Simple models for non-destructive leaf area predictionin fig (Ficus carica L.) cv. Deanna and Poona
Keywords:
leaf area, non-destructive, regression analysis, modelsAbstract
The edible fig (Ficus carica L.) has emerged as an important fruit in the world of commerce. Leaf area is an important parameter in fig research, especially for plant physiological studies. Most of the available methods for calculating plant leaf area are difficult to apply, expensive and destructive, which destroy the canopy, as a result of which it becomes difficult to perform further tests on the same plant. Therefore, an experiment was conducted to develop the statistical models for cv. Deanna and Poona of fig using regression analysis during 2010-11 for non-destructive estimation of leaf area. For this purpose the leaf area was recorded with the help of leaf area meter for 100 randomly selected leaves each for Deanna and Poona fig and leaf parameters were recorded for the same hundred leaves. Later, models for computing leaf area in non destructive manner for cv. Deanna and Poona were developed separately by performing the regression analysis with regard to the relationship between leaf area and petiole length, left lobe (V2), middle lobe (V1) and right (V3) lobe. The statistical models for Deanna and Poona respectively were,
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