Table of Contents
ISRN Agronomy
Volume 2013 (2013), Article ID 816767, 10 pages
Research Article

Spectral Indices: In-Season Dry Mass and Yield Relationship of Flue-Cured Tobacco under Different Planting Dates and Fertiliser Levels

1Department of Crop Science, University of Zimbabwe, Harare, Zimbabwe
2Department of Geography and Environmental Studies, University of Zimbabwe, Harare, Zimbabwe
3Tobacco Research Board/Kutsaga Research Station, Harare, Zimbabwe

Received 18 July 2013; Accepted 13 August 2013

Academic Editors: O. Ferrarese-Filho and J. Hatfield

Copyright © 2013 Ezekia Svotwa et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This experiment investigated the relationship between tobacco canopy spectral characteristics and tobacco biomass. A completely randomized design, with plantings on the 15th of September, October, November, and December, each with 9 variety × fertiliser management treatments, was used. Starting from 6 weeks after planting, reflectance measurements were taken from one row, using a multispectral radiometer. Individual plants from the other 3 rows were also measured, and the above ground whole plants were harvested and dried for reflectance/dry mass regression analysis. The central row was harvested, cured, and weighed. Both the maximum NDVI and mass at untying declined with later planting and so was the mass-NDVI coefficient of determination. The best fitting curves for the yield-NDVI correlations were quadratic. September reflectance values from the October crop reflectance were statistically similar (), while those for the November and the December crops were significantly different () from the former two. Mass at untying and NDVI showed a quadratic relationship in all the three tested varieties. The optimum stage for collecting spectral data for tobacco yield estimation was the 8–12 weeks after planting. The results could be useful in accurate monitoring of crop development patterns for yield forecasting purposes.