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首页> 外文期刊>Photosynthetica >Nondestructive, simple, and accurate model for estimation of the individual leaf area of som (Persea bombycina)
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Nondestructive, simple, and accurate model for estimation of the individual leaf area of som (Persea bombycina)

机译:无损,简单且准确的模型来估算som(Persea bombycina)的单个叶面积

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Nondestructive approach of modeling leaf area could be useful for plant growth estimation especially when number of available plants is limited and/or experiment demands repeated estimation of leaf area over a time scale. A total of 1,280 leaves were selected randomly from eight different morphotypes of som (Persea bombycina) established at randomized complete block design under recommended cultural regimes in field. Maximum leaf laminar width (B), length (L) and their squares B2, L2; leaf area (LA), and lamina length × width (L×B) were determined over two successive seasons. Leaf parameters were significantly affected by morphotypes; but seasons had nonsignificant impacts on tested features. Therefore, pooled seasonal morphotype means of each parameter were used to establish relationship with LA. L and its square L2 did not provide accurate models for LA predictions. Considerably better models were obtained by using B (y = 2.984 + 7.9664 x, R 2 = 0.615, P≥0.001, n = 119) and B2 (y = 12.784+ 0.9604 x, R 2 = 0.605, P≥0.001, n = 119) as independent variables. However, maximum accuracy of prediction of LA could be achieved through a simple linear relationship of L×B (y = 8.2203 + 0.4224 x, R 2 = 0.843, P≥0.0001, n = 119). The model (LA:L×B) was validated with randomly selected leaf samples (n = 360) of som morphotypes and highly significant (P≤0.001) linear function was found between actual and predicted LAs. Therefore, the last model may consider adequate to predict leaf area of all cultivars of som with sufficient fidelity.
机译:对叶面积建模的非破坏性方法可能对植物生长估算很有用,尤其是在可用植物数量有限和/或实验要求在一定时间内对叶面积进行重复估算时。从8种不同形态的som(Persea bombycina)中随机选择了总共1,280张叶子,这些形态是在田间建议的文化制度下通过随机完整块设计而建立的。最大叶片层流宽度(B),长度(L)及其平方B2 ,L2 ;确定了连续两个季节的叶片面积(LA)和叶片长度×宽度(L×B)。叶片形态参数显着影响叶片参数。但是季节对测试功能没有重大影响。因此,使用每个参数的合并季节性形态型平均值来建立与LA的关系。 L及其平方L2 没有为LA预测提供准确的模型。使用B(y = 2.984 + 7.9664 x,R 2 = 0.615,P≥0.001,n = 119)和B2 (y = 12.784+ 0.9604 x,R 2 < / sup> = 0.605,P≥0.001,n = 119)作为自变量。然而,通过简单的线性关系L×B(y = 8.2203 + 0.4224 x,R 2 = 0.843,P≥0.0001,n = 119)可以实现LA预测的最大准确性。该模型(LA:L×B)已通过随机选择的som形态型叶片样本(n = 360)进行了验证,并且在实际和预测的LA之间发现了高度显着的(P≤0.001)线性函数。因此,最后一个模型可以考虑以足够的保真度来预测所有som品种的叶面积。

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