Sujeeun Leeladarshini, Isaac Marney E, Cathline Kimberley, Robertson Gavin, Martin Adam R
Department of Physical and Environmental Sciences University of Toronto Scarborough Canada.
Horticultural & Environmental Sciences Innovation Centre Niagara College Canada.
Plant Environ Interact. 2025 Sep 12;6(5):e70077. doi: 10.1002/pei3.70077. eCollection 2025 Oct.
Quantifying crop responses to increasing temperatures is critical for predicting the productivity and sustainability of agricultural systems under environmental change. Physiological trait data associated with maximum Rubisco carboxylation ( ) and maximum electron transport ( ) rates are especially important predictors of crop response to elevated temperatures. However, when generating and data, steady-state methods of gas exchange measurements are time-consuming; thus, non-steady-state methods have been developed to obtain these measurements faster, prospectively allowing for trait data collection of considerably more varieties of crops. Globally important and geographically widespread vineyards are of particular interest due to the high economic value and the susceptibility of these managed systems to climate warming, especially in Canada, where the annual rate of warming far exceeds global averages. In this study, we examined the efficacy of the high-throughput, non-steady-state dynamic assimilation technique (DAT) for obtaining and data from wine grapes. Specifically, we measured and (alongside leaf nitrogen [N] concentrations and leaf mass per unit area [LMA]) across seven of the world's most common wine grape ( L.) varieties, namely, Cabernet franc, Cabernet sauvignon, Merlot, Pinot noir, Riesling, Sauvignon blanc, and Viognier. Our results show that and estimates derived from the DAT were strongly correlated to those obtained through the steady-state method ( = 0.748 and 0.908, respectively), and did not differ significantly between the two methods. Additionally, leaf N explained 43%-46% and 56%-58% of the variation in and , respectively, across both methods. Our results suggest that the DAT represents a viable tool for rapidly estimating intraspecific variation in important physiological traits and allows for increased replication and the inclusion of additional varieties when evaluating the responses of wine grape and other crops to climate warming.
量化作物对气温升高的响应对于预测环境变化下农业系统的生产力和可持续性至关重要。与最大羧化酶羧化作用（ ）和最大电子传递（ ）速率相关的生理性状数据是作物对气温升高响应的特别重要的预测指标。然而，在生成 和 数据时，气体交换测量的稳态方法耗时较长；因此，已开发出非稳态方法以更快地获得这些测量结果，有望允许收集更多种类作物的性状数据。由于全球重要且地理分布广泛的葡萄园具有较高的经济价值，且这些人工管理系统易受气候变暖影响，特别是在加拿大，其年变暖速率远超过全球平均水平，因此备受关注。在本研究中，我们检验了高通量、非稳态动态同化技术（DAT）从酿酒葡萄中获取 和 数据的有效性。具体而言，我们测量了世界上最常见的七个酿酒葡萄（ ）品种，即品丽珠、赤霞珠、梅洛、黑皮诺、雷司令、长相思和维欧尼的 和 （以及叶片氮 [N] 浓度和单位面积叶片质量 [LMA]）。我们的结果表明，从DAT得出的 和 估计值与通过稳态方法获得的估计值高度相关（分别为 = 0.748和0.908），并且两种方法之间的 没有显著差异。此外，在两种方法中，叶片N分别解释了 和 中43% - 46% 和56% - 58% 的变异。我们的结果表明，DAT是一种用于快速估计重要生理性状种内变异的可行工具，并且在评估酿酒葡萄和其他作物对气候变暖的响应时允许增加重复次数并纳入更多品种。
