Prediction of main potato compounds by NIRS
Fecha
2017Autor
Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión publicada / Argitaratu den bertsioa
Impacto
|
10.3303/CET1758065
Resumen
Potato (Solanum tuberosum, L) compounds are generally determined by analytical methods including gasliquid
chromatography (GLC), HPLC and UV-VIS spectrophotometry. These methods require a lot of time and
are destructive. Therefore, they seem to be not suitable for in-line applications in the food industry. Nearinfrared
spectroscopy (NIRS) is a technique that presents some advantages over refer ...
[++]
Potato (Solanum tuberosum, L) compounds are generally determined by analytical methods including gasliquid
chromatography (GLC), HPLC and UV-VIS spectrophotometry. These methods require a lot of time and
are destructive. Therefore, they seem to be not suitable for in-line applications in the food industry. Nearinfrared
spectroscopy (NIRS) is a technique that presents some advantages over reference methods for
quantitative analysis of agricultural and food products since it is fast, reliable and non-destructive.
For this reason, in this study, quantitative analyses were carried out to determine main compounds in potatoes
using NIRS.
Potato tubers grown in two consecutive years were used for the analyses. NIR spectral acquisition was
acquired on lyophilized samples. In year 1, a total of 135 samples were used while 228 samples were used in
year 2. Lyophilized samples were also scanned by NIRS, two replicates per samples were acquired and the
mean spectrum of each sample was used for the analysis.
Different chemical analyses were carried out each year. Thus, in year 1 the following parameters were
quantified: reducing sugars (RS) and nitrogen (N), whereas in year 2, total soluble phenolics (TSP) and
hydrophilic antioxidant capacity (HAC) were extracted and quantified. Then, chemometric analyses were
performed using Unscrambler X (version 10.3, CAMO software AS, Oslo, Norway) to correlate wet chemical
analysis with spectral data. Quantitative analyses based on PLS regression models were developed in order
to predict the above chemical compounds of tubers in a non-destructive manner.
Good PLS regression models were obtained for the prediction of nitrogen and TSP with coefficients of
determination (R2) above 0.83. Moreover, PLS models obtained for the estimation of HAC could be used for
screening and approximate calibrations. [--]
Materias
Potato compounds,
NIRS
Editor
AIDIC
Publicado en
Chemical Engineering Transactions, vol. 58, 2017
Departamento
Universidad Pública de Navarra. Departamento de Proyectos e Ingeniería Rural /
Nafarroako Unibertsitate Publikoa. Landa Ingeniaritza eta Proiektuak Saila
Versión del editor
Entidades Financiadoras
This work was financed within the frame of INIA’s project RTA2013-00006-C03-01-03, the Basque
Government and the Universidad Pública de Navarra through the concession of a predoctoral research grant.