A chemometric evaluation of the underlying physical and chemical patterns that support near infrared spectroscopy of barley seeds as a tool for explorative classification of endosperm genes and gene combinations

Jacobsen, Susanne; Søndergaard, Ib; Møller, Birger Lindberg; Desler, Torben; Munck, L.

doi:10.1016/j.jcs.2005.02.008

Cited by 52 publications

(61 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Near Infrared Reflectance log1/R Multiple Scatter Corrected [46] spectra (1100-2500 nm) were obtained from milled samples of a barley endosperm mutant material [47,48]. The 92 barley samples are grown in greenhouse (n ¼ 69) and in the field (n ¼ 23).…”

Section: Description Of Data Set and Methodsmentioning

confidence: 99%

“…Table I). The PCA and spectra in Figure 1A-D used as an introduction to the data set displays new figures from the previously published material [ [6] p. 39 [47,48]]. The barley samples include replicate formations of 16 normal barleys and 12 mutants-5 very high lysine mutants (the alleles lys3a, lys3b, lys3c, lys3m and lys4d), 6 carbohydrate mutants (the alleles 5f and 5g, mutant 16, mutant 95, mutant 449 and mutant 1201 called w1, earlier misclassified as waxy, high amylopectin) as well as one confirmed waxy mutant w2 (841878).…”

Section: Description Of Data Set and Methodsmentioning

confidence: 99%

“…'Lysimax' and 'Lysiba' are two seed quality and starch improved crossbred cultivars from Carlsberg carrying the high lysine lys3a gene. The samples were analysed [47] The high lysine mutant collection is here used as a tool to test the discrimination capability of NIR spectroscopy [47,48]. A PCA on spectra 1100-2500 nm for the 23 samples in the field material ( Figure 1A) revealed for the first time [47] that there were two kinds of mutants in this material; protein mutants (P; 20-45% increase in lysine, 5-10% decrease in starch) and carbohydrate mutants (C; 5-10% increase in lysine and 10-50% decrease in starch).…”

Section: Description Of Data Set and Methodsmentioning

confidence: 99%

“…In Figure 2, 92 NIR log/R MSC mean centred spectra at 1100-2500 nm are visualised. This data set implies 64.400 spectral data points from the total barley material of 92 samples [47,48] grown in field (n ¼ 23) and in greenhouse (n ¼ 69) extended by six chemical variables (Table I). The spectra are shown in Figure 2A and marked in colour with normal barley spectra (N) in green, protein mutants (P) in blue and carbohydrate C spectra in red.…”

Section: The Latentix Data Programme For Visualisation Of Spectra Andmentioning

confidence: 99%

“…The physicochemical relevance of the finely structured log 1/R MSC spectral fingerprints for mutant identification and genetic/environment classification A PCA cannot correctly classify the genotypes from the two environments in the combined data set [48]. However, this is now possible by the newly developed extended canonical variates analysis (ECVA) developed by Nørgaard et al [53].…”

Section: 24mentioning

confidence: 99%

See 4 more Smart Citations

A new holistic exploratory approach to Systems Biology by Near Infrared Spectroscopy evaluated by chemometrics and data inspection

Munck

2007

Journal of Chemometrics

View full text Add to dashboard Cite

There is a need for an improved biological and theoretical interpretation of Near Infra‐Red Spectral (NIRS) fingerprints from tissues that could contribute with holistic overview to fine‐grained detail modelled in Systems Biology. The concept of gene expression in self‐organised networks was experimentally tested in a barley endosperm model with molecularly defined and undefined mutants. Surprisingly reproducible gene‐specific NIRS fingerprints were observed directly in log1/R MSC pre‐treated spectra that could not be accurately represented by destructive mathematical models. A mutant spectrum in an isogenic background represents the physiochemical expression of the gene in the whole network (tissue). The necessary holistic overview that is needed experimentally to introduce Ilya Prigogine's theory on self‐organisation in Systems Biology was supplied by defining the spectral phenome. Interval spectral information on genotypes and environment was classified by interval Extended Canonical Variates Analysis (iECVA). Genetic changes in spectra were interpreted by interval Partial Least Squares Regression (iPLSR) correlations to chemical variables. A new pathway regulation was detected. The finely grained ‘bottom up’ modelling of molecular and chemical data from pathways requires a coarsely grained exploratory ‘top down’ overview by NIRS to account for the outcome of self‐organisation. The amplification of expression from a gene to the phenome (pleiotropy) can now for the first time be quantified as a whole reproducible phenomenological pattern by NIRS and compared to other gene spectra. It explains published findings that transformed respectively mutated genes in genetically modified organisms (GMOs) and cancer patients can be detected unsupervised from tissues by spectroscopy, chemometrics and data inspection. Copyright © 2007 John Wiley & Sons, Ltd.

show abstract

Section: Description Of Data Set and Methodsmentioning

confidence: 99%

Section: Description Of Data Set and Methodsmentioning

confidence: 99%

Section: Description Of Data Set and Methodsmentioning

confidence: 99%

Section: The Latentix Data Programme For Visualisation Of Spectra Andmentioning

confidence: 99%

Section: 24mentioning

confidence: 99%

See 3 more Smart Citations

A new holistic exploratory approach to Systems Biology by Near Infrared Spectroscopy evaluated by chemometrics and data inspection

Munck

2007

Journal of Chemometrics

View full text Add to dashboard Cite

show abstract

The Analysis of Wheat by Near‐Infrared Spectroscopy

Williams¹

2001

Handbook of Vibrational Spectroscopy

View full text Add to dashboard Cite

Rapid, cheap, non-destructive, chemical free, accurate and reproducible methods are important tools in the selection for ingredients of crops. In case of yellow endosperm pigments the determination of carotenoids and other compounds by HPLC is both time consuming and expensive. Other method such as spectrophotometry after extraction with butanol is laborious and unpleasant due to the extraction time and odour of the solvent, respectively. Near-infrared spectroscopy (NIRS) is widely applied in different food crops for the determination of a broad variation of ingredients, e.g. protein, carotenoids, fatty acids, oils etc. The objective of the study was to establish a NIRS calibration for yellow endosperm pigments of different wheat species. The results indicated that NIRS discriminated satisfactorily between high and low yellow pigment contents of different wheat genotypes and species. The analysis showed that diploid einkorn wheat was clearly separated from tetraploid and hexaploid species. Moreover, durum varieties were also clearly separated from other tetraploid species/subspecies. It is concluded that NIRS is a valuable selection method to separate a large amount of genotypes in low and high yellow pigment types which subsequently can be analysed by other methods for an exact determination of quantity and quality of endosperm pigments.

show abstract

Adapting Cereal Plants and Human Society to a Changing Climate and Economy Merged by the Concept of Self‐Organization

Munck

Jespersen

2010

Barley

View full text Add to dashboard Cite

A chemometric evaluation of the underlying physical and chemical patterns that support near infrared spectroscopy of barley seeds as a tool for explorative classification of endosperm genes and gene combinations

Cited by 52 publications

References 26 publications

A new holistic exploratory approach to Systems Biology by Near Infrared Spectroscopy evaluated by chemometrics and data inspection

A new holistic exploratory approach to Systems Biology by Near Infrared Spectroscopy evaluated by chemometrics and data inspection

The Analysis of Wheat by Near‐Infrared Spectroscopy

Adapting Cereal Plants and Human Society to a Changing Climate and Economy Merged by the Concept of Self‐Organization

Contact Info

Product

Resources

About