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Determination of ni...
Determination of nitrogen content in Ulva fenestrata by color image analysis – a rapid and cost-efficient method to estimate nitrogen content in seaweeds
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- Stedt, Kristoffer, 1991 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för marina vetenskaper, Tjärnö marinlaboratoriet,Department of marine sciences, Tjärnö Marine Laboratory
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- Toth, Gunilla B., 1973 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för marina vetenskaper, Tjärnö marinlaboratoriet,Department of marine sciences, Tjärnö Marine Laboratory
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Davegård, Johan (author)
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- Pavia, Henrik, 1964 (author)
- Gothenburg University,Göteborgs universitet,SWEMARC,Institutionen för marina vetenskaper, Tjärnö marinlaboratoriet,Department of marine sciences, Tjärnö Marine Laboratory
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- Steinhagen, Sophie (author)
- Gothenburg University,Göteborgs universitet,SWEMARC,Institutionen för marina vetenskaper,Institutionen för marina vetenskaper, Tjärnö marinlaboratoriet,Department of marine sciences,Department of marine sciences, Tjärnö Marine Laboratory
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(creator_code:org_t)
- 2022-12-02
- 2022
- English.
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In: Frontiers in Marine Science. - : Frontiers Media SA. - 2296-7745. ; 9
- Related links:
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https://gup.ub.gu.se...
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https://doi.org/10.3...
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Abstract
Subject headings
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- There is an increasing interest in the cultivation of seaweeds for food and feed, and the seaweed aquaculture industry is rapidly developing. The nutritional status of the seaweeds is important to ensure a good quality crop. Cost-efficient and straightforward methods for farmers to analyze their crop are essential for the successful development of the industry. In this study, we developed non-destructive, labor- and cost-efficient models to estimate the nitrogen content in the crop seaweed Ulva fenestrata by color image analysis. We quantified tissue nitrogen content and thallus color in sea-farmed seaweed every week throughout a whole cultivation season (15 consecutive weeks) and analyzed data with linear regression models. We showed that color image analysis accurately estimated the nitrogen content in the seaweed (R2 = 0.944 and 0.827 for fresh tissue and dried powder, respectively), and through tenfold cross validation we showed that the developed models were robust and precise. Based on these models, we developed a web-based application that automatically analyzes the nitrogen content of the seaweeds. Furthermore, we produced a color guide that can easily be brought to the farm for onsite crude estimation of seaweeds’ nitrogen content. Our results demonstrate that color can be a powerful tool for seaweed farmers (and researchers) to estimate seaweeds’ nutritional status. We anticipate that similar models can be developed for other commercially interesting seaweed species.
Subject headings
- NATURVETENSKAP -- Biologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences (hsv//eng)
- NATURVETENSKAP -- Geovetenskap och miljövetenskap (hsv//swe)
- NATURAL SCIENCES -- Earth and Related Environmental Sciences (hsv//eng)
- LANTBRUKSVETENSKAPER -- Lantbruksvetenskap, skogsbruk och fiske (hsv//swe)
- AGRICULTURAL SCIENCES -- Agriculture, Forestry and Fisheries (hsv//eng)
- LANTBRUKSVETENSKAPER -- Bioteknologi med applikationer på växter och djur (hsv//swe)
- AGRICULTURAL SCIENCES -- Agricultural Biotechnology (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Kemiteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Chemical Engineering (hsv//eng)
Publication and Content Type
- ref (subject category)
- art (subject category)
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