Published in

Wiley, Agronomy Journal, 6(103), p. 1597-1603, 2011

DOI: 10.2134/agronj2011.0124

Links

Tools

Export citation

Search in Google Scholar

Use of the Canopy Chlorophyl Content Index (CCCI) for Remote Estimation of Wheat Nitrogen Content in Rainfed Environments

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Orange circle
Postprint: archiving restricted
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Estimation of canopy N content in rainfed environments early in the growing season and across different locations is challenging due to differences in canopy structure, canopy cover, and soil reflectance. The hypothesis of this study was that the combination of the remotely sensed Canopy Content Chlorophyll Index (CCCI) and the Canopy Nitrogen Index (CNI) allows for the estimation of canopy N status directly from remote measurements, independently of cultivar and site. The aims of this study were to (i) estimate canopy N content from CCCI and CNI in two rainfed environments and on two different wheat cultivars; (ii) study the effects of different ways of deriving the CCCI on the estimation of canopy N content. Data were collected from two rainfed sites cropped to wheat, one in Italy (Foggia) and the other in Australia (Horsham, Victoria). Studies were conducted during the growing seasons 2006-2007 (December-June) and 2007 (June-December) for the Italian and Australian sites, respectively. The use of the CCCI in combination with the CNI show that it is possible to estimate canopy N content early in the season (DC 30), (y = 0.94x + 0.15; r(2) = 0.97; RMSE = 0.20 g N m(-2)) when farmers make their N fertilization decisions. Future research is needed to further validate such approach on independent locations with different growing season rainfall; and to study the robustness of the CCCI boundaries on different environments and different crop types and develop a method to estimate biomass under chronic and acute water stress.