scholarly journals Methods for conservation of intra-varietal genetic variability in ancient grapevine varieties

2019 ◽  
Vol 15 ◽  
pp. 01029
Author(s):  
E. Gonçalves ◽  
A. Martins
Keyword(s):  
Genetic Variability ◽  
Abiotic Stresses ◽  
Quantitative Traits ◽  
Quality Traits ◽  
Varietal Diversity ◽  
Advantages And Disadvantages ◽  
Future Challenges ◽  
Selection Of

Conservation of intra-varietal genetic variability is a crucial strategy to preserve traditional viticulture and to face future challenges. Conservation can be performed through two processes: (1) conservation without other immediate objectives; (2) conservation which simultaneously ensures the evaluation of important quantitative traits (such as yield, must quality traits, tolerance to abiotic stresses). The second strategy permits the quantification of intra-varietal genetic variability for important quantitative traits and the selection of a superior group of genotypes (polyclonal selection). Based on the results obtained from the conservation of ancient Portuguese varieties, the abovementioned methods for conservation of intra-varietal diversity are compared, and the advantages and disadvantages of each one are discussed.

Genetic variability, principal component and cluster analyses in black gram under Foot-hills conditions of Manipur

2018 ◽  
Author(s):  
M. Samuel Jeberson ◽  
K. S. Shashidhar ◽  
Amit Kumar Singh
Keyword(s):  
Genetic Variability ◽  
Path Analysis ◽  
Quantitative Traits ◽  
Principal Component ◽  
Yield Attributes ◽  
Eigen Values ◽  
Correlation And Path Analysis ◽  
And Cluster Analysis ◽  
100 Seed Weight ◽  
Selection Of

Analysis of genetic variability, heritability, correlation, path analysis, principal component and cluster analysis was carried for 25 blackgram genotypes grown in the foothills of Manipur. The results showed that phenotypic coefficients of variability recorded were higher than the genotypic coefficients of variability, irrespective of traits, demonstrating the effect of environment thereon. The present study revealed that the heritability (bs) estimates were maximum (>50%) for the traits such as days taken to attain the 50% flowering, number of clusters/plant, number of pods/plant and 100 seed weight. The correlation and path analysis proved the selection of the yield attributes in blackgram based on the characters, viz., number of pods/plant and number of cluster/plants. The first three principal components, having the Eigen values more than 1, contributed 84.52% towards variability among the 25 genotypes screened for quantitative traits. Based on the average linkage, 25 genotypes were grouped into five (5) clusters.

scholarly journals Genetic Divergence in Urena lobata Accessions to Quantitative Traits

2019 ◽  
Vol 11 (11) ◽  
pp. 81
Author(s):  
Lucinete Miranda Gomes ◽  
Albejamere Pereira de Castro ◽  
Therezinha de Jesus Pinto Fraxe ◽  
Pedro de Queiroz Costa Neto ◽  
Angela Maria da Silva Mendes ◽  
...  
Keyword(s):  
Genetic Variability ◽  
Genetic Improvement ◽  
Quantitative Traits ◽  
Germplasm Collection ◽  
Clustering Method ◽  
Reliable Measure ◽  
High Heritability ◽  
Great Divergence ◽  
Phenotypic Groups ◽  
Selection Of

In this study, 14 quantitative traits were evaluated, divided into five distinct categories, related to the plants, leaves, flowers, fruits and seeds of seven Mallow accessions belonging to the NUSEC/UFAM germplasm collection. With the characteristics measured, the genetic variability of the accessions was evaluated, aiming at the genetic improvement of the culture. Through the analysis of variance, it was possible to assemble and propose the 14 agronomic descriptors, being that with the application of the clustering method (UPGMA), which generated a dendrogram of dissimilarity, it was possible to divide the seven genotypes into two distinct phenotypic groups, and their subgroups. The study showed that there is a great divergence between the accesses and the recommendation for the crossover is between the accesses ANÃ/MAC, ANÃ/MAQ and PIN/BER. The high heritability observed for the characters analyzed suggests the phenotypic value as a reliable measure for selection of the genotypes studied.

scholarly journals Genetic variability of hull-less barley accessions based on molecular and quantitative data

2015 ◽  
Vol 50 (2) ◽  
pp. 160-167 ◽  
Author(s):  
Ricardo Meneses Sayd ◽  
Renato Fernando Amabile ◽  
Fabio Gelape Faleiro ◽  
Graciele Bellon
Keyword(s):  
Molecular Markers ◽  
Genetic Variability ◽  
Quantitative Data ◽  
Quantitative Traits ◽  
Agronomic Traits ◽  
The Other ◽  
Brazilian Cerrado ◽  
Breeding Programs ◽  
Barley Genotypes ◽  
Selection Of

The objective of this work was to characterize and quantify the genetic, molecular, and agronomic variability of hull-less barley genotypes, for the selection of parents and identification of genotypes adapted to the irrigated production system in the Brazilian Cerrado. Eighteen hull-less barley accessions were evaluated, and three covered barley accessions served as reference. The characterization was based on 157 RAPD molecular markers and ten agronomic traits. Genetic distance matrices were obtained based on molecular markers and quantitative traits. Graphic grouping and dispersion analyses were performed. Genetic, molecular, and agronomic variability was high among genotypes. Ethiopian accessions were genetically more similar, and the Brazilian ones were genetically more distant. For agronomic traits, two more consistent groupings were obtained, one with the most two-rowed materials, and the other with six-rowed materials. The more diverging materials were the two-rowed CI 13453, CN Cerrado 5, CN Cerrado 1, and CN Cerrado 2. The PI 356466, CN Cerrado 1, PI 370799, and CI 13453 genotypes show agronomic traits of interest and, as genetically different genotypes, they are indicated for crossing, in breeding programs.

scholarly journals Variations in agronomic traits of Soybean genotypes

2015 ◽  
Vol 12 (2) ◽  
pp. 90-100 ◽  
Author(s):  
MSA Khan ◽  
MA Karim ◽  
MM Haque ◽  
AJMS Karim ◽  
MAK Mian
Keyword(s):  
Genetic Variability ◽  
Quantitative Traits ◽  
Agronomic Traits ◽  
Yield Potential ◽  
Morphological Similarity ◽  
Experimental Site ◽  
Soybean Genotypes ◽  
Clustering Pattern ◽  
High Degree ◽  
Selection Of

The experiment was conducted at the experimental site of Agronomy Department of the Bangabandhu Sheikh Mujibur Rahman Agricultural University, Salna, Gazipur during January to June 2010 to evaluate some important agronomic traits of one hundred and fifteen genotypes of soybean to screen out high yielding soybean genotypes. Considerable genetic variability was observed in the 115 germplasm. Depending on the variability in quantitative traits, the genotypes were grouped in six clusters. The genotypes which have greater morphological similarity were grouped in clusters. The results indicated the presence of high degree of divergence in the genotypes. The clustering pattern of the 115 soybean genotypes in six groups and their inter-group distances revealed that genotypes in Cluster III comprised of BARI Soybean 5, G00083, BARI Soybean 6, G00342, BD 2338, BD 2355, BD 2329, BD 2340, AGS 95, G00056, AGS 129, BD 2336, BGH 02026, BGM 02093, Galarsum, BD 2350, G00084, BD 2331, G00103 indicated better performance which could be marked for the selection of yield potential genotypes through further evaluation. DOI: http://dx.doi.org/10.3329/sja.v12i2.21921 SAARC J. Agri., 12(2): 90-100 (2014)

Evolution and Selection of Quantitative Traits

2018 ◽  
Author(s):  
Bruce Walsh ◽  
Michael Lynch
Keyword(s):  
Mathematical Models ◽  
Quantitative Genetics ◽  
Complex Traits ◽  
Evolutionary Biology ◽  
Quantitative Traits ◽  
Specific Gene ◽  
Real World Data ◽  
Holistic Treatment ◽  
Genetics And Genomics ◽  
Selection Of

Quantitative traits—be they morphological or physiological characters, aspects of behavior, or genome-level features such as the amount of RNA or protein expression for a specific gene—usually show considerable variation within and among populations. Quantitative genetics, also referred to as the genetics of complex traits, is the study of such characters and is based on mathematical models of evolution in which many genes influence the trait and in which non-genetic factors may also be important. Evolution and Selection of Quantitative Traits presents a holistic treatment of the subject, showing the interplay between theory and data with extensive discussions on statistical issues relating to the estimation of the biologically relevant parameters for these models. Quantitative genetics is viewed as the bridge between complex mathematical models of trait evolution and real-world data, and the authors have clearly framed their treatment as such. This is the second volume in a planned trilogy that summarizes the modern field of quantitative genetics, informed by empirical observations from wide-ranging fields (agriculture, evolution, ecology, and human biology) as well as population genetics, statistical theory, mathematical modeling, genetics, and genomics. Whilst volume 1 (1998) dealt with the genetics of such traits, the main focus of volume 2 is on their evolution, with a special emphasis on detecting selection (ranging from the use of genomic and historical data through to ecological field data) and examining its consequences. This extensive work of reference is suitable for graduate level students as well as professional researchers (both empiricists and theoreticians) in the fields of evolutionary biology, genetics, and genomics. It will also be of particular relevance and use to plant and animal breeders, human geneticists, and statisticians.

scholarly journals Prediction of meat quality traits in the abattoir using portable near-infrared spectrometers: heritability of predicted traits and genetic correlations with laboratory-measured traits

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Simone Savoia ◽  
Andrea Albera ◽  
Alberto Brugiapaglia ◽  
Liliana Di Stasio ◽  
Alessio Cecchinato ◽  
...  
Keyword(s):  
Meat Quality ◽  
Near Infrared ◽  
External Validation ◽  
Genetic Correlations ◽  
Genetic Selection ◽  
Quality Traits ◽  
Eye Muscle ◽  
Meat Quality Traits ◽  
Color Traits ◽  
Selection Of

Abstract Background The possibility of assessing meat quality traits over the meat chain is strongly limited, especially in the context of selective breeding which requires a large number of phenotypes. The main objective of this study was to investigate the suitability of portable infrared spectrometers for phenotyping beef cattle aiming to genetically improving the quality of their meat. Meat quality traits (pH, color, water holding capacity, tenderness) were appraised on rib eye muscle samples of 1,327 Piemontese young bulls using traditional (i.e., reference/gold standard) laboratory analyses; the same traits were also predicted from spectra acquired at the abattoir on the intact muscle surface of the same animals 1 d after slaughtering. Genetic parameters were estimated for both laboratory measures of meat quality traits and their spectra-based predictions. Results The prediction performances of the calibration equations, assessed through external validation, were satisfactory for color traits (R2 from 0.52 to 0.80), low for pH and purge losses (R2 around 0.30), and very poor for cooking losses and tenderness (R2 below 0.20). Except for lightness and purge losses, the heritability estimates of most of the predicted traits were lower than those of the measured traits while the genetic correlations between measured and predicted traits were high (average value 0.81). Conclusions Results showed that NIRS predictions of color traits, pH, and purge losses could be used as indicator traits for the indirect genetic selection of the reference quality phenotypes. Results for cooking losses were less effective, while the NIR predictions of tenderness were affected by a relatively high uncertainty of estimate. Overall, genetic selection of some meat quality traits, whose direct phenotyping is difficult, can benefit of the application of infrared spectrometers technology.

scholarly journals Combining metabolomic and transcriptomic approaches to assess and improve crop quality traits

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Delphine M. Pott ◽  
Sara Durán-Soria ◽  
Sonia Osorio ◽  
José G. Vallarino
Keyword(s):  
Quality Trait ◽  
Quality Traits ◽  
Crop Species ◽  
Breeding Programs ◽  
Crop Quality ◽  
Crop Varieties ◽  
New Genes ◽  
Technical Advances ◽  
Health Promoting ◽  
Selection Of

AbstractPlant quality trait improvement has become a global necessity due to the world overpopulation. In particular, producing crop species with enhanced nutrients and health-promoting compounds is one of the main aims of current breeding programs. However, breeders traditionally focused on characteristics such as yield or pest resistance, while breeding for crop quality, which largely depends on the presence and accumulation of highly valuable metabolites in the plant edible parts, was left out due to the complexity of plant metabolome and the impossibility to properly phenotype it. Recent technical advances in high throughput metabolomic, transcriptomic and genomic platforms have provided efficient approaches to identify new genes and pathways responsible for the extremely diverse plant metabolome. In addition, they allow to establish correlation between genotype and metabolite composition, and to clarify the genetic architecture of complex biochemical pathways, such as the accumulation of secondary metabolites in plants, many of them being highly valuable for the human diet. In this review, we focus on how the combination of metabolomic, transcriptomic and genomic approaches is a useful tool for the selection of crop varieties with improved nutritional value and quality traits.

Analysis of phenotypic diversity of apricot (Prunus armeniaca L.) accessions from Jammu and Kashmir, India

2021 ◽  
pp. 1-13
Author(s):  
Showkat A. Zargar ◽  
Aijaz A. Wani ◽  
M. I. S. Saggoo
Keyword(s):  
Fruit Quality ◽  
Quantitative Traits ◽  
Fruit Weight ◽  
Kernel Weight ◽  
Prunus Armeniaca ◽  
Quality Traits ◽  
Jammu And Kashmir ◽  
Fruit Length ◽  
Upgma Dendrogram ◽  
Fruit Quality Traits

Abstract Apricot (Prunus armeniaca L.) is a world-wide highly appreciated fruit, with its attractive colour, soft texture and typical flavour. In the current investigation, 68 apricot accessions collected from Jammu and Kashmir, India were analysed to determine the measure of variation using 12 qualitative and 16 quantitative traits with an aim to identify superior apricot accessions with excellent fruit quality traits. High phenotypic variability was observed among the studied apricot accessions with significant differences among most of the qualitative and quantitative traits. Fruit-related characteristics including fruit weight, fruit length, fruit ratio, fruit firmness, fruit shape, fruit suture, stone weight, kernel weight and stone shape were the most diverse with a high coefficient of variation (>30%). One way analysis of variance showed significant differences (P < 0.0001) among all the quantitative traits. Significant positive and negative correlations were observed between all the agronomically important fruit quality traits. The principal component analysis (PCA) revealed that 75.34% of the variability was defined by the first eight components. The unweighted pair group method with arithmetic mean (UPGMA) dendrogram, based on all traits measured grouped the accessions into two main clusters with several sub-clusters. Both UPGMA dendrogram and PCA scatter plot formed a cluster of 14 accessions, having the highest values regarding most important fruit quality traits such as fruit weight, fruit length and width, fruit ratio, stone weight and kernel weight can be treated as potentially superior accessions. These accessions can be used directly for cultivation and in future apricot breeding programmes. The present findings are promising for genetic resource management, cultivar improvement and commercial applications of apricot in Jammu and Kashmir, India.

Genetic markers and the selection of quantitative traits in forage grasses

Euphytica ◽  
1994 ◽  
Vol 77 (3) ◽  
pp. 269-275 ◽  
Author(s):  
M. D. Hayward ◽  
N. J. Mcadam ◽  
J. G. Jones ◽  
C. Evans ◽  
G. M. Evans ◽  
...  
Keyword(s):  
Genetic Markers ◽  
Quantitative Traits ◽  
Forage Grasses ◽  
Selection Of

scholarly journals A Systematic Literature Review of Multi-Criteria Decision-Making Methods for Sustainable Selection of Insulation Materials in Buildings

2021 ◽  
Vol 13 (2) ◽  
pp. 737
Author(s):  
Indre Siksnelyte-Butkiene ◽  
Dalia Streimikiene ◽  
Tomas Balezentis ◽  
Virgilijus Skulskis
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Energy Demand ◽  
Energy Performance ◽  
Future Research ◽  
Multi Criteria Decision Making ◽  
Insulation Materials ◽  
Advantages And Disadvantages ◽  
Selection Of

The European Commission has recently adopted the Renovation Wave Strategy, aiming at the improvement of the energy performance of buildings. The strategy aims to at least double renovation rates in the next ten years and make sure that renovations lead to higher energy and resource efficiency. The choice of appropriate thermal insulation materials is one of the simplest and, at the same time, the most popular strategies that effectively reduce the energy demand of buildings. Today, the spectrum of insulation materials is quite wide, and each material has its own specific characteristics. It is recognized that the selection of materials is one of the most challenging and difficult steps of a building project. This paper aims to give an in-depth view of existing multi-criteria decision-making (MCDM) applications for the selection of insulation materials and to provide major insights in order to simplify the process of methods and criteria selection for future research. A systematic literature review is performed based on the Search, Appraisal, Synthesis and Analysis (SALSA) framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. In order to determine which MCDM method is the most appropriate for different questions, the main advantages and disadvantages of different methods are provided.

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