Arsenic toxicity of humans due to consumption of arsenic-contaminated rice is an international health crisis. Arsenic is often supplied through water from shallow wells used for irrigation of rice. Reduced soil conditions present in flooded rice fields enable the arsenic to be converted to a form that is easily taken-up by the plants.
Arsenic levels causing injury to the rice plant may be detectable via remote-sensing methods.
Hyperspectral image data can be processed to detect materials that may not typically be distinguished by multispectral remote sensors, and plant canopy biophysical/chemical properties can also more accurately be estimated via hyperspectral data, relative to multispectral data, which is useful for stress detection.
Anthony Filippi and Burak Güneralp (Dept. of Geography, Texas A&M University, College Station, TX), and Lee Tarpley (Texas A&M AgriLife Research Center, Beaumont, TX) are employing close-range, hyperspectral imaging via a SOC710-VP HS-Portable Spectral Imaging System from Surface Optics Corp. This research, which is supported by the Ocean Optics Blue Ocean Grant program, offers the potential to enable remote detection of arsenic-contaminated rice, thus possibly minimizing arsenic-contaminated rice entering food products and adversely affecting human health.
Anthony Filippi and Burak Güneralp (Dept. of Geography, Texas A&M University, College Station, TX), and Lee Tarpley (Texas A&M AgriLife Research Center, Beaumont, TX) are employing close-range, hyperspectral imaging via a SOC710-VP HS-Portable Spectral Imaging System from Surface Optics Corp. This research, which is supported by the Ocean Optics Blue Ocean Grant program, offers the potential to enable remote detection of arsenic-contaminated rice, thus possibly minimizing arsenic-contaminated rice entering food products and adversely affecting human health.