The quality of fresh fruits and vegetables is of paramount interest to consumers. There is a huge demand for alternatives to conventional disruptive quality analysis methods in anticipation of quick, accurate, multiple repetitive assessments with huge data, and non-destructive quality monitoring techniques are finding applications in the supply chain management of fruits and vegetables. The non-destructive quality monitoring techniques have proved crucial for checking freshness, assurance of nutritive value retention, ensuring safety, and optimizing processing and storage capabilities. Various non-destructive techniques such as Computer vision and Convolutional neural network models, Fluorescence spectroscopy, Fourier transform infrared, Raman spectroscopy, Visible/Near-Infrared Spectroscopy, Acoustic Impulse Response Method, X-ray radiography, Ultrasound Imaging, Electrical Impedance Spectroscopy, Electronic Nose, Hyperspectral Imaging, Thermal imaging, Magnetic Resonance Imaging, Capacitive sensing and Artificial intelligence models along with their working principles, merits and demerits are reviewed in this book chapter.