Design and test of portable comprehensive quality non-destructive detector for grape bunches based on spectrum

Based on the analysis technology of visible/near infrared diffuse reflectance spectroscopy a portable and nondestructive detector was designed to test comprehensive quality of red globe grape bunches in the growth period.The detector included spectrum acquisition probe,spectrometer,lithium battery,halogen lamp light source,advanced RISC machines(ARM)board and peripheral circuit.Based on microsoft foundation classes(MFC)development tool,the real-time analysis and processing software of the detector was written by C++language.The optimal partial least squares regression(PLSR)detection model of multi-quality parameters was implanted into the hardware device.This paper selected the red globe grapes bunches in the growth period as the research samples,collected the visible/near infrared diffuse reflectance spectrum information,and then used the established PLSR model to detect the soluble solid content(SSC),total acid(TA)and pH of the samples to generate comprehensive quality parameter.So as to realize the nondestructive detecting of comprehensive quality of red globe grapes bunches in the growth period.In conclusion,the detector could realize real-time and non-destructive detecting of red globe grapes bunches in growth period aiming at the comprehensive quality.

Grape size detection and online gradation based on machine vision

This research investigated the size detecting and online grading of Red Globe grapes using images of entire cases,rather than individual grapes.Method of ellipse fitting based on iterative least median squares was proposed and the process of grape grading includes the following four steps:stem removal from the RGB and NIR images collected by the 2-CCD camera;edge extraction by multiple methods of edge detection,image binarization,morphological processing,et al.;size determination of individual grapes by using image segmentation and ellipse fitting to calculate short axis length;Finally,grading based on the 15%downgrade principle,this means that if the case contains more than 15%of multiple grades,then the case is re-evaluated.Thirty-eight cases of Red Globe grapes were graded using these methods and 35 cases were correctly graded with an accuracy rate reaching 92.1%.The results showed that the accuracy and speed meet the requirements of grape automatic online detection.