Research progress on nitrogen nutrition diagnosis method based on SPAD for main grain crops
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摘要:
基于叶绿素计测定的SPAD值与植物叶片叶绿素和氮浓度的关系，详细综述了用叶绿素计在玉米、小麦、水稻以及其他作物上进行氮素营养诊断的研究进展。第一，“相对SPAD值”、“氮饱和指数”或“归一化SPAD”等指标能够消除或减小品种、生育期及区域年际间的误差；第二，不同生育期应选择理想指示叶作为诊断目标；第三，不同叶位间的SPAD差值与氮素营养的关系较为稳定可靠。总结了基于SPAD的作物营养诊断和推荐施肥技术规范、不同作物种类SPAD值及其衍生参数的筛选、模型的稳定性和普适性，除氮素外其他营养元素与SPAD的响应关系等方面存在的问题和不足。在此基础上提出了利用叶绿素计开展植物氮素营养诊断与施肥需要进一步研究的方向：一是建立基于SPAD的不同作物氮素营养诊断的技术规范；二是确定基于叶片SPAD值的作物氮营养丰缺指标；三是建立基于叶片SPAD值的作物施肥模型；四是开发基于SPAD的施肥决策支持系统；五是开展钾、镁、铁、锰等与叶绿素合成有关的其他营养元素与SPAD值的关系研究。
Abstract:This paper reviews the research progress on N nutrition diagnosis of corn, wheat, rice, and other crops using chlorophyll meter. The review focused on the relationship between SPAD, plant leaf chlorophyll, and N concentration. Firstly, indicators such as “relative SPAD value” , “nitrogen saturation index” , or “normalized SPAD” could eliminate or reduce errors between varieties, growth periods, and regions interannual. Secondly, leaf is the ideal indicator suitable for the diagnostic target at different growth periods. Thirdly, the relationship between SPAD differences among various layers of leaves and N nutrition is more stable and reliable. We summarized the identified problems and shortcomings in the technical specification of crop nutrition diagnosis. Further, we recommend fertilization based on SPAD, building and screening SPAD values of different crop species and their derivative parameters, stability and universality of models, and the response relationship between other nutrients besides N and SPAD. On this basis, the paper put forward further research directions on the diagnosis of plant N nutrition and fertilization using a chlorophyll meter. 1) There is a need to scale up technical specifications for different crops N nutrition diagnosis based on SPAD. 2) There is a need to consider the determination of N sufficiency and deficiency indexes of leaf SPAD. 3) Fertilization models based on leaf SPAD should be established. 4) A fertilization decision support system based on SPAD should be developed. 5) There is a need for further research on the relationships between other nutrients related to chlorophyll synthesis such as K, Mg, Fe, and Mn and SPAD values.
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Keywords:
- SPAD /
- chlorophyll /
- nitrogen nutrition /
- diagnosis and fertilization
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在发现植物叶片叶绿素浓度与氮浓度高度相关之后，从20世纪70年代开始就研发非破坏性的能够估算植物叶片叶绿素浓度的仪器[1]。日本渔业和农业部与美能达公司联合启动土壤植物分析(soil and plant analysis development，简称SPAD)项目，研发了一种商业化的手持式仪器(SPD-501和SPAD-502)。它测量端能够夹住叶片进行读数，能够存储30个读数并得到平均值。它是利用叶绿素在可见光波段(660 nm)强吸收和近红外波段(940 nm)强反射特性得到两个波段的透射光比值，从而得到叶片叶绿素相对含量，也常被称为叶绿素计。目前国内外常用的是SPAD-502叶绿素计。众所周知，SPAD是利用植物体内叶绿素含量与氮素营养的密切相关关系来进行氮素营养诊断的，因此从上世纪80年代以来，研究人员利用SPAD-502开展了大量的有关植物氮营养状况的研究。本文就基于SPAD的作物氮素营养诊断研究进展作一综述。
1. SPAD值与叶片叶绿素浓度的关系
尽管植物叶片叶绿素浓度与SPAD值的关系受到植物种类[2]、叶龄[3]、取样位置[4]、生长环境[5]等因素的影响，但是二者之间存在的显著关系已被科学家研究证实，只是这种关系有线性关系和非线性关系之分。在22种植物叶片SPAD值与叶绿素浓度关系的研究中发现二者存在显著的线性相关关系(R2=0.48)[6]；同样在6个玉米杂交种上按时间序列采集了大量的SPAD数据，分析发现叶绿素浓度与SPAD值存在单因素线性回归关系(R2= 0.83)[7]。有报道称在美国阿拉巴马州3个研究基地的牛毛草叶绿素浓度和SPAD值存在线性关系，且决定系数达到0.96[8]。但在研究玉米、小麦、水稻、烟草和大豆叶子的SPAD值与叶绿素浓度的关系中发现，二者呈现一元二次方程关系(R2=0.89)[9]，这个关系覆盖了整个叶绿素水平；也有人认为当叶绿素浓度较高(>60)时二者存在着非线性关系[叶绿素浓度=a+b (SPAD)2，R2=0.97]；当叶绿素浓度处于20～60时，二者间存在很好的线性关系[10]。另外在茶树[11]、马铃薯[12]和其他一些树种[13]上还发现二者呈指数关系。虽然众多研究都表明了单因素回归方程能准确地描述叶绿素浓度与SPAD值之间的定量关系，但是也有研究发现二者相关关系在同一物种或者品种范围内更好。例如，在8个热带和亚热带树种上发现，叶绿素浓度和SPAD值间分别存在8个独立的线性回归关系(R2=0.91～0.96)与不同树种分别对应[14]。同样在不同葡萄品种间也有类似发现[15]。由此可见，模拟SPAD值与叶片叶绿素浓度时应充分考虑植物种类、叶龄、叶片厚度、含水量等因素，对所建立的关系应有精确的前提条件。
2. SPAD值与植株氮浓度的关系
开发SPAD叶绿素计最初的目的是估算水稻的氮素营养状况，用于更准确地为水稻氮肥管理决策服务。但如何更好地利用SPAD叶绿素计在其他作物上进行氮肥高效管理，已有大量的尝试。研究表明SPAD值与植物叶片氮浓度密切相关[16-21]。但就针对具体作物来讲，其定量关系表现不一。
研究发现，与叶绿素浓度与SPAD值的关系一样，不同栽培品种间的叶片氮浓度与SPAD值的关系需用单一或者独立的回归方程来描述，这一结果在21个热带玉米品种[4]、8个玉米杂交种[8, 16, 22]、苹果[19]以及4个基因型牛尾草[20]上都得到了证实。玉米试验表明，缺氮情况下其叶片氮浓度与SPAD值通常呈线性关系[23-24]。玉米生长期间8月份穗位叶叶片SPAD值分别与单位质量氮浓度和单位面积氮浓度均表现出较强的线性关系，决定系数分别为0.84和0.92[23]；两年试验表明，7月和8月两次取样的叶片氮浓度和SPAD值二者的线性回归系数是不同的，并且发现，利用多元回归分析的方法，采用播种后天数得到多元回归关系能够解释二者回归系数84%的变异性[24]。但也有研究表明叶片氮浓度与SPAD值呈非线性关系，例如Dwyer等[7]发现二次方程+线性平台回归方程能反映玉米3个生育期期间叶片氮浓度与SPAD值的响应关系，不同时期的响应方程系数有所不一，但是它们的决定系数都达到了0.88。除二次方程+线性平台关系外，二者还呈现曲线关系[25]，但这种关系因取样时期和年份不同而改变。当玉米叶片氮浓度过高时，它与SPAD值的关系呈渐近线性关系[7,16]，这一结果表明叶绿素计不能用于估算过量氮条件下的玉米和其他作物叶片氮浓度。
综上，SPAD可以用于准确(R2>0.85)预测多种作物叶片的叶绿素和氮浓度。单一回归方程能够预测叶片氮浓度在多种作物上得到了证实；而也有其他研究表明，每个品种或物种需要单独建立回归方程。通常情况下SPAD值与叶绿素或氮浓度的关系是线性的，但也有曲线关系现象的发生。当氮素的供应超过了最高产量需要量时，叶片氮浓度可能无法预测，因为叶片氮浓度持续增加，但SPAD值趋于平稳。
3. 不同作物叶片SPAD值及其氮素管理
3.1 玉米叶片SPAD值及其氮素管理
由于玉米叶片大而宽，易被SPAD-叶绿素计测定。因此，SPAD-叶绿素计在玉米氮素营养诊断和施肥方面的应用研究较多。如Piekielek等研究表明，在玉米6叶阶段(V6)，第5片展开叶SPAD值能够判断是否需要追肥，其判断结果与根据土壤测试的判断结果一致[26]；该阶段玉米叶片的SPAD值预测氮肥反应的正确率达到80%[27]。但也有研究表明玉米V6到V8阶段叶片的SPAD值并不能作为追施氮肥的准确指标[28]。大量研究表明，玉米氮肥与SPAD值的关系均受玉米品种、生育期、生长环境条件的影响[23, 27, 29-33]。虽然Sunderman等[31]利用多年玉米氮肥试验对杂交玉米叶片氮与SPAD值关系的研究最为深入(2年45个玉米杂交品种试验发现，叶片SPAD值在V6和V10生育期阶段品种间有显著差异，在R1和R6阶段品种间没有显著差异)，认为不同区域、不同试验、不同品种玉米叶片氮与SPAD值之间的关系有很多相似之处，但这些关系的适用范围过于宽泛，无法精确估计。
随着研究的进一步深入，科学家提出“相对SPAD值”或者“氮饱和指数”(通过在田间设一高施氮量小区，将不同氮营养水平的作物叶片SPAD 值与高氮区SPAD值相比得到)。利用该值作为氮素营养诊断指标，该指标可不受品种、区域、取样时期的影响[27]，且与植株氮素含量、氮营养指数、产量和最优施氮量的相关性高于绝对SPAD值[34-36]，可有效地指导玉米施肥[27-30, 33, 37-38]。将氮饱和指数等于0.95 (或95%)作为评估作物氮素水平的一个临界值，当氮饱和指数小于0.95时，作物缺氮，需要追施氮肥[39]，否则导致玉米减产[37,40]。美国宾夕法尼亚州的一项研究表明[38]，使用相对SPAD值可以对玉米V6到V8阶段追施氮肥做出最准确的估算，该阶段如果获得平均相对的SPAD值超过0.95，建议不追施氮肥；如果该读数小于或等于0.95，那么需要考虑多方面因素，包括产量潜力、叶片数量、对照区SPAD值以及过去使用的有机肥等，对氮肥施用量做出推荐。赵士诚等[41]也发现在保证相对SPAD值在0.95～0.98范围内的玉米氮肥用量比农民常规氮肥用量减少42%，在产量不降低的情况下，氮肥利用率得到显著提高。
早期研究表明，SPAD值可以预测灌溉施肥(氮肥)时期，但对于准确的施肥量并不确定[22]。研究人员发现随着作物生育期的推进，SPAD对氮素状态判断的准确度也越高[23,30,33,37]，即能依据施肥时期得出确切的施肥量[24,28,29,32,42]。尤其在玉米生长后期，比如在玉米灌浆前期果穗叶的SPAD值能够区分缺氮区和富氮区，这种判别准确度能达到93%[30]。而从乳熟期到蜡熟期相对SPAD值可以将氮响应区从氮非响应区分离，准确率达92%[33]，并且灌浆前期相对SPAD值与氮素响应区的产量密切相关。
就玉米叶片测定位置而言，有学者提出在接近玉米叶片中部的位置，SPAD 值测定结果偏差最小，且在40%～70% 区域内测定值变异系数较低[21]。但SPAD用来指示氮营养状态时也存在其弊端，即当施氮量超出经济最佳产量需求量时，SPAD值并不随着施氮量的增加而增加；因此，当施氮量超出经济最佳产量需氮量时，SPAD值并不是一个很好的指标[30, 43]。
3.2 小麦叶片SPAD值及其氮素管理
研究发现，不同小麦品种同一生育期同位叶片绝对SPAD值最大差异可达10个单位[44]；即使是同一品种不同叶位SPAD值与全氮含量的关系表现也不一致[45]。有研究得出冬小麦叶片SPAD 值与氮素水平随叶位的空间分布特征，顶3 叶与顶2 叶SPAD 值分别与叶片的平均含氮量和氮素累积量相关性最好[46]。但早期也有研究表明，孕穗期SPAD值建立的氮素估算模型最可靠[47]。综上可见，基于绝对SPAD值对作物营养诊断和氮肥管理，因品种、叶位、生育期、年份和区域产生诸多差异和不一致[44-49]。基于此，科学家们也同样引入了“归一化SPAD值”(即“相对SPAD值”和“氮饱和指数”)。研究发现，冬小麦在起身后拔节前叶片归一化SPAD值、氮素吸收量及干物质积累量建立的多元回归方程(R2=0.81)可以作为判定达到最高产量是否需要追施氮肥的依据[17, 50-51]。并且已建立了基于叶片SPAD 值的滴灌春小麦氮肥分期施用推荐模型[52]。
近年来氮营养指数(nitrogen nutrition index，缩写NNI)这一指标被广泛应用于作物氮营养诊断[53]。有研究表明，氮营养指数在作物当季估算产量、氮肥需要量以及氮肥利用效率等方面具有明显潜力[54-59]。因此，氮营养指数与叶片SPAD值以及冠层光谱关系的研究愈来愈多，该方法提供给科学家一种无损、实时和有价值的信息，利用氮营养指数在较大尺度上估算作物氮状况、产量和品质[60-62]。
Debaeke等[63]用小麦顶1叶归一化SPAD 值与NNI 建立关系，以消除环境的影响，结果比较稳定。利用旗叶和倒2叶归一化SPAD值与冬小麦氮营养指数在开花期呈现显著指数关系(R2=0.89)，说明在该生育期可以利用归一化SPAD值代替氮营养指数表征冬小麦氮素营养状况[60]。也有人系统分析了小麦上部4张单叶不同叶位的SPAD值和归一化SPAD指数(NDSPADij)与氮营养指数(NNI)的定量关系，结果表明，小麦单叶SPAD 值与NNI 的关系呈显著正相关，但这种关系在品种或年份之间不稳定，对小麦氮素诊断存在风险；除NDSPAD12外，NDSPADij与NNI 之间呈显著负相关，且NDSPAD14与NNI 之间在年份和品种之间表现最稳定，能够较好地定量估算氮营养指数[64]。也有研究表明，倒2叶与旗叶的SPAD差值能与NNI建立显著对数关系，并且在6个小麦品种上得到验证[65]。Ravier等研究表明，利用归一化SPAD 值能够消除冬小麦生物量、品种和年份间带来的影响，且对NNI预测保持较高的准确度。缺点是不能消除生育期的影响；另外对于施氮条件下的植株缺氮情况，其预测准确度相对较低[66]。
综上所述，利用归一化SPAD开展冬小麦氮素营养诊断是目前较为认可的方法，并且与氮营养指数建立了较为稳定的关系模型；但在具体利用叶片的位置上存在研究差异，还需要进一步深入探讨。
3.3 水稻叶片SPAD值及其氮素管理
科学家们业已证实水稻产量与关键生育期的叶片SPAD值或者氮浓度存在显著相关关系[67-72]。较为引人注意的研究是，叶片SPAD值与不同方法表示的氮含量之间的关系。结果表明，单位叶面积表示的氮含量(N g/m2)优于单位叶重量表示的氮含量(N g/kg)与SPAD值的相关性[73-75]。同时发现如果水稻叶片含氮量以叶面积为基础来表示，利用SPAD/SLW (特定叶片重量)对SPAD值进行校正，则可消除叶片厚度或质量对SPAD读数的影响[68,73]。但是也有研究发现这两种表示方法得到的叶片氮浓度与SPAD值的线性相关系数差异不显著[76]。
SPAD虽然可以便捷、无损地诊断水稻氮素营养状况，但其估测精确度受水稻品种、生长时期、测定叶位和生长环境等因素的影响[77-79]。叶位是作物研究中最容易精准定位的目标之一，因此科学家们测定不同叶位SPAD，主要集中在顶部四片叶，将其差值或比值作为诊断指标[80]。研究发现，水稻上叶片SPAD 值对氮素的敏感性顺序为顶4 叶、顶3 叶和顶2 叶，而顶1 叶的敏感性排序因品种不同而不同；穗分化期、齐穗期和成熟期均以顶3 叶与总叶片及植株含氮量相关系数最高；且适宜氮素水平下，穗分化期顶3 叶SPAD 值的变异系数最小。以某一特定叶片的SPAD 值或以叶色差的大小来诊断水稻氮素营养状况和推荐水稻穗肥施用时，顶3 叶是较为理想的指示叶或参照叶[81]。有研究认为顶4叶与顶3叶间的SPAD差值诊断氮素营养状况时，该指标不受施肥条件和生长时期的影响[79,82-83]。但也有人发现不同生育期应选择不同叶片作为氮素诊断的理想指示叶[75]。
同样，研究人员为消除品种、生育期及管理措施的影响，发展了归一化SPAD指数、均值SPAD指数和差值SPAD指数等。利用标准化的SPAD值对最高产量推荐施氮量比预设施氮量减少N 30～40 kg/hm2[84]。筛选出水稻第4片完全展开叶的NSI4 (归一化SPAD指数)为参数，建立了水稻拔节期至孕穗期的植株氮累积量和氮营养指数诊断模型[85]。也有人指出分蘖成穗期顶叶SPAD值[86]、顶三叶SPAD均值[87]是反映水稻氮素水平的最佳测量指标；同时分蘖成穗期顶叶SPAD值与产量关系密切[86]。
虽然科研人员在关于不同形式SPAD指标与氮营养的关系方面做了大量研究，但利用这种关系建立的模型来指导施肥尤其在氮素追肥方面还不成熟。有研究发现，水稻幼穗分化前后10天，叶片SPAD值可以用来判定是否需要追施氮肥。当读数超过40，追施氮肥对产量没有贡献[67,88]。这就启示研究人员需要对SPAD阈值有一个定义，用作追施氮肥的依据和前提[89]。利用水稻叶片SPAD阈值变化实时变量施肥得到了较好效果，例如当叶片SPAD值为35时，水稻需要补充氮肥[73, 90]。又有当叶片SPAD值为36时，需要追肥N 35～25 kg/hm2，与常规追肥相比，能节省肥料20%～35%，且维持产量不减，从而提高氮肥利用率[91]。
3.4 SPAD在其他作物氮素管理上的研究
利用SPAD-502估算氮素营养状态在棉花、黄瓜、油菜等作物上也开展了尝试研究。早在1992年就有发现，棉花叶片氮浓度与SPAD值呈曲线关系，但这种关系因生育期和年份不同而改变[92]。通过研究棉花主茎顶部4片叶SPAD值对氮素营养水平的敏感程度发现，倒4叶相对稳定，用于氮素营养诊断较为理想[93-95]。进一步研究发现倒1叶和倒4叶构建的叶位差指数(PDI)诊断棉花氮素营养状况最为可靠，不受生育期和土壤养分状况影响[96]。另外研究发现，叶片的观测位点对SPAD值的稳定性及其与氮含量的相关性至关重要，认为靠近棉花功能叶叶缘的位点适宜作为测试区域[97]。
黄瓜的试验证明幼苗期和开花期的第3叶、结果期的第7 叶对氮素响应最敏感，可作为黄瓜氮素缺乏诊断的最佳部位[98]。胡静等[99]利用叶绿素计探讨了黄瓜叶片上SPAD 值的空间分布及氮素诊断的位点选择，结果表明叶片各位点的SPAD 值与叶片含氮量均存在显著的相关关系。选择离叶尖部相对距离20% 与叶边缘之间的叶尖顶三角区域作为黄瓜氮素诊断的最佳位点。还有研究得出黄瓜氮营养指数和产量与SPAD的关系随着生育期的推移逐渐加强，能够预测其最大生长量和产量的SPAD值为45.2±0.7[100]。
李岚涛等[101]研究了应用SPAD值诊断油菜氮素营养状况的最佳测试叶位及位点，发现主茎顶4片完全展开叶中部SPAD值与叶绿素含量、叶片氮含量和植株全氮含量之间相关性显著，满足氮素快速诊断的要求。
4. 问题和建议
通过上述大量资料表明，叶绿素计与作物氮素营养及产量方面的关系研究较多，但是利用其在田间开展氮素施肥的实践还相对较少，或者结果不令人满意。究其原因，作者认为主要有以下几点：其一，没有建立基于SPAD的作物营养诊断和推荐施肥技术规范，包括，1)不同作物间的测试技术规范；2)不同作物间的氮素丰缺指标、施肥体系等。正如前文所述，不同作物(或物种)间差异较大；不同叶位的SPAD值因生育期不同而变化很大；同一叶片测定位点的选择，叶尖、叶中、叶柄的SPAD值与植株氮含量的相关性均存在差异。其二，SPAD值及其衍生量的筛选。比如，相对SPAD值或归一化SPAD值都是为数据稳定性和可比性而衍生出来的。其三，模型的稳定性和普适性。其四，与叶绿素合成有关的其他营养元素(钾、镁、铁、锰等)的缺乏或者元素间交互作用与SPAD的响应关系。
众所周知，利用叶绿素计对作物氮含量的估算或者诊断是第一步，如何根据SPAD对氮含量的估算和诊断进行氮肥精准管理是研究者的最终目的。因此，针对以上存在问题，研究要对测量目标精准定位，明确不同作物不同生育期选取的叶片层位；同时筛选适宜的SPAD值或其衍生参数，建立稳定估算模型；并且需要大量的、多年的、多个品种间的数据来支撑，否则数据的精度和可靠性无法保证。笔者认为，利用叶绿素计开展氮素营养诊断还需解决的问题主要有以下几方面：1)基于SPAD的不同作物氮素营养诊断的技术规范。包括不同作物不同生育期测定叶位的精准定位以及叶片的测定位点等。2)确定基于叶片SPAD值作物氮营养丰缺指标。3)建立基于叶片SPAD值的作物施肥模型。4)开发基于SPAD的施肥决策支持系统。5)开展钾、镁、铁、锰等与叶绿素合成有关的其他营养元素与SPAD值的关系研究，扩充和丰富基于SPAD的作物营养诊断技术和方法。
需要指出的是，田间养分精准管理是极具技术性和经验性相结合的复杂工程，不同营养元素的植物有效性受土壤类型、pH、温度、降雨、微生物种类等多种因素的影响，即使实验室土壤植株养分的准确测定也只能在4R (right source, right rate, right time, right place)之一施肥量(right rate)的确定给予建议，在施肥时间(right time)和施肥位置(right place)上不能指导田间施肥。SPAD是科技进步的产物，它在研究逐步成熟和正确应用条件下，能够判断作物营养元素尤其氮素的丰缺，为作物生长发育中期追肥提供实时决策，较实验室的化验分析效率提高数十倍，可以说为实现正确施肥时间(right time)提供一种较好的技术手段。所以田间养分精准管理需要多技术、多方法、多手段相结合才能实现理想的养分精准管理。但正如前文所说，SPAD的成熟应用和发展还需要多年、多点、多试验的数据验证和完善。
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