Range-wide genetic variation of black spruce

1978 ◽  
Vol 8 (4) ◽  
pp. 463-473 ◽  
Author(s):  
E. K. Morgenstern
Keyword(s):  
Black Spruce ◽  
Atlantic Coast ◽  
Principal Component ◽  
Clinal Variation ◽  
Variation Pattern ◽  
Breeding Programs ◽  
Total Height ◽  
Seed Sources ◽  
Natural Stands ◽  
Major Factors

Initiation and cessation of growth and total height of seedlings at ages 2 and 3 years were measured in a nursery experiment with 100 seed sources of Piceamariana (Mill.) B.S.P. from natural stands sampled across the range from the Atlantic Coast to Alaska. Correlations with climatic and geographic factors were calculated and principal component, variance, and regression analyses made. The results showed that photoperiod and temperature were major factors of natural selection and that a clinal variation pattern is predominant. Since south–north trends of photoperiod and temperature are closely related to latitude, the regression of phenological variables and of height on latitude of origin gave an indication of response gradients. Total height changed by 2 to 11% from the experimental mean if a seed source was moved 1° of latitude north or south from its native area to a new site. The consequences for seed movement and breeding programs are discussed.

scholarly journals Genetic variability and genome-wide association analysis of flavor and texture in cooked beans (Phaseolus vulgaris L.)

2021 ◽  
Author(s):  
Amber Bassett ◽  
Kelvin Kamfwa ◽  
Daniel Ambachew ◽  
Karen Cichy
Keyword(s):  
Genetic Variability ◽  
Seed Coat ◽  
Principal Component ◽  
Breeding Programs ◽  
Flavor Intensity ◽  
Genome Wide ◽  
White Bean ◽  
The Usa ◽  
New Varieties ◽  
End Use

Abstract Key message Cooked bean flavor and texture vary within and across 20 Andean seed types; SNPs are significantly associated with total flavor, beany, earthy, starchy, bitter, seed-coat perception, and cotyledon texture. Abstract Common dry beans are a nutritious food recognized as a staple globally, but their consumption is low in the USA. Improving bean flavor and texture through breeding has the potential to improve consumer acceptance and suitability for new end-use products. Little is known about genetic variability and inheritance of bean sensory characteristics. A total of 430 genotypes of the Andean Diversity Panel representing twenty seed types were grown in three locations, and cooked seeds were evaluated by a trained sensory panel for flavor and texture attribute intensities, including total flavor, beany, vegetative, earthy, starchy, sweet, bitter, seed-coat perception, and cotyledon texture. Extensive variation in sensory attributes was found across and within seed types. A set of genotypes was identified that exhibit extreme attribute intensities generally stable across all three environments. seed-coat perception and total flavor intensity had the highest broad-sense heritability (0.39 and 0.38, respectively), while earthy and vegetative intensities exhibited the lowest (0.14 and 0.15, respectively). Starchy and sweet flavors were positively correlated and highest in white bean genotypes according to principal component analysis. SNPs associated with total flavor intensity (six SNPs across three chromosomes), beany (five SNPs across four chromosomes), earthy (three SNPs across two chromosomes), starchy (one SNP), bitter (one SNP), seed-coat perception (three SNPs across two chromosomes), and cotyledon texture (two SNPs across two chromosomes) were detected. These findings lay a foundation for incorporating flavor and texture in breeding programs for the development of new varieties that entice growers, consumers, and product developers alike.

scholarly journals Simple Sequence Repeat and S-Locus Genotyping to Assist the Genetic Characterization and Breeding of Polyploid Prunus Species, P. spinosa and P. domestica subsp. insititia

2021 ◽  
Author(s):  
Júlia Halász ◽  
Noémi Makovics-Zsohár ◽  
Ferenc Szőke ◽  
Sezai Ercisli ◽  
Attila Hegedűs
Keyword(s):  
Simple Sequence Repeat ◽  
Principal Component ◽  
Sequence Repeat ◽  
Breeding Programs ◽  
Allele Number ◽  
Genetic Potential ◽  
Ssr Loci ◽  
High Level ◽  
Diversity Studies ◽  
Simple Sequence

AbstractPolyploid Prunus spinosa (2n = 4 ×) and P. domestica subsp. insititia (2n = 6 ×) represent enormous genetic potential in Central Europe, which can be exploited in breeding programs. In Hungary, 16 cultivar candidates and a recognized cultivar ‘Zempléni’ were selected from wild-growing populations including ten P. spinosa, four P. domestica subsp. insititia and three P. spinosa × P. domestica hybrids (2n = 5 ×) were also created. Genotyping in eleven simple sequence repeat (SSR) loci and the multiallelic S-locus was used to characterize genetic variability and achieve a reliable identification of tested accessions. Nine SSR loci proved to be polymorphic and eight of those were highly informative (PIC values ˃ 0.7). A total of 129 SSR alleles were identified, which means 14.3 average allele number per locus and all accessions but two clones could be discriminated based on unique SSR fingerprints. A total of 23 S-RNase alleles were identified and the complete and partial S-genotype was determined for 10 and 7 accessions, respectively. The DNA sequence was determined for a total of 17 fragments representing 11 S-RNase alleles. ‘Zempléni’ was confirmed to be self-compatible carrying at least one non-functional S-RNase allele (SJ). Our results indicate that the S-allele pools of wild-growing P. spinosa and P. domestica subsp. insititia are overlapping in Hungary. Phylogenetic and principal component analyses confirmed the high level of diversity and genetic differentiation present within the analysed accessions and indicated putative ancestor–descendant relationships. Our data confirm that S-locus genotyping is suitable for diversity studies in polyploid Prunus species but non-related accessions sharing common S-alleles may distort phylogenetic inferences.

scholarly journals Person - job fi t and the work commitment of IT Personnel

2016 ◽  
Vol 26 (2) ◽  
pp. 218 ◽  
Author(s):  
Therasa C. ◽  
C. Vijayabanu
Keyword(s):  
Regression Analysis ◽  
Principal Component ◽  
Attrition Rate ◽  
P Value ◽  
Work Commitment ◽  
Key Factors ◽  
Coeffi Cients ◽  
Work Autonomy ◽  
Major Factors ◽  
The Impact

Introduction: There have been given a much higher importance to employee commitment and retention since India is experiencing the highest attrition rate globally Economic Times, 2015. Hence, considering the factors of Person-job fi t to interpret the impact towards work commitment is very well essential, especially in the current scenario. Work Commitment is a vital element in any organization which has outstanding impact on productivity and functioning and hence it is very much vital to have a committed workforce which is necessary in this competitive environment and tight labour market. In the same way, there is considerable amount of evidence that if P-J fi t is high then it will have a direct impact on organization commitment also. Person-job fi t is the compatibility between person’s competency and abilities and the requirements of the job Zheng et al.2. If there exists a mismatch between person-job fi t then the consequences might result in poor work commitment, low job satisfaction and extremely lower involvement in the job. Objective: This study analyzed the key factors that contribute to Person- job compatibility among IT workers and also analyzed the relationship and impact of Person- job compatibility towards work commitment. Methods: Exploratory Factor Analysis (EFA) was used to fi lter the key factors initially, followed by a linear regression technique to determine the impact of Person- job compatibility factors in work commitment on a sample of 300 employees. EFA used Principal Component analysis for extraction and Promax for rotation. Finally regression analysis was carried out to predict the work commitment through statistically significant person-job compatibility variables. Results: The impact of person-job compatibility on work commitment was studied through regression analysis and it imply that for every unit increase in HR Policy, a 0.52 (unstandardised coeffi cients) increase in work commitment is predicted and it has been turned out as a most impacting variable to predict work commitment. The coeffi cients for Relationship (B =.330, sig =.000), HR Policies (B =.519, sig =.000), Pay and Benefi ts (B =.386, sig =.000) and Employee Growth (B =.290, sig =.001) were statistically significant, since its p-value is .000 which is smaller than .05. The coeffi cients for Work Autonomy (B =.154, sig = .081) was not statistically signifi cant, since its p-value is 0.081 which is greater than.05. Conclusion: The major factors responsible for creating work commitment among IT employees are Relationship, HR Policies and strategies, Pay and benefi ts, Work autonomy and Employee growth. The most contributing regressors which accounts for creating work commitment are HR policies, Pay and benefi ts, Employee growth and work autonomy.

scholarly journals Penerapan Kansei Engineering dalam Perbandingan Desain Aplikasi Mobile Marketplace di Indonesia

2020 ◽  
Vol 6 (2) ◽  
Author(s):  
Nucky Vilano ◽  
Setia Budi
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Mobile Application ◽  
Principal Component ◽  
Kansei Engineering ◽  
Multivariate Statistical ◽  
Christian University ◽  
Emotional Factors ◽  
Coefficient Corrélation ◽  
Major Factors

The company's application design is very important because it displays the company's image and to attract more users to purchase/utilize the application. This research applies Kansei Engineering Method to analyze the emotion or feelings of the user towards the design of a mobile application interface. Six Kansei Words and three specimens are utilised in this research, where Kansei words are selected from words related to user experience. The participants of this research consist of 54 students from Maranatha Christian University. Participants’ responses are studied using multivariate statistical analysis (e.g., Coefficient Correlation Analysis, Principal Component Analysis, and Factor Analysis). This study explores the emotional factors that occur in designing an application. This analysis shows that there are some major factors that greatly influence the design of a mobile application interface.

scholarly journals Use of Highly Discriminating Morphological Characters and Isozymes in the Study of Spanish Chestnut Cultivars

2006 ◽  
Vol 131 (6) ◽  
pp. 770-779 ◽  
Author(s):  
Santiago Pereira-Lorenzo ◽  
María Belén Díaz-Hernández ◽  
Ana María Ramos-Cabrer
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Multivariate Analysis ◽  
Castanea Sativa ◽  
Principal Component ◽  
Market Value ◽  
Morphological Characters ◽  
Minor Importance ◽  
Breeding Programs ◽  
And Cluster Analysis

Morphological characters (six traits) and isozymes (four systems, five loci) were used to discriminate between Spanish chestnut cultivars (Castanea sativa Mill.) from the Iberian Peninsula. A total of 701 accessions (representing 168 local cultivars) were analyzed from collections made between 1989 and 2003 in the main chestnut growing areas: 31 were from Andalucía (12 cultivars), 293 from Asturias (65 cultivars), 25 from Castilla-León (nine cultivars), four from Extremadura (two cultivars) and 348 from Galicia (80 cultivars). Data were synthesized using multivariate analysis, principal component analysis, and cluster analysis. A total of 152 Spanish cultivars were verified: 58 cultivars of major importance and 94 of minor importance, of which 18 had high intracultivar variation. Thirty-seven cultivars were clustered into 14 synonymous groups. Six of these were from Galicia, one from Castilla-León (El Bierzo), four from Asturias, one from Asturias and Castilla-León (El Bierzo), and two from Asturias, Castilla-León (El Bierzo), and Galicia. The chestnut cultivars from Galicia and Asturias were undifferentiated in genetic terms, indicating that they are not genetically isolated. Overall, chestnut cultivars from southern Spain showed the least variation. Many (58%) of Spanish cultivars produced more than 100 nuts/kg; removing this low market-value character will be a high priority. The data obtained will be of use in chestnut breeding programs in Spain and elsewhere.

Boreal forest provenance tests used to predict optimal growth and response to climate change: 2. Black spruce

2009 ◽  
Vol 39 (1) ◽  
pp. 143-153 ◽  
Author(s):  
Ashley M. Thomson ◽  
Claire L. Riddell ◽  
William H. Parker
Keyword(s):  
Survival Data ◽  
Transfer Functions ◽  
Black Spruce ◽  
Optimal Growth ◽  
Height Growth ◽  
Optimal Performance ◽  
Seed Sources ◽  
Contour Lines ◽  
Provenance Trials ◽  
Maximum Temperatures

Height, diameter, and survival data were obtained from 20 range-wide black spruce ( Picea mariana (Mill.) BSP) provenance trials established from 1973 to 1977. Population response functions based on February minimum temperatures were developed for 23 Ontario and Great Lakes states provenances to predict climate values maximizing height growth for individual seed sources. Site transfer functions based on February maximum temperatures and May maximum temperatures were developed for five test sites to predict climate values maximizing height growth for test locations. Contour lines representing optimal performance were fitted to current (1961–1990) and future (2041–2070) climate grids. For black spruce seed sources from the east of Lake Superior and Lake Huron, optimal height growth was achieved between 45° and 47°N; for the western sources optimal performance moved north between 46° and 48°N. In eastern Ontario, height growth of northern sources may increase with transfer to warmer environments and with future temperature increases. Central sources are currently growing at or close to optimum and will be negatively affected by increased future temperatures. Southern sources may currently benefit from transfer to cooler environments, and the effects of global warming may cause significant height growth loss and the potential extirpation of local populations.

Drought Response of Rice in Northeastern Thailand Assessed via Fourier Transform Infrared Spectroscopy

2021 ◽  
Vol 74 ◽  
Author(s):  
Piyaporn Phansak ◽  
Supatcharee Siriwong ◽  
Nantawan Kanawapee ◽  
Kanjana Thumanu ◽  
Wuttichai Gunnula ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Drought Stress ◽  
Lignin Content ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Breeding Programs ◽  
Treatment Groups ◽  
Drought Tolerant ◽  
Relative Water ◽  
Rice Landrace

Abstract Drought isa major constraint in many rainfed areas and affects rice yield. We aimed to characterize the physiological changes in rice in response to drought using Fourier transform infrared (FTIR) spectroscopy. Eighty rice landrace seedlings were subjected to drought in the greenhouse using a PEG 6000. Physiological parameters, including total chlorophyll content, relative water content, electrolyte leakage, and biochemical changes were evaluated. Based on the FTIR results, the landraces were divided into three main groups: tolerant, moderately tolerant, and susceptible. Principal component analysis revealed spectral differences between the control and drought stress treatment groups. Lipid, pectin, and lignin content increased after drought stress. The biochemical components of plants at different drought tolerance levels were also compared. The lipid (CH2 and CH3), lignin (C=C), pectin (C=O), and protein (C=O, N–H) contents were the highest in the drought-tolerant cultivars, followed by the moderately tolerant and susceptible cultivars, respectively. Cultivar 17 and 49 were the most tolerant, and the functional groups were identified and characterized using FTIR. Overall, these results will be useful in selecting parental cultivars for rice breeding programs.

scholarly journals Ancient Danish Apple Cultivars—A Comprehensive Metabolite and Sensory Profiling of Apple Juices

Metabolites ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 139 ◽  
Author(s):  
Nunzia Iaccarino ◽  
Camilla Varming ◽  
Mikael Agerlin Petersen ◽  
Nanna Viereck ◽  
Birk Schütz ◽  
...  
Keyword(s):  
Sugar Content ◽  
Screening Method ◽  
Principal Component ◽  
Gas Chromatography Mass Spectrometry ◽  
Breeding Programs ◽  
Apple Cultivars ◽  
Aroma Components ◽  
Different Levels ◽  
Comprehensive Characterization

In recent decades, intensive selective breeding programs have allowed the development of disease-resistant and flavorsome apple cultivars while leading to a gradual decline of a large number of ancient varieties in many countries. However, the re-evaluation of such cultivars could lead to the production new apple-based products with health beneficial properties and/or unique flavor qualities. Herein, we report the comprehensive characterization of juices obtained from 86 old, mostly Danish, apple cultivars, by employing traditional analysis (ion chromatography, °Brix, headspace gas chromatography/mass spectrometry (GC–MS), and panel test evaluation) as well as an innovative nuclear magnetic resonance (NMR)-based screening method developed by Bruker for fruit juices, known as Spin Generated Fingerprint (SGF) Profiling™. Principal component analysis showed large differences in aroma components and sensory characteristics, including odd peculiar odors and flavors such as apricot and peach, and very different levels of phenolic compounds, acids and sugars among the analyzed juices. Moreover, we observed a tendency for late-season juices to be characterized by higher °Brix values, sugar content and they were perceived to be sweeter and more flavor intense than early-season juices. Our findings are useful for the production of specialty vintage-cultivar apple juices or mixed juices to obtain final products that are characterized both by healthy properties and peculiar sensory attributes.

An Empirical Study on the Financial Competitiveness Evaluation System of Stock Exchange Listed SMEs of Gujarat, India

2019 ◽  
Vol 46 (4) ◽  
pp. 256-263
Author(s):  
Nikita Mehta ◽  
Mamta Brahmbhatt
Keyword(s):  
Evaluation System ◽  
Stock Exchange ◽  
Small And Medium Enterprises ◽  
Principal Component ◽  
Factors Affecting ◽  
Financial Factors ◽  
Management Efficiency ◽  
Major Factors ◽  
Medium Enterprises ◽  
Financial Competitiveness

The purpose of this study is to identify the financial factors that enhance the financial competitiveness of small and medium enterprises (SMEs) in Gujarat, India. The principal component analysis has been applied to extract the financial factors from financial performance ratios of a sample size of 38 stock exchange SMEs, based in Gujarat, India. The ranking has been given to the SMEs based upon their factor score and comprehensive score. The results show that profitability, management efficiency, liquidity and leverage factors are the major factors affecting the financial competitiveness of SMEs. The study covers only one state of the country, and the findings from different states may differ and need to get verified. Despite the highest contribution of SMEs in the GDP of India, there exist very few Indian studies on SME competitiveness. This study contributes to filling this gap.

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