The use of visible and near-infrared reflectance measurements to assess sensory changes in carrot texture and sweetness during heat treatment

被引:38
作者
De Belie, N
Pedersen, DK
Martens, M
Bro, R
Munck, L
De Baerdemaeker, J
机构
[1] State Univ Ghent, Dept Struct Engn, Magnel Lab Concrete Res, B-9052 Ghent, Belgium
[2] Royal Vet & Agr Univ, Dept Dairy & Food Sci, Copenhagen, Denmark
[3] Katholieke Univ Leuven, Dept Agroengn & Econ, Lab Agromachinery & Proc, B-3001 Heverlee, Belgium
关键词
D O I
10.1016/S1537-5110(03)00047-3
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
The use of non-destructive near-infrared reflectance (NIR) measurements to predict the change in sensory quality of carrot discs during heat treatment was investigated. Near-infrared reflectance measurements were performed on five different batches of carrots, cooked for 0, 1, 2, 5, 10, or 15 min, with a spectrophotometer with a wavelength range of 400-2500 nm. Per combination of batch and heat treatment, 20 carrot discs with a height of 8 mm and a diameter of 25 mm were tested. As instrumental reference measurements the dry matter content (DM), soluble solids content (SSC), compressive strength F-C and tensile strength F-t were recorded on carrots from the same batches and heat treatments. Sensory profiling was carried out on three of the five batches. The sensory attributes considered were hardness, crispness, juiciness, sweet smell, and sweet taste. The shape of the NIR spectra was determined by the water absorption bands and the absorption by carotenoids in the visual light region. Partial least-squares regression (PLSR) was used to predict the average sensory scores for each batch and cooking time from the NIR spectra obtained from individual carrot discs. Second-order derivative pre-processing combined with meancentring, provided a better prediction capability than first-order derivation or multiplicative scatter correction. The root mean square errors of prediction (RMSEP) amounted to 1.13, 1.20, 0.89, 0.78, and 1.06 for hardness, crispness, juiciness, sweet smell and sweet taste, respectively, in sensory units (scale 0 to 15). To obtain the best possible prediction, it appeared to be important to include batch-specific information in the model. Compared with a PLSR model based on the four physico-chemical reference measurements, the NIR model provided a better estimation of hardness, crispness, and sweet smell. Measurements for one batch on xylem and phloem parts of the carrot discs separately, showed that a further improvement of the model calibration could be obtained by taking the NIR spectrum on the phloem part. The average physico-chemical results for a specific batch and heat treatment, could be estimated from a PLSR model based on the NIR spectra, with an average RMSEP of 7-13% of the measurement range under consideration. The results suggest that NIR measurements could be successfully used to control sensory quality during heat treatment. (C) 2003 Silsoe Research Institute. All rights reserved Published by Elsevier Science Ltd.
引用
收藏
页码:213 / 225
页数:13
相关论文
共 30 条
  • [1] Method for the static headspace analysis of carrot volatiles
    Alasalvar, C
    Grigor, JM
    Quantick, PC
    [J]. FOOD CHEMISTRY, 1999, 65 (03) : 391 - 397
  • [2] [Anonymous], 2007, 8589 UNI EN ISO
  • [3] [Anonymous], 1989, MULTIVARIATE CALIBRA
  • [4] *ASTM STP, 1986, ASTM STP, V913
  • [5] BOUERIU CG, 1998, J NEAR INFRARED SPEC, V6, pA291
  • [6] BOURNE M.C., 1989, ACS SYM SER, P98
  • [7] BRO R, 1999, N WAY TOOLBOX MATLAB
  • [8] A REVIEW OF NONDESTRUCTIVE METHODS FOR QUALITY EVALUATION AND SORTING OF AGRICULTURAL PRODUCTS
    CHEN, P
    SUN, Z
    [J]. JOURNAL OF AGRICULTURAL ENGINEERING RESEARCH, 1991, 49 (02): : 85 - 98
  • [9] CZARNIEKCKA SE, 1996, HYGIENE NUTR FOODSER, V1, P191
  • [10] Use of physico-chemical methods for assessment of sensory changes in carrot texture and sweetness during cooking
    De Belie, N
    Laustsen, AM
    Martens, M
    Bro, R
    De Baerdemaeker, J
    [J]. JOURNAL OF TEXTURE STUDIES, 2002, 33 (05) : 367 - 388