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Identification of pesticide varieties by testing microalgae using Visible/Near Infrared Hyperspectral Imaging technology.

Shao Y, Jiang L, Zhou H, Pan J, He Y - Sci Rep (2016)

Bottom Line: In our study, the feasibility of using visible/near infrared hyperspectral imaging technology to detect the changes of the internal components of Chlorella pyrenoidosa so as to determine the varieties of pesticides (such as butachlor, atrazine and glyphosate) at three concentrations (0.6 mg/L, 3 mg/L, 15 mg/L) was investigated.The RC-LDA model, which achieved an average correct classification rate of 97.0% was more superior than FW-PLSDA (72.2%) and CARS-PLSDA (84.0%), and it proved that visible/near infrared hyperspectral imaging could be a rapid and reliable technique to identify pesticide varieties.It also proved that microalgae can be a very promising medium to indicate characteristics of pesticides.

View Article: PubMed Central - PubMed

Affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.

ABSTRACT
In our study, the feasibility of using visible/near infrared hyperspectral imaging technology to detect the changes of the internal components of Chlorella pyrenoidosa so as to determine the varieties of pesticides (such as butachlor, atrazine and glyphosate) at three concentrations (0.6 mg/L, 3 mg/L, 15 mg/L) was investigated. Three models (partial least squares discriminant analysis combined with full wavelengths, FW-PLSDA; partial least squares discriminant analysis combined with competitive adaptive reweighted sampling algorithm, CARS-PLSDA; linear discrimination analysis combined with regression coefficients, RC-LDA) were built by the hyperspectral data of Chlorella pyrenoidosa to find which model can produce the most optimal result. The RC-LDA model, which achieved an average correct classification rate of 97.0% was more superior than FW-PLSDA (72.2%) and CARS-PLSDA (84.0%), and it proved that visible/near infrared hyperspectral imaging could be a rapid and reliable technique to identify pesticide varieties. It also proved that microalgae can be a very promising medium to indicate characteristics of pesticides.

No MeSH data available.


Related in: MedlinePlus

The average visible and near infrared spectra of four samples in 3 mg/L on day 1.
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f2: The average visible and near infrared spectra of four samples in 3 mg/L on day 1.

Mentions: The spectra in the Vis/NIR region contain much rich but complex information of samples related to certain vibration behavior of molecular bonds (e.g. C–H, O–H). These characteristics can be explored to predict samples polluted by different pesticides. The mean spectra (420–1020 nm, the wavelengths of 380–420 nm were excluded for noisy signals) of samples cultured in water and 3 mg/L of three types of pesticides on day 1 are shown in Fig. 2. A significant absorption band was observed between 930 and 1020 nm related to O–H third stretching overtone19. Another obvious low reflectance between 650 nm and 700 nm might be related to the algal chlorophyll15. The front part of spectra between 425 nm and 500 nm were associated with some pigments, such as carotenoid and chlorophyll20. Combining Figs 1 and 2, wavelengths between 650 nm and 700 nm reflected the content of chlorophyll a. The figures showed that the content of chlorophyll a in microalgae polluted by glyphosate was higher than those by atrazine and butachlor, and the reflectance of glyphosate was lower than other pesticides. The hyperspectral reflectance characteristic of microalgae had also proved strong correlations with the concentrations of microalgae chlorophyll212223.


Identification of pesticide varieties by testing microalgae using Visible/Near Infrared Hyperspectral Imaging technology.

Shao Y, Jiang L, Zhou H, Pan J, He Y - Sci Rep (2016)

The average visible and near infrared spectra of four samples in 3 mg/L on day 1.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4829843&req=5

f2: The average visible and near infrared spectra of four samples in 3 mg/L on day 1.
Mentions: The spectra in the Vis/NIR region contain much rich but complex information of samples related to certain vibration behavior of molecular bonds (e.g. C–H, O–H). These characteristics can be explored to predict samples polluted by different pesticides. The mean spectra (420–1020 nm, the wavelengths of 380–420 nm were excluded for noisy signals) of samples cultured in water and 3 mg/L of three types of pesticides on day 1 are shown in Fig. 2. A significant absorption band was observed between 930 and 1020 nm related to O–H third stretching overtone19. Another obvious low reflectance between 650 nm and 700 nm might be related to the algal chlorophyll15. The front part of spectra between 425 nm and 500 nm were associated with some pigments, such as carotenoid and chlorophyll20. Combining Figs 1 and 2, wavelengths between 650 nm and 700 nm reflected the content of chlorophyll a. The figures showed that the content of chlorophyll a in microalgae polluted by glyphosate was higher than those by atrazine and butachlor, and the reflectance of glyphosate was lower than other pesticides. The hyperspectral reflectance characteristic of microalgae had also proved strong correlations with the concentrations of microalgae chlorophyll212223.

Bottom Line: In our study, the feasibility of using visible/near infrared hyperspectral imaging technology to detect the changes of the internal components of Chlorella pyrenoidosa so as to determine the varieties of pesticides (such as butachlor, atrazine and glyphosate) at three concentrations (0.6 mg/L, 3 mg/L, 15 mg/L) was investigated.The RC-LDA model, which achieved an average correct classification rate of 97.0% was more superior than FW-PLSDA (72.2%) and CARS-PLSDA (84.0%), and it proved that visible/near infrared hyperspectral imaging could be a rapid and reliable technique to identify pesticide varieties.It also proved that microalgae can be a very promising medium to indicate characteristics of pesticides.

View Article: PubMed Central - PubMed

Affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.

ABSTRACT
In our study, the feasibility of using visible/near infrared hyperspectral imaging technology to detect the changes of the internal components of Chlorella pyrenoidosa so as to determine the varieties of pesticides (such as butachlor, atrazine and glyphosate) at three concentrations (0.6 mg/L, 3 mg/L, 15 mg/L) was investigated. Three models (partial least squares discriminant analysis combined with full wavelengths, FW-PLSDA; partial least squares discriminant analysis combined with competitive adaptive reweighted sampling algorithm, CARS-PLSDA; linear discrimination analysis combined with regression coefficients, RC-LDA) were built by the hyperspectral data of Chlorella pyrenoidosa to find which model can produce the most optimal result. The RC-LDA model, which achieved an average correct classification rate of 97.0% was more superior than FW-PLSDA (72.2%) and CARS-PLSDA (84.0%), and it proved that visible/near infrared hyperspectral imaging could be a rapid and reliable technique to identify pesticide varieties. It also proved that microalgae can be a very promising medium to indicate characteristics of pesticides.

No MeSH data available.


Related in: MedlinePlus