DAILY PAPER REVIEW

0616_Development of Models for Predicting the predominant Taste and Odor Compounds...

 

 

1       Title, Journal and Authors

Title : Development of Models for Predicting the predominant Taste and Odor Compounds in Taihu Lake, China

Journal : http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0051976#pone-0051976-g006

Accepted November 8, 2012

Published December 19, 2012

Authors : Min Qi, Jun Chen, Xiaoxue Sun, Xuwei Deng, Yuan Niu, Ping Xie

Donghu Experimental Station of Lake Ecosystems, State Key Laboratory of Freshwater Ecology and Biotechnology of China, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, Hubei, People’s Republic of China

 

2       Summary

2.1       Abstract

Site  : lake

Object : need to develop optimum models to predict these T&O problems

Biotic & abiotic environmental parameters were monitored

Phytoplankton taxa were important variable

2-MIB is related to Oscillatoria

Whereas, p-β-cyclocitral and p-β-ionone were correlated with Microcystis levels

Abiotic factors : contributed to the T&O predictive models

Dissolved T&O compounds related to algal biomass and abiotic environmental factors

Particle-bound T&O compounds strongly related to the algal presence

2.2       Results

Model Development

Factors affecting to MIB

2.3       Discussion

The Importance of Developing Predictive Models for Both Dissolved and Particle-bound T&O Compounds

-      Dissolved T&O compounds : related to both the algal biomass and the abiotic environmental factors.

-      Particle-bound T&O compounds : related to the algae.

-      Dissolved T&O fraction could directly influence water quality

-      Particle-bound fraction in the algal cells could become an important source of T&O problems when the cells are damaged or decomposed.

-      Thus, it was necessary to establish a separate model for each form of the T&O compounds.

Influences of Phytoplankton on the Predictive models

-      Some of the T&O compounds (e.g., DMS, MIB, β-cyclocitral, and β-ionone) are often assumed to be produced by specific algae, bacteria, or fungi.

-      Such organisms include Oscillatoria for the MIB in Eqs. (5) and (6), and Microcystis for the β-cyclocitral and β-ionone in Eqs. (9) ~ (12).

-      However, some algae that have not been reported to produce odors were included in the models;

-      for example, Bacillariophyta in Eq. (4), Pectodictyon and Synedra in Eq. (6), and Chlorella in Eq. (10).

-      consequently, influenced the T&O compounds indirectly.

-      In summary, the odor-producing algae played important roles in the dynamics of the T&O compounds in Taihu Lake, and other phytoplankton species might also have substantial influences on these compounds.

-      Thus, algal species besides the odor-producing algae should also be considered when investigating the T&O compounds.

Influences of Physiochemical Parameters on the Predictive models

-      Thus, it is likely that nitrogen might indirectly affect the production and release of the T&O compounds by algae.

-      Therefore, changes in the available nitrogen forms and their ratios may also influence the phytoplankton and the subsequent production of the T&O compounds.

-      The great heterogeneity is also a characteristic of this huge lake.

Model Test and Extension

-      The use of the independent data set to test the accuracy of the models showed that the occurrence and intensity of these T&O compounds were satisfactorily predicted, though there were several deviations.

-      In a body of water as large and spatially heterogeneous as Taihu Lake, the environmental and climatic conditions may substantially vary both spatially and temporally.

-      In addition, it is known that the volatility of the compounds producing the off-flavors causes their concentrations to vary easily in aquatic environments.

-      The above phenomena could certainly result in discrepancies between the predicted and observed values.

-      Nevertheless, the models developed in the present study accurately predicted the levels of a number of the T&O compounds in Taihu, which supplies water for drinking, industry and agriculture to millions of people.

-      Therefore, these models, basing on easily collected environmental data, are of practical value to water resource managers for evaluating the probability of T&O accidents in Taihu Lake.

-      Previous researchers reported that the dynamics of odor compounds strongly depend on the local environmental conditions and vary from system to system [9], [13], [14].

-      Even for the same T&O compound, different models were generated in different reservoirs of the same region; thus, it is difficult to obtain a universal model applicable to all ecosystems [9], [13], [14].

-      It was not possible to test our models in other systems because of the lack of sufficient data, as we mentioned above.

-      Nevertheless, models developed here have good utilities in such a huge lake based on the quite informative data in different algal growth seasons for different fractions of the T&O compounds.

We believe that the models in the present study should provide insights into developing a general model applicable to a variety of lake systems, especially other shallow eutrophic lakes with Microcystis blooms.

2.4       Conclusion

-      Abiotic and biotic parameters from Taihu Lake : T&O compound predictive models

-      Two Algal season : Blooming& Nonblooming

-      Two fractions of the T&O compounds : Dissolved & Particle-bound

: Contributed to the accuracy and sensitivity of the models

Dissolved T&O : varied with the algal biomass and with a variety of abiotic factors

Particle-bound T&O : varied primarily with the algal biomass

-      Model : of practical value to the water resource managers for predicting the probability of T&O accidents

3       Originality & Creativity

맛냄새물질은 Dissolved Particle-bound form 으로 나타내었음.

Dissolved form은 다양한 환경인자에 영향을 받으나 particle-bound form algal biomass와 상당한 연관성이 있음.

모델 개발 시 Non-blooming blooming 기간을 나눠서 개발하였음.

 

4       Application to the research

모델개발 시 고려해야 할 사항 : Dissolved form, Particle-bound form 여부/ Nonblooming, blooming 기간동안의 상관관계 확인 필요.

5       Contact

Inhyeok Yim

 

Yim89@gist.ac.kr

첨부 (1)
02_Qi et al., 2012, PLOS ONE_Review.pdf
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