基于叶形分类的淡竹叶面积预测模型研究

编号 lyqk008110

中文标题 基于叶形分类的淡竹叶面积预测模型研究

作者 谈丽华  巫娟  胡姝珍  谈太腾  武红燕  张振烨  施建敏 

作者单位 1. 江西省瑞昌市林业局 江西瑞昌 332200;
2. 江西农业大学林学院 南昌 330045;
3. 江西省竹子种质资源与利用重点实验室 南昌 330045

期刊名称 世界竹藤通讯 

年份 2020 

卷号 18

期号 1

栏目名称 学术园地 

中文摘要 竹子叶片极易卷曲的特性增加了叶面积测量的难度，本研究致力于建立淡竹快速、便捷、准确测量叶片面积的模型。通过对淡竹叶片的形态特点进行分类，将叶面积仪测量面积作为对照，利用叶长、叶宽数据和扫描实际叶面积进行建模，并采用均方根误差、残差平方和、预测精度来检验模型的精度。结果表明：1）根据淡竹叶片的长宽比将叶片分为3类：长宽比≤ 5.770，5.770<长宽比≤ 6.682，长宽比>6.682；2）形态学指标相关性显示，淡竹叶片长宽积与叶面积相关性最大，相关系数为0.990；3）以叶片长宽的积建立了叶形分类拟合模型，模型的预测精度为97.11%，其预测结果优于整体拟合和叶面积仪测量结果。研究提出的淡竹叶片面积分类拟合模型可快速、准确地预测叶片面积，解决了淡竹叶片面积测量难的问题，为淡竹相关的生态学研究和经营生产提供了基础。

关键词 叶面积  预测模型  叶形态  淡竹 

基金项目 国家大学生创新基金训练项目（201910410018）；江西省重点研发计划项目（20161BBF60082）。

英文标题 Leaf Area Predicting Model for Phyllostachys glauca Based on Leaf Morphology Classification

作者英文名 Tan Lihua, Wu Juan, Hu Shuzhen, Tan Taiteng, Wu Hongyan, Zhang Zhenye, Shi Jianmin

单位英文名 1. Ruichang Forestry Bureau of Jiangxi Province, Ruichang 332200, Jiangxi, China;
2. College of Forestry, Jiangxi Agricultural University, Nanchang 330045, China;
3. Jiangxi Provincial Key Laboratory for Bamboo Germplasm Resources and Utilization, Nanchang 330045, China

英文摘要 Bamboo leaves being very easy to curl increases the difficulty of leaf area measurement. This study is to establish a rapid, convenient and accurate measurement model of leaf area for Phyllostachys glauca. Based on the classification of leaf shapes, leaf length and leaf width, we build a model to predict leaf area, taking the area measured by leaf area meter as the control. The root mean square error, residual sum of squares and predicted precision are then used to test the errors and the goodness of the model. The results show that:1) According to the length-to-width ratio, Ph. glauca leaves can be divided into three types, whose ratios are ≤ 5.770, in the range of 5.770-6.682 and >6.682, respectively; 2) The correlation of morphological indexes shows that the length-width product of leaves is significantly correlated with leaf area, with the correlation coefficient at 0.990; 3) The classified fitting model of Ph. glauca incorporating leaf shape types is based on the product of leaf length and width, with the predicting precision at 97.11%. The prediction outcomes are better than the whole fitting model and the measurements of the leaf area meter. The classified fitting model of leaf area proposed in this study can quickly and accurately predict leaf area only by measuring the length and width of leaves. It solves the difficulty of leaf area measurement and provides a solution for the ecological research and the management and production of Ph. glauca.

英文关键词 leaf area;prediction model;leaf shape;Phyllostachys glauca