Characterization of  producing 2-methylisoborneol and geosmin

Tsuchiya, Y.; Matsumoto, Atsuhiko

doi:10.1016/s0273-1223(99)00564-8

Cited by 7 publications

(1 citation statement)

References 12 publications

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“…Among the identified monoterpenes in the phytoplankton was β-ionone, which is one of the most common terpenoids produced by cyanobacteria. , β-Ionone was also the most abundant terpene in some of the present plankton samples. Certain filamentous cyanobacteria are known to produce sesquiterpenes in addition to geosmin, e.g., germacrene-D and γ-cadinene by Oscillatoria sp. , and 8a-epi-α-selinene by Nostoc punctiforme . The phytoplankton in the Bangladeshi ponds was dominated by chlorophytes and diatoms, rather than cyanobacteria, but the terpene profiles of these two algal groups are still uncharacterized.…”

Section: Discussionmentioning

confidence: 99%

Potential Contribution of Fish Feed and Phytoplankton to the Content of Volatile Terpenes in Cultured Pangasius (Pangasianodon hypophthalmus) and Tilapia (Oreochromis niloticus)

Podduturi

Petersen

Mahmud

et al. 2017

J. Agric. Food Chem.

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Geosmin and 2-methylisoborneol are the most recognized off-flavors in freshwater fish, but terpenes may also contribute off-flavor in fish. We identified six monoterpenes, 11 sesquiterpenes, and three terpene-related compounds in pangasius and tilapia from aquaculture farms in Bangladesh. The concentrations of most of the volatiles were below published odor thresholds, except for α-pinene, limonene, β-caryophyllene, α-humulene, and β-ionone in tilapia, and limonene and β-ionone in pangasius. To identify sources of the terpenes, terpene profiles of fish feed and phytoplankton in the ponds were analyzed. In feed and mustard cake (feed ingredient), five monoterpenes and two sesquiterpenes were identified, and five of these compounds were also detected in the fish. In phytoplankton, 11 monoterpenes were found and three also occurred in the fish. The higher number of terpenes common to both fish and feed, than to fish and phytoplankton, suggests that feed was a more abundant source of odor-active terpenes in the fish than phytoplankton.

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Section: Discussionmentioning

confidence: 99%

Potential Contribution of Fish Feed and Phytoplankton to the Content of Volatile Terpenes in Cultured Pangasius (Pangasianodon hypophthalmus) and Tilapia (Oreochromis niloticus)

Podduturi

Petersen

Mahmud

et al. 2017

J. Agric. Food Chem.

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Modelling geosmin concentrations in three sources of raw water in Quebec, Canada

Parinet

Rodriguez

Sérodes

2012

Environ Monit Assess

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The presence of off-flavour compounds such as geosmin, often found in raw water, significantly reduces the organoleptic quality of distributed water and diverts the consumer from its use. To adapt water treatment processes to eliminate these compounds, it is necessary to be able to identify them quickly. Routine analysis could be considered a solution, but it is expensive and delays associated with obtaining the results of analysis are often important, thereby constituting a serious disadvantage. The development of decision-making tools such as predictive models seems to be an economic and feasible solution to counterbalance the limitations of analytical methods. Among these tools, multi-linear regression and principal component regression are easy to implement. However, due to certain disadvantages inherent in these methods (multicollinearity or non-linearity of the processes), the use of emergent models involving artificial neurons networks such as multi-layer perceptron could prove to be an interesting alternative. In a previous paper (Parinet et al., Water Res 44: 5847-5856, 2010), the possible parameters that affect the variability of taste and odour compounds were investigated using principal component analysis. In the present study, we expand the research by comparing the performance of three tools using different modelling scenarios (multi-linear regression, principal component regression and multi-layer perceptron) to model geosmin in drinking water sources using 38 microbiological and physicochemical parameters. Three very different sources of water, in terms of quality, were selected for the study. These sources supply drinking water to the Québec City area (Canada) and its vicinity, and were monitored three times per month over a 1-year period. Seven different modelling methods were tested for predicting geosmin in these sources. The comparison of the seven different models showed that simple models based on multi-linear regression provide sufficient predictive capacity with performance levels comparable to those obtained with artificial neural networks. The multi-linear regression model (R(2) = 0.657, <0.001) used only four variables (phaeophytin, sum of green algae, chlorophyll-a and potential Redox) in comparison with ten variables (potassium, heterotrophic bacteria, organic nitrogen, total nitrogen, phaeophytin, total organic carbon, sum of green algae, potential Redox, UV absorbance at 254 nm and atypical bacteria) for the best model obtained with artificial neural networks (R(2) = 0.843).

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Hydrocarbon profiles and phylogenetic analyses of diversified cyanobacterial species

Liu¹,

Zhu²,

Lü³

et al. 2013

Applied Energy

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Characterization of producing 2-methylisoborneol and geosmin

Cited by 7 publications

References 12 publications

Potential Contribution of Fish Feed and Phytoplankton to the Content of Volatile Terpenes in Cultured Pangasius (Pangasianodon hypophthalmus) and Tilapia (Oreochromis niloticus)

Potential Contribution of Fish Feed and Phytoplankton to the Content of Volatile Terpenes in Cultured Pangasius (Pangasianodon hypophthalmus) and Tilapia (Oreochromis niloticus)

Modelling geosmin concentrations in three sources of raw water in Quebec, Canada

Hydrocarbon profiles and phylogenetic analyses of diversified cyanobacterial species

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