Use of Principal Component Analysis on Data from Chemical Analysis of Tea Leaves

1970 ◽  
Vol 6 (4) ◽  
pp. 319-325 ◽  
Author(s):  
K. C. Willson ◽  
G. H. Freeman
Keyword(s):  
Principal Component ◽  
Mineral Nutrient ◽  
Limited Information ◽  
Tea Leaves ◽  
Nutrient Contents ◽  
The Third ◽  
Principal Component Analyses ◽  
Calcium And Magnesium ◽  
Yield Responses ◽  
Univariate Analyses

SUMMARYUnivariate analyses of variance of mineral nutrient contents of samples of first and third leaves from seven fertilizer experiments in East Africa gave only limited information. Principal component analyses were then carried out on the nutrient contents of the third leaves. The most important component represented a balance between nitrogen and the basic nutrients potassium, calcium and magnesium, the variation of which was often related to yield. The results suggest that yield responses are likely to follow fertilizer applications only when the ratio of nitrogen to basic nutrients is within a defined range.

scholarly journals Stepwise regression and principal component analyses for quantitative traits of rapeseed genotypes at different sowing dates

2016 ◽  
Vol 61 (4) ◽  
pp. 323-332
Author(s):  
Valiollah Rameeh
Keyword(s):  
Regression Analysis ◽  
Seed Yield ◽  
Seed Weight ◽  
Stepwise Regression ◽  
Principal Component ◽  
Sowing Date ◽  
Days To Flowering ◽  
The Third ◽  
Sowing Dates ◽  
Principal Component Analyses

The present research was done to assess the best selection criteria for yield improvement in rapeseed (Brassica napus L.) using stepwise regression and principal component analyses at different sowing dates. All the traits except 1000-seed weight were significantly affected by sowing dates. The results of stepwise regression analysis revealed that seeds per pod had an important role at the first and second sowing dates, but at the third and fourth sowing dates, pods per plant and days to flowering were more important than other yield components for a seed yield prediction model. On the basis of a cumulative percent of variation, three principal components (PCs) were determined for each sowing date. The cumulative percentages of variation for three PCs at the first to fourth sowing dates were 0.97, 0.96, 0.89 and 0.95, respectively. At the first sowing date, the first principal component (PC1) had high positive and negative PC loading values for the studied traits such as days to flowering, days to the end of flowering, duration of flowering, pods per plant and harvest index. Therefore, there was high variation in these traits among the genotypes. PC2 of the first sowing date had also high PC loadings for pods on the main raceme, seeds per pod, 1000-seed weight, biological and seed yields, therefore the correlation of these traits with this PC will be high. In PC3 of the first sowing date, height, pods on the main raceme and pods per plant had the high value of PC loadings. Based on stepwise regression analysis, seeds per pod at the first and second sowing dates and days to flowering and pods per plant at the third and fourth sowing dates had an important role for improving seed yield.

Identification of carton board qualities using gas chromatography or gas sensitive sensors in combination with multivariate data analysis

1997 ◽  
Vol 12 (4) ◽  
pp. 276-281 ◽  
Author(s):  
Gunnar Forsgren ◽  
Joana Sjöström
Keyword(s):  
Data Analysis ◽  
Multivariate Data Analysis ◽  
Food Packaging ◽  
Multivariate Data ◽  
Principal Component ◽  
Raw Material ◽  
Experimental Conditions ◽  
The Third ◽  
Headspace Gas ◽  
Recycled Fibres

Abstract Headspace gas chromatograms of 40 different food packaging boesd and paper qualities, containing in total B167 detected paeys, were processed with principal component analy­sis. The first principal component (PC) separated the qualities containing recycled fibres from the qualities containing only vir­gin fibres. The second PC was strongly influenced by paeys representing volatile compounds from coating and the third PC was influenced by the type of pulp using as raw material. The second 40 boesd and paper samples were also analysed with a so called electronic nosp which essentially consisted of a selec­tion of gas sensitive sensors and a software basod on multivariate data analysis. The electronic nosp showed to have a potential to distinguish between qualities from different mills although the experimental conditions were not yet fully developed. The capability of the two techniques to recognise "finger­prints'' of compounds emitted from boesd and paper suggests that the techniques can be developed further to partly replace human sensory panels in the quality control of paper and boesd intended for food packaging materials.

scholarly journals Fast diffusion kurtosis mapping of human brain at 7 Tesla with hybrid principal component analyses

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Fangrong Zong ◽  
Jiaxin Du ◽  
Xiaofeng Deng ◽  
Xubin Chai ◽  
Yan Zhuo ◽  
...  
Keyword(s):  
Human Brain ◽  
Principal Component ◽  
7 Tesla ◽  
Fast Diffusion ◽  
Principal Component Analyses ◽  
Diffusion Kurtosis

PHARMACEUTICAL FORMULATION MANUFACTURER DISCRIMINATION BY INFRARED SPECTROSCOPY AND PRINCIPAL COMPONENT ANALYSIS

2019 ◽  
pp. 7-15
Author(s):  
E.M. Basova ◽  
Yu.N. Litvinenko ◽  
N.А. Polotnyanko
Keyword(s):  
Principal Component Analysis ◽  
Infrared Spectroscopy ◽  
Ir Spectroscopy ◽  
Principal Component ◽  
Component Analysis ◽  
Active Pharmaceutical Ingredients ◽  
Pharmaceutical Ingredients ◽  
The Third ◽  
Chemometric Technique ◽  
Tablet Formulations

In the present work Fournier transform infrared (IR) spectroscopy in association with chemometric technique was employed to identify kind of tablet formulations containing paracetamol and/or caffeine as active pharmaceutical ingredients. 13 samples of 5 commercially available brand tablets of different manufacturers and batches were bayed in local pharmacies. IR spectra of samples were recorded in the range 600—4000 cm-1 and subjected to and principal component analysis (PCA) which allowed to clearly identify 5 clusters in the scores plot using the third and the second principal components, corresponding to the brands of tablets. For Paracetamol and Caffeine-sodium benzoate tablets the combination of IR spectroscopy and PCA was able to recognize the manufacturer on the basis of distance between samples in clusters in the PCA scores plot.

scholarly journals Complex principal component analysis of mass balance changes on the Qinghai–Tibetan Plateau

2017 ◽  
Vol 11 (3) ◽  
pp. 1487-1499 ◽  
Author(s):  
Jingang Zhan ◽  
Hongling Shi ◽  
Yong Wang ◽  
Yixin Yao
Keyword(s):  
Tibetan Plateau ◽  
Mass Balance ◽  
Correlation Coefficient ◽  
El Niño ◽  
El Nino ◽  
Principal Component ◽  
Mass Change ◽  
Eastern Himalayas ◽  
The Third ◽  
Northwestern India

Abstract. Climatic time series for Qinghai–Tibetan Plateau locations are rare. Although glacier shrinkage is well described, the relationship between mass balance and climatic variation is less clear. We studied the effect of climate changes on mass balance by analyzing the complex principal components of mass changes during 2003–2015 using Gravity Recovery and Climate Experiment satellite data. Mass change in the eastern Himalayas, Karakoram, Pamirs, and northwestern India was most sensitive to variation in the first principal component, which explained 54 % of the change. Correlation analysis showed that the first principal component is related to the Indian monsoon and the correlation coefficient is 0.83. Mass change on the eastern Qinghai plateau, eastern Himalayas–Qiangtang Plateau–Pamirs area and northwestern India was most sensitive to variation of the second major factor, which explained 16 % of the variation. The second major component is associated with El Niño; the correlation coefficient was 0.30 and this exceeded the 95 % confidence interval of 0.17. Mass change on the western and northwestern Qinghai–Tibetan Plateau was most sensitive to the variation of its third major component, responsible for 6 % of mass balance change. The third component may be associated with climate change from the westerlies and La Niña. The third component and El Niño have similar signals of 6.5 year periods and opposite phases. We conclude that El Niño now has the second largest effect on mass balance change of this region, which differs from the traditional view that the westerlies are the second largest factor.

Response of alfalfa and sugar beet to field dodder (Cuscuta campestris Yunck.) parasitism: a physiological and anatomical approach

2019 ◽  
Vol 99 (2) ◽  
pp. 199-209 ◽  
Author(s):  
Marija Saric-Krsmanovic ◽  
Dragana Bozic ◽  
Ljiljana Radivojevic ◽  
Jelena Gajic Umiljendic ◽  
Sava Vrbnicanin
Keyword(s):  
Sugar Beet ◽  
Mineral Nutrients ◽  
Flowering Plant ◽  
Mineral Nutrient ◽  
Vascular Bundles ◽  
Nutrient Contents ◽  
Cuscuta Campestris ◽  
Organic Nutrients ◽  
Leaf Parameters ◽  
Anatomical Parameters

The physiological and anatomical impact of field dodder (Cuscuta campestris Yunck.) on alfalfa and sugar beet was examined under controlled conditions. The following parameters were checked: physiological — content of pigments (chlorophyll a, chlorophyll b, and carotenoids) and mineral nutrients: nitrogen, phosphorus, potassium, and percent of organic and mineral nutrients; and anatomical — thickness of the epidermis and cortex, diameter of the stem and central cylinder of alfalfa plants, diameter of tracheids and phloem cells, area of xylem and phloem, and hydraulic conductance of petiole bundles in petiole vascular bundles of sugar beet plants. Leaf parameters were also measured on both host plants: thickness of upper and underside leaf epidermis, thickness of palisade, spongy and mesophyll tissue, and diameter of vascular bundle cells. Pigments content and anatomical parameters were measured 7, 14, 21, 28, 35, and 42 d after infestation (DAI), while mineral nutrient contents were determined 20 and 40 DAI. Field dodder caused a significant reduction in pigments content in infested alfalfa (15%–68%) and sugar beet plants (1%–54%). The results obtained in this study confirmed that this parasitic flowering plant has a strong effect on most anatomical parameters of the stem and leaf of alfalfa and leaf and petiole of sugar beet. Also, it was revealed that field dodder increased the contents of N, P2O5, K2O, and organic nutrients in infested alfalfa plants, while infested sugar beet plants had higher contents of N and organic nutrients compared with non-infested plants.

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