Rice is the staple food for more than half of the global population and contributes 20% of the global dietary energy supply. Ensuring high rice yields while reducing environmental impacts has become a central challenge for Chinese agriculture. The Erhai Lake Basin is home to Erhai Lake—the seventh-largest freshwater lake in China and the second-largest plateau lake in Yunnan Province—which is known as the “Mother Lake”. However, rapid economic development and intensified agricultural activities have led to eutrophication and ecological degradation, and nitrogen and phosphorus losses from farmland have been confirmed as a major source of non-point source pollution in Erhai Lake. To address this, the local government has issued strict regulations prohibiting the application of mineral nitrogen and phosphorus fertilizers and mandating organic fertilizer use. However, rice production in the Erhai Lake Basin is still dominated by smallholders with plots of only 0.1–0.3 ha. These farmers often rely heavily on local environmental resources, resulting in excessive nutrient inputs, low fertilizer use efficiency, and impaired environmental benefits. Improving energy use efficiency while minimizing resource and energy inputs is crucial for ensuring the sustainability of rice production. However, under the unique ecological and policy constraints of the Erhai Lake Basin—especially the prohibition of mineral nitrogen and phosphorus fertilizers—the specific pathways for reducing energy inputs without compromising yield remain unclear.
Recently, the research team led by Jiuliang Xu and Shuntao Zhang at the College of Resources and Environmental Sciences, China Agricultural University, published a research paper titled “Evaluation of the impact of the Science and Technology Backyard initiative on the rice production system in the Erhai Lake Basin based on emergy analysis” in ENGINEERING Agriculture, an ENGINEERING cluster journal of the Chinese Academy of Engineering (DOI: 10.15302/J-FASE-2026689). Based on survey data from 171 farming households, the study used emergy analysis to assess the current sustainability of rice cultivation in the Erhai Lake Basin and, through a two-year comparative experiment between the current system (CS) and a green system (GS), tested the practical effects of a complete green technology package under the Science and Technology Backyard (STB) initiative.
The study used a stratified sampling method to conduct household surveys in 16 townships in the Erhai Lake Basin in July 2022. A total of 180 questionnaires were collected, of which 171 were valid, with an effective rate of 95%. Follow-up comparative experiments were conducted in Yousuo and Shangguan towns, surveying 80 CS farmers and 80 GS farmers in 2023 and 2024, respectively. CS represents the traditional rice cultivation method in the Erhai Lake Basin, while GS is a comprehensive green ecological rice planting model developed by STB through long-term positioning experiments. Its core technology is green intelligent fertilizer (N:P:K:Ca:Mg:Si = 15:4.8:11.62:4:1:2), combined with reduced mineral fertilizer and pesticide inputs, improved nutrient and water management, and the selection of better-performing rice cultivars. As a platform connecting government agencies, scientists, smallholders, and fertilizer companies, STB has researchers stationed in villages to conduct field trials, provide technical training, and offer regular technical guidance services.
The results showed that in 2022, the average emergy input for rice production in the Erhai Lake Basin was approximately 7.24 × 10¹⁵ sej·ha⁻¹, and the emergy output was 1.08 × 10¹⁶ sej·ha⁻¹. The emergy exchange ratio (EER) exceeded 1, achieving a net emergy gain. Of the emergy input, renewable environmental inputs accounted for 5.1%, non-renewable environmental inputs for 3.4%, purchased renewable inputs for 53.4%, and purchased non-renewable inputs for 38.1%. The average emergy yield ratio (EYR) for rice production in the Erhai Lake Basin was 1.71, and the average environmental loading ratio (ELR) was 0.81. The average emergy sustainability index (ESI) values for the top 25% and bottom 25% of townships were 2.59 and 2.13, respectively, indicating significant spatial heterogeneity. Based on random forest model analysis of the relative contribution of each input to ESI, the results showed that rice yield, nitrogen fertilizer, phosphorus fertilizer, and manure input were the main influencing factors of ESI, with contribution rates of 27.5%, 23.3%, 23.2%, and 16.8%, respectively.
Compared with CS, GS reduced the emergy inputs of nitrogen, phosphorus, and potassium fertilizers by 29%, 32%, and 20%, respectively, and required no additional manure input. The emergy outputs of rice grains and straw under GS increased by 11% and 10%, respectively. In 2023 and 2024, the total emergy input of GS was significantly lower than that of CS, decreasing by 34.9% and 24.7%, respectively; the total emergy output of GS was better than that of CS, being 10.2% and 14.7% higher, respectively; the EER of GS was significantly higher than that of CS, increasing by 34.9% and 50.5%, respectively; and the ESI of GS was 33.3% and 37.2% higher than that of CS, respectively. These results indicate that GS significantly enhances the sustainability of rice production by increasing emergy output and reducing environmental loading. This highlights the potential of GS to balance productivity and ecological protection, making it a more sustainable alternative to CS.
This study applied emergy analysis to the sustainability assessment of rice production in the Erhai Lake Basin, addressing the deficiencies in the application of emergy analysis in this region and the lack of comparative analyses of different production models. The study revealed that yield, nitrogen and phosphorus fertilizer inputs, and manure input are core drivers of sustainability, and demonstrated that the GS technology package, supported by STB-mediated social and technical services, can significantly improve the emergy sustainability of rice production in the Erhai Lake Basin and provide a replicable practical model for the green development of other plateau lake regions.