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采用近红外光纤探头结合稳定性竞争自适应重采样评估菠萝醋生产发酵液质量。

Assessing Fermentation Broth Quality of Pineapple Vinegar Production with a Near-Infrared Fiber-Optic Probe Coupled with Stability Competitive Adaptive Reweighted Sampling.

机构信息

Laboratory of Non-Destructive Quality Evaluation of Commodities, Kasetsart Agricultural and Agro-Industrial Product Improvement Institute (KAPI), Kasetsart University, Bangkok 10900, Thailand.

Laboratory of Enzyme and Microbiology, KAPI, Kasetsart University, Bangkok 10900, Thailand.

出版信息

Molecules. 2023 Aug 25;28(17):6239. doi: 10.3390/molecules28176239.

Abstract

In this study, the performance of a near-infrared (NIR) fiber-optic probe coupled with stability competitive adaptive reweighted sampling (SCARS) was investigated for the analysis of acetic acid, ethanol, total soluble solids, caffeic acid, gallic acid, and tannic acid in the broth of pineapple vinegar during fermentation. The NIR spectra of the broth samples in the region of 11,536-3956 cm were collected during vinegar fermentation promoted by . This continuous biological process led to changes in the concentrations of all analytes studied. SCARS provided optimized and stabilized NIR spectral variables for the construction of a partial least squares (PLS) model for each analyte using a small number of optimal variables (under 88 variables). The SCARS-PLS model outperformed the conventional PLS model, and achieved excellent accuracy in accordance with ISO 12099:2017 for the four prediction models of acetic acid, ethanol, caffeic acid, and gallic acid, with root-mean-square error of prediction values of 0.137%, 0.178%, 0.637 μg/mL and 0.640 μg/mL, respectively. In contrast, only an acetic acid content prediction model constructed via the conventional PLS method and using the whole spectral region (949 variables) could pass with acceptable accuracy. These results indicate that the NIR optical probe coupled with SCARS is an appropriate method for the continuous monitoring of multianalytes during vinegar fermentation, particularly acetic acid and ethanol contents, which are indicators of the finished fermentation of pineapple vinegar.

摘要

在这项研究中,研究了近红外(NIR)光纤探头与稳定竞争自适应重加权采样(SCARS)相结合,用于分析菠萝醋发酵过程中发酵液中乙酸、乙醇、总可溶固形物、咖啡酸、没食子酸和单宁酸。在 通过菠萝醋发酵促进的过程中,在 11,536-3956 cm 的区域内收集了发酵液的 NIR 光谱。这个连续的生物过程导致了所有研究分析物浓度的变化。SCARS 为每个分析物的偏最小二乘(PLS)模型提供了优化和稳定的 NIR 光谱变量,使用少量最佳变量(少于 88 个变量)。SCARS-PLS 模型优于传统的 PLS 模型,并且根据 ISO 12099:2017,对于四个预测模型(乙酸、乙醇、咖啡酸和没食子酸),其预测值的均方根误差预测值分别为 0.137%、0.178%、0.637 μg/mL 和 0.640 μg/mL,达到了极好的准确性。相比之下,只有通过传统 PLS 方法和使用整个光谱区域(949 个变量)构建的乙酸含量预测模型才能以可接受的准确性通过。这些结果表明,近红外光学探头与 SCARS 相结合是一种用于监测菠萝醋发酵过程中多分析物连续监测的合适方法,特别是乙酸和乙醇含量,这是菠萝醋发酵完成的指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a0b/10488555/faad254b98cd/molecules-28-06239-g001.jpg

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