There is an increasing demand for tools able to optimise water management in cropping systems, especially in cases of dry areas or when water management has a deep effect on both the amount and quality of productions. A method is proposed to estimate grape stomatal conductance (g_s) from 3D leaf scans obtained using a smartphone. The method is based (i) on the use of the 3D leaf scans to derive the χ parameter of the Campbell's leaf angle distribution (the lower the χ, the larger the leaf tendency to be vertical) and (ii) on the changes in leaf orientation due to decrease in leaf turgor. Experimental data were collected on Vitis vinifera (cv. Malvasia and Chardonnay) in seven experiments carried out in vineyards in Northern Italy during 2021 and 2022. Results revealed significant (p-value < 0.01) linear relationships between g_s and χ (R² ≥ 0.79 for both cultivars). From the data collected, 13 leaves (90 s to perform measurements) at each point (vine) and seven points ha^-1 was identified as the optimal sample size to capture vineyard heterogeneity. The suitability of the method for use in commercial vineyard conditions opens new opportunities for optimizing water management in vineyards.

人们对能够优化耕作系统水分管理的工具的需求不断增加，特别是在干旱地区或当水分管理对产量和质量产生深远影响时。提出了一种根据智能手机获得的 3D 叶子扫描来估计葡萄气孔导度 ( g _{s ) 的方法。}该方法基于 (i) 使用 3D 叶片扫描来推导坎贝尔叶片角度分布的 χ 参数（χ 越低，叶片垂直的趋势越大）和 (ii) 叶片的变化由于叶片饱满度的降低而导致的定向。实验数据是在 2021 年和 2022 年期间在意大利北部葡萄园进行的 7 项实验中收集的葡萄（葡萄品种 Malvasia 和霞多丽）。结果显示g _s和 χ 之间存在显着的线性关系 ( p值 < 0.01) (R ²  ≥两个品种均为 0.79）。根据收集的数据，每个点（葡萄树）的 13 个叶子（执行测量需要 90 秒）和七个点 ha ^-1被确定为捕捉葡萄园异质性的最佳样本量。该方法适用于商业葡萄园条件，为优化葡萄园水管理开辟了新的机会。