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Identification of Aging-Associated Food Quality Changes in Citrus Products Using Untargeted Chemical Profiling
Journal of Agricultural and Food Chemistry ( IF 6.1 ) Pub Date : 2018-01-10 00:00:00 , DOI: 10.1021/acs.jafc.7b04450
Ian G. Ronningen 1 , Devin G. Peterson 1
Affiliation  

Chemometric techniques have seen wide application in biological and medical sciences, but they are still developing in the food sciences. This study illustrated the use of untargeted LC/MS chemometric methods to identify features (retention time_m/z) associated with food quality changes as products age (freshness). Extracts of three citrus fruit varietals aged over four time points that corresponded to noted changes in sensory attributes were chemically profiled and modeled by two discriminatory multivariate statistical techniques, projection partial least-squares discrimant analysis (PLS-DA) and machine learning random forest (RF). Age-associated compounds across the citrus platform were identified. Varietal was treated as a nuisance variable to emphasize aging chemistry, and further variable selection using age-related piecewise model generation and meta filtering to emphasize features associated with general aging chemistry common to all the citrus extracts. The identified features were further replicated in a validation study to illustrate the validity and persistence of these markers for applications in citrus food platforms.

中文翻译:

使用非靶向化学分析法鉴定柑橘类产品中与衰老相关的食品质量变化

化学计量学技术已在生物学和医学领域得到广泛应用,但在食品科学领域仍在发展。这项研究说明了使用非靶向LC / MS化学计量方法来识别特征(保留时间_ m / z)随着产品的老化(新鲜)而与食品质量变化有关。通过两种歧视性多元统计技术,投影偏最小二乘判别分析(PLS-DA)和机器学习随机森林(RF),对4个时间点上与感觉属性发生明显变化相对应的3个柑橘类水果的提取物进行了化学分析和建模,并对它们进行了建模和建模。 )。鉴定了跨柑橘平台的与年龄相关的化合物。品种被视为有害变量,以强调衰老化学,并使用与年龄相关的分段模型生成和元过滤来进一步选择变量,以强调与所有柑橘类提取物共有的一般衰老化学相关的特征。
更新日期:2018-01-10
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