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Canopy‐Based Normalized Difference Vegetation Index Sensors for Monitoring Cotton Nitrogen Status
Author(s) -
Raper Tyson B.,
Varco Jac J.,
Hubbard Ken J.
Publication year - 2013
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj2013.0080
Subject(s) - normalized difference vegetation index , canopy , fertilizer , vegetation (pathology) , crop , agronomy , environmental science , field experiment , reflectivity , malvaceae , fiber crop , leaf area index , remote sensing , mathematics , botany , geography , biology , medicine , physics , optics , pathology
Crop reflectance using ground‐based sensors has the potential to provide information on crop N status in real‐time. However, the unique physiological and structural characteristics of cotton ( Gossypium hirsutum , L.) complicate normalized difference vegetation index (NDVI)‐based inferences on cotton N status. Therefore, the objectives of this study were to (i) determine the sensitivity of selected sensors and resulting NDVI measurements to different levels of fertilizer N; (ii) determine relationships between sensors and biophysical measurements; and (iii) compare absolute NDVI readings reported by each sensor. Field trials were conducted during crop years conducted from 2008 through 2010 at Mississippi State, MS. Fertilizer N rates of 0, 45, 90, and 135 kg N ha –1 were applied and replicated four times to establish N‐induced growth differences. Sensors used included the Yara N Sensor (Yara International ASA, Oslo, Norway), GreenSeeker (GS) Model 505 Optical Sensor Unit (NTech Industries, Inc., Ukiah, CA) and Crop Circle (CC) Model ACS‐210 (Holland Scientific, Inc., Lincoln, NE). Sensor readings failed to consistently predict cotton leaf N status before early flowering; however, plant height relationships with NDVIs were strong. Comparison of sensor response curves to fertilizer N resulted in no significant differences in slope values, although consistent, significant differences in y intercepts were noted beginning at early flowering and continuing through peak flowering. Greater accuracy in the detection of cotton leaf N status may require the utilization of an index which is less responsive to changes in plant height or canopy architecture. Furthermore, the magnitude of canopy reflectance‐based NDVI values differed across sensors.