Organic fertilizer substitution for chemical fertilizers is an important strategy for sustainable agriculture. This study aimed to investigate the effects of different organic nitrogen substitution ratios for a chemical nitrogen fertilizer on the soil microbial community structure in cotton fields. A three-year field experiment was conducted in Changji, Xinjiang, China, with six treatments: no fertilization (CK), a single application of chemical fertilizer (CF), and organic nitrogen substituting for 25% (T1), 50% (T2), 75% (T3), and 100% (T4) of a chemical nitrogen fertilizer. High-throughput sequencing was used to analyze the bacterial and fungal community structures. Results showed that organic substitution treatments significantly increased the bacterial Simpson and Shannon diversity indices compared to CK. At the phylum level, organic substitution treatments increased the relative abundance of Proteobacteria (1.27–22.44%), Gemmatimonadota (3.50–9.33%), and Actinobacteriota (17.25–38.57%) compared to CK. For fungi, organic substitution treatments improved the Simpson and Shannon indices, with the T2, T3, and T4 treatments showing significant increases. Organic substitution treatments increased the relative abundance of Ascomycota (2.05–14.75%), Basidiomycota (0.41–178.44%), and Glomeromycota (6.15–502.88%) compared to CK, while Rozellomycota was exclusively present in organic substitution treatments. Cotton yield data showed that the T1 treatment produced the highest seed cotton yield over the three-year study period, with significant increases of 6.19% compared to the CF treatment in the third year. These findings suggest that organic fertilizer substitution can effectively improve the soil microbial community structure and diversity, with moderate to high substitution ratios showing the most beneficial effects for maintaining soil health in cotton fields.

The Xinjiang cotton-producing region is the main cotton-growing region in China; however, the combination of excessive application but low utilization of fertilizers has restricted its agricultural development. Estimating the balanced nutrient requirements for cotton is essential to increase its yield and nutrient use efficiency. The results from 372 field experiments performed between 1996 and 2019 were used to build a QUEFTS (quantitative evaluation of the fertility of tropical soils) model to investigate relationships between cotton seed yield and nutrient accumulation, with the data from 2017 to 2020 used to validate the model. The results demonstrated that the QUEFTS model predicted a linear relationship between target yield and nutrient uptake until the target yield reached about 60–70% of the potential yield. To produce 1000 kg of seed cotton, 28.3 kg N, 6.1 kg P, and 29.6 kg K were required for cotton, and the corresponding ratio of N, P, and K was 4.64:1:4.85. The corresponding internal efficiencies (IEs) for N, P, and K were 35.4, 163.2, and 33.7 kg/kg, respectively. Field validation indicated that the QUEFTS model could be used to estimate nutrient uptake at a targeted yield and contribute to developing a fertilizer recommendation strategy for Xinjiang cotton production.

Imbalanced and excessive fertilization leads to low nutrient utilization efficiency and wastage of fertilizer resources in processing tomatoes in Xinjiang. Determining nutrient requirements is vital for devising fertilization strategies that enhance yield, profitability, and environmental sustainability. This study utilized observational data from 181 farms across Xinjiang’s major processing tomato production areas from 2003 to 2023 to explore the relationship between fruit yield and nutrient uptake in aboveground dry matter. The Quantitative Evaluation of the Fertility of Tropical Soils (QUEFTS) model was employed to estimate nutrient requirements. The results indicated that when the target yield reached 60–70% of its potential, nutrient uptake by processing tomatoes increased linearly with fruit yield. To produce 1000 kg of fruit, the aboveground parts required 1.95 kg of nitrogen, 0.33 kg of phosphorus, and 2.28 kg of potassium, reflecting a N:P:K ratio of 1:0.17:1.17. In contrast, during harvesting, alternative plant parts required 1.31 kg of nitrogen, 0.21 kg of phosphorus, and 0.71 kg of potassium, with fruit nutrient uptake rates of 67.3%, 65.6%, and 74.9%, respectively. Field validation showed a strong correlation between the observed and simulated nutrient uptake rates, demonstrating the model’s accuracy in predicting nutrient demands. These findings provide critical insights for developing optimized fertilization strategies to enhance yield and nutrient use efficiency in Xinjiang’s processing tomato production.