Abstract:84.42%The relationship between the yield of a wheat spike and its image texture features was investigated with image processing technology. The spike images were obtained by a digital camera and processed with Matlab. The spike textures described with the mean value, standard deviation, smoothness, third moment, consistency and entropy were extracted based on gray level statistical properties of the spike image and the relationship between wheat spike yield and its image texture features was established by means of multiple linear-regression method. For the given breed named wheat 9918, the experimental results showed that the kernel yield of the wheat spike and its image texture features are significantly correlated with the confidence of 95% and correlative coefficient of 0.980 7. Using established model, wheat spike yield could be predicted with relative error less than 15% for 84.42% samples.