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首页> 外文期刊>Photosynthetica >Leaf area estimation by simple measurements and evaluation of leaf area prediction models in Cabernet-Sauvignon grapevine leaves
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Leaf area estimation by simple measurements and evaluation of leaf area prediction models in Cabernet-Sauvignon grapevine leaves

机译:通过简单测量和评估赤霞珠-长相思葡萄叶片面积的叶面积估算模型

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摘要

For two growing seasons (2005 and 2006), leaves of grapevine cv. Cabernet-Sauvignon were collected at three growth stages (bunch closure, veraison, and ripeness) from 10-year-old vines grafted on 1103 Paulsen and SO4 rootstocks and subjected to three watering regimes in a commercial vineyard in central Greece. Leaf shape parameters (leaf area-LA, perimeter-Per, maximum midvein length-L, maximum width-W, and average radial-AR) were determined using an image analysis system. Leaf morphology was affected by sampling time but not by year, rootstock, or irrigation treatment. The rootstock×irrigation×sampling time interaction was significant for all the leaf shape parameters (LA, Per, L, W, and AR) and the means of the interaction were used to establish relationships between them. A highly significant linear function between L and LA could be used as a non-destructive LA prediction model for Cabernet-Sauvignon. Eleven models proposed for the non-destructive LA estimation in various grapevine cultivars were evaluated for their accuracy in predicting LA in this cultivar. For all the models, highly significant linear functions were found between calculated and measured LA. Based on r 2 and the mean square deviation (MSD), the model proposed for LA estimation in cv. Cencibel [LA = 0.587(L×W)] was the most appropriate.
机译:在两个生长季节(2005年和2006年),葡萄树的简历。 Cabernet-Sauvignon赤霞珠是在三个生长阶段(关闭,成熟和成熟)从1103年保尔森和SO4砧木上嫁接的10年老藤中收集的,并在希腊中部的一家商业葡萄园中进行了三种浇水制度。使用图像分析系统确定叶片形状参数(叶面积-LA,周长-Per,最大中脉长度-L,最大宽度-W和平均径向-AR)。叶片形态受采样时间的影响,但不受年份,砧木或灌溉处理的影响。砧木×灌溉水×采样时间对所有叶片形状参数(LA,Per,L,W和AR)均具有显着的交互作用,并利用交互作用的方式建立了它们之间的关系。 L和LA之间的高度重要的线性函数可以用作赤霞珠的无损LA预测模型。评估了11个用于各种葡萄品种无损LA估计的模型,评估了其预测该品种LA的准确性。对于所有模型,在计算出的和测量出的LA之间都发现了高度有效的线性函数。基于r 2 和均方差(MSD),提出了用于cv中LA估计的模型。 Cencibel [LA = 0.587(L×W)]最合适。

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