Abstract: Nanoelectrospray ionization (NanoESI) is a highly sensitive mass spectrometry ionization technique, which has been widely used in life science, drug analysis and other fields. Compared with conventional ESI technology, NanoESI has higher sample utilization and desolvation efficiency, mainly due to its smaller spray needle inner diameter (usually 1-10 μm) and lower injection rate (usually in the level of nL/min), which enables the sample to form smaller charged droplets and more easily further convert into ions. However, in practical application, the spray morphology of NanoESI is susceptible to environmental disturbances such as temperature, humidity, and background air flow rate, resulting in a significant decrease in the stability of mass spectrum signal, which is one of the main bottlenecks limiting its performance. In order to improve the desolvation stability of NanoESI, an automatic spray control system based on machine vision technology was proposed to achieve the optimal desolvation efficiency of NanoESI. The system consists of three core modules, including a desolvation efficiency verification module, an image processing module, and a feedback control module. In the desolvation efficiency verification module, a series of experiments were carried out with a self-made verification device to determine the spray morphology when the desolvation efficiency was optimal. The image processing module used reflectivity image recognition algorithm based on channel difference prior to realizing real-time monitoring and effective extraction of spray morphology. By analyzing the reflectance difference between the spray region and the air, the algorithm combined with morphological processing method can accurately identify the morphological characteristics of the spray. The feedback control module adjusted NanoESI’s injection rate, excitation voltage and other parameters in real time through PID control algorithm, so as to achieve automatic optimization and stabilization of spray morphology. The experimental results showed that the system can greatly reduce the NanoESI spray morphology change rate (37.41%) and significantly improve the stability of mass spectrum signal (32.33%), and the average response time is only 0.02 s. The results of this study provide an effective solution for further improving the application of NanoESI in complex environments, and a new idea for the development of related techniques. The successful development of the system not only solves the key problems of NanoESI technique in practical application, but also provides a reference for the automatic control of other precision analytical instruments. In the future, this technique is expected to play a role in the frontier research field of mass spectrometry analysis technology, and promotes the development of mass spectrometry technology to higher sensitivity and higher stability.