高产小麦几个性状的相关性研究  被引量:4

Correlation analysis on selected traits of high-yield wheat

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作  者:慕晓茜[1] 慕美财[2] 刘新程[2] 

机构地区:[1]北京交通大学理学院,北京100044 [2]中国农业大学(烟台),烟台264670

出  处:《中国生态农业学报》2010年第4期787-791,共5页Chinese Journal of Eco-Agriculture

基  金:中国粮食与食物安全研究中心资助项目

摘  要:为了解高产小麦在"稳叶控株增穗"栽培途径下产量及有关性状间的相关关系,寻找该途径的优势及产量进一步提高的限制因素,本文用SPSS软件对47块采用该途径、单产在7243~10610kg·hm-2范围内麦田的产量、单位面积穗数、穗粒数、粒重、籽粒最大容积、穗颈维管束数、群体维管束数7个性状进行了性状相关性分析。研究表明,产量三因素中只有粒重与产量呈显著正相关关系,说明粒重是影响"稳叶控株增穗"途径产量提高的主要因素,且粒重与籽粒最大容积呈极显著正相关关系,认为采取一定措施来增大籽粒最大容积将是提高粒重,进而提高产量的有效途径。群体维管束总数与单位面积穗数呈极显著正相关关系,表明增加单位面积穗数可达到畅流的目的。研究还对粒重与籽粒最大容积进行曲线拟合,拟合方程为y=12.925+0.479x,对群体维管束数与穗数之间进行曲线拟合,拟合方程为y=-14.231+2.685lnx。Correlation analysis was conducted among selected traits and yield of wheat from 47 fields with yield range of 7 243~ 10 610 kg·hm^-2 under stabilizing leaf-controlling plant type-increasing ear number (CPCE) management conditions using SPSS. The research task of this study was to determine the enabling and limiting factors of CPCE. Selected traits analyzed in this study include ear number per-unit-area, grain number per ear, grain weight, maximum grain volume, vascular bundle number per panicle and total vascular bundle number. Among three yield components (ear number per-unit-area, grain number per ear and grain weight), only grain weight is positively correlated with yield, suggesting that grain weight is the main determinant of yield under CPCE management. Positive correlation is also noted between grain weight and maximum grain volume. This implies that management measures to increase maximum grain volume can enhance grain yield. The positive correlation between ear number per-unit-area and total vascular bundle number suggests that high ear number per-unit-area ensures smooth flowing. Based on curve fitting, the regression equations for grain weight and maximum grain volume, and also for ear number per-unit-area and total vascular bundle number are respectively given as y = 12.925+0.479x and y =-14.231+2.685lnx.

关 键 词:高产小麦 稳叶控株增穗 产量因素 穗颈维管束 籽粒容积 性状相关性分析 曲线拟合 SPSS软件 

分 类 号:S512.11[农业科学—作物学]

 

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