Can semiquantitative NMR deliver quantitative reproducibility? A harmonized qNMR strategy for betaine determination in durum wheat and pasta

Can a semiquantitative NMR workflow deliver truly quantitative results? This study shows that, under carefully harmonized conditions and with gravimetrically traceable reference standards, the answer can be yes (Figure 1). In a field where semiquantitative 1H NMR is routinely used for non-targeted metabolite profiling, demonstrating quantitative reproducibility from the same spectra would represent a major analytical advantage for food applications. To address this question, an interlaboratory comparison was carried out on the determination of betaine in aqueous extracts of durum wheat (cvv. Marco Aurelio and Iride) and the corresponding pasta products. A common set of samples was analyzed using a harmonized acquisition protocol across 50 spectrometers operating at magnetic field strengths from 80 to 700 MHz. Two data-processing strategies were compared: distributed operator-dependent processing, involving multiple operators and software environments, and centralized processing performed by a single operator using five different software platforms. Quantification was carried out by both internal and external standard methods, using TSP-d4, DMSO₂, and betaine as reference compounds. The results clearly demonstrate that the metrological reliability of the approach strongly depends on the reference standard employed. TSP-d4 systematically overestimated betaine concentration and introduced additional dispersion, whereas DMSO2 and betaine yielded accurate and highly precise results. Moreover, it was demonstrated that a non-targeted NMR workflow, commonly regarded as semiquantitative, can provide quantitatively robust determination of target analytes, when anchored to traceable standards with documented uncertainty. More broadly, the work highlights the possibility of using a single harmonized NMR experiment to obtain both reliable metabolite profiling and metrologically sound quantification in complex food matrices. Acknowledgements This work has been supported by Regione Puglia (Project IPERDURUM, Fondo europeo per lo sviluppo rurale: l’Europa investe nelle zone rurali” PSR 2014-2020. MISURA 16.2 Focus Area 2a).