幼龄栓皮栎叶面积预测模型建立及应用

李慧; 张婉; 常益豪; 杨霞; 肖祥伟; 朱景乐

doi:10.12302/j.issn.1000-2006.202208069

幼龄栓皮栎叶面积预测模型建立及应用

李慧, 张婉, 常益豪, 杨霞, 肖祥伟, 朱景乐

南京林业大学学报（自然科学版） ›› 2024, Vol. 48 ›› Issue (5) : 246-254.

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南京林业大学学报（自然科学版） ›› 2024, Vol. 48 ›› Issue (5) : 246-254. DOI: 10.12302/j.issn.1000-2006.202208069

研究论文

幼龄栓皮栎叶面积预测模型建立及应用

李慧 ¹^,² ,
张婉 ¹^,² ,
常益豪 ² ,
杨霞 ³ ,
肖祥伟 ⁴ ,
朱景乐 ¹^,^*

作者信息 +

Construction and application of the leaf area prediction model for young Quercus variabilis

LI Hui ¹^,² ,
ZHANG Wan ¹^,² ,
CHANG Yihao ² ,
YANG Xia ³ ,
XIAO Xiangwei ⁴ ,
ZHU Jingle ¹^,^*

Author information +

文章历史 +

摘要

【目的】建立幼龄栓皮栎叶面积预测模型,实现快速无损测量,并对43个栓皮栎家系的叶片形状变异情况和差异特征进行分析,为栓皮栎遗传多样性研究及良种选育提供理论基础。【方法】从全国不同地区筛选出43个栓皮栎家系作为研究对象,通过对叶长、叶宽、叶长宽比、叶长宽积与实测叶面积的相关性分析及曲线拟合分析,筛选出叶面积预测模型最佳参数;通过几何模型和曲线拟合分析,筛选最优的幼龄栓皮栎叶面积预测模型,并进行验证;运用统计描述、单因素方差分析、相关性分析、聚类分析的方法进行不同家系间叶片的差异分析。【结果】①叶长宽积(X₁×X₂)与幼龄栓皮栎叶面积呈显著相关,可根据这一组合指标进行幼龄栓皮栎叶面积预测模型的建立。②幼龄栓皮栎叶面积预测模型Y=0.595X₁×X₂+257.640最为精确,R²=0.946,标准误差低至32.830 cm²,可以用来预测幼龄栓皮栎叶片的面积。③43个栓皮栎家系间各项叶片指标均有不同程度的变异,不同家系间和家系内叶片差异均较大。④叶片性状与原产地地理信息相关性分析结果表明,除叶干质量与年降水量外,与其他指标均无显著相关性;43个家系不能独立分类,规律性不强。【结论】以叶长宽积为参数,建立了较为精准的幼龄栓皮栎叶面积预测模型Y=0.595X₁×X₂+257.640,为获得栓皮栎叶面积提供了一种高效、无损的方法,为栓皮栎良种培育和家系选择提供理论基础。

Abstract

【Objective】The leaf area prediction model of young Quercus variabilis was established to apply a rapid and nondestructive measurement. The leaf shape variation and difference characteristics of 43 different Q. variabilis families were analyzed to provide a theoretical basis for studying the genetic diversity and breeding of Q. variabilis. 【Method】A total of 43 Q. variabilis families were selected from different regions of China as the research objects. The optimal parameters of the leaf area prediction model were selected through correlation analysis and curve fitting analysis of leaf length, width, length-width ratio, length-width product, and measured leaf area.Through geometric model and curve fitting analysis, the optimal prediction model of the leaf area of young Q. variabilis was screened, and the results were verified. The differences in leaves among different families were analyzed by statistical description, one-way analysis of variance, correlation analysis, and cluster analysis. 【Result】(1) Leaf length-width product (X₁×X₂) was significantly correlated with the leaf area of young Q. variabilis, and the prediction model of leaf area of young Q. variabilis could be established according to this combination index. (2) The leaf area prediction model of young Q. variabilis Y=0.595X₁ ×X₂+257.640 was the most accurate, R²=0.946, and the standard error was as low as 32.830 cm², which could be used to predict the leaf area of young Q. variabilis.(3) The leaf indexes of the 43 Q. variabilis families had different degrees of variation. The differences in leaves among different families and within families were large. (4) The results of the correlation analysis between leaf traits and geographical information of origin showed no significant correlation between other indexes except leaf dry weight and annual precipitation. 43 families could not be classified independently, and the regularity was not strong. 【Conclusion】A more accurate prediction model of the leaf area of young Q. variabilis Y=0.595X₁×X₂+257.640 was established by using leaf length and width product as parameters, which provided an efficient and nondestructive method for obtaining the leaf area of Q. variabilis and provided a theoretical basis for breeding and family selection of Q. variabilis.

导出引用

李慧, 张婉, 常益豪, 等. 幼龄栓皮栎叶面积预测模型建立及应用[J]. 南京林业大学学报（自然科学版）. 2024, 48(5): 246-254 https://doi.org/10.12302/j.issn.1000-2006.202208069

LI Hui, ZHANG Wan, CHANG Yihao, et al. Construction and application of the leaf area prediction model for young Quercus variabilis[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY. 2024, 48(5): 246-254 https://doi.org/10.12302/j.issn.1000-2006.202208069

中图分类号： S792

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