Interactions Between Leaf Area Dynamics and Vineyard Performance, Environment, and Viticultural Practices

Yishai Netzer () and Noa Ohana-Levi
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Yishai Netzer: Department of Chemical Engineering, Ariel University, Ariel 4070000, Israel
Noa Ohana-Levi: Independent Researcher, Variability, Kfar Vradim 2514700, Israel

Agriculture, 2025, vol. 15, issue 6, 1-22

Abstract: The Leaf Area Index (LAI) is a key physiological metric in viticulture, associated with vine health, yield, and responsiveness to environmental and management factors. This study, conducted in a Mediterranean Sauvignon Blanc vineyard (2017–2023), examines how irrigation and environmental variables affect LAI across phenological stages, and their impact on yield (clusters per vine, cluster weight, total yield) and pruning parameters (cane weight, pruning weight). Results show that irrigation is the primary driver of LAI, with increased water availability promoting leaf area expansion. Environmental factors, including temperature, vapor pressure deficits, and solar radiation, influence LAI dynamics, with chilling hours playing a crucial role post-veraison. Excessive LAI (>1.6–1.7) reduces yield due to competition between vegetative and reproductive sinks. Early-season LAI correlates more strongly with yield, while late-season LAI predicts pruning weight and cane growth. Machine learning models reveal that excessive pre-veraison LAI in one season reduces cluster numbers in the next. This study highlights LAI as a critical tool for vineyard management. While irrigation promotes vegetative growth, excessive LAI can hinder fruit set and yield, emphasizing the need for strategic irrigation timing, canopy management, and climate adaptation to sustain long-term vineyard productivity.

Keywords: leaf area index; machine learning; Vitis vinifera; vine physiology; yield components; pruning components; agrometeorology (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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