Skip to main content
Evidence-Based Supplement Research
Evidence-Based Supplement Research

Study Design

Type
Meta-Analysis
Population
235 studies on maize production in China
Methods
Meta-analysis of 235 studies following PRISMA guidelines
Organic substitution technology is regarded as a key pathway for achieving sustainable agricultural development. However, systematic quantitative analyses examining the effects of different organic substitution ratios on maize productivity in China remain scarce. Therefore, following the PRISMA guidelines, we screened 235 studies for a meta-analysis to systematically assess the effects of different organic substitution ratios on grain yield (GY), water productivity (WP), nitrogen uptake (NU), and N losses, while exploring key associated factors. Organic substitution significantly increased GY (1.6%, 95% confidence interval (CI): 0.7-2.4%), WP (2.2%, 95%CI: 0.2-4.4%), and NU (2.7%, 95%CI: 1.3-4.3%), with the effects were most pronounced when the substitution ratio was 20-40%. Climatic conditions with mean annual temperature of 7-12 °C and mean annual precipitation >550 mm were more favorable for increasing production and efficiency. The greatest increases in GY, WP, and NU were observed in slightly acidic and nutrient-sufficient medium soils. The most significant increase in maize productivity was observed with nitrogen application rate of 180-240 kg ha-1 and irrigation, and was further amplified in spring maize cropping system with planting density >7 × 104 plants ha-1. The increments of GY, WP, and NU were amplified when organic fertilizer N > 2.5%, organic fertilizer C > 50%, and organic fertilizer C:N > 30. Furthermore, a substitution ratio of 20-40% clearly reduced N losses. The optimal substitution intervals for the Northeast, Northwest, Southwest, North, and Southeast regions were 25.6-39.8%, 27.9-42.8%, 22.8-39.5%, 19.9-41.5%, and 37.5-58.1%, respectively. Organic substitution technology effectively enhances crop productivity and reduces N losses in China's maize production, providing valuable insights for sustainable production. The most notable issue is that the robustness of this study's conclusions may be limited due to the high heterogeneity of the sample and the reliance on variance estimation. Future research requires methodological breakthroughs to improve its extrapolation value.

Research Insights

    Back to top