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In this study NIR spectroscopy and Partial Least Square Regression (PLSR) were evaluated for prediction of citral superficial content (SC-superficial of citral) on microparticles. For this purpose, samples of microparticles with different SC were prepared; varying the citral:dextrin (Ct:Dx) ratio, in the solution (1:5 and 1:20), in the solution and inlet air temperature (TAI) in a spray dryer (120 and 200 °C), in the drying process, getting 12 treatments. The SC was measured by gas chromatography. Then, each treatment was divided into six-parts, four for modeling and two for validation, obtaining 72 parts and from each one its absorbance spectral profile (1100 and 2500 nm), was extracted and pretreated. Subsequently, the PLSR method was applied to model the relationship between the spectral profiles and the SC values. Models were obtained with full spectra and optimized models with the relevant wavelengths. The results obtained with the optimized PLSR model showed R2 values higher than 0.89 and RMSEC less than 4.86x10-15. So, the NIR-PLSR method showed potential for the determination of citral on microcapsules.

Prediction of citral superficial content on microparticles by NIR spectroscopy and partial least square regression