'Calçots', the immature floral stems of second-year onion resprouts, are an economically important traditional crop in Catalonia (Spain). Classical approaches to evaluating the chemical properties of 'calçots' are time consuming and expensive; near-infrared spectroscopy (NIRS) may be faster and cheaper. We used NIRS to develop partial least square (PLS) models to predict dry matter, soluble solid content, titratable acidity, and ash content in cooked 'calçots'. To guarantee the robustness of the models, calibration samples were grown and analyzed in a first season (2014-15) and validation samples in a second season (2015-16). NIRS on puree spectra estimated dry matter and soluble solid content with excellent accuracy (R2pred = 0.953, 0.985 and RPD = 4.571, 8.068, respectively). However, good estimation of titratable acidity and ash content required using ground dried puree spectra (R2pred = 0.852, 0.820 and RPD = 2.590, 1.987, respectively). NIRS can be a helpful tool for 'calçots' breeding and quality control.
Keywords: Chemometrics; Multivariate calibration; NIR; PLS; Quality; ‘Calçot’.
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