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Variations in dendrometric and fruiting characters of Vitellaria paradoxa populations and multivariate models for estimation of fruit yield

机译:Vitellaria paradoxa种群的树状和结实特征的变异以及估计水果产量的多元模型

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摘要

The fruit of Vitellaria paradoxa is an ideal raw material in cosmetic, pharmaceutical and confectionery industries. There are no accurate data on annual fruit yield due to the lack of objective assessment tools. The objectives of this study were to develop fruit yield prediction models based on dendrometric and fruiting variables, to examine variations in these variables between upland and lowland populations in Burkina Faso, and associations between these variables. A total of 191 fruiting trees were selected according to crown accessibility, and 17 dendrometric and fruiting variables were recorded. The fruit yield, expressed in number of fruits per tree, fresh and dry weights of fruits, was assessed by collecting fruits dropped overnight until the end of the fruiting period. Fruit yield prediction models were derived for each population using partial least squares regression. The results showed significant differences in dendrometric and fruiting variables between populations (P < 0.01). The lowland population had the highest values for most of the dendrometric variables while fruiting variables were the highest for the upland population. A strong significant correlation (P < 0.01) was found between number of shoots and fruiting variables. Within individual trees, fruit yield was lowest for the bottom part of the crown and the section of the crown with north-east orientation. Fruit yield parameters were successfully predicted based on selected dendrometric and fruiting variables (prediction error = 0.092 and 0.125 for upland and lowland populations, respectively). All fruiting variables, number of shoots and crown attributes had the highest influence on the models.
机译:Vitellaria paradoxa的果实是化妆品,制药和糖果行业的理想原料。由于缺乏客观的评估工具,没有关于年度水果产量的准确数据。这项研究的目的是建立基于树状变量和结果变量的水果产量预测模型,以检查布基纳法索高地和低地人口之间这些变量的变异以及这些变量之间的关联。根据树冠的可及性,总共选择了191棵果树,并记录了17个树状变量和果树变量。通过收集整夜掉落至出果期结束的果实来评估以单棵树的果实数,果实的新鲜和干燥重量表示的果实产量。使用偏最小二乘回归为每个人群得出了水果产量预测模型。结果表明,不同种群之间的树状变量和结果变量存在显着差异(P <0.01)。对于大多数树状变量,低地人口的价值最高,而高地人口的结实变量最高。枝条数量与结果变量之间存在极强的相关性(P <0.01)。在单个树木中,树冠的底部和朝东北的树冠部分的果实产量最低。根据选定的树状变量和结果变量成功预测了水果产量参数(旱地和低地人口的预测误差分别为0.092和0.125)。所有结果变量,枝条数量和冠状属性对模型的影响最大。

著录项

  • 来源
    《Agroforestry Systems》 |2007年第1期|1-11|共11页
  • 作者单位

    Département de Productions Forestières INERA-CNRST 01 BP: 910 Bobo-Dioulasso 01 Burkina Faso;

    Department of Forest Genetics and Plans Physiology Tropical Silviculture and Seed Science Group SLU Umeå S-901 83 Sweden;

    Laboratoire de Biologie et Ecologie Végétales/UFR-SVT Université de Ouagadougou 03 BP: 7021 Ouagadougou 03 Burkina Faso;

    Department of Forest Genetics and Plans Physiology Tropical Silviculture and Seed Science Group SLU Umeå S-901 83 Sweden;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Fruit production; Prediction; Shea tree; Karité; Shea butter;

    机译:水果生产;预测;乳木果树;Karité;乳木果油;
  • 入库时间 2022-08-18 02:21:16

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