IN-SEASON ASSESSMENT OF WHEAT CROP HEALTH USING VEGETATION INDICES BASED ON GROUND MEASURED HYPER SPECTRAL DATA
- 1 Department of Agricultural Engineering, Precision Agriculture Research Chair, College of Food and Agriculture Sciences, King Saud University, Riyadh, Saudi Arabia
- 2 Precision Agriculture Research Chair, King Saud University, Riyadh, Saudi Arabia
Abstract
An experiment on a 50 ha center pivot field was conducted to determine the Vegetation Indices (VI’s) that were helpful in assessing the in-season performance of wheat crop treated with graded levels of irrigation water and fertilizers. The irrigation levels were at 100, 90, 80 and 70% evapotranspiration (ETc); however, the fertilizer levels of N: P: K kg-1ha included 300:150:200 (low); 400:250:300 (medium) and 500:300:300 (High). The crop was sown on January 1st and harvested on May 9th, 2012. Temporal data on biophysical parameters and reflectance of the crop in hyper spectral bands (350-2500 nm) were collected at booting and ripening growth stages (February 17th and April 5th, 2012). Results of the study revealed that many of the tested spectral indices showed significant response to irrigation levels. Out of those, only two spectral indices (Plant Senescence Reflectance Index ’PSRI’ and Photochemical Reflectance Index ’PRI’) also exhibited significant response to fertilizer levels. The Middle Infrared-Based Vegetation Index (MIVI) showed a significant response to the irrigation levels for both sampling dates. Among the tested spectral indices, Normalized Difference Infrared Index (NDII) and Normalized Difference Nitrogen Index (NDNI) exhibited the highest correlation to crop Leaf Area Index (LAI). Five indices showed the most response to wheat grain yield. These indices included Near Infrared band (NIR), Water Band Index (WBI), Normalized Water Index-1 (NWI-1), Normalized Water Index-3 (NWI-3) and Normalized Water Index-4 (NWI-4).
DOI: https://doi.org/10.3844/ajabssp.2014.138.146
Copyright: © 2014 Khalid Ali Al-Gaadi, Virupakshagouda Patil, ElKamil Tola, Rangaswamy Madugundu and Samy Marey. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Remote Sensing
- Spectral Reflectance
- Vegetation Indices
- Wheat