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首页> 外文期刊>Journal of the American Society for Horticultural Science >Statistical model estimates potential yields in pear cultivars 'Blanquilla' and 'Conference' before bloom
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Statistical model estimates potential yields in pear cultivars 'Blanquilla' and 'Conference' before bloom

机译：统计模型估计梨品种“ Blanquilla”和“ Conference”开花前的潜在产量

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Spring frosts are usual in many of Spain's fruit-growing areas, so it is common to insure crops against frost damage. After a frost, crop loss must be evaluated, by comparing what crop is left with the amount that would have been obtained under normal conditions. Potential crop must be evaluated quickly through the use of measurements obtainable at the beginning of the tree's growth cycle. During 1996 and 1997 and in 95 commercial plots of 'Blanquilia' and 'Conference' pear (Pyrus communis L.), the following measurements were obtained: trunk cross-sectional area (TCA, cm(2)), space allocated per tree (ST, m(2)), trunk cross-sectional area per hectare (TCA/ha), flower density (FD, number of flower budS/cm(2) TCA), flower density per land area (FA, number of flower buds/m(2) land area), cluster set (CS, number of fruit clustersumber of flower clusters, %), crop density (CD, number of fruit/cm(2) TCA), fruit clusters per trunk cross-sectional area (FCT, number of fruit clusters/cm(2) TCA), fruit clusters per land area (FCA, number of fruit clusters/m(2) land area), fruit number per cluster (FNC), average fruit weight (FW, g), average yield per fruit cluster (CY, g), yield efficiency (YE, fruit g-cm(-2) TCA), and tree yield (Y, fruit kg/tree). CS and average CY were related to the rest of the variables through the use of multiple regression models. The models that provided the best fit were CS = TCA/ha-FA and CY = -FA-FCT. These models were significant, consistent, and appropriate for both years. Predicted yield per land area was obtained by multiplying FA x CS x CY. The models' predictive ability was evaluated for 46 different plots in 2001 and 2002. Statistical analysis showed the models to be valid for the forecast of orchards' potential yield efficiency, so that they represent a useful tool for early crop prediction and evaluation of losses due to late frosts.
机译：在西班牙许多水果产区，通常会出现春季霜冻，因此确保作物免受霜冻损害是很普遍的。霜冻后，必须通过比较剩下的作物与正常条件下的收获量来评估作物损失。必须通过在树木生长周期开始时获得的测量值快速评估潜在作物。在1996年至1997年期间，在95个“ Blanquilia”和“ Conference”梨（Pyrus communis L.）商业区中，获得了以下测量值：树干横截面积（TCA，cm（2）），每棵树分配的空间（ ST，m（2）），每公顷树干横截面积（TCA / ha），花密度（FD，花蕾数S / cm（2）TCA），每土地面积花密度（FA，花蕾数/ m（2）土地面积），群集集（CS，水果群集数量/花群集数量，％），作物密度（CD，水果数量/ cm（2）TCA），每个树干横截面的水果群集面积（FCT，水果簇数/ cm（2）TCA），每个陆地面积的水果簇（FCA，水果簇数/ m（2）土地面积），每簇水果数（FNC），平均水果重量（FW ，g），每个水果簇的平均产量（CY，g），产量效率（YE，水果g-cm（-2）TCA）和树木产量（Y，水果千克/棵）。通过使用多元回归模型，CS和平均CY与其余变量相关。提供最佳拟合的模型是CS = TCA / ha-FA和CY = -FA-FCT。这些模型是重要的，一致的，并且适用于两年。通过将FA x CS x CY乘以得出每个土地面积的预测产量。在2001年和2002年对46个样地进行了模型预测能力的评估。统计分析表明，该模型对于预测果园的潜在单产效率是有效的，因此它们可作为早期作物预测和损失评估的有用工具。到晚霜。

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