Abstract: A system comprising: at least one hardware processor; and a non-transitory computer-readable storage medium having stored thereon program instructions, the program instructions executable by the at least one hardware processor to: receive, as input, spectral image data representing spectral reflectance associated with at least one plant, calculate a first and second chlorophyll fluorescence indices in respective first and second wavelength bands, based, at least in part, on said spectral reflectance, and derive a quantum yield value with respect to said at least one plant, by: (i) dividing said first chlorophyll fluorescence index in a sum of said first and second chlorophyll fluorescence indices, and (ii) multiplying (i) by a vegetation index value associated with said at least one plant.

Abstract: A method comprising: receiving, as input, a plurality of spectral data samples, wherein each of the spectral data samples represents spectral reflectance from a plant; at a training stage, training a machine learning model on a training set comprising: (i) the spectral data samples, and (ii) labels associated with stomatal conductance in each of the plants; and at an inference stage, applying the machine learning model to a target spectral data sample associated with a target plant, to predict a stomatal conductance value for the target plant.

Abstract: A system comprising: at least one hardware processor; and a non-transitory computer-readable storage medium having stored thereon program instructions, the program instructions executable by the at least one hardware processor to: receive, as input, spectral image data representing spectral reflectance associated with at least one plant, calculate a first and second chlorophyll fluorescence indices in respective first and second wavelength bands, based, at least in part, on said spectral reflectance, and derive a quantum yield value with respect to said at least one plant, by: (i) dividing said first chlorophyll fluorescence index in a sum of said first and second chlorophyll fluorescence indices, and (ii) multiplying (i) by a vegetation index value associated with said at least one plant.