Literature DB >> 15652574

Quantification of glucosinolates in leaves of leaf rape (Brassica napus ssp. pabularia) by near-infrared spectroscopy.

Rafael Font1, Mercedes del Río-Celestino, Elena Cartea, Antonio de Haro-Bailón.   

Abstract

The potential of near-infrared spectroscopy (NIRS) for screening the total glucosinolate (t-GSL) content, and also, the aliphatic glucosinolates gluconapin (GNA), glucobrassicanapin (GBN), progoitrin (PRO), glucoalyssin (GAL), and the indole glucosinolate glucobrassicin (GBS) in the leaf rape (Brassica napus L. ssp. pabularia DC), was assessed. This crop is grown for edible leaves for both fodder and human consumption. In Galicia (northwestern Spain) it is highly appreciated for human nutrition and have the common name of "nabicol". A collection of 36 local populations of nabicol was analysed by NIRS for glucosinolate composition. The reference values for glucosinolates, as they were obtained by high performance liquid chromatography on the leaf samples, were regressed against different spectral transformations by modified partial least-squares (MPLS) regression. The coefficients of determination in cross-validation (r2) shown by the equations for t-GSL, GNA, GBN, PRO, GAL and GBS were, respectively, 0.88, 0.73, 0.81, 0.78, 0.37 and 0.41. The standard deviation to standard error of cross-validation ratio, were for these constituents, as follows: t-GSL, 2.96; GNA, 1.94; GBN, 2.31; PRO, 2.11; GAL, 1.27, and GBS, 1.29. These results show that the equations developed for total glucosinolates, as well as those for gluconapin, glucobrassicanapin and progoitrin, can be used for screening these compounds in the leaves of this species. In addition, the glucoalyssin and glucobrassicin equations obtained, can be used to identify those samples with low and high contents. From the study of the MPLS loadings of the first three terms of the different equations, it can be concluded that some major cell components as protein and cellulose, highly participated in modelling the equations for glucosinolates.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 15652574     DOI: 10.1016/j.phytochem.2004.11.011

Source DB:  PubMed          Journal:  Phytochemistry        ISSN: 0031-9422            Impact factor:   4.072


  7 in total

1.  Screening for erucic acid and glucosinolate content in rapeseed-mustard seeds using near infrared reflectance spectroscopy.

Authors:  Satyanshu Kumar; Jitendra Singh Chauhan; Arvind Kumar
Journal:  J Food Sci Technol       Date:  2010-10-29       Impact factor: 2.701

Review 2.  Perspectives for integrated insect pest protection in oilseed rape breeding.

Authors:  Christian Obermeier; Annaliese S Mason; Torsten Meiners; Georg Petschenka; Michael Rostás; Torsten Will; Benjamin Wittkop; Nadine Austel
Journal:  Theor Appl Genet       Date:  2022-03-16       Impact factor: 5.699

3.  Using Near-infrared reflectance spectroscopy (NIRS) to predict glucobrassicin concentrations in cabbage and brussels sprout leaf tissue.

Authors:  Ilse E Renner; Vincent A Fritz
Journal:  Plant Methods       Date:  2020-10-12       Impact factor: 4.993

4.  Classification and quantification analysis of peach kernel from different origins with near-infrared diffuse reflection spectroscopy.

Authors:  Wei Liu; Zhen-Zhong Wang; Jian-Ping Qing; Hong-Juan Li; Wei Xiao
Journal:  Pharmacogn Mag       Date:  2014-10       Impact factor: 1.085

5.  Rapid and Cost-Effective Quantification of Glucosinolates and Total Phenolic Content in Rocket Leaves by Visible/Near-Infrared Spectroscopy.

Authors:  Eva María Toledo-Martín; Rafael Font; Sara Obregón-Cano; Antonio De Haro-Bailón; Myriam Villatoro-Pulido; Mercedes Del Río-Celestino
Journal:  Molecules       Date:  2017-05-20       Impact factor: 4.411

6.  Glucosinolates, Ca, Se Contents, and Bioaccessibility in Brassica rapa Vegetables Obtained by Organic and Conventional Cropping Systems.

Authors:  Fernando Cámara-Martos; Sara Obregón-Cano; Antonio de Haro-Bailón
Journal:  Foods       Date:  2022-01-26

7.  The Potential of Hyperspectral Patterns of Winter Wheat to Detect Changes in Soil Microbial Community Composition.

Authors:  Sabrina Carvalho; Wim H van der Putten; W H G Hol
Journal:  Front Plant Sci       Date:  2016-06-09       Impact factor: 5.753

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.