Noodle flour quality - Using multivariate analysis on the RVA curve to predict Viscograph® results


The pasting properties of flour provide a useful indication of its suitability for making noodles, bread, cakes, batters and other products. Flour pasting quality is now commonly measured using the Rapid Visco Analyser (RVA). Nonetheless many users still require the results to be converted to historical Viscograph® units for trade. Most commonly this is done by simple correlations. However multivariate analysis (MVA) offers a potentially superior method.

MVA techniques use multiple variables from the NIR spectra to develop calibrations that predict parameters like moisture and protein in wheat of flour in the NIR instrument. For rheological instruments like the RVA, doughLAB or TVT, the corresponding viscosity/torque/force versus time 'spectrum' (curve) can be used.

The Prediction Pack is an optional software available to users of the Thermocline for Windows (TCW) software for the RVA, the doughLAB for Windows (DLW) software for the doughLAB and micro-doughLAB, and the TexCalc software for the TVT. The Prediction Pack allows the use of MVA techniques on the available data to predict a desired parameter. The Prediction Pack is used to load prediction models first created using The Unscrambler® X software, which can then be used to create analysis results.

This study describes how MVA can improve prediction of Viscograph® parameters using the RVA curve as “spectrum”.

Materials and Methods

Forty-seven noodle wheat flours with varying compositional (ash, gluten) and rheological qualities (Viscograph®, Farinograph®, Extensograph® and Falling Number® values) were obtained from a commercial source in Tianjin, China. Viscosity analyses were performed on a Perten Instruments RVA 4500 using the noodle profile (Table 1), at the same sample concentration used in Viscograph® tests (15.1%). Viscograph® analyses of interest were peak, hold, final, breakdown and setback viscosities, peak time and pasting temperature.

Table 1: RVA Noodle Method profile (RVA Method no. 12.06).

Idle temperature: 60 ± 1°C, Time between readings: 4 s

Univariate comparisons of the Viscograph® and the corresponding RVA results were performed by regression analyses and The Unscrambler® X software were used for the MVA.

A suitable (optimum) model is one with large R2 and small RMSE of calibration (RMSEC) and cross-validation (RMSECV). RMSECV was used in preference to RMSE of prediction (RMSEP) in this study, since it indicates model robustness in the absence of a separate validation data set.

Results and Discussion

Typical RVA and Viscograph® curves for each of the test profiles are shown in Figure 1. 

Figure 1. Example viscosity curves of wheat noodle flours tested on the RVA using the noodle profile (left) and Viscograph® using the standard profile (right). Points on the Viscograph® graph: A - point of pasting temperature, B - peak viscosity, C - end of heating phase, D - end of maximum temperature holding phase, E - end of cooling phase, F - end of test.

Univariate Analysis of RVA and Viscograph® Results

Univariate analyses of the corresponding primary results (peak, hold and final viscosities) compared well between RVA and Viscograph® (R2 > 89.5%) (Table 2, Figure 2). Derived viscosity parameters (breakdown and setback) had weaker correlations (R2 50 – 70%); this was expected since the derived values were dependent on variation between the multiple parameters. Weak or no correlation (R2 < 50%) was observed between the instruments for peak time and pasting temperature using univariate analyses. This was probably due to the different heating rates used.

Figure 2. Univariate regressions of RVA with Viscograph® primary parameters (peak, hold and final viscosities; left) and derived parameters (breakdown and setback; right). n=47.

Table 2. Goodness of fit of univariate and MVA PLS regression models between RVA and Viscograph® data. n=47.a

aPLS = partial least squares, VG = Viscograph®, RVA = Rapid Visco Analyser, R2 = coefficient of determination (%), n = number of samples, RMS = root mean square error fit of univariate regression, RMSEC = root mean squared error of calibration and RMSECV = root mean squared error of cross-validation. Error values for viscosity (peak, hold, breakdown, final, setback) are in BU, time in min and temperature in °C.

Multivariate Analysis of RVA and Viscograph® Results

Multivariate analyses (PLS) of RVA viscosity spectra gave better predictions of Viscograph® values than univariate analyses for every parameter (smaller residual errors and larger R2 values, Table 2). Generally, better predictions of Viscograph® results were also achieved using the entire RVA curve compared to selected RVA analysis points, and with separate models rather than a combined model (results not shown).

Predictive models created in The Unscrambler ®can be exported to the RVA software using the Prediction Pack. With the Prediction Pack, a test configuration combining predictive models and other analysis functions (e.g. for peak, hold and final viscosities) can be created. Additional covariates from other sources could also be added to the model, in which case the value for these parameters will be requested by TCW each time a test is run and then used in the prediction. When the given test configuration is used to test future samples, the software will output the predicted Viscograph® values using the RVA viscosity curve.


The RVA 4500, using the noodle test profile and multivariate analysis (PLS) of the viscosity spectra, gave good predictions of Viscograph® results.

The Prediction Pack offers users of RVA, as well as doughLAB, micro-doughLAB and TVT Texture analyzer a tool to be able to use MVA on the instruments viscosity/torque/force vs. time curve. In this way results from other instrument can be better predicted and new information and parameters may also be developed that use the full information in the viscosity/torque/force curve to predict a given attribute in the analyzed sample type.

Viscograph®, Farinograph® and Extensograph® are registered trademarks of Brabender GmbH & Co.
The Unscrambler® is a registered trademark of CAMO Software AS.
Falling Number® is a registered trademark of Perten Instruments AB.