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. |
Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.
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