2013 Annual Report
1a.Objectives (from AD-416):
The overall objective is to develop high throughput (~75 samples/s), economically feasible sorting devices for specialty crop product streams. The means for detection will include sensors and/or imaging coupled with algorithm development that differentiates good product from defective, contaminated, or otherwise undesirable product. Sorting devices based on these techniques may be high-speed and non-destructive for mass inspection or as an aid in the sampling and grading process. Specific objectives over the period covered by this project plan are: Detect insect damage in almonds; Detect fungal infestation in walnuts; Detect Olive fly infestation in olives and; Sort shells and kernels in the pistachio nut process stream.
1b.Approach (from AD-416):
1) Appropriate methodologies will be developed to create samples of the product defect to be identified in sufficient quantity for sorter and algorithm development..
2)Using primarily x-ray and color camera imaging technology features will be identified that distinguish undesirable product from good product..
3) Automatic algorithms will be developed to extract the identified features from images in real-time..
4)Material handling systems will be developed to allow construction of prototype sorting devices based on 1 through 3 above..
5)Prototype testing will be conducted to demonstrate the feasibility of implementing the technology in processing plant environments.
Considerable progress has been made towards achieving each objective over the course of the present reporting period. Much of the work has been published, in print, or under preparation. Some of the major progress includes: for almonds, X-ray has been abandoned in favor of near infrared (NIR), in which calibration and testing are complete; for walnuts, NIR has provided good results with respect to detecting fungal infections; for olives, a prototype X-ray-based sorting device is under construction; and, for pistachios very high accuracy sorting has been achieved. An initial single channel prototype sorting device has been built and a more sophisticated four-channel version is under construction.
Sorter for separating in-shell pistachios from kernels. Pistachio nuts are sorted into various process streams, including one for kernels with no shells. The presence of shells or shell fragments in the kernel stream is a major concern for processors, retailers, and consumers. Researchers at ARS in Albany, California, have developed an economical and efficient method and device for sorting kernels from shells based on the reflection of light at a single wavelength. This device has the potential to alleviate the effort and cost of manual sorting of these pistachio streams.
Haff, R.P., Pearson, T.C., Jackson, E.S. 2013. One dimensional Linescan x-ray detection of pits in fresh cherries. American Journal of Agricultural Science and Technology. 1:18-26.
Haff, R.P., Saranwong, S., Thanapase, W., Janhiran, A., Kasemsumran, S., Kawano, S. 2013. Automatic image analysis and spot classification for detection of fruit fly infestation in hyperspectral images of mangoes. Postharvest Biology and Technology. 86:23-28.
Moscetti, R., Haff, R.P., Sayes, W., Monarca, D., Cecchini, M., Massintini, R. 2013. Detection of flaws in hazelnuts using VIS/NIR spectroscopy. Journal of Food Engineering. 118:1-7.
Saranwong, S., Ikehata, A., Noguchi, G., Park, S., Sashida, K., Okura, T., Haff, R.P., Kawano, S. 2013. Development of a low-cost NIR instrument for minced meat analysis: Part 1 - Spectrophotometer and sample presentations. American Journal of Agricultural Science and Technology. 2:61-68.