Title

Corn (Zea mays L.) Growth, Leaf Pigment Concentration, Photosynthesis and Leaf Hyperspectral Reflectance Properties as Affected by Nitrogen Supply

Document Type

Article

Publication Date

11-1-2003

Department

Biological Sciences

Abstract

Plant nitrogen (N) deficiency often limits crop productivity. Early detection of plant N deficiency is important for improving fertilizer N-use efficiency and crop yield. An experiment was conducted in sunlit, controlled environment chambers in the 2001 growing season to determine responses of corn (Zea mays L. cv. 33A14) growth and leaf hyperspectral reflectance properties to varying N supply. Four N treatments were: ( 1) half-strength Hoagland's nutrient solution applied throughout the experiment (control); (2) 20% of control N starting 15 days after emergence (DAE); (3) 0% N starting 15 DAE; and (4) 0% N starting 23 DAE (0% NL). Plant height, the number of leaves, and leaf lengths were examined for nine plants per treatment every 3 - 4 days. Leaf hyperspectral reflectance, concentrations of chlorophyll a, chlorophyll b, and carotenoids, leaf and canopy photosynthesis, leaf area, and leaf N concentration were also determined during the experiment. The various N treatments led to a wide range of N concentrations (11 - 48 g kg(-1) DW) in uppermost fully expanded leaves. Nitrogen deficiency suppressed plant growth rate and leaf photosynthesis. At final harvest ( 42 DAE), plant height, leaf area and shoot biomass were 64 - 66% of control values for the 20% N treatment, and 46-56% of control values for the 0% N treatment. Nitrogen deficit treatments of 20% N and 0% N ( Treatment 3) could be distinguished by changes in leaf spectral reflectance in wavelengths of 552 and 710 nm 7 days after treatment. Leaf reflectance at these two wavebands was negatively correlated with either leaf N ( r = - 0.72 and - 0.75**) or chlorophyll ( r = - 0.60 and - 0.72**) concentrations. In addition, higher correlations were found between leaf N concentration and reflectance ratios. The identified N-specific spectral algorithms may be used for image interpretation and diagnosis of corn N status for site-specific N management.

Publication Title

Plant and Soil

Volume

257

Issue

1

First Page

205

Last Page

217