• ISSN 1008-505X
  • CN 11-3996/S

基于产量反应和农学效率的小麦智能化推荐施肥方法研究

徐新朋, 串丽敏, 何萍, 周卫

徐新朋, 串丽敏, 何萍, 周卫. 基于产量反应和农学效率的小麦智能化推荐施肥方法研究[J]. 植物营养与肥料学报, 2023, 29(7): 1190-1201. DOI: 10.11674/zwyf.2023234
引用本文: 徐新朋, 串丽敏, 何萍, 周卫. 基于产量反应和农学效率的小麦智能化推荐施肥方法研究[J]. 植物营养与肥料学报, 2023, 29(7): 1190-1201. DOI: 10.11674/zwyf.2023234
XU Xin-peng, CHUAN Li-min, HE Ping, ZHOU Wei. The study of intelligent fertilizer recommendation method for wheat based on yield response and agronomic efficiency[J]. Journal of Plant Nutrition and Fertilizers, 2023, 29(7): 1190-1201. DOI: 10.11674/zwyf.2023234
Citation: XU Xin-peng, CHUAN Li-min, HE Ping, ZHOU Wei. The study of intelligent fertilizer recommendation method for wheat based on yield response and agronomic efficiency[J]. Journal of Plant Nutrition and Fertilizers, 2023, 29(7): 1190-1201. DOI: 10.11674/zwyf.2023234

基于产量反应和农学效率的小麦智能化推荐施肥方法研究

基金项目: 农田智慧施肥项目(05);国家重点研发计划项目(2016YFD0200101);中国农业科学院科技创新工程项目。
详细信息
    作者简介:

    徐新朋 E-mail: xuxinpeng@caas.cn

    通讯作者:

    何萍 E-mail: heping02@caas.cn

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

  • 摘要:
    目的 

    为更准确地优化小麦肥料用量,提高肥料利用效率,我们基于产量反应和农学效率,分别建立了适用于长江流域和北方地区的小麦养分专家系统(NE),并采用大量田间试验验证了其可行性。

    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小麦田间试验结果,建立产量和养分吸收数据库,采用QUEFTS模型分析不同种植区域小麦养分吸收特征,分析小麦产量反应、农学效率和相对产量参数及其内在联系,构建施肥模型,开发小麦养分专家系统。于2011—2020年,在小麦主产区11省份开展了467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:小麦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。调查了小麦产量、经济效益、养分回收率和肥料农学效率。

    结果 

    1)将数据分为北方地区和长江流域两部分,经QUEFTS模型模拟小麦养分吸收结果显示,每生产1 t小麦籽粒地上部所需氮、磷和钾养分北方地区为25.6、4.6和20.1 kg,长江流域为20.6、3.9和16.1 kg;小麦对氮、磷和钾肥的平均产量反应北方地区为1.69、0.85和0.69 t/hm2,长江流域为2.60、0.99和0.72 t/hm2;小麦氮、磷和钾肥的平均农学效率北方地区为8.7、8.9和7.0 kg/kg,长江流域为12.6、12.2和8.4 kg/kg;小麦氮、磷和钾养分的平均相对产量北方地区为0.76、0.88和0.90,长江流域为0.59、0.83和0.87。2)田间试验结果显示,与FP处理相比,我国北方地区和长江流域NE处理氮和磷肥用量平均分别减少了37.4%和26.1%,钾肥用量增加了39.2%;与ST处理相比,氮、磷肥用量分别减少了18.2%、14.1%,而钾肥用量相当。NE处理的产量和经济效益较FP处理分别增加了0.22 t/hm2和998元/hm2,与ST处理产量相同,但经济效益增加了260元/hm2。NE处理氮肥回收率较FP和ST处理分别增加了12.9和4.6个百分点,农学效率分别增加了4.0和1.5 kg/kg;磷肥回收率分别增加了5.7和1.1个百分点,农学效率分别增加了2.9和0.6 kg/kg;钾肥回收率较FP处理提高了2.0个百分点,与ST处理相当。

    结论 

    我国北方生产1 t小麦所需的氮、钾养分量高于长江流域,两个区域磷养分需求量差异较小。长江流域小麦产量对氮肥的反应以及氮肥农学效率均高于北方,两个区域磷肥和钾肥的产量反应和农学效率差异较小。经多年多点田间试验证实,分区域建立的小麦养分专家系统进行施肥推荐,可保证小麦产量,增加农民经济效益,提高肥料利用率,是解决我国小麦种植区小农户推荐施肥难题的科学方法。

    Abstract:
    Objectives 

    Aiming to optimize fertilizer application rate and improve fertilizer use efficiency with a simple and easy-to-operate recommendation system, we constructed Nutrient Expert (NE) system suitable for the north of China and the Yangtze Valley, respectively, and verified their feasibility by large amount of field experiments.

    Methods 

    The wheat yield and nutrient uptake database was setup using multi-year and -site wheat field experiments from International Plant Nutrient Institute (IPNI) China Program, our research group and the published literatures. QUEFTS model was used to calculate the nutrient uptake, yield response, agronomic efficiency and relative yield in the north of China and the Yangtze Valley, respectively, to establish the interrelationships among them, and construct a fertilizer application model and develop NE system for wheat. Totally 467 field experiments were conducted in eleven provinces in the main wheat producing areas of China from 2011 to 2020 to calibrate and improve the system. Each experiment included six treatments: fertilizer recommendation based on Nutrient Expert system (NE), farmers’ practices (FP), conventional recommendation based on soil testing (ST), and N omission, P omission and K omission based on the NE treatment. Wheat yield, economic benefit, nutrient use efficiency and fertilizer agronomic efficiency were investigated.

    Results 

    1) The calculation results by QUEFTS model showed that the aboveground N, P and K requirements to produce 1 ton of wheat grain were 25.6, 4.6 and 20.1 kg in the north region, and 20.6, 3.9 and 16.1 kg in Yangtze Valley, respectively; the average yield responses to N, P and K fertilizer were 1.69, 0.85 and 0.69 t/hm2 in the north region, and 2.60, 0.99 and 0.72 t/hm2 in the Yangtze Valley; the average agronomic efficiency of N, P and K fertilizer were 8.7, 8.9 and 7.0 kg/kg in the north region, and 12.6, 12.2 and 8.4 kg/kg in the Yangtze Valley. The average relative yield of N, P and K fertilizer were 0.76, 0.88 and 0.90 kg/kg in the north region, and 0.59, 0.83 and 0.87 kg/kg in the Yangtze Valley. 2) The results of field validation showed that NE treatment applied 37.4% and 26.1% less N and P fertilizer and 39.2% more K fertilizer than FP treatment, and 18.2% and 14.1% less N and P fertilizer than ST treatment and the same amount of K fertilizer with ST. Compared with FP, NE treatment increased yield and net profit by 0.22 t/hm2 and 998 yuan/hm2; compared with ST, NE treatment produced the same yield but extra 260 yuan/hm2 of net profit. Compared with FP and ST treatments, NE increased N recovery efficiency by 12.9 and 4.6 percentage points, and the agronomic efficiency of N fertilizer by 4.0 and 1.5 kg/kg; increased P recovery efficiency by 5.7 and 1.1 percentage points, and the agronomic efficiency of P fertilizer increased by 2.9 and 0.6 kg/kg; increased K recovery efficiency by 2.0 percentage points than FP treatment and exhibited similar K recovery efficiency to the ST treatment.

    Conclusions 

    The north of China requires more N and K, and similar P for one ton of wheat production, compared to the Yangtze Valley. The yield response to N and the agronomic efficiency of N fertilizers in the Yangtze valley are higher than in the north region, and both regions have similar yield response to P and K and the agronomic efficiencies of P and K fertilizers. The multi-year and -site field experiments verified the easy-to-operate and simplification of the constructed Nutrient Expert for Wheat system specified for the north region and the Yangtze Valley.

  • 诸多调查结果显示,我国小麦种植区存在严重过量施肥问题[13]。肥料的长期过量施用,减弱了施肥对小麦的增产效应,还造成肥料利用率低,肥料资源浪费等问题[45]以及肥料损失引起的环境风险[6]。因此,倡导合理施肥对小麦增产稳产和可持续发展十分重要。依据传统的土壤测试通过确定土壤养分丰缺水平,布置肥效试验进而建立土壤养分与产量或者养分吸收关系,确定最佳施肥量[7],以及在此基础上开展的如基于GIS和SPAD值的养分推荐和施肥配方[8]等方法,仍然是当前较为盛行的配方施肥方法。测土配方施肥在提高作物产量和优化施肥方面发挥了重要作用,但需要投入大量的人力、物力和财力,存在工作量大、时耗长的缺点,且从土壤样品采集到实验室分析整个过程存在诸多不确定性[9],土壤测试结果与作物反应相关性不高,导致肥料难以推荐。除此之外,我国华北以及长江流域小麦种植区域一年两茬的种植制度,存在测土不及时和小农户不具备测土条件等问题,这就给养分管理提出了新的挑战。作物施肥效果最终将在产量上得到体现,如何建立土壤养分供应与作物产量间的量化关系是当前推荐施肥的关键。作物产量所需养分可以分为土壤供应和施肥供应两部分,应用不施某种养分处理的产量来表征土壤养分供应和施肥后的产量反应来表征施肥效应具有普遍意义,其将土壤养分供应看作一个黑箱,包含了环境中带入的养分,这就解决了氮素难以推荐的难题。与此同时,将复杂的推荐施肥原理简化为用户方便使用的操作系统也是实现科学施肥的重要组成部分。由中国农业科学院农业资源与农业区划研究所研发的基于产量反应和农学效率的推荐施肥方法,采用QUEFTS模型考虑作物氮、磷、钾三大营养元素间的交互作用模拟作物养分吸收,通过建立各农学参数间的内在联系,同时考虑土壤养分平衡,依据产量反应进行推荐施肥,构建了小麦养分推荐模型,研发了智能操作系统[1011]。本研究分析了所构建的小麦养分专家系统中各农学参数,包括养分吸收、产量反应、相对产量和农学效率等,通过多年多点的田间试验对小麦养分专家系统进行验证,以实现小麦的科学施肥。

    收集汇总来自国际植物营养研究所中国项目部、研究团队于2000—2020年在中国小麦主产区开展的田间试验,以及此期间在学术期刊上公开发表的学术论文,其中文献数据来源于中国知网数据库(CNKI)通过检索关键词及关键词组合“小麦”、“小麦+产量”、“小麦+养分吸收”、“小麦+肥料利用率”等得到的中文文献。根据气候特征,将数据分为北方地区和长江流域两部分,其中北方地区包括华北、东北和西北地区,长江流域包括西南和长江中下游地区。应用QUEFTS模型模拟小麦最佳养分吸收,其采用线性−抛物线−平台函数模拟产量和养分吸收关系,其中北方地区氮、磷和钾养分吸收数据量分别为5634、4173和4289个,长江流域分别为2317、1779和1748个。小麦养分专家系统基于产量反应和农学效率关系原理进行施肥推荐,本研究中,北方地区小麦氮、磷和钾产量反应数据分别有1261、698和978个,长江流域分别有742、367和419个。

    为验证小麦养分专家系统的可行性,于2011—2020年在河北、河南、山东、山西、内蒙古、安徽、湖北、江苏、云南、四川、浙江11省份开展了467个田间试验,其中北方地区405个,长江流域62个。所有试验采用统一处理,均包含6个处理,分别为:1)基于小麦养分专家系统推荐施肥,即NE处理,试验开始前调查试验地块农户过去3年小麦产量、施肥量及施肥措施等;2)当地农民习惯施肥,即FP处理,完全遵循农民习惯施肥,记录施肥量、施肥措施等;3)土壤测试施肥,即ST处理,如测土不及时或条件不具备,采用当地农技推广部门的推荐量;4)、5)、6)处理分别为NE处理基础上不施氮(NE-N)、不施磷(NE-P)和不施钾(NE-K)处理,用于计算产量反应和肥料利用率。每个处理小区面积30~50 m2,小麦品种选用当地主栽品种。同一试验各处理播种量、病虫草害防治均一致。田间试验使用肥料包括尿素、过磷酸钙、磷酸氢二铵、氯化钾和硫酸钾等。

    采用随机采样法测定小麦产量,各试验点采用相同标准进行样品采集,小麦成熟期于每个小区中央部分均匀选取3个1 m2测定小麦产量,并最终折合成含水量13.5%的产量。每个小区采集1 m长有代表性样品带回室内分成籽粒和秸秆两部分,于60℃下烘干至质量恒定,称重用于计算收获指数。选取部分烘干样品粉碎后,采用H2SO4−H2O2消煮,分别用凯氏法、钒钼黄比色法和原子吸收法测定氮、磷和钾养分含量。

    采用Excel 2020对数据进行处理,使用SPSS 17.0软件对NE、FP和ST处理的施肥量、产量、净效益和养分利用率在0.05水平上进行ANOVA分析,使用Sigmaplot 14.0软件绘制箱图。NE、FP和ST采用相同计算公式,以NE处理氮计算为例,磷和钾计算同氮,其相关计算如下:

    氮产量反应(kg/hm2)=NE产量−NE-N产量;

    氮农学效率(kg/kg)=(NE产量−NE-N产量)/施氮量;

    氮相对产量=NE-N产量/NE产量;

    氮回收利用率(%) = (NE植株地上部氮累积量−NE-N植株地上部氮累积量)/NE施氮量×100;

    肥料成本(元/hm2)为氮、磷和钾肥料成本总和;净效益 (元/hm2)=收获后产值−肥料成本。

    所有计算公式中,氮、磷和钾施用量分别为N、P2O5和K2O量。

    应用QUEFTS模型模拟不同潜在产量下(8、12、16 t/hm2)小麦最佳养分吸收量得出,当目标产量达到潜在产量的60%~70%时,生产1 t小麦籽粒其地上部氮(N)、磷(P)和钾(K)养分需求量北方地区分别为25.6、4.6和20.1 kg,长江流域分别为20.6、3.9和16.1 kg (图1)。相比长江流域,北方地区生产1 t小麦籽粒需要吸收更多的氮、磷和钾养分。

    图  1  QUEFTS模型模拟的不同潜在产量小麦最佳养分吸收量
    注:红色线条表示北方地区,黑色线条表示长江流域;YA、YD和YU分别表示最大累积边界线、最大稀释边界线和QUEFTS模型模拟的养分吸收曲线;自下而上的潜在产量分别为8、12和16 t/hm2
    Figure  1.  The optimum nutrient requirements simulated by QUEFTS model under different potential yields of wheat
    Note: The red and black lines represent the north region and the Yangtze Valley, respectively. YA, YD and YU indicate the lines of maximum accumulation, maximum dilution, and balanced N, P and K uptake predicted by QUEFTS model. The lines from bottom to top indicate the potential yield of 8, 12 and 16 t/hm2.

    就全部产量反应数据而言,我国小麦种植区施用氮肥的产量反应最高,其次为磷,最后为钾,平均产量反应分别为2.03、0.90和0.70 t/hm2。不同区域的产量反应存在一定差异,长江流域的氮、磷和钾产量反应均高于北方地区,其中长江流域分别为2.60、0.99和0.72 t/hm2,北方地区分别为1.69、0.85和0.69 t/hm2 (图2)。较高的氮素产量反应说明养分管理中氮肥施用在小麦增产方面发挥着最为重要的作用。就本研究数据库中全部肥料农学效率数据而言,施用氮、磷和钾肥的平均农学效率分别为10.1、10.1和7.4 kg/kg。北方地区施用氮、磷和钾肥的平均农学效率均低于长江流域,其中北方地区分别为8.7、8.9和7.0 kg/kg,长江流域分别为12.6、12.2和8.4 kg/kg (图2)。

    图  2  小麦产量反应和肥料农学效率分布
    注:箱体中间实线代表中值,虚线代表均值,方框上下边缘、上下实线和实心圆圈分别代表上下25%的数值、90%和10%的数值、95%和5%的数值。
    Figure  2.  The distribution of yield response and agronomic efficiency of fertilizer for wheat
    Note: The solid and dotted lines inside the boxes represent the median and mean values, the upper and lower frames of the box, the upper and lower solid lines, and the solid circles outside the boxes represent the upper and lower 25%, the 90% and 10% values, the 95% and 5% values.

    小麦产量反应和肥料农学效率间存在显著的二次曲线关系(图3),小麦养分专家系统则是在分析大量试验数据基础上以产量反应和肥料农学效率为依据进行推荐施肥。研究结果显示,北方地区和长江流域氮的产量反应和农学效率关系曲线较为接近,而磷和钾的产量反应和农学效率关系曲线北方地区要低于长江流域,说明在相同的产量反应下,北方地区的肥料农学效率要低于长江流域,在同等目标产量下则需要更多的磷和钾肥。

    图  3  小麦产量反应和肥料农学效率关系
    注:图中红色曲线表示北方地区,黑色曲线表示长江流域。
    Figure  3.  The relationship between yield response and agronomic efficiency of fertilizer for wheat
    Note: Red lines represent the north region, and black lines represent Yangtze Valley.

    就全部数据而言,当前我国小麦主产区的土壤氮、磷和钾养分对小麦总养分需求的供应程度分别达到了70%、86%和89%。北方地区的氮、磷和钾平均相对产量均高于长江流域,北方地区分别为0.76、0.88和0.90,长江流域分别为0.59、0.83和0.87 (图4)。

    图  4  小麦相对产量分布
    注:箱体中间实线代表中值,虚线代表均值,方框上下边缘、上下实线和实心圆圈分别代表上下25%的数值、90%和10%的数值、95%和5%的数值。
    Figure  4.  The distribution of wheat relative yield
    Note: The solid and dotted lines inside the boxes represent the median and mean values, the upper and lower frames of the box, the upper and lower solid lines, and the solid circles outside the boxes represent the upper and lower 25%, the 90% and 10% values, the 95% and 5% values.

    就总体施肥量数据平均值而言,NE处理氮、磷和钾肥用量分别为166、85和71 kg/hm2,FP处理分别为265、115和51 kg/hm2,ST处理分别为203、99和72 kg/hm2。与FP处理相比,NE处理的氮肥和磷肥用量分别降低了37.4% (P<0.001)和26.1% (P<0.001),但增加了39.2%的钾肥用量(P<0.001);与ST处理相比,NE处理氮、磷肥用量分别减少了18.2% (P<0.001)和14.1% (P<0.001),而钾肥用量相当(P=0.785)。统计不同区域各处理施肥量,与FP和ST处理相比,NE处理在北方地区的氮肥用量分别降低了38.6%和19.5%,磷肥用量分别降低了26.9%和13.2%,但钾肥用量分别增加了48.4%和3.4%;在长江流域的氮肥用量分别降低了25.8%和8.0%,磷肥用量分别降低了11.8%和16.5%,钾肥用量分别降低了4.5%和24.1% (图5)。

    图  5  不同施肥处理小麦施肥量
    注:NE—小麦养分专家系统;FP—农民习惯施肥;ST—测土施肥。箱体中间实线代表中值,虚线代表均值,方框上下边缘、上下实线和实心圆圈分别代表上下25%的数值、90%和10%的数值、95%和5%的数值。
    Figure  5.  Fertilizer application rate of wheat under different treatments
    Note: NE—Nutrient expert for wheat; FP—Farmers’ practice; ST—Soil testing based recommendation. The solid and dotted lines inside the boxes represent the median and mean values, the upper and lower frames of the box, the upper and lower solid lines, and the solid circles outside the boxes represent the upper and lower 25%, the 90% and 10% values, the 95% and 5% values.

    由于FP处理完全遵循农户自己的施肥管理模式,导致施肥量变异很大,总体存在施肥过量问题。就总体数据而言,FP处理中有88.9%的试验点施氮量大于180 kg/hm2,而60.2%的试验点施氮量大于250 kg/hm2。北方地区的FP处理平均氮肥用量显著高于长江流域,北方地区和长江流域FP处理平均氮肥用量分别达到了273和210 kg/hm2,减施幅度北方地区显著高于长江流域。与施氮量相似,FP处理小麦施磷量总体较高,高施磷量主要集中在北方地区,平均施磷量北方地区和长江流域分别为121和74 kg/hm2。FP处理中有62.7%的试验点施磷量超过100 kg/hm2,而19.9%的试验点施磷量超过150 kg/hm2。与氮、磷肥相反,FP需要加强钾肥的施用,尤其是北方地区,平均钾肥用量仅有49 kg/hm2。FP处理中施钾量小于50 kg/hm2的试验点占到了全部试验数量的63.2%,而有20.3%的试验点不施钾肥。

    就总体数据而言(图6),与FP处理相比,NE处理提高了产量和经济效益,分别增加了0.22 t/hm2 (3.0%,P=0.071)和998元/hm2 (7.1%,P<0.001);与ST处理相比,NE处理的平均产量相同(7.71 t/hm2),但经济效益增加了260元/hm2 (1.8%,P=0.340)。就不同地区小麦而言,与FP处理相比,NE处理在北方地区的产量和经济效益分别提高了0.21 t/hm2 (2.8%)和1012元/hm2 (6.8%),长江流域分别增加了0.26 t/hm2 (5.4%)和901元/hm2 (10.7%);与ST处理相比,NE处理在北方地区和长江流域的产量均无显著差异,但经济效益分别增加了216元/hm2 (1.4%)和547元/hm2 (6.2%),而此经济效益增量并未考虑ST处理的测土费用。与FP处理相比,NE处理的经济效益增加量有48.7%来自于产量增量,而与ST相比,NE处理的经济效益增加量主要来自于节约肥料费用。

    图  6  不同施肥处理小麦产量和净效益比较
    注:NE—小麦养分专家系统;FP—农民习惯施肥;ST—测土施肥。箱体中间实线代表中值,虚线代表均值,方框上下边缘、上下实线和实心圆圈分别代表上下25%的数值、90%和10%的数值、95%和5%的数值。
    Figure  6.  Comparison of wheat yield and net profit under different treatments
    Note: NE—Nutrient expert for wheat; FP—Farmers’ practice; ST—Soil testing based recommendation. The solid and dotted lines inside the boxes represent the median and mean values, the upper and lower frames of the box, the upper and lower solid lines, and the solid circles outside the boxes represent the upper and lower 25%, the 90% and 10% values, the 95% and 5% values.

    就总体数据而言,与FP和ST处理相比,NE处理的氮肥回收率分别提高了12.9个百分点(P<0.001)和4.6个百分点(P<0.001),氮肥农学效率分别提高了4.0 kg/kg (P<0.001)和1.5 kg/kg (P<0.001) (图7)。就不同地区而言,北方地区NE处理的氮肥回收率和农学效率较FP处理分别提高了13.2个百分点和3.8 kg/kg,较ST处理分别提高了4.5个百分点和1.3 kg/kg;长江流域NE处理的氮肥回收率和农学效率较FP处理分别提高了11.2个百分点和5.5 kg/kg,较ST处理分别提高了4.8个百分点和2.3 kg/kg。NE处理较FP处理显著提高了磷肥回收率和农学效率,分别提高了5.7个百分点(P<0.001)和2.9 kg/kg (P<0.001),而与ST处理无显著差异,但分别提高了1.1个百分点(P=0.164)和0.6 kg/kg (P=0.297) (图7)。长江流域磷肥利用率要高于北方地区,与FP和ST处理相比,北方地区NE处理的磷肥回收率分别增加了5.6和0.4个百分点,农学效率分别提高了2.6和0.2 kg/kg;长江流域的磷肥回收率分别增加了6.0和5.3个百分点,农学效率分别提高了4.2和3.1 kg/kg。就钾肥利用率总体数据而言,由于NE处理较FP处理提高了钾肥用量,其钾肥回收率仅提高了2.0个百分点(P=0.408),而与ST处理相当(图7)。北方地区NE处理施钾量显著高于FP处理,与ST处理相当,三者的钾肥回收率和农学效率无显著差异;长江流域NE处理较FP和ST处理的钾肥回收率分别提高了13.3和11.5个百分点,农学效率分别提高了5.2和3.6 kg/kg。

    图  7  不同施肥处理小麦肥料利用率比较
    注:NE—小麦养分专家系统;FP—农民习惯施肥;ST—测土施肥。误差线代表标准误。
    Figure  7.  Comparison of fertilizer use efficiency of wheat among different treatments
    Note: NE—Nutrient expert for wheat; FP—Farmers’ practice; ST—Soil testing based recommendation. Error bar represents standard error.

    确定目标产量的养分需求量是开展养分管理的前提,QUEFTS模型通过应用田间试验大数据并考虑养分间交互作用得出最佳养分吸收量,为研究区域间的养分吸收差异提供了技术手段[1213]。本研究中小麦养分吸收分析结果显示,相较于水稻和玉米[14],在相同气候条件下,生产1 t小麦籽粒需要更多的养分,属于高耗养分作物,尤其是氮和磷。而前人在中国关于小麦方面的研究主要集中在华北平原地区,如Liu等[15]应用1985—1995年的642个数据模拟的氮磷钾养分需求量分别为24.6、3.7和23.0 kg/t,Chuan等[10]利用2000—2011年数据(氮磷钾养分吸收数据量分别为3372、2088和2098个)研究氮磷钾养分需求量分别为22.8、4.4和19.0 kg/t。本研究得出的北方地区单位产量氮和磷养分需求量要高于前人的研究结果[10, 15],这与该区域的可获得产量不断提升具有一定关系,因为随着目标产量的提升,当达到一定潜在产量后,其作物养分内在效率呈降低趋势,导致生产1 t籽粒所需养分逐渐增加[1617]。由于气候、品种和管理上的差异,不同国家和地区间的小麦养分需求也存在一定差异,如Pathak等[18]应用整个印度的数据得出生产1 t小麦籽粒产量其地上部氮、磷、钾养分需求分别为23.1、3.5和28.5 kg/t,而Maiti等[19]应用印度东北地区的数据研究氮磷钾养分需求量则为15.8、3.2和28.4 kg/t。本研究中根据气候和土壤类型差异将数据分为北方地区和长江流域进行养分吸收模拟,如我国长江流域轮作体系以小麦−水稻为主,土壤以水稻土为主,而北方地区则以小麦−玉米轮作体系为主,土壤以潮土为主;长江流域生育期降雨量较大,产量潜力较低,昼夜温差低导致其形成单位产量的养分需求量要低于北方地区,而QUEFTS模型模拟得出的养分吸收差异也说明了进行养分吸收差异化分析的必要性。虽然本研究中的数据量得到了大幅度扩充,尤其是长江流域的养分吸收数据方面,然而我国小麦种植区的自然环境、土壤类型差异较大,且当前研究的数据主要集中在主产区,进一步细分麦区进行养分吸收差异相关研究对于优化养分管理十分必要,但这需要一个庞大的数据库作为支撑。

    充分利用土壤养分是提高肥料利用效率需要考虑的重要因素之一,孙昭安等[20]研究结果显示冬小麦的氮素吸收中有2/3都来自于土壤,如应用本研究数据得到的平均土壤氮、磷、钾养分供应量北方地区分别达到了148、32和159 kg/hm2,长江流域分别为73、18和82 kg/hm2 (数据未显示)。长期过量施肥导致北方冬小麦种植区的土壤供肥能力呈逐渐增加趋势,年均增加1.6%,其施肥增产率已由2005年的30.9%下降至2016年的20.2%[1]。虽然土壤基础养分供应随着土壤养分含量的增加而增加,但土壤养分测试值与土壤基础养分供应间的相关性较弱[21],因此需要选择合适的指标来反映土壤基础养分供应。采用作物产量反应表征土壤养分供应可以考虑土壤本体及外界环境带入的养分,并使用农学效率表征施肥效应可有效解决此问题,在同一气候条件下,施用某种养分的产量反应越大,说明土壤中该养分的供应量越小,而肥料农学效率则随着产量反应的增加呈增加趋势。长期过量施肥导致我国小麦种植区的肥料农学效率呈降低趋势,维持在6.3~6.7 kg/kg [1],与其相比,本研究数据库计算获得了较高的肥料农学效率,是因为本研究采用的是优化施肥下计算得到的肥料农学效率,由此计算得到的施肥量也更加合理。而在缺乏相关数据时,小麦养分专家系统可通过总结大量的田间试验,采用相对产量对产量反应进行估测[11],这就克服了田间试验中样品采集工作量大、土壤和植株测试时间长等缺点,在测土不及时和条件不具备时更加凸显了该技术的优势。根据不同麦区的气候条件和土壤类型等建立产量反应和肥料农学效率关系,分析其变化规律,有助于养分专家系统对小麦进行精准的差异化养分管理。然而由于一些区域相关数据较少,在建立产量反应与肥料农学效率关系过程中就会出现因为个别试验点的数据对关系曲线造成很大影响,因此当前研究中仅划分了两个区域,未来在不同麦区的产量反应和肥料农学效率关系方面仍需进行深入研究。

    小麦种植区是当前我国粮食作物化肥减施的重点区域,其过量施肥程度远高于其它粮食作物,尤其是氮肥和磷肥用量。研究显示我国华北平原冬小麦种植区的氮素盈余均值达到了165 kg/hm2[22],氮肥在减施30%情况下不会显著影响我国小麦产量[23]。而全国的平均磷肥用量达到了137.7 kg/hm2[24],在巢湖流域稻麦轮作区磷肥减量20%仍可保证作物稳产[25]。长期的过量施肥导致土壤养分累积,我国潮土区(小麦和玉米主产区) 29年长期监测结果显示土壤全氮提升了37.8%,土壤有效磷含量提升了226%[26]。虽然本研究中与FP处理相比,NE处理通过优化肥料用量显著提高了氮肥和磷肥利用效率,但仍有进一步提高的空间。所有试验点中,NE处理仅有15.4%的试验点氮肥回收率超过了50%,磷肥回收率超过30%的试验点仅占10.3%,而FP处理氮肥回收率超过50%和磷肥回收率超过30%的试验点分别仅占4.7%和2.4%,说明高施肥量和土壤中累积的养分双方面限制了肥料利用率的提升。马悦等[2728]研究显示,在我国北方麦区土壤有效磷含量应维持在20~30 mg/kg,收获期1 m土层硝态氮残留量应介于55~100 kg/hm2,但当前我国小麦主产区的土壤养分含量或累积量通常高于这个数值。因此,倡导合理施肥十分必要,是从源头解决肥料过量施用的基本措施之一。

    我国化肥零增长目标已经实现,农业养分管理已步入一个新的阶段,但目前农民盲目施肥导致的化肥不合理施用现象仍然突出,实现化肥科学施用仍有很长的路要走。随着农业人口的短缺,节约劳动力成本对进一步提高经济效益至关重要,智能化推荐施肥方法则显得尤为重要。应用当前信息技术,小麦养分专家系统已从最初的网络版发展到现在只需关注微信公众号即可使用,用户只需回答一些简单问题,如作物过去3年平均产量、上季作物施肥量、秸秆还田方式和有机肥施用情况等,系统就会给出推荐用量,其操作更加简便、智能。针对当前高强度利用下的耕地系统,减少肥料投入的另一重要途径是提高耕地质量,因为肥料贡献率随着土壤地力的提高呈下降趋势,在促进小麦增产、增收的同时,可降低小麦产量对施用化肥的依赖[29]。当前的一些措施如有机无机肥配施是培肥土壤,提高小麦目标产量和进一步肥料减施的主要措施[3031];施用土壤改良剂,改善土壤理化性质,提高团聚体稳定性,进而提高土壤肥力,促进产量提升[32]。在养分专家系统中用户可自行添加购买的肥料品种,系统会根据推荐用量和选择的肥料品种给出肥料的实物用量。然而施用肥料也要因地制宜,不同土壤施用不同的肥料品种,如砂姜黑土施用重过磷酸钙和聚磷酸铵、红壤施用磷酸二铵和重过磷酸钙,对土壤有效磷含量提升、小麦磷素吸收以及产量提高更加有利[33];酰胺态氮在中氮条件下有助于提高强筋小麦产量和籽粒含氮量,更加有助于小麦蛋白质的积累[3435]。而在当前小麦养分专家系统中,其关注点主要集中在肥料用量合理推荐上,虽然考虑了秸秆还田和上季养分残效等因素,并给出了以氮肥为准的有机替代比例,但在施用有机肥情况下磷和钾肥用量优化以及肥料品种选择方面有待开展相关研究。

    通过小麦养分专家系统可以获得合理的氮磷钾肥用量,辅助一些先进的管理措施和高效产品可进一步发挥其作用。一些含有小分子氨基酸如黄腐酸、天冬氨酸的肥料产品等能显著促进小麦根系生长和养分吸收、提高生物量,并有利于改善小麦籽粒营养[3637];结合包衣和添加抑制剂等手段可保障小麦整个生育期的土壤氮素持续供应能力,且减少氮素淋溶损失[3839];增效剂[40]、绿色新型肥料[41]等等也都是研究养分增效的热点。控释肥施用技术是当前较为流行的措施[42],卞文新等[43]研究显示,与农民习惯施肥相比,施用控释包膜尿素可降低30%的氮肥用量。但碍于当前市售的能够实现小麦一次性施肥的相关产品较少,在小麦养分专家系统推荐施肥下,不同小麦种植区实现一次性施肥的控释肥施用技术还有待进一步研究。除此之外,结合水氮耦合[44]和优化施肥位置[45]等措施可进一步实现化肥减施增效,如同时优化氮肥用量和基追比可使氮肥对小麦的增产效应提高8%~30%[46];配合中微量元素有利于建成良好根系形态,调节根系生理活性,促进养分吸收利用[4748]等。各种单项技术或者产品已经很成熟,高效的集成技术模式才是今后的研究重点,如山东省冬小麦农户产量只实现了最高纪录产量的64.34%,通过优化并集成水肥投入、优化追肥比例、增施有机肥和锌肥等措施可使冬小麦产量差缩减23.46%,氮肥偏生产力提高56.99%[49]。推荐施肥在化肥减施增效方面发挥了不可替代的作用,但今后仍需建立适宜不同生态区的集养分专家系统、有机替代、水肥耦合、肥料机械深施等土壤培肥综合技术模式,聚焦耕地科技创新,着力解决好土壤与肥料的重大科技问题,实现粮食增产和养分资源高效利用双赢。

    以田间试验大数据为支撑分区域建立的小麦养分专家系统,应用QUEFTS模型分析了北方地区和长江流域小麦养分吸收特征,以及产量反应和肥料农学效率等参数的内在联系,研发了简便、易操作的推荐施肥方法。大量田间试验证明,在当前生产条件下,小麦养分专家系统可降低氮肥和磷肥用量,提高小麦产量,并获得了优于传统测土施肥方法的经济效益。较好的实践效果显示,小麦养分专家系统可实现小农户不具备土壤测试条件下的肥料推荐,是全面提高我国小麦生产效益、适应范围广泛的推荐施肥系统。

  • 图  1   QUEFTS模型模拟的不同潜在产量小麦最佳养分吸收量

    注:红色线条表示北方地区,黑色线条表示长江流域;YA、YD和YU分别表示最大累积边界线、最大稀释边界线和QUEFTS模型模拟的养分吸收曲线;自下而上的潜在产量分别为8、12和16 t/hm2

    Figure  1.   The optimum nutrient requirements simulated by QUEFTS model under different potential yields of wheat

    Note: The red and black lines represent the north region and the Yangtze Valley, respectively. YA, YD and YU indicate the lines of maximum accumulation, maximum dilution, and balanced N, P and K uptake predicted by QUEFTS model. The lines from bottom to top indicate the potential yield of 8, 12 and 16 t/hm2.

    图  2   小麦产量反应和肥料农学效率分布

    注:箱体中间实线代表中值,虚线代表均值,方框上下边缘、上下实线和实心圆圈分别代表上下25%的数值、90%和10%的数值、95%和5%的数值。

    Figure  2.   The distribution of yield response and agronomic efficiency of fertilizer for wheat

    Note: The solid and dotted lines inside the boxes represent the median and mean values, the upper and lower frames of the box, the upper and lower solid lines, and the solid circles outside the boxes represent the upper and lower 25%, the 90% and 10% values, the 95% and 5% values.

    图  3   小麦产量反应和肥料农学效率关系

    注:图中红色曲线表示北方地区,黑色曲线表示长江流域。

    Figure  3.   The relationship between yield response and agronomic efficiency of fertilizer for wheat

    Note: Red lines represent the north region, and black lines represent Yangtze Valley.

    图  4   小麦相对产量分布

    注:箱体中间实线代表中值,虚线代表均值,方框上下边缘、上下实线和实心圆圈分别代表上下25%的数值、90%和10%的数值、95%和5%的数值。

    Figure  4.   The distribution of wheat relative yield

    Note: The solid and dotted lines inside the boxes represent the median and mean values, the upper and lower frames of the box, the upper and lower solid lines, and the solid circles outside the boxes represent the upper and lower 25%, the 90% and 10% values, the 95% and 5% values.

    图  5   不同施肥处理小麦施肥量

    注:NE—小麦养分专家系统;FP—农民习惯施肥;ST—测土施肥。箱体中间实线代表中值,虚线代表均值,方框上下边缘、上下实线和实心圆圈分别代表上下25%的数值、90%和10%的数值、95%和5%的数值。

    Figure  5.   Fertilizer application rate of wheat under different treatments

    Note: NE—Nutrient expert for wheat; FP—Farmers’ practice; ST—Soil testing based recommendation. The solid and dotted lines inside the boxes represent the median and mean values, the upper and lower frames of the box, the upper and lower solid lines, and the solid circles outside the boxes represent the upper and lower 25%, the 90% and 10% values, the 95% and 5% values.

    图  6   不同施肥处理小麦产量和净效益比较

    注:NE—小麦养分专家系统;FP—农民习惯施肥;ST—测土施肥。箱体中间实线代表中值,虚线代表均值,方框上下边缘、上下实线和实心圆圈分别代表上下25%的数值、90%和10%的数值、95%和5%的数值。

    Figure  6.   Comparison of wheat yield and net profit under different treatments

    Note: NE—Nutrient expert for wheat; FP—Farmers’ practice; ST—Soil testing based recommendation. The solid and dotted lines inside the boxes represent the median and mean values, the upper and lower frames of the box, the upper and lower solid lines, and the solid circles outside the boxes represent the upper and lower 25%, the 90% and 10% values, the 95% and 5% values.

    图  7   不同施肥处理小麦肥料利用率比较

    注:NE—小麦养分专家系统;FP—农民习惯施肥;ST—测土施肥。误差线代表标准误。

    Figure  7.   Comparison of fertilizer use efficiency of wheat among different treatments

    Note: NE—Nutrient expert for wheat; FP—Farmers’ practice; ST—Soil testing based recommendation. Error bar represents standard error.

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  • 收稿日期:  2023-05-25
  • 录用日期:  2023-07-09
  • 网络出版日期:  2023-07-17
  • 刊出日期:  2023-07-24

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