1) Adopting advanced and mature imported sensors, it has multiple advantages such as high sensitivity, high signal-to-noise ratio, high speed, and high stability;

2) The sample model established using full penetration detection technology and a new dynamic modeling method is more realistic and effective. At the same time, multi-dimensional model coupling algorithm and neural network algorithm are used, and big data and deep learning methods are innovatively used to continuously optimize the model;

3) It can be used to detect internal physiological indicators such as sugar content, mold heart disease, and water heart disease.

1) Using multiple high-resolution industrial camera lenses and a specially designed LED light source system for all-round data acquisition;

2) Using Gaussian Laplace mixture model algorithm to solve object detection in high-speed dynamic backgrounds. Using UV, H chromatography, and grayscale segmentation techniques for color recognition;

3) It can be used to detect external quality indicators such as fruit shape, color, and defects of fruits.

1) Using imported high-speed and high-precision sensors, with a high-speed dynamic measurement of up to 1600 times per second, and four levels of effective filtering, ensuring fast and accurate weight readings;

2) Using a single sensor and a specially designed fruit cup, with four point contact, to avoid measurement errors caused by mechanical vibration issues;

3) Unique dynamic calibration and temperature compensation functions to avoid measurement errors caused by environmental differences.

1) Using 3D visual imaging technology for all-round data collection, combining external quality features and quality information to obtain density information;

2) Can be used to detect fruits that are dry and dehydrated.