1999
DOI: 10.3168/jds.s0022-0302(99)75446-9
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Fluorescence Spectroscopy Investigation of Acid-or Rennet-Induced Coagulation of Milk

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Cited by 98 publications
(102 citation statements)
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“…The maximum in the emission spectra of TRP was found at a relatively higher value than in previous papers, 340-342 nm against 330-333 nm, either in emulsions with dairy proteins, in processed milk or in soft cheeses [9,10,17,18]. This shift of the maximum cannot be due to the heat treatment of milk.…”
Section: Front-face Fluorescence Spectroscopymentioning
confidence: 41%
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“…The maximum in the emission spectra of TRP was found at a relatively higher value than in previous papers, 340-342 nm against 330-333 nm, either in emulsions with dairy proteins, in processed milk or in soft cheeses [9,10,17,18]. This shift of the maximum cannot be due to the heat treatment of milk.…”
Section: Front-face Fluorescence Spectroscopymentioning
confidence: 41%
“…This method might be regarded as a nondestructive, in situ, powerful and sensitive method, when associated with PCA, particularly recommended when studying a gelation under varying physicochemical environments such as acidification. During the acidification of unheated milk with GDL studied with intrinsic tryptophan (TRP), a shift of the maximum of spectra to lower wavelengths was evidenced, due to a more hydrophobic environment of TRP [17]. A first linear increase of the intensity at 320 nm versus pH was reported, followed by a second one with a higher slope.…”
Section: Introductionmentioning
confidence: 90%
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“…Considering the semi-hard cheeses such as Salers cheese, the interactions between the protein network and the fat globule vary, depending on the milk composition and on the manufacturing process (acidification rate), and modify in different ways the vitamin A spectra [7,14,15]. Crystallisation of the triglycerides during ripening time may also alter the shape of vitamin A fluorescence spectra [8,20].…”
Section: Correlations Between Sensory and Fluorescence Datamentioning
confidence: 99%
“…Principal Component Analysis (PCA) was applied to the physico-chemical data, to the stress/strain curves and to the normalised spectra in order to investigate changes in the data [14][15]. This statistical multivariate treatment makes it possible to draw similarity maps of the samples and to get spectral patterns [1,17].…”
Section: Multidimensional Analysis Of the Datamentioning
confidence: 99%