| Autor: |
Xiaorong Wu, Armstrong, Paul R., Maghirang, Elizabeth B. |
| Zdroj: |
Applied Engineering in Agriculture; 2022, Vol. 38 Issue 3, p469-476, 8p |
| Abstrakt: |
The increasing demand for specialized high-quality popcorn products necessitates that the popcorn industry continuously identify quality parameters that can be improved through plant breeding or manipulated or sorted for improved end-products. Relationships between protein content (PC) and popping performance (expansion, ball rate, and number of unpopped kernels) has been investigated but there has been no research on segregating individual kernels from within the same variety for specific PC ranges, which may eliminate possible interference from some 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 for independent validations. MC showed 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 may 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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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