scholarly journals Assessment of genetic divergence for quantitative traits in thermo tolerant tomato (Solanum lycopersicum L.) genotypes

2018 ◽  
Vol 10 (1) ◽  
pp. 55-58
Author(s):  
Manish Kumar ◽  
R. K. Yadav ◽  
T. K. Behera ◽  
Akshay Talukdar ◽  
Manpreet Kour
Keyword(s):  
Principal Component Analysis ◽  
Solanum Lycopersicum ◽  
Quantitative Traits ◽  
Principal Component ◽  
Component Analysis ◽  
Fruit Weight ◽  
Solanum Lycopersicum L ◽  
Wide Range ◽  
Cluster Distance ◽  
Heat Tolerant

In the present study, 21 thermo tolerant tomato (Solanum lycopersicum L.) genotypes were evaluated to delineate the extent of genetic diversity through 10 quantitative traits. The genotypes were categorized into 4 distinct clusters using D2 statistics. Cluster IV had the maximum number (10) of genotypes, where all heat tolerant genotypes grouped together, followed by cluster I (5). Intra cluster analysis revealed that the cluster IV had highest distance, while the inter cluster distance was maximum between cluster III and cluster IV (6.53) indicating the presence of wide range of variability among genotypes of the cluster. Cluster IV recorded maximum cluster mean for yield (579.0), average fruit weight (33.33) and fruit set per cent (54.8) and the cluster III recorded highest mean value for days to 50 percent flowering (67.33). Principal component analysis showed that the first two principal components (PC’s) accounting for 77.6 per cent of total variation. On the basis of inter cluster distance, cluster mean and principal component analysis observed in the present study, a crossing programme involving genotypes from cluster IV will be promising one for developing heat tolerant tomato hybrids.

scholarly journals Assessment of the genetic components and trait associations in diverse set of fieldpea (Pisum sativum L.) genotypes

2015 ◽  
Vol 43 (3) ◽  
pp. 323-330 ◽  
Author(s):  
AK Parihar ◽  
GP Dixit ◽  
V Pathak ◽  
D Singh
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Principal Components ◽  
Agronomic Traits ◽  
Principal Component ◽  
Component Analysis ◽  
Genetic Components ◽  
Wide Range ◽  
Cluster Distance ◽  
Biological Yield

One hundred and 40 genotypes of fieldpea were used to assess the genetic divergence for various agronomic traits. The study revealed that all the accessions were significantly different for the traits and a wide range of variability exists for most of the traits. Correlation studies exhibited that seed yield had positive significant correlation with most of the traits. Cluster analysis classified 140 genotypes into 12 distinct groups. A large number of genotypes (30) were placed in cluster IV followed by cluster III with 24 genotypes. The maximum inter-cluster distance was observed between clusters III and IV indicating the possibility of high heterotic effect if the individuals from these clusters are cross-bred. Principal component analysis yielded 12 Eigen vectors and PCA analysis revealed significant variations among traits with seven major principal components explaining about 90% of variations. The estimates of Eigen value associated with the principal components and their respective relative and accumulated variances explained 50.16% of total variation in the first two components. The characters with highest weight in component first were biological yield, pods/plant, yield/plant and branches/plant which explained 34.22% of the total variance. The results of principal component analysis were closely in line with those of the cluster analysis. The grouping of genotypes and hybridization among genetically diverse genotypes of different cluster would be helpful in broadening the genetic base of fieldpea and producing desirable recombinants for developing new fieldpea varieties. DOI: http://dx.doi.org/10.3329/bjb.v43i3.21605 Bangladesh J. Bot. 43(3): 323-330, 2014 (December)

The use of multivariate analysis in identifying relationships among disorder and mineral element content in apples

1974 ◽  
Vol 25 (5) ◽  
pp. 783 ◽  
Author(s):  
DA Ratkowsky ◽  
D Martin
Keyword(s):  
Principal Component Analysis ◽  
Mineral Content ◽  
Principal Component ◽  
Component Analysis ◽  
Calcium Deficiency ◽  
Fruit Weight ◽  
Wide Range ◽  
Mathematical Techniques ◽  
Using Data ◽  
The Relationship

The use of principal component analysis, followed by rotation of a reduced number of component axes, and its role in the identification and interpretation of relationships between disorder and mineral content in apple research is described. The relationship among bitter pit incidence, calcium deficiency and mean fruit weight per tree is illustrated by using data obtained on Jonathan apples from potted trees. Principal component analysis must be performed on unstructured data, and emphasis is placed upon the removal of treatment and block effects when constructing the correlation matrix upon which the analysis is performed. The mathematical techniques described are applicable to a wide range of agricultural experimentation.

scholarly journals Forensic analysis on printer inks via chemometrics

2021 ◽  
Vol 1192 (1) ◽  
pp. 012029
Author(s):  
L H Mohd Zawawi ◽  
N F Mohamed Azmin ◽  
M F Abd. Wahab ◽  
S I Ibrahim ◽  
M Y Mohd Yunus
Keyword(s):  
Principal Component Analysis ◽  
Digital Media ◽  
Graphical Representation ◽  
Rapid Development ◽  
Principal Component ◽  
Component Analysis ◽  
Forensic Analysis ◽  
Criminal Cases ◽  
Trial Court ◽  
Wide Range

Abstract Printer inks are becoming necessary for utilization for wide range of purposes by society in current times with rapid development in technology and digital media area. Thus, forgery and counterfeiting becoming easier for the criminals. It is dangerous as some criminals will misused the technology by mean of addition and adulteration of parts of text or numbers on document as the inks and document can be made as an evidence in the trial court. Thus, the characterization and differentiation of the printed inks in the suspected documents (civil or criminal cases) may provide important information about the authenticity of the printer inks. The focus of this study to differentiate the chemical component of three different types of sample inks by incorporation of FTIR spectrophotometer with principal component analysis. The unique features of the ink samples were unmasked from the score plots of the principal component analysis. Thus, the graphical representation provided by the FTIR spectra with principal component analysis enabled the discrimination certain chemical in the printer inks.

Evaluating the Performance Degradation of Centrifugal Pumps Using the Principal Component Analysis

2021 ◽  
Author(s):  
Andrew Eaton ◽  
Wael Ahmed ◽  
Marwan A. Hassan
Keyword(s):  
Principal Component Analysis ◽  
Distribution Systems ◽  
Water Distribution ◽  
Principal Component ◽  
Component Analysis ◽  
Performance Degradation ◽  
Centrifugal Pumps ◽  
Pump Performance ◽  
Hydraulic Machines ◽  
Wide Range

Abstract Centrifugal pumps are used in a variety of engineering applications, such as power production, heating, cooling, and water distribution systems. Although centrifugal pumps are considered to be highly reliable hydraulic machines, they are susceptible to a wide range of damage due to several degradation mechanisms, which make them operate away from their best efficiency range. Therefore, evaluating the energy efficiency and performance degradation of pumps is an important consideration to the operation of these systems. In the present study, the hydraulic performance along with the vibration response of an industrial scale centrifugal pump (7.5KW) subjected to different levels of impeller unbalance were experimentally investigated. Extensive testing of pump performance along with vibration measurements were carried. Both time and frequency domain techniques coupled with principal component analysis (PCA) were used in this evaluation. The effect of unbalance on the pump performance was found to be mainly on the shaft power, while no change in the flow rate and the pump head were observed. As the level of unbalance increased, the power required to operate the pump at the designated speed increased by as much as 12%. The PCA found to be a useful tool in comparing the pump vibrations in the field in order to determine the presence of unbalance as well as the degree of damage. The results of this work can be used to evaluate and monitor pump performance under prescribed degradation in order to enhance preventative maintenance programs.

scholarly journals Genetic variability and trait relationship in cherry tomato (Solanum lycopersicum L. var. cerasiforme (Dunnal) A. Gray)

2013 ◽  
Vol 41 (2) ◽  
pp. 163-167 ◽  
Author(s):  
MS Islam ◽  
HC Mohanta ◽  
MR Ismail ◽  
MY Rafii ◽  
MA Malek
Keyword(s):  
Genetic Variability ◽  
Solanum Lycopersicum ◽  
Fruit Weight ◽  
Fruit Yield ◽  
High Yield ◽  
Genetic Advance ◽  
Cherry Tomato ◽  
Solanum Lycopersicum L ◽  
Wide Range ◽  
Additive Gene

Nine traits of 11 cherry tomato (Solanum lycopersicum L.) var. cerasiforme (Dunal) A. Gray) inbred lines exhibited a wide range of genetic variability. High geno- and phenotypic coefficients of variation were obtained for individual fruit weight (68.16 and 74.23%, respectively) followed by number of fruits/plant (58.8 and 68.34%, respectively). High estimates of heritability, genetic advance and genotypic coefficient of variation for the traits of individual fruit weight, number of fruits and clusters/plant were controlled by additive gene action indicating the possibility of selection to improve these characters. Fruit yield/plant showed low heritability along with low genetic advance and did not show significant and positive correlation with the remaining characters. It indicates that improvement of high yield through selection is difficult, rather hybridization can be effective for improving the fruit yield/plant. Among the lines, CH154 produced the highest number of fruits/plant (291) and highest fruit yield (1.89 kg/plant and 63.4 t/ha) and can be selected for cultivation under Bangladesh condition. DOI: http://dx.doi.org/10.3329/bjb.v41i2.13443 Bangladesh J. Bot. 41(2): 163-167, 2012 (December)

QUANTIFICATION OF THE CONTRIBUTION OF FILLER CHARACTERISTICS TO NATURAL RUBBER REINFORCEMENT USING PRINCIPAL COMPONENT ANALYSIS

2018 ◽  
Vol 91 (1) ◽  
pp. 79-96 ◽  
Author(s):  
Cindy S. Barrera ◽  
Alfred B. O. Soboyejo ◽  
Katrina Cornish
Keyword(s):  
Principal Component Analysis ◽  
Carbon Black ◽  
Natural Rubber ◽  
Polymer Composites ◽  
Principal Component ◽  
Component Analysis ◽  
Specific Product ◽  
Industrial Residues ◽  
Explanatory Variables ◽  
Wide Range

ABSTRACT Practical statistical models were developed to quantify individual contributions from characteristics of conventional and non-conventional fillers and predict resulting mechanical properties of both hevea and guayule natural rubber composites. Carbon black N330 and four different agro-industrial residues, namely, eggshells, carbon fly ash, processing tomato peels, and guayule bagasse, were used in this study. Filler characteristics were used as explanatory variables in multiple linear regression analyses. Principal component analysis was used to evaluate correlations among explanatory variables based on their correlation matrices and to transform them into a new set of independent variables, which were then used to generate reliable regression models. Surface area, dispersive component of surface energy, carbon black, and waste-derived filler loading were found to have almost equal importance in the prediction of composite properties. However, models developed for ultimate elongation poorly explained variability, indicating the dependence of this property on other variables. Agro-industrial residues could potentially serve as more sustainable fillers for polymer composites than conventional fillers. This new modeling approach for polymer composites allows the performance of a wide range of different waste-derived fillers to be predicted with minimum laboratory work, facilitating the optimization of compound recipes to address specific product requirements.

scholarly journals Principal Component Analysis of Some Quantitative and Qualitative Traits in Iranian Spinach Landraces

2017 ◽  
Vol 71 (4) ◽  
pp. 307-310
Author(s):  
Mehdi Mohebodini ◽  
Naser Sabaghnia ◽  
Farhad Behtash ◽  
Mohsen Janmohammadi
Keyword(s):  
Principal Component Analysis ◽  
Principal Components ◽  
Quantitative Traits ◽  
Agronomic Traits ◽  
Principal Component ◽  
Component Analysis ◽  
Leaf Width ◽  
Petiole Length ◽  
Qualitative Traits ◽  
Eigen Values

Abstract Landraces of spinach in Iran have not been sufficiently characterised for their morpho-agronomic traits. Such characterisation would be helpful in the development of new genetically improved cultivars. In this study 54 spinach accessions collected from the major spinach growing areas of Iran were evaluated to determine their phenotypic diversity profile of spinach genotypes on the basis of 10 quantitative and 9 qualitative morpho-agronomic traits. High coefficients of variation were recorded in some quantitative traits (dry yield and leaf area) and all of the qualitative traits. Using principal component analysis, the first four principal components with eigen-values more than 1 contributed 87% of the variability among accessions for quantitative traits, whereas the first four principal components with eigen-values more than 0.8 contributed 79% of the variability among accessions for qualitative traits. The most important relations observed on the first two principal components were a strong positive association between leaf width and petiole length; between leaf length and leaf numbers in flowering; and among fresh yield, dry yield and petiole diameter; a near zero correlation between days to flowering with leaf width and petiole length. Prickly seeds, high percentage of female plants, smooth leaf texture, high numbers of leaves at flowering, greygreen leaves, erect petiole attitude and long petiole length are important characters for spinach breeding programmes.

A strategy for selecting diverse accessions using Principal Component Analysis from a large germplasm collection of soybean

2003 ◽  
Vol 1 (2-3) ◽  
pp. 151-156 ◽  
Author(s):  
R. L Sapra ◽  
S. K. Lal
Keyword(s):  
Principal Component Analysis ◽  
Sample Size ◽  
Principle Component Analysis ◽  
Quantitative Traits ◽  
Germplasm Collection ◽  
Principal Component ◽  
Target Population ◽  
Component Analysis ◽  
Principle Component ◽  
The Individual

AbstractWe suggest a diversity-dependent strategy, based on Principle Component Analysis, for selecting distinct accessions/parents for breeding from a soybean germplasm collection comprising of 463 lines, characterized and evaluated for 10 qualitative and eight quantitative traits. A sample size of six accessions included all the three states, namely low, medium and high of the individual quantitative traits, while a sample of 16–19 accessions included all the 60–64 distinct states of qualitative as well as quantitative traits. Under certain assumptions, the paper also develops an expression for estimating the size of a target population for capturing maximum variability in a sample three accessions.

Sign in / Sign up

Export Citation Format

Share Document