Principal Component Analysis in Biometric, Pulp Quality and Anatomical Properties of Thronless Bamboo (Bambusa balcooa)

Main Article Content

N. Krishnakumar
S. Umesh Kanna
K. T. Parthiban

Abstract

Aims: To estimate the impact, connection and association among the biometric attributes, pulping qualities and anatomical characters in Bambusa balcooa.

Place and Duration of Study: The study was conducted across the agro climatic regions viz., North Eastern Zone, Northern Zone, Western Zone, Cauvery Delta Zone and Southern Zone of Tamil Nadu, India during 2017-2018.

Methodology: The Principal Components Analysis (PCA) was examined to establish the numbers of clusters using Statistical Package for Social Studies (SPSS) version 16.0.1 software in order to identify the patterns of variation (PCA). The principal component analysis was computed using the equation PCA = Σa jXj.

Results: The PCA separated into three cluster principal components among the nineteen parameters studied. Out of nineteen principal components generated, twelve principal components had contributed positively on pulp yield. Among these twelve traits, maximum contribution to the pulp yield was observed by the traits viz., numbers of culms, hollocellulose, kappa number, tear index, burst index, fibre wall thickness and vessel diameter with respect to Bambusa balcooa.

Conclusion: The results showed some relationships between the biometric attributes, pulping qualities and anatomical characters in Bambusa balcooa. PCA was shown to be a useful tool for assessing the impact and connection for further research.

Keywords:
Thornless bamboos, PCA, impact & connection, biometric attributes, pulping qualities, anatomical characters, Bambusa balcooa

Article Details

How to Cite
Krishnakumar, N., Kanna, S. U., & Parthiban, K. T. (2019). Principal Component Analysis in Biometric, Pulp Quality and Anatomical Properties of Thronless Bamboo (Bambusa balcooa). International Journal of Environment and Climate Change, 9(6), 350-355. https://doi.org/10.9734/ijecc/2019/v9i630120
Section
Original Research Article

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