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In view of the current problem that apple picking operations are mainly manual picking, and the quality and efficiency of mechanised picking are not high, an apple picking robot monitoring system is proposed. The monitoring system completes the monitoring of the whole process from pre-harvest environmental monitoring to post-harvest quality monitoring through four modules: plantation environment, robot operation status, robot operation quality and background monitoring system. At the same time, in order to monitor the quality of apples after picking, a method for detecting apple surface defects based on Mo-M2Det is proposed. With the aim of reducing the amount of parameters and calculations, the M2Det target detection network is improved to achieve lightweight and high-precision detection. The experimental results show that the detection accuracy of the improved M2Det target detection network has reached 98.45%,and the number of model parameters has been reduced by 56.3%. In practical application, the improved lightweight network model has a good detection effect on the detection platform.