Rapid analyses of oil and fat content in agri‐food products using continuous wave free precession time domain NMR

Abstract

Time-domain nuclear magnetic resonance (TD-NMR) is one of the most popular solutions for quality control in the food industry. Despite the recognized success of TD-NMR in quality control and quality assurance, the speed by which samples can be characterized by TD-NMR techniques is still a concern, primarily when considering online or high-throughput applications. Therefore, to enhance the speed of TD-NMR analysis, we developed rapid methods based on steady-state free precession of nuclear spins, which we denoted continuous wave free precession (CWFP). CWFP substantially increases the sensitivity of TD-NMR compared with free induction decay or spin-echo detection, which are traditionally used. The objective of this paper was to present the physical background of CWFP and review its recent developments and applications in fat and oil quantifications in agri-food products.

Food Analysis: Present, Future, and Foodomics

“…The use of the midinfrared region has been applied to study the secondary structure of food proteins [42] or to study intact food systems exploring their molecular structurequality relationships [43], while raman spectroscopy has also found a number of applications in agricultural products and food analysis [44]. Another spectroscopic technique such as nuclear magnetic resonance (NMR) has been used for the rapid analysis of oil and fact content in agrifood products [45], or in the mode 31P NMR to solve different problems in food analysis [46]. Other topics currently under development are the application of chemiluminescence in food analysis [47] or the use of chemiluminescence as detection in LC [48] or CE [49].…”

Uso da RMN como um sensor online em processos industriais

“…39 Nesse trabalho também foi utilizado o método de análise de componentes principais, PCA -Principal Component Analysis, para visualização de similaridades ou diferenças entre os sinais CWFP das amostras de sementes analisadas. Os gráficos dos escores de PCA representaram mais de 98% dos dados (PC 1 = 95,01% e PC 2 = 3,70%) (Figura 6).…”

“…Os gráficos dos escores de PCA representaram mais de 98% dos dados (PC 1 = 95,01% e PC 2 = 3,70%) (Figura 6). 39 As sementes de Fevillea trilobata e café (), que são compostas por mais de 40% de ácidos graxos saturados, com razão T 1 /T 2 > 2 ficaram do lado esquerdo do gráfico (valores de PC 1 de -100 a -80), enquanto que as sementes ricas em ácidos graxos monoinsaturados, com razão T 1 /T 2 próxima de 2, isto é, moringa, macadâmia e rabanete (), ficaram entre -60 a -40. Entre -20 a +40 ( e ) ficaram as sementes ricas em ácidos graxos poli-insaturados com razão T 1 /T 2 próxima de 1.…”

“…A linhaça () ficou no topo do lado direito de PC 1 , devido seu alto conteúdo de ácido linolênico. 39 Andrade et al desenvolveram um novo método para medidas de qualidade de sementes oleaginosas online, baseado na dependência de T 1 e T 2 . 40 Esse método foi denominado CP-CWFP por ser baseado na sequência de eco de spin proposta por Carr-Purcell (CP) e, ainda, por possuir características semelhantes ao método CWFP.…”

Suppression of spectral anomalies in SSFP-NMR signal by the Krylov Basis Diagonalization Method

“…This sequence has been used to enhance signal to noise ratio (S/N) or in fast acquisition protocols in low field NMR [8][9][10] and MRI [11]. However, it has been rarely used to enhance S/N in high resolution NMR, because the overlap between FID and echo signal in SSFP signal introduces severe phase, intensity and truncation anomalies in the Fourier transform spectrum.…”