Literature DB >> 21842198

Characterisation of non-viable whole barley, wheat and sorghum grains using near-infrared hyperspectral data and chemometrics.

Cushla M McGoverin1, Paulina Engelbrecht, Paul Geladi, Marena Manley.   

Abstract

Undesired germination of cereal grains diminishes process utility and economic return. Pre-germination, the term used to describe untimely germination, leads to reduced viability of a grain sample. Accurate and rapid identification of non-viable grain is necessary to reduce losses associated with pre-germination. Viability of barley, wheat and sorghum grains was investigated with near-infrared hyperspectral imaging. Principal component analyses applied to cleaned hyperspectral images were able to differentiate between viable and non-viable classes in principal component (PC) five for barley and sorghum and in PC6 for wheat. An OH stretching and deformation combination mode (1,920-1,940 nm) featured in the loading line plots of these PCs; this water-based vibrational mode was a major contributor to the viable/non-viable differentiation. Viable and non-viable classes for partial least squares-discriminant analysis (PLS-DA) were assigned from PC scores that correlated with incubation time. The PLS-DA predictions of the viable proportion correlated well with the viable proportion observed using the tetrazolium test. Partial least squares regression analysis could not be used as a source of contrast in the hyperspectral images due to sampling issues. © Springer-Verlag 2011

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Year:  2011        PMID: 21842198     DOI: 10.1007/s00216-011-5291-x

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  4 in total

1.  Determination of Seed Soundness in Conifers Cryptomeria japonica and Chamaecyparis obtusa Using Narrow-Multiband Spectral Imaging in the Short-Wavelength Infrared Range.

Authors:  Osamu Matsuda; Masashi Hara; Hiroyuki Tobita; Kenichi Yazaki; Toshinori Nakagawa; Kuniyoshi Shimizu; Akira Uemura; Hajime Utsugi
Journal:  PLoS One       Date:  2015-06-17       Impact factor: 3.240

Review 2.  Hyperspectral imaging for seed quality and safety inspection: a review.

Authors:  Lei Feng; Susu Zhu; Fei Liu; Yong He; Yidan Bao; Chu Zhang
Journal:  Plant Methods       Date:  2019-08-08       Impact factor: 4.993

3.  Non-destructive classification and prediction of aflatoxin-B1 concentration in maize kernels using Vis-NIR (400-1000 nm) hyperspectral imaging.

Authors:  Subir Kumar Chakraborty; Naveen Kumar Mahanti; Shekh Mukhtar Mansuri; Manoj Kumar Tripathi; Nachiket Kotwaliwale; Digvir Singh Jayas
Journal:  J Food Sci Technol       Date:  2020-06-06       Impact factor: 2.701

4.  Near-infrared (NIR) hyperspectral imaging and multivariate image analysis to study growth characteristics and differences between species and strains of members of the genus Fusarium.

Authors:  Paul J Williams; Paul Geladi; Trevor J Britz; Marena Manley
Journal:  Anal Bioanal Chem       Date:  2012-08-18       Impact factor: 4.142

  4 in total

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