Yang Weiwei, Zhu Junqi, van Leeuwen Cornelis, Dai Zhanwu, Gambetta Gregory A
Beijing Key Laboratory of Grape Science and Enology and Key Laboratory of Plant Resources, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China.
EGFV, Univ. Bordeaux, Bordeaux Sciences Agro, INRAE, ISVV, Villenave d'Ornon, 33882, France.
Hortic Res. 2023 Apr 13;10(6):uhad071. doi: 10.1093/hr/uhad071. eCollection 2023 Jun.
Climate and water availability greatly affect each season's grape yield and quality. Using models to accurately predict environment impacts on fruit productivity and quality is a huge challenge. We calibrated and validated the functional-structural model, GrapevineXL, with a data set including grapevine seasonal midday stem water potential (Ψ), berry dry weight (DW), fresh weight (FW), and sugar concentration per volume ([Sugar]) for a wine grape cultivar ( cv. Cabernet Franc) in field conditions over 13 years in Bordeaux, France. Our results showed that the model could make a fair prediction of seasonal Ψ and good-to-excellent predictions of berry DW, FW, [Sugar] and leaf gas exchange responses to predawn and midday leaf water potentials under diverse environmental conditions with 14 key parameters. By running virtual experiments to mimic climate change, an advanced veraison (i.e. the onset of ripening) of 14 and 28 days led to significant decreases of berry FW by 2.70% and 3.22%, clear increases of berry [Sugar] by 2.90% and 4.29%, and shortened ripening duration in 8 out of 13 simulated years, respectively. Moreover, the impact of the advanced veraison varied with seasonal patterns of climate and soil water availability. Overall, the results showed that the GrapevineXL model can predict plant water use and berry growth in field conditions and could serve as a valuable tool for designing sustainable vineyard management strategies to cope with climate change.
气候和水资源可利用性极大地影响着每个季节葡萄的产量和品质。利用模型准确预测环境对果实生产力和品质的影响是一项巨大挑战。我们使用一个数据集对功能-结构模型GrapevineXL进行了校准和验证，该数据集包含法国波尔多地区13年田间条件下一个酿酒葡萄品种（品丽珠）的葡萄藤季节性午间茎水势（Ψ）、浆果干重（DW）、鲜重（FW）以及每体积糖浓度（[糖]）。我们的结果表明，该模型能够对季节性Ψ做出合理预测，并且在14个关键参数的情况下，能够对不同环境条件下浆果的DW、FW、[糖]以及叶片气体交换对黎明前和午间叶片水势的响应做出良好到极佳的预测。通过进行虚拟实验来模拟气候变化发现，提前14天和28天进入始熟期（即成熟开始）分别导致浆果FW显著下降2.70%和3.22%，浆果[糖]明显增加2.90%和4.29%，并且在13个模拟年份中有8个年份的成熟持续时间缩短。此外，提前始熟期的影响因气候和土壤水分可利用性的季节模式而异。总体而言，结果表明GrapevineXL模型能够预测田间条件下植物的水分利用和浆果生长，并且可以作为设计可持续葡萄园管理策略以应对气候变化的宝贵工具。
