PASTIC Dspace Repository

HYPERSPECTRAL ESTIMATION MODEL FOR NITROGEN CONTENTS OF SUMMER CORN LEAVES UNDER RAINFED CONDITIONS

Show simple item record

dc.contributor.author MUHAMMAD NAVEED TAHIR
dc.contributor.author LI, JUN
dc.contributor.author LIU, BINGFENG
dc.contributor.author ZHAO, GANGFENG
dc.contributor.author FUQI, YAO
dc.contributor.author CHENGFENG, CUI
dc.date.accessioned 2023-01-10T03:59:58Z
dc.date.available 2023-01-10T03:59:58Z
dc.date.issued 2013-10-25
dc.identifier.citation Tahir, M. N., Li, J., Liu, B., Zhao, G., Fuqi, Y., & Chengfeng, C. (2013). Hyperspectral estimation model for nitrogen contents of summer corn leaves under rainfed conditions. Pak. J. Bot, 45(5), 1623-1630. en_US
dc.identifier.issn 2070-3368
dc.identifier.uri http://142.54.178.187:9060/xmlui/handle/123456789/15808
dc.description.abstract Accuracy and precision of nitrogen estimation can be improved by hyperspectral remote sensing that leads effective management of nitrogen application in precision agriculture. The objectives of this study were to identify N sensitive spectral wavelengths, their combinations and spectral vegetation indices (SVIs) that are indicative of nitrogen nutritional condition and to analyze the accuracy of different spectral parameters for remote estimation of nitrogen status temporally. A study was conducted during 2010 at Northwest A & F University, China, to determine the relationship between leaf hyperspectral reflectance (350-1075 nm) and leaf N contents in the field-grown corn (Zea mays L.) under five nitrogen rates (0, 60, 120, 180 and 240 kg/ha pure nitrogen) were measured at key developmental stages. The accuracy of nitrogen nutrition diagnosis among the single (R) and dual (R1+R2) wavelengths spectral reflectance, spectral ratio (SR) in the green, red and near infrared, NDVI, GNDVI and SAVI were compared. Chose the highest determination of coefficient (R2 ) model and lowest RMSE and RRMSE at each growth stage, fitted the smaller as the best model. The results showed that Y = 4.450+0.00X-17.99X2 +10.496X3 was the best prediction model for remote estimation of leaf N contents with GNDVI at 10-12 leaf stage followed by Y = 3.986X0.161 at silking stage, then Y = 3.092+1.684X+1.995X2 at tasseling stage with R630 nm and Y = -3.860-12.692X+0.00X2 +7.632X3 at early dent stage with R720. The study results indicated that leaf spectral reflectance can be effectively used as nondestructive, quick, and reliable for real time monitoring of corn nitrogen status and important tool for N fertilizer management in precision agriculture. en_US
dc.language.iso en en_US
dc.publisher Karachi: Pakistan Botanical Society en_US
dc.title HYPERSPECTRAL ESTIMATION MODEL FOR NITROGEN CONTENTS OF SUMMER CORN LEAVES UNDER RAINFED CONDITIONS en_US
dc.type Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account