Literature DB >> 33094367

A Rapid Method to Measure Serum Retinol Concentrations in Japanese Black Cattle Using Multidimensional Fluorescence.

Yoshio Tamura1, Hiroki Inoue2, Satoshi Takemoto2, Kazuo Hirano2, Kazutoshi Miyaura2.   

Abstract

Vitamin A levels in fattening Japanese Black cattle affect meat quality; therefore, it is important to monitor serum retinol concentrations. To simplify and accelerate the evaluation of serum retinol concentrations in cattle, we developed a new predictive method using excitation-emission matrix (EEM) fluorescence spectrophotometry. For analytical comparison, the concentration of serum retinol was also measured using the conventional HPLC method. We examined excitation (Ex) and emission (Em) wavelengths of cattle serum, which were 250-450 and 250-600 nm, respectively. Parallel factor analysis separated four components from EEM data, one of which was related to retinol. Next, a partial least square regression model was created using the obtained EEMs as explanatory variables and accrual measurement values as objective variables. The determination coefficient value (R2), root mean squared error of prediction (RMSEP), and the ratio of performance to deviation (RPD) of the model were determined. A comparison with reference values found that R2, RMSEP, and RPD of the calibration model were 0.95, 6.4 IU/dl, and 4.2, respectively. This implies that EEM can estimate the serum retinol concentration with high accuracy. Additionally, the fluorescent peaks that contributed to the calibration, which were extracted from the regression coefficient and variable importance in projection plots, were Ex/Em = 320/390 and 330/520 nm. Thus, we assume that this method observes not only free retinol, but also retinol-binding protein. In conclusion, multidimensional fluorescence analysis can accurately and quickly determine serum retinol concentrations in fattening cattle.

Entities:  

Keywords:  Multidimensional fluorescence; Parallel factor analysis; Partial least square regression; Retinol; Serum

Mesh:

Substances:

Year:  2020        PMID: 33094367      PMCID: PMC7819940          DOI: 10.1007/s10895-020-02640-w

Source DB:  PubMed          Journal:  J Fluoresc        ISSN: 1053-0509            Impact factor:   2.217


  14 in total

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Journal:  J Dairy Sci       Date:  2003-04       Impact factor: 4.034

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Journal:  Meat Sci       Date:  1998-01       Impact factor: 5.209

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Authors:  Evgeny Shirshin; Olga Cherkasova; Tatiana Tikhonova; Elena Berlovskaya; Alexander Priezzhev; Victor Fadeev
Journal:  J Biomed Opt       Date:  2015-05       Impact factor: 3.170

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Authors:  W J Driskell; J S Hewett; M M Bashor
Journal:  Clin Chem       Date:  1986-05       Impact factor: 8.327

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Journal:  J Nutr       Date:  1970-01       Impact factor: 4.798

6.  Quantitative fluorescence kinetic analysis of NADH and FAD in human plasma using three- and four-way calibration methods capable of providing the second-order advantage.

Authors:  Chao Kang; Hai-Long Wu; Chang Zhou; Shou-Xia Xiang; Xiao-Hua Zhang; Yong-Jie Yu; Ru-Qin Yu
Journal:  Anal Chim Acta       Date:  2016-01-12       Impact factor: 6.558

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Authors:  C A Collins; C K Chow
Journal:  J Chromatogr       Date:  1984-12-28

8.  Effect of dietary vitamin A concentration and roasted soybean inclusion on marbling, adipose cellularity, and fatty acid composition of beef.

Authors:  M A Gorocica-Buenfil; F L Fluharty; C K Reynolds; S C Loerch
Journal:  J Anim Sci       Date:  2007-04-27       Impact factor: 3.159

9.  Identification of cow and buffalo milk based on Beta carotene and vitamin-A concentration using fluorescence spectroscopy.

Authors:  Rahat Ullah; Saranjam Khan; Hina Ali; Muhammad Bilal; Muhammad Saleem
Journal:  PLoS One       Date:  2017-05-18       Impact factor: 3.240

10.  Hypovitaminosis A coupled to secondary bacterial infection in beef cattle.

Authors:  Xiuyuan He; Yongtao Li; Meng Li; Guangmin Jia; Haiju Dong; Yanru Zhang; Cong He; Chuanqing Wang; Lixin Deng; Yurong Yang
Journal:  BMC Vet Res       Date:  2012-11-14       Impact factor: 2.741

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