Digital Agriculture Drives Agricultural Low-Carbon Transformation: A Discussion Based on Chinese Cases

Digital Agriculture Drives Agricultural Low-Carbon Transformation: A Discussion Based on Chinese Cases

Introduction

Climate change poses a dual challenge to agricultural production: climate risks exacerbate production uncertainty, while simultaneously raising the urgency for emission reduction in agriculture. In the fields of agricultural economics and environment, ensuring the alignment between food security and the transition to low-carbon agriculture has become a core issue. China is committed to coordinating the "dual carbon" goals with the process of agricultural modernization. Agricultural carbon emissions primarily originate from the use of fertilizers and pesticides, agricultural machinery operation, and irrigation, as well as the processes of major inputs and operations.

Theoretical Framework of Agricultural Digitalization and Low-Carbon Transition

In the agricultural sector, the focus of research has shifted from simple carbon emission accounting to exploring the underlying mechanisms driving the transition to low-carbon agriculture. The development of digital agriculture encompasses three dimensions: digital human capital and application capabilities, digital infrastructure and production conditions, and the digital industry and service environment. This transformation is not merely the adoption of technology but a reshaping of the efficiency of production factors (capital, labor, land).

Existing research indicates that the promotion of digital agriculture can enhance the utilization efficiency of input factors to some extent by improving information transparency and optimizing production decisions, thereby promoting the greening of agricultural production.

Analysis of the Impact of Digital Agriculture on Carbon Emission Intensity

Panel data analysis of 30 provincial areas in China from 2012 to 2023 shows a significant negative correlation between the digital agriculture development index and agricultural carbon emission intensity. This finding suggests that the digitalization process in agriculture plays a positive role in reducing agricultural carbon emissions.

Mechanism analysis further reveals this process: digital agriculture development is significantly negatively correlated with capital mismatch, and capital mismatch is positively correlated with agricultural carbon emission intensity. This implies that digital agriculture effectively reduces resource waste and inefficient inputs by optimizing capital allocation, thereby lowering agricultural carbon emission intensity.

Regional Heterogeneity and Policy Implications

In heterogeneity analysis, the coefficient for digital agriculture showed a significant negative impact in major grain-producing areas and eastern regions, but no significant effect in non-major grain-producing areas and western regions. This suggests that policymakers, when promoting digital agriculture, should formulate targeted support strategies based on the resource endowments and agricultural structural differences of the respective regions.

Industry Impact

Agricultural Production Efficiency and Operating Models: The application of digital agriculture, such as precision fertilization, smart irrigation, and drone operations, directly improves the real-time decision-making and accuracy of production, enhancing resource utilization efficiency. This drives a shift from experience-based agriculture to data-driven intelligent operation models.

Agricultural Labor Structure: Although research results indicate that labor mismatch is not significant, the digital transformation places new demands on skill structures, accelerating the demand for agricultural technology talent.

Food Supply Chain and Trade: Improving production efficiency and lowering the carbon intensity per unit of output will help enhance the international competitiveness of agricultural products and promote more sustainable agricultural product production standards in the global food supply chain.Agricultural Labor Structure: Although research results show no significant labor mismatch, digital transformation places new demands on skill structures, accelerating the demand for agricultural technology talent.

Food Supply Chain and Trade: Improving production efficiency and reducing the carbon emission intensity per unit of output will help enhance the international competitiveness of agricultural products and promote more sustainable agricultural production standards in the global food supply chain.

Agricultural Investment Directions: The investment focus should shift from purely hardware investment to building data platforms, agricultural SaaS services, and comprehensive digital infrastructure capable of efficient allocation of factors.

Future Outlook

Trends for the Next 3-5 Years: Digital agriculture will transition from the technology application stage to the system integration stage, focusing on how to deeply integrate the Internet of Things (IoT), Artificial Intelligence (AI), and big data platforms to shift from "precision input" to "closed-loop management." Agricultural automation will further permeate planting, harvesting, and even downstream processing stages.

Prospects for Agricultural AI Applications: Agricultural AI will play a core role in crop health monitoring, early pest and disease warnings, and climate adaptation decision support, providing crucial intelligent support for climate-resilient agriculture.

Changes in Global Food Demand: With global population growth and increased production uncertainty due to climate fluctuations, the demand for climate-resilient agriculture will continue to rise, and digital technology is an important means of addressing climate risks and ensuring the resilience of the food supply system.

Hotspots for Agricultural Capital Investment: Green agriculture projects, carbon agriculture technologies, and agricultural ESG indicators that can directly quantify environmental benefits will become focal points for capital, driving the green development of agricultural technology.

Food Technology Innovation Trends: In the field of food technology, technologies such as alternative proteins and cultivated meat will combine with agricultural digitalization to build more sustainable protein sources, influencing the structural upgrade of the global food system.

Conclusion

The development of digital agriculture is not a simple stacking of technologies but a systematic optimization of the efficiency of agricultural production factor allocation and environmental performance. By deeply embedding digital technology into agricultural operations and policy-making, Chinese agriculture is evolving towards a lower-carbon and more resilient direction. Continuously paying attention to the construction of data platforms and the optimization of capital allocation is the key path to supporting the long-term sustainable development of agriculture.