Literature DB >> 18971953

Stability across environments of the coffee variety near infrared spectral signature.

H Posada1, M Ferrand, F Davrieux, P Lashermes, B Bertrand.   

Abstract

Previous study on food plants has shown that near infrared (NIR) spectral methods seem effective for authenticating coffee varieties. We confirm that result, but also show that inter-variety differences are not stable from one harvest to the next. We put forward the hypothesis that the spectral signature is affected by environmental factors. The purpose of this study was to find a way of reducing this environmental variance to increase the method's reliability and to enable practical application in breeding. Spectral collections were obtained from ground green coffee samples from multilocation trials. Two harvests of bean samples from 11 homozygous introgressed lines, and the cv 'Caturra' as the control, supplied from three different sites, were compared. For each site, squared Euclidean distances among the 12 varieties were estimated from the NIR spectra. Matrix correlation coefficients were assessed by the Mantel test. We obtained very good stability (high correlations) for inter-variety differences across the sites when using the two harvests data. If only the most heritable zones of the spectrum were used, there was a marked improvement in the efficiency of the method. This improvement was achieved by treating the spectrum as succession of phenotypic variables, each resulting from an environmental and genetic effect. Heritabilities were calculated with confidence intervals. A near infrared spectroscopy signature, acquired over a set of harvests, can therefore effectively characterize a coffee variety. We indicated how this typical signature can be used in breeding to assist in selection.

Mesh:

Year:  2008        PMID: 18971953     DOI: 10.1038/hdy.2008.88

Source DB:  PubMed          Journal:  Heredity (Edinb)        ISSN: 0018-067X            Impact factor:   3.821


  4 in total

1.  Phenomic selection in wheat breeding: identification and optimisation of factors influencing prediction accuracy and comparison to genomic selection.

Authors:  Pauline Robert; Jérôme Auzanneau; Ellen Goudemand; François-Xavier Oury; Bernard Rolland; Emmanuel Heumez; Sophie Bouchet; Jacques Le Gouis; Renaud Rincent
Journal:  Theor Appl Genet       Date:  2022-01-06       Impact factor: 5.699

2.  The Optical Response of a Mediterranean Shrubland to Climate Change: Hyperspectral Reflectance Measurements during Spring.

Authors:  Jean-Philippe Mevy; Charlotte Biryol; Marine Boiteau-Barral; Franco Miglietta
Journal:  Plants (Basel)       Date:  2022-02-12

3.  Stabilization Effects Induced by Trehalose on Creatine Aqueous Solutions Investigated by Infrared Spectroscopy.

Authors:  Maria Teresa Caccamo; Salvatore Magazù
Journal:  Molecules       Date:  2022-09-24       Impact factor: 4.927

4.  Phenomic Selection Is a Low-Cost and High-Throughput Method Based on Indirect Predictions: Proof of Concept on Wheat and Poplar.

Authors:  Renaud Rincent; Jean-Paul Charpentier; Patricia Faivre-Rampant; Etienne Paux; Jacques Le Gouis; Catherine Bastien; Vincent Segura
Journal:  G3 (Bethesda)       Date:  2018-12-10       Impact factor: 3.154

  4 in total

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