Application of reflectance near infrared spectroscopy for bread analyses

Detection of low-level gluten content in flour and batter by near infrared reflectance spectroscopy (NIRS)

“…This mathematical treatment is most commonly used in NIRS food analysis and has been used previously to develop a gluten calibration in commercial wheat flour (Miralbés, 2004) and for starch content in maize flour samples (Paulsen et al, 2003). Nevertheless, Sørensen (2009) calibrations for routine determination of dietary constituents of wheat and rye breads using the treatment 1, 10, 10, 1. The models obtained (Table 2) were satisfactory for the 8 calibrations presented, showing R 2 from 0.893 to 0.985, SEC values from 0.16 to 0.42 and SD/SECV ratio from 1.97 to 5.21.…”

“…The use of NIRS for quality control of cereals is well established in the literature (Osborne, 2000) and has been introduced successfully as a rapid technique for grain (Miralbés, 2003;Scholz et al, 2007), flour (Baslar and Ertugay, 2011;Miralbés, 2004;Paulsen et al, 2003), dough (Alava et al, 2001;Kaddour and Cuq, 2011;Sinelli et al, 2008) and bread (Osborne et al, 1984;Sørensen, 2009). In wheat flours, protein fractions (gliadin and glutenin) have been predicted using NIRS techniques (Wesley et al, 2001).…”

Development of a rapid, non-destructive method for egg content determination in dry pasta using FT-NIR technique

“…Bias represents the average difference between the data sets of reference values and the predicted values, R 2 is the percentage of variance accounted for by the calibration, RPD (residual prediction deviation) value is the quotient of the standard deviation of the reference values and the bias-corrected mean error of prediction of the validation (SEP). The values of R 2 , Rank, RMSEE, RMSEP, and RMSECV, respectively, were used to characterize the calibration and validation models (Naes et al, 2002;Sørensen, 2009). …”

Rapid screening astaxanthin-hyperproducing Haematococcus pluvialis mutants through near-infrared spectroscopy

“…In this study, the calibration equation was accepted with low RESECV values 0·284, 7·03 and 1·56 respectively. The parameter of residual predictive deviation (RPD) values are equally important for defining the robustness of models: values <2·5 correspond to poor modelling, values from 2·5 to 4 refers to fairly good modelling, and values >4 indicate excellent modelling (Sørensen ). As a result, we obtained the RPD values 4·97, 7·45 and 4·55 for astaxanthin content, biomass content and percentage astaxanthin respectively.…”