Determination of Carbohydrate Composition in Lentils Using Near-Infrared Spectroscopy

被引:1
|
作者
Lopez-Calabozo, Rocio [1 ]
Liberal, Angela [1 ,2 ,3 ]
Fernandes, Angela [2 ,3 ]
Revilla, Isabel [1 ]
Ferreira, Isabel C. F. R. [2 ,3 ]
Barros, Lillian [2 ,3 ]
Vivar-Quintana, Ana M. [1 ]
机构
[1] Univ Salamanca, Escuela Politecn Super Zamora, Food Technol Area, Ave Requejo 33, Zamora 49022, Spain
[2] Inst Politecn Braganca, Ctr Invest Montanha CIMO, Campus Santa Apolonia, P-5300253 Braganca, Portugal
[3] Inst Politecn Braganca, Lab Sustentabilidade & Tecnol Regioes Montanha, Campus Santa Apolonia, P-5300253 Braganca, Portugal
关键词
lentil; carbohydrates; NIR; fibre; starch; sugars; LENS-CULINARIS MEDIK; GEOGRAPHICAL ORIGIN; HEALTH-BENEFITS; SUCROSE CONTENT; FT-NIR; QUALITY; PROTEIN; STARCH; PULSES; MAIZE;
D O I
10.3390/s24134232
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Carbohydrates are the main components of lentils, accounting for more than 60% of their composition. Their content is influenced by genetic factors, with different contents depending on the variety. These compounds have not only been linked to interesting health benefits, but they also have a significant influence on the techno-functional properties of lentil-derived products. In this study, the use of near-infrared spectroscopy (NIRS) to predict the concentration of total carbohydrate, fibre, starch, total sugars, fructose, sucrose and raffinose was investigated. For this purpose, six different cultivars of macrosperm (n = 37) and microsperm (n = 43) lentils have been analysed, the samples were recorded whole and ground and the suitability of both recording methods were compared. Different spectral and mathematical pre-treatments were evaluated before developing the calibration models using the Modified Partial Least Squares regression method, with a cross-validation and an external validation. The predictive models developed show excellent coefficients of determination (RSQ > 0.9) for the total sugars and fructose, sucrose, and raffinose. The recording of ground samples allowed for obtaining better models for the calibration of starch content (R > 0.8), total sugars and sucrose (R > 0.93), and raffinose (R > 0.91). The results obtained confirm that there is sufficient information in the NIRS spectral region for the development of predictive models for the quantification of the carbohydrate content in lentils.
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页数:17
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