Publication:
Onfield estimation of quality parameters in alfalfa through hyperspectral spectrometer data

dc.contributor.authorGámez Guzmán, Angie Lorena
dc.contributor.authorVatter, Thomas
dc.contributor.authorSantesteban García, Gonzaga
dc.contributor.authorAraus, José Luis
dc.contributor.authorAranjuelo Michelena, Iker
dc.contributor.departmentAgronomía, Biotecnología y Alimentaciónes_ES
dc.contributor.departmentAgronomia, Bioteknologia eta Elikaduraeu
dc.date.accessioned2024-04-18T18:12:10Z
dc.date.available2024-04-18T18:12:10Z
dc.date.issued2024
dc.date.updated2024-04-18T17:48:13Z
dc.description.abstractAlfalfa is a forage of vast importance around the world. In the past, near-infrared spectroscopy (NIRS) technique have been explored in the lab to determine quality traits such as fibre content in dried and ground material. During the last decade, portable hyperspectral devices have emerged as a tools for in-field prediction, of not only crop yield but also a large range of quality and physiological markers. The objective of this study was to estimate quality parameters in an alfalfa crop using hyperspectral data acquired from a full-range (350–2500 nm) spectrometer under field conditions. Reflected spectra were measured in single leaves as well as at the canopy level, then reflectance was related to target parameters such as biomass, leaf pigments, sugars, protein, and mineral contents. Due to their large effect on crop quality parameters, meteorological conditions and phenological stages were included as predictors in the models. We found that meteorological and phenological variables improved the accuracies and percentage of variance explained (R2) for most of the parameters evaluated. Based on R2 values, the best prediction models were obtained for biomass (0.71), sucrose (0.65), flavonoids (Flav) (0.56) and nitrogen (0.70) with normalized root mean squared errors of 0.196, 0.32, 0.087 and 0.08, respectively. These parameters were associated mainly with visible (VIS) (approx. 350–700 nm) and near infrared (NIR) (700–1250 nm) regions of the spectrum. Regarding mineral composition, the best prediction models were developed for P (0.51), B (0.50) and Zn (0.44), associated with the short-wave infra-red (SWIR) region (1250–2500 nm). The results of this study demonstrated the potential of hyperspectral techniques to be used as a base for performing initial evaluations in the field of quality traits in alfalfa crops.en
dc.description.sponsorshipAngie L. Gámez is the recipient of a PhD grant (reference 0011-1408- 2020-000005) funded by the Government of Navarre and Nafosa S.L. This manuscript has been conducted within the context of the CropEqualT-CEC project funded by the European Union’s Horizon 2020, Belgium Marie Curie Rise research and innovation programme.en
dc.format.mimetypeapplication/pdfen
dc.format.mimetypeapplication/msworden
dc.identifier.citationGámez, A. L., Vatter, T., Santesteban, L. G., Araus, J. L., Aranjuelo, I. (2024) Onfield estimation of quality parameters in alfalfa through hyperspectral spectrometer data. Computers and Electronics in Agriculture, 216, 1-11. https://doi.org/10.1016/j.compag.2023.108463.en
dc.identifier.doi10.1016/j.compag.2023.108463
dc.identifier.issn0168-1699
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/48008
dc.language.isoengen
dc.publisherElsevieren
dc.relation.ispartofComputers and Electronics in Agriculture 216, 2024, 108463en
dc.relation.projectIDinfo:eu-repo/grantAgreement/Gobierno de Navarra//0011-1408- 2020-000005en
dc.relation.publisherversionhttps://doi.org/10.1016/j.compag.2023.108463
dc.rights© 2023 The Authors. This is an open access article under the CC BY-NC-ND license.en
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectAlfalfaen
dc.subjectCanopyen
dc.subjectHyperspectral techniqueen
dc.subjectQuality parametersen
dc.subjectTrait predictionen
dc.titleOnfield estimation of quality parameters in alfalfa through hyperspectral spectrometer dataen
dc.typeinfo:eu-repo/semantics/article
dc.type.versionVersión publicada / Argitaratu den bertsioaes
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
dspace.entity.typePublication
relation.isAuthorOfPublication8afeb09d-4593-4d40-8219-c00a6da4ef90
relation.isAuthorOfPublication70e95546-7fe8-4555-b366-74356bdb746e
relation.isAuthorOfPublicationb8dd84ae-83ed-4e3f-873e-b0023505b3df
relation.isAuthorOfPublication.latestForDiscovery8afeb09d-4593-4d40-8219-c00a6da4ef90

Files

Original bundle
Now showing 1 - 2 of 2
Loading...
Thumbnail Image
Name:
Gamez_OnfieldEstimation.pdf
Size:
3.81 MB
Format:
Adobe Portable Document Format
No Thumbnail Available
Name:
Gamez_OnfieldEstimation_MatCompl.docx
Size:
1.12 MB
Format:
Microsoft Word XML
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.78 KB
Format:
Item-specific license agreed to upon submission
Description: