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ASSESSING NITROGEN NUTRITIONAL STATUS, BIOMASS AND YIELD OF COTTON WITH NDVI, SPAD AND PETIOLE SAP NITRATE CONCENTRATION

Published online by Cambridge University Press:  19 June 2017

GUISU ZHOU  and
XINHUA YIN
GUISU ZHOU
Affiliation:
College of Tobacco Science, Yunnan Agricultural University, Kunming, Yunnan 650201, China Department of Plant Sciences, The University of Tennessee, 605 Airways Blvd., Jackson, TN 38301, USA
XINHUA YIN*
Affiliation:
Department of Plant Sciences, The University of Tennessee, 605 Airways Blvd., Jackson, TN 38301, USA
*
§Corresponding author. Email: xyin2@utk.edu
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Summary

Canopy normalized difference vegetation index (NDVI), soil plant analysis development (SPAD) reading and petiole sap NO3−‒N concentration are increasingly used as quick and non-destructive methods to monitor plant N nutrition and growth status and predict yield of crops. However, little information is available on the comparisons of these three methods in assessing N nutrition, growth and yield for cotton (Gossypium hirsutum L.). Four N rates (0, 34, 67 and 101 kg N ha−1) under two cover conditions [no cover crop and hairy vetch (Vicia villosa) crop] in a 33-year long-term field trial were used to evaluate how canopy NDVI, SPAD reading (related to chlorophyll content) and petiole sap NO3−‒N concentration (conventional method) are able to assess N nutrition and plant biomass and predict yield for cotton. Canopy NDVI and SPAD readings responded less sensitively to N rates than petiole sap NO3−‒N. The responses of NDVI and SPAD reading to N rates were generally reduced due to the winter cover crop with hairy vetch. Significant and positive correlations existed mostly among NDVI, SPAD reading, and petiole sap NO3−‒N concentration. Canopy NDVI during mid-bloom to late bloom and SPAD reading during early bloom to late bloom were effective alternative methods for assessing cotton N nutrition status. The SPAD reading at late bloom was an effective parameter to estimate cotton biomass. The NDVI at early square and SPAD reading during early square to mid-bloom were effective for cotton yield prediction.

Type
Research Article
Information
Experimental Agriculture , Volume 54 , Issue 4 , August 2018 , pp. 531 - 548
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Copyright
Copyright © Cambridge University Press 2017 

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