b T; A S; H S
Abstract
Background and Objectives Accurate measurements of leaf area are important for agronomic and physiological studies. Leaf area can be calculated in two ways: direct and indirect. Direct ...
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Background and Objectives Accurate measurements of leaf area are important for agronomic and physiological studies. Leaf area can be calculated in two ways: direct and indirect. Direct methods for determining leaf area are a destructive method and need a planimeter to measure the total leaf area attached to shoots which are all time-consuming and tedious approaches. All direct methods are similar in that they are difficult, extremely labor-intensive, require many replicates to account for spatial variability in the canopy, and are therefore costly in terms of time and money and also destructive. In the indirect methods, leaf area was estimated through some crop vegetative characteristics which are less costly and time-consuming. Therefore, the objective of the present study is to examine different relationships between leaf area and some vegetative characteristics in safflower and to select the best characteristic for estimating leaf area. Materials and Methods The field experiment was conducted with four safflower cultivars (411, Sina, Esfahan and Sofeh) in three planting dates (4April, 25 April and 16 May 2012) as arrangement factorial in randomized complete blocks design. During the growing season, every 5 or 10 days, the leaf area was measured by the planimeter (T Devices, Cambridge, UK). At the same time, leaf dry weight (LDW), stem dry weight (SDW), vegetative dry weight (VDW), node number on main stem (MSNN) and leaf number on main stem (MSLN) were measured. The relationships between leaf area and these vegetative characteristics were examined by the regression. Consequently, the best characteristic for estimating leaf area was selected by the high R2, r and low RMSD. Results In this study, regression models were developed for estimating leaf area (LA) from measurements of main stem leaf number (MSLN), and main stem node number (MSNN), leaf dry weight (LDW), stem dry weight (LDW) and vegetative dry weight (VDW). On the basis of RMSD and coefficient correlation (r) between predicted and observed leaf area, LDW was found to be the best independent characteristic for determining the leaf area by the linear model. The values of RMSD varied from 39.9 to 61.4 and the values of r were higher than 0.96. Once there was no significant difference between model coefficients across cultivars we pooled all data and obtained a generalized linear model for estimating LA in all cultivars (LA=10.6+102.2LDW) with RMSD=52 and r=0.96. Discussions Overall, this study suggests that in the absence of planimeter device, it may be appropriate to estimate leaf area using the relationship between LA and LDW. Also, because of the close relationship between LDW and LA than other relationships, this relationship can be used to estimate leaf area in simulation models.
