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.
|Número de páginas||7|
|Publicación||Advances in Intelligent Systems and Computing|
|Estado||Publicada - 2014|
|Publicado de forma externa||Sí|
|Evento||8th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2014 - Salamanca, Espana|
Duración: 4 jun. 2014 → 6 jun. 2014