Interval resonance analysis (InRA): A versatile tool for automated untargeted 1H NMR fingerprinting – A case study in sugar beet field authentication

IF 5.7 2区化学 Q1 CHEMISTRY, ANALYTICAL

Analytica Chimica Acta Pub Date : 2025-05-15 DOI:10.1016/j.aca.2025.344175

Cristian A. Fuentes , David Montoya , Mecit Öztop , Macarena Rojas-Rioseco , Martin Bravo , Francisca González , Rosario del P. Castillo

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引用次数: 0

Abstract

Background

The extraction of relevant information from proton nuclear magnetic resonance (¹H NMR) spectra through preprocessing and multivariate analysis requires integrating multiple software tools and extensive manual intervention, compromising efficiency and reproducibility when the technique is used. Consequently, the development of automated, versatile, and reliable methodologies has become imperative to streamline workflows, improve analytical performance, and broaden the applicability of multivariate methods for the analysis of diverse sample types and experimental conditions.

Results

This work presents the development and application of Interval Resonance Analysis (InRA), an alternative software tool focused on ¹H NMR multivariate analysis. InRA includes a novel algorithm for resonance signal detection (intervals), specifically designed to operate with flexibility across diverse ¹H NMR spectra. All intervals are integrated using multivariate curve resolution with alternating least squares (MCR–ALS) and analyzed by exploratory analysis. The performance of InRA was tested by evaluating the ¹H NMR spectra of hydrophilic sugar beet root extracts cultivated in three different fields and their discrimination by partial least squares – discriminant analysis (PLS–DA). The workflow provided by InRA yielded consistent results regarding the distribution of samples according to their field, enabling the identification of subtle sources of variation and achieving classification accuracies ≥ 88.9 %.

Significance

The proposed methodology represents an advancement in the multivariate analysis of ¹H NMR spectra for untargeted studies and enhances analytical efficiency by reducing manual intervention and reliance on analyst experience. InRA is versatile and can be applied to various sample types and analytical objectives, as it is not restricted by specific experimental conditions.

Abstract Image

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区间共振分析（InRA）：用于自动非靶向1H核磁共振指纹识别的多功能工具-甜菜田认证案例研究

通过预处理和多变量分析从质子核磁共振（1H NMR）光谱中提取相关信息需要集成多个软件工具和大量的人工干预，在使用该技术时影响效率和可重复性。因此，开发自动化、通用和可靠的方法已成为当务之急，以简化工作流程，提高分析性能，并扩大多元方法的适用性，以分析不同的样品类型和实验条件。本工作介绍了区间共振分析（InRA）的开发和应用，这是一种专注于1H NMR多元分析的替代软件工具。InRA包括一种新的共振信号检测（间隔）算法，专门设计用于跨不同1H NMR谱的灵活性操作。所有区间采用交替最小二乘（MCR-ALS）多元曲线分辨率进行积分，并进行探索性分析。采用偏最小二乘判别分析（PLS-DA）对3个不同栽培地的亲水甜菜根提取物进行1H NMR谱分析，并对其进行判别，验证了InRA的性能。InRA提供的工作流程对样品按其领域的分布产生了一致的结果，能够识别细微的变异源，分类准确率≥88.9%。所提出的方法代表了非靶向研究的1H NMR谱多变量分析的进步，并通过减少人工干预和对分析师经验的依赖来提高分析效率。InRA是通用的，可以应用于各种样品类型和分析目标，因为它不受特定实验条件的限制。

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来源期刊

Analytica Chimica Acta 化学-分析化学

CiteScore

10.40

自引率

6.50%

发文量

1081

审稿时长

38 days

期刊介绍： Analytica Chimica Acta has an open access mirror journal Analytica Chimica Acta: X, sharing the same aims and scope, editorial team, submission system and rigorous peer review. Analytica Chimica Acta provides a forum for the rapid publication of original research, and critical, comprehensive reviews dealing with all aspects of fundamental and applied modern analytical chemistry. The journal welcomes the submission of research papers which report studies concerning the development of new and significant analytical methodologies. In determining the suitability of submitted articles for publication, particular scrutiny will be placed on the degree of novelty and impact of the research and the extent to which it adds to the existing body of knowledge in analytical chemistry.