Application of near infra-red spectroscopy as an instantaneous and simultaneous prediction tool for anthocyanins and sugar in whole fresh raspberry

Background: The determination of fresh whole raspberry quality is a laborious and expensive process for commercial producers and researchers. Quantitative results for raspberry quality parameters are currently determined using a range of chemical tests within a commercial laboratory. The present work is the first calibration and validation of near infra‐red spectroscopy (NIRS) for instantaneous and simultaneous of prediction of raspberry quality parameters. The importance and applicability of the findings of this research underscore its need and importance for both producers and researchers.

Results: Near infra‐red quantification models were developed to predict the level of soluble solid concentration (SSC) and anthocyanins present in whole fresh raspberries. Results highlighted a promising application for the prediction of anthocyanins (R²_cv = 0.77) and SSC (R²_cv = 0.77). The anthocyanin model had an root mean square error (RMSE) of 12.57 mg/L whilst SSC had 0.76 °Brix.

Conclusion: Both NIR models combined with new portable NIR devices provide unprecedented opportunity for the application of instantaneous and simultaneous quality parameter prediction for commercial raspberry producers and researchers. The numerous benefits NIR has brought to other horticultural industries are now closer for the raspberry industry with this proof of concept.