Predicting Single Kernel Moisture and Protein Content of Mushroom Popcorn Using NIR Spectroscopy: Tool for Determining their Effect on Popping Performance
{"title":"Predicting Single Kernel Moisture and Protein Content of Mushroom Popcorn Using NIR Spectroscopy: Tool for Determining their Effect on Popping Performance","authors":"Xiaorong Wu, P. Armstrong, E. Maghirang","doi":"10.13031/aea.14875","DOIUrl":null,"url":null,"abstract":"HighlightsPrediction models for high accuracy measurement of single kernel (SK) moisture content (MC) and protein content (PC) were developed using near-infrared reflectance (NIR) spectroscopy.USDA-ARS tube SKNIR instrument sorted individual kernels based on single kernel protein content (SKPC) which enabled determining the effect of three PC levels within a popcorn variety on popping performance.Variety, MC, and PC affected popping expansion, ball rate, and number of unpopped/half-popped kernels.Within popcorn variety, increased PC significantly increased expansion and reduced number of unpopped kernels but did not affect ball rate of popped flakes.The ability to sort single kernels for specific quality parameter, such as PC, is an important and useful tool for popcorn breeders and processors to meet consumer demand for specialized products.Abstract. 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. Keywords: Ball rate, Expansion, Mushroom popcorn, NIR spectroscopy, Popcorn quality, Single kernel, Unpopped kernels.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":"1 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Engineering in Agriculture","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.13031/aea.14875","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AGRICULTURAL ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
HighlightsPrediction models for high accuracy measurement of single kernel (SK) moisture content (MC) and protein content (PC) were developed using near-infrared reflectance (NIR) spectroscopy.USDA-ARS tube SKNIR instrument sorted individual kernels based on single kernel protein content (SKPC) which enabled determining the effect of three PC levels within a popcorn variety on popping performance.Variety, MC, and PC affected popping expansion, ball rate, and number of unpopped/half-popped kernels.Within popcorn variety, increased PC significantly increased expansion and reduced number of unpopped kernels but did not affect ball rate of popped flakes.The ability to sort single kernels for specific quality parameter, such as PC, is an important and useful tool for popcorn breeders and processors to meet consumer demand for specialized products.Abstract. 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. Keywords: Ball rate, Expansion, Mushroom popcorn, NIR spectroscopy, Popcorn quality, Single kernel, Unpopped kernels.
期刊介绍:
This peer-reviewed journal publishes applications of engineering and technology research that address agricultural, food, and biological systems problems. Submissions must include results of practical experiences, tests, or trials presented in a manner and style that will allow easy adaptation by others; results of reviews or studies of installations or applications with substantially new or significant information not readily available in other refereed publications; or a description of successful methods of techniques of education, outreach, or technology transfer.