Non-invasive method to predict the composition of requeijão cremoso directly in commercial packages using time domain NMR relaxometry and chemometrics.

• Autor(a) principal: MACHADO, G. O.
• Data de Publicação: 2022
• Outros Autores: TEIXEIRA, G. G., GARCIA, R. H. S., MORAES, T. B., BONA, E., SANTOS, P. M., COLNAGO, L. A.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
• Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1148849; https://doi.org/10.3390/molecules27144434
• topic: TD-NMR; Requeijão cremoso; CPMG; PLS; OPS

Low Field Time-Domain Nuclear Magnetic Resonance (TD-NMR) relaxometry was used to determine moisture, fat, and defatted dry matter contents in ?requeijão cremoso? (RC) processed cheese directly in commercial packaged (plastic cups or tubes with approximately 200 g). Forty-five samples of commercial RC types (traditional, light, lactose-free, vegan, and fiber) were analyzed using longitudinal (T1) and transverse (T2) relaxation measurements in a wide bore Halbach magnet(0.23 T) with a 100 mm probe. The T1 and T2 analyses were performed using CWFP-T1(Continuous Wave Free Precession) and CPMG (Carr-Purcell-Meiboom-Gill) single shot pulses. The scores of the principal component analysis (PCA) of CWFP-T1 and CPMG signals did not show clustering related to the RC types. Optimization by variable selection was carried out with ordered predictorsselection (OPS), providing simpler and predictive partial least squares (PLS) calibration models. The best results were obtained with CWFP-T1 data, with root-mean-square errors of prediction (RMSEP) of 1.38, 4.71, 3.28, and 3.00% for defatted dry mass, fat in the dry and wet matter, and moisture, respectively. Therefore, CWFP-T1 data modeled with chemometrics can be a fast method to monitor the quality of RC directly in commercial packages