刘琰琰,史学家,杜宏娟,等. 西北酿酒葡萄物候模型优选及气候变化对物候期的影响[J]. 农业工程学报,2024,40(12):138-147. DOI: 10.11975/j.issn.1002-6819.202310053
    引用本文: 刘琰琰,史学家,杜宏娟,等. 西北酿酒葡萄物候模型优选及气候变化对物候期的影响[J]. 农业工程学报,2024,40(12):138-147. DOI: 10.11975/j.issn.1002-6819.202310053
    LIU Yanyan, SHI Xuejia, DU Hongjuan, et al. Optimal selection of the phenological models for wine grapevine and the impact of climate change on phenology in northwest China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2024, 40(12): 138-147. DOI: 10.11975/j.issn.1002-6819.202310053
    Citation: LIU Yanyan, SHI Xuejia, DU Hongjuan, et al. Optimal selection of the phenological models for wine grapevine and the impact of climate change on phenology in northwest China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2024, 40(12): 138-147. DOI: 10.11975/j.issn.1002-6819.202310053

    西北酿酒葡萄物候模型优选及气候变化对物候期的影响

    Optimal selection of the phenological models for wine grapevine and the impact of climate change on phenology in northwest China

    • 摘要: 为预测气候变暖背景下西北地区酿酒葡萄物候期变化规律,该研究利用2007—2022年西北地区地表温度数据及酿酒葡萄(赤霞珠、黑比诺、美乐和霞多丽)物候观测数据(萌芽期、开花期和转色期),对酿酒葡萄物候模型(积温模型,包含生长日度模型(growing degree day model,GDD)及葡萄开花转色期模型(grapevine flowering veraison model,GFV),BRIN模型、WE模型)进行参数优化和模拟比较,选取最适模型结合气候模式数据预测SSP245和SSP585情景下酿酒葡萄物候期的变化。结果表明:1)萌芽期,BRIN模型最适用于赤霞珠、美乐和霞多丽,GDD5模型最适于黑比诺;2)开花期,GDD10模型最适用于赤霞珠和美乐,GFV和WE模型分别适用于黑比诺和霞多丽;3)转色期,WE模型最适用于赤霞珠、黑比诺和美乐,GFV模型则最适于霞多丽;4)在SSP245情景下,西北地区2035—2065年与2055—2085年4种葡萄的3个物候期分别平均提前2 d与4 d;在SSP585情景下,西北地区2035—2065年4种葡萄的3个物候期平均提前5 d,2055—2085年除了天山北麓地区的酿酒葡萄转色期因夏季高温影响而平均延后6 d外,其他酿酒葡萄物候期平均提前10 d,进一步分析表明夏季高温是导致转色期延迟的重要因素。研究结果为适应气候变化充分利用气候资源,保障西北地区酿酒葡萄生产优势地位提供理论依据和科学支撑。

       

      Abstract: Grape wine is the largest type of fruit wine industry in the world. Among them, Northwest China is one of the most important regions to produce wine grapes with enormous market potential and high added value, due to the unique climate conditions for the growth and development of grapes. However, the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) also released that the global climate system has posed a significant impact under industrialization and human activities. Particularly, climate change has threatened the regional development of the wine grape industry in Northwest China. This research aims to conduct on the phenological phases of wine grapes in the northwest, and then their changes were predicted to efficiently utilize the local climate resources. The surface temperature and phenological parameters (budburst, flowering, and veraison phases) of wine grapes (Cabernet Sauvignon, Pinot Noir, Merlot, and Chardonnay) were collected from 2007 to 2022. The effective accumulated temperature (GDD5, GDD10, and GFV), BRIN, and WE models were optimized during the growth period. The phenological phase of wine grapes was further simulated under the SSP245 and SSP585 scenarios using climate model data. The results showed that the BRIN model exhibited the best simulation for Cabernet Sauvignon, Merlot, and Chardonnay, while the GDD5 model was most effective for Pinot Noir during the budburst phase. Furthermore, the GDD10 model shared the best performance for Cabernet Sauvignon and Merlot during the flowering phase, whereas, the GFV and WE models were superior for Pinot Noir and Chardonnay, respectively. In the veraison phase, the WE model demonstrated the best simulation for the Cabernet Sauvignon, Pinot Noir, and Merlot, while the GFV model was the most accurate for Chardonnay. Compared with the historical period, the phenological phases of the four wine grape species showed no significant difference under the SSP245 scenario. However, the budburst, flowering, and veraison phases of wine grapes all showed a noticeable trend of advancement under the SSP585 scenario, except for the veraison phase at the northern foot of the Tianshan Mountains. Further analysis revealed that there was no significant advancement in the future frequent occurrence of high-temperature disasters in the northern foothills of the Tianshan region, even delayed in the veraison phase of wine grapes. Meanwhile, the extreme spring temperatures were underestimated to delay the BRIN model, according to the climate model data. Three phenological models shared great variations to simulate the different phenological phases of wine grapes. Overall, the best performance was achieved in the flowering phase, followed by the veraison and budburst phase. According to the phenological phases, the BRIN model demonstrated that there was a significant advantage to simulating the budburst phase, while the WE model was more accurate than that in the veraison phase. Therefore, the effect of high temperatures on the phenological phase was evaluated to predict the veraison phase. Especially, the early effects caused by rising temperatures were partially offset by high temperatures in summer. Therefore, the WE model with high temperatures was usually more accurate to reflect future trends. The phenological phase of wine grapes was also determined under the future climate scenarios. The finding can provide the scientific basis to optimize the wine grape phenology models, in order to promote the development of the local wine grape industry.

       

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