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Detecting molecular features of spectra mainly associated with structural and non-structural carbohydrates in co-products from bioEthanol production using DRIFT with uni- and multivariate molecular spectral analyses.

Yu P, Damiran D, Azarfar A, Niu Z - Int J Mol Sci (2011)

Bottom Line: This study indicated that the bioethanol processing changes carbohydrate molecular structural profiles, compared with the original grains.In general, the bioethanol processing increases the molecular spectral intensities for the structural carbohydrates and decreases the intensities for the non-structural carbohydrates.Further study is needed to quantify carbohydrate related molecular spectral features of the bioethanol co-products in relation to nutrient supply and availability of carbohydrates.

View Article: PubMed Central - PubMed

Affiliation: College of Agriculture and Bioresources, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK, S7N 5A8 Canada; E-Mails: dad884@mail.usask.ca (D.D.); ara833@mail.usask.ca (A.A.); zyn847@mail.usask.ca (Z.N.).

ABSTRACT
The objective of this study was to use DRIFT spectroscopy with uni- and multivariate molecular spectral analyses as a novel approach to detect molecular features of spectra mainly associated with carbohydrate in the co-products (wheat DDGS, corn DDGS, blend DDGS) from bioethanol processing in comparison with original feedstock (wheat (Triticum), corn (Zea mays)). The carbohydrates related molecular spectral bands included: A_Cell (structural carbohydrates, peaks area region and baseline: ca. 1485-1188 cm(-1)), A_1240 (structural carbohydrates, peak area centered at ca. 1240 cm(-1) with region and baseline: ca. 1292-1198 cm(-1)), A_CHO (total carbohydrates, peaks region and baseline: ca. 1187-950 cm(-1)), A_928 (non-structural carbohydrates, peak area centered at ca. 928 cm(-1) with region and baseline: ca. 952-910 cm(-1)), A_860 (non-structural carbohydrates, peak area centered at ca. 860 cm(-1) with region and baseline: ca. 880-827 cm(-1)), H_1415 (structural carbohydrate, peak height centered at ca. 1415 cm(-1) with baseline: ca. 1485-1188 cm(-1)), H_1370 (structural carbohydrate, peak height at ca. 1370 cm(-1) with a baseline: ca. 1485-1188 cm(-1)). The study shows that the grains had lower spectral intensity (KM Unit) of the cellulosic compounds of A_1240 (8.5 vs. 36.6, P < 0.05), higher (P < 0.05) intensities of the non-structural carbohydrate of A_928 (17.3 vs. 2.0) and A_860 (20.7 vs. 7.6) than their co-products from bioethanol processing. There were no differences (P > 0.05) in the peak area intensities of A_Cell (structural CHO) at 1292-1198 cm(-1) and A_CHO (total CHO) at 1187-950 cm(-1) with average molecular infrared intensity KM unit of 226.8 and 508.1, respectively. There were no differences (P > 0.05) in the peak height intensities of H_1415 and H_1370 (structural CHOs) with average intensities 1.35 and 1.15, respectively. The multivariate molecular spectral analyses were able to discriminate and classify between the corn and corn DDGS molecular spectra, but not wheat and wheat DDGS. This study indicated that the bioethanol processing changes carbohydrate molecular structural profiles, compared with the original grains. However, the sensitivities of different types of carbohydrates and different grains (corn and wheat) to the processing differ. In general, the bioethanol processing increases the molecular spectral intensities for the structural carbohydrates and decreases the intensities for the non-structural carbohydrates. Further study is needed to quantify carbohydrate related molecular spectral features of the bioethanol co-products in relation to nutrient supply and availability of carbohydrates.

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Multivariate molecular spectral analyses of the co-products from bioethanol production at the total carbohydrate region (ca. 1187–950 cm−1): CLA cluster analyses of molecular spectrum (Distance method: Euclidean; Cluster method: Ward’s algorithm); Principal component analysis (PCA) analyses of molecular mid-IR spectrum. (a,c) wheat DDGS (code 2) vs. wheat (code 5); (b,d) corn DDGS (code 1) vs. corn (code 6). (a) Cluster analysis: molecular structure of wheat vs. molecular structure of wheat DDGS; (b) Cluster analysis: molecular structure of corn vs. molecular structure of corn; (c) PCA: molecular structure of wheat vs. molecular structure of wheat DDGS. 1st vs. 2nd principal component; (d) PCA: molecular structure of corn vs. molecular structure of corn DDGS. 1st vs. 2nd principal component.
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f5-ijms-12-01921: Multivariate molecular spectral analyses of the co-products from bioethanol production at the total carbohydrate region (ca. 1187–950 cm−1): CLA cluster analyses of molecular spectrum (Distance method: Euclidean; Cluster method: Ward’s algorithm); Principal component analysis (PCA) analyses of molecular mid-IR spectrum. (a,c) wheat DDGS (code 2) vs. wheat (code 5); (b,d) corn DDGS (code 1) vs. corn (code 6). (a) Cluster analysis: molecular structure of wheat vs. molecular structure of wheat DDGS; (b) Cluster analysis: molecular structure of corn vs. molecular structure of corn; (c) PCA: molecular structure of wheat vs. molecular structure of wheat DDGS. 1st vs. 2nd principal component; (d) PCA: molecular structure of corn vs. molecular structure of corn DDGS. 1st vs. 2nd principal component.

Mentions: This method helps discriminate in the structural differences between the grain and its co-products. Figures 2–5 show that two classes can be clear distinguished between corn and corn DDGS, but not between wheat and wheat DDGS. These results indicate that molecular structure between the corn and bioethanol co-product (corn DDGS) were different. These results also indicate that different cereal grains have different responses to bioethanol processing and different sensitivity to heating and fermentation.


Detecting molecular features of spectra mainly associated with structural and non-structural carbohydrates in co-products from bioEthanol production using DRIFT with uni- and multivariate molecular spectral analyses.

Yu P, Damiran D, Azarfar A, Niu Z - Int J Mol Sci (2011)

Multivariate molecular spectral analyses of the co-products from bioethanol production at the total carbohydrate region (ca. 1187–950 cm−1): CLA cluster analyses of molecular spectrum (Distance method: Euclidean; Cluster method: Ward’s algorithm); Principal component analysis (PCA) analyses of molecular mid-IR spectrum. (a,c) wheat DDGS (code 2) vs. wheat (code 5); (b,d) corn DDGS (code 1) vs. corn (code 6). (a) Cluster analysis: molecular structure of wheat vs. molecular structure of wheat DDGS; (b) Cluster analysis: molecular structure of corn vs. molecular structure of corn; (c) PCA: molecular structure of wheat vs. molecular structure of wheat DDGS. 1st vs. 2nd principal component; (d) PCA: molecular structure of corn vs. molecular structure of corn DDGS. 1st vs. 2nd principal component.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC3111642&req=5

f5-ijms-12-01921: Multivariate molecular spectral analyses of the co-products from bioethanol production at the total carbohydrate region (ca. 1187–950 cm−1): CLA cluster analyses of molecular spectrum (Distance method: Euclidean; Cluster method: Ward’s algorithm); Principal component analysis (PCA) analyses of molecular mid-IR spectrum. (a,c) wheat DDGS (code 2) vs. wheat (code 5); (b,d) corn DDGS (code 1) vs. corn (code 6). (a) Cluster analysis: molecular structure of wheat vs. molecular structure of wheat DDGS; (b) Cluster analysis: molecular structure of corn vs. molecular structure of corn; (c) PCA: molecular structure of wheat vs. molecular structure of wheat DDGS. 1st vs. 2nd principal component; (d) PCA: molecular structure of corn vs. molecular structure of corn DDGS. 1st vs. 2nd principal component.
Mentions: This method helps discriminate in the structural differences between the grain and its co-products. Figures 2–5 show that two classes can be clear distinguished between corn and corn DDGS, but not between wheat and wheat DDGS. These results indicate that molecular structure between the corn and bioethanol co-product (corn DDGS) were different. These results also indicate that different cereal grains have different responses to bioethanol processing and different sensitivity to heating and fermentation.

Bottom Line: This study indicated that the bioethanol processing changes carbohydrate molecular structural profiles, compared with the original grains.In general, the bioethanol processing increases the molecular spectral intensities for the structural carbohydrates and decreases the intensities for the non-structural carbohydrates.Further study is needed to quantify carbohydrate related molecular spectral features of the bioethanol co-products in relation to nutrient supply and availability of carbohydrates.

View Article: PubMed Central - PubMed

Affiliation: College of Agriculture and Bioresources, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK, S7N 5A8 Canada; E-Mails: dad884@mail.usask.ca (D.D.); ara833@mail.usask.ca (A.A.); zyn847@mail.usask.ca (Z.N.).

ABSTRACT
The objective of this study was to use DRIFT spectroscopy with uni- and multivariate molecular spectral analyses as a novel approach to detect molecular features of spectra mainly associated with carbohydrate in the co-products (wheat DDGS, corn DDGS, blend DDGS) from bioethanol processing in comparison with original feedstock (wheat (Triticum), corn (Zea mays)). The carbohydrates related molecular spectral bands included: A_Cell (structural carbohydrates, peaks area region and baseline: ca. 1485-1188 cm(-1)), A_1240 (structural carbohydrates, peak area centered at ca. 1240 cm(-1) with region and baseline: ca. 1292-1198 cm(-1)), A_CHO (total carbohydrates, peaks region and baseline: ca. 1187-950 cm(-1)), A_928 (non-structural carbohydrates, peak area centered at ca. 928 cm(-1) with region and baseline: ca. 952-910 cm(-1)), A_860 (non-structural carbohydrates, peak area centered at ca. 860 cm(-1) with region and baseline: ca. 880-827 cm(-1)), H_1415 (structural carbohydrate, peak height centered at ca. 1415 cm(-1) with baseline: ca. 1485-1188 cm(-1)), H_1370 (structural carbohydrate, peak height at ca. 1370 cm(-1) with a baseline: ca. 1485-1188 cm(-1)). The study shows that the grains had lower spectral intensity (KM Unit) of the cellulosic compounds of A_1240 (8.5 vs. 36.6, P < 0.05), higher (P < 0.05) intensities of the non-structural carbohydrate of A_928 (17.3 vs. 2.0) and A_860 (20.7 vs. 7.6) than their co-products from bioethanol processing. There were no differences (P > 0.05) in the peak area intensities of A_Cell (structural CHO) at 1292-1198 cm(-1) and A_CHO (total CHO) at 1187-950 cm(-1) with average molecular infrared intensity KM unit of 226.8 and 508.1, respectively. There were no differences (P > 0.05) in the peak height intensities of H_1415 and H_1370 (structural CHOs) with average intensities 1.35 and 1.15, respectively. The multivariate molecular spectral analyses were able to discriminate and classify between the corn and corn DDGS molecular spectra, but not wheat and wheat DDGS. This study indicated that the bioethanol processing changes carbohydrate molecular structural profiles, compared with the original grains. However, the sensitivities of different types of carbohydrates and different grains (corn and wheat) to the processing differ. In general, the bioethanol processing increases the molecular spectral intensities for the structural carbohydrates and decreases the intensities for the non-structural carbohydrates. Further study is needed to quantify carbohydrate related molecular spectral features of the bioethanol co-products in relation to nutrient supply and availability of carbohydrates.

Show MeSH
Related in: MedlinePlus