Visual Clustering Analysis of some traditional Mango (Mangifera indica L.) varieties of Murshidabad District, West Bengal using Clust Vis web tool

  • Mitu De Department of Botany, Gurudas College, Kolkata 700054, India https://orcid.org/0000-0002-0757-2381
  • Subhasree Dutta Department of Zoology, Rammohan College, Kolkata 700009, West Bengal, India
  • Susanta Ray Goalpara Tarun Sangha Junior High School, Khagra, Murshidabad, India
  • Santi Ranjan Dey Department of Zoology, Rammohan College, Kolkata 700009, West Bengal, India https://orcid.org/0000-0003-2769-9109

Abstract

A clustergram or a heatmap is one of several techniques that directly visualize data without the need for dimensionality reduction. Heatmap is a representation of data in the form of a map or diagram in which data values are represented as colours. Cluster heatmaps have high data density, allowing them to compact large amounts of information into a small space. “ClustVis”, is a web tool for visualizing clustering of multivariate data using Principal Component Analysis and Heatmap. Using this web tool, genetic relationships among the traditional mango (Mangifera indica L.) varieties can be visualized. In this investigation ten (10) indigenous mango varieties were selected. These were elite varieties of Murshidabad viz. Anaras, Bhabani, Champa, Dilpasand, Kalabati, Kohinoor, Kohitoor, Molamjam. The morphological and biological characters were analyzed using this tool. Analysis and assessment of the current status of mango genetic resources will be important for ascertaining the relationship among traditional varieties. This data may be used for appropriate conservation and sustainable utilization measures. This information may also be needed to carry out breeding programs to develop improved cultivars for sustainable livelihoods of local communities.

Keywords: ClustVis; Heatmap; traditional mango variety; Murshidabad.

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De, M., Dutta, S., Ray, S., & Dey, S. (2021). Visual Clustering Analysis of some traditional Mango (Mangifera indica L.) varieties of Murshidabad District, West Bengal using Clust Vis web tool. International Journal of Advancement in Life Sciences Research, 4(3), 32-43. https://doi.org/https://doi.org/10.31632/ijalsr.2021.v04i03.005