We propose spectral imaging methods for estimating fluorescence spectra emitted from plant grains and leaves. Two types of multiband imaging systems with six channels are constructed using ordinary off-the-shelf cameras; the first of these is for rice grains, wherein a mobile phone camera is rendered multiband to detect fluorescence emission in the visible wavelength region; the second one is for plant leaves, wherein a monochrome camera is used with additional optical filters to detect chlorophyll fluorescence in the red to far-red wavelength region. A statistical approach, inspired by the Wiener estimator is developed to estimate fluorescence emission from the image data. Here, the observations are modeled by accounting for noise in the imaging system, and the incident fluorescence spectra to the system are estimated from the observed image data. The noise variance is estimated on the basis of the fluorescence spectrum measurement. In the experiments, UV-light is used to illuminate real rice grains and green leaves; the emitted fluorescence spectra are estimated, and the reliability of the proposed methods is demonstrated.