Assessing Suitable Tree Species for Biochar Production and Their Performance in Enriching Soil Quality and Plant Growth of Oryza sativa L. and Acacia auriculiformis A. Cunn. Ex Benth.

Aims: This study aims to identify suitable tree species for biochar production and evaluate their effectiveness in improving soil quality and the growth of Rice (Oryza sativa L.) and Akshmoni (Acacia auriculiformis A. Cunn. ex Benth). The findings will help determine the most effective biochar feedstock for sustainable agroforestry practices in tropical regions. Study Design: The experiment was conducted using a Complete Randomized Block Design (CRBD) with six different tropical tree species as feedstock for biochar production. Biochar was applied as a soil amendment at a rate of 10 t/ha, with a control group for comparison. Place and Duration of Study: The study was carried out at the nursery of the Department of Forestry and Environmental Science, Shahjalal University of Science and Technology (SUST) in Sylhet, Bangladesh over a specific period, focusing on biochar production and its impact on soil properties and plant growth. Methodology: Six tropical tree species—Rain tree (Albizia saman), Kadam (Neolamarckia cadamba), Kathal (Artocarpus heterophyllus), Mango (Mangifera indica), Chambul (Terminalia arjuna), and Mahogany (Swietenia mahagoni)—were selected as feedstock for biochar production. A one-way ANOVA and Tukey HSD Post Hoc Test were used to determine statistical significance (α = 0.05) in evaluating biochar yield, soil quality improvement, and plant growth performance. Results: Among the six species, Chambul (Terminalia arjuna) produced the highest biochar yield (41.6%) and exhibited the highest germination potential (88.3%). It also showed positive effects on plant growth performance. However, certain biochar types had adverse effects on plant growth, indicating that the choice of feedstock significantly influences biochar effectiveness. Conclusion: The study highlights the importance of selecting appropriate feedstock species for biochar production. Chambul (Terminalia arjuna) biochar demonstrated the most promising results in terms of yield, soil quality enhancement, and plant growth. However, careful selection of tree species is crucial before biochar application to ensure optimal benefits for soil and plant health.

Authors

Institutions

Publication Details

Journal
Asian Journal of Research in Agriculture and Forestry
Published
2025-03-26
DOI
https://doi.org/10.9734/ajraf/2025/v11i2384
Citations
1
Primary Topic
Soil Carbon and Nitrogen Dynamics
Type
article
Field-Weighted Citation Impact
1.19
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing Suitable Tree Species for Biochar Production and Their Performance in Enriching Soil Quality and Plant Growth of Oryza sativa L. and Acacia auriculiformis A. Cunn. Ex Benth.

O. P. Dutta, Narayan Saha, Farhana Bintay Hye, Montasir Shamim
1 citations
Asian Journal of Research in Agriculture and Forestry
Soil Carbon and Nitrogen Dynamics
1.19
article

Assessing Suitable Tree Species for Biochar Production and Their Performance in Enriching Soil Quality and Plant Growth of Oryza sativa L. and Acacia auriculiformis A. Cunn. Ex Benth.

O. P. Dutta, Narayan Saha, Farhana Bintay Hye, Montasir Shamim
article en
1 citations

Abstract

Aims: This study aims to identify suitable tree species for biochar production and evaluate their effectiveness in improving soil quality and the growth of Rice (Oryza sativa L.) and Akshmoni (Acacia auriculiformis A. Cunn. ex Benth). The findings will help determine the most effective biochar feedstock for sustainable agroforestry practices in tropical regions. Study Design: The experiment was conducted using a Complete Randomized Block Design (CRBD) with six different tropical tree species as feedstock for biochar production. Biochar was applied as a soil amendment at a rate of 10 t/ha, with a control group for comparison. Place and Duration of Study: The study was carried out at the nursery of the Department of Forestry and Environmental Science, Shahjalal University of Science and Technology (SUST) in Sylhet, Bangladesh over a specific period, focusing on biochar production and its impact on soil properties and plant growth. Methodology: Six tropical tree species—Rain tree (Albizia saman), Kadam (Neolamarckia cadamba), Kathal (Artocarpus heterophyllus), Mango (Mangifera indica), Chambul (Terminalia arjuna), and Mahogany (Swietenia mahagoni)—were selected as feedstock for biochar production. A one-way ANOVA and Tukey HSD Post Hoc Test were used to determine statistical significance (α = 0.05) in evaluating biochar yield, soil quality improvement, and plant growth performance. Results: Among the six species, Chambul (Terminalia arjuna) produced the highest biochar yield (41.6%) and exhibited the highest germination potential (88.3%). It also showed positive effects on plant growth performance. However, certain biochar types had adverse effects on plant growth, indicating that the choice of feedstock significantly influences biochar effectiveness. Conclusion: The study highlights the importance of selecting appropriate feedstock species for biochar production. Chambul (Terminalia arjuna) biochar demonstrated the most promising results in terms of yield, soil quality enhancement, and plant growth. However, careful selection of tree species is crucial before biochar application to ensure optimal benefits for soil and plant health.

Asian Journal of Research in Agriculture and ForestryVol. 11(2)
Shahjalal University of Science and Technology (BD)
Openalex Percentile: Top 22%
Soil Carbon and Nitrogen Dynamics
1.19
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.