178
Views
3
CrossRef citations to date
0
Altmetric
Original Articles

EFFECTS OF NITROGEN FERTILIZATION ON THE BIOCHEMICAL AND PHYSIOLOGICAL PARAMETERS IN LEAVES AND ROOT OF SUGAR BEET ASSOCIATED WITH AZOTOBACTER CHROOCOCCUM

, , , &
Pages 15-26 | Received 18 Jan 2008, Accepted 12 Oct 2008, Published online: 07 Dec 2009
 

Abstract

A field experiment was conducted to investigate the effect of nitrogen (N) application on the growth and metabolism of sugar beet (Beta vulgaris L.). Changes in nitrate, ammonium, soluble protein and pigment levels, nitrogen metabolism enzyme activity, biomass of leaves and beet, and sucrose and α-amino-N were studied in relation to five different NPK application rates (0, 50, 100, 150, and 200 kg N ha−1) and association with Azotobacter chrooccocum. The availability of nitrate and ammonium ions in the leaves proved to be influenced by the different nitrogen treatments. The most important enzymatic activities within nitrogen metabolism were affected negatively by the highest NPK rate. With increasing nitrogen supply, the concentration of α-amino-N increased considerably and that of sucrose decreased. Application of NPK had a significant positive effect on the growth and biomass production. The measured parameters of plants associated with A. chrooccocum were of similar magnitude comparing to the controls.

ACKNOWLEDGMENT

This work was founded by the Ministry for Science and Environmental Protection of the Republic of Serbia.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 495.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.