A single-wavelength spectral-imaging-based Thai jasmine rice breed identification is demonstrated. Our nondestructive identification approach relies on a combination of fluorescent imaging and simple image processing techniques. Especially, we apply simple image thresholding, blob filtering, and image subtracting processes to either a 545 or a $575\mathrm{nm}$ image in order to identify our desired Thai jasmine rice breed from others. Other key advantages include no waste product and fast identification time. In our demonstration, UVC light is used as our exciting light, a liquid crystal tunable optical filter is used as our wavelength seclector, and a digital camera with $640\mathrm{active}\mathrm{pixels}\times 480\mathrm{active}\mathrm{pixels}$ is used to capture the desired spectral image. Eight Thai rice breeds having similar size and shape are tested. Our experimental proof of concept shows that by suitably applying image thresholding, blob filtering, and image subtracting processes to the selected fluorescent image, the Thai jasmine rice breed can be identified with measured false acceptance rates of $<22.9\%$ and $<25.7\%$ for spectral images at 545 and $575\mathrm{nm}$ wavelengths, respectively. A measured fast identification time is $25\mathrm{ms}$ , showing high potential for real-time applications.