Predicting single kernel moisture and protein content of mushroom popcorn using NIR spectroscopy: Tool for detecting their effect on popping performance

Authors: WU, XIAORONG; MAGHIRANG, ELIZABETH; Armstrong, Paul

Submitted to: Applied Engineering in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/29/2021
Publication Date: 1/1/2022
Citation: Wu, X., Maghirang, E.B., Armstrong, P.R. 2022. Predicting single kernel moisture and protein content of mushroom popcorn using NIR spectroscopy: Tool for detecting their effect on popping performance. Applied Engineering in Agriculture. 38(3):469-476. https://doi.org/10.13031/aea.14875.
DOI: https://doi.org/10.13031/aea.14875

Interpretive Summary: The increasing demand for specialized high-quality popcorn products necessitates that the popcorn industry continuously assess quality parameters affecting popcorn and focus on those that can improve popping through plant breeding or post-harvest processing. Understanding the relationships between protein content (PC) and popping performance (expansion, ball rate, and number of unpopped kernels) may help processors supply an increasingly demanding popcorn market with improved and more consistent quality popcorn products. The USDA-ARS developed methods to measure single-kernel moisture content (MC) and PC with good accuracy using a single-kernel near-infrared reflectance (SKNIR) instrument. The ability to sort popcorn that normally would have contained a wide range of single kernel MC and PC into specific and narrowed range of traits allowed for the determination of their specific effect on popping. Popping tests showed that increased kernel PC significantly (p<0.05) increased expansion volume and lowered the number of unpopped kernels but had no effect on the ball rate of popped flakes. Thus, applications that require increased overall expansion and reduced number of unpopped kernels may be addressed by the removal of low protein popcorn kernels from popcorn, which could potentially be achieved using a high-throughput near-infrared technique. The SKNIR technique also provides a means for plant breeders to work on a targeted PC level or PC range based on single kernel selection.

Technical Abstract: The increasing demand for specialized high-quality popcorn products necessitates that the popcorn industry continuously determines quality parameters that can be improved through plant breeding or can be manipulated or sorted for improved end-products. Being able to understand relationships between protein content (PC) and popping performance (expansion, ball rate, and number of unpopped kernels) has been investigated but there has not been a study on segregation of individual kernels from the same variety with varying PC, which may eliminate possible interference from underlying variety- or production-related effects. Prediction models for determination of single kernel moisture content (MC) and PC were developed for the USDA-ARS tube single kernel near infrared reflectance (SKNIR) instrument. Both parameters were predicted with high accuracies with MC showing an R2 of 0.94 and SEP of 0.25 while PC had R2 of 0.92 and SEP of 0.35. Popping tests showed that increased kernel PC significantly (p<0.05) increased expansion and lowered the number of unpopped kernels but had no effect on the ball rate of popped flakes. Thus, applications that require increased overall expansion and reduced number of unpopped kernels might be addressed by the removal of low protein popcorn kernels from a popcorn lot, which can be achieved using an automated SKNIR technique. The SKNIR technique also provides a means for plant breeders to work on targeted/specific PC or PC range based on the single kernel selection.