中国农业科学 ›› 2016, Vol. 49 ›› Issue (1): 69-79.doi: 10.3864/j.issn.0578-1752.2016.01.006

• 耕作栽培·生理生化·农业信息技术 • 上一篇    下一篇

玉米茎秆的支撑功能及其可塑性

杨锦忠1,梁淑敏2,李娜娜3,刘永花4,郝建平4

 
  

  1. 1青岛农业大学,山东青岛 266109
    2云南省农业科学院,昆明 650205
    3山西省农业科学院,太原 030031
    4山西农业大学,山西太谷 030801
  • 收稿日期:2015-05-04 出版日期:2016-01-01 发布日期:2016-01-01
  • 通讯作者: 杨锦忠,Tel:0532-8830340;E-mail:jzyang@qdau.edu.cn
  • 作者简介:杨锦忠,Tel:0532-8830340;E-mail:jzyang@qdau.edu.cn
  • 基金资助:
    国家自然科学基金(31271658)、国家科技支撑计划(2011BAD09B01-2)、山东省高校优秀科研创新团队(20121025)

Functional Traits of Maize Stems as Supporting Organs and Their Plasticity

YANG Jin-zhong1, LIANG Shu-min2, LI Na-na3, LIU Yong-hua4, HAO Jian-ping4   

  1. 1Qingdao Agricultural University, Qingdao 266109, Shandong
    2Yunnan Academy of Agricultural Sciences, Kunming 650205
    3Shanxi Academy of Agricultural Sciences, Taiyuan 030031
    4Shanxi Agricultural University, Taigu 030801, Shanxi
  • Received:2015-05-04 Online:2016-01-01 Published:2016-01-01

摘要: 【目的】从植物茎支持功能相关性状出发,阐明其在各种生态因子作用下的可塑性变化及生态适应意义。【方法】定义玉米茎的3个支撑功能性状:(1)线密度=节间重量/节间长度;(2)承重自重比=节间承重/节间重量,其中,承重=节间上方全部组织与器官的重量(不包括该节间自重);(3)承重线密度比=节间承重/节间线密度。可塑性用塑性系数表示,此系数值仿照变异系数的公式进行计算,其中方差组分根据数据的期望均方模型估算。共包括6个田间试验,处理组成分别为:5个地点×2个品种组合、11个采样期×2个品种组合、4个种植密度(3.0—9.75株/m2)×3个采样期组合、4个种植密度(2.4—6.0 株/m2)、3种施氮量×2个追肥期组合、高密无肥对比低密有肥。采用方差分析检验处理间差异,采用LSD比较处理均值,采用负对数模型拟合茎线密度依节位的垂直分布。【结果】节间线密度变幅为0.052—0.72 g DW·cm-1,其垂直分布符合负对数方程:线密度=a-b×log(节位);承重自重比变幅为7—51,承重线密度比变幅为122—260 cm,计入雌穗重量后以上两个数值比的最大值出现在穗下第一节间,分别为246和3 425 cm。茎功能性状在品种间、地点间差异明显,在灌浆中后期线密度呈下降趋势;随种植密度增加,节间线密度持续下降,而承重自重比在较大密度范围内基本保持不变;加大施氮量提高了线密度,但是却不影响承重线密度比。茎性状的可塑性表现为:线密度>承重自重比>承重线密度比,干物质在茎上各节间的承重投入受最优化策略控制。【结论】以上3个茎支撑功能性状反映了植物的承重特征,从一个新的角度刻划了干物质投入及其投资效率,有助于深入认识植物的干物质分配现象。

关键词: 玉米, 茎, 支撑功能性状, 性状可塑性, 基因型, 地点与农艺措施, 线密度, 承重自重比, 承重线密度比

Abstract: 【Objective】Plant stems function as supporting organs among many other functions, however, information on their load-bearing capacity has seldom been reported. The objectivs of this study were to: (1) define some stem functional traits; (2) examine effects of abiotic and biotic factors on these traits; (3) feature plasticities of these traits; and (4) explore their potential implications. 【Method】Three stem functional traits, namely, linear mass density (MD), ratio of load to self-weight (RLSW), and ratio of load to linear density (RLMD), were proposed and examined in 6 field experiments with maize (Zea Mays) as a model plant. MD = internode weight / its length, RLSW = internode mass load / its weight, RLMD = internode mass load / MD, where the mass load of an internode is the sum of the weights of all organs and tissues above the internode. The plasticity of a trait was represented as plasticity coefficients, which were computed after the manner of variation coefficients, and where variance components were estimated from the component models of expected mean squares for the experiment’s data. The 6 field experiments were conducted in Taigu, Shanxi. The treatments of these experiments are as follows: (1) the combinations of 5 sites by 2 cultivars; (2) the combinations of 11 sampling timings by 2 cultivars; (3) the combinations of 4 plant densities by 3 sampling timings; (4) 4 plant densities from 2.4 to 6.0 plants per square meter; (5) the combinations of 3 nitrogen fertilizer rates by 2 fertilization timings; and (6) high plant density without fertilization versus low plant density with fertilization. All 3 traits were subject to ANOVA, and means were separated by means of Least Significant Difference. The profile of MD along node ranks was fitted with a negative logarithm equation. 【Result】MDs of internodes varied from 0.052 to 0.72 g DW·cm-1 and followed a straight line equation of a negative logarithm of node ranks. RLSWs of internodes ranged from 7 to 51, and RLMDs of internodes from 122 to 260 cm. If including load of ear weights, these ratios for the first node below the ear jumped to 246 and 3225 cm at their maximum values, respectively. These 3 stem functional traits showed statistically significant differences among genotypes and geographical sites. In the late duration of the kernel filling stage, MDs generally went down. MDs decreased with plant density, but RLSWs remained stable within a large range of plant densities. Higher nitrogen fertilizer rates increased MDs, but did not affect RLMDs, compared with lower ones. The plasticity of stem functional traits ranked as: MD>RLSW>RLMD, and the biomass investments for supporting were modulated by the optimization strategy. 【Conclusion】These findings showed that the stem functional traits proposed were able to feature the load-bearing of stems, and could delineate the biomass investments in the stem structure of plants and the investment efficiency, and may improve the understanding of biomass partitioning within whole plants.

Key words: Zea mays, stems, functional traits, trait plasticity, genotype, sites and agronomic measures, linear mass density, ratio of load to self-weight, ratio of load to linear density