Soil-line vegetation indices for corn nitrogen content prediction

The soil-line vegetation indices for prediction of corn canopy nitrogen content were investigated. Results indicated that the vegetation indices applied were correlated with corn canopy nitrogen content and the wavelengths between 630-860 nm are suitable for nitrogen diagnosis. The second-order poly...

Full description

Saved in:
Bibliographic Details
Published inInternational Agrophysics Vol. 26; no. 2; pp. 103 - 108
Main Authors Bagheri, N., Ahmadi, H., Alavipanah, S., Omid, M.
Format Journal Article
LanguageEnglish
Published Lublin Versita 01.04.2012
Polish Academy of Sciences, Institute of Agrophysics
Subjects
corn
nitrogen
satellite remote sensing
soil-line vegetation indices
Online AccessGet full text

Cover

Abstract The soil-line vegetation indices for prediction of corn canopy nitrogen content were investigated. Results indicated that the vegetation indices applied were correlated with corn canopy nitrogen content and the wavelengths between 630-860 nm are suitable for nitrogen diagnosis. The second-order polynomial equation was the best model for nitrogen content prediction among different regression types. Analyses based on both predicted and measured data were carried out to compare the performance of existing vegetation indices.
AbstractList The soil-line vegetation indices for prediction of corn canopy nitrogen content were investigated. Results indicated that the vegetation indices applied were correlated with corn canopy nitrogen content and the wavelengths between 630-860 nm are suitable for nitrogen diagnosis. The second-order polynomial equation was the best model for nitrogen content prediction among different regression types. Analyses based on both predicted and measured data were carried out to compare the performance of existing vegetation indices.
Soil-line vegetation indices for corn nitrogen content prediction The soil-line vegetation indices for prediction of corn canopy nitrogen content were investigated. Results indicated that the vegetation indices applied were correlated with corn canopy nitrogen content and the wavelengths between 630-860 nm are suitable for nitrogen diagnosis. The second-order polynomial equation was the best model for nitrogen content prediction among different regression types. Analyses based on both predicted and measured data were carried out to compare the performance of existing vegetation indices.
Soil-line vegetation indices for corn nitrogen content prediction The soil-line vegetation indices for prediction of corn canopy nitrogen content were investigated. Results indicated that the vegetation indices applied were correlated with corn canopy nitrogen content and the wavelengths between 630-860 nm are suitable for nitrogen diagnosis. The second-order polynomial equation was the best model for nitrogen content prediction among different regression types. Analyses based on both predicted and measured data were carried out to compare the performance of existing vegetation indices.
Author Omid, M.
Ahmadi, H.
Bagheri, N.
Alavipanah, S.
Author_xml – sequence: 1
  givenname: N.
  surname: Bagheri
  fullname: Bagheri, N.
  organization: Department of Agricultural Technology and Engineering, University of Tehran, Karaj, Iran
– sequence: 2
  givenname: H.
  surname: Ahmadi
  fullname: Ahmadi, H.
  organization: Department of Agricultural Technology and Engineering, University of Tehran, Karaj, Iran
– sequence: 3
  givenname: S.
  surname: Alavipanah
  fullname: Alavipanah, S.
  organization: Department of Geography, University of Tehran, Karaj, Iran
– sequence: 4
  givenname: M.
  surname: Omid
  fullname: Omid, M.
  organization: Department of Agricultural Technology and Engineering, University of Tehran, Karaj, Iran
BookMark eNp1UF1r2zAUFSOFZWl_wN4Me1Z7JdmW9DS6sC2lgdI2g70JW74K7jIpk5W2-feVcSl92X0558L5gPOJzHzwSMhnBue8lOrikUFGCoxTAFZT9YHMuQCgSvJqRubART1y_pGcDcMD5BNa10LOyeV96Hd013ssHnGLqUl98EXvu97iULgQCxuiL3yfYtiiz59P6FOxj5glo_iUnLhmN-DZKy7Irx_fN8sVXd_8vFperqktFSTayqoE55rOMl1pV4pSVW1nLQjVqUq2wB1Dqy0yVTEnaw1aso5Bi6LV0jqxIF-m3H0M_w44JPMQDtHnSsME50JpoVVWsUllYxiGiM7sY_-3iUfDwIxjmWksk8cy41hm9HydPE_NLmHscBsPx0zeFfzPy2vOQOQEOiX0Q8Lnt8om_jG1FLIyt5vSfFuWavX7emPuxAsfnoEx
CitedBy_id crossref_primary_10_1007_s10661_019_7989_8
crossref_primary_10_1017_S0014479722000308
crossref_primary_10_29133_yyutbd_1114636
crossref_primary_10_1590_S0100_204X2013001000011
crossref_primary_10_33409_tbbbd_757448
crossref_primary_10_33409_tbbbd_668890
crossref_primary_10_1016_j_ecolind_2020_107001
crossref_primary_10_1177_0967033520939319
crossref_primary_10_1007_s12355_023_01329_1
crossref_primary_10_1007_s40333_023_0020_9
Cites_doi 10.1016/j.fcr.2007.11.001
10.1016/S0034-4257(97)00171-5
10.1016/0034-4257(94)90134-1
10.1016/j.rse.2003.12.013
10.1016/j.eja.2007.11.005
10.1080/014311600210326
10.13031/2013.16023
10.1016/0034-4257(88)90106-X
10.1016/j.compag.2008.10.003
10.1016/j.compag.2007.05.002
10.1016/j.compag.2007.01.004
10.13031/2013.18308
10.2134/agronj1996.00021962008800010001x
10.1016/j.jag.2004.03.002
10.1081/PLN-120013295
10.1016/j.agee.2004.10.030
10.2134/agronj2005.0099
10.1016/j.jag.2004.10.002
10.1016/S1002-0160(06)60032-5
10.1016/j.biosystemseng.2008.05.005
10.13031/2013.18303
ContentType Journal Article
Copyright Copyright Versita Apr 2012
Copyright_xml – notice: Copyright Versita Apr 2012
DBID BSCLL
AAYXX
CITATION
3V.
7X2
8FE
8FH
8FK
ABUWG
AFKRA
ATCPS
AZQEC
BENPR
BHPHI
CCPQU
DWQXO
HCIFZ
M0K
PIMPY
PQEST
PQQKQ
PQUKI
PRINS
DOI 10.2478/v10247-012-0016-8
DatabaseName Istex
CrossRef
ProQuest Central (Corporate)
Agricultural Science Collection
ProQuest SciTech Collection
ProQuest Natural Science Collection
ProQuest Central (Alumni) (purchase pre-March 2016)
ProQuest Central (Alumni)
ProQuest Central UK/Ireland
Agricultural & Environmental Science Collection
ProQuest Central Essentials
ProQuest Central
ProQuest Natural Science Collection
ProQuest One Community College
ProQuest Central
SciTech Premium Collection
Agriculture Science Database
Publicly Available Content Database
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Academic
ProQuest One Academic UKI Edition
ProQuest Central China
DatabaseTitle CrossRef
Agricultural Science Database
Publicly Available Content Database
ProQuest Central Essentials
ProQuest One Academic Eastern Edition
Agricultural Science Collection
ProQuest Central (Alumni Edition)
SciTech Premium Collection
ProQuest One Community College
ProQuest Natural Science Collection
ProQuest SciTech Collection
ProQuest Central China
ProQuest Central
ProQuest One Academic UKI Edition
Natural Science Collection
ProQuest Central Korea
Agricultural & Environmental Science Collection
ProQuest One Academic
ProQuest Central (Alumni)
DatabaseTitleList
Agricultural Science Database

CrossRef
Database_xml – sequence: 1
  dbid: BENPR
  name: AUTh Library subscriptions: ProQuest Central
  url: https://www.proquest.com/central
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Agriculture
EISSN 2300-8725
EndPage 108
ExternalDocumentID 2933225151
10_2478_v10247_012_0016_8
10_2478_v10247_012_0016_8262103
ark_67375_QT4_BC48HXKT_R
GroupedDBID 0R~
29J
2WC
3EA
5GY
5VS
7X2
8FE
8FH
AAHBH
ACGFS
ADBBV
ADUQZ
AENEX
AFKRA
AFRAH
AGGNV
ALMA_UNASSIGNED_HOLDINGS
ASPBG
ATCPS
AVWKF
AZFZN
BCNDV
BENPR
BHPHI
BSCLL
CCPQU
E0C
E3Z
ECGQY
FEDTE
GROUPED_DOAJ
HCIFZ
HVGLF
HZ~
KQ8
M0K
MET
M~E
O9-
OK1
PIMPY
PROAC
SA.
SLJYH
TR2
Y2W
~02
~Z8
9WM
AAPBV
AGKVL
M48
AAYXX
CITATION
3V.
8FK
ABUWG
AZQEC
DWQXO
PQEST
PQQKQ
PQUKI
PRINS
ID FETCH-LOGICAL-c480t-b7540ffadc1959f43485bdcc038d857b02f1ec9ce1851f7690971d10be3b97cf3
IEDL.DBID BENPR
ISSN 0236-8722
IngestDate Thu Oct 10 17:31:33 EDT 2024
Fri Aug 23 03:36:04 EDT 2024
Fri Nov 25 00:40:46 EST 2022
Wed Oct 30 09:29:50 EDT 2024
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 2
Language English
License This content is open access.
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c480t-b7540ffadc1959f43485bdcc038d857b02f1ec9ce1851f7690971d10be3b97cf3
Notes ArticleID:v10247-012-0016-8
v10247-012-0016-8.pdf
istex:A989F983EB2B09A21A5F5DBA9624D71E0D7215E2
ark:/67375/QT4-BC48HXKT-R
OpenAccessLink https://www.proquest.com/docview/1322389398?pq-origsite=%requestingapplication%
PQID 1322389398
PQPubID 2026528
PageCount 6
ParticipantIDs proquest_journals_1322389398
crossref_primary_10_2478_v10247_012_0016_8
walterdegruyter_journals_10_2478_v10247_012_0016_8262103
istex_primary_ark_67375_QT4_BC48HXKT_R
PublicationCentury 2000
PublicationDate 2012-4-1
PublicationDateYYYYMMDD 2012-04-01
PublicationDate_xml – month: 04
  year: 2012
  text: 2012-4-1
  day: 01
PublicationDecade 2010
PublicationPlace Lublin
PublicationPlace_xml – name: Lublin
PublicationTitle International Agrophysics
PublicationYear 2012
Publisher Versita
Polish Academy of Sciences, Institute of Agrophysics
Publisher_xml – name: Versita
– name: Polish Academy of Sciences, Institute of Agrophysics
References M. Eldaw Elwadie (6) 2005; 97
D. Reum (22) 2007; 56
C. Zhao (25) 2005; 7
Z. Jin-Heng (10) 2006; 16
R. Lawrence (14) 1998; 64
F. Li (15) 2008; 106
J. Piekarczyk (20) 2001; 15
M. Min (17) 2005; 48
A. Huete (9) 1988; 25
L. Xue (24) 2008; 100
H. Buscaglia (5) 2002; 25
M. Abrams (1) 2003; 21
O. Beeri (2) 2005; 107
W. Feng (7) 2008; 28
R. Jongschaap (11) 2004; 5
L. Lough (16) 2000
M. Kostrzewski (13) 2002; 46
D. Sena, jr (23) 2007
T. Blackmer (3) 1996; 88
D. Haboudane (8) 2004; 90
J. Qi (21) 1994; 48
M. Perry (19) 2007; 59
M. Borhan (4) 2004; 47
Y. Karimi (12) 2005; 48
M. Pagola (18) 2008; 65
References_xml – volume: 106
  start-page: 77
  year: 2008
  ident: 15
  article-title: Estimating N status of winter wheat using a handheld spectrometer in the North China plain
  publication-title: J. Field Crops. Res
  doi: 10.1016/j.fcr.2007.11.001
  contributor:
    fullname: F. Li
– volume: 46
  start-page: 29
  issue: 1
  year: 2002
  ident: 13
  article-title: Ground-based remote sensing of water and nitrogen stress
  publication-title: J. Trans. ASABE
  contributor:
    fullname: M. Kostrzewski
– year: 2007
  ident: 23
  article-title: Multivariate classifiers using image texture features for nitrogen doses discrimination in wheat
  contributor:
    fullname: D. Sena, jr
– volume: 64
  start-page: 91
  year: 1998
  ident: 14
  article-title: Comparisons among vegetation indices and bandwise regression in a highly disturbed, heterogeneous landscape
  publication-title: J. Remote Sens. Environ
  doi: 10.1016/S0034-4257(97)00171-5
  contributor:
    fullname: R. Lawrence
– volume: 48
  start-page: 119
  year: 1994
  ident: 21
  article-title: A modified soil vegetation adjusted index
  publication-title: J. Remote Sens. Environ
  doi: 10.1016/0034-4257(94)90134-1
  contributor:
    fullname: J. Qi
– volume: 90
  start-page: 337
  year: 2004
  ident: 8
  article-title: Hyper spectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modeling and validation in the context of precision agriculture
  publication-title: J. Remote Sens. Environ
  doi: 10.1016/j.rse.2003.12.013
  contributor:
    fullname: D. Haboudane
– volume: 28
  start-page: 394
  year: 2008
  ident: 7
  article-title: Monitoring leaf nitrogen status with hyper spectral reflectance in wheat
  publication-title: J. Eur. Agron
  doi: 10.1016/j.eja.2007.11.005
  contributor:
    fullname: W. Feng
– volume: 21
  start-page: 847
  year: 2003
  ident: 1
  article-title: The advanced space borne thermal emission and reflection radiometer (ASTER): data products for the high spatial resolution imager on NASA's Terra platform
  publication-title: J. Int. J. Remote Sens
  doi: 10.1080/014311600210326
  contributor:
    fullname: M. Abrams
– volume: 47
  start-page: 599
  issue: 2
  year: 2004
  ident: 4
  article-title: Multi-spectral and color imaging techniques for nitrate and chlorophyll determination of potato leaves in a controlled environment
  publication-title: J. Trans. ASABE
  doi: 10.13031/2013.16023
  contributor:
    fullname: M. Borhan
– volume: 25
  start-page: 295
  year: 1988
  ident: 9
  article-title: A soil vegetation adjusted index (SAVI)
  publication-title: J. Remote Sens. Environ
  doi: 10.1016/0034-4257(88)90106-X
  contributor:
    fullname: A. Huete
– volume: 65
  start-page: 213
  issue: 2
  year: 2008
  ident: 18
  article-title: New method to assess barely nitrogen nutrition status based on image colour analysis comparison with SPAD-502
  publication-title: J. Comput. Electron. Agric
  doi: 10.1016/j.compag.2008.10.003
  contributor:
    fullname: M. Pagola
– volume: 15
  start-page: 101
  year: 2001
  ident: 20
  article-title: Studies of soil temperature on the basis of satellite data
  publication-title: Int. Agrophysics
  contributor:
    fullname: J. Piekarczyk
– volume: 59
  start-page: 56
  year: 2007
  ident: 19
  article-title: Spectral and spatial differences in response of vegetation indices to nitrogen treatments on apple
  publication-title: J. Comput. Electron. Agric
  doi: 10.1016/j.compag.2007.05.002
  contributor:
    fullname: M. Perry
– year: 2000
  ident: 16
  article-title: Effects of varing N and K nutrition on the spectral reflectance properties of cotton
  contributor:
    fullname: L. Lough
– volume: 56
  start-page: 60
  year: 2007
  ident: 22
  article-title: Wavelet based multi-spectral image analysis of maize leaf chlorophyll content
  publication-title: J. Comput. Electron. Agric
  doi: 10.1016/j.compag.2007.01.004
  contributor:
    fullname: D. Reum
– volume: 48
  start-page: 455
  issue: 2
  year: 2005
  ident: 17
  article-title: Determination of significant wave-lengths and prediction of nitrogen content for citrus
  publication-title: J. Trans. ASABE
  doi: 10.13031/2013.18308
  contributor:
    fullname: M. Min
– volume: 88
  start-page: 1
  year: 1996
  ident: 3
  article-title: Nitrogen deficiency detection using reflected short-wave radiation from irrigated corn canopies
  publication-title: J. Agron
  doi: 10.2134/agronj1996.00021962008800010001x
  contributor:
    fullname: T. Blackmer
– volume: 5
  start-page: 205
  year: 2004
  ident: 11
  article-title: Spectral measurements at different spatial scales in potato: relating leaf, plant and canopy status
  publication-title: J. Int. Appl. Earth Obser. Geoinf
  doi: 10.1016/j.jag.2004.03.002
  contributor:
    fullname: R. Jongschaap
– volume: 25
  start-page: 2067
  year: 2002
  ident: 5
  article-title: Early detection of cotton leaf nitrogen status using leaf reflectance
  publication-title: J. Plant Nutr
  doi: 10.1081/PLN-120013295
  contributor:
    fullname: H. Buscaglia
– volume: 107
  start-page: 21
  year: 2005
  ident: 2
  article-title: Alternate satellite models for estimation of sugar beet residue nitrogen credit
  publication-title: J. Agric. Ecosys. Environ
  doi: 10.1016/j.agee.2004.10.030
  contributor:
    fullname: O. Beeri
– volume: 97
  start-page: 99
  year: 2005
  ident: 6
  article-title: Remote sensing of canopy dynamics and biophysical variables estimation of corn in Michigan
  publication-title: J. Agron
  doi: 10.2134/agronj2005.0099
  contributor:
    fullname: M. Eldaw Elwadie
– volume: 7
  start-page: 1
  year: 2005
  ident: 25
  article-title: Predicting grain protein content of winter wheat using remote sensing data based on nitrogen status and water stress
  publication-title: Int. J. Appl. Earth Obser. Geoinf
  doi: 10.1016/j.jag.2004.10.002
  contributor:
    fullname: C. Zhao
– volume: 16
  start-page: 108
  issue: 1
  year: 2006
  ident: 10
  article-title: Predicting nitrogen status of rice using multi spectral data at canopy scale
  publication-title: Pedosphere
  doi: 10.1016/S1002-0160(06)60032-5
  contributor:
    fullname: Z. Jin-Heng
– volume: 100
  start-page: 524
  year: 2008
  ident: 24
  article-title: Recommendations for nitrogen fertilizer topdressing rates in rice using canopy reflectance spectra
  publication-title: J. Biosyst. Eng
  doi: 10.1016/j.biosystemseng.2008.05.005
  contributor:
    fullname: L. Xue
– volume: 48
  start-page: 805
  issue: 2
  year: 2005
  ident: 12
  article-title: Discriminant analysis of hyper spectral data for assessing water and nitrogen stresses in corn
  publication-title: J. Trans. ASABE
  doi: 10.13031/2013.18303
  contributor:
    fullname: Y. Karimi
SSID ssj0000399637
Score 1.9747393
Snippet The soil-line vegetation indices for prediction of corn canopy nitrogen content were investigated. Results indicated that the vegetation indices applied were...
Soil-line vegetation indices for corn nitrogen content prediction The soil-line vegetation indices for prediction of corn canopy nitrogen content were...
Soil-line vegetation indices for corn nitrogen content prediction The soil-line vegetation indices for prediction of corn canopy nitrogen content were...
SourceID proquest
crossref
walterdegruyter
istex
SourceType Aggregation Database
Publisher
StartPage 103
SubjectTerms corn
nitrogen
satellite remote sensing
soil-line vegetation indices
Title Soil-line vegetation indices for corn nitrogen content prediction
URI https://api.istex.fr/ark:/67375/QT4-BC48HXKT-R/fulltext.pdf
http://www.degruyter.com/doi/10.2478/v10247-012-0016-8
https://www.proquest.com/docview/1322389398
Volume 26
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1LTxsxELZocmkPES2tCC_5UHFAsvB6nbX3VAECRSAQoCDlZq1fUdUqCUuA9t93ZtfhUQnuo13psz3fN57xDCHfVR65y2xgCsQtk4FzZqvgmZW-sEHluXP4wPn8ohjeyNPxYJwu3O5SWeXSJzaO2s8c3pHvY9SE5FrqH_NbhlOjMLuaRmh8IF0BkQLvkO7h8cXl9dMtCwf-LdrGmQI77yoh2tSmkErvPwC7Sqy8FAylD9OvyKmLOP95pTx7j00O24dJff93scyZNlR0skp6SUPSg3bRP5OVMP1CPh1M6tRHI6yBt5z9_M1QQtKHMEklhRTz0-AXKAhVClHnlMJ5rmewhShWrAP90HmNiRs0_kpuTo5HR0OWpiUwJzVfMKtAfMVYeYf9YqLMpR5Y7xzPtdcDZbmIWXClC8DQWVQQFZcq8xm3IbelcjH_RjrT2TSsEwqWmSuzwPGZayy4VtFa7iuhqqBK4ftkbwmTmbdNMQwEE4ipaTE1gCmWyxVG98luA-STZVX_wmoyNTBXI2kOj6Qejs9G5rpPtpZIm3SQ7szzsveJ_g_9F1Zv_VwUENLmG-9_eZN8FM0ewHqcLdJZ1PdhG6TGwu6k_bTThOr_AE9p0UI
link.rule.ids 315,783,787,867,21400,27936,27937,33756,43817,67015,68799
linkProvider ProQuest
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1LTxsxELZacmg5oD5FgFIfqh4qWXi9ztp7QoBAaYGoRUHKzVq_IgRKwia8_n1ndh1akNr7aFf6bM_3jWc8Q8gXlUfuMhuYAnHLZOCc2Sp4ZqUvbFB57hw-cD4dFP1z-WPUG6ULt3kqq1z6xMZR-6nDO_IdjJqQXEu9O7tmODUKs6tphMZL0sFWVRB8dfYPBz_PHm9ZOPBv0TbOFNh5VwnRpjaFVHrnFthVYuWlYCh9mH5CTh3E-f6J8ly7a3LYPozrm4fFMmfaUNHRG7KWNCTdaxf9LXkRJu_I6t64Tn00wnvwltOLK4YSkt6GcSoppJifBr9AQahSiDonFM5zPYUtRLFiHeiHzmpM3KDxB3J-dDg86LM0LYE5qfmCWQXiK8bKO-wXE2Uudc9653iuve4py0XMgitdAIbOooKouFSZz7gNuS2Vi_lHsjKZTsI6oWCZuTILHJ-5xoJrFa3lvhKqCqoUvku-LWEys7YphoFgAjE1LaYGMMVyucLoLvnaAPloWdWXWE2meubXUJr9A6n7o-OhOeuSrSXSJh2kufmz7F2in6H_l9W_fi4KCGnzjf9_-TN51R-enpiT74PjTfJaNPsBa3O2yMqivgmfQHYs7HbaW78BdRDTRw
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LTxsxELZ4SBUcEH2JAKU-VBwqWfF6nbX3SANRWh4CFKTcrPUrQqAkWpIA_56Z7CYC1F56n33oW9vzjefzt4T8UGnkLrGBKSC3TAbOmS2CZ1b6zAaVps7hAefzi6x7I__0W_0Vcrw4C4OySh8G5fR5UjmkNv3ITXGjbOE1IKTSzRnkRYmaScGQtDDdHPu4StYzBekNSRFvL3daOOTgrDLPFOi-q4So2pt_v9ObBLWOWD-9YZ9bj_M-9vIlX6WjzjbZqnkkPao-_EeyEoafyObRoKy9NMJnWDFHt_cMaSSdhUEtK6TYo4a1gQJZpVB5DinM6XIEw4iiah0QoOMSmzcY_IXcdE567S6r_5jAnNR8wqwCAhZj4R16xkSZSt2y3jmeaq9bynIRk-ByFyBLJ1FBZZyrxCfchtTmysX0K1kbjoZhh1CITFyeBI5HXWPGtYrWcl8IVQSVC98gPxcwmXFljGGgoEBMTYWpAUxRMpcZ3SCHcyCXkUV5h4oy1TJXPWl-taXu9k975rpB9hdIm3oyPRgsmJFX5XAf_Q79V1H_erjIoKxNd___0u_kw-Vxx5z9vjjdIxtiPlRQurNP1iblNHwDVjKxB_NB9wJjTNi-
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Soil-line+vegetation+indices+for+corn+nitrogen+content+prediction&rft.jtitle=International+Agrophysics&rft.au=Bagheri%2C+N&rft.au=Ahmadi%2C+H&rft.au=Alavipanah%2C+S&rft.au=Omid%2C+M&rft.date=2012-04-01&rft.pub=Polish+Academy+of+Sciences%2C+Institute+of+Agrophysics&rft.issn=0236-8722&rft.eissn=2300-8725&rft.volume=26&rft.issue=2&rft.spage=103&rft_id=info:doi/10.2478%2Fv10247-012-0016-8&rft.externalDocID=2933225151
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0236-8722&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0236-8722&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0236-8722&client=summon