A Meta-Analysis of 30 Years in China and Micro-District Experiments Shows Organic Fertilizer Quantification Combined with Chemical Fertilizer Reduction Enhances Rice Yield on Saline-Alkali Land

doi:10.1016/j.rsci.2025.01.004

Abstract

Abstract:

To improve the yield and quality of rice grown on saline-alkali soil, a meta-analysis combined with micro-district experimental studies was conducted in China to examine the impact of humic acid- based organic fertilizer and chemical fertilizer on rice yield and quality. This study employed a two-factor fully randomized experimental design, incorporating four levels of humic acid (F0, 0.0 g/pot; F1, 4.8 g/pot; F2, 12.0 g/pot; and F3, 19.2 g/pot) and three levels of chemical fertilizer (A1, full conventional dosage; A2, 85% of conventional dosage; and A3, 70% of conventional dosage). The meta-analysis revealed that the application of organic fertilizer (at a rate of 1500‒3000 kg/hm²) combined with chemical fertilizer had a significantly positive effect on the theoretical yield, tiller number, partial factor productivity, and SPAD value of rice. Temperature, organic fertilizer application, and chemical fertilizer levels were identified as critical factors affecting rice yield. The micro-experiments demonstrated that the application of humic acid organic fertilizer with treatment F3 significantly elevated the SPAD value at the full heading and grain filling stages. Increased panicle number and seed-setting rate were the main contributors to the rise in yield, with the F3 treatment yielding the highest overall. The effective leaf area, high-efficiency leaf area, and dry matter accumulation in rice treated with F3 were all higher compared with the F0 treatment. Our findings indicated that the addition of humic acid organic fertilizer can markedly improve the partial factor productivity and agronomic efficiency of rice. In conclusion, the application of F3 organic fertilizer combined with A3 chemical fertilizer (F3A3) significantly increased the yield of saline-alkali rice, which was 6.62% higher than that of the F0A1 treatment, thereby validating the meta-analysis outcomes. We propose that the combined use of humic acid organic fertilizer and chemical fertilizer can promote the growth of rice in saline-alkali soils. Consequently, these management practices provide a means to foster the green and healthy development of rice in saline-alkali regions across China.

Key words: humic acid, chemical fertilizer, rice, yield, saline-alkali land

He Chen, Ruan Yunze, Jia Zhongjun. A Meta-Analysis of 30 Years in China and Micro-District Experiments Shows Organic Fertilizer Quantification Combined with Chemical Fertilizer Reduction Enhances Rice Yield on Saline-Alkali Land[J]. Rice Science, 2025, 32(2): 259-272.

Figures/Tables 9

Fig. 1. Meta-analysis of theoretical yield (A) and yield (B) in rice. The number on the right represents the sample size. MAP, Mean annual precipitation; MAT, Mean annual temperature; CF, Chemical fertilizer; OF, Organic fertilizer.

Fig. 2. Meta-analysis of tiller number (A), SPAD value (B), plant height (C), and biomass (D) in rice. The number on the right represents the sample size. MAP, Mean annual precipitation; MAT, Mean annual temperature; CF, Chemical fertilizer; OF, Organic fertilizer.

Fig. 3. Meta-analysis of partial factor productivity (A) and agronomic efficiency (B). The number on the right represents the sample size. MAP, Mean annual precipitation; MAT, Mean annual temperature; CF, Chemical fertilizer; OF, Organic fertilizer.

Fig. 4. Meta-analysis of random forest on yield (A), theoretical yield (B), linear regression between organic fertilizer and theoretical yield (C), linear regression between organic fertilizer and yield (D), linear regression between chemical fertilizer and theoretical yield (E), and linear regression between chemical fertilizer and yield (F). MAT, Mean annual temperature; CF, Chemical fertilizer; OF, Organic fertilizer; TY, Theoretical yield; PP, Partial factor productivity; MAP, Mean annual precipitation; Bi, Biomass; TN, Tiller number; PH, Plant height; SPAD, Soil Plant Analysis Development value; AE, Agronomic efficiency; Y, Yield; lnRR, Effect size; MSE, Mean square error. *, P < 0.05; **, P < 0.01 by least significant difference test.

Fig. 5. Effects of humic acid and chemical fertilizer reduction on the number of panicles per plant (A), number of grains per panicle (B), seed-seeding rate (C), 1000-grain weight (D), and theoretical yield (E). F0, 0.0 g/pot humic acid; F1, 4.8 g/pot humic acid; F2, 12.0 g/pot humic acid; F3, 19.2 g/pot humic acid; A1, Full conventional application; A2, 85% of conventional application; A3, 70% of conventional application. Different lowercase letters above the bars indicate significant differences (Least significant difference test, P < 0.05).

Fig. 6. Effects of humic acid and chemical fertilizer reduction on effective leaf area at tillering stage (A), effective leaf area at heading stage (B), high effective leaf area (C), biomass at tillering stage (D), biomass at heading stage (E), and biomass at maturity stage (F). F0, 0.0 g/pot humic acid; F1, 4.8 g/pot humic acid; F2, 12.0 g/pot humic acid; F3, 19.2 g/pot humic acid; A1, Full conventional application; A2, 85% of conventional application; A3, 70% of conventional application. Different lowercase letters above the bars indicate significant differences (Least significant difference test, P < 0.05).

Fig. 7. Correlation between rice yield, yield compositions, and biomass.

Fig. 8. Importance of variables on theoretical yield (A) and structural equation model (B). MSE, Mean square error; df, Degree of freedom; Chisq, Chi-square; GFI, Goodness of fit index; CFI, Comparative fit index; RMR, Root mean square residual; SRMR, Standardized root mean square residual; RMSEA, Root mean square error of approximation; AIC, Akaike information criterion; NFI, Non-normed fit index; TLI, Tucker-Lewis index; AGFI, Adjusted goodness of fit index. Blue lines represent significant positive correlation. Dotted lines represent no significant correlation. *, P < 0.05; **, P < 0.01; ***, P < 0.001 by least significant difference test.

Fig. 9. Linear relationship between rice theoretical yield and panicle number (A), grain number (B), high effective leaf area (C), leaf area at the full heading stage (D), biomass at the full heading stage (E), biomass at the maturity stage (F), agronomic efficiency (G), SPAD value at the heading stage (H), and SPAD value at the filling stage (I).

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