Geographical origin identification of sweet cherry based on quality traits combined with DD-SIMCA and XGBoost

IF 9.8 1区农林科学 Q1 CHEMISTRY, APPLIED

Food Chemistry Pub Date : 2025-07-10 DOI:10.1016/j.foodchem.2025.145525

Linxia Wu, Ziye Liu, Meng Wang

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引用次数: 0

Abstract

Geographical origin identification technologies based on physical and nutritional characteristics have recently been developed and applied. This study evaluated the feasibility of identifying the geographical origin of sweet cherries using organoleptic traits and phenolic compound profiles. Data-driven soft independent modeling of class analogy (DD-SIMCA) and extreme gradient boosting (XGBoost) were applied to 170 sweet cherry samples collected in 2023 and 2024 from Beijing, Dalian, Tianshui, and Yantai, China. Measurements included transverse diameter, longitudinal diameter, fruit weight, soluble solid content, titratable acidity, organic acids, ascorbic acid, and 14 phenolic compounds. The DD-SIMCA model showed high sensitivity (98.00 %) and specificity (100.00 %). XGBoost yielded a prediction accuracy of 94.12 %, outperforming LDA (82.35 %), RF (88.24 %), and k-NN (82.35 %). Key discriminatory features included malic acid, quinic acid, citric acid, kaempferol-3-O-rutinoside, titratable acidity, and cyanidin-3-O-rutinoside. These findings indicate that DD-SIMCA and XGBoost are effective methods for the geographical origin identification of sweet cherries based on quality attributes. This approach supports quality assurance and control in regional production systems.

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基于品质性状结合DD-SIMCA和XGBoost的甜樱桃产地鉴定

基于物理和营养特征的地理原产地鉴定技术最近得到了发展和应用。本研究评估了利用感官性状和酚类化合物谱鉴定甜樱桃地理来源的可行性。对2023年和2024年在中国北京、大连、天水和烟台采集的170份甜樱桃样本进行了数据驱动的类类比软独立建模（DD-SIMCA）和极端梯度增强（XGBoost）。测量包括横向直径、纵向直径、果实重量、可溶性固形物含量、可滴定酸度、有机酸、抗坏血酸和14种酚类化合物。DD-SIMCA模型具有较高的灵敏度（98.00 %）和特异性（100.00 %）。XGBoost的预测准确率为94.12 %，优于LDA（82.35 %）、RF（88.24 %）和k-NN（82.35 %）。主要的鉴别特征包括苹果酸、奎宁酸、柠檬酸、山奈酚-3- o -芦丁苷、可滴定酸度和花青素-3- o -芦丁苷。上述结果表明，DD-SIMCA和XGBoost是基于品质属性的甜樱桃产地识别的有效方法。这种方法支持区域生产系统的质量保证和控制。

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来源期刊

Food Chemistry 工程技术-食品科技

CiteScore

16.30

自引率

10.20%

发文量

3130

审稿时长

122 days

期刊介绍： Food Chemistry publishes original research papers dealing with the advancement of the chemistry and biochemistry of foods or the analytical methods/ approach used. All papers should focus on the novelty of the research carried out.