HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Figures Only Full Text Free Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in ISI Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (5) Citing Articles via Google Scholar Google Scholar Articles by Fridgen, J. L. Articles by Varco, J. J. Search for Related Content PubMed Articles by Fridgen, J. L. Articles by Varco, J. J. Agricola Articles by Fridgen, J. L. Articles by Varco, J. J. Related Collections Nitrogen Cotton Nutrient Management Plant Analysis Plant Nutrition

COTTON

Dependency of Cotton Leaf Nitrogen, Chlorophyll, and Reflectance on Nitrogen and Potassium Availability

Dep. of Plant and Soil Sci., Mississippi State Univ., Mississippi State, MS 39762

^* Corresponding author (jvarco{at}pss.msstate.edu).

Received for publication January 13, 2003. In-season assessment of cotton (Gossypium hirsutum L.) leaf N and K concentration using remote sensing techniques is needed to address spatial and temporal variation of these two nutrients. The objective of this study was to evaluate the effects of varying N and K availability on cotton chlorophyll concentration and detection of leaf N utilizing reflectance properties. Fertilizer N rates of 0, 45, 90, 135, and 180 kg ha^–1 in factorial combination with K rates of 0 and 112 kg ha^–1 were applied to cotton under field conditions. Recently matured leaves on the main stem were collected at first bloom and peak bloom physiological stages of growth in 1999 and 2000 to determine leaf N and K concentrations, chlorophyll concentration, and spectral reflectance. Nutrient stress anomalies from spectral reflectance data were predicted using partial least-squares regression. Partial least squares yielded a better predictability of leaf N concentration at first bloom and peak bloom when K was adequately supplied. The greatest predictability of leaf N was observed at peak bloom in 2000 with a maximum r² of 0.77 and minimum standard error of prediction of 2.72. A red-edge shift to longer wavelengths with increased N supply was observed when K was sufficient. Utilization of leaf N concentration sampled at a coarse resolution in combination with timely and appropriate imagery may enhance nutrient management capabilities in precision agriculture so long as other nutrients are not limiting.

Abbreviations: DAP, days after planting • NIR, near infrared • PLS, partial least squares • SEP, standard error of prediction • _re, red edge

This article has been cited by other articles:

				M. T. Gomez-Casero, F. Lopez-Granados, J. M. Pena-Barragan, M. Jurado-Exposito, L. Garcia-Torres, and R. Fernandez-Escobar Assessing Nitrogen and Potassium Deficiencies in Olive Orchards through Discriminant Analysis of Hyperspectral Data J. Amer. Soc. Hort. Sci., September 1, 2007; 132(5): 611 - 618. [Abstract] [Full Text] [PDF]

				J. K. Kruse, N. E. Christians, and M. H. Chaplin Remote Sensing of Nitrogen Stress in Creeping Bentgrass Agron. J., October 31, 2006; 98(6): 1640 - 1645. [Abstract] [Full Text] [PDF]

				K. F. Bronson, J. D. Booker, J. W. Keeling, R. K. Boman, T. A. Wheeler, R. J. Lascano, and R. L. Nichols Cotton Canopy Reflectance at Landscape Scale as Affected by Nitrogen Fertilization Agron. J., April 27, 2005; 97(3): 654 - 660. [Abstract] [Full Text] [PDF]