Abiotic stresses such as salinity affect rice yield components and grain quality. A new, automated methodology is presented to analyze grain weight, length and width distributions for grain samples. Frequency distribution analyses on the basis of histograms generally gave bimodal patterns for grain weight (filled and unfilled grains) and monomodal patterns for grain dimensions. These histograms permit the distinction of unfilled, partially filled and fully filled grains. Peak shape and location on the histogram provide further information potentially useful for the diagnostics of physiological stresses affecting grain hull development, spikelet fertility and filling, and may be of value in breeding and grain quality research. The methodology was applied to rice grain samples taken from farmers' fields having different levels of soil salinity in the Camargue delta region in France. High salinity levels were associated with an increased fraction of unfilled spikelets and reduced grain dimensions and weight, which point at salinity affects taking place largely before flowering during hull development. The methodology is being completed with a biometric tool for histogram analysis, and will be extended to other stresses and germplasm.