Implementation of real-time image processing on bacterial cellulose formation using soybean-boiled wastewater with the variation of carbon sources during fermentation
Bacterial cellulose (BC) is produced by aerobic bacteria through oxidative fermentation in synthetic and non-synthetic mediums. Several mediums reported to be used as BC formation mediums are coconut water and soybean-boiled wastewater. Carbon sources are needed to optimize the BC formation process....
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2023-01-01
|
| Series: | BIO Web of Conferences |
| Online Access: | https://www.bio-conferences.org/articles/bioconf/pdf/2023/25/bioconf_icosia2023_01002.pdf |
| _version_ | 1797353038782922752 |
|---|---|
| author | Marzuki Ahmad Fatih Nugroho Darmawan Ari Ahmadi Tyasto Prima Suyantohadi Atris |
| author_facet | Marzuki Ahmad Fatih Nugroho Darmawan Ari Ahmadi Tyasto Prima Suyantohadi Atris |
| author_sort | Marzuki Ahmad Fatih |
| collection | DOAJ |
| description | Bacterial cellulose (BC) is produced by aerobic bacteria through oxidative fermentation in synthetic and non-synthetic mediums. Several mediums reported to be used as BC formation mediums are coconut water and soybean-boiled wastewater. Carbon sources are needed to optimize the BC formation process. Recent study has implemented a real-time image processing approach for monitoring BC formation. This study aimed to investigate the correlation between variables that influence the fermentation and to determine the kinetic model of BC formation using an image processing approach with the variation of carbon sources during the fermentation. The results showed that the correlation between fermentation time and thickness had the highest percentage for glucose, sucrose, and mannitol mediums. The kinetic observation of BC formation in the medium using glucose, sucrose, and mannitol followed the Gompertz model equation, with the medium using sucrose having the fastest rate of increase at the 44th hour, followed by the medium using mannitol at the 112th hour, and the medium using glucose at the 149th hour. |
| first_indexed | 2024-03-08T13:25:23Z |
| format | Article |
| id | doaj.art-4507ece7236d4d3c95efe4b1ced7cb9d |
| institution | Directory Open Access Journal |
| issn | 2117-4458 |
| language | English |
| last_indexed | 2024-03-08T13:25:23Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | BIO Web of Conferences |
| spelling | doaj.art-4507ece7236d4d3c95efe4b1ced7cb9d2024-01-17T14:58:03ZengEDP SciencesBIO Web of Conferences2117-44582023-01-01800100210.1051/bioconf/20238001002bioconf_icosia2023_01002Implementation of real-time image processing on bacterial cellulose formation using soybean-boiled wastewater with the variation of carbon sources during fermentationMarzuki Ahmad Fatih0Nugroho Darmawan Ari1Ahmadi Tyasto Prima2Suyantohadi Atris3Department of Agroindustrial Technology, Faculty of Agricultural Technology, Universitas Gadjah MadaDepartment of Agroindustrial Technology, Faculty of Agricultural Technology, Universitas Gadjah MadaDepartment of Agroindustrial Technology, Faculty of Agricultural Technology, Universitas Gadjah MadaDepartment of Agroindustrial Technology, Faculty of Agricultural Technology, Universitas Gadjah MadaBacterial cellulose (BC) is produced by aerobic bacteria through oxidative fermentation in synthetic and non-synthetic mediums. Several mediums reported to be used as BC formation mediums are coconut water and soybean-boiled wastewater. Carbon sources are needed to optimize the BC formation process. Recent study has implemented a real-time image processing approach for monitoring BC formation. This study aimed to investigate the correlation between variables that influence the fermentation and to determine the kinetic model of BC formation using an image processing approach with the variation of carbon sources during the fermentation. The results showed that the correlation between fermentation time and thickness had the highest percentage for glucose, sucrose, and mannitol mediums. The kinetic observation of BC formation in the medium using glucose, sucrose, and mannitol followed the Gompertz model equation, with the medium using sucrose having the fastest rate of increase at the 44th hour, followed by the medium using mannitol at the 112th hour, and the medium using glucose at the 149th hour.https://www.bio-conferences.org/articles/bioconf/pdf/2023/25/bioconf_icosia2023_01002.pdf |
| spellingShingle | Marzuki Ahmad Fatih Nugroho Darmawan Ari Ahmadi Tyasto Prima Suyantohadi Atris Implementation of real-time image processing on bacterial cellulose formation using soybean-boiled wastewater with the variation of carbon sources during fermentation BIO Web of Conferences |
| title | Implementation of real-time image processing on bacterial cellulose formation using soybean-boiled wastewater with the variation of carbon sources during fermentation |
| title_full | Implementation of real-time image processing on bacterial cellulose formation using soybean-boiled wastewater with the variation of carbon sources during fermentation |
| title_fullStr | Implementation of real-time image processing on bacterial cellulose formation using soybean-boiled wastewater with the variation of carbon sources during fermentation |
| title_full_unstemmed | Implementation of real-time image processing on bacterial cellulose formation using soybean-boiled wastewater with the variation of carbon sources during fermentation |
| title_short | Implementation of real-time image processing on bacterial cellulose formation using soybean-boiled wastewater with the variation of carbon sources during fermentation |
| title_sort | implementation of real time image processing on bacterial cellulose formation using soybean boiled wastewater with the variation of carbon sources during fermentation |
| url | https://www.bio-conferences.org/articles/bioconf/pdf/2023/25/bioconf_icosia2023_01002.pdf |
| work_keys_str_mv | AT marzukiahmadfatih implementationofrealtimeimageprocessingonbacterialcelluloseformationusingsoybeanboiledwastewaterwiththevariationofcarbonsourcesduringfermentation AT nugrohodarmawanari implementationofrealtimeimageprocessingonbacterialcelluloseformationusingsoybeanboiledwastewaterwiththevariationofcarbonsourcesduringfermentation AT ahmadityastoprima implementationofrealtimeimageprocessingonbacterialcelluloseformationusingsoybeanboiledwastewaterwiththevariationofcarbonsourcesduringfermentation AT suyantohadiatris implementationofrealtimeimageprocessingonbacterialcelluloseformationusingsoybeanboiledwastewaterwiththevariationofcarbonsourcesduringfermentation |