• ISSN 1008-505X
  • CN 11-3996/S
徐新朋, 丁文成, 何萍, 周卫. 基于产量反应和农学效率的水稻智能化推荐施肥方法研究[J]. 植物营养与肥料学报, 2023, 29(5): 802-812. DOI: 10.11674/zwyf.2023116
引用本文: 徐新朋, 丁文成, 何萍, 周卫. 基于产量反应和农学效率的水稻智能化推荐施肥方法研究[J]. 植物营养与肥料学报, 2023, 29(5): 802-812. DOI: 10.11674/zwyf.2023116
XU Xin-peng, DING Wen-cheng, HE Ping, ZHOU Wei. The study of intelligent fertilizer recommendation method for rice based on yield response and agronomic efficiency[J]. Journal of Plant Nutrition and Fertilizers, 2023, 29(5): 802-812. DOI: 10.11674/zwyf.2023116
Citation: XU Xin-peng, DING Wen-cheng, HE Ping, ZHOU Wei. The study of intelligent fertilizer recommendation method for rice based on yield response and agronomic efficiency[J]. Journal of Plant Nutrition and Fertilizers, 2023, 29(5): 802-812. DOI: 10.11674/zwyf.2023116

基于产量反应和农学效率的水稻智能化推荐施肥方法研究

The study of intelligent fertilizer recommendation method for rice based on yield response and agronomic efficiency

  • 摘要:
    目的 水稻专家推荐系统早期版本没有区分水稻种植类型,有时会降低推荐的精准性。我们优化并建立了基于不同种植类型水稻的产量反应和农学效率的水稻推荐施肥方法,并采用大量田间试验验证了其普遍性和可行性。
    方法 收集汇总来自于国际植物营养研究所中国项目部、团队研究以及公开发表的多年多点水稻田间试验,建立产量和养分吸收数据库。采用QUEFTS模型分析不同种植类型水稻养分吸收特征,建立水稻产量反应和农学效率的内在联系,构建施肥模型,开发水稻养分专家系统。于2013—2020年在水稻主产区8个省份开展了452个田间试验对系统进行校正和改进。每个试验包括6个处理:水稻养分专家系统推荐施肥(NE)、农民习惯施肥(FP)、土壤测试施肥(ST)以及基于NE的不施氮、不施磷和不施钾处理。调查了水稻产量、经济效益、养分回收率和肥料农学效率。
    结果 QUEFTS模型分析的水稻产量与养分吸收关系结果显示,生产1 t籽粒产量地上部所需氮、磷和钾养分一季稻分别为14.2、3.9和14.3 kg,早、中、晚稻分别为16.9、3.3、20.9 kg。我国水稻主产区施用氮、磷和钾肥的平均产量反应一季稻分别为3.1、1.1和1.0 t/hm2,早稻分别为2.3、1.0和1.0 t/hm2,中稻分别为2.3、0.9和1.0 t/hm2,晚稻分别为1.9、0.8和0.8 t/hm2。氮、磷和钾化肥的平均农学效率一季稻分别为17.6、15.3和9.8 kg/kg,早稻分别为14.6、15.3和10.1 kg/kg,中稻分别为11.4、12.4和9.1 kg/kg,晚稻分别为11.5、14.8和9.2 kg/kg。与FP处理相比,NE处理氮、磷和钾肥施用量分别减少了12.6%、9.6%和21.4%;与ST处理相比,NE处理氮肥用量减少了7.6%,钾肥用量减少了15.6%。与FP和ST处理相比,NE处理产量分别增加了0.5和0.3 t/hm2;经济效益分别增加了1627和893元/hm2;氮肥回收率分别增加了13.1和9.3个百分点,农学效率分别增加了4.1和2.7 kg/kg;磷肥回收率分别增加了7.8和5.0个百分点,农学效率分别增加了6.6和3.3 kg/kg;钾肥回收率分别增加了14.6和9.5个百分点,农学效率分别增加了5.6和4.9 kg/kg。
    结论 以田间试验大数据为支撑,优化并建立的不同种植类型水稻的养分专家推荐施肥系统,提高了系统的可操作性和针对性。连续多年不同种植类型水稻的田间试验结果充分证明,优化后的水稻养分专家系统具有优化肥料种类和用量、提高水稻产量和肥料利用率和增加农民收入的功能,是实现我国小农户推荐施肥行之有效的智能技术系统。

     

    Abstract:
    Objectives The early version of Nutrient Expert for Rice did not differentiate rice types, reducing the precision of fertilizer recommendation at times. We optimized the version by establishing Nutrient Expert for Rice targeted to specific rice type.
    Methods The yield and nutrient uptake data were collected and summarized from multi-year and -site rice field experiments from International Plant Nutrient Institute (IPNI) China Program, our research group and relevant published articles. QUEFTS model was used to analyze the nutrient uptake of different rice types, to establish the intrinsic relationship between rice yield response and agronomic efficiency, construct a fertilizer application model and develop Nutrient Expert system for rice. A total of 452 field experiments were conducted in eight provinces in the main rice producing areas from 2013 to 2020 to calibrate and improve the system. Each experiment included six treatments: fertilizer recommendation based on Nutrient Expert (NE), farmers’ practices (FP), conventional recommendation based on soil testing (ST), and N omission, P omission and K omission based on the NE treatment. Rice yield, economic benefit, nutrient use efficiency and fertilizer agronomic efficiency were investigated.
    Results The result of the relationship between rice yield and nutrient uptake based on QUEFTS model showed that the N, P and K requirements at above-ground dry matter to produce 1 ton of grain yield were 14.2, 3.9 and 14.3 kg for single-season rice, respectively, and 16.9, 3.3 and 20.9 kg for early, middle, late rice, respectively. The yield responses to N, P and K fertilizer application were 3.1, 1.1 and 1.0 t/hm2 for single-season rice, 2.3, 1.0 and 1.0 t/hm2 for early rice, 2.3, 0.9 and 1.0 t/hm2 for middle rice, 1.9, 0.8 and 0.8 t/hm2 for late rice, respectively. The agronomic efficiency of N, P and K fertilizer were 17.6, 15.3 and 9.8 kg/kg for single-season rice, 14.6, 15.3 and 10.1 kg/kg for early rice, 11.4, 12.4 and 9.1 kg/kg for middle rice, and 11.5, 14.8 and 9.2 kg/kg for late rice, respectively. The NE treatment applied 12.6%, 9.6% and 21.4% less N, P and K fertilizer than FP treatment, and 7.6% less N and 15.6% less K fertilizer than ST treatment. Compared with FP and ST treatments, the NE treatment increased yield by 0.5 and 0.3 t/hm2, and net profit by 1627 and 893 yuan/hm2; increased N recovery rate by 13.1 and 9.3 percentage points, and increase agronomic efficiency by 4.1 and 2.7 kg/kg; increased P recovery rate by 7.8 and 5.0 percentage points; increased agronomic efficiency by 6.6 and 3.3 kg/kg; increased K recovery rate by 14.6 and 9.5 percentage points; and increased agronomic efficiency by 5.6 and 4.9 kg/kg, respectively.
    Conclusions The newly constructed Nutrient Expert for Rice, based on the intrinsic relationship of yield response, agronomic efficiency and relative yield of different rice types further optimazed fertilizer rate, improved rice yield and fertilizer use efficiency, and increased farmers’ income. The nutrient expert for rice is a feasible fertilizer application method for small farmers in China.

     

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