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作物学报 ›› 2025, Vol. 51 ›› Issue (11): 3052-3064.doi: 10.3724/SP.J.1006.2025.54022

• 耕作栽培·生理生化 • 上一篇    下一篇

基于产量反应和农学效率的棉花智能化推荐施肥方法研究

哈丽哈什·依巴提1(), 张炎1,*(), 李青军1, 徐新朋2, 何萍2   

  1. 1 新疆维吾尔自治区农业科学院农业资源与环境研究所 / 农业农村部荒漠绿洲作物生理生态与耕作重点实验室, 新疆乌鲁木齐 830091
    2 中国农业科学院农业资源与农业区划研究所, 北京 100081
  • 收稿日期:2025-02-13 接受日期:2025-08-13 出版日期:2025-11-12 网络出版日期:2025-08-25
  • 通讯作者: *张炎, E-mail: yanzhangxj@163.com
  • 作者简介:E-mail: harlhax10@163.com
  • 基金资助:
    国家农业科技项目“农田智慧施肥项目”(20221805);国家重点研发计划项目(2016YFD0200101);农业农村部荒漠绿洲作物生理生态与耕作重点实验室开放课题项目(25107020-202104)

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 Accepted:2025-08-13 Published:2025-11-12 Published online:2025-08-25
  • Contact: *E-mail: yanzhangxj@163.com
  • Supported by:
    National Agricultural Science and Technology Project “Smart Fertilization Project”(20221805);National Key Research and Development Program(2016YFD0200101);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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摘要：

针对新疆棉花生产中缺乏先进高效的推荐施肥方法和不合理施肥带来的肥料利用率低的现状, 本研究以1996—2019年新疆主要植棉区21个植棉县的414个棉花田间肥料试验为基础, 建立养分管理大数据库。采用QUEFTS模型模拟棉花最佳养分需求量, 并分析土壤基础养分供应、肥料的农学效率与产量反应之间的相关关系, 在此基础上构建施肥模型, 并开发了适用于新疆棉花生产的养分专家系统。为验证该系统的应用效果, 于2017—2021年在新疆主要棉花种植区开展田间验证试验。试验共设6个施肥处理, 分别为棉花养分专家系统推荐施肥(NE), 基于NE推荐施肥基础上的不施氮肥、不施磷肥和不施钾肥, 农民习惯施肥(FP)和当地的优化推荐施肥(ST), 调查了棉花产量、肥料利用效率和经济效益。QUEFTS模型模拟棉花养分吸收结果表明, 每生产1 t籽棉地上部所需氮、磷和钾养分分别为27.7、6.2和29.3 kg。施用氮、磷和钾肥的平均产量反应分别为1624、1096和804 kg hm-2, 平均相对产量分别为0.7、0.8和0.8, 平均农学效率分别为6.8、8.5和16.7 kg kg-1。田间验证结果显示, 与FP处理相比, NE处理分别减施氮、磷、钾肥40.7%、60.1%和10.7%; 与ST处理相比, NE处理分别减施氮、磷肥30.3%和38.0%, 增施钾肥10.8%。与FP和ST相比, NE处理的棉花产量分别增加了365 kg hm-2和92 kg hm-2, 经济效益分别增加了4302元 hm-2和1094元 hm-2, 氮、磷和钾肥回收率分别提高了18.8和11.8、14.2和11.5、13.4和6.0个百分点, 氮和磷肥农学效率分别增加了3.5 kg kg-1和2.2 kg kg-1、7.2 kg kg-1和4.4 kg kg-1, 钾肥农学效率分别减少了1.6 kg kg-1和0.6 kg kg-1。综上所述, 基于产量反应和农学效率构建的智能化新疆棉花养分专家系统, 能够为每块地提供个性化的施肥方案。连续多点的田间试验结果充分证明, 该方法优化了肥料用量与养分配比, 提高了棉花产量和肥料利用率, 增加了经济效益, 是适用于新疆棉花生产的推荐施肥新方法。

关键词: 棉花, QUEFTS模型, 养分专家系统, 产量, 农学效率, 肥料利用率

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 kg hm-2 and 92 kg hm-2, respectively, and improved economic returns by 4302 yuan hm-2 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 kg kg-1 and 2.2 kg kg-1, and 7.2 kg kg-1 and 4.4 kg kg-1, respectively. In contrast, the agronomic efficiency of K under NE decreased by 1.6 kg kg-1 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

表1

养分专家系统推荐施肥、农民习惯施肥及当地的优化推荐施肥下棉花化肥氮、磷和钾施肥量"

年份
Year		 地点
Site		 施氮量
N application rate (kg hm-2)		 施磷量
P2O5 application rate (kg hm-2)		 施钾量
K2O application rate (kg hm-2)
NE FP ST NE FP ST NE FP ST
2017 昌吉CJ1 200 345 300 150 173 173 60 75 60
昌吉CJ2 200 345 300 150 173 173 60 75 60
阿瓦提AWT1 270 510 300 150 240 180 120 30 90
2018
 昌吉CJ3 210 260 300 100 201 173 90 75 60
阿瓦提AWT1 161 357 210 115 240 180 110 30 90
2019
 昌吉CJ3 225 345 300 81 173 173 86 75 60
阿瓦提AWT1 240 510 300 88 240 180 98 30 90
2020
 昌吉CJ4 219 328 150 90 310 275 115 112 142
昌吉CJ5 222 328 150 90 310 275 86 112 142
阿瓦提AWT2 230 440 345 95 240 173 75 38 65
库尔勒KEL 260 592 453 164 458 230 120 188 33
尉犁YL 245 434 442 113 371 159 110 113 75
巴楚BC 239 342 392 109 345 173 80 0 42
沙湾SW 251 268 340 159 290 225 134 146 112
2021
 沙雅SY1 253 305 495 95 335 100 60 160 105
沙雅SY2 247 503 495 70 474 100 60 393 105

图1

QUEFTS模型模拟不同潜在产量下新疆棉花最佳养分吸收量 上下黑色直线分别表示最大累积边界线和最大稀释边界线。红色、绿色和紫色曲线潜在产量分别为4000、6000和8000 kg hm-2。黄色圆圈表示数据库中与产量对应的养分吸收量。"

图2

棉花产量反应分布"

图3

棉花相对产量分布"

图4

棉花农学效率分布"

图5

棉花产量反应和农学效率关系"

表2

不同施肥方法下棉花的施肥量"

处理
Treatment		 施氮量 N rate (kg hm-2) 施磷量 P2O5 rate (kg hm-2) 施钾量 K2O rate (kg hm-2)
平均值 Mean 范围 Range 平均值 Mean 范围 Range 平均值 Mean 范围 Range
NE 230 b 161-270 114 c 70-164 92 a 60-134
FP 388 a 260-592 286 a 173-474 103 a 0-393
ST 330 a 150-495 184 b 100-275 83 a 33-142

图6

不同施肥方法下棉花籽棉产量和经济效益 处理同表1。不同小写字母表示处理间的差异达到显著水平(P < 0.05); 箱型图中的中间实线是中位数, 虚线是均值。箱型上下代表上下25%的数据, 箱型上下的“帽子”则分别代表90%和10%的数值。"

图7

不同施肥方法下棉花肥料利用率 处理同表1。不同小写字母表示处理间的差异达到显著水平(P < 0.05); 箱型图中的中间实线是中位数, 虚线是均值。箱型上下代表上下25%的数据, 箱型上下的“帽子”则分别代表90%和10%的数值。"

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