TY - JOUR
T1 - Discrimination of Brazilian Cassava Genotypes (Manihot Esculenta Crantz) According to Their Physicochemical Traits and Functional Properties Through Bioinformatics Tools
AU - Moresco, Rodolfo
AU - Uarrota, VirgíLio G.
AU - Nunes, Eduardoda C.
AU - Coelho, Bianca
AU - Amante, Edna Regina
AU - Gervin, Vanessa Maria
AU - Eduardo M Campos, Carlos
AU - Rocha, Miguel
AU - Maraschin, Marcelo
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2014.
PY - 2014
Y1 - 2014
N2 - Manihot esculenta currently ranks as the third most important species source of calories in the world. The most important part of the plant is the root, rich in starch. The starch fraction is basically composed of amylose and amylopectin, and different ratios of contents of these two polysaccharides determine the physicochemical traits and functional properties peculiars to genotypes. In this study, principal component analysis (PCA) and clusters analysis were applied to a set of physicochemical and functional variables of ten starch samples of M. esculenta genotypes. Moreover, a further chemometric approach was used to a FTIR spectral data set. The analytical techniques employed, associated with chemometric analyzes, allowed distinguishing and/or grouping the genotypes according to their physicochemical traits and functional peculiarities. It was also observed a good relationship between the descriptive models built using the physicochemical dataset and the FTIR dataset from the carbohydrate fingerprint region, allowing a more detailed and robust understanding of possible differences and/or similarities of the studied genotypes.
AB - Manihot esculenta currently ranks as the third most important species source of calories in the world. The most important part of the plant is the root, rich in starch. The starch fraction is basically composed of amylose and amylopectin, and different ratios of contents of these two polysaccharides determine the physicochemical traits and functional properties peculiars to genotypes. In this study, principal component analysis (PCA) and clusters analysis were applied to a set of physicochemical and functional variables of ten starch samples of M. esculenta genotypes. Moreover, a further chemometric approach was used to a FTIR spectral data set. The analytical techniques employed, associated with chemometric analyzes, allowed distinguishing and/or grouping the genotypes according to their physicochemical traits and functional peculiarities. It was also observed a good relationship between the descriptive models built using the physicochemical dataset and the FTIR dataset from the carbohydrate fingerprint region, allowing a more detailed and robust understanding of possible differences and/or similarities of the studied genotypes.
KW - Cassava genotypes
KW - Chemometrics
KW - FTIR
KW - Manihot esculenta Crantz
UR - http://www.scopus.com/inward/record.url?scp=84921735691&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-07581-5_7
DO - 10.1007/978-3-319-07581-5_7
M3 - Conference article
AN - SCOPUS:84921735691
SN - 2194-5357
VL - 294
SP - 57
EP - 63
JO - Advances in Intelligent Systems and Computing
JF - Advances in Intelligent Systems and Computing
IS - AISC
T2 - 8th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2014
Y2 - 4 June 2014 through 6 June 2014
ER -