Leaf area (LA) is a valuable parameter in many agronomic and plant physiological studies. Its measurement is time consuming and involves leaf destruction. Therefore, there is a tendency in using simple, fast, non-destructive, and electronic devices methods to estimate LA. The aim of this study was to estimate LA across different water regime treatments using a combination of leaf mass and leaf dimensions of sunflower (Helianthus annuus L.). For this purpose, different leaf sizes were collected from plants during the growing season on different time intervals. Experiment was conducted during 2012 summer time in Sari Agriculture Sciences and Natural Resources University, Iran. On field leaf dimension measurements were carried out, and leaves sketches were put on paper, scanned and then areas were measured using AutoCAD software. Multivariate linear and non-linear regression models were constructed between LA and other leaf components measured. All constructed models provided highly significant correlations (r = 0.90–0.99) between LA and different leaf components. The exponential model [LA = 0.619 [(L × W)0.5]2.019] provided the best estimation of sunflower LA (R2 = 0.993). In conclusion, the simple and quick models developed in this study could predict the sunflower LA and leaf area index (LAI) with high precision.
