scholarly journals Principal Component Analysis of Chlorophyll Content in Tobacco, Bean and Petunia Plants Exposed to Different Tropospheric Ozone Concentrations

2014 ◽  
Vol 12 (1) ◽  
pp. 5-16 ◽  
Author(s):  
Klaudia Borowiak ◽  
Janina Zbierska ◽  
Anna Budka ◽  
Dariusz Kayzer
Keyword(s):  
Principal Component Analysis ◽  
Chlorophyll Content ◽  
Plant Species ◽  
Ozone Concentration ◽  
Tropospheric Ozone ◽  
Principal Component ◽  
Ambient Air ◽  
Component Analysis ◽  
Chlorophyll Contents ◽  
Ozone Concentrations

Abstract Three plant species were assessed in this study - ozone-sensitive and -resistant tobacco, ozone-sensitive petunia and bean. Plants were exposed to ambient air conditions for several weeks in two sites differing in tropospheric ozone concentrations in the growing season of 2009. Every week chlorophyll contents were analysed. Cumulative ozone effects on the chlorophyll content in relation to other meteorological parameters were evaluated using principal component analysis, while the relation between certain days of measurements of the plants were analysed using multivariate analysis of variance. Results revealed variability between plant species response. However, some similarities were noted. Positive relations of all chlorophyll forms to cumulative ozone concentration (AOT 40) were found for all the plant species that were examined. The chlorophyll b/a ratio revealed an opposite position to ozone concentration only in the ozone-resistant tobacco cultivar. In all the plant species the highest average chlorophyll content was noted after the 7th day of the experiment. Afterwards, the plants usually revealed various responses. Ozone-sensitive tobacco revealed decrease of chlorophyll content, and after few weeks of decline again an increase was observed. Probably, due to the accommodation for the stress factor. While during first three weeks relatively high levels of chlorophyll contents were noted in ozone-resistant tobacco. Petunia revealed a slow decrease of chlorophyll content and the lowest values at the end of the experiment. A comparison between the plant species revealed the highest level of chlorophyll contents in ozone-resistant tobacco.

scholarly journals Data-driven regionalization for analyzing the spatiotemporal characteristic of air quality in China

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Sheng Li ◽  
Jiangtao Liu ◽  
Chao Wu
Keyword(s):  
Principal Component Analysis ◽  
Air Pollution ◽  
Cluster Analysis ◽  
Air Quality ◽  
Principal Component ◽  
Ambient Air ◽  
Component Analysis ◽  
Data Driven ◽  
Regional Collaboration ◽  
The Government

<p><strong>Abstract.</strong> With the development of urbanization and industrialization, the degradation of ambient air quality has become a serious issue that impacts human health and the environment; thus, it has attracted more attention from scholars. Usually, the mass concentrations of sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3) and particulate matter with an aerodynamic diameter less than 10&amp;thinsp;&amp;mu;m and 2.5&amp;thinsp;&amp;mu;m (PM10 and PM2.5) are used to evaluate air quality. A commonly used data-driven regionalization framework for studying air quality issues, identifying areas with similar air pollution behavior and locating emission sources involves an incorporation of the principal component analysis (PCA) with cluster analysis (CA) methods. However, the traditional PCA does not consider spatial variations, which is a notable issue in geographic studies. This article focuses on extracting the local principal components (PCs) of air quality indicators based on a geographically weighted principal component analysis (GWPCA), which is superior to the PCA when considering spatial heterogeneity. Then, a spatial cluster analysis (SCA) is used to identify the areas with similar air pollution behavior based on the results of the GWPCA. The results are all visualized and show that the GWPCA has a higher explanatory ability than the traditional PCA. Our modified framework based on the GWPCA and SCA for assessing air quality can effectively guide environmentalists and geographers in evaluating and improving air quality from a new perspective. Furthermore, the visualization results can be used by city planners and the government for monitoring and managing air pollution. Finally, policy suggestions are recommended for mitigating air pollution via regional collaboration.</p>

Temporal variations in ozone concentrations derived from Principal Component Analysis

2007 ◽  
Vol 92 (1-2) ◽  
pp. 47-58 ◽  
Author(s):  
S. Yonemura ◽  
S. Kawashima ◽  
H. Matsueda ◽  
Y. Sawa ◽  
S. Inoue ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Temporal Variations ◽  
Ozone Concentrations

scholarly journals Identification of Tropical Plants Leaves Image Base on Principal Component Analysis

2020 ◽  
Vol 4 (1) ◽  
pp. 64-75
Author(s):  
Indra Laksmana ◽  
Hendra Hendra ◽  
Sri Aulia Novita ◽  
Fithra Herdian ◽  
Mohamad Riza Nurtam ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Plant Species ◽  
Mangifera Indica ◽  
Leaf Shape ◽  
Principal Component ◽  
Component Analysis ◽  
Persea Americana ◽  
Commission Error ◽  
Tropical Plants ◽  
Durio Zibethinus

Difference and variation of leaves shape is usually used as primary identifier of the plant species. But some plants may have a similar leaf shape and thus require another more accurate identifier. This study applied principal component analysis (PCA) methods for identifying tropical plant species from the shape of the leaves. This method simplified the observed variables by reducing the dimensions of the information that is stored as much as 75%, so it did not eliminate important information and can save the data processing time. There were 100 images of leaves taken from several sides of the leaf in JPEG format with which the shape of leaves were look similar, like citrus (Citrus aurantifolia), durian (Durio zibethinus), guava (Psidium guajava), mango (Mangifera indica), jackfruit (Artocarpus heterophyllus), avocado (Persea americana), rambutan (Nephelium lappaceum), sapodilla (Manilkara zapota), red betel (Piper crocatum) and soursop (Annona muricata). Identification of those 10 kind plant leaves produced 97% accuracy rate. Measurement systems were designed using the K-fold Cross Validation with k = 10, the results of experiments shown omission error occurs on the leaves of guava, jackfruit and red betel while twice commission error were found on the leaves sapodilla and once on citrus leaves.

scholarly journals ANÁLISE DAS COMPONENTES PRINCIPAIS NO PROCESSO DE MONITORAMENTO AMBIENTAL

Nativa ◽  
2018 ◽  
Vol 6 (6) ◽  
pp. 639 ◽  
Author(s):  
Amaury De Souza ◽  
Débora Aparecida da Silva Santos
Keyword(s):  
Principal Component Analysis ◽  
Nitrogen Oxides ◽  
Principal Component ◽  
Barometric Pressure ◽  
Ambient Air ◽  
Component Analysis ◽  
Time Of Day ◽  
Mato Grosso ◽  
Mean Values ◽  
Mato Grosso Do Sul

O presente trabalho apresenta os resultados da medição das concentrações de ozônio, óxidos de nitrogênio (NO, NO2 e NOx) e SO2 em ar ambiente em paralelo com o registro dos parâmetros meteorológicos: temperatura, radiação solar, umidade relativa, pressão barométrica, velocidade e direção do vento durante o ano de 2015. As medições foram efetuadas na estação de medição situada dentro do campus da Universidade Federal de Mato Grosso do Sul. Os resultados são apresentados neste trabalho como valores médios em relação ao tempo do dia. Diversas correlações da concentração de ozônio vs. observação atmosféricos foram feitas, juntamente com a Análise de Componentes Principais. A análise estatística dos dados obtidos, com base na Análise de Componentes Principais (ACP), levou a que 73,2% da variância dos valores medidos pudessem ser descritos com quatro fatores. Foi determinado um alto grau de intercorrelação de NOx. Estes poluentes foram todos agrupados no fator 1 e 2, que descreveu 54,6% de variâncias dos valores medidos.Palavras-chave: poluentes, ozônio, óxidos de nitrogênio. PRINCIPAL COMPONENT ANALYSIS IN THE ENVIRONMENTAL MONITORING PROCESS ABSTRACT: The present work presents the results of measuring the concentrations of ozone, nitrogen oxides (NO, NO2 and NOx) and SO2 in ambient air in parallel with the recording of meteorological parameters: temperature, solar radiation, relative humidity, barometric pressure, velocity and Wind direction during the year 2015. The measurements were taken at the measuring station located inside the campus of the Federal University of Mato Grosso do Sul. The results are presented in this work as mean values in relation to the time of day. Several correlations of the ozone concentration vs. Atmospheric observations were made along with Principal Component Analysis. Statistical analysis of the data obtained, based on Principal Component Analysis (PCA), led to 73.2% of the variance of the measured values could be described with four factors. A high degree of NOx intercorrelation was determined. These pollutants were all grouped in factor 1 and 2, which described 54.6% of variances of the measured values.Keywords: pollutants, ozone, nitrogen oxides.

Sign in / Sign up

Export Citation Format

Share Document