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      Comparative studies of four cumin landraces grown in Egypt

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          Abstract

          One of the significant aromatic plants applied in food and pharma is cumin. Despite its massive trading in Egypt, there are no comprehensive reports on cumin landraces profile screening. This study aimed to investigate the variation in seeds’ physical and biochemical profiles and genetic diversity as well as assess the efficiency of seeds’ germination under salinity stress. Consequently, during the 2020/2021 growing season, four common cumin seed landraces were gathered from various agro-climatic regions: El Gharbia, El Menia, Assiut, and Qena. Results showed a significant variation in physical profile among the four seeds of landraces. In addition, Assiut had the highest percentage of essential oil at 8.04%, whilst Qena had the largest amount of cumin aldehyde, the primary essential oil component, at 25.19%. Lauric acid was found to be the predominant fatty acid (54.78 to 62.73%). According to ISSR amplification, El Menia presented a negative unique band, whereas other landraces offered a positive band. Additionally, the cumin genotypes were separated into two clusters by the dendrogram, with El Gharbia being located in an entirely separate cluster. There were two sub-clusters within the other cluster: El Menia in one and Assiut and Qena in the other. Moreover, the germination sensitivity to the diverse salinity concentrations (control, 4, 8, 12, and 16 dS/m) findings showed that landraces exhibited varying responses to increased salinity when El Gharbia and El Menia showed a moderate response at four dS/m. Whilst, Qena landraces showed supreme values among other landraces under 12 and 16 dS/m. The majority of the examined features had strong positive associations over a range of salinity levels, according to phenotypic correlation coefficient analysis. To accomplish the aims of sustainable agriculture in Egypt, it would be imperative that the potential breeding program for cumin landraces consider this screening study.

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          MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods.

          Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net.
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            Mechanisms of salinity tolerance.

            The physiological and molecular mechanisms of tolerance to osmotic and ionic components of salinity stress are reviewed at the cellular, organ, and whole-plant level. Plant growth responds to salinity in two phases: a rapid, osmotic phase that inhibits growth of young leaves, and a slower, ionic phase that accelerates senescence of mature leaves. Plant adaptations to salinity are of three distinct types: osmotic stress tolerance, Na(+) or Cl() exclusion, and the tolerance of tissue to accumulated Na(+) or Cl(). Our understanding of the role of the HKT gene family in Na(+) exclusion from leaves is increasing, as is the understanding of the molecular bases for many other transport processes at the cellular level. However, we have a limited molecular understanding of the overall control of Na(+) accumulation and of osmotic stress tolerance at the whole-plant level. Molecular genetics and functional genomics provide a new opportunity to synthesize molecular and physiological knowledge to improve the salinity tolerance of plants relevant to food production and environmental sustainability.
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              ClustVis: a web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap

              The Principal Component Analysis (PCA) is a widely used method of reducing the dimensionality of high-dimensional data, often followed by visualizing two of the components on the scatterplot. Although widely used, the method is lacking an easy-to-use web interface that scientists with little programming skills could use to make plots of their own data. The same applies to creating heatmaps: it is possible to add conditional formatting for Excel cells to show colored heatmaps, but for more advanced features such as clustering and experimental annotations, more sophisticated analysis tools have to be used. We present a web tool called ClustVis that aims to have an intuitive user interface. Users can upload data from a simple delimited text file that can be created in a spreadsheet program. It is possible to modify data processing methods and the final appearance of the PCA and heatmap plots by using drop-down menus, text boxes, sliders etc. Appropriate defaults are given to reduce the time needed by the user to specify input parameters. As an output, users can download PCA plot and heatmap in one of the preferred file formats. This web server is freely available at http://biit.cs.ut.ee/clustvis/.
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                Author and article information

                Contributors
                aliaamer@arc.sci.eg
                drmohamedmarey19@alexu.edu.eg
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                5 April 2024
                5 April 2024
                2024
                : 14
                : 7990
                Affiliations
                [1 ]Seed Technology Research Department, Field Crops Research Institute, Agriculture Research Center, ( https://ror.org/05hcacp57) Giza, Egypt
                [2 ]Cell Department, Field Crops Research Institute, Agriculture Research Center, ( https://ror.org/05hcacp57) Giza, Egypt
                [3 ]Horticultural Department, Faculty of Agriculture, Ain Shams University, ( https://ror.org/00cb9w016) Cairo, Egypt
                [4 ]Medicinal and Aromatic Plants Research Department, Horticulture Research Institute, Agricultural Research Center, ( https://ror.org/05hcacp57) Giza, Egypt
                [5 ]Department of Plant Cultivation Technology and Commodity Sciences, University of Life Sciences in Lublin, ( https://ror.org/03hq67y94) 13 Akademicka Street, 20-950 Lublin, Poland
                [6 ]Plant Production Department (Horticulture - Medicinal and Aromatic Plants), Faculty of Agriculture (Saba Basha), Alexandria University, ( https://ror.org/00mzz1w90) Alexandria, 21531 Egypt
                Article
                57637
                10.1038/s41598-024-57637-3
                10997781
                38580717
                acc6f0e2-5ced-4cc6-b476-c358fd24cf8b
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 3 July 2023
                : 20 March 2024
                Funding
                Funded by: Agricultural Research Center
                Categories
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                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                agricultural genetics,plant sciences,plant physiology,plant stress responses,secondary metabolism

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