Bioenergy crop production and management Open access Peer reviewed

Integrating dendrometric traits and wood density to predict biomass productivity, bioenergy yield, and carbon sequestration in hybrid Populus clones

Yanal Alkuddsi, Marius Aleinikovas, Benas Silinskas, Mohamad Alahmad and 6 more

Scientific Reports | Jul 16, 2026

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It is demonstrated that integrating dendrometric traits with wood density provides a robust predictive approach for biomass and bioenergy assessment in hybrid poplar plantations, and that branch exclusion can lead to substantial underestimation of stand-level resource availability in biomass-oriented plantation systems.

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Accurate prediction of biomass productivity and bioenergy potential remains a major challenge in plantation forestry, particularly for fast-growing species such as hybrid Populus where tree architecture, wood properties, and genetic variability interact in complex ways. This study evaluates the relationships between dendrometric traits and biomass-based bioenergy indicators across 19 hybrid poplar clones cultivated under northern European conditions. Diameter at breast height (DBH), tree height, stem volume, stem dry mass, branch dry mass, and wood density were used to estimate above-ground biomass, energy yield, carbon stock, and CO₂-equivalent mitigation potential. Substantial genetic variability was observed among clones, with mean above-ground biomass reaching 214.6 t ha⁻ 1 and ranging from 71.8 to 456.9 t ha⁻ 1 . DBH showed the strongest correlation with biomass accumulation (r = 0.768, p < 0.001), followed by stem volume (r = 0.724) and wood density (r = 0.647). A multiple regression model integrating stem volume and wood density explained 94.8% of the variation in biomass (R 2 = 0.948), Although volume and density explained a high proportion of biomass variation, this association should be interpreted as explanatory because biomass estimates are mathematically related to these variables. The model is therefore best viewed as an explanatory framework rather than a fully independent predictive model. Accounting for branch biomass increased estimated biomass, bioenergy yield, and carbon sequestration estimates by 24.63% compared with stem-only assessments, demonstrating that branch exclusion can lead to substantial underestimation of stand-level resource availability in biomass-oriented plantation systems. The clones SvSF Po11, SvSF Po12, and Nyd3261-Degrosso exhibited the highest biomass productivity and energy potential. These results demonstrate that integrating dendrometric traits with wood density provides a robust predictive approach for biomass and bioenergy assessment in hybrid poplar plantations.

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Yanal Alkuddsi

first | Lithuanian Research Centre for Agriculture and Forestry | ORCID 0009-0001-9840-6257

Marius Aleinikovas

middle | Lithuanian Research Centre for Agriculture and Forestry | ORCID 0000-0003-1588-2950

Benas Silinskas

middle | Lithuanian Research Centre for Agriculture and Forestry | ORCID 0000-0003-2353-5350

Mohamad Alahmad

middle | Council for Scientific and Industrial Research | ORCID 0009-0006-2802-6829

Abdul Monim Abdul Hafez

middle | Council for Scientific and Industrial Research | ORCID 0009-0008-2511-5548

Ibrahim Alghoraibi

middle | Council for Scientific and Industrial Research | ORCID 0000-0002-7609-9137

Mindaugas Skema

middle | Lithuanian Research Centre for Agriculture and Forestry | ORCID 0000-0001-5242-9827

Lina Beniusiene

middle | Lithuanian Research Centre for Agriculture and Forestry | ORCID 0000-0002-4369-2815

Yaser Thalji

middle | United Nations Relief and Works Agency for Palestine Refugees in the Near East | ORCID 0009-0000-2616-9099

Saeed Saado

last | Emirates Foundation | ORCID 0009-0008-6295-7437

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BibTeX

@article{Alkuddsi2026Integrating,
  title = {Integrating dendrometric traits and wood density to predict biomass productivity, bioenergy yield, and carbon sequestration in hybrid Populus clones},
  author = {Yanal Alkuddsi and Marius Aleinikovas and Benas Silinskas and Mohamad Alahmad and Abdul Monim Abdul Hafez and Ibrahim Alghoraibi and Mindaugas Skema and Lina Beniusiene and Yaser Thalji and Saeed Saado},
  journal = {Scientific Reports},
  year = {2026},
  doi = {10.1038/s41598-026-61798-8},
  url = {https://doi.org/10.1038/s41598-026-61798-8}
}

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