Phenotypic characterization of sweet potato Ipomoea batatas (L.) Lam. genotypes in relation to prediction of chemical quality constituents by NIRS equations
This study evaluates the potential of NIRS (near-infrared reflectance spectroscopy) to predict the major constituents (starch, sugars, cellulose, proteins and minerals) of the sweet potato root. Overall, 240 accessions were morphologically described, chemically analysed and their NIR spectra recorded. No correlations were observed between aerial and underground traits, and between morphological traits and major constituents. Calibration equations, developed on 190 accessions, showed high explained variances in cross-validation (r2cv) for starch (0.82), sugars (0.91), proteins (0.89) and minerals (0.74) but no response for cellulose (0.21). The predictions were tested on an independent set of 50 randomly selected accessions. The r2pred values for starch, sugars and proteins were, respectively, of 0.71, 0.82 and 0.87 with ratios of performance to deviation (RPD) of 2.11, 2.29 and 2.93. New calibration equations developed on 240 accessions showed improved RPD values for starch (2.65), sugars (2.75), cellulose (1.58), proteins (3.47) and minerals (2.34), indicating that larger sets could improve prediction. NIRS could be used in sweet potato breeding programmes to predict starch, sugars and proteins contents in the roots.
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dig-cirad-fr-5600052024-01-28T19:12:35Z http://agritrop.cirad.fr/560005/ http://agritrop.cirad.fr/560005/ Phenotypic characterization of sweet potato Ipomoea batatas (L.) Lam. genotypes in relation to prediction of chemical quality constituents by NIRS equations. Lebot Vincent, Ndiaye André, Malapa Roger. 2011. Plant Breeding, 130 (2) : 457-463.https://doi.org/10.1111/j.1439-0523.2010.01840.x <https://doi.org/10.1111/j.1439-0523.2010.01840.x> Phenotypic characterization of sweet potato Ipomoea batatas (L.) Lam. genotypes in relation to prediction of chemical quality constituents by NIRS equations Lebot, Vincent Ndiaye, André Malapa, Roger eng 2011 Plant Breeding F30 - Génétique et amélioration des plantes Q04 - Composition des produits alimentaires U30 - Méthodes de recherche F60 - Physiologie et biochimie végétale F50 - Anatomie et morphologie des plantes Ipomoea batatas igname qualité composition chimique génotype technique de prévision spectroscopie infrarouge teneur en glucides teneur en éléments minéraux teneur en protéines amidon cellulose partie souterraine partie aérienne légume racine phénotype morphologie végétale http://aims.fao.org/aos/agrovoc/c_3937 http://aims.fao.org/aos/agrovoc/c_8478 http://aims.fao.org/aos/agrovoc/c_6400 http://aims.fao.org/aos/agrovoc/c_1794 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_3041 http://aims.fao.org/aos/agrovoc/c_28568 http://aims.fao.org/aos/agrovoc/c_1298 http://aims.fao.org/aos/agrovoc/c_4848 http://aims.fao.org/aos/agrovoc/c_6251 http://aims.fao.org/aos/agrovoc/c_7369 http://aims.fao.org/aos/agrovoc/c_1423 http://aims.fao.org/aos/agrovoc/c_32357 http://aims.fao.org/aos/agrovoc/c_32353 http://aims.fao.org/aos/agrovoc/c_6647 http://aims.fao.org/aos/agrovoc/c_5776 http://aims.fao.org/aos/agrovoc/c_13434 Vanuatu http://aims.fao.org/aos/agrovoc/c_5159 This study evaluates the potential of NIRS (near-infrared reflectance spectroscopy) to predict the major constituents (starch, sugars, cellulose, proteins and minerals) of the sweet potato root. Overall, 240 accessions were morphologically described, chemically analysed and their NIR spectra recorded. No correlations were observed between aerial and underground traits, and between morphological traits and major constituents. Calibration equations, developed on 190 accessions, showed high explained variances in cross-validation (r2cv) for starch (0.82), sugars (0.91), proteins (0.89) and minerals (0.74) but no response for cellulose (0.21). The predictions were tested on an independent set of 50 randomly selected accessions. The r2pred values for starch, sugars and proteins were, respectively, of 0.71, 0.82 and 0.87 with ratios of performance to deviation (RPD) of 2.11, 2.29 and 2.93. New calibration equations developed on 240 accessions showed improved RPD values for starch (2.65), sugars (2.75), cellulose (1.58), proteins (3.47) and minerals (2.34), indicating that larger sets could improve prediction. NIRS could be used in sweet potato breeding programmes to predict starch, sugars and proteins contents in the roots. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/560005/1/document_560005.pdf application/pdf Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1111/j.1439-0523.2010.01840.x 10.1111/j.1439-0523.2010.01840.x info:eu-repo/semantics/altIdentifier/doi/10.1111/j.1439-0523.2010.01840.x info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1111/j.1439-0523.2010.01840.x |
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Europa del Oeste |
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F30 - Génétique et amélioration des plantes Q04 - Composition des produits alimentaires U30 - Méthodes de recherche F60 - Physiologie et biochimie végétale F50 - Anatomie et morphologie des plantes Ipomoea batatas igname qualité composition chimique génotype technique de prévision spectroscopie infrarouge teneur en glucides teneur en éléments minéraux teneur en protéines amidon cellulose partie souterraine partie aérienne légume racine phénotype morphologie végétale http://aims.fao.org/aos/agrovoc/c_3937 http://aims.fao.org/aos/agrovoc/c_8478 http://aims.fao.org/aos/agrovoc/c_6400 http://aims.fao.org/aos/agrovoc/c_1794 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_3041 http://aims.fao.org/aos/agrovoc/c_28568 http://aims.fao.org/aos/agrovoc/c_1298 http://aims.fao.org/aos/agrovoc/c_4848 http://aims.fao.org/aos/agrovoc/c_6251 http://aims.fao.org/aos/agrovoc/c_7369 http://aims.fao.org/aos/agrovoc/c_1423 http://aims.fao.org/aos/agrovoc/c_32357 http://aims.fao.org/aos/agrovoc/c_32353 http://aims.fao.org/aos/agrovoc/c_6647 http://aims.fao.org/aos/agrovoc/c_5776 http://aims.fao.org/aos/agrovoc/c_13434 http://aims.fao.org/aos/agrovoc/c_5159 F30 - Génétique et amélioration des plantes Q04 - Composition des produits alimentaires U30 - Méthodes de recherche F60 - Physiologie et biochimie végétale F50 - Anatomie et morphologie des plantes Ipomoea batatas igname qualité composition chimique génotype technique de prévision spectroscopie infrarouge teneur en glucides teneur en éléments minéraux teneur en protéines amidon cellulose partie souterraine partie aérienne légume racine phénotype morphologie végétale http://aims.fao.org/aos/agrovoc/c_3937 http://aims.fao.org/aos/agrovoc/c_8478 http://aims.fao.org/aos/agrovoc/c_6400 http://aims.fao.org/aos/agrovoc/c_1794 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_3041 http://aims.fao.org/aos/agrovoc/c_28568 http://aims.fao.org/aos/agrovoc/c_1298 http://aims.fao.org/aos/agrovoc/c_4848 http://aims.fao.org/aos/agrovoc/c_6251 http://aims.fao.org/aos/agrovoc/c_7369 http://aims.fao.org/aos/agrovoc/c_1423 http://aims.fao.org/aos/agrovoc/c_32357 http://aims.fao.org/aos/agrovoc/c_32353 http://aims.fao.org/aos/agrovoc/c_6647 http://aims.fao.org/aos/agrovoc/c_5776 http://aims.fao.org/aos/agrovoc/c_13434 http://aims.fao.org/aos/agrovoc/c_5159 |
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F30 - Génétique et amélioration des plantes Q04 - Composition des produits alimentaires U30 - Méthodes de recherche F60 - Physiologie et biochimie végétale F50 - Anatomie et morphologie des plantes Ipomoea batatas igname qualité composition chimique génotype technique de prévision spectroscopie infrarouge teneur en glucides teneur en éléments minéraux teneur en protéines amidon cellulose partie souterraine partie aérienne légume racine phénotype morphologie végétale http://aims.fao.org/aos/agrovoc/c_3937 http://aims.fao.org/aos/agrovoc/c_8478 http://aims.fao.org/aos/agrovoc/c_6400 http://aims.fao.org/aos/agrovoc/c_1794 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_3041 http://aims.fao.org/aos/agrovoc/c_28568 http://aims.fao.org/aos/agrovoc/c_1298 http://aims.fao.org/aos/agrovoc/c_4848 http://aims.fao.org/aos/agrovoc/c_6251 http://aims.fao.org/aos/agrovoc/c_7369 http://aims.fao.org/aos/agrovoc/c_1423 http://aims.fao.org/aos/agrovoc/c_32357 http://aims.fao.org/aos/agrovoc/c_32353 http://aims.fao.org/aos/agrovoc/c_6647 http://aims.fao.org/aos/agrovoc/c_5776 http://aims.fao.org/aos/agrovoc/c_13434 http://aims.fao.org/aos/agrovoc/c_5159 F30 - Génétique et amélioration des plantes Q04 - Composition des produits alimentaires U30 - Méthodes de recherche F60 - Physiologie et biochimie végétale F50 - Anatomie et morphologie des plantes Ipomoea batatas igname qualité composition chimique génotype technique de prévision spectroscopie infrarouge teneur en glucides teneur en éléments minéraux teneur en protéines amidon cellulose partie souterraine partie aérienne légume racine phénotype morphologie végétale http://aims.fao.org/aos/agrovoc/c_3937 http://aims.fao.org/aos/agrovoc/c_8478 http://aims.fao.org/aos/agrovoc/c_6400 http://aims.fao.org/aos/agrovoc/c_1794 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_3041 http://aims.fao.org/aos/agrovoc/c_28568 http://aims.fao.org/aos/agrovoc/c_1298 http://aims.fao.org/aos/agrovoc/c_4848 http://aims.fao.org/aos/agrovoc/c_6251 http://aims.fao.org/aos/agrovoc/c_7369 http://aims.fao.org/aos/agrovoc/c_1423 http://aims.fao.org/aos/agrovoc/c_32357 http://aims.fao.org/aos/agrovoc/c_32353 http://aims.fao.org/aos/agrovoc/c_6647 http://aims.fao.org/aos/agrovoc/c_5776 http://aims.fao.org/aos/agrovoc/c_13434 http://aims.fao.org/aos/agrovoc/c_5159 Lebot, Vincent Ndiaye, André Malapa, Roger Phenotypic characterization of sweet potato Ipomoea batatas (L.) Lam. genotypes in relation to prediction of chemical quality constituents by NIRS equations |
description |
This study evaluates the potential of NIRS (near-infrared reflectance spectroscopy) to predict the major constituents (starch, sugars, cellulose, proteins and minerals) of the sweet potato root. Overall, 240 accessions were morphologically described, chemically analysed and their NIR spectra recorded. No correlations were observed between aerial and underground traits, and between morphological traits and major constituents. Calibration equations, developed on 190 accessions, showed high explained variances in cross-validation (r2cv) for starch (0.82), sugars (0.91), proteins (0.89) and minerals (0.74) but no response for cellulose (0.21). The predictions were tested on an independent set of 50 randomly selected accessions. The r2pred values for starch, sugars and proteins were, respectively, of 0.71, 0.82 and 0.87 with ratios of performance to deviation (RPD) of 2.11, 2.29 and 2.93. New calibration equations developed on 240 accessions showed improved RPD values for starch (2.65), sugars (2.75), cellulose (1.58), proteins (3.47) and minerals (2.34), indicating that larger sets could improve prediction. NIRS could be used in sweet potato breeding programmes to predict starch, sugars and proteins contents in the roots. |
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article |
topic_facet |
F30 - Génétique et amélioration des plantes Q04 - Composition des produits alimentaires U30 - Méthodes de recherche F60 - Physiologie et biochimie végétale F50 - Anatomie et morphologie des plantes Ipomoea batatas igname qualité composition chimique génotype technique de prévision spectroscopie infrarouge teneur en glucides teneur en éléments minéraux teneur en protéines amidon cellulose partie souterraine partie aérienne légume racine phénotype morphologie végétale http://aims.fao.org/aos/agrovoc/c_3937 http://aims.fao.org/aos/agrovoc/c_8478 http://aims.fao.org/aos/agrovoc/c_6400 http://aims.fao.org/aos/agrovoc/c_1794 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_3041 http://aims.fao.org/aos/agrovoc/c_28568 http://aims.fao.org/aos/agrovoc/c_1298 http://aims.fao.org/aos/agrovoc/c_4848 http://aims.fao.org/aos/agrovoc/c_6251 http://aims.fao.org/aos/agrovoc/c_7369 http://aims.fao.org/aos/agrovoc/c_1423 http://aims.fao.org/aos/agrovoc/c_32357 http://aims.fao.org/aos/agrovoc/c_32353 http://aims.fao.org/aos/agrovoc/c_6647 http://aims.fao.org/aos/agrovoc/c_5776 http://aims.fao.org/aos/agrovoc/c_13434 http://aims.fao.org/aos/agrovoc/c_5159 |
author |
Lebot, Vincent Ndiaye, André Malapa, Roger |
author_facet |
Lebot, Vincent Ndiaye, André Malapa, Roger |
author_sort |
Lebot, Vincent |
title |
Phenotypic characterization of sweet potato Ipomoea batatas (L.) Lam. genotypes in relation to prediction of chemical quality constituents by NIRS equations |
title_short |
Phenotypic characterization of sweet potato Ipomoea batatas (L.) Lam. genotypes in relation to prediction of chemical quality constituents by NIRS equations |
title_full |
Phenotypic characterization of sweet potato Ipomoea batatas (L.) Lam. genotypes in relation to prediction of chemical quality constituents by NIRS equations |
title_fullStr |
Phenotypic characterization of sweet potato Ipomoea batatas (L.) Lam. genotypes in relation to prediction of chemical quality constituents by NIRS equations |
title_full_unstemmed |
Phenotypic characterization of sweet potato Ipomoea batatas (L.) Lam. genotypes in relation to prediction of chemical quality constituents by NIRS equations |
title_sort |
phenotypic characterization of sweet potato ipomoea batatas (l.) lam. genotypes in relation to prediction of chemical quality constituents by nirs equations |
url |
http://agritrop.cirad.fr/560005/ http://agritrop.cirad.fr/560005/1/document_560005.pdf |
work_keys_str_mv |
AT lebotvincent phenotypiccharacterizationofsweetpotatoipomoeabatatasllamgenotypesinrelationtopredictionofchemicalqualityconstituentsbynirsequations AT ndiayeandre phenotypiccharacterizationofsweetpotatoipomoeabatatasllamgenotypesinrelationtopredictionofchemicalqualityconstituentsbynirsequations AT malaparoger phenotypiccharacterizationofsweetpotatoipomoeabatatasllamgenotypesinrelationtopredictionofchemicalqualityconstituentsbynirsequations |
_version_ |
1792497818353532928 |