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ARS Home » Pacific West Area » Albany, California » Western Regional Research Center » Healthy Processed Foods Research » Research » Publications at this Location » Publication #329790

Research Project: New Sustainable Processing Technologies to Produce Healthy, Value-Added Foods from Specialty Crops

Location: Healthy Processed Foods Research

Title: Sorting in-shell walnuts using near infrared spectroscopy for improved drying efficiency and product quality

item WANG, XIAOTUO - University Of California
item ATUNGULU, GRIFFITHS - University Of Arkansas
item GEBREIL, RAGAB - University Of California
item GAO, ZHENJIANG - China Agricultural University
item Pan, Zhongli
item WILSON, SHANTAE - University Of Arkansas
item OLATUNDE, GBENGA - University Of Arkansas
item SLAUGHTER, DAVID - University Of California

Submitted to: International Agricultural Engineering Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/10/2016
Publication Date: 12/14/2016
Citation: Wang, X., Atungulu, G.G., Gebreil, R., Gao, Z., Pan, Z., Wilson, S.A., Olatunde, G., Slaughter, D. 2016. Sorting in-shell walnuts using near infrared spectroscopy for improved drying efficiency and product quality. International Agricultural Engineering Journal. 26(1):165-172.

Interpretive Summary: The moisture content (MC) of individual walnut varies significantly due to uneven maturation in the field. Existing dryers commingle all walnuts regardless of the wide range of their MC. When walnuts with higher MC must be dried longer to safe storage MC, the nuts with lower MC will be over-dried. Over-drying results in a significant waste in energy, prolonged drying time and reduction dried product quality. To overcome the over-drying, it is vital to develop a new method that can be used to sort freshly harvested in-shell walnuts based on their MC during drying. Compared to traditional chemical analyses, near-infrared (NIR) spectroscopy in combination with chemometrics has become an established method for rapid and nondestructive assessment of quality parameters such as moisture content in the food and agricultural sectors. The study indicated feasibility of using NIR spectroscopy to sort walnuts of different shell moisture contents (MC). Ultimately, the new and rapid non-destructive sorting method could be easily implemented to reduce variability within walnuts in each batch loaded into dryers. The reduced variability of the MC of walnuts entering the dryers will result in improved drying efficiency and dried product quality following minimized over- and under-drying of walnuts.

Technical Abstract: In the current walnut drying practice, dryers comingle nuts with varying moisture contents (MC) which results in over drying of nuts with low MC and thereby decrease product quality. The objectives of this research were to investigate correlations among near infrared (NIR) spectral data and MC of freshly harvested in-shell walnuts and determine feasibility of using NIR spectroscopic sorting of walnuts to minimize moisture variability in individual nuts within each batch introduced into dryers. NIR transmission spectra of in-shell walnuts of Chandler variety with MCs ranging from 10% to 70% wet basis were determined. Partial least square regression (PLS-R) of the spectral data was performed to establish correlations among the spectral data and walnut MC. Model validation was also performed to establish the accuracy of MC prediction. The results revealed that there was a strong linear relationship between walnut shell MC and whole nut (R2 = 0.968) and walnut shell MC and kernel MC (R2 = 0.851). The wavelengths at which peak NIR transmission intensity occurred were between 820 and 910 nm. The higher the concentration of moisture in the nut, the lower the NIR transmission value. Also, there was a spatial variation in individual nut surface transmission spectra. Model validation indicated that five partial least square (PLS) latent variables were adequate to explain 98% of response variation (MC) and also provided the simplest model with a Predicted Residual Error Sum of Square (PRESS) statistic of 0.751, which was not significantly different from the absolute minimum PRESS value of 0.744. Predicted and observed MC of walnuts agreed with R2 of 0.978. The results are vital for developing new MC-based sorting methods for walnut using NIR to improve drying efficiency and product quality.