrate neighborhood advantages in enhancing carbon efficiency. In contrast, the South China and Southwest regions rely more on local carbon efficiency advantages to reduce the carbon intensity of animal husbandry. Furthermore, the carbon intensity in local and neighboring areas can be reduced through environmental regulations and industrial agglomeration. While technical progress significantly negatively impacts carbon intensity in neighboring regions, it does not contribute to reducing the carbon intensity of local animal husbandry. The findings provide valuable insights for local governments, aiding them in recognizing the pros and cons of carbon reduction in animal husbandry and strengthening regional cooperation in emission reduction management., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

China is the foremost global consumer, producer, and exporter of fresh apples. In 2021, China produced roughly 44 million tons of apples and exported just over 1 million tons, a nearly 2% increase over the previous year. However, the ongoing COVID-19 pandemic has had a detrimental impact on global trade and has led to a decrease in China's agricultural exports. The present study aims to contribute to the existing body of literature by analyzing plausible macroeconomic determinants that might impact China's apple exports. We used novel dynamic autoregressive distributed lag (DYARDL) simulations to model causal relationships among fundamental economic parameters. We made use of annual time series data from 1990 to 2020 from the World Bank and China's national statistical bureau. We found that increases in apple orchard area, apple production, and trade openness had a positive impact on apple exports over both the short and long term. Conversely, decreases in the prices of exported apples, agrochemicals, and carbon emissions in the agricultural sector had a positive impact on the long-term and short-term exportation of apples. Finally, we note that pictographic illustrations from the DYARDL simulations provide corroborative evidence for our findings. Based on the study results, this study proposes that the adoption of technological advancements in apple orchards could potentially enhance apple production while simultaneously upholding environmental sustainability., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)