Convenient and effective methods to determine seasonal changes in individual leaf area (LA) and leaf mass (LM) of plants are useful in research on plant physiology and forest ecology. However, practical methods for es...Convenient and effective methods to determine seasonal changes in individual leaf area (LA) and leaf mass (LM) of plants are useful in research on plant physiology and forest ecology. However, practical methods for estimating LA and LM of elm (Ulmus japonica) leaves in different periods have rarely been reported. We collected sample elm leaves in June, July and September. Then, we developed allometric models relating LA, LM and leaf parameters, such as leaf length (L) and width (W) or the product of L and W (LW). Our objective was to find optimal allometric models for conveniently and effectively estimating LA and LM of elm leaves in different periods. LA and LM were significantly correlated with leaf parameters (P < 0.05), and allometric models with LW as an independent variable were best for estimating LA and LM in each period. A linear model was separately developed to predict LA of elm leaves in June, July and September, and it yielded high accuracies of 93, 96 and 96%, respectively. Similarly, a specific allometric model for predicting LM was developed separately in three periods, and the optimal model form in both June and July was a power model, but the linear model was optimal for September. The accuracies of the allometric models in predicting LM were 88, 83 and 84% for June, July and September, respectively. The error caused by ignoring seasonal variation of allometric models in predicting LA and LM in the three periods were 1-4 and 16-59%, respectively.展开更多
介绍一种基于Photoshop CS5和Image-Pro Plus 6.0软件处理数字图像辅助测量杉木球果长、宽的新方法,分别用游标卡尺法和软件法测量了150个杉木球果的长、宽.相关性分析表明,两种测量方法间呈显著的线性相关,两种方法测得的杉木球果长的...介绍一种基于Photoshop CS5和Image-Pro Plus 6.0软件处理数字图像辅助测量杉木球果长、宽的新方法,分别用游标卡尺法和软件法测量了150个杉木球果的长、宽.相关性分析表明,两种测量方法间呈显著的线性相关,两种方法测得的杉木球果长的相关系数R2=0.900 7,宽的相关系数R2=0.903 8.与游标卡尺法相比,本文所介绍的软件法更方便快速,可用于杉木球果长、宽的实际测量工作,在林业生产等领域具有很强的应用性、实用性和推广性.展开更多
基金financially supported by the National Natural Science Foundation of China(No.31600587)
文摘Convenient and effective methods to determine seasonal changes in individual leaf area (LA) and leaf mass (LM) of plants are useful in research on plant physiology and forest ecology. However, practical methods for estimating LA and LM of elm (Ulmus japonica) leaves in different periods have rarely been reported. We collected sample elm leaves in June, July and September. Then, we developed allometric models relating LA, LM and leaf parameters, such as leaf length (L) and width (W) or the product of L and W (LW). Our objective was to find optimal allometric models for conveniently and effectively estimating LA and LM of elm leaves in different periods. LA and LM were significantly correlated with leaf parameters (P < 0.05), and allometric models with LW as an independent variable were best for estimating LA and LM in each period. A linear model was separately developed to predict LA of elm leaves in June, July and September, and it yielded high accuracies of 93, 96 and 96%, respectively. Similarly, a specific allometric model for predicting LM was developed separately in three periods, and the optimal model form in both June and July was a power model, but the linear model was optimal for September. The accuracies of the allometric models in predicting LM were 88, 83 and 84% for June, July and September, respectively. The error caused by ignoring seasonal variation of allometric models in predicting LA and LM in the three periods were 1-4 and 16-59%, respectively.
