ABSTRACT

Canopy development and production efficiency variations were evaluated in four sweet cherry (Prunus avium L.) cultivars: ‘Bing’, ‘Lapins’, ‘Sweetheart’ and ‘Regina’, grafted on different vigor rootstocks: ‘Colt’, ‘Cab-6P, ‘Maxma-14’ and ‘Gisela-12’, and conducted in two training systems: Central Leader (CL) and Kym Green Bush (KGB), growing in Chile. Leaf indicators were calculated after tree defoliation. A principal components analysis (PCA) was conducted to select indicators that explain the variation among the combinations. Results showed that leaf size and number varied between different cultivar/rootstock combinations and training systems. By means of two principal components, the model employed could explain 72% of the data variability. The most relevant indicators for the PC1 were: leaf weight per hectare (0.98) and leaf area index (0.97), with a significant training system effect, whereas for the PC2 they were: leaf weight per leaf area (0.85) and production per leaf area (0.72), mainly for productive efficiency. In ‘Lapins’/‘Colt’, the KGB system presented a higher weight and leaf area than CL, with almost double the leaf weight per hectare and leaf area index, due mainly to a 37% leaf area per tree and 20% higher tree number/ha in KGB. However, average production per leaf area reached 0.49 kg m⁻², without distinction between training systems.

摘要

评估了四种甜樱桃（Prunus aviumL.) 栽培品种：'Bing'、'Lapins'、'Sweetheart' 和 'Regina'，嫁接到不同的活力砧木：'Colt'、'Cab-6P、'Maxma-14' 和 'Gisela-12'，并进行在两个培训系统中：Central Leader (CL) 和 Kym Green Bush (KGB)，在智利成长。树叶指标在树木落叶后计算。进行主成分分析 (PCA) 以选择解释组合之间变化的指标。结果表明，不同品种/砧木组合和训练系统之间的叶片大小和数量不同。通过两个主成分，所采用的模型可以解释 72% 的数据变异性。PC1 最相关的指标是：每公顷叶重 (0.98) 和叶面积指数 (0.97)，具有显着的训练系统效果，而对于 PC2，它们是：每公顷叶重 (0.98)。85) 和每叶面积产量 (0.72)，主要是为了生产效率。在“Lapins”/“Colt”中，KGB 系统呈现出比 CL 更高的权重和叶面积，每公顷的叶重和叶面积指数几乎翻了一番，这主要是由于每棵树的叶面积增加了 37%，树木增加了 20%克格勃数量/公顷。然而，每叶面积的平均产量达到了 0.49 kg m⁻²，不区分训练系统。