Page Banner

United States Department of Agriculture

Agricultural Research Service

Related Topics

Research Project: TECHNOLOGIES FOR ASSESSING AND GRADING QUALITY AND CONDITION OF CUCUMBERS AND TREE FRUITS

Location: Sugarbeet and Bean Research

Project Number: 3635-43000-004-00
Project Type: Appropriated

Start Date: Sep 19, 2004
End Date: Sep 19, 2009

Objective:
The overall research goal is to develop new and/or improved sensing technologies for rapid, nondestructive assessment and grading of quality and condition of pickling cucumbers and tree fruits, primarily apples and cherries, during preharvest, harvest, and postharvest handling, sorting and processing. Specific objectives are to: 1) develop new techniques and systems for assessing and grading quality and maturity of apples; 2) develop an optical technique for rapid detection of pits and pit fragments in processed tart cherries; and 3) develop nondestructive sensing methods and techniques for detecting and segregating defective and inferior cucumbers to assure the keeping and processing quality of pickling cucumbers.

Approach:
Imaging spectroscopy will be used for determining the spectral absorption and scattering properties of apple fruit and computer simulations will be developed to quantify light propagation and scattering in apple fruit and its relationship with fruit quality attributes. A prototype sensing system will be developed, using multispectral imaging technique, for grading apple fruit for firmness and soluble solids content. A new technique of combining hyperspectral reflectance and fluorescence will be developed to measure apple fruit maturity. A rapid sensing technique and system, using hyperspectral and/or multispectral transmission imaging, will be developed for detecting pits and pit fragments in processed tart cherries. Hyperspectral and/or multispectral reflectance and fluorescence imaging techniques will be used to detect defective cucumbers resulting from mechanical stress, temperature chilling, physiological disorder and diseases. Image processing algorithms, using artificial neural networks and statistical classification methods, will be developed and incorporated into a hyperspectral/multispectral imaging system for real-time sorting of defective pickling cucumbers. Near-infrared spectroscopy and/or imaging spectroscopy in transmission and reflectance modes will be used for measuring the keeping and processing quality of pickling cucumbers.

Last Modified: 9/10/2014
Footer Content Back to Top of Page