Abstract Brazil is still the world's largest producer and exporter of coffee. In order to maximize profits, some producers may add lower cost materials (such as corn, barley, or even coffee husks) to commercial coffee. In view of the growing market for coffee products and the importance of coffee for the Brazilian economy, it is necessary to have a rapid, simple, and reliable methodology to identify and quantify coffee adulterants. NMR has proved to be a versatile and robust tool for the identification of adulterants in foods and beverages. Here, we explore the versatility of 1H NMR assisted with chemometric tools, avoiding laborious data analysis, for the quantification of coffee adulteration. Six different adulterants were considered: barley, corn, coffee husks, soybean, rice, and wheat. The NMR-based methodology described here provided satisfactory LOD values (0.31–0.86%) for adulterants in medium and dark roast coffees. The statistical techniques PCA and SIMCA were employed for pattern recognition and the identification of pure and adulterated samples. Use of the SIMCA model enabled 100% correct classification for both training and prediction sets, ensuring the accuracy, traceability, and reliability of the results.

中文翻译：

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使用核磁共振和化学计量学方法鉴定含有多种掺杂物的烘焙和研磨咖啡样品

摘要 巴西仍然是世界上最大的咖啡生产国和出口国。为了使利润最大化，一些生产商可能会在商业咖啡中添加成本较低的材料（如玉米、大麦，甚至咖啡皮）。鉴于咖啡产品市场不断增长以及咖啡对巴西经济的重要性，有必要采用一种快速、简单且可靠的方法来识别和量化咖啡掺假。核磁共振已被证明是一种用于识别食品和饮料中掺假物的通用且强大的工具。在这里，我们探索了 1H NMR 在化学计量工具辅助下的多功能性，避免了费力的数据分析，用于量化咖啡掺假。考虑了六种不同的掺杂物：大麦、玉米、咖啡壳、大豆、大米和小麦。此处描述的基于 NMR 的方法为中度和深度烘焙咖啡中的掺杂物提供了令人满意的 LOD 值 (0.31–0.86%)。统计技术 PCA 和 SIMCA 用于模式识别和纯样品和掺假样品的鉴定。使用 SIMCA 模型可以对训练集和预测集进行 100% 正确分类，确保结果的准确性、可追溯性和可靠性。