The article discusses how receptor noise influences color thresholds in visual systems. It argues that psychophysical thresholds can only reliably indicate mechanisms at a particular stage of the visual pathway if the noise at that stage dominates other noise sources. The study models color vision using color opponency mechanisms, which are limited by photoreceptor noise, and shows that the achromatic signal is disregarded. This model predicts color vision performance in animals where physiological and anatomical data are available, but without direct measurements of perceptual thresholds. The model is widely applicable for comparative studies of eye design and visual ecology. The model assumes that color is coded by n-1 unspecified color opponent mechanisms, and that thresholds are set by receptor noise, not by opponent mechanisms. It is based on three assumptions: (1) color is coded by n-1 unspecified color opponent mechanisms; (2) color opponent mechanisms give zero signal for stimuli that differ from the background in intensity only; and (3) thresholds are set by receptor noise, not by opponent mechanisms. The model is used to predict threshold spectral sensitivity for various animals, including humans, tree shrews, ground squirrels, honeybees, and birds. The model agrees with experimental data for some animals, but not all, particularly in dim light or for animals with different photoreceptor types. The study concludes that receptor noise limits the accuracy of color vision in photopic conditions, and that the model is a simple and physiologically plausible way to predict color discrimination in any animal where spectral sensitivities and relative numbers of photoreceptors are known.The article discusses how receptor noise influences color thresholds in visual systems. It argues that psychophysical thresholds can only reliably indicate mechanisms at a particular stage of the visual pathway if the noise at that stage dominates other noise sources. The study models color vision using color opponency mechanisms, which are limited by photoreceptor noise, and shows that the achromatic signal is disregarded. This model predicts color vision performance in animals where physiological and anatomical data are available, but without direct measurements of perceptual thresholds. The model is widely applicable for comparative studies of eye design and visual ecology. The model assumes that color is coded by n-1 unspecified color opponent mechanisms, and that thresholds are set by receptor noise, not by opponent mechanisms. It is based on three assumptions: (1) color is coded by n-1 unspecified color opponent mechanisms; (2) color opponent mechanisms give zero signal for stimuli that differ from the background in intensity only; and (3) thresholds are set by receptor noise, not by opponent mechanisms. The model is used to predict threshold spectral sensitivity for various animals, including humans, tree shrews, ground squirrels, honeybees, and birds. The model agrees with experimental data for some animals, but not all, particularly in dim light or for animals with different photoreceptor types. The study concludes that receptor noise limits the accuracy of color vision in photopic conditions, and that the model is a simple and physiologically plausible way to predict color discrimination in any animal where spectral sensitivities and relative numbers of photoreceptors are known.