SSSAJ Grow Your Career with SSSA
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


This Article
Right arrow Figures Only
Right arrow Full Text Free
Right arrow Full Text (PDF) Free
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (7)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Bronson, K. F.
Right arrow Articles by Lascano, R. J.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Bronson, K. F.
Right arrow Articles by Lascano, R. J.
Agricola
Right arrow Articles by Bronson, K. F.
Right arrow Articles by Lascano, R. J.
Related Collections
Right arrow Cotton
Right arrow Plant Nutrition
Right arrow Soil History
Published in Soil Sci. Soc. Am. J. 67:1439-1448 (2003).
© 2003 Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA

DIVISION S-4—SOIL FERTILITY & PLANT NUTRITION

In-Season Nitrogen Status Sensing in Irrigated Cotton

II. Leaf Nitrogen and Biomass

Kevin F. Bronson*, Teresita T. Chua, J. D. Booker, J. Wayne Keeling and Robert J. Lascano

Texas A&M Univ. Texas Agricultural Experiment Station, RR 3, Box 219, Lubbock, TX 79403

* Corresponding author (k-bronson{at}tamu.edu).

Pre-plant soil NO-3–N tests and petiole NO-3–N analysis are bases for Upland cotton (Gossypium hirsutum L.) N management in the western USA. Alternative approaches include proximal multispectral reflectance sensing and chlorophyll meter readings. Our objective was to determine if spectral reflectance and chlorophyll meter measurements correlate with cotton leaf N and biomass. Urea ammonium nitrate was applied after emergence and with low energy precision (LEPA) center-pivot, surface or subsurface drip irrigation water up to peak bloom. Multispectral reflectance readings 0.5 m above the canopy, chlorophyll meter readings, and biomass samplings were taken at early squaring, early bloom, and peak bloom for 3 site-years in Lubbock, TX and Ropesville, TX. Green vegetative indices (GVI) and green normalized difference vegetative indices (GNDVI) calculated from reflectance data generally correlated better with leaf N and leaf N accumulation than did red vegetative indices (RVI) and red normalized difference vegetative indices (RNDVI). Biomass and lint yield correlated more often with red-based indices than green-based indices. Chlorophyll meter readings correlated with leaf N as often as GVI and GNDVI did. Biomass, however was poorly related to chlorophyll meter readings. These results demonstrate the effectiveness of GVI, GNDVI, and chlorophyll meter readings in assessing leaf N, and RVI and RNDVI in assessing cotton biomass. However, we recommend converting vegetative indices or chlorophyll meter readings to sufficiency indices, which are calculated from indices or readings relative to well-fertilized plots. Sufficiency indices were able to successfully predict little or no need for in-season N fertilizer in the low-yielding 2000 crops (sufficiency index > 0.95), and predicted greater need of N fertilizer in the high-yielding 2001 crop (sufficiency index < 0.95).

Abbreviations: ET, evapotranspiration • GNDVI, green normalized difference vegetative index • GVI, green vegetative index • LEPA, Low energy precision application irrigation • NDVI, normalized difference vegetative index • NIR, near infrared • RNDVI, red normalized difference vegetative index • RVI, red vegetative index




This article has been cited by other articles:


Home page
jashsHome page
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]


Home page
Agron. J.Home page
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]


Home page
Agron. J.Home page
B. L. Ma, K. D. Subedi, and C. Costa
Comparison of Crop-Based Indicators with Soil Nitrate Test for Corn Nitrogen Requirement
Agron. J., March 1, 2005; 97(2): 462 - 471.
[Abstract] [Full Text] [PDF]


Home page
Soil Sci.Home page
T. T. Chua, K. F. Bronson, J. D. Booker, J. W. Keeling, A. R. Mosier, J. P. Bordovsky, R. J. Lascano, C. J. Green, and E. Segarra
In-Season Nitrogen Status Sensing in Irrigated Cotton: I. Yields and Nitrogen-15 Recovery
Soil Sci. Soc. Am. J., September 1, 2003; 67(5): 1428 - 1438.
[Abstract] [Full Text] [PDF]




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
The SCI Journals Agronomy Journal Crop Science
Vadose Zone Journal Journal of Plant Registrations
Journal of Natural Resources
and Life Sciences Education
Journal of
Environmental Quality
Copyright © 2003 by the Soil Science Society of America.