Submitted to: American Society of Agricultural Engineers Meetings Papers
Publication Type: Abstract Only
Publication Acceptance Date: 7/29/2001
Publication Date: N/A
Citation: N/A Interpretive Summary:
Technical Abstract: Development of an automated bruise detection system will help the industry and the retailer by providing superior fruit for the consumer and reducing potential economic losses. The objective of this research was to investigate the potential of near-infrared (NIR) hyperspectral imaging for detecting bruises on apples in the spectral region between 900 nm and 1700 nm. A NIR hyperspectral imaging system was developed and a computer algorithm was created to detect both new and old bruises on apples. Experiments were conducted to collect hyperspectral images from individual apple fruit over a period of 47 days after each fruit was bruised with different degrees of bruises. Results showed that bruise features changed over time from lower reflectance to higher reflectance and the rate of the change was variety dependent. The spectral region between 1000 nm and 1340 nm was most appropriate for bruise detection. Using both principal component and minimum noise fraction transforms, the system was able to detect both new and old bruises, with the correct detection rate from 62% to 88% for Red Delicious apples and from 59% to 94% for Golden Delicious apples. The optimal number of spectral bands needed for bruise detection was between 20 and 40 with the corresponding spectral resolution between 8 and 17 nm. This research shows that NIR hyperspectral imaging offers great potential for effective detection of bruises and other surface defects on apples. With the improvement in image acquisition speed and detector technology, the NIR hyperspectral imaging technique can be used for on-line sorting of fruit for surface defects such as bruises. This would improve sorting efficiency and enhance fruit quality; thus, leading to savings in labor costs and the increased profitability of growing apples.