Predicting agronomic performance of barley using canopy reflectance data

T. G. Fetch, B. J. Steffenson, V. D. Pederson

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

The ability to accurately and rapidly predetermine agronomic performance would be desirable in most plant breeding programs. Remote sensing of canopy reflectance is a quick and nondestructive method that may be useful in the estimation of agronomic performance. Studies were conducted at Fargo and Langdon, North Dakota, to determine the effectiveness of a multispectral radiometer in estimating yield, kernel plumpness (KP), and 1000-kernel weight (TKW) in barley. Canopy reflectance was measured in eight (500-850 nm) discrete narrow-wavelength bands. Three types of reflectance models were evaluated: simple models using one to four wavelengths, simple ratio and normalized difference vegetation indices (NDVI) using green, red, and near-infrared wavelengths, and soil-adjusted vegetation indices (SAVI). The relationship between canopy reflectance and agronomic performance was significantly influenced by environment, growth stage, and plant genotype. Grain yield was best estimated near GS73 (0.84 < R2 < 0.92) at Fargo and at GS83 (0.55 < R2 < 0.81) at Langdon. In contrast, KP and TKW could be estimated at both late (GS83; 0.68 < R2 < 0.93) and early (GS24-GS47; 0.72 < R2 < 0.91) growth stages. The 550-nm and 800-nm wavelengths are critical for development of predictive models. A simple model using 550-nm, 600-nm, and 800-nm from GS47-GS73 gave significant (0.45 < R2 < 0.64) estimation of agronomic performance across all environments. In contrast, simple ratio, NDVI, and SAVI were less effective (0.05 < R2 < 0.77) in predicting agronomic performance. Remote sensing using canopy reflectance is a potential tool to estimate agronomic performance of barley, but genotypic and crop stage factors affect this method. Further studies are needed to improve the usefulness of multispectral radiometry in predicting agronomic performance.

Original languageEnglish (US)
Pages (from-to)1-9
Number of pages9
JournalCanadian Journal of Plant Science
Volume84
Issue number1
DOIs
StatePublished - Jan 2004

Keywords

  • Crop yield
  • Hordeum vulgare
  • Kernel plumpness
  • Remote sensing

Fingerprint Dive into the research topics of 'Predicting agronomic performance of barley using canopy reflectance data'. Together they form a unique fingerprint.

  • Cite this