Home Physical Sciences Selection of the elite genotype among the five different Eucalyptus hybrid pulpwood clones for social and farm forestry
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Selection of the elite genotype among the five different Eucalyptus hybrid pulpwood clones for social and farm forestry

  • Sowmya Kuppusamy ORCID logo EMAIL logo and Thamaraiselvi Kaliannan
Published/Copyright: December 16, 2025
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Abstract

To meet the raw material demands of the paper industry, social and farm forestry programs require the selection of improved Eucalyptus clones with superior wood properties. In this study, five improved Eucalyptus hybrid clones 9, 21, 4, 16, and 41 were evaluated. These clones were selected on the basis of their field performance. Clone ITC 2315, which performs well in commercial pulp mills, was used as the reference clone. The objective of this study was to assess the kappa number, pulp yield, and pulp properties of the five test clones and compare their performance with the reference clone. Kraft pulping of the extracted wood chips was carried out using a 19 % active alkali charge at 165 °C. Clones with higher pulp yield exhibited lower kappa numbers, indicating effective lignin removal during pulping. The resulting kraft pulps were bleached using a sequence of 70 % chlorine dioxide, 1 % hydrogenperoxide, and 30 % chlorinedioxide. Handsheets were prepared from both the unbleached and bleached pulps, and their properties including brightness, tensile strength, burst index, bulk, and opacity were evaluated. Clones 41, 16, 21 demonstrated higher pulp yields than the reference clone and showed favourable pulp and paper properties. These results suggest that these inter-hybrid clones are more suitable for papermaking applications.


Corresponding author: Sowmya Kuppusamy, PG & Research Department of Biotechnology and Bioinformatics, Holy Cross College, Tiruchirappalli, 620002, Tamil Nadu, India; and Laboratory of Molecular Bioremediation and Nanobiotechnology, Department of Environmental Biotechnology, School of Environmental Sciences, Bharathidasan University, Tiruchirappalli, 620024, Tamil Nadu, India, E-mail:

Acknowledgments

We thank the Department of Science and Technology, Government of India, for providing support through the Fund improvement of S&T infrastructure in Universities and Higher Educational Institutions (FIST) program (Grant No. SR/FIST/College-/2020/943).

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/npprj-2025-0040).


Received: 2025-06-19
Accepted: 2025-12-04
Published Online: 2025-12-16

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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