贺兰山东麓‘赤霞珠’品质形成气象条件与评级方法研究

Meteorological conditions and rating method of quality formation of 'Cabernet Sauvignon' grape in eastern foothills of Helan Mountain

  • 摘要: 葡萄品质很大程度上决定了葡萄酒品质,其与气象条件关系密切。在正常管理和农业技术水平下,衡量葡萄生长气象条件是否适宜品质形成的方法称为酿酒葡萄品质气象评价技术。研究酿酒葡萄品质形成的气象评级技术和气象指标,可为葡萄酒商业评级、年份酒鉴定和窖藏提供气候参考依据。利用贺兰山东麓2003-2011年多点采样化验的101份‘赤霞珠’总糖、总酸、糖酸比、pH和单宁资料,选取其中的51份进行相关普查,确定了有生物学意义的显著气象因子,以各因子的决定系数分别建立了5项品质指标的权重模型,通过单项品质指标对综合品质的贡献构建了综合品质气象评价模型。参照前人对葡萄酒品质、酿酒葡萄品质的研究和葡萄酒和葡萄品质标准,根据酿造葡萄酒所需的总糖、总酸、糖酸比、pH和单宁,确定‘赤霞珠’各项品质指标的阈值,利用模型反推出与葡萄酒品质相对应的气象因子阈值和‘赤霞珠’品质气象分类标准。回代检验显示5项品质指标均通过了0.001的R检验和F检验,与实测值接近且变化趋势一致。总糖、总酸、糖酸比和单宁的模拟效果较好,R ≥ 0.59且RMSE较小,但pH误差相对较大。用50份未参与建模的样本估算了‘赤霞珠’品质等级。总糖、总酸与实测接近;个别样本的糖酸比、单宁误差相对较大,但变化趋势与实测一致;样本pH均在适宜范围内且较稳定。从综合评分和等级来看,28个样本与实况等级相同,18个样本误差在1级内,仅4个样本相差2级,准确反映出原料的质量。‘赤霞珠’品质气象评价指标和模型为评价贺兰山东麓酿酒葡萄品质提供了一套可行的方法。

     

    Abstract: The quality of grape wine is largely determined by the quality of grapes, which is closely related to meteorological conditions during grape growing season. Under normal management conditions and agricultural technology, the method of evaluation of meteorological conditions for fruit growth is called quality meteorological evaluation of wine grape. Meteorological condition rating techniques and meteorological indexes research on wine grape quality formation provide the base lines of climatic conditions for rating commercial wine, vintage identification and hoarding. In this paper, five indexes were tested for total sugar, total acid, sugar-acid ratio, pH and tannin content of 101 'Cabernet Sauvignon' fruit samples collected at various sites in eastern Helan Mountain during 2003-2011. Test data for 51 samples were selected to analyze for correlations with meteorological data for fruit growth. Based on the analysis of biological effects of meteorological factors on quality, meteorological factors affecting each quality index were determined for significant level. Based on the determination coefficient of each meteorological factor to a quality index, five weight models of quality indexes with significant meteorological factors were constructed. Thus the quality indexes of 'Cabernet Sauvignon' grape were reckoned with the meteorological conditions for fruit growth period. Using determination coefficients of meteorological factors as weight, an integrated meteorological simulation model with 5 quality indicators was constructed and a comprehensive quality meteorological evaluation model was established by using the weight of individual quality indicators. Using related research results coupled with the winemaker suggestion, a comprehensive meteorological scoring model for wine grape quality was constructed based on the contribution of each quality index and wine quality. In relation to previous studies and the criteria of quality of grape and wine, 5 quality indicators and quality grades were classified. The threshold meteorological factors corresponding to the wine quality and classification criteria for grape climatic conditions of 'Cabernet Sauvignon' were also determined. It implied that based on the requirements of total sugar, total acid, sugar-acid ratio, pH and tannin content needed for brewing high quality wine, the 5 quality indicators and comprehensive meteorological grades of 'Cabernet Sauvignon' were divided into five grades. This included excellent (grade 5), very good (grade 4), good (grade 3), medium (grade 2) and poor (grade 1). Then based on the threshold of each quality grade and the comprehensive meteorological simulation equation of the above 5 quality indicators, the threshold of the meteorological factors affecting each quality grade was deduced. This was in turn used as the meteorological factor classification index for evaluating the climate condition for quality of 'Cabernet Sauvignon' grape. The effects of simulation and grape classification of the 5 quality indicators and 'Cabernet Sauvignon' grape in the foothills of Helan Mountain were tested using the 51 samples selected to establish the model. The results showed that all the models of the 5 quality indicators passed the 0.001 R-test and F-test, indicating that the estimated values were within the measured values and that the variation trends were consistent. Among these, the simulation effects of total sugar content, total acid content, sugar-acid ratio and tannin content were better (R ≥ 0.59 and small RMSE) than the effects of pH (where there was a relative large simulation dispersion). To predict the effects of the evaluation model and indexes by using the other 50 samples that were not included in the model development and meteorological data during fruit development, the effects of the grading were tested for 'Cabernet Sauvignon' grape quality in the eastern foothills of Helan Mountain. The results indicated that the contents of total sugar and total acid were close to the measured values. In addition to a relative large error for few samples of sugar-acid ratio and tannin content, the error for the other samples was relatively small and the overall trend was consistent with the measured values. pH was relatively stable and all the samples were within the appropriate range for brewing high-quality wine, and differences in yearly meteorological conditions were difficult to determine, indicating that the local climatic conditions were conducive for the pH needed for high quality wine brewing. From the comprehensive score and grade, 28 samples were the same as the actual level and only 4 samples differed at 2 levels. The rest of the samples were within level 1, which more accurately reflected the quality of raw materials. The meteorological evaluation indexes and models of 'Cabernet Sauvignon' provided a feasible tool for evaluating the quality of wine grape in the eastern foothills of Helan Mountain.

     

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