Use of multivariate techniques in studying the flour making properties of some CMD resistant cassava clones

High quality cassava flour (HQCF) is one of the primary products of raw cassava root that has continued to find wider food application in Nigeria. In this study, some 43 newly developed cassava mosaic disease (CMD) resistant clones of cassava were screened based on some physical (flour yield, bulk d...

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Main Authors: Shittu, T.A., Sanni, Lateef O., Awonorin, S.O., Maziya-Dixon, B.B., Dixon, A.
Format: Journal Article
Language:Inglés
Published: Elsevier 2007
Subjects:
Online Access:https://hdl.handle.net/10568/92160
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author Shittu, T.A.
Sanni, Lateef O.
Awonorin, S.O.
Maziya-Dixon, B.B.
Dixon, A.
author_browse Awonorin, S.O.
Dixon, A.
Maziya-Dixon, B.B.
Sanni, Lateef O.
Shittu, T.A.
author_facet Shittu, T.A.
Sanni, Lateef O.
Awonorin, S.O.
Maziya-Dixon, B.B.
Dixon, A.
author_sort Shittu, T.A.
collection Repository of Agricultural Research Outputs (CGSpace)
description High quality cassava flour (HQCF) is one of the primary products of raw cassava root that has continued to find wider food application in Nigeria. In this study, some 43 newly developed cassava mosaic disease (CMD) resistant clones of cassava were screened based on some physical (flour yield, bulk density, and tri-stimulus colour characteristics (Lab, Chroma and Hue), chemical (moisture,protein, ash, starch, amylose, sugar contents, TTA, pH, and cyanogenic potential), functional (water and oil absorption capacities, water solubility, swelling power, least gelation capacity, diastatic activity, percent damaged starch, and alkaline water retention), and pasting properties. One-way analysis of variance (ANOVA) showed that all properties measured varied significantly (P< 0.001). The flours had a wider range of starch content (65–88%), amylose content (13–23%), water absorption capacity (136–224%), diastatic activity (128–354 mg maltose), peak viscosity (77–328 RVU), final viscosity (56–217 RVU), and trough (32–152). Due to the peculiarity of the experimental data generated, two protocols of applying multivariate statistical techniques were evaluated for discriminating the cassava clones. By first applying principal component analysis (PCA), followed by cluster analysis (CA) and finally, discriminant function analysis (DFA) of the experimental data, it was possible to achieve about 87% correct classification of the cassava clones. The final viscosity and diastatic activity of the flours were found to be the most important variables for classifying the cassava clones.
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spelling CGSpace921602024-05-15T05:12:01Z Use of multivariate techniques in studying the flour making properties of some CMD resistant cassava clones Shittu, T.A. Sanni, Lateef O. Awonorin, S.O. Maziya-Dixon, B.B. Dixon, A. cassava mosaic disease resistant clones cassava flour physical properties chemical properties functional properties multivariate data analysis High quality cassava flour (HQCF) is one of the primary products of raw cassava root that has continued to find wider food application in Nigeria. In this study, some 43 newly developed cassava mosaic disease (CMD) resistant clones of cassava were screened based on some physical (flour yield, bulk density, and tri-stimulus colour characteristics (Lab, Chroma and Hue), chemical (moisture,protein, ash, starch, amylose, sugar contents, TTA, pH, and cyanogenic potential), functional (water and oil absorption capacities, water solubility, swelling power, least gelation capacity, diastatic activity, percent damaged starch, and alkaline water retention), and pasting properties. One-way analysis of variance (ANOVA) showed that all properties measured varied significantly (P< 0.001). The flours had a wider range of starch content (65–88%), amylose content (13–23%), water absorption capacity (136–224%), diastatic activity (128–354 mg maltose), peak viscosity (77–328 RVU), final viscosity (56–217 RVU), and trough (32–152). Due to the peculiarity of the experimental data generated, two protocols of applying multivariate statistical techniques were evaluated for discriminating the cassava clones. By first applying principal component analysis (PCA), followed by cluster analysis (CA) and finally, discriminant function analysis (DFA) of the experimental data, it was possible to achieve about 87% correct classification of the cassava clones. The final viscosity and diastatic activity of the flours were found to be the most important variables for classifying the cassava clones. 2007 2018-04-24T08:40:07Z 2018-04-24T08:40:07Z Journal Article https://hdl.handle.net/10568/92160 en Limited Access Elsevier Shittu, T.A., Sanni, L.O., Awonorin, S.O., Maziya-Dixon, B. & Dixon, A. (2007). Use of multivariate techniques in studying the flour making properties of some CMD resistant cassava clones. Food Chemistry, 101, 1606-1615.
spellingShingle cassava mosaic disease resistant clones
cassava flour
physical properties
chemical properties
functional properties
multivariate data analysis
Shittu, T.A.
Sanni, Lateef O.
Awonorin, S.O.
Maziya-Dixon, B.B.
Dixon, A.
Use of multivariate techniques in studying the flour making properties of some CMD resistant cassava clones
title Use of multivariate techniques in studying the flour making properties of some CMD resistant cassava clones
title_full Use of multivariate techniques in studying the flour making properties of some CMD resistant cassava clones
title_fullStr Use of multivariate techniques in studying the flour making properties of some CMD resistant cassava clones
title_full_unstemmed Use of multivariate techniques in studying the flour making properties of some CMD resistant cassava clones
title_short Use of multivariate techniques in studying the flour making properties of some CMD resistant cassava clones
title_sort use of multivariate techniques in studying the flour making properties of some cmd resistant cassava clones
topic cassava mosaic disease resistant clones
cassava flour
physical properties
chemical properties
functional properties
multivariate data analysis
url https://hdl.handle.net/10568/92160
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