scholarly journals MORPHOMETRIC CHARACTER AND MORPHOLOGY OF ABALONE Haliotis squamata REEVE 1864 IN COASTAL SOUTHERN JAVA AND BALI

2019 ◽  
Vol 11 (2) ◽  
pp. 273-284
Author(s):  
Syamsul Bachry ◽  
Dedy Duryadi Solihin ◽  
Rudhy Gustiano ◽  
Kadarwan Soewardi ◽  
Nurlisa A. Butet
Keyword(s):  
Discriminant Analysis ◽  
Sampling Method ◽  
Morphological Characteristics ◽  
Principal Component ◽  
Canonical Discriminant Analysis ◽  
Shell Morphology ◽  
Morphometric Character ◽  
Color Patterns ◽  
And Cluster Analysis ◽  
Key Characters

The standard of measurement of abalone is very important because it can help to identify accurately abalone shellfish based on shell morphology. This research was aimed to examine the truss morphometric and morphologycal characters of Haliotis squamata intraspecies in the southern coastal Java and Bali. The research was conducted from December 2014 to August 2016. Abalone was collected based on the purposive sampling method, it was then identified. The shellfish of abalone was measured and analyzed by using principal component analysis (PCA), canonical discriminant analysis and cluster analysis. The results showed that PCA was able to separate Haliotis squamata populations from Java and Bali using combination of PCIII and PCIV based on the factor coefficient values. The key characters that separated Haliotis squamata from the population of Java and Bali were the combination of characters BF (0.535) for PCIII and characters CH (0.522) for PCIV. Canonical discriminant analysis showed that Bali was the highest sharing component value (100%) of intra population and also the lowest sharing component of inter population (0%). The highest percentage of similarity was 99.91% that indicated the population of Binuangeun and Pangandaran, while the lowest was 99.31% for the population of Banyuwangi and Bali. The morphological characteristics of Haliotis squamata species in several locations showed specific characters such as color patterns, textures and shapes.

scholarly journals Morphological evaluation of common bean diversity in Bosnia and Herzegovina using the discriminant analysis of principal components (DAPC) multivariate method

Genetika ◽  
2013 ◽  
Vol 45 (3) ◽  
pp. 963-977 ◽  
Author(s):  
Jasmin Grahic ◽  
Fuad Gasi ◽  
Mirsad Kurtovic ◽  
Lutvija Karic ◽  
Mirha Djikic ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Common Bean ◽  
Bosnia And Herzegovina ◽  
Principal Components ◽  
Morphological Characteristics ◽  
Principal Component ◽  
Discriminant Functions ◽  
Factor Loadings ◽  
Geographical Regions ◽  
High Level

In order to analyze morphological characteristics of locally cultivated common bean landraces from Bosnia and Herzegovina (B&H), thirteen quantitative and qualitative traits of 40 P. vulgaris accessions, collected from four geographical regions (Northwest B&H, Northeast B&H, Central B&H and Sarajevo) and maintained at the Gene bank of the Faculty of Agriculture and Food Sciences in Sarajevo, were examined. Principal component analysis (PCA) showed that the proportion of variance retained in the first two principal components was 54.35%. The first principal component had high contributing factor loadings from seed width, seed height and seed weight, whilst the second principal component had high contributing factor loadings from the analyzed traits seed per pod and pod length. PCA plot, based on the first two principal components, displayed a high level of variability among the analyzed material. The discriminant analysis of principal components (DAPC) created 3 discriminant functions (DF), whereby the first two discriminant functions accounted for 90.4% of the variance retained. Based on the retained DFs, DAPC provided group membership probabilities which showed that 70% of the accessions examined were correctly classified between the geographically defined groups. Based on the taxonomic distance, 40 common bean accessions analyzed in this study formed two major clusters, whereas two accessions Acc304 and Acc307 didn?t group in any of those. Acc360 and Acc362, as well as Acc324 and Acc371 displayed a high level of similarity and are probably the same landrace. The present diversity of Bosnia and Herzegovina?s common been landraces could be useful in future breeding programs.

scholarly journals Morphological and Chemical Analysis of 16 Avocado Accessions (Persea americana) From China by Principal Component Analysis and Cluster Analysis

2018 ◽  
Vol 10 (8) ◽  
pp. 80
Author(s):  
Yu Ge ◽  
Funing Ma ◽  
Bin Wu ◽  
Lin Tan
Keyword(s):  
Fatty Acids ◽  
Cluster Analysis ◽  
Fatty Acid ◽  
Morphological Characteristics ◽  
Principal Component ◽  
Persea Americana ◽  
Physicochemical Composition ◽  
Avocado Fruit ◽  
Total Fatty Acids ◽  
And Cluster Analysis

The physicochemical composition of avocado fruit has been well reported, but there is little detail on Chinese native avocado varieties. The present study investigated the morphological characteristics, oil contents, and fatty acid compositions of 16 avocado accessions grown in the tropical and subtropical regions of China. Eight fatty acids were identified and quantified by GC-MS. The major fatty acids of avocado pulp were palmitic, oleic, and linoleic acids, accounting for 78-91% of the total fatty acids content. The analysis of one-way variance (ANOVA) of the data revealed morphological and chemical differences between most of avocado accessions. Moreover, 16 avocado accessions were distinguished through a PCA scores scatter plot and cluster analysis based on fatty acid profiles. The results identified some remarkable characteristics of avocado accessions from different places of collection.

Morphometrics and paleoecology of Catenipora (Tabulata) from the Xiazhen Formation (Upper Ordovician), Zhuzhai, South China

2016 ◽  
Vol 90 (6) ◽  
pp. 1027-1048 ◽  
Author(s):  
Kun Liang ◽  
Robert J. Elias ◽  
Suk-Joo Choh ◽  
Dong-Chan Lee ◽  
Dong-Jin Lee
Keyword(s):  
Discriminant Analysis ◽  
Geometric Morphometrics ◽  
South China ◽  
Morphological Characteristics ◽  
Principal Component ◽  
Morphological Characters ◽  
Depositional Environments ◽  
Heterogeneous Environments ◽  
Upper Ordovician ◽  
Species Specific

AbstractCatenipora is one of the most common tabulate coral genera occurring in various lithofacies in the Upper Ordovician Xiazhen Formation at Zhuzhai in South China. A combination of traditional multivariate analysis and geometric morphometrics is applied to a large number of specimens to distinguish and identify species. Based on three major principal components extracted from 11 morphological characters, three major groups as determined by the cluster-analysis dendrogram are considered to be morphospecies. Their validity and distinctiveness are confirmed by discriminant analysis, descriptive statistics, and bivariate plots. Tabularium area and common wall thickness are the most meaningful characters to distinguish the three morphospecies. Geometric morphometrics is adopted to compare the morphospecies with types and/or figured specimens of species previously reported from the vicinity of Zhuzhai. Despite discrepancies in corallite size, principal component analysis and discriminant analysis, as well as consideration of overall morphological characteristics, indicate that the morphospecies represent C. zhejiangensis Yu in Yu et al., 1963, C. shiyangensis Lin and Chow, 1977, and C. dianbiancunensis Lin and Chow, 1977.Catenipora occurs in seven stratigraphic intervals in the Xiazhen Formation at Zhuzhai, representing a variety of heterogeneous environments. The coralla preservation is variable due to differential compaction; coralla preserved in limestones are commonly intact and in growth position, whereas those in shales are mostly crushed or fragmentary. The size and shape of corallites are considered primarily to be species-specific characters, but are also related to the depositional environments. In all species, morphological characters, including corallite size, septal development, and shape and size of lacunae, show high variability in accordance with lithofacies and stratigraphic position. The intraspecific differences in corallite size at various localities in the Zhuzhai area may indicate responses to local environmental factors, but may also reflect genetic differences if there was limited connection among populations.

Seed classification of three species of amaranth (Amaranthus spp.) using artificial neural network and canonical discriminant analysis

2019 ◽  
Vol 157 (04) ◽  
pp. 333-341 ◽  
Author(s):  
A. Bagheri ◽  
L. Eghbali ◽  
R. Sadrabadi Haghighi
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Discriminant Analysis ◽  
Recognition Accuracy ◽  
Morphological Characteristics ◽  
Amaranthus Retroflexus ◽  
Canonical Discriminant Analysis ◽  
Identification Accuracy ◽  
Predictor Variables ◽  
Artificial Neural

AbstractThe current study was conducted in 2013 to identify the seeds of three species of Amaranthus, Amaranthus viridis L., Amaranthus retroflexus L. and Amaranthus albus L., by using the artificial neural network (ANN) and canonical discriminant analysis (CDA) methods. To begin with, photographs were taken of the seeds and 13 morphological characteristics of each seed extracted as predictor variables. Backward regression was used to find the most influential variables and seven variables were derived. Thus, predictor variables were divided into two sets of 13 and seven morphological characteristics. The results showed that the recognition accuracy of the ANN made using 13 and seven predictor variables was 81.1 and 80.3%, respectively. Meanwhile, recognition accuracy of the CDA using the seven and 13 predictor variables was 74.0 and 75.7%, respectively. Therefore, in comparison to CDA, ANN showed higher identification accuracy; however, the difference was not statistically significant. Identification accuracy for A. retroflexus was higher using the CDA method than ANN, while the ANN method had higher recognition accuracy for A. viridis than CDA. In addition, use of 13 predictor variables yielded a greater identification accuracy than seven. The results of the current study showed that using seed morphological characteristics extracted by computer vision could be effective for reliable identification of the similar seeds of Amaranthus species.

Ammonoid morphological signal versus sea-level changes

1997 ◽  
Vol 134 (2) ◽  
pp. 261-264 ◽  
Author(s):  
P. NEIGE ◽  
D. MARCHAND ◽  
A. BONNOT
Keyword(s):  
Sea Level ◽  
Sampling Method ◽  
Morphological Characteristics ◽  
Morphological Diversity ◽  
Shell Morphology ◽  
Sea Level Changes ◽  
Third Order ◽  
Biological Signal ◽  
Upper Callovian ◽  
Physical Signal

The morphological diversity, considered as a biological signal, of a series of four Upper Callovian (Middle Jurassic) ammonite populations of Côte-d’Or (France) is quantified. These populations fall within two third-order sequences of a second-order transgression. A sampling method that adheres as closely as possible to the morphological characteristics of the populations is established. It is valuable in that it eliminates the subjectivity related to taxonomy to allow more objective comparisons between the biological signal (shell morphology) and the physical signal (eustasy).

scholarly journals Combined approach based on principal component analysis and canonical discriminant analysis for investigating hyperspectral plant response

2012 ◽  
Vol 7 (3) ◽  
pp. 34 ◽  
Author(s):  
Anna Maria Stellacci ◽  
Annamaria Castrignanò ◽  
Mariangela Diacono ◽  
Antonio Troccoli ◽  
Adelaide Ciccarese ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Discriminant Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Canonical Discriminant Analysis ◽  
Plant Response ◽  
Combined Approach

scholarly journals Taxonomic studies on the Chara section Hartmania in Poland based on morphological and molecular data

PhytoKeys ◽  
2019 ◽  
Vol 135 ◽  
pp. 71-90
Author(s):  
Jacek Urbaniak ◽  
Paweł Kwiatkowski
Keyword(s):  
Discriminant Analysis ◽  
Morphological Characteristics ◽  
Principal Component ◽  
Taxonomic Status ◽  
Component Analysis ◽  
Molecular Data ◽  
Morphological Features ◽  
Green Macroalgae ◽  
Molecular Group ◽  
Water Ecosystems

Charophytes are aquatic green macroalgae, which inhabit fresh and brackish water ecosystems. In this study, four species belonging to the genus Chara were examined to determine their taxonomic status. Morphological characteristics of the plant bodies as well as plastid psaB barcoding genes were applied to test the relations among Chara species. Plants were initially classified using morphological features into four species: C. baltica, C. hispida, C. polyacantha and C. rudis, and twelve quantitative characters were used in a principal component analysis and discriminant analysis to determine groupings among the species and to determine the morphological features that best separated the groups. In the component analysis and discriminant analysis, results showed that only C. polyacantha and partly C. baltica formed separate groups. The other species C. hispida and C. rudis were only partially distinguishable. All species from one molecular group, and no differentiation in the psaB variability between them has been found.

Allozyme variation of old Ginkgobiloba memorial trees in western Japan

1992 ◽  
Vol 22 (7) ◽  
pp. 939-944 ◽  
Author(s):  
Yoshihiko Tsumura ◽  
Hiroshi Motoike ◽  
Kihachiro Ohba
Keyword(s):  
Principal Component Analysis ◽  
Discriminant Analysis ◽  
Genetic Relationships ◽  
Principal Component ◽  
Allozyme Variation ◽  
Canonical Discriminant Analysis ◽  
Scatter Diagram ◽  
Enzyme Systems ◽  
Multivariate Procedures ◽  
Western Japan

Allozyme variation of 89 old memorial trees of Ginkgobiloba L. in western Japan were investigated. For 12 loci from 10 enzyme systems, the percentage of polymorphic loci (95% level), the number of alleles per locus, and the observed heterozygosity were 75.0%, 2.5, and 0.234, respectively. The variation of this species is relatively high in comparison with other gymnosperms. Genetic relationships between four regions (Kansai, Shikoku, North Kyushu, and South Kyushu) were investigated by using two multivariate procedures. Based on a principal component analysis, these four regional groups were not separated clearly, except for the Shikoku and South Kyushu groups, which were almost completely separated in opposite peripheral zones of a scatter diagram. The canonical discriminant analysis also almost completely separated the Shikoku and South Kyushu groups. These results indicate that most trees of the Shikoku and South Kyushu groups might be descendants of individuals from the Kansai and North Kyushu groups, respectively, excluding some exceptions.

scholarly journals Analisis Diskriminan Terhadap Pengelompokan Mutu Pendidikan Sekolah Menengah Atas di Kabupaten Lamongan

2020 ◽  
Vol 6 (2) ◽  
pp. 11-20
Author(s):  
Mu’tasim Billah ◽  
Novita Eka Chandra ◽  
Siti Amiroch
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Discriminant Analysis ◽  
Principal Component ◽  
Original Data ◽  
Quality Of Education ◽  
Linkage Method ◽  
And Cluster Analysis ◽  
Index Value

Quality of education is the educational services ability that can fill the needs or expectations, satisfaction internally and externally which includes educational inputs, processes and outputs. The purpose of this reserach is to classify the quality of high school education in Lamongan District using factor, cluster and discriminant analysis. The dominant factors of 12 education quality variables can be known from the results of factor analysis using the PCA (Principal Component Analysis) method. The grouping of 48 high schools did by cluster analysis using 5 hierarchical methods. The validity index used to determine the optimal group number of the five hierarchical methods is RMSSTD (Root Mean Square Standard Deviation). The classification accuracy testing uses discriminant analysis based on the results of factor analysis and cluster analysis. Grouping the quality of education is influenced by dominant factors such as the number of classrooms, the value of accreditation, the number of certification and non-certification teachers, the number of education staff, the ratio of students to teachers, the number of laboratory rooms that can be known from the results of factor analysis. In cluster analysis, using the Mahalanobis distance because there is multicollinearity and the smallest RMSSTD index value obtained in the Complete Linkage method with 5 clusters. So, with discriminant analysis, it can be concluded that the grouping based on factor analysis and cluster analysis is 58.3% of the 48 processed data that has been entered in the group that matches the original data.

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