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首页> 外文期刊>The Journal of Agricultural Science >Predicting the flowering date of Portuguese grapevine varieties using temperature-based phenological models: a multi-site approach
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Predicting the flowering date of Portuguese grapevine varieties using temperature-based phenological models: a multi-site approach

机译:使用基于温度的鉴性模型预测葡萄牙葡萄种品种的开花日期:一种多网站方法

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Phenological models for predicting the grapevine flowering were tested using phenological data of 15 grape varieties collected between 1990 and 2014 in Vinhos Verdes and Lisbon Portuguese wine regions. Three models were tested: Spring Warming (Growing Degree Days – GDD model), Spring Warming modified using a triangular function – GDD triangular and UniFORC model, which considers an exponential response curve to temperature. Model estimation was performed using data on two grape varieties (Loureiro and Fern?o Pires), present in both regions. Three dates were tested for the beginning of heat unit accumulation (t0 date): budburst, 1 January and 1 September. The best overall date was budburst. Furthermore, for each model parameter, an intermediate range of values common for the studied regions was estimated and further optimized to obtain one model that could be used for a diverse range of grape varieties in both wine regions. External validation was performed using an independent data set from 13 grape varieties (seven red and six white), different from the two used in the estimation step. The results showed a high coefficient of determination (R2: 0.59–0.89), low Root Mean Square Error (RMSE: 3–7 days) and Mean Absolute Deviation (MAD: 2–6 days) between predicted and observed values. The UniFORC model overall performed slightly better than the two GDD models, presenting higher R2 (0.75) and lower RMSE (4.55) and MAD (3.60). The developed phenological models presented good accuracy when applied to several varieties in different regions and can be used as a predictor tool of flowering date in Portugal.
机译:使用1990年至2014年间Vinhos Verdes和Lisbon葡萄牙葡萄酒区收集的15个葡萄品种的毒性数据来测试用于预测葡萄花开花的酚类模型。测试了三种型号:弹簧变暖(生长度天 - GDD模型),使用三角形功能 - GDD三角形和UniForc模型进行修改的弹簧升温,这使得指数响应曲线进行温度。在两个地区存在的两种葡萄品种(Loureiro和Fern?O Pires)上的数据进行了模型估计。测试了三个日期,以获得热量单位积累(T0日期):Budburst,1月1日和9月1日。最好的整体日期是布伯斯特。此外,对于每个模型参数,估计了研究区域共同的值的中间范围,并进一步优化,以获得一种可用于两种葡萄酒区中各种葡萄品种的模型。使用从13个葡萄品种(七个红色和六个白色)的独立数据进行外部验证,与估计步骤中使用的两种不同。结果显示出高度的测定系数(R2:0.59-0.89),低根均方误差(RMSE:3-7天),平均值偏差(MAD:2-6天)之间的预测和观察值之间。 uniforc模型总体上略高于两个GDD型号,呈现出更高的R2(0.75)和更低的RMSE(4.55)和MAD(3.60)。当应用于不同地区的几种品种时,发达的鉴效模型呈现出良好的准确性,并且可以用作葡萄牙开花日期的预测工具。

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