scholarly journals Elucidation of Genetic Diversity as Morphological, Phytochemical and Molecular Markers in Some Hawthorn (Crataegus) Genotypes

2021 ◽  
Author(s):  
Ercan YILDIZ ◽  
Mehmet YAMAN ◽  
Ahmet SÜMBÜL ◽  
Ahmet SAY
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Molecular Marker ◽  
Geographical Location ◽  
Similarity Index ◽  
Principal Component ◽  
Component Analysis ◽  
Biochemical Properties ◽  
Total Phenolic ◽  
Fruit Species

Abstract Backround: Thanks to its ecological and geographical location, Turkey is the homeland of many fruit species and allows many fruit species to be grown. Hawthorn, which is understood to be important in human health and nutrition, is one of these fruit types. This study was carried out to identify morphological, biochemical and molecular genetic variations of 22 hawthorn genotypes belonging to three different species collected from Kayseri province. Methods and Results: Morphological, biochemical and molecular marker (ISSR) techniques were used to determine genetic diversity. The fruit and leaf characteristics of the genotypes showed differences. Among the biochemical properties of the genotypes, the antioxidant activity ranged from 23.13–61.59%, the total flavonoid content ranged from 16.63 to 57.22 mg QE/100 g, and the total phenolic content ranged from 277.28 to 310.80 mg GAE/100 g. Genotypes were compared with principal component analysis according to their morphological and biochemical characteristics. In the principal component analysis, species generally formed similar clusters. In molecular marker analysis, 101 bands were obtained from 13 ISSR primers. 76 of the bands are polymorphic and the polymorphism rate was calculated as 75.24%. The similarity index in the UPGMA dendogram obtained as a result of the molecular analysis ranged between 0.71 and 0.88. In the dendrogram, genotypes did not show a dense clustering by species. Conclusion The results obtained may benefit researchers in the determination and protection of gene sources in breeding studies on hawthorn species.

scholarly journals Relationships Between the Content of Phenolic Compounds and the Antioxidant Activity of Polish Honey Varieties as a Tool for Botanical Discrimination

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1810
Author(s):  
Monika Kędzierska-Matysek ◽  
Małgorzata Stryjecka ◽  
Anna Teter ◽  
Piotr Skałecki ◽  
Piotr Domaradzki ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Antioxidant Activity ◽  
Phenolic Compounds ◽  
Caffeic Acid ◽  
Principal Component ◽  
Total Content ◽  
Component Analysis ◽  
Total Phenolic ◽  
Hydroxybenzoic Acid ◽  
Coumaric Acid

The study compared the content of eight phenolic acids and four flavonoids and the antioxidant activity of six Polish varietal honeys. An attempt was also made to determine the correlations between the antioxidant parameters of the honeys and their polyphenol profile using principal component analysis. Total phenolic content (TPC), total flavonoid content (TFC), antioxidant activity (ABTS) and reduction capacity (FRAP) were determined spectrophotometrically, and the phenolic compounds were determined using high-performance liquid chromatography (HPLC). The buckwheat honeys showed the strongest antioxidant activity, most likely because they had the highest concentrations of total phenols, total flavonoids, p-hydroxybenzoic acid, caffeic acid, p-coumaric acid, vanillic acid and chrysin. The principal component analysis (PCA) of the data showed significant relationships between the botanic origin of the honey, the total content of phenolic compounds and flavonoids and the antioxidant activity of the six Polish varietal honeys. The strongest, significant correlations were shown for parameters of antioxidant activity and TPC, TFC, p-hydroxybenzoic acid, caffeic acid and p-coumaric acid. Analysis of four principal components (explaining 86.9% of the total variance), as a classification tool, confirmed the distinctiveness of the Polish honeys in terms of their antioxidant activity and content of phenolic compounds.

scholarly journals Sensory Profile of Chihuahua Cheese Manufactured from Raw Milk

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Sarai Villalobos-Chaparro ◽  
Erika Salas-Muñóz ◽  
Néstor Gutiérrez-Méndez ◽  
Guadalupe Virginia Nevárez-Moorillón
Keyword(s):  
Principal Component Analysis ◽  
Geographical Location ◽  
Principal Component ◽  
Raw Milk ◽  
Component Analysis ◽  
Sensory Profile ◽  
Different Seasons ◽  
Quantitative Descriptive ◽  
Traditional Manufacturing ◽  
Chihuahua Cheese

Chihuahua cheese is a local artisanal cheese traditionally produced from raw milk. When this cheese is produced with pasteurized milk, cheesemakers complain that there are differences in taste and aroma as compared with traditional manufacturing. This work aimed to obtain a descriptive sensory analysis of Chihuahua cheese manufactured with raw milk under traditional conditions. Samples were collected in five cheese dairies at two different seasons (summer and autumn), and a Quantitative Descriptive Sensorial Analysis was done by a panel of trained judges. For aroma descriptors, cooked descriptor showed differences between dairies, and whey was different among dairies and sampling seasons (P<0.01); diacetyl, fruity (P<0.01), as well as free fatty acids, nutty and sulphur (P<0.05) descriptors varied between seasons. For flavour descriptors, bitter perception was different between dairies and seasons (P<0.01). Salty and creamy cheese was also different among dairies (P<0.01). A Principal Component Analysis for differences among dairies and sampling season demonstrated that the first three components accounted for 90% of the variance; variables were more affected by the sampling seasons than by the geographical location or if the dairy was operated by Mennonites. Chihuahua cheese sensorial profile can be described as a semi-matured cheese with a bitter flavour, slightly salted, and with a cream flavour, with aroma notes associated with whey and sour milk. Principal Component Analysis demonstrated season influence on flavour and aroma characteristics.

Genetic Diversity Assessment in Dolichos Bean (Lablab purpureus L.) Based on Principal Component Analysis and Single Linkage Cluster Analysis

2021 ◽  
Author(s):  
S.R. Singh ◽  
S. Rajan ◽  
Dinesh Kumar ◽  
V.K. Soni
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Single Linkage ◽  
Pod Yield ◽  
Diversity Assessment ◽  
Single Linkage Cluster ◽  
Linkage Cluster

Background: Dolichos bean occupies a unique position among the legume vegetables of Indian origin for its high nutritive value and wider climatic adaptability. Despite its wide genetic diversity, no much effort has been undertaken towards genetic improvement of this vegetable crop. Knowledge on genetic variability is an essential pre-requisite as hybrid between two diverse parental lines generates broad spectrum of variability in segregating population. The current study aims to assess the genetic diversity in dolichos genotypes to make an effective selection for yield improvement.Methods: Twenty genotypes collected from different regions were evaluated during year 2016-17 and 2017-18. Data on twelve quantitative traits was analysed using principal component analysis and single linkage cluster analysis for estimation of genetic diversity.Result: Principal component analysis revealed that first five principal components possessed Eigen value greater than 1, cumulatively contributed greater than 82.53% of total variability. The characters positively contributing towards PC-I to PC-V may be considered for dolichos improvement programme as they are major traits involved in genetic variation of pod yield. All genotypes were grouped into three clusters showing non parallelism between geographic and genetic diversity. Cluster-I was best for earliness and number of cluster/plant. Cluster-II for vine length, per cent fruit set, pod length, pod width, pod weight and number of seed /pod, cluster III for number of pods/cluster and pod yield /plant. Selection of parent genotypes from divergent cluster and component having more than one positive trait of interest for hybridization is likely to give better progenies for development of high yielding varieties in Dolichos bean.

↵Genetic Diversity and Principal Component Analysis in Mungbean [Vigna radiata (L.) Wilczek] under Rainfed Condition

2021 ◽  
Author(s):  
Deepak Gupta ◽  
Suresh Muralia ◽  
N.K. Gupta ◽  
Sunita Gupta ◽  
M.L. Jakhar ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Seed Yield ◽  
Agricultural Research ◽  
Principal Component ◽  
Component Analysis ◽  
Grain Legume ◽  
Research Station ◽  
Rainfed Condition

Background: Mungbean is a short duration grain legume widely grown in south and Southeast Asia. The extent of variability through Principal Component Analysis (PCA) and cluster analysis in promising mungbean genotypes should be known for possible yield improvement. A study was undertaken to work out the extent of variability among twenty four mungbean genotypes through cluster analysis and Principal Component Analysis (PCA). Methods: The experiment was laid out in a randomized block design with three replications during kharif 2018 and 2019 at the experimental field of Agricultural Research Station, Navgaon (Alwar) under rainfed condition. Result: Principal component analysis revealed that the first three main PCAs amounted 78.80% of the total variation among genotypes for different traits. Out of total principal components, PC1 accounts for maximum variability in the data with respect to succeeding components. Number of branches per plant (28.62%), number of clusters per plant (23.55%) and seed yield (15.58%) showed maximum per cent contribution towards total genetic divergence on pooled basis. Cluster analysis showed that genotypes fall into seven different clusters and their inter and intra cluster distance showed genetic diversity between different genotypes. The maximum number of genotypes i.e., 8 was found in cluster II followed by cluster III comprising of 6 genotypes. Genotypes RMG-1138 and IPM-02-03 representing the mono genotypic cluster signifies that it can be the most diverse variety and it would be the appropriate genotype for hybridization with ones present in other clusters to tailor the agriculturally important traits and ultimately to boost the seed yield in mungbean under rainfed conditions.

scholarly journals Discrimination of Natural Mature Acacia Honey Based on Multi-Physicochemical Parameters Combined with Chemometric Analysis

Molecules ◽  
2019 ◽  
Vol 24 (14) ◽  
pp. 2674 ◽  
Author(s):  
Tianchen Ma ◽  
Haoan Zhao ◽  
Caiyun Liu ◽  
Min Zhu ◽  
Hui Gao ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Physicochemical Parameters ◽  
Phenolic Content ◽  
Principal Component ◽  
Component Analysis ◽  
Chemometric Analysis ◽  
Total Phenolic ◽  
Total Protein Content ◽  
Acacia Honey

Honey maturity is an important factor in evaluating the quality of honey. We established a method for the identification of natural mature acacia honey with eighteen physicochemical parameters combined with chemometric analysis. The analysis of variance showed significant differences between mature and immature acacia honey in physicochemical parameters. The principal component analysis explained 82.64% of the variance among samples, and indicated that total phenolic content, total protein content, and total sugar (glucose, fructose, sucrose) were the major variables. The cluster analysis and orthogonal partial least squares-discriminant analysis demonstrated that samples were grouped in relation to the maturity coinciding with the results of the principal component analysis. Meanwhile, the 35 test samples were classified with 100% accuracy with the method of multi-physicochemical parameters combined with chemometric analysis. All the results presented above proved the possibility of identifying mature acacia honey and immature acacia honey according to the chemometric analysis based on the multi-physicochemical parameters.

Genetic diversity based on cluster and principal component analysis in wheat and triticale genotypes

2015 ◽  
Vol 16 (4) ◽  
pp. 712
Author(s):  
Bhanu Priya ◽  
Sunil Diyali ◽  
Subhra Mukherjee ◽  
M. Srinivasarao
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis
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