Host status and phenotypic diversity of rice cultivars resistant to Meloidogyne species under glasshouse conditions

Nematology ◽  
2014 ◽  
Vol 16 (8) ◽  
pp. 991-999
Author(s):  
Andressa C.Z. Machado ◽  
Jerônimo V. de Araújo Filho
Keyword(s):  
Cluster Analysis ◽  
Phenotypic Diversity ◽  
Genetic Material ◽  
Principal Component ◽  
Broad Sense ◽  
Broad Sense Heritability ◽  
Rice Cultivars ◽  
Reproductive Factor ◽  
Pot Trials ◽  
Host Status

Five pot trials were carried out under glasshouse conditions to assess the host response of some selected rice cultivars to Meloidogyne javanica, M. paranaensis and M. enterolobii, based on nematode reproductive factor (RF) and number of nematodes (g root)−1. We also determined the broad-sense heritability and variance component estimations associated with M. paranaensis and M. incognita resistance. In addition, cluster analysis of cultivars was conducted. All cultivars were rated as susceptible or highly susceptible to M. javanica and highly resistant to M. enterolobii. To M. paranaensis, only cvs IAPAR 177 and BRS Caravela were resistant. From the principal component analysis and Ward’s cluster analysis, we obtained four conspicuous clusters of cultivars according to Meloidogyne species resistance, which demonstrates the variability of the genetic material studied. Higher broad-sense heritability values for RF and nematodes (g root)−1 were obtained. Taken together, our findings suggest that improvement of resistance of rice to Meloidogyne species resistance is possible. The implications for management programmes are also discussed.

scholarly journals Polymorphism analysis in some Algerian Opuntia species using morphological and phenological UPOV descriptors

2017 ◽  
Vol 95 (3) ◽  
pp. 391 ◽  
Author(s):  
Boubakr Hadjkouider ◽  
Ammar Boutekrabt ◽  
Bahia Lallouche ◽  
Salim Lamine ◽  
Néjia Zoghlami
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Phenotypic Diversity ◽  
Principal Component ◽  
Morphological Diversity ◽  
Hierarchical Cluster ◽  
Relative Magnitude ◽  
Polymorphism Analysis ◽  
Opuntia Ficus Indica ◽  
New Varieties

<p><strong>Background: </strong>In the present study, we have investigated the morphological variation in a set of five <em>Opuntia</em> species from the Algerian steppes using 49 UPOV descriptors.</p><p><strong>Questions: </strong>which of the 49 descriptors that can be used as powerful estimators of the phenotypic diversity within <em>Opuntia</em> species? How is the morphological diversity patterned in Algerian <em>Opuntia</em>?</p><p><strong>Species study/ Mathematical model: </strong><em>Opuntia ficus-indica, Opuntia amycleae, Opuntia streptacantha, Opuntia engelmannii, Opuntia robusta</em><strong>.</strong> Principal Components Analysis (PCA) and Hierarchical Cluster Analysis were used.</p><p><strong>Study site: </strong>Four counties were studied located in the Algerian steppes. The present research was carried out during 2014.</p><p><strong>Methods:</strong> 49 descriptors adopted by the International Union for the Protection of New Varieties of Plants (UPOV) were employed in the present research, where cladode, flower and fruit traits were used to determine the overall degree of polymorphism among 5 <em>Opuntia</em> species.</p><p><strong>Results:</strong> Principal Component Analysis and Hierarchical Cluster Analysis indicated a consistent differentiation between all studied species. The relative magnitude of the first two PCA eigenvectors showed that 8 descriptors out of 49 were identified as the most important descriptors for the classification of the species. The dendrogram performed on the calculated Euclidean distances between all species pairs allowed the identification of 3 groups, unlike the PCA that identified 4 groups. The species <em>Opuntia ficus-indica </em>and <em>Opuntia amycleae</em> were identified as very close morphologically.</p><p><strong>Conclusions: </strong>The present outcome represents a paramount step towards the fast selection of interesting species and for their best management and conservation.</p>

scholarly journals Keragaman Fenotipik Bunga Telang Double Petal Asal Indonesia dan Thailand Berdasarkan Morfologi Bunga

2021 ◽  
Vol 14 (1) ◽  
pp. 78-89
Author(s):  
Virda Aziza ◽  
Trixie Almira Ulimaz ◽  
Debby Ustari ◽  
Tarkus Suganda ◽  
Vergel Concibido ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Phenotypic Diversity ◽  
Principal Component ◽  
Component Analysis ◽  
Flower Morphology ◽  
West Java ◽  
Clitoria Ternatea ◽  
Butterfly Pea ◽  
And Cluster Analysis

AbstrakBunga telang (Clitoria ternatea L.) merupakan tanaman legum yang bagian bunganya telah banyak dimanfaatkan. Double petal adalah salah satu varian spesies bunga telang yang banyak ditemukan di Asia Tenggara. Penelitian ini bertujuan untuk mengevaluasi keragaman fenotipik plasma nutfah bunga telang double petal asal Indonesia (Bali, Jawa Barat, dan Jawa Timur) dan Thailand berdasarkan morfologi bunga. Percobaan disusun dalam Rancangan Acak Kelompok (RAK) dengan tiga ulangan. Data morfologi dianalisis menggunakan analisis multivariat berupa Analisis Komponen Utama (Principal Component Analysis) dan Analisis Klaster (Cluster Analysis) dengan bantuan program NTSYS 2.1. Hasil penelitian menunjukkan terdapat lima komponen utama yang berpengaruh terhadap keragaman aksesi dengan persentase keragaman kumulatif 88,82%. Karakter tipe bunga, susunan mahkota bunga, keberadaan lunas, tipe benang sari, dan posisi kepala putik memberi pengaruh terbesar terhadap keragaman aksesi. Analisis klaster membagi aksesi-aksesi tersebut menjadi dua klaster dengan koefisien ketidakmiripan 3,01–6,83. Dari hasil penelitian dapat disimpulkan bahwa bunga telang double petal asal Indonesia dan Thailand memiliki keragaman yang luas dan kekerabatan yang jauh; aksesi asal Bali memiliki morfologi bunga dan klaster yang berbeda dengan aksesi asal Jawa Barat, Jawa Timur, dan Thailand. Informasi ini akan bermanfaat dalam merencanakan pengelolaan plasma nutfah dan pemuliaan bunga telang double petal. Abstract Butterfly pea (Clitoria ternatea L.) is a legumeplant of which flower parts are widely used. One of butterfly pea variant is double petal which commonly found in Southern Asia. This study aimed to evaluate phenotypic diversity of double petal butterfly pea germplasm from Indonesia (Bali, West Java, and East Java) and Thailand based on flower morphology. The experiment was arranged in randomized complete blocks design with three replications. Morphology data were subjected to multivariate analysis using Principal Component Analysis and Cluster Analysis and performed by NTSYS 2.1. The result showed that there were five significant principal components that cumulatively explained 88.82% of variance. Existence of keel, aestivation type, position of stigma, type of stamen, and flower type gave high contributions to the diversity of accessions. Cluster analysis grouped the accessions into two clusters with dissimilarity coefficient from 3.01–6.83. From the results, it can be concluded that double petal butterfly pea from Indonesia and Thailand have wide diversity and genetic relationship; the accessions from Bali have different flower morphology and cluster compared to the accessions from East Java, West Java, and Thailand. The information will help planning management of the germplasm and breeding double petal butterfly pea.

scholarly journals Genetic Variability and Cluster Analysis for Phenological Traits of Thai Indigenous Upland Rice (Oryza sativa L.)

2020 ◽  
Author(s):  
Shams Shaila Islam ◽  
Jakarat Anothai ◽  
Charassri Nualsri ◽  
Watcharin Soonsuwon
Keyword(s):  
Cluster Analysis ◽  
Genetic Variability ◽  
Upland Rice ◽  
Oryza Sativa L ◽  
Broad Sense ◽  
Broad Sense Heritability ◽  
Area Index ◽  
Group I ◽  
Southern Thailand ◽  
And Cluster Analysis

Estimating genetic variability and cluster analysis of grain yield and yield contributing traits need to require for rice breeders to choose the best breeding programs. Ten upland rice genotypes were conducted from farmers’ fields during the years of 2017 at three provinces of southern Thailand. Extreme broad sense heritability and genetic gain values for flag leaf length, leaf area index, harvest index, total dry weight and filled grains showed that assortment of these yield contributing traits would be effective. Cluster analysis categorized genotypes into three groups. In each group some genotypes such as Dawk Pa-yawm or Dawk Kha 50 (group I), Nahng Kian (group II) and Khao/ Trai (group III) showed that genotypes had different better traits. These studies revealed that high broad sense heritability traits and the best genotypes Nahng Kian and Khao/ Trai would be useful for improving new upland rice varieties in southern Thailand.

scholarly journals Prediction of Genotypic Values for Apple Fruit Texture Traits in a Breeding Population Derived from ‘Honeycrisp’

2011 ◽  
Vol 136 (6) ◽  
pp. 408-414 ◽  
Author(s):  
Steven J. McKay ◽  
James M. Bradeen ◽  
James J. Luby
Keyword(s):  
Block Design ◽  
Principal Component ◽  
Breeding Population ◽  
Apple Fruit ◽  
Broad Sense ◽  
Broad Sense Heritability ◽  
Phenotypic Data ◽  
Fruit Texture ◽  
Common Parent ◽  
Instrumental Methods

The commercially successful apple (Malus pumila Mill.) cultivar Honeycrisp is known for its high degrees of crispness and juiciness. This cultivar has been incorporated into numerous breeding programs in an effort to duplicate its desirable texture traits in conjunction with such other traits as reduced postharvest disorders, disease resistance, and improved tree vigor. This study characterizes variability and estimates heritability for several apple fruit texture traits within a large breeding population over several years. Five full-sib families, all sharing ‘Honeycrisp’ as a common parent, were assayed with respect to crispness, firmness, and juiciness using sensory evaluation panels and total work required to fracture tissue using instrumental methods. The incomplete block design of the sensory panels, coupled with best linear unbiased prediction, facilitated the evaluation of a large number of genotypes with small numbers of fruit per genotype while accounting for individual sensory panelist effects. Broad-sense heritability estimates exceeded 0.70 for all four traits. Principal component analysis, applied to the phenotypic data, characterized ‘Honeycrisp’ as having average crispness and low firmness (53rd percentile relative to its offspring) but also as being a relatively extreme example of high juiciness and low work to fracture (first percentile). The improved characterization of desired fruit texture phenotypes and the high levels of broad-sense heritability provide valuable tools for the further development of new, high-quality apple cultivars.

scholarly journals Agronomic characters, genetic and phenotypic diversity coefficients, and heritability of 12 genotypes of rice

2021 ◽  
Vol 22 (3) ◽  
Author(s):  
Jaenudin Kartahadimaja ◽  
SETYO DWI UTOMO ◽  
ERWIN YULIADI ◽  
ABDUL KADIR SALAM ◽  
WARSONO ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Phenotypic Diversity ◽  
Block Design ◽  
Broad Sense ◽  
Broad Sense Heritability ◽  
Agronomic Characters ◽  
Mean Values ◽  
Panicle Number ◽  
New Varieties ◽  
Grain Width

Abstract. Kartahadimaja J, Utomo SD, Yuliadi E, Salam AK, Warsono, Wahyudi A. 2021. Agronomic characters, genetic and phenotypic diversity coefficients, and heritability of 12 genotypes of rice. Biodiversitas 22: 1091-1097. The achievement of national rice production is always below the target. One of the causes is the low productivity of the varieties grown due to the stagnant genetic capacity of these varieties. The assembly of new lines through breeding is one solution that can increase the genetic capacity of new varieties. Genetic diversity is one of the factors that influence the success of plant breeding. Ten new F9 rice lines were successfully assembled showing various phenotypes. The identification of the specific advantages of each of these new rice lines was based largely on the phenotypic response. The research objective was to identify the genetic advantages of each line through the analysis approach of genetic diversity coefficient (GDC), Phenotific Diversity Coefficient (PDC), and broad-sense heritability. The research was designed on a randomized completely block design (RCBD) with ten new F9 rice lines and two comparison varieties as treatments, repeated three times. The variables observed were plant height, maximum number of tillers, number of productive tillers, flowering time, harvesting time, panicle length, number of grain per panicle, number of filled grains per panicle, number of empty grain per panicle, grain length, grain width, grain thickness, and grain yield per hectare. The data were analyzed using Analysis of Variance (ANOVA), if there was a difference between the mean values, it was continued with a 5% LSD test. The results showed that (i) the genotypes tested showed wide genetic and phenotypic diversity, (ii) based on the analysis of GDC, PDC, and broad sense heritability, the appearance of phenotypes of several agronomic characters was controlled by genetic factors.

Classification of Observations through Combination of the Dimension Reduction and the Cluster Analysis

2017 ◽  
Vol 7 (8) ◽  
pp. 30
Author(s):  
Hyeuk Kim
Keyword(s):  
Machine Learning ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Unsupervised Learning ◽  
Principal Component ◽  
Component Analysis ◽  
Baseball Players ◽  
Partitioning Around Medoids ◽  
Different Characteristics

Unsupervised learning in machine learning divides data into several groups. The observations in the same group have similar characteristics and the observations in the different groups have the different characteristics. In the paper, we classify data by partitioning around medoids which have some advantages over the k-means clustering. We apply it to baseball players in Korea Baseball League. We also apply the principal component analysis to data and draw the graph using two components for axis. We interpret the meaning of the clustering graphically through the procedure. The combination of the partitioning around medoids and the principal component analysis can be used to any other data and the approach makes us to figure out the characteristics easily.

Quality evaluation of tugaksheeree samples by ATR-FTIR spectroscopy using multicomponent analysis

2020 ◽  
Vol 10 ◽  
Author(s):  
Nikunj D. Patel ◽  
Niranjan S. Kanaki
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Quality Evaluation ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Attenuated Total Reflectance ◽  
Chemometric Methods ◽  
Total Reflectance ◽  
Fingerprint Region ◽  
Ftir Technique

Background: Numerous Ayurvedic formulations contains tugaksheeree as key ingredient. Tugaksheereeis the starch gained from the rhizomes of two plants, Curcuma angustifoliaRoxb. (Zingiberaceae) and Marantaarundinacea (MA) Linn. (Marantaceae). Objective: The primary concerns in quality assessment of Tugaksheeree occur due to adulteration or substitution. Method: In current study, Fourier transform infrared (FTIR) technique with attenuated total reflectance (ATR) facility was used to evaluate tugaksheeree samples. Total 10 different samples were studied and transmittance mode was kept to record the spectra devoid of pellets of KBR. Further treatment was given with multi component tools by considering fingerprint region of the spectra. Multivariate analysis was performed by various chemometric methods. Result: Multi component methods like Principal Component Analysis (PCA), and Hierarchical Cluster Analysis (HCA)were used to discriminate the tugaksheeree samples using Minitab software. Conclusion: This method can be used as a tool to differentiate samples of tugaksheeree from its adulterants and substitutes.

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