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Optimising and scaling up hot water extraction of tannins from Norway spruce and Scots pine bark

dc.contributor.authorKilpeläinen, Petri
dc.contributor.authorLiski, Eero
dc.contributor.authorSaranpää, Pekka
dc.contributor.departmentid4100211210
dc.contributor.departmentid4100111010
dc.contributor.departmentid4100211110
dc.contributor.orcidhttps://orcid.org/0000-0002-0982-0123
dc.contributor.orcidhttps://orcid.org/0000-0002-1129-2315
dc.contributor.organizationLuonnonvarakeskus
dc.date.accessioned2022-12-16T08:21:12Z
dc.date.accessioned2025-05-28T13:22:25Z
dc.date.available2022-12-16T08:21:12Z
dc.date.issued2023
dc.description.abstractTannins from Norway spruce (Picea abies [L.] Karst.) and Scots pine (Pinus sylvestris L.) bark were extracted with water at different temperatures (60–140 °C) in an ASE-350 system in order to optimize yield. In addition, the effect of chemicals such as urea, sodium bisulfite (NaHSO3), sodium carbonate (Na2CO3), and sodium benzoate on the yield was also investigated. Bark from debarking processes at both a sawmill and a pulp mill were included. The highest overall yield expressed as total dissolved solids (TDS) was obtained with hot water extraction of spruce bark at 140 °C. The TDS was 117 mg/g and it contained 47 mg/g tannins. With an increase in extraction temperature over 100 °C, the proportion of tannins decreased, whereas the proportion of carbohydrates increased. The addition of sodium carbonate improved yield within a 60–90 °C temperature range compared with pure water. Other chemicals did not improve the yield. Pine bark showed similar extraction yields to spruce bark but the proportion of tannins was lower in spruce than in pine. Pure water at 110 °C was chosen to be used for piloting in larger scale 300-liter extraction vessel. Based on the results, a machine-learning approach was applied using seemingly unrelated regression models (SUR). The models were able to predict the extracted tannin yields of spruce and pine bark when extractions were scaled up to 2 liters and then to 300 liters.
dc.description.vuosik2023
dc.format.bitstreamtrue
dc.format.pagerange11 p.
dc.identifier.olddbid495277
dc.identifier.oldhandle10024/552718
dc.identifier.urihttps://jukuri.luke.fi/handle/11111/23757
dc.identifier.urnURN:NBN:fi-fe2022121672008
dc.language.isoen
dc.okm.corporatecopublicationei
dc.okm.discipline116
dc.okm.internationalcopublicationei
dc.okm.openaccess2 = Hybridijulkaisukanavassa ilmestynyt avoin julkaisu
dc.okm.selfarchivedon
dc.publisherElsevier BV
dc.relation.articlenumber116089
dc.relation.doi10.1016/j.indcrop.2022.116089
dc.relation.ispartofseriesIndustrial Crops and Products
dc.relation.issn0926-6690
dc.relation.volume192
dc.rightsCC BY 4.0
dc.source.identifierhttps://jukuri.luke.fi/handle/10024/552718
dc.subjectSpruce
dc.subjectPine
dc.subjectTannin
dc.subjectHot water extraction
dc.subjectOptimization
dc.subjectMachine learning
dc.teh41007-00212300
dc.titleOptimising and scaling up hot water extraction of tannins from Norway spruce and Scots pine bark
dc.typepublication
dc.type.okmfi=A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä|sv=A1 Originalartikel i en vetenskaplig tidskrift|en=A1 Journal article (refereed), original research|
dc.type.versionfi=Publisher's version|sv=Publisher's version|en=Publisher's version|

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