Simple models for predicting leaf area of mango (Mangifera indica L.)

M. Ghoreishi, Yaghoob Hossini, M. Maftoon
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引用次数: 30

Abstract

Mango ( Mangifera indica L.), one of the most popular tropical fruits, is cultivated in a considerable part of southern Iran. Leaf area is a valuable parameter in mango research, especially plant physiological and nutrition field. Most of available methods for estimating plant leaf area are difficult to apply, expensive and destructive which could in turn destroy the canopy and consequently make it difficult to perform further tests on the same plant. Therefore, a non-destructive method which is simple, inexpensive, and could yield an accurate estimation of leaf area will be a great benefit to researchers. A regression analysis was performed in order to determine the relationship between the leaf area and leaf width, leaf length, dry and fresh weight. For this purpose 50 mango seedlings of local selections were randomly took from a nursery in the Hormozgan province, and different parts of plants were separated in laboratory. Leaf area was measured by different method included leaf area meter, planimeter, ruler (length and width) and the fresh and dry weight of leaves were also measured. The best regression models were statistically selected using Determination Coefficient, Maximum Error, Model Efficiency, Root Mean Square Error and Coefficient of Residual Mass. Overall, based on regression equation, a satisfactory estimation of leaf area was obtained by measuring the non-destructive parameters, i.e. number of leaf per seedling, length of the longest and width of widest leaf (R 2 = 0.88) and also destructive parameters, i.e. dry weight (R 2 = 0.94) and fresh weight (R 2 = 0.94) of leaves.
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芒果叶面积的简单预测模型
芒果(Mangifera indica L.)是最受欢迎的热带水果之一,在伊朗南部的相当一部分地区种植。叶面积是芒果研究的重要参数,特别是在植物生理营养研究领域。估计植物叶面积的大多数现有方法难以应用、昂贵且具有破坏性,这可能反过来破坏冠层,从而使对同一植物进行进一步试验变得困难。因此,一种简单、廉价且能准确估算叶面积的非破坏性方法将对研究人员大有裨益。为了确定叶面积与叶宽、叶长、干重和鲜重之间的关系,进行了回归分析。为此,从霍尔木兹甘省的一个苗圃中随机抽取50株当地选择的芒果幼苗,并在实验室中对植株的不同部位进行分离。采用叶面积计、平面计、尺(长、宽)等不同测量方法测定叶片面积,并测定叶片鲜重和干重。采用决定系数、最大误差、模型效率、均方根误差和剩余质量系数对最佳回归模型进行统计筛选。总体而言,根据回归方程,通过测量叶片的非破坏性参数(单株叶数、最长叶长和最宽叶宽)(r2 = 0.88)以及叶片的干重(r2 = 0.94)和鲜重(r2 = 0.94),得到了满意的叶面积估值。
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