Exploration du potentiel de l’imagerie hyperspectrale proche infrarouge et de la chimiométrie pour discriminer la banque de graines du sol de deux espèces de bois d’Afrique centrale : Erythrophleum suaveolens (Guill. & Perr.) Brenan et Erythrophleum ivorense A. Chev.
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DOI :
https://doi.org/10.19182/bft2024.360.a37138Mots-clés
banque de graines, espèces de bois, imagerie hyperspectrale proche infrarouge, chimiométrie, identification, discrimination.Résumé
Les semences contenues dans le stock semencier du sol peuvent être trop petites pour être quantifiées visuellement. Les essences concernées sont généralement identifiées lors d’essais de germination en pépinière, ce qui prend du temps. Cette étude examine une nouvelle approche basée sur l'imagerie hyperspectrale dans le proche infrarouge (PIR) couplée à des outils chimiométriques. Elle se concentre sur le stock semencier du sol des forêts humides africaines, qui est encore méconnu. Nous avons utilisé quatre-vingt-trois semences de deux espèces sœurs, Erythrophleum suaveolens (Guill. & Perr.) Brenan et Erythrophleum ivorense A.Chev., collectées dans le sol forestier (profondeur entre 0 et 10 cm) au Gabon, au Cameroun et au Congo. À l’aide d'analyses en composantes principales et d’analyses discriminantes par moindres carrés partiels, nous avons étudié la capacité de l'imagerie hyperspectrale dans le proche infrarouge à identifier les semences des deux espèces. La méthode est rapide, non-destructive et offre de nouvelles perspectives pour l'étude des stocks semenciers des sols forestiers.
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Références
Aubréville A., 1970. Légumineuses-Césalpinioidés (Leguminosae-Caesalpinioideae). Flore du Cameroun. Volume 9. Muséum National d’histoire Naturelle, Paris, France, 339 p.
Biancarosa I., Espe M., Bruckner C. G., Heesch S., Liland N., Waagbo R., et al., 2017. Amino acid composition, protein content, and nitrogen-to-protein conversion factors of 21seaweed species from Norwegian waters. Journal of Applied Phycology, 29: 1001-1009.
https://doi.org/10.1007/s10811-016-0984-3
Ben-Dor E., Banin A., 1995. Near infrared analysis as a rapid method to simultaneously evaluate several soil properties. Soil Science Society of America Journal, 59: 364-372. https://doi.org/10.2136/sssaj1995.03615995005900020014x
Caporaso N., Whitworth M. B., Fisk I. D., 2018. Near-Infrared spectroscopy and hyperspectral imaging for non-destructive quality assessment of cereal grains. Applied Spectroscopy Reviews, 1-21. https://doi.org/10.1080/05704928.2018.1425214
Cui Y., Xu L., An D., Liu Z., Gu J., Li S., et al., 2018. Identification of maize seed varieties based on near infrared reflectance spectroscopy and chemometrics. International Journal of Agricultural and Biological Engineering, 11: 177-183. https://doi.org/10.25165/j.ijabe.20181102.2815
Daïnou K., Bauduin A., Bourland N., Gillet J. F., Fétéké F., Doucet J.-L., 2011. Soil seed bank characteristics in Cameroonian rainforests and implications for post-logging forest recovery. Ecological Engineering, 37: 1499-1506. https://doi.org/10.1016/j.ecoleng.2011.05.004
Dale L. M., Thewis A., Boudry C., Rotar I., Dardenne P., Baeten V, et al., 2013. Hyperspectral imaging applications in agriculture and agrofood product quality and safety control: a review. Applied Spectroscopy Reviews, 48: 142-159. https://doi.org/10.1080/05704928.2012.705800
Dale L. M., Thewis A., Rotar I., Fernández Piema J. A., Boudry C., Vidican R. M., et al., 2012. Chemometric tools for NIRS and NIR hyperspectral imaging. Bulletin of Usavm Cluj Napoca Agriculture, 69: 70-76. http://hdl.handle.net/2268/132855
D'Erfurth I., Le Signor C., Aubert G., Sanchez M., Vernoud V., Darchy B., et al., 2012. A role for an endosperm-localized subtilase in the control of seed size in legumes. New Phytologist, 196: 738-751. https://doi.org/10.1111/j.1469-8137.2012.04296.x
Douh C., Daïnou K., Loumeto J. J., Moutsambote J.-M., Fayolle A., Tosso F, et al., 2018a. Soil seed bank characteristics in two central African forest types and implications for forest restoration. Forest Ecology and Management, 409: 766-776. https://doi.org/10.1016/j.foreco.2017.12.012
Douh C., Gorel A. P., Daïnou K., Fonteyn D., Bustillo E., Obsomer L, et al., 2018b. Banque de graines du sol et déterminants de la germination du tali, Erythrophleum suaveolens (Guill. & Perr.) Brenan. Bois et Forêts des Tropiques, 338 : 43-55. https://doi.org/10.19182/bft2018.338.a31681
Douh C., Mabengo B. C., Nzila J. D., Malonga Mbouchi L., Nsongola G., Loumeto J. J., et al., 2023. Soil Seed Bank Characteristics in Congolese Rainforests and Implications for Post-Logging Plots Reforestation. Open Journal of Forestry, 13: 294-314. https://doi.org/10.4236/ojf.2023.133018
Dumas C., Rogowsky P., 2008. Fertilization and early seed formation. , Académie des Sciences Institut de France, Comptes Rendus Biologies, 331: 715-725. https://doi.org/10.1016/j.crvi.2008.07.013
Duminil J., Daïnou K., Kombi Kaviriri D., Gillet P., Loo J., Doucet J.-L., et al., 2016. Relationships between population density, fine-scale genetic structure, mating system and pollen dispersal in a timber tree from African rainforests. Heredity (Edinb), 116: 295-303. https://doi.org/10.1038/hdy.2015.101
Duminil J., Heuertz M., Doucet J.-L., Bourland N., Cruaud C., Gavory F, et al., 2010. CpDNA-based species identification and phylogeography: application to African tropical tree species. Molecular Ecology, 19: 5469-5483. https://doi.org/10.1111/j.1365-294X.2010.04917.x
Eylenbosch D., Bodson B., Baeten V., Fernández Pierna J. A., 2017. NIR hyperspectral imaging spectroscopy and chemometrics for the discrimination of roots and crop residues extracted from soil samples. Journal of Chemometrics, 32: e2982. https://doi.org/10.1002/cem.2982
Fernández Pierna J. A., Vermeulen P., Amand O., Tossens A., Dardenne P., Baeten V., 2012. NIR Hyperspectral Imaging spectroscopy and chemometrics for the detection of undesirable substances in food and feed. Chemometrics and intelligent laboratory systems, 117: 233-239. https://doi.org/10.1016/j.chemolab.2012.02.004
Fernández Pierna J. A., Vermeulen P., Stilmant D., Dupuis B., Dardenne P., Baeten V., 2010. Characterisation of fonio millet by near infrared hyperspectral imaging, Proceedings of the 14th International Conference on Near Infrared Spectroscopy (ICNIRS): Breaking the Dawn. Bangkok, Thailand, 997-1002.
Fernández Pierna J. A., Baeten V., Dardenne P., Dubois J., Lewis E. N., Burger J., 2009. Spectroscopic Imaging. In: Comprehensive Chemometrics – 1st Edition. Brown S., Tauler R., Walczak B. (eds). Elsevier, 4: 173-196. https://doi.org/10.1016/B978-044452701-1.00004-1
Fernández Pierna J. A., Baeten V., Dardenne P., 2006. Screening of compound feeds using NIR hyperspectral data. Chemometrics and intelligent laboratory systems, 84: 114-118. https://doi.org/10.1016/j.chemolab.2006.03.012
Fernández Pierna J. A., Baeten V., Michotte Renier A., Cogdill R. P., Dardenne P., 2004. Combination of support vector machines (SVM) and near-infrared (NIR) imaging spectroscopy for the detection of meat and bone meal (MBM) in compound feeds. Journal of Chemometrics, 18: 341-349. https://doi.org/10.1002/cem.877
Freycon V., 2014. Caractérisation des sols de Loundoungou et de Mokabi (Congo). Rapport de mission DynAfFor, 2 au 24 avril 2014. CIRAD, Montpelier. https://agritrop.cirad.fr/573670/
Gorel A. P., Fayolle A., Doucet J. -L., 2015. Écologie et gestion des espèces multi-usages du genre Erythrophleum (Fabaceae-Caesapinioideae) en Afrique (synthèse bibliographique). Biotechnologie, Agronomie, Société et Environnement, 19 : 415-429. https://popups.uliege.be/1780-4507/index.php?id=12455
Hacisalihoglu G., Larbi B., Settles A., 2010. Near-Infrared reflectance spectroscopy predicts protein, starch, and seed weight in intact seeds of Common Bean (Phaseolus vulgaris L.). Journal of Agricultural and Food Chemistry, 58: 702-706. https://doi.org/10.1021/jf9019294
Hille Ris Lambers J., Clark J. S., Lavine M., 2005. Implications of seed banking for recruitment of southern Appalachian woody species. Ecology, 86: 85-95. https://doi.org/10.1890/03-0685
Janné K., Pettersen J., Lindberg N. O., Lundstedt T., 2001. Hierarchical principal component analysis (PCA) and projection to latent structure (PLS) technique on spectroscopic data as a data pre-treatment for calibration. Journal of Chemometrics, 15: 203-213. https://doi.org/10.1002/cem.677
Kjeldahl J., 1883. Neue Methode zur Bestimmung des Stickstoffs in organischen Körpern. Zeitschrift fur Anal Chemie, 22: 366-382. https://doi.org/10.1007/BF01338151
Legendre P., Gallagher E. D., 2001. Ecologically meaningful transformations for ordination of species data. Oecologia, 129: 271-280. https://doi.org/10.1007/s004420100716
Lipoma M. L., Funes G., Díaz S., 2018. Fire effects on the soil seed bank and post‐fire resilience of a semi‐arid shrubland in central Argentina. Austral Ecology, 43: 46-55. https://doi.org/10.1111/aec.12533
Martins A. M., Engel V. L., 2007. Soil seed banks in tropical forest fragments with different disturbance histories in south-eastern Brazil. Ecological Engineering, 31: 165-174. https://doi.org/10.1016/j.ecoleng.2007.05.008
Massart D. L., Vandeginste B. G. M., Buydens L. M. C., De Jong S., Lewi P. J., Smeyers-Verbeke J., 1998. Handbook of chemometrics and qualimetrics, Part A. NIR Publications, West Sussex, United Kingdom, 867 p. https://www.sciencedirect.com/bookseries/data-handling-in-science-and-technology/vol/20/part/PA
McGoverin C. M., Engelbrecht P., Geladi P., Manley M., 2011. Characterisation of nonviable whole barley, wheat and sorghum grains using near-infrared hyperspectral data and chemometrics. Analytical Bioanalytical. Chemistry, 401: 2283-2289. https://doi.org/10.1007/s00216-011-5291-x
Mæhre H. K., Dalheim L., Edvinsen G. K., Elvevoll E. O., Jensen I. -J., 2018. Protein determination-method matters. Foods, 7: 5. https://doi.org/10.3390/foods7010005
Naganathan G. K., Grimes L. M., Subbiah J., Calkins C. R., Samal A., Meyer G. E., 2008. Visible/near-infrared hyperspectral imaging for beef tenderness prediction. Computers and Electronics in Agriculture, 64: 225-233. https://doi.org/10.1016/j.compag.2008.05.020
Noguero M., Le Signor C., Verdier J., Aubert G., Udvardi M. K., Buitink J., et al., 2011. Rôle de l'albumen dans le développement de la graine chez les légumineuses. In : Graine 2011 (p. S4). Colloque national du Réseau français de Biologie des Graines, Nantes, France, 27-28 octobre 2011. https://prodinra.inra.fr/record/48575
Odum E. P., 1969. The strategy of ecosystem development. Science, 164: 262-270.
Padonou E. A., Akakpo B. A., Tchigossou B., Djossa B., 2022. Methods of soil seed bank estimation: a literature review proposing further work in Africa. iForest, 15: 121-127. https://doi.org/10.3832/ifor3850-015
Phuangsombut K., Ma T., Inagaki T., Tsuchikawa S., Terdwongworakul A., 2018. Near-infrared hyperspectral imaging for classification of mung bean seeds. International Journal of Food Properties, 21: 799-807. https://doi.org/10.1080/10942912.2018.1476378
Plaza-Bonilla D., Álvaro-Fuentes J., Hansen N. C., Lampurlanés J., Cantero-Martínez C., 2014. Winter cereal root growth and aboveground-belowground biomass ratios as affected by site and tillage system in dryland Mediterranean conditions. Plant and soil, 374: 925-939. https://doi.org/10.1007/s11104-013-1926-3
Plue J., Verheyen K., Calster H. V., Marage D., Thompson K., Kalamees R., et al., 2010. Seed banks of temperate deciduous forests during secondary succession. Journal of Vegetation Science, 21: 965-978. https://doi.org/10.1111/j.1654-1103.2010.01203.x
Reeve A. S., Siegel D., Glaser P. H., 1996. Geochemical controls on peatland pore water from the Hudson Bay lowland: a multivariate statistical approach. Journal of Hydrology, 181: 285-304. https://doi.org/10.1016/0022-1694(95)02900-1
Roberts H. A., 1981. Seed banks in soils. In: Advances in Applied Biology. Coaker T. H. (ed.). Academic Press, 6: 1-55.
Roggo Y., Edmond A., Chalus P., Ulmschneider M., 2005. Infrared Hyperspectral Imaging for qualitative analysis of pharmaceutical solid forms. Analytica Chimica Acta, 535: 79-87. https://doi.org/10.1016/j.aca.2004.12.037
Sadaiah K., Veronica N., Nagendra V., Niharika G., Neeraja C. N., Surekha K, et al., 2018. Methods of Protein Estimation and the Influence of Heat Stress on Rice Grain Protein. International Journal of Pure & Applied Bioscience, 6: 159-168. http://doi.org/10.18782/2320-7051.5733
Segalen P., 1967. Les sols et la géomorphologie du Cameroun. Cahier de l’ORSTOM, Série Pédologie, 5 (2) : 137-188.
Shahin M. A., Symons S. J., Hatcher D. W., 2014. Quantification of Mildew Damage in Soft Red Winter Wheat Based on Spectral Characteristics of Bulk Samples: A Comparison of Visible-Near-Infrared Imaging and Near-Infrared Spectroscopy. Food and Bioprocess Technology, 7: 224-234. https://doi.org/10.1007/s11947-012-1046-8
Shen Y. X., Liu W. L., Li Y. H., Guan H. L., 2014. Large sample area and size are needed for forest soil seed bank studies to ensure low discrepancy with standing vegetation. PLoS ONE, 9 (8): e105235. https://doi.org/10.1371/journal.pone.0105235
Silverstein R. M., Webster F. X., Kiemle D. J., 2007. Spectrometric identification of organic compounds. Seventh edition. State University of New York. College of Environmental Science & Forestry, 502 p. https://doi.org/10.1021/ed039p546
Skowronek S., Terwei A., Zerbe S., Mölder I., Annighöfer P., Kawaletz H., et al., 2014. Regeneration potential of floodplain forests under the influence of non-native tree species: soil seed bank analysis in Northern Italy. Restoration Ecology, 22: 22-30. https://doi.org/10.1111/rec.12027
Sousa T. R., Costa F. R. C., Bentos T. V., Leal Filho N., Mesquita R. C. G., Ribeiro I. O., 2017. The effect of forest fragmentation on the soil seed bank of Central Amazonia. Forest Ecology and Management, 393: 105-112. https://doi.org/10.1016/j.foreco.2017.03.020
R Core Team, 2013. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.r-project.org/
Vermeulen P., Ebene M. B., Orlando B., Fernández Pierna J. A., Baeten V., 2017. Online detection and quantification of particles of ergot bodies in cereal flour using near infrared hyperspectral imaging. Food Additives & Contaminants: Part A, 34 (8): 1312-1319. https://doi.org/10.1080/19440049.2017.1336798
Vermeulen P., Fernández Pierna J. A., Abbas O., Dardenne P., Baeten V., 2010. Authentication and traceability of agricultural and food products using vibrational spectroscopy. In: Applications of vibrational spectroscopy in food science. Li-Chan E.C.Y., Griffiths P.R., Chalmers J. M. (Eds.). United Kingdom, John Wiley & Sons, 609-630. https://doi.org/10.1002/0470027320.s8969
Williams P., Geladi P., Fox G., Manley M., 2009. Maize kernel hardness classification by Near Infrared (NIR) Hyperspectral Imaging and multivariate data analysis. Analytica Chimica Acta, 653: 121-130. https://doi.org/10.1016/j.aca.2009.09.005
Wise B. M., Shaver J. M., Gallagher N. B., Windig W., Bro R., Koch R. S., 2006. PLSJToolbox Version 4.0 for use with Matlab™. USA, Eigenvector Research Inc., 420 p.
Yang Z., Hana L., Fernandez Pierna J. A., Dardenne P., Baeten V., 2011. The potential of near infrared microscopy to detect, identify and quantify processed animal by-products. Journal of Near Infrared Spectroscopy, 19: 211-231. https://doi.org/10.1255/jnirs.935
Zebaze D., Fayolle A., Daïnou K., Libalah M., Droissart V., Sonké B., et al., 2021. Land Use Has Little Influence on the Soil Seed Bank in a Central African Moist Forest. Biotropica, 54: 100-112. https://doi.org/10.1111/btp.13032
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