Abstract: Non-destructive detection of fruit maturity is crucial for reducing unnecessary losses during fruit production, transportation, and storage. Traditional methods for assessing fruit maturity include empirical judgment, destructive testing, and non-destructive testing. Empirical judgment and destructive testing often suffer from low efficiency, inadequate accuracy, or cause sample damage.In recent years, non-destructive detection technologies, such as near-infrared spectroscopy, hyperspectral imaging, machine vision, fluorescence sensing, acoustic vibration, electrical properties, tactile sensing, and electronic noses, have rapidly developed. These technologies can precisely evaluate fruit maturity by measuring key parameters closely related to maturity, such as color, hardness, sugar-acid ratio, and volatile gases.This study reviews the principles of these non-destructive technologies and their current applications. It categorizes common fruit characteristics based on the core parameters that influence maturity, such as respiratory jump, color gradient, texture sensitivity, and aroma markers. It also summarizes the detection methods commonly used for different types of fruit.Additionally, the study identifies common challenges in this field, including significant environmental interference, difficulty in simultaneous multi-parameter detection, and lack of standardized systems. Finally, the study discusses potential future developments, including the integration of miniaturized multimodal sensors, the standardization of detection data, and the deeper integration of artificial intelligence with sensor systems.

Key words: Non-destructive testing, Fruit ripeness, multimodal fusion, Sensors