长沙市典型园林植物叶片的滞尘等级与模式识别研究

doi:10.16258/j.cnki.1674-5906.2022.01.013

生态环境学报 ›› 2022, Vol. 31 ›› Issue (1): 110-116.DOI: 10.16258/j.cnki.1674-5906.2022.01.013

长沙市典型园林植物叶片的滞尘等级与模式识别研究

廖慧敏(), 师凤起^*(), 李明, 朱逸龙

中南大学资源与安全工程学院,湖南长沙 410083

收稿日期:2021-08-14 出版日期:2022-01-18 发布日期:2022-03-10
通讯作者: *师凤起（1997年生）,女,硕士研究生,主要从事环境安全研究。E-mail: 1036689835@qq.com
作者简介:廖慧敏（1977年生）,女,副研究员,硕士研究生导师,主要从事安全与环保方向研究。E-mail: liaohuimin201@csu.edu.cn
基金资助:
国家自然科学基金项目(51704328);国家自然科学基金项目(51674289)

Study on Dust Retention Rank and Pattern Recognition of Typical Garden Plant Leaves in Changsha

LIAO Huimin(), SHI Fengqi^*(), LI Ming, ZHU Yilong

School of Resources and Safety Engineering, Central South University, Changsha 410083, P. R. China

Received:2021-08-14 Online:2022-01-18 Published:2022-03-10

摘要/Abstract

摘要：

基于长沙市10种典型植物叶片的多个滞尘指标,运用模糊数学理论构建植物的滞尘等级与识别模型,实现绿化植物滞尘综合量化评判方法的探究。首先,常规方法采集叶样后,运用打孔称质量法测量叶表面积参数,显微观察法计算植物叶表气孔与绒毛密度,干洗法测量单位叶面积最大滞尘量与自然滞尘量。然后,运用模糊聚类理论对10种植物滞尘指标进行滞尘等级划分与模式识别。模糊聚类将9种植物叶片的滞尘指标分为7个不同λ水平的聚类。其中λ为0.907时,F检验值为21.41,滞尘指标间差异最显著。9种植物滞尘指标聚为4种最优,9种植物可对应划分为低、中、较高与高4个滞尘等级,即金叶女贞（Ligustrum×vicaryi）滞尘等级最高,红花檵木（Loropetalum chinense）滞尘等级较高,瓜子黄杨（Buxus sinica）、金边黄杨（Euonymus japonicus）与红叶石楠（Photinia×fraseri）3种植物滞尘等级为中等,海桐（Pittosporum tobira）、冬青（Ilex chinensis）、月季（Rosa chinensis）、杜鹃花（Rhododendron simsii）滞尘等级最低。第10种植物小蜡在模式识别中辨识为中等滞尘等级。滞尘等级与模式识别结论与相关研究基本相符,模糊聚类构建的绿化植物叶片滞尘等级模式识别方法具有可操作性,可为绿化植物叶片滞尘效果综合量化评价提供新思路。

关键词: 园林植物, 滞尘等级, 模糊聚类, 模式识别, 贴近度, 单位叶面积

Abstract:

Based on multiple dust retention indexes of 10 typical plant leaves in Changsha, the dust retention rank and pattern recognition model of plants are constructed by using the fuzzy mathematics theory. In addition, a comprehensive quantitative evaluation of dust retention of greening plants was performed. Firstly, after leaf samples were collected by conventional methods, leaf surface area parameters were measured by the drilling and weighing method; the densities of pores and fluff on plant leaf surface were calculated by the microscopic observation method; and the maximum dust retention per unit leaf area and natural dust retention were measured by the dry-cleaning method. Then, the dust retention rank and pattern recognition of 10 plant dust retention indexes were carried out by using the fuzzy clustering theory. The dust retention indexes of 9 plants were divided into 7 clusters with different λ levels by using fuzzy clustering. When it was 0.907, the F test value was 21.41, and the difference between dust retention indexes was more evident. The dust retention indexes of 9 plants were the best and 9 plants could be divided into 4 dust retention ranks: low, medium, higher and the highest, in that, Ligustrum×vicaryi has the highest dust retention rank, Loropetalum chinense has a higher dust retention rank, Buxus sinica, Euonymus japonicus and Photinia×fraseri have a medium dust retention rank, and Pittosporum tobira, Llex chinensis, Rosa chinensis and Rhododendron simsii have the lowest dust retention rank. The 10th plant wax was identified as a medium dust retention rank based on pattern recognition. The dust retention rank and pattern recognition conclusion are basically consistent with previous research. The pattern recognition method of dust retention rank of greening plant leaves constructed by fuzzy clustering is viable and can provide a new perspective for a comprehensive quantitative evaluation of dust retention of greening plant leaves.

Key words: garden plants, dust retention rank, fuzzy cluster, pattern recognition, close degree, unit leaf area

中图分类号:

X513

廖慧敏, 师凤起, 李明, 朱逸龙. 长沙市典型园林植物叶片的滞尘等级与模式识别研究[J]. 生态环境学报, 2022, 31(1): 110-116.

LIAO Huimin, SHI Fengqi, LI Ming, ZHU Yilong. Study on Dust Retention Rank and Pattern Recognition of Typical Garden Plant Leaves in Changsha[J]. Ecology and Environment, 2022, 31(1): 110-116.

图/表 5

参考文献 28

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植物名称 Plant name	叶表面积 Leaf surface area/cm²	指标排序 Index order	气孔密度 stomata density/ (ind∙mm^-2)	指标排序 Index order	绒毛密度 Pubescence density/ (ind∙mm^-2)	指标排序 Index order	单位叶面积自然滞尘量 Natrual dust retention amount per unit leaf area/(g∙m^-2)	指标排序 Index order	单位叶面积最大滞尘量 Maximum dust retretention amount per unit leaf area/ (g∙m^-2)	指标排序 Index order
海桐 Pittosporum tobira	16.51	6	184	8	0	6	0.85	7	3.36	9
红花檵木 Loropetalum chinense	7.23	10	350	2	907	1	1.13	5	6.12	6
瓜子黄杨 Buxus sinica	20.58	4	247	4	0	6	1.14	4	7.27	3
金叶女贞 Ligustrum×vicaryi	10.13	8	800	1	234	4	1.59	1	9.54	1
金边黄杨 Euonymus japonicus	7.04	9	233	6	0	6	1.35	2	8.19	2
冬青 Llex chinensis	30.92	1	245	5	0	6	0.63	9	3.09	8
月季 Rosa chinensis	25.79	2	122	10	0	6	0.44	10	2.22	10
杜鹃花 Rhododendron simsii	12.93	7	168	9	163	5	0.82	8	4.17	7
红叶石楠 Photinia×fraseri	21.27	3	212	7	320	2	1.16	3	7.26	4
小蜡 Ligustrum sinense	19.46	5	330	3	295	3	0.98	6	6.37	5

植物名称 Plant name	叶表面积 Leaf surface area/cm²	指标排序 Index order	气孔密度 stomata density/ (ind∙mm^-2)	指标排序 Index order	绒毛密度 Pubescence density/ (ind∙mm^-2)	指标排序 Index order	单位叶面积自然滞尘量 Natrual dust retention amount per unit leaf area/(g∙m^-2)	指标排序 Index order	单位叶面积最大滞尘量 Maximum dust retretention amount per unit leaf area/ (g∙m^-2)	指标排序 Index order
海桐 Pittosporum tobira	16.51	6	184	8	0	6	0.85	7	3.36	9
红花檵木 Loropetalum chinense	7.23	10	350	2	907	1	1.13	5	6.12	6
瓜子黄杨 Buxus sinica	20.58	4	247	4	0	6	1.14	4	7.27	3
金叶女贞 Ligustrum×vicaryi	10.13	8	800	1	234	4	1.59	1	9.54	1
金边黄杨 Euonymus japonicus	7.04	9	233	6	0	6	1.35	2	8.19	2
冬青 Llex chinensis	30.92	1	245	5	0	6	0.63	9	3.09	8
月季 Rosa chinensis	25.79	2	122	10	0	6	0.44	10	2.22	10
杜鹃花 Rhododendron simsii	12.93	7	168	9	163	5	0.82	8	4.17	7
红叶石楠 Photinia×fraseri	21.27	3	212	7	320	2	1.16	3	7.26	4
小蜡 Ligustrum sinense	19.46	5	330	3	295	3	0.98	6	6.37	5

λ值 λ value	分类数 (r) Classification number (r)	F值 F value	自由度 (r-1, n-r) Degrees of freed (r-1, n-r)	F_0.05	F_0.01
0.951	8	10.56	7, 1	236	5928
0.933	7	16.41	6, 2	19.33	99.33
0.922	6	8.09	5, 3	9.01	28.24
0.910	5	10.72^*	4, 4	6.39	15.98
0.907	4	21.41^**	3, 5	5.41	12.06
0.896	3	16.36^**	2, 6	5.14	10.92
0.869	2	2.85	1, 7	5.59	12.25

λ值 λ value	分类数 (r) Classification number (r)	F值 F value	自由度 (r-1, n-r) Degrees of freed (r-1, n-r)	F_0.05	F_0.01
0.951	8	10.56	7, 1	236	5928
0.933	7	16.41	6, 2	19.33	99.33
0.922	6	8.09	5, 3	9.01	28.24
0.910	5	10.72^*	4, 4	6.39	15.98
0.907	4	21.41^**	3, 5	5.41	12.06
0.896	3	16.36^**	2, 6	5.14	10.92
0.869	2	2.85	1, 7	5.59	12.25

滞尘指标与贴近度 Dust-retention index and close degree	滞尘等级模型 Dust retention models				待识别样本 Identified sample
滞尘指标与贴近度 Dust-retention index and close degree	U₈ (杜鹃花) U₈ (Rhododendron simsii)	U₃ (瓜子黄杨) U₃ (Buxus sinica)	U₂ (红花檵木) U₂ (Loropetalum chinense)	U₄ (金叶女贞) U₄ (Ligustrum×vicaryi)	U₀ (小蜡) U₀(Ligustrum sinense)
叶表面积 Leaf surface are	0.25	0.57	0.01	0.14	0.52
气孔密度 Stomata density	0.07	0.18	0.34	1.00	0.31
绒毛密度 Pubescence density	0.18	0.00	1.00	0.26	0.33
单位叶面积自然滞尘量 Natrual dust retention amount per unit leaf area	0.33	0.61	0.60	1.00	0.47
单位叶面积最大滞尘量 Maximum dust retretention amount per unit leaf area	0.27	0.69	0.53	1.00	0.57
贴近度 Close degree	0.51	0.63	0.60	0.62

长沙市典型园林植物叶片的滞尘等级与模式识别研究

Study on Dust Retention Rank and Pattern Recognition of Typical Garden Plant Leaves in Changsha

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