Influence of particle size on NIR spectroscopic characterization of sorghum biomass for the biofuel industry
NIR spectroscopy is a rapid and accurate green technology for high-throughput biomass characterization, including sorghum (Sorghum bicolor), a promising energy crop for the biofuel industry. This study assessed the influence of particle size on NIR spectroscopic analysis (wavelength range: 867–2535 ...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-01-01
|
| Series: | Results in Chemistry |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2211715624007124 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832583096044617728 |
|---|---|
| author | Md Wadud Ahmed Carlos A. Esquerre Kristen Eilts Dylan P. Allen Scott M. McCoy Sebastian Varela Vijay Singh Andrew D.B. Leakey Mohammed Kamruzzaman |
| author_facet | Md Wadud Ahmed Carlos A. Esquerre Kristen Eilts Dylan P. Allen Scott M. McCoy Sebastian Varela Vijay Singh Andrew D.B. Leakey Mohammed Kamruzzaman |
| author_sort | Md Wadud Ahmed |
| collection | DOAJ |
| description | NIR spectroscopy is a rapid and accurate green technology for high-throughput biomass characterization, including sorghum (Sorghum bicolor), a promising energy crop for the biofuel industry. This study assessed the influence of particle size on NIR spectroscopic analysis (wavelength range: 867–2535 nm) of sorghum biomass composition. Grown under field conditions, a total of 113 types of genetically diverse sorghum accessions were dried, ground, and sieved (<250, 250–600, 600–850, and > 850 µm particle size) for developing partial least square regression (PLSR) prediction models for moisture, ash, extractive, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin (ASL + AIL). Overall, smaller particle sizes provided better model performance, while no single particle size provided the best performance for all the selected components. With only 9 selected bands and 4 latent variables (LVs), the best PLSR model was obtained for moisture with particle size of 600–850 µm with the square root of the coefficient of determination (R) of 0.85, the ratio of prediction to deviation (RPD) of 2.2, and the root mean square error (RMSE) of 0.46 % in external validation. Similar model performances were also obtained for ash, extractive, glucan, and xylan. This study showed that size reduction could effectively improve NIR spectroscopic analysis for lipid-producing sorghum biomass for the biofuel industry. |
| format | Article |
| id | doaj-art-7714d4ae2d4444d6a5e761e08d7d1dcd |
| institution | Kabale University |
| issn | 2211-7156 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Chemistry |
| spelling | doaj-art-7714d4ae2d4444d6a5e761e08d7d1dcd2025-01-29T05:00:57ZengElsevierResults in Chemistry2211-71562025-01-0113102016Influence of particle size on NIR spectroscopic characterization of sorghum biomass for the biofuel industryMd Wadud Ahmed0Carlos A. Esquerre1Kristen Eilts2Dylan P. Allen3Scott M. McCoy4Sebastian Varela5Vijay Singh6Andrew D.B. Leakey7Mohammed Kamruzzaman8The Grainger College of Engineering, College of Agricultural, Consumer and Environmental Sciences, Department of Agricultural and Biological Engineering, University of Illinois Urbana-Champaign, Urbana 61801, IL, United StatesThe Grainger College of Engineering, College of Agricultural, Consumer and Environmental Sciences, Department of Agricultural and Biological Engineering, University of Illinois Urbana-Champaign, Urbana 61801, IL, United StatesThe Grainger College of Engineering, College of Agricultural, Consumer and Environmental Sciences, Department of Agricultural and Biological Engineering, University of Illinois Urbana-Champaign, Urbana 61801, IL, United States; DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois Urbana-Champaign, Urbana 61801, IL, United StatesInstitute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana 61801, IL, United StatesInstitute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana 61801, IL, United States; Department of Plant Biology, University of Illinois Urbana-Champaign, Urbana 61801, IL, United StatesDepartment of Plant Biology, University of Illinois Urbana-Champaign, Urbana 61801, IL, United States; Varela Quintela, Canelones 15800, UruguayThe Grainger College of Engineering, College of Agricultural, Consumer and Environmental Sciences, Department of Agricultural and Biological Engineering, University of Illinois Urbana-Champaign, Urbana 61801, IL, United States; DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois Urbana-Champaign, Urbana 61801, IL, United StatesInstitute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana 61801, IL, United States; Department of Plant Biology, University of Illinois Urbana-Champaign, Urbana 61801, IL, United States; DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois Urbana-Champaign, Urbana 61801, IL, United States; Department of Crop Sciences, University of Illinois Urbana-Champaign, Urbana 61801, IL, United StatesThe Grainger College of Engineering, College of Agricultural, Consumer and Environmental Sciences, Department of Agricultural and Biological Engineering, University of Illinois Urbana-Champaign, Urbana 61801, IL, United States; Corresponding author.NIR spectroscopy is a rapid and accurate green technology for high-throughput biomass characterization, including sorghum (Sorghum bicolor), a promising energy crop for the biofuel industry. This study assessed the influence of particle size on NIR spectroscopic analysis (wavelength range: 867–2535 nm) of sorghum biomass composition. Grown under field conditions, a total of 113 types of genetically diverse sorghum accessions were dried, ground, and sieved (<250, 250–600, 600–850, and > 850 µm particle size) for developing partial least square regression (PLSR) prediction models for moisture, ash, extractive, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin (ASL + AIL). Overall, smaller particle sizes provided better model performance, while no single particle size provided the best performance for all the selected components. With only 9 selected bands and 4 latent variables (LVs), the best PLSR model was obtained for moisture with particle size of 600–850 µm with the square root of the coefficient of determination (R) of 0.85, the ratio of prediction to deviation (RPD) of 2.2, and the root mean square error (RMSE) of 0.46 % in external validation. Similar model performances were also obtained for ash, extractive, glucan, and xylan. This study showed that size reduction could effectively improve NIR spectroscopic analysis for lipid-producing sorghum biomass for the biofuel industry.http://www.sciencedirect.com/science/article/pii/S2211715624007124Particle sizeSorghum biomassComposition analysisPLSRFeature selection |
| spellingShingle | Md Wadud Ahmed Carlos A. Esquerre Kristen Eilts Dylan P. Allen Scott M. McCoy Sebastian Varela Vijay Singh Andrew D.B. Leakey Mohammed Kamruzzaman Influence of particle size on NIR spectroscopic characterization of sorghum biomass for the biofuel industry Results in Chemistry Particle size Sorghum biomass Composition analysis PLSR Feature selection |
| title | Influence of particle size on NIR spectroscopic characterization of sorghum biomass for the biofuel industry |
| title_full | Influence of particle size on NIR spectroscopic characterization of sorghum biomass for the biofuel industry |
| title_fullStr | Influence of particle size on NIR spectroscopic characterization of sorghum biomass for the biofuel industry |
| title_full_unstemmed | Influence of particle size on NIR spectroscopic characterization of sorghum biomass for the biofuel industry |
| title_short | Influence of particle size on NIR spectroscopic characterization of sorghum biomass for the biofuel industry |
| title_sort | influence of particle size on nir spectroscopic characterization of sorghum biomass for the biofuel industry |
| topic | Particle size Sorghum biomass Composition analysis PLSR Feature selection |
| url | http://www.sciencedirect.com/science/article/pii/S2211715624007124 |
| work_keys_str_mv | AT mdwadudahmed influenceofparticlesizeonnirspectroscopiccharacterizationofsorghumbiomassforthebiofuelindustry AT carlosaesquerre influenceofparticlesizeonnirspectroscopiccharacterizationofsorghumbiomassforthebiofuelindustry AT kristeneilts influenceofparticlesizeonnirspectroscopiccharacterizationofsorghumbiomassforthebiofuelindustry AT dylanpallen influenceofparticlesizeonnirspectroscopiccharacterizationofsorghumbiomassforthebiofuelindustry AT scottmmccoy influenceofparticlesizeonnirspectroscopiccharacterizationofsorghumbiomassforthebiofuelindustry AT sebastianvarela influenceofparticlesizeonnirspectroscopiccharacterizationofsorghumbiomassforthebiofuelindustry AT vijaysingh influenceofparticlesizeonnirspectroscopiccharacterizationofsorghumbiomassforthebiofuelindustry AT andrewdbleakey influenceofparticlesizeonnirspectroscopiccharacterizationofsorghumbiomassforthebiofuelindustry AT mohammedkamruzzaman influenceofparticlesizeonnirspectroscopiccharacterizationofsorghumbiomassforthebiofuelindustry |