• español
    • English
  • English 
    • español
    • English
  • Login
baner

CIMMYT Publications Repository

Seeding innovation ... Nourishing hope

View Item 
  •   DSpace Home
  • CIMMYT
  • Maize
  • View Item
  •   DSpace Home
  • CIMMYT
  • Maize
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Use of hyperspectral image data outperforms vegetation indices in prediction of maize yield


Type:
Article
Title:
Use of hyperspectral image data outperforms vegetation indices in prediction of maize yield
Author:
Aguate, F.M.;
Trachsel, S.;
Trachsel, S.
ORCID iD iconhttps://orcid.org/0000-0003-4727-1871
Items in this Repository
View

Gonzalez-Perez, L.;
Gonzalez-Perez, L.
ORCID iD iconhttps://orcid.org/0000-0002-5840-0803
Items in this Repository
View

Burgueño, J.;
ORCID iD icon
Burgueño, J.
ORCID iD iconhttps://orcid.org/0000-0002-1468-4867
ScopusScopus ID
Items in this Repository
View

Crossa, J.;
ORCID iD icon
Crossa, J.
ORCID iD iconhttps://orcid.org/0000-0001-9429-5855
ScopusScopus ID
Items in this Repository
View

Balzarini, M.;
Gouache, D.;
Bogard, M.;
Bogard, M.
ORCID iD iconhttps://orcid.org/0000-0003-1349-8330
Items in this Repository
View

De los Campos, G.
De los Campos, G.
ORCID iD iconhttps://orcid.org/0000-0001-5692-7129
Items in this Repository
View
Year:
2017
URI:
https://hdl.handle.net/10883/19304
Copyright:
CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose.
Journal:
Crop Science
Journal volume:
57
Journal issue:
5
Pages:
2517-2524
DOI:
10.2135/cropsci2017.01.0007
Place of Publication:
Madison, Wisconsin, U.S.
Publisher:
Crop Science Society of America (CSSA)
Citation:
Use of hyperspectral image data outperforms vegetation indices in prediction of maize yield. 2017. Aguate, F.M.; Trachsel, S.; Gonzalez-Perez, L.; Burgueño, J.; Crossa, J.; Balzarini, M.; Gouache, D.; Bogard, M.; De los Campos, G. 57 (5) DOI: 10.2135/cropsci2017.01.0007 Crop Science Society of America (CSSA).

Show full item record

Related Datasets

  • Link to dataset 1
  • Link to dataset 2






Files in this item

Thumbnail
Name:
59301.pdf
Size:
247.9Kb
Format:
application/pdf
Descripción:
...
View/Open

This item appears in the following Collection(s)

  • Maize

Collections

Genetic ResourcesInstitutionalMaizeSocioeconomicsSustainable Agrifood SystemsSustainable IntensificationWheat

Multimedia Collection

PhotographyVideo

All of DSpace
Communities & CollectionsAuthorsTitlesSubjectsBy YearConferenceJournal
This Collection
AuthorsTitlesSubjectsBy YearConferenceJournal

CIMMYT staff access

Login

View Usage Statistics


baner
 

 


DSpace software copyright © 2002-2015  DuraSpace
Contact Us | Send Feedback