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Influence of polymorphism on the solid fat content determined by FID deconvolution

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Abstract
One of the most important quality parameters of a fat, is its solid fat content (SFC). The standard method to determine the SFC is pNMR using a f-factor. This factor is determined with three standards. However, this contribution shows that SFC standards are not required when using deconvolution methods. At first, data acquisition is optimized. These experiments revealed that the deconvolution method worked better, if more sample is present in the detection zone of the NMR, due to a higher signal-to-noise ratio (SNR). Regarding deconvolution, a bi-Gaussian model and a model combining a Gaussian and Abragamian function are compared. Both models are able to fit the free induction decay (FID) data. Furthermore, the corresponding SFC values are comparable with the SFC values of the f-factor method when analyzing SFC standards or fats which are preprocessed using the AOCS tempering protocol. Upon evaluating the influence of the polymorphic states of cocoa butter, it became clear that the f-factor standards resemble fats containing -polymorphs. As a further consequence, the f-factor method fails when -polymorphs are present to a large extent. Overall this study shows that the deconvolution method is superior to the f-factor method since it does not require any standards and is less affected by the polymorphic state.Practical Applications: This work shows that the solid fat content (SFC) of a fat can be calculated without the use of calibration standards. If deconvolution would replace the standard used pNMR method, it could potentially reduce the preparation time for the measurements, because no calibration is necessary. Next to this, it also lowers the cost of SFC determination, because no standards should be bought. Deconvolution also gives insight in the behavior of the different components present in the sample, for example, T-2-values. There above, research toward deconvolution of pNMR signals is necessary as it could potentially also determine the presence of different fat crystal polymorphs present in samples. One of the most important quality parameters of a fat, is its solid fat content (SFC). The standard method to determine the SFC is pNMR using a f-factor. However, this contribution shows that SFC standards are not requires when using deconvolution methods. At first, data acquisition is optimized. These experiments revealed that the deconvolution method worked better, if more sample is present in the detection zone of the NMR, due to a higher signal-to-noise ratio (SNR). Regarding deconvolution, a bi-Gaussian model and a model combining a Gaussian and Abragamian function are compared. Both models are able to fit the free induction decay (FID) data.
Keywords
deconvolution, free induction decays, lipids, NMR, solid fat content, TIME-DOMAIN NMR, PHASE-COMPOSITIONAL ASSESSMENT, NUCLEAR-MAGNETIC-RESONANCE, FOOD-PRODUCTS, LIQUID RATIOS, OIL, BLENDS, CRYSTALLIZATION, SHORTENINGS, EMULSIONS

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Chicago
Declerck, Arnout, Veronique Nelis, Tom Rimaux, Koen Dewettinck, and Paul Van Der Meeren. 2018. “Influence of Polymorphism on the Solid Fat Content Determined by FID Deconvolution.” European Journal of Lipid Science and Technology 120 (3).
APA
Declerck, A., Nelis, V., Rimaux, T., Dewettinck, K., & Van Der Meeren, P. (2018). Influence of polymorphism on the solid fat content determined by FID deconvolution. EUROPEAN JOURNAL OF LIPID SCIENCE AND TECHNOLOGY, 120(3).
Vancouver
1.
Declerck A, Nelis V, Rimaux T, Dewettinck K, Van Der Meeren P. Influence of polymorphism on the solid fat content determined by FID deconvolution. EUROPEAN JOURNAL OF LIPID SCIENCE AND TECHNOLOGY. 2018;120(3).
MLA
Declerck, Arnout, Veronique Nelis, Tom Rimaux, et al. “Influence of Polymorphism on the Solid Fat Content Determined by FID Deconvolution.” EUROPEAN JOURNAL OF LIPID SCIENCE AND TECHNOLOGY 120.3 (2018): n. pag. Print.
@article{8538988,
  abstract     = {One of the most important quality parameters of a fat, is its solid fat content (SFC). The standard method to determine the SFC is pNMR using a f-factor. This factor is determined with three standards. However, this contribution shows that SFC standards are not required when using deconvolution methods. At first, data acquisition is optimized. These experiments revealed that the deconvolution method worked better, if more sample is present in the detection zone of the NMR, due to a higher signal-to-noise ratio (SNR). Regarding deconvolution, a bi-Gaussian model and a model combining a Gaussian and Abragamian function are compared. Both models are able to fit the free induction decay (FID) data. Furthermore, the corresponding SFC values are comparable with the SFC values of the f-factor method when analyzing SFC standards or fats which are preprocessed using the AOCS tempering protocol. Upon evaluating the influence of the polymorphic states of cocoa butter, it became clear that the f-factor standards resemble fats containing -polymorphs. As a further consequence, the f-factor method fails when -polymorphs are present to a large extent. Overall this study shows that the deconvolution method is superior to the f-factor method since it does not require any standards and is less affected by the polymorphic state.Practical Applications: This work shows that the solid fat content (SFC) of a fat can be calculated without the use of calibration standards. If deconvolution would replace the standard used pNMR method, it could potentially reduce the preparation time for the measurements, because no calibration is necessary. Next to this, it also lowers the cost of SFC determination, because no standards should be bought. Deconvolution also gives insight in the behavior of the different components present in the sample, for example, T-2-values. There above, research toward deconvolution of pNMR signals is necessary as it could potentially also determine the presence of different fat crystal polymorphs present in samples. One of the most important quality parameters of a fat, is its solid fat content (SFC). The standard method to determine the SFC is pNMR using a f-factor. However, this contribution shows that SFC standards are not requires when using deconvolution methods. At first, data acquisition is optimized. These experiments revealed that the deconvolution method worked better, if more sample is present in the detection zone of the NMR, due to a higher signal-to-noise ratio (SNR). Regarding deconvolution, a bi-Gaussian model and a model combining a Gaussian and Abragamian function are compared. Both models are able to fit the free induction decay (FID) data.},
  articleno    = {1700339},
  author       = {Declerck, Arnout and Nelis, Veronique and Rimaux, Tom and Dewettinck, Koen and Van Der Meeren, Paul},
  issn         = {1438-7697},
  journal      = {EUROPEAN JOURNAL OF LIPID SCIENCE AND TECHNOLOGY},
  language     = {eng},
  number       = {3},
  pages        = {11},
  title        = {Influence of polymorphism on the solid fat content determined by FID deconvolution},
  url          = {http://dx.doi.org/10.1002/ejlt.201700339},
  volume       = {120},
  year         = {2018},
}

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