Leaf Area Calculation Models for Vines Based on Foliar Descriptors.

Area of Science:

• Viticulture
• Plant Physiology
• Agricultural Engineering

Background:

• Accurate foliar area determination is crucial for vine studies.
• Existing methods can be time-consuming and costly for large sample sizes.
• Vine leaf morphology presents complexity in measurement.

Purpose of the Study:

• To evaluate models for calculating vine leaf area using descriptive parameters.
• To determine the surface constant (KA) for six distinct grape cultivars.
• To establish a fast, accurate, and cost-effective method for foliar area analysis.

Main Methods:

• Regression analysis was used to develop leaf area prediction models.
• Descriptive leaf parameters (e.g., venation, sinuses, length, width) were utilized.
• Surface constants (KA) were determined for 'Cabernet Sauvignon', 'Muscat Iantarnîi', 'Muscat Ottonel', 'Chasselas', 'Victoria', and 'Muscat Hamburg'.

Main Results:

• Leaf area prediction models achieved high statistical accuracy (R² up to 0.988).
• Surface constants (KA) were generally subunitary (0.91-0.97), with exceptions for 'Muscat Iantarnîi' and 'Muscat Ottonel' (KA₂ > 1).
• Models utilizing left-side leaf elements relative to the median rib showed more reliable predictions.

Conclusions:

• Developed models offer a reliable and efficient method for estimating vine leaf area.
• The approach is adaptable across different grape cultivars.
• This method simplifies foliar area studies, enabling more extensive research.