Rapid Physiological Trait Measurements in Wine Grape (Vitis vinifera) Varieties Using the Dynamic Assimilation Technique

利用动态同化技术快速测定酿酒葡萄(Vitis vinifera)品种的生理性状

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Abstract

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 (V (cmax)) and maximum electron transport (J (max)) rates are especially important predictors of crop response to elevated temperatures. However, when generating V (cmax) and J (max) 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 V (cmax) and J (max) data from wine grapes. Specifically, we measured V (cmax) and J (max) (alongside leaf nitrogen [N] concentrations and leaf mass per unit area [LMA]) across seven of the world's most common wine grape (Vitis vinifera L.) varieties, namely, Cabernet franc, Cabernet sauvignon, Merlot, Pinot noir, Riesling, Sauvignon blanc, and Viognier. Our results show that V (cmax) and J (max) estimates derived from the DAT were strongly correlated to those obtained through the steady-state method (r (2) = 0.748 and 0.908, respectively), and J (max) did not differ significantly between the two methods. Additionally, leaf N explained 43%-46% and 56%-58% of the variation in V (cmax) and J (max), 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.

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