Journal of Food Composition and Analysis最新文献_第7页

Variation of kokumi γ-glutamyl dipeptides during Jinhua ham processing and γ-glutamyl transpeptidase-mediated formation research: UHPLC-Q-TOF-MS analysis and sensory evaluation 金华火腿加工过程中国米γ-谷氨酰二肽的变化及γ-谷氨酰转肽酶介导的形成研究：UHPLC-Q-TOF-MS分析和感官评价

IF 4.6 2区农林科学 Q2 CHEMISTRY, APPLIED

Journal of Food Composition and Analysis

Pub Date : 2026-01-20 DOI: 10.1016/j.jfca.2026.108924

Feiran Xu , Tong Ji , Yu Wang , Guosheng Xu , Xingguang Chen , Zhaoming Wang , Bao Zhang , Jiansheng Zhao , Baocai Xu

γ-Glutamyl dipeptides (γ-GGDPs) have been implicated be generated by enzymatic action on γ‑glutamyl groups, modulate kokumi sensation of fermented foods via activating calcium-sensing receptors (CaSR). However, their variation and potential formation mechanism in Jinhua ham remain unclear. 10 γ-GGDPs (γ-EA, γ-ED, γ-EE, γ-EL, γ-EM, γ-EG, γ-EF, γ-EY, γ-EI, γ-EW) in Jinhua ham were quantified by UHPLC-Q-TOF-MS and accumulating significantly during processing (P < 0.05), with final contents ranging from 0.78 ± 0.01 μg/g (γ-EW) to 24.75 ± 0.33 μg/g (γ-EA). Sensory evaluation confirmed these γ-GGDPs enhanced the kokumi, saltiness, and umami of Jinhua ham during the post-ripening periods. Mechanistic investigation indicated that γ-glutamyl transpeptidase (GGT) transfer and hydrolytic activities increased progressively to 9.11 ± 0.17 U/mg and 12.19 ± 0.40 U/mg, respectively, which corroborated GGT's role in driving γ-GGDPs formation by catalyzing the transfer of γ-glutamyl groups to free amino acids (FAAs) generated by endogenous enzymes in Jinhua ham. Further validation via a ternary reaction system (comprising FAAs, γ-glutamyl donors, and GGT extracted from Jinhua ham) confirmed this GGT-catalyzed transfer reaction for γ-GGDPs biosynthesis. This study provides a theoretical foundation for the potential formation mechanisms of γ-GGDPs in Jinhua ham and regulation of Kokumi sensation in fermented foods.

γ-谷氨酰二肽（γ- ggdps）被认为是由酶对γ-谷氨酰基的作用产生的，它通过激活钙感应受体（CaSR）来调节发酵食品的高味感觉。然而，它们在金华火腿中的变异及其潜在的形成机制尚不清楚。采用UHPLC-Q-TOF-MS对金花火腿中的10种γ- ggdp （γ-EA、γ-ED、γ-EE、γ-EL、γ-EM、γ-EG、γ-EF、γ-EY、γ-EI、γ-EW）进行定量分析，结果表明，加工过程中γ- ggdp含量显著增加（P <； 0.05），最终含量范围为0.78 ± 0.01 μg (γ-EW) ~ 24.75 ± 0.33 μg/g （γ-EA）。感官评价证实，这些γ- ggdp增强了金华火腿熟后的高味、咸味和鲜味。机制研究表明，γ-谷氨酰转肽酶（GGT）的转移活性和水解活性逐渐增加，分别达到9.11 ± 0.17 U/mg和12.19 ± 0.40 U/mg，证实了GGT通过催化内源酶生成的γ-谷氨酰基向游离氨基酸（FAAs）转移，促进了γ- ggdp的形成。通过三元反应体系（包括FAAs、γ-谷氨酰供体和从金华火腿中提取的GGT）进一步验证了GGT催化的γ- ggdp生物合成转移反应。本研究为金华火腿中γ-GGDPs的潜在形成机制及发酵食品中香感的调控提供了理论基础。

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引用次数: 0

Comparing and optimizing precise methods for measuring capsaicin content in dried peppers 比较和优化干辣椒中辣椒素含量的精确测定方法

IF 4.6 2区农林科学 Q2 CHEMISTRY, APPLIED

Journal of Food Composition and Analysis

Pub Date : 2026-01-20 DOI: 10.1016/j.jfca.2026.108923

Yue Peng , Jingyuan Zheng , Xiongze Dai , Shudong Zhou , Yanling Li , Yanqing Ma , Jie Li

This study evaluated the efficacy of two distinct Enzyme-Linked Immunosorbent Assay (ELISA) kits for quantifying total capsaicinoids in dried peppers, benchmarked against High-Performance Liquid Chromatography (HPLC) as the reference method. Our analysis revealed a high correlation between the results from the ELISA-1 kit and HPLC (R² = 0.9335, p < 0.0001), confirming its accuracy and reliability. In contrast, the ELISA-2 kit proved unsuitable, yielding inconsistent data. To maximize the utility of the more cost-effective ELISA-1 assay, we systematically optimized its extraction protocol. The optimal conditions were established as using 80-mesh sieved pericarp powder, 95 % ethanol as the extraction solvent, and an ultrasonic treatment of 15 min, which significantly enhanced capsaicinoid recovery. Consequently, this research establishes an optimized protocol, validated through its strong correlation with HPLC, that offers an efficient and economical workflow for capsaicinoid analysis. This provides a valuable tool for high-throughput screening in pepper breeding programs and for industrial quality control.

本研究以高效液相色谱法（HPLC）为参比方法，评价了两种不同的酶联免疫吸附法（ELISA）测定干辣椒中总辣椒素的效果。我们的分析显示ELISA-1试剂盒的结果与HPLC之间具有很高的相关性（R²= 0.9335,p <； 0.0001），证实了其准确性和可靠性。相反，ELISA-2试剂盒被证明是不合适的，产生不一致的数据。为了使更具成本效益的ELISA-1检测的效用最大化，我们系统地优化了其提取方案。确定最佳提取条件为：以80目过滤的果皮粉，95 %乙醇为提取溶剂，超声处理时间为15 min，可显著提高辣椒素的回收率。因此，本研究建立了一个优化的方案，并通过其与高效液相色谱的强相关性验证，为辣椒素分析提供了一个高效、经济的工作流程。这为辣椒育种计划的高通量筛选和工业质量控制提供了有价值的工具。

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引用次数: 0

A convenient and practical colorimetric chemosensor for sulfide monitoring in pure water: Applications to environmental water, smartphone-based platform, colorimetric food imaging and spoilage 一种方便实用的用于纯水硫化物监测的比色化学传感器：应用于环境水，基于智能手机的平台，比色食品成像和腐败

IF 4.6 2区农林科学 Q2 CHEMISTRY, APPLIED

Journal of Food Composition and Analysis

Pub Date : 2026-01-20 DOI: 10.1016/j.jfca.2026.108920

Chanwoo Song , Jae Jun Lee , Sooseong Lee , Yun-Seo Lee, Otgontsetseg Batsaikhan, Cheal Kim

Sulfide is an environmentally harmful and toxic substance. Thus, its sensitive detection is important for water-quality monitoring and food safety. In this work, we synthesized a convenient and practical colorimetric chemosensor DNP (1,3-dimethyl-5-(7-nitrobenzo[c][1,2,5]oxadiazol-4-yl)pyrimidine-2,4,6(1H,3H,5H)-trione) for sensing S^2- in pure water. DNP selectively detected S^2- among varied analytes through color change from red to colorless. The probe DNP showed a low detection limit (2.8 μM) for S^2- in a wide linear range of 0–150 μM, which was significantly below the WHO guideline (14.8 μM). The detecting process of S^2- by DNP was proposed to be a sulfide-triggered reduction of the NBD nitro group, supported by ¹H NMR titration, calculations, and ESI-mass. DNP could certainly quantify S^2- in environmental samples like river water and seawater with recoveries of 98.33 % - 103.49 %. Also, test-strip and smartphone applications were conveniently applied for S^2- sensing. DNP demonstrated the ability for imaging sulfide in mushroom and onion epidermal cells. In particular, DNP-coated strips could be used as a convenient sulfide indicator of foods such as pork, chicken, and garlic. All these results highlighted DNP as a promising and versatile chemosensor for sulfide detection in food and real-field systems.

硫化物是一种对环境有害的有毒物质。因此，它的灵敏检测对水质监测和食品安全具有重要意义。在本工作中，我们合成了一种方便实用的比色化学传感器DNP（1,3-二甲基-5-（7-硝基苯[c][1,2,5]恶二唑-4-基）嘧啶-2,4,6(1H,3H,5H)-三酮），用于检测纯水中的S2-。DNP通过从红色到无色的颜色变化，选择性地检测不同分析物中的S2-。探针DNP在0 ~ 150 μM的宽线性范围内对S2-的检出限较低（2.8 μM），显著低于WHO标准（14.8 μM）。DNP检测S2-的过程被认为是硫化物触发的NBD硝基还原，由1H NMR滴定、计算和ESI-mass支持。DNP可以定量测定河水、海水等环境样品中的S2-，回收率为98.33 % ~ 103.49 %。此外，测试条和智能手机应用程序也方便地应用于S2传感。DNP对蘑菇和洋葱表皮细胞中的硫化物具有显像能力。特别是，dnp涂层条可以作为食品，如猪肉，鸡肉和大蒜的一个方便的硫化物指示器。所有这些结果都突出了DNP作为一种有前途的多功能化学传感器，可用于食品和现场系统中的硫化物检测。

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引用次数: 0

ND-YOLO: An enhanced framework integrating omni-dimensional dynamic convolution and occlusion-aware mechanisms for small defect detection in noodle cakes ND-YOLO：一种集成全维动态卷积和闭塞感知机制的面饼小缺陷检测增强框架

IF 4.6 2区农林科学 Q2 CHEMISTRY, APPLIED

Journal of Food Composition and Analysis

Pub Date : 2026-01-19 DOI: 10.1016/j.jfca.2026.108916

Fuquan Dai , Shaojia Deng , Chun Li , Xinyi Yu , Tieping Wei

Automated visual inspection of instant noodle cakes faces significant challenges stemming from minute defect sizes, complex morphological variations, and severe partial occlusion caused by noodle texture. To overcome these limitations, we propose ND-YOLO, an enhanced YOLOv8-based framework specifically designed for high-precision, real-time small defect detection in manufacturing environments. The architecture is strategically improved through: 1) a dedicated small-scale feature layer to prevent fine-grained feature loss; 2) the novel C2f-OD module, leveraging Omni-Dimensional Dynamic Convolution (ODConv) for morphology-aware feature representation; and 3) the Separated and Enhancement Attention Module (SEAM), which reconstructs the detection head to robustly mitigate false detections induced by texture occlusion. Additionally, we integrate a SpA-Former generative adversarial network for shadow removal preprocessing, significantly improving environmental robustness. ND-YOLO achieved a mean average precision (mAP50 of 94.9 % with preprocessing, representing a substantial improvement over the YOLOv8s baseline. Crucially, real-time deployment verification on an industrial line, accelerated by TensorRT, confirms a stable throughput of 142 items/minute, validating the algorithm's superior practical deployability for critical quality control applications.

方便面面饼的自动视觉检测面临着巨大的挑战，这些挑战来自于微小的缺陷尺寸、复杂的形态变化以及面条质地引起的严重的局部闭塞。为了克服这些限制，我们提出了ND-YOLO，这是一种基于yolov8的增强型框架，专为制造环境中的高精度、实时小缺陷检测而设计。从战略上改进了该体系结构：1)专用的小尺度特征层，防止细粒度特征丢失；2)新颖的C2f-OD模块，利用全维动态卷积（ODConv）进行形态感知特征表示；3)分离与增强注意模块（SEAM），该模块对检测头进行重构，以鲁棒地减轻纹理遮挡引起的误检。此外，我们集成了一个SpA-Former生成对抗网络进行阴影去除预处理，显著提高了环境鲁棒性。经过预处理，ND-YOLO的平均精度（mAP50）为94.9 %，比YOLOv8s基线有了实质性的提高。至关重要的是，TensorRT加速了在工业生产线上的实时部署验证，确认了142件/分钟的稳定吞吐量，验证了该算法在关键质量控制应用中的卓越实际部署能力。

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引用次数: 0

Non-destructive estimation of chlorophyll content in wasabi (Eutrema japonicum) leaves using spectral reflectance and deep learning models 基于光谱反射和深度学习模型的山葵叶片叶绿素含量无损估测

IF 4.6 2区农林科学 Q2 CHEMISTRY, APPLIED

Journal of Food Composition and Analysis

Pub Date : 2026-01-19 DOI: 10.1016/j.jfca.2026.108919

Adenan Yandra Nofrizal , Rei Sonobe , Hiroto Yamashita , Akio Morita , Takashi Ikka

Accurate, non-destructive estimation of chlorophyll content is essential for monitoring crop physiological status and supporting precision cultivation management. This study investigated the feasibility of combining leaf spectral reflectance with deep learning models to estimate chlorophyll content in hydroponically grown wasabi (Eutrema japonicum), while also deriving insights applicable to other leafy crops. A total of 179 leaf samples were collected under diverse nutrient conditions, including variations in pH, sulfur levels, and macronutrient composition across two growing seasons. Spectral data were preprocessed using second-order trend removal followed by a fractional-order derivative (FOD) transformation based on the Grünwald–Letnikov definition to enhance subtle spectral features. Three regression models—a one-dimensional convolutional neural network (1D-CNN), a Vision Transformer (ViT), and a Swin Transformer (SWIN)—were evaluated. The 1D-CNN achieved the highest accuracy when low-order fractional derivatives (0–0.4) were applied, highlighting its sensitivity to localized spectral variations, whereas SWIN performed best with minimally processed original spectra, and ViT showed relatively stable performance across preprocessing methods. These findings indicate that optimal preprocessing strategies depend on model architecture, providing practical guidance for selecting suitable combinations of spectral preprocessing and deep learning models when designing chlorophyll monitoring systems for wasabi and other crops.

准确、无损地估算叶绿素含量对于监测作物生理状况和支持精准栽培管理至关重要。本研究探讨了将叶片光谱反射率与深度学习模型相结合估算水培山葵叶绿素含量的可行性，同时也得出了适用于其他叶类作物的见解。在不同的营养条件下，包括pH、硫水平和两个生长季节的宏量营养素组成的变化，共收集了179个叶片样品。利用二阶趋势去除和基于gr nwald - letnikov定义的分数阶导数（FOD）变换对光谱数据进行预处理，增强细微光谱特征。对一维卷积神经网络（1D-CNN）、视觉变压器（ViT）和Swin变压器（Swin）三种回归模型进行了评估。1D-CNN在使用低阶分数阶导数（0-0.4）时获得了最高的精度，突出了其对局部光谱变化的敏感性，而SWIN在对原始光谱进行最小处理时表现最佳，ViT在各种预处理方法中表现出相对稳定的性能。这些发现表明，最佳预处理策略取决于模型结构，为在设计山葵和其他作物叶绿素监测系统时选择合适的光谱预处理和深度学习模型组合提供了实用指导。

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引用次数: 0

Simultaneous quantification of rice amylose and protein content with an optimized convolutional neural network model via near-infrared spectroscopy 基于优化卷积神经网络模型的近红外光谱水稻直链淀粉和蛋白质含量同时定量研究

IF 4.6 2区农林科学 Q2 CHEMISTRY, APPLIED

Journal of Food Composition and Analysis

Pub Date : 2026-01-18 DOI: 10.1016/j.jfca.2026.108905

Qian Zhao , Zhuoyuan Cheng , Yiting Han , Qian Zhu , Jie Wang , Yuanliang Gao , Zhanyu Han , Zhenzhen Cao , Jun Huang

Rice amylose and protein contents are pivotal quality indicators influencing rice physicochemical properties. Near-infrared (NIR) spectroscopy offers rapid, non-destructive analysis, yet conventional convolutional neural network (CNN) models often suffer from overfitting and limited consideration of global spectral features, hindering simultaneous multi-target prediction. In this study, we introduce an advanced Convolutional Neural Network Regression (CNNR) model for the simultaneous determination of amylose and protein content. Calibration models of partial least squares regression (PLSR) and support vector machine regression (SVMR) were first optimized through spectral preprocessing and wavenumber selection. While PLSR achieved superior performance in amylose prediction, CNNR significantly outperformed PLSR in protein prediction. To further enhance robustness, a deep CNNR model integrated with data augmentation (DA) and a convolutional block attention module (CBAM) was developed. This enhanced model achieved high predictive accuracy, with coefficients of determination (R_P²) of 0.972 for amylose and 0.992 for protein. In addition, a user-friendly application, RiceQuant-NIR, was developed to enable efficient data upload, prediction, and visualization, facilitating practical large-scale quality evaluation. These findings demonstrate that the DA + CBAM + CNNR model provides a robust and precise approach for simultaneous rice quality assessment, advancing the efficiency of food analysis research.

直链淀粉和蛋白质含量是影响水稻理化性状的关键品质指标。近红外（NIR）光谱提供了快速、无损的分析，但传统的卷积神经网络（CNN）模型往往存在过拟合和对全局光谱特征考虑有限的问题，阻碍了同时进行多目标预测。在这项研究中，我们引入了一种先进的卷积神经网络回归（CNNR）模型来同时测定直链淀粉和蛋白质的含量。首先通过光谱预处理和波数选择对偏最小二乘回归（PLSR）和支持向量机回归（SVMR）的标定模型进行优化。虽然PLSR在直链淀粉预测方面表现优异，但CNNR在蛋白质预测方面的表现明显优于PLSR。为了进一步增强鲁棒性，开发了一种集成数据增强（DA）和卷积块注意模块（CBAM）的深度CNNR模型。该模型具有较高的预测精度，直链淀粉和蛋白质的决定系数（RP²）分别为0.972和0.992。此外，开发了一个用户友好的应用程序RiceQuant-NIR，以实现高效的数据上传、预测和可视化，促进实际的大规模质量评估。这些结果表明，DA + CBAM + CNNR模型为水稻品质同步评价提供了一种稳健、精确的方法，提高了食品分析研究的效率。

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引用次数: 0

Impact of processing and roasting on quality parameters of Guatemalan, Peruvian, Rwandan, and Javanese specialty coffees 加工和烘焙对危地马拉、秘鲁、卢旺达和爪哇特色咖啡质量参数的影响

IF 4.6 2区农林科学 Q2 CHEMISTRY, APPLIED

Journal of Food Composition and Analysis

Pub Date : 2026-01-16 DOI: 10.1016/j.jfca.2026.108912

Matúš Várady , Jan Tauchen , Adéla Fraňková , Pavel Klouček , Miriam Vlčáková , Anna Reitznerová , Slavomír Marcinčák , Peter Popelka

We determined the impacts of natural (N), washed (W), honey (H), anaerobic fermentation (AF), and carbonic maceration (CM) processing methods and of roasting level (light and dark) on the colour parameters, antioxidant activity, and the contents of acrylamide (AA), 5-O-caffeoylquinic acid (5-O-CQA), caffeine (CAF), gallic acid (GA), cinnamic acid (CNA), and caffeic acid (CA) in specialty coffees from Guatemala (GUA), Peru (PER), Rwanda (RWA), and Java (JAV). The AA content in dark-roasted coffees (GUA-W, GUA-AF-H, and GUA-AF) decreased with the effects of roasting and processing, with values reaching 53, 39, and 30 µg/kg, respectively. The relationship between AA content and coffee color parameters could not be confirmed due to processing × roasting (P × R) interactions. Further P × R interactions were also found for the content of 5-O-CQA, CAF, GA, CNA and CA in the tested coffees. The colours, antioxidant activity, and the contents of AA, 5-O-CQA, CAF, GA, CNA, and CA were used to discriminate between 11 coffee samples based on processing method, origin, and within farms using principal component analysis (PCA). The PCA distinguished between coffees with high quality parameters that were processed using the W, AF, and CM methods and those processed using the N method and all RWA coffees. All of the specialty coffees examined were good sources of antioxidants and had low AA contents. Producing high-quality coffee requires achieving the optimal level of roasting for each specialty coffee, depending on processing method and origin, even within farms.

我们测定了天然(N)、水洗(W)、蜂蜜(H)、厌氧发酵（AF）和碳浸渍（CM）加工方法以及焙烧水平（浅焙烧和深焙烧）对危地马拉（GUA）、秘鲁（PER）、卢旺达（RWA）和爪哇（JAV）特产咖啡的颜色参数、抗氧化活性以及丙烯酰胺（AA）、5- o -咖啡酰奎宁酸（5-O-CQA）、咖啡因（CAF）、没食子酸（GA）、肉桂酸（CNA）和咖啡酸（CA）含量的影响。深焙咖啡中的AA含量（GUA-W、GUA-AF- h和GUA-AF）随着烘焙和加工的影响而降低，分别达到53、39和30 µg/kg。由于加工× 焙烧（P × R）的相互作用，AA含量与咖啡颜色参数之间的关系无法确定。测试咖啡中5-O-CQA、CAF、GA、CNA和CA的含量也存在P × R相互作用。采用主成分分析（PCA），利用颜色、抗氧化活性以及AA、5-O-CQA、CAF、GA、CNA和CA的含量对加工方法、产地和农场内的11种咖啡样品进行了区分。PCA区分了使用W、AF和CM方法加工的具有高质量参数的咖啡，以及使用N方法加工的咖啡和所有RWA咖啡。所有被检测的特色咖啡都是抗氧化剂的良好来源，AA含量低。生产高品质的咖啡需要达到每一种特色咖啡的最佳烘焙水平，这取决于加工方法和产地，甚至在农场内。

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引用次数: 0

On-site quantification of polysaccharides in Dendrobium huoshanense using a portable NIR spectrometer: A machine learning approach with SHAP interpretation 使用便携式近红外光谱仪现场定量霍山石斛多糖：机器学习方法与SHAP解释

IF 4.6 2区农林科学 Q2 CHEMISTRY, APPLIED

Journal of Food Composition and Analysis

Pub Date : 2026-01-16 DOI: 10.1016/j.jfca.2026.108915

Wenxia Li , Shuyu Chen , Hao Huang , Chaochuan Jia , Jiaqi Liu , Leilei Gao , Tao Xu , Maosheng Fu , Bangxing Han , Fang Wang

Dendrobium huoshanense, a precious edible-medicinal plant, faces a dearth of rapid, reliable quality assessment tools, hampering efficient resource utilization and market quality supervision. To address this gap, this study developed a portable, non-destructive, and interpretable method for quantifying D. huoshanense polysaccharides (DHP) using near-infrared spectroscopy (NIRS) coupled with machine learning. A systematic optimization workflow was implemented, incorporating outlier removal, MSC-second derivative preprocessing, UVE variable selection, and comparative evaluation of four machine learning models (BP-ANN, PLSR, RFR, 1D-CNN). The proposed MSC-2nd Derivative-UVE-RFR hybrid model delivered robust prediction performance: the test set yielded an average R² of 0.863 ± 0.072, RMSE of 1.915 ± 0.299, and RPD of 3.058 ± 0.753, while the optimal fold in cross-validation achieved an exceptionally high test R² of 0.938. Notably, SHAP (SHapley Additive exPlanations) analysis was integrated to enhance model interpretability, identifying key polysaccharide-associated spectral bands and clarifying their quantitative contribution mechanisms. This study provides a rapid, eco-friendly, and interpretable solution for on-site quality control of D. huoshanense, effectively mitigating batch variation in practical applications. It further facilitates sustainable utilization of this medicinal resource, reinforces market quality supervision, and lays a technical foundation for the non-destructive testing of other plant-based food and medicinal products.

霍山石斛是一种珍贵的食药两用植物，缺乏快速、可靠的质量评价工具，制约了资源的有效利用和市场质量监管。为了解决这一空白，本研究开发了一种便携式、非破坏性和可解释的方法，利用近红外光谱（NIRS）结合机器学习来定量霍山多糖（DHP）。系统的优化工作流程包括异常值去除、msc -二阶导数预处理、UVE变量选择以及四种机器学习模型（BP-ANN、PLSR、RFR、1D-CNN）的比较评估。所建立的MSC-2nd Derivative-UVE-RFR混合模型具有较好的预测效果：测试集的平均R²为0.863 ± 0.072，RMSE为1.915 ± 0.299，RPD为3.058 ± 0.753，交叉验证的最优fold达到了极高的检验R²0.938。值得注意的是，该研究整合了SHapley加性解释（SHapley Additive exPlanations）分析，以提高模型的可解释性，确定了关键的多糖相关光谱带，并阐明了它们的定量贡献机制。本研究提供了一种快速、环保、可解释性强的火山火龙鱼现场质量控制方案，有效减少了实际应用中的批次差异。进一步促进了该药材资源的可持续利用，加强了市场质量监管，并为其他植物性食品和药品的无损检测奠定了技术基础。

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引用次数: 0

Investigating the free and glycosidically-bound volatiles of an Indian landrace mango ‘Tikhilya’ during ripening 研究印度地方芒果“提希利亚”在成熟过程中的游离和糖苷结合挥发物

IF 4.6 2区农林科学 Q2 CHEMISTRY, APPLIED

Journal of Food Composition and Analysis

Pub Date : 2026-01-16 DOI: 10.1016/j.jfca.2026.108913

Hemangi Bawane, Ravish Godse, Purva Aditi, Ram Kulkarni

India harbors a vast collection of locally grown mango landraces. Landraces are important due to their role in maintaining agro-ecosystem and genetic diversity, yet they remain largely understudied. Here, a mango landrace ‘Tikhilya’ was assessed for changes in the free and glycosidically bound volatiles as well as activities of cell wall hydrolysis-related enzymes, viz. β-D-galactosidase, β-D-glucosidase, and α-D-mannosidase, during ripening. Among free volatiles, the pulp exhibited monoterpene-dominant profile, whereas peel was dominated by sesquiterpenes. Furanones, lactones, and pyrone showed ripening-specific appearance. In the glycosidically-bound fraction, oxygenated monoterpenes and phenolics dominated the pulp, while norisoprenoids and oxygenated sesquiterpenes emerged specifically during ripening. The activities of cell-wall hydrolysis enzymes increased exponentially during ripening, supporting the observation of the longer ripening period of ‘Tikhilya’ mango. β-D-Galactosidase exhibited the highest activity, suggesting its central role in fruit softening during ripening. Overall, the distinct profiles of free and glycosidically bound volatiles, combined with the enzyme activity patterns, underscore the biochemical uniqueness of ‘Tikhilya’ mango. This study emphasizes the need for conservation and further exploration of mango landraces.

印度拥有大量当地种植的芒果品种。地方品种在维持农业生态系统和遗传多样性方面发挥着重要作用，但它们在很大程度上仍未得到充分研究。在这里，我们评估了芒果地方品种“Tikhilya”在成熟过程中游离挥发物和糖苷结合挥发物的变化，以及细胞壁水解相关酶（β- d -半乳糖苷酶、β- d -葡萄糖苷酶和α- d -甘露糖苷酶）的活性。游离挥发物中，果肉以单萜为主，果皮以倍半萜为主。呋喃酮、内酯和吡酮表现出成熟特异性。在糖苷结合的部分中，果肉中主要是含氧的单萜和酚类物质，而在成熟过程中主要是类降异戊二烯和含氧的倍半萜。细胞壁水解酶活性在成熟过程中呈指数增长，支持了“Tikhilya”芒果成熟时间较长的观察结果。β- d -半乳糖苷酶表现出最高的活性，表明其在果实成熟软化过程中起着核心作用。总的来说，游离挥发物和糖苷结合挥发物的独特特征，结合酶活性模式，强调了“Tikhilya”芒果的生化独特性。本研究强调了保护和进一步开发芒果地方品种的必要性。

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引用次数: 0

Lebanese bay leaves (Laurus nobilis): A unique chemotypic and pharmacological profile with culinary and medicinal potential 黎巴嫩月桂叶（月桂叶）：具有独特的化学型和药理特征，具有烹饪和药用潜力

IF 4.6 2区农林科学 Q2 CHEMISTRY, APPLIED

Journal of Food Composition and Analysis

Pub Date : 2026-01-16 DOI: 10.1016/j.jfca.2026.108914

Rony Abou-Khalil , Diana Al-Hayek , Malak Al-Hakim , Jeanne Andary

Lebanese Laurus nobilis (Lebanese L. nobilis - bay laurel) is a widely studied Mediterranean aromatic plant; however, regional chemotypic variability, particularly in Lebanese populations, remains insufficiently characterized. This narrative review critically evaluates current literature on the phytochemical composition and pharmacological properties of Lebanese L. nobilis in comparison with other Mediterranean sources.

Available evidence indicates that Lebanese bay leaves exhibit distinct essential oil profiles, with notable variability in key constituents such as 1,8-cineole, sabinene, and α-terpinyl acetate, largely driven by altitudinal and climatic gradients. These findings support the existence of geographically influenced chemotypes with potential functional relevance. Pharmacological studies further suggest antimicrobial, antioxidant, anti-inflammatory, and neuroprotective activities, though most evidence remains derived from in vitro and preclinical models.

Despite promising bioactivity, this review identifies critical gaps in the literature, including limited chemotype standardization, scarcity of clinical validation, and insufficient integration of ecological and genetic data. Furthermore, the impact of climate change on chemical expression and resource sustainability remains poorly addressed.

Overall, this review concludes that Lebanese L. nobilis represents a chemotypically distinct and pharmacologically promising resource but emphasizes the need for coordinated multidisciplinary research to support its scientific validation, sustainable utilization, and potential industrial application.

黎巴嫩月桂（黎巴嫩L. nobilis -月桂）是一种被广泛研究的地中海芳香植物；然而，区域化学型变异，特别是在黎巴嫩人口中，仍然没有充分的特征。这篇叙事性的评论批判性地评估了目前关于黎巴嫩白杨的植物化学成分和药理特性的文献，并与其他地中海来源进行了比较。现有证据表明，黎巴嫩月桂叶具有独特的精油特征，其关键成分（如1,8-桉树油脑、sabinene和α-松油酯乙酸酯）具有显著的差异，主要受海拔和气候梯度的影响。这些发现支持地理影响的化学型与潜在功能相关性的存在。药理学研究进一步表明其具有抗菌、抗氧化、抗炎和神经保护活性，尽管大多数证据仍来自体外和临床前模型。尽管具有良好的生物活性，但本综述指出了文献中的关键空白，包括有限的化学型标准化，缺乏临床验证，以及生态和遗传数据的整合不足。此外，气候变化对化学表达和资源可持续性的影响仍未得到充分解决。综上所述，本综述认为，黎巴嫩白杨是一种化学特征独特且具有药理前景的资源，但强调需要协调多学科研究来支持其科学验证、可持续利用和潜在的工业应用。

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引用次数: 0