• ISSN 1008-505X
  • CN 11-3996/S
徐慧敏, 蔡明蕾, 李秧秧. 玉米叶片经济和水力性状及其关联性对氮肥和水分的响应[J]. 植物营养与肥料学报, 2020, 26(2): 223-232. DOI: 10.11674/zwyf.19105
引用本文: 徐慧敏, 蔡明蕾, 李秧秧. 玉米叶片经济和水力性状及其关联性对氮肥和水分的响应[J]. 植物营养与肥料学报, 2020, 26(2): 223-232. DOI: 10.11674/zwyf.19105
XU Hui-min, CAI Ming-lei, LI Yang-yang. Leaf economic and hydraulic traits and their correlation under varying nitrogen and water supplies in maize[J]. Journal of Plant Nutrition and Fertilizers, 2020, 26(2): 223-232. DOI: 10.11674/zwyf.19105
Citation: XU Hui-min, CAI Ming-lei, LI Yang-yang. Leaf economic and hydraulic traits and their correlation under varying nitrogen and water supplies in maize[J]. Journal of Plant Nutrition and Fertilizers, 2020, 26(2): 223-232. DOI: 10.11674/zwyf.19105

玉米叶片经济和水力性状及其关联性对氮肥和水分的响应

Leaf economic and hydraulic traits and their correlation under varying nitrogen and water supplies in maize

  • 摘要:
    目的 研究叶片经济性状和水力性状的变异性及权衡策略是揭示植物适应环境变化机制和水碳模拟的基础。分析不同氮(N)肥和水分供给下玉米叶片经济性状和水力性状的变异性及相关性,及这些叶片性状与整株植物行为间的关系,以揭示同一物种内不同氮、水有效性下叶片经济性状和叶水力性状间的关系,并探讨叶片性状预测整株生物量和水分利用特征的可能性。
    方法 采用二因素三水平的盆栽试验,其中氮肥水平包括不施氮肥 (N0)、播种前施N 0.2 g/kg干土 (N1)、播种前和五叶期各施N 0.2 g/kg干土 (N2);水分供应水平包括充分灌水 (W2)、中度水分胁迫 (W1) 和重度水分胁迫 (W0),土壤含水量分别维持在田间持水量的75%~80%、50%~55%和30%~35%约3周,共9个处理。主要测定项目包括叶经济性状 比叶质量(LMA)、叶厚度(LT)、组织密度(TD)、质量基础上的氮含量(Nmass)和面积基础上的氮含量Narea 及水力性状 叶脉密度(VD)、气孔密度(SD)、气孔长度(SL)和最大气孔导度(gwmax)。
    结果 施氮显著增加了LMA、Nmass、Narea、VD、SD、SL和gwmax (P < 0.05),灌水显著提高了LMA、TD和Narea (P < 0.05);在3种氮水平下,W2处理的LMA和TD均较W0处理增加;在N0和N1下,W2处理的SD和gwmax亦较W0处理增加,但在N2下,W2处理的SD和gwmax则低于W0处理,氮、水间的交互作用对LMA、TD、SD和gwmax的影响达到显著水平 (P < 0.05)。不同氮、水条件下叶经济性状和水力性状间是紧密耦联的,表现在Nmass和SD、gwmax之间、Nareagwmax之间呈显著正相关 (P < 0.05)。影响生物量的主要叶性状为Narea、Nmass和VD,影响耗水量的主要为Narea、Nmassgwmax和LT;影响水分利用效率的主要为Nmass、LMA、LT和VD。
    结论 玉米叶片氮含量与气孔密度、最大气孔导度间存在高度协调性,这种协调性增加了玉米对不同资源有效性的适应性;利用叶片性状可预测不同氮、水供给下玉米的生物量和水分利用特征。

     

    Abstract:
    Objectives The variation and tradeoff of leaf economic and hydraulic traits are the strategy of plant adapting to environment, which is the base of constructing water-carbon modeling. The variation and correlation between leaf economic and hydraulic traits as well as their association with plant performance under different N and water supplies in maize were studied, aiming to elucidate the relationship between leaf economic and hydraulic traits in response to different nutrient and water availabilities at the intraspecific level, and evaluate the possibility of using these leaf traits to predict whole plant biomass and water use.
    Methods A pot experiment with completely randomized two-factor-three level design was conducted. The three levels of urea application were no N (N0), N 0.2 g/kg dry soil before planting (N1), and N 0.2 g/kg dry soil before planting and during 5-leaf stage (0.4 g N in total, N2); the three watering levels were adequate irrigation (W2), moderate water stress (W1) and severe water stress (W0), the corresponding soil moisture in W2, W1 and W0 treatments was 75%–80%, 50%–55% and 30%–35% of field capacity, and lasted about 3 weeks. The measured leaf economic traits involved leaf mass per area (LMA), leaf thickness (LT), tissue density (TD), mass-based N content (Nmass) and area-based N content (Narea); the measured hydraulic traits included vein density (VD), stomatal density (SD), stomatal length (SL) and maximum stomatal conductance to water (gwmax).
    Results N fertilizer significantly increased LMA, Nmass, Narea, VD, SD, SL and gwmax (P < 0.05), and irrigation significantly increased LMA, TD and Narea (P < 0.05). LMA and TD were larger under W2 than under W0 in all the three N levels, but SD and gwmax were larger in W2 than W0 treatment only under N0 and N1 levels, and lower in W2 than W0 treatment under N2 level, the interactions of nitrogen and water on LMA, TD, SD and gwmax were significant (P < 0.05). Leaf economic traits were closely coupled with hydraulic traits, in details, Nmass were positively correlated with SD and gwmax, Narea was positively correlated with gwmax (P < 0.05). The major leaf traits affecting biomass were Narea, Nmass and VD, those affecting water consumptions were Narea, Nmass, gwmax and LT, those affecting water use efficiency were Nmass, LMA, LT and VD.
    Conclusions Leaf N content is closely coordinated with stomatal density and the maximum stomatal conductance to water. This coordination may enhance the adaptation of plants to different resource availabilities. Leaf traits can be used to predict whole plant performance under different N and water supplies in maize.

     

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