Submitted to: Crop Protection Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 18, 2007
Publication Date: January 15, 2008
Citation: Yang, C., Everitt, J.H., Liu, T. 2008. Estimating cabbage physical parameters using remote sensing technology. Crop Protection Journal. 27:25-35.
Interpretive Summary: Ground surveys and measurements are commonly used to evaluate the effectiveness of different cultural practices and chemical control methods for cabbage production. This study examined remote sensing techniques, including aerial photography and ground reflectance spectra, for estimating cabbage physical parameters. Statistical analysis showed that cabbage physical parameters such as plant diameter and head weight were significantly related to photo-derived plant area and ground reflectance data. These results indicate that remote sensing could be a useful tool for evaluating cabbage growth and yield variations and for assessing the efficacies of different insecticide treatments for controlling cabbage insects.
Remote sensing has long been used as a tool to extract plant growth and yield information for many crops, but little research has been conducted on cabbage (Brassica oleracea) with this technology. The objective of this study was to evaluate aerial photography and field reflectance spectra for estimating cabbage physical parameters. An experiment was conducted on a cabbage field with 81 experimental plots to which different insecticide treatments were applied. Aerial color-infrared (CIR) photographs were taken from the field shortly before harvest. Meanwhile, field reflectance spectra and plant physical parameters, including plant diameter, head diameter, plant weight and head weight, were measured from a total of 243 plants (three plants per plot). Plant area and digital values for the near-infrared, red and green bands for each of the 243 plants were extracted from a digitized aerial CIR photograph. Four different vegetation indices, including the normalized difference vegetation index (NDVI), were calculated. Correlation analysis showed that the cabbage physical parameters were significantly related to the photo-derived plant area and spectral variables. Regression analysis showed that head weight was linearly related to plant area with an r-squared value of 0.91 and quadratically related to NDVI with an r-squared value of 0.66. Stepwise regression performed on cabbage head weight and 601 bands from 400 to 1000 nm in the field reflectance spectra revealed that 71% of the variability in head weight could be explained by eight significant bands in the spectra. These results indicate that remote sensing can be a useful tool for evaluating cabbage growth and yield variations.