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首页> 外文期刊>Australian Journal of Crop Science >Use of multi-dimensional scaling for analysis of teak plants (Tectona grandis) under omission of macronutrients
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Use of multi-dimensional scaling for analysis of teak plants (Tectona grandis) under omission of macronutrients

机译:多维比例分析在缺少大量营养素的情况下对柚木植物(Tectona grandis)的分析

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The aim of this study was to diagnose the deficiency symptoms and evaluate the production of dry matter, contents and accumulation of macronutrients in teak plants (Tectona grandis) grown on substrates with omission of nutrients using the multidimensional scaling analysis. The experimental design was completely randomized blocks with seven treatments with four replications as follows: treatment complete (C), and the individual omissions such as: zero levels of -N (omission of nitrogen), -P (omission of phosphorus), - K (omission of potassium), -Ca (omission of calcium), -Mg (omission of magnesium), -S (omission of sulfur). The statistical analysis model was Multivariate Multidimensional Scaling (MDS) using the statistical Software SPSS 17.0, which summarizes information and points the mechanisms of extreme use fullness. The results showed that omissions of macronutrients cause nutritional deficiency and visual symptoms known to other species as usual. The deficiencies restricted the dry matter production according to the following order: K > N > Mg > Ca > P > S. The leaf content of macronutrients in teak plants subjected to omission of nutrients compared to treatment resulted in complete change in the values as: N = 14.5-20.7 g kg-1, P = 1.0-2.1 g kg-1, K = 3.0-7.1 g kg-1, Ca = 3.9-10.5 g kg-1, Mg = 0.8-4.9 g kg-1, and S = 1.5-2.1 g kg-1. The multi-dimensional scaling analysis demonstrated that calcium, phosphorus and magnesium were limiting factors in the production of dry matter and in macronutrient contents, while nitrogen was accumulated mainly in leaves. Phosphorus and magnesium were accumulated in smaller amounts.
机译:这项研究的目的是使用多维标度分析法诊断缺乏症状,并评估在缺少养分的基质上生长的柚木植物(Tectona grandis)中干物质的产生,常量养分的含量和积累。实验设计是采用7种处理方法的完全随机区组,重复四次,如下所示:处理完成(C),以及个别遗漏,例如:-N(氮遗漏),-P(磷遗漏),-K为零水平(缺少钾),-Ca(缺少钙),-Mg(缺少镁),-S(没有硫)。统计分析模型是使用统计软件SPSS 17.0进行的多维多维缩放(MDS),该模型汇总了信息并指出了极端使用程度的机制。结果表明,缺乏大量营养素会导致营养缺乏和其他物种通常所见的视觉症状。缺陷按照以下顺序限制了干物质的生产:K> N> Mg> Ca> P>S。与处理相比,缺少养分的柚木植物中大量养分的叶片含量导致值的完全变化: N = 14.5-20.7 g kg-1,P = 1.0-2.1 g kg-1,K = 3.0-7.1 g kg-1,Ca = 3.9-10.5 g kg-1,Mg = 0.8-4.9 g kg-1,和S = 1.5-2.1g kg-1。多维尺度分析表明,钙,磷和镁是限制干物质生产和丰富养分的因素,而氮则主要在叶片中积累。磷和镁的积累量较小。

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