Leaf Area Estimation Model for Small Fruits from Linear Measurements

Abstract

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 small fruit like raspberry (Rubus idaeus L.), redcurrant (Ribes rubrum L.), blackberry (Rubus fruticosus L.), gooseberry (Ribes grossularia L.), and highbush blueberry (Vaccinium corymbosum L.) involves measurements of leaf parameters such as length (L) and width (W) or some combinations of these parameters. A 2-year investigation was carried out during 2006 (on seven raspberry, seven redcurrant, six blackberry, five gooseberry, and two highbush blueberry cultivars) and 2007 (on one cultivar per species) under open field conditions to test whether a model could be developed to estimate LA of small fruits across cultivars. Regression analysis of LA versus L and W revealed several models that could be used for estimating the area of individual small fruit leaves. A linear model having LW as the independent variable provided the most accurate estimate (highest R 2, smallest mean square error, and the smallest predicted residual error sum of squares) of LA in all small fruit berries. Validation of the model having LW of leaves measured in the 2007 experiment coming from other cultivars of small fruit berries showed that the correlation between calculated and measured small fruit berries LAs was very high. Therefore, these models can estimate accurately and in large quantities the LA of small fruit plants in many experimental comparisons without the use of any expensive instruments.