Performance comparison of sampling designs for quality and safety control of raw materials in bulk: a simulation study based on NIR spectral data and geostatistical analysis
This study exploits the potential of near infrared (NIR) spectroscopy to deliver a measurement for each sampling point. Furthermore, it provides a protocol for the modelling of the spatial pattern of analytical constituents. On the basis of these two aspects, the methodology proposed in this work offers an opportunity to provide a real-time monitoring system to evaluate raw materials, easing and optimising the existing procedures for sampling and analysing products transported in bulk. In this paper, Processed Animal Proteins (PAPs) were selected as case study, and two types of quality/safety issues were tested in PAP lots —induced by moisture and cross-contamination. A simulation study, based on geostatistical analysis and the use of a set of sampling protocols, made a qualitative analysis possible to compare the representation of the spatial surfaces produced by each design. Moreover, the Root Mean Square Error of Prediction (RMSEP), calculated from the differences between the analytical values and the geostatistical predictions at unsampled locations, was used to measure the performance in each case. Results show the high sensitivity of the process to the sampling plan used — understood as the sampling design plus the sampling intensity. In general, a gradual decrease in the performance can be observed as the sampling intensity decreases, so that unlike for higher intensities, the too low ones resulted in oversmoothed surfaces which did not manage to represent the actual distribution. Overall, Stratified and Simple Random samplings achieved the best results in most cases. This indicated that an optimal balance between the design and the intensity of the sampling plan is imperative to perform this methodology
