Using Cluster Analysis and Principal Component Analysis to Group Lines and Determine Important Traits in White Bean

Koij, Fariba Shafiei; Saba, Jalal

doi:10.1016/j.proenv.2015.07.145

Cited by 14 publications

(10 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The efficiency with which genotypic variability can be exploited by selection depends upon heritability, genetic advance and correlation among the individual traits ( Bilgin et al., 2010 ). Moreover, the use of multivariate statistical tools such as Principal Component Analysis (PCA) and Cluster analysis are essential for grouping the genotypes and provides the opportunity to the breeder to select appropriate parents for crossing ( Koij and Saba, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

Genetic variability, heritability and correlation analysis among maturity and yield traits in Cowpea (Vigna unguiculata (L) Walp) in Northern Ghana

Owusu

Karikari

Kusi

et al. 2021

Heliyon

View full text Add to dashboard Cite

Experimental studies were conducted to evaluate 16 advanced breeding lines of cowpea ( Vigna unguiculata (L) Walp) for genetic variability, heritability and correlation between maturity and yield related traits. The genotypes exhibited significant ( P < 0.05) differences for the eight traits evaluated viz., number of days to 50 % flowering, number of days to 90 % pod maturity, plant height at maturity, number of pods per plant, number of seeds per pod, pod yield, grain yield and hundred seed weight. SARI-3-11-100, SARI-6-2-6, SARVX-09-004 and IT07K-299-6 had grain yields of 1.99 ± 0.30, 1.88 ± 0.20, 1.95 ± 0.30 and 1.91 ± 0.20 t/ha, respectively, which were significantly higher than the check ( Songotra ) (1.68 ± 0.01 t/ha). In addition, SARI-5-5-5 matured significantly earlier than the check but no significant difference was observed for grain yield. The higher value of phenotypic component compared to the corresponding genotypic component for all the traits suggest that there was an environmental influence on the performance of the genotypes. Hence, the need for multi-location evaluation of the promising lines for onward release if found stable. The information provided in this study, can be exploited in cowpea breeding program.

show abstract

Section: Introductionmentioning

confidence: 99%

Genetic variability, heritability and correlation analysis among maturity and yield traits in Cowpea (Vigna unguiculata (L) Walp) in Northern Ghana

Owusu

Karikari

Kusi

et al. 2021

Heliyon

View full text Add to dashboard Cite

show abstract

“…O clasificare reușită a genotipurilor în baza similitudinilor/deosebirilor se realizează prin metoda aglomerativ-iteraţională de construire a dendrogramelor de repartiţie, metoda centroidă a k-mediilor, ambele metode fiind utilizate cu succes în cercetările de genetică şi ameliorare [17,18,19]. În analiza clusteriană k-medii, s-a optat pentru repartizarea genotipurilor în 4 clustere conform valorilor caracterelor analizate.…”

Section: Materials șI Metodeunclassified

Heritability of common wheat resistance to the Fusarium avenaceum (fr.) Sacc. fungus in the F1 generation

Cristea

2023

Studia MSU. St.Nat.

View full text Add to dashboard Cite

The fungus Fusarium avenaceum (Fr.) Sacc. – one of the causative agents of root rot and spike fusarium, is very widespread in the grass cereal crops, including common wheat, throughout the world, including in the Republic of Moldova. Incorporating genetic resistance into crop plants is considered the most effective and sustainable method of the disease control. For the strategies to improve disease resistance, knowledge of the genetic basis of the reaction to the causative agents is necessary. Article presents the data regarding: i) influence of the F. avenaceum culture filtrate (CF) on the growth organs of the parental forms and F1 descendants of wheat, ii) the degree of dominance of the seedling vigor index in the cont rol variant and with CF, iii) the influence of the parental factor on the manifestation of the vigor index, iv) the classification (dendrograms, k-means, multidimensional scanning) of the forms tested under the influence of the pathogen, v) the identification of genotypes that can be used as sources of resistance.

show abstract

“…Cluster analysis. One of the most successful procedures for classifying objects based on similarities / differences is cluster analysis (Shafiei and Sabaa 2015). By applying the agglomerativeiterational method of constructing the distribution dendrogram of the compounds under study, in which MIC and MBC are used as cases for the studied bacteria it can be observed an obvious separation of the compounds into different clusters.…”

Section: Determination Of Physical and Chemical Indicatorsmentioning

confidence: 99%

Relationship Between Physicochemical Parameters and Antimicrobial Activity of Moldavian Honey

Eremia,

Coșeleva,

Sucman

et al. 2023

Sylwan

View full text Add to dashboard Cite

Six samples of Moldavian honey from different regions were analyzed, physical and chemical parameters, the content of macro-, microelements, and aminoacids were determined, as well as antibacterial and antifungal activity. The antibacterial and antifungal properties were determined using the double serial dilution method. It was established that all of the samples of acacia, linden, and sunflower honey possess high antibacterial activity. The bioactivity of the samples of honey was proven to be dependent on the type and origin of honey. Sunflower honey has higher antibacterial potency than linden, but linden honey is more active than acacia. Both Gram-positive and Gram-negative bacterial species proved to be susceptible to Moldavian honey. Acacia, linden, and sunflower honey, possess high antibacterial potency against S. aureus and P. aeruginosa even at a dilution of 1:16 (2.5%). The studied samples showed weak antifungal activity against Candida albicans, with the MIC determined at 1:2 dilution (20%). For linden and sunflower honey, the antifungal activity was higher than for acacia honey. The samples with the best bioactivity (sunflower honey) contain a higher amount of free acids, had lower pH values of the honey solution, and these samples also have the highest content of OMF.

show abstract

Using Cluster Analysis and Principal Component Analysis to Group Lines and Determine Important Traits in White Bean

Cited by 14 publications

References 1 publication

Genetic variability, heritability and correlation analysis among maturity and yield traits in Cowpea (Vigna unguiculata (L) Walp) in Northern Ghana

Genetic variability, heritability and correlation analysis among maturity and yield traits in Cowpea (Vigna unguiculata (L) Walp) in Northern Ghana

Heritability of common wheat resistance to the Fusarium avenaceum (fr.) Sacc. fungus in the F1 generation

Relationship Between Physicochemical Parameters and Antimicrobial Activity of Moldavian Honey

Contact Info

Product

Resources

About