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Application of near infrared reflectance spectroscopy for the evaluation of yam ( Dioscorea alata ) germplasm and breeding lines
Author(s) -
Lebot Vincent,
Malapa Roger
Publication year - 2013
Publication title -
journal of the science of food and agriculture
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.782
H-Index - 142
eISSN - 1097-0010
pISSN - 0022-5142
DOI - 10.1002/jsfa.6002
Subject(s) - germplasm , amylose , starch , dioscorea , near infrared reflectance spectroscopy , chemistry , food science , horticulture , botany , near infrared spectroscopy , biology , medicine , alternative medicine , pathology , neuroscience
BACKGROUND Thousands of yam ( Dioscorea spp.) accessions are maintained in germplasm collections. The physico‐chemical characteristics of the tubers are rarely characterised. Unless a simple, low cost, screening tool is available, it is difficult to evaluate the quality of varieties and breeding lines. We investigated the potential of near infrared reflectance spectroscopy ( NIRS ) as an alternative method for predicting the major constituents of the yam tuber.RESULTS Two hundred and sixty‐five accessions, belonging to seven different Dioscorea spp., were analysed for starch, amylose, sugars, proteins, minerals and cellulose. The comparison of the NIR spectra and the chemical values allowed the establishment of equations of calibration for the prediction of starch, sugars and proteins (equivalent N). The r 2 pred values for starch, sugars and proteins (respectively 0.84, 0.86 and 0.88) are high enough to allow good estimates of their contents. Values for the ratio of performance to deviation ( RPD ) of 4.046 and 3.641 for the sugars and proteins models also allow good quantitative predictions to be made. Amylose, cellulose and minerals could not be predicted precisely. A second calibration conducted by adding the calibration and validation sets (260 accessions) revealed an improvement of the RPD values for starch, sugars and proteins, indicating that the models can be improved. Discriminant analysis conducted using 2151 wavelengths (in nanometres) as variables was applied to a set of 214 accessions of D. alata and the results were compared to the principal component analysis of chemical data. Accessions can be classified according to the amylaceous fraction of the chemotype.CONCLUSION NIRS could be used in yam breeding programmes to characterise rapidly and at low cost the numerous accessions and breeding lines. © 2012 Society of Chemical Industry