Dataset Information

Rapid quantitative typing spectra model for distinguishing sweet and bitter apricot kernels.

ABSTRACT: Amygdalin content in apricot kernels is an essential factor in the rapid and nondestructive identification of sweet or bitter apricot kernels through spectroscopy. Now, amygdalin content has been determined by high-performance liquid chromatography and near-infrared spectral database to construct a model so that the sweet or bitter apricot kernels could be identified and classified. Principal component analysis-K-nearest neighbor classification algorithm combined with multivariate scattering correction pretreatment method could distinguish sweet and bitter apricot kernels in the wavelength range of 1650-1740 nm with 98.3% accuracy and apricot kernel species with 96.3% recognition rate in the full wavelength spectrum. Furthermore, prediction of amygdalin content in bitter and sweet apricot kernels by partial least squares model was superior to that by back-propagation neural network model. This study provides a theoretical basis for quality identification of apricot kernel quality, as well as a method for nondestructive and rapid detection of sweet and bitter apricot kernels.

Supplementary information

The online version contains supplementary material available at 10.1007/s10068-022-01095-y.

SUBMITTER: Huang X

PROVIDER: S-EPMC9339053 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Rapid quantitative typing spectra model for distinguishing sweet and bitter apricot kernels.

Huang Xue X Xu Jiayi J Gao Feng F Zhang Hongyan H Guo Ling L

Food science and biotechnology 20220623 9

Amygdalin content in apricot kernels is an essential factor in the rapid and nondestructive identification of sweet or bitter apricot kernels through spectroscopy. Now, amygdalin content has been determined by high-performance liquid chromatography and near-infrared spectral database to construct a model so that the sweet or bitter apricot kernels could be identified and classified. Principal component analysis-K-nearest neighbor classification algorithm combined with multivariate scattering cor ...[more]

PMID: 35919360

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Project description:Humans will eat almost anything, from caribou livers to rutabagas, but there are some types of foods, and their associated taste qualities, that are preferred by large groups of people regardless of culture or experience. When many choices are available, humans chose foods that taste good, that is, create pleasing sensations in the mouth. The concept of good taste for most people encompasses both flavor and texture of food, and these sensations merge with taste proper to form the concept of goodness. Although we acknowledge the universality of the goodness (sweet) or badness (bitter) of basic taste qualities, we also find that people differ, sometimes extremely so, in their ability to perceive and enjoy these qualities and, by extension, food and drink. The reasons for these differences among people are not clear but are probably due to a combination of experience beginning at an early age, perhaps in utero; learning, for example, as with conditioned taste aversions; sex and maturity; and perceptual differences that arise from genetic variation. In this review, we focus on individual variations that arise from genetic differences and review two domains of science: recent developments in the molecular biology of taste transduction, with a focus on the genes involved and second, studies that examine biological relatives to determine the heritability of taste perception. Because the receptors for sweet, savory (umami), and bitter have recently been discovered, we summarize what is known about their function by reviewing the effect of naturally occurring and man-made alleles of these receptors, their shape and function based on receptor modeling techniques, and how they differ across animal species that vary in their ability to taste certain qualities. We discuss this literature in the context of how taste genes may differ among people and give rise to individuated taste experience, and what is currently known about the genetic effects on taste perception in humans.

Dataset Information

Rapid quantitative typing spectra model for distinguishing sweet and bitter apricot kernels.

Supplementary information

Publications

Rapid quantitative typing spectra model for distinguishing sweet and bitter apricot kernels.

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