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将感官描述符与特色水稻品种风味中的挥发性成分相关联。

Relating sensory descriptors to volatile components in flavor of specialty rice types.

作者信息

Limpawattana M, Yang D S, Kays S J, Shewfelt R L

机构信息

Department of Food Science and Technology, University of Georgia, Athens, GA, USA.

出版信息

J Food Sci. 2008 Nov;73(9):S456-61. doi: 10.1111/j.1750-3841.2008.00952.x.

Abstract

Flavor is a key factor contributing to consumer acceptance and repeat purchase of rice. Plant breeders focus on production yield and ignoring quality traits because there are no readily useable tools to evaluate quality. A systematic approach is needed for rice breeders to select rice with favorable flavor traits. Descriptive sensory analysis combined with chemical analysis provided an insight of sensory significance to interpret chemical data for a better understanding approach of rice flavor. This study was aimed to develop prediction models for sensory descriptors based on the volatile components derived from the gas chromatography-olfactometry (GC-O) that would be useful to help select rice cultivars containing a satisfactory flavor to produce improved quality in rice breeding programs. Thirteen Korean specialty rice samples were evaluated for their flavor components using descriptive analysis and GC-O. Nineteen aroma attributes in cooked specialty rice samples were evaluated by 8 trained panelists and statistically correlated to the concentration of aroma-active compounds derived from GC-O analysis. Prediction models were developed for most aroma descriptors including popcorn, cooked grain, starchy, woody, smoky, grain, corn, hay-like, barny, rancid, waxy, earthy, and sweet aroma using stepwise multiple linear regression. (E,E)-2, 4-decadienal, naphthalene, guaiacol, (E)-2-hexenal, 2-acetyl-1-pyrroline, 2-heptanone contributed most to these sensory attributes. These models help provide a quantitative link between sensory characteristics of commercial rice samples and aroma volatile components desirable in developing a rapid analytical method for use by rice breeders to screen progeny for superior flavor quality.

摘要

风味是影响消费者对大米接受度和重复购买率的关键因素。植物育种者专注于产量而忽视品质性状,因为缺乏易于使用的品质评估工具。水稻育种者需要一种系统的方法来选择具有良好风味性状的水稻。描述性感官分析与化学分析相结合,为解读化学数据以更好地理解水稻风味提供了感官意义上的见解。本研究旨在基于气相色谱 - 嗅觉测量法(GC - O)衍生的挥发性成分开发感官描述符的预测模型,这将有助于在水稻育种计划中选择具有令人满意风味的水稻品种,以提高水稻品质。使用描述性分析和GC - O对13个韩国特色水稻样品的风味成分进行了评估。8名经过培训的评判员对煮熟的特色水稻样品中的19种香气属性进行了评估,并与GC - O分析得出的香气活性化合物浓度进行了统计关联。使用逐步多元线性回归为大多数香气描述符建立了预测模型,包括爆米花味、煮熟谷物味、淀粉味、木质味、烟熏味、谷物味、玉米味、干草味、谷仓味、酸败味、蜡味、土腥味和甜味。(E,E)-2,4 - 癸二烯醛、萘、愈创木酚、(E)-2 - 己烯醛、2 - 乙酰 - 1 - 吡咯啉、2 - 庚酮对这些感官属性贡献最大。这些模型有助于在商业水稻样品的感官特征与开发快速分析方法所需的理想香气挥发性成分之间建立定量联系,供水稻育种者用于筛选具有优异风味品质的后代。

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