Measurement of leaf area is commonly used in many horticultural research experiments, but it is generally destructive, requiring leaves to be removed for measurement. Determining the individual leaf area (LA) of bedding plants like pot marigold (Calendula officinalis L.), dahlia (Dahlia pinnata), sweet William (Dianthus barbatus L.), geranium (Pelargonium × hortorum), petunia (Petunia × hybrida), and pansy (Viola wittrockiana) involves measurements of leaf parameters such as length (L) and width (W) or some combinations of these parameters. Two experiments were carried out during spring 2010 (on two pot marigold, four dahlia, three sweet William, four geranium, three petunia, and three pansy cultivars) and summer 2010 (on one cultivar per species) under greenhouse conditions to test whether a model could be developed to estimate LA of bedding plants across cultivars. Regression analysis of LA versus L and W revealed several models that could be used for estimating the area of individual bedding plants leaves. A linear model having LW as the independent variable provided the most accurate estimate (highest R2, smallest mean square error, and the smallest predicted residual error sum of squares) of LA in all bedding plants. Validation of the model having LW of leaves measured in the summer 2010 experiment coming from other cultivars of bedding plants showed that the correlation between calculated and measured bedding plants leaf areas was very high. Therefore, these allometric models could be considered simple and useful tools in many experimental comparisons without the use of any expensive instruments. and F. Giuffrida ... [et al.].
Accurate and nondestructive methods to determine individual leaf areas of plants are a useful tool in physiological and agronomic research. Determining the individual leaf area (LA) of rose (Rosa hybrida L.) involves measurements of leaf parameters such as length (L) and width (W), or some combinations of these parameters. Two-year investigation was carried out during 2007 (on thirteen cultivars) and 2008 (on one cultivar) under greenhouse conditions, respectively, to test whether a model could be developed to estimate LA of rose across cultivars. Regression analysis of LA vs. L and W revealed several models that could be used for estimating the area of individual rose leaves. A linear model having L×W as the independent variable provided the most accurate estimate (highest r2, smallest MSE, and the smallest PRESS) of LA in rose. Validation of the model having L×W of leaves measured in the 2008 experiment coming from other cultivars of rose showed that the correlation between calculated and measured rose LA was very high. Therefore, this model can estimate accurately and in large quantities the LA of rose plants in many experimental comparisons without the use of any expensive instruments. and Y. Rouphael ... [et al.].
The aim of the present experiment was to evaluate the currently used allometric models for Vitis vinifera L., as well as to develop a simple and accurate model using linear measurements [leaf length (L.) and leaf width (W)] for estimating the individual leaf area (LA) of nine grapevine genotypes. For model construction, a total of 1,630 leaves coming from eight genotypes in 2010 was sampled during different leaf developmental stages and encompassed the full spectrum of leaf sizes. The model with single measurement of L could be considered an interesting option because it requires measurement of only one variable, but at the expense of accuracy. To find a model to estimate individual LA accurately for grapevine plants of all genotypes, both measurements of L and W should be involved. The proposed linear model [LA = 0,465 + 0,914 (L x W)] was adopted for its accuracy: the highest coefficient of determination (>0,98), the smallest mean square error, the smallest prediction sum of squares, and the reasonable close prediction sum of squares value to error sum of squares. To validate the LW model, an independent data set of 200 leaves coming from another genotype in 2011 was used. Correlation coefficients showed that there was a highly reliable relationships between predicted leaf area and the observed leaf area, giving an overestimation of 0.8% in the prediction. and Obsahuje seznam literatury