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Study on smart fertilizer recommendation methods based on yield response and agronomic efficiency for cotton

Halihashi Yibati1,Zhang Yan1,*,Li Qing-Jun1,Xu Xin-Peng2,He Ping2   

  1. 1 Institute of Agricultural Resources and Environment, Xinjiang Academy of Agricultural Sciences / Key Laboratory of Desert Oasis Crop Physiology, Ecology and Cultivation, Ministry of Agriculture and Rural Affairs, Urumqi 830091, Xinjiang, China; 2 Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
  • Received:2025-02-13 Revised:2025-08-13 Accepted:2025-08-13 Published:2025-08-25
  • Supported by:
    This study was supported by the National Agricultural Science and Technology Project “Smart Fertilization Project” (20221805), the National Key Research and Development Program (2016YFD0200101) and the Open Project of the Key Laboratory of Crop Physiology, Ecology, and Tillage in Desert Oasis, Ministry of Agriculture and Rural Affairs (25107020-202104).

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Abstract:

To address the low fertilizer use efficiency resulting from the lack of advanced fertilization recommendations and the widespread practice of improper fertilization in Xinjiang’s cotton production, this study established a large-scale nutrient management database based on 414 field fertilizer trials conducted from 1996 to 2019 across 21 major cotton-producing counties. The QUEFTS model was employed to simulate optimal nutrient requirements for cotton and to evaluate the relationships among indigenous soil nutrient supply, fertilizer agronomic efficiency, and crop yield response. Based on these analyses, a quantitative fertilization model was developed, and a field-specific Nutrient Expert (NE) decision support system was designed to suit the conditions of cotton production in Xinjiang. To validate the NE system, field experiments were conducted between 2017 and 2021 in major cotton-growing regions. Each experiment included six fertilization treatments: NE-recommended fertilization (NE); nitrogen (N), phosphorus (P), and potassium (K) omission treatments based on NE; farmer's practice (FP); and locally optimized soil test-based fertilization (ST). Data were collected on cotton yield, fertilizer use efficiency, and economic returns. Model simulations indicated that producing 1 ton of seed cotton requires 27.7 kg N, 6.2 kg P, and 29.3 kg K in above-ground biomass. The average yield responses to N, P2O5, and K2O applications were 1624, 1096, and 804 kg hm?2, respectively; corresponding relative yields were 0.7, 0.8, and 0.8; and agronomic efficiencies were 6.8, 8.5, and 16.7 kg kg?1, respectively. Field experiment results showed that the NE treatment applied 40.7%, 60.1%, and 10.7% less N, P, and K fertilizer, respectively, compared to FP, and 30.3% less N and 38.0% less P compared to ST. Compared to FP and ST, the NE treatment increased cotton yield by 365 and 92 kg ha?1, respectively, and improved economic returns by 4302 and 1094 yuan hm?2. The recovery efficiencies of N, P, and K fertilizers under NE also improved by 18.8 and 11.8, 14.2 and 11.5, and 13.4 and 6.0 percentage points, respectively. Furthermore, the agronomic efficiencies of N and P increased by 3.5 and 2.2 kg kg?1, and 7.2 and 4.4 kg kg?1, respectively. In contrast, the agronomic efficiency of K under NE decreased by 1.6 and 0.6 kg kg?1 compared to FP and ST, respectively. In conclusion, the intelligent, field-specific Nutrient Expert system developed based on yield response and agronomic efficiency offers a tailored fertilization strategy for individual plots. Multi-year, multi-location field experiments demonstrated that this approach optimizes nutrient input and balance, enhances cotton yield and fertilizer use efficiency, and improves economic returns. Therefore, the NE system represents an advanced and practical fertilization strategy for sustainable cotton production in Xinjiang.

Key words: cotton, QUEFTS model, Nutrient Expert system, yield, agronomic efficiency, fertilizer use efficiency

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