Journal of Food Composition and Analysis最新文献_第3页

Evaluation of fruit quality and chemical characterization of local and standard pear (Pyrus communis L.) cultivars grown in Slovenia 斯洛文尼亚本地和标准梨（Pyrus communis L.）品种果实品质和化学特性的评价

IF 4.6 2区农林科学 Q2 CHEMISTRY, APPLIED

Journal of Food Composition and Analysis

Pub Date : 2026-01-21 DOI: 10.1016/j.jfca.2026.108921

Maja Mikulic-Petkovsek , Saša Krošelj , Petra Povše , Gregor Osterc

This study evaluated the specific morphological and biochemical parameters of fruits from ten pear cultivars, including several traditional old cultivars, such as 'President Drouard', 'Hartilian', 'Clapp’s Favorite', 'Poire de Cure', 'False Pituralka', 'Risovka', 'Santa Maria', 'Starkrimson', 'Triomphe de Vienne' and 'Nordhäuser Winterflorelle'. Significant differences in fruit quality were observed among the evaluated pear cultivars. The cultivars 'Risovka' (32.62 g) and 'President Drouard' (47.31 g) exhibited the lowest fruit weight, whereas 'Triomphe de Vienne' produced very large fruits with an average weight of 254.4 g. The highest total sugar content was recorded in 'False Pituralka' (138.5 g/kg FW), followed by 'Hartilian', 'Poire de Cure' and 'Nordhäuser Winterflorelle'. In contrast, the lowest total acid content was observed in 'Triomphe de Vienne' and 'Nordhäuser Winterflorelle', resulting in a high sugar-to-acid ratio (S/A) and, consequently, a sweet perceived flavor. The more acidic cultivars, characterized by lower S/A ratios, included 'Starkrimson', 'Santa Maria', 'President Drouard', 'Poire de Cure' and 'Clapp’s Favorite'. The highest phenolic compound contents in the fruit flesh were detected in 'Hartilian', 'Risovka', 'President Drouard' and 'Poire de Cure' (58.77–82.12 mg/kg FW), whereas in the peel, the cultivars 'False Pituralka', 'President Drouard' and 'Poire de Cure' contained the highest phenolic levels (1291–2111 mg/kg FW). The characterization of old pear cultivars from a specific growing region is vital for assessing their quality, as they represent an excellent source of genetic diversity and are invaluable for breeding new cultivars.

本研究对10个梨品种果实的形态和生化指标进行了评价，其中包括“总统Drouard”、“Hartilian”、“Clapp’s Favorite”、“Poire de Cure”、“假Pituralka”、“Risovka”、“Santa Maria”、“Starkrimson”、“Triomphe de Vienne”和“Nordhäuser Winterflorelle”等传统老品种。各评价品种果实品质差异显著。品种‘Risovka’（32.62 g）和‘President Drouard’（47.31 g）的果实重量最低，而‘Triomphe de Vienne’的果实非常大，平均重量为254.4 g。总糖含量最高的是“假Pituralka”（138.5 g/kg FW），其次是“Hartilian”，“Poire de Cure”和“Nordhäuser Winterflorelle”。相比之下，在“凯旋门”和“Nordhäuser冬花”中观察到的总酸含量最低，导致糖酸比高（S/ a），因此，感知到的甜味。酸性较强的品种，其特征是较低的S/A比率，包括“Starkrimson”、“Santa Maria”、“President Drouard”、“Poire de Cure”和“Clapp’S Favorite”。果肉中酚类化合物含量最高的品种为‘Hartilian’、‘Risovka’、‘President Drouard’和‘Poire de Cure’（58.77 ~ 82.12 mg/kg FW），而果皮中酚类化合物含量最高的品种为‘False Pituralka’、‘President Drouard’和‘Poire de Cure’（1291 ~ 2111 mg/kg FW）。来自特定产区的老梨品种的特性对评估其质量至关重要，因为它们代表了遗传多样性的极好来源，对培育新品种具有不可估量的价值。

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引用次数: 0

Afyonkarahisar province local dishes: Evaluation with five different nutrient profiling models Afyonkarahisar省地方菜肴：用五种不同的营养分析模型进行评估

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.2026.108922

Esila BAYAR , Ayşe ÜNLÜ

Nutrient profiling (NP) is a method used to assess foods based on their nutrient composition, which holds relevance for public health interventions. Local cuisines are often evaluated for their gastronomic value, but their health impacts warrant equal attention. This study aimed to evaluate 52 local dishes from Afyonkarahisar in Türkiye using five different NP models. The selected NP models were NRF9.3, SAIN-LIM, and Choices Programme, alongside the FSA-Ofcom WXY and Nutri-Score. Scores generated from NP models were ranked for comparative assessment. Salads had the highest score of NRF9.3, while soups had the lowest. According to FSA-Ofcom WXY, 63.46 % of dishes were healthier. SAIN-LIM model classified 17.31 % of dishes as Class 1 (recommended), and 38.46 % as Class 4 (be limited). Nutri-Score results showed 26.92 % of dishes in Class A (best quality), with none in Class E (lowest quality). Meanwhile, 3.85 % of dishes complied with Choices Programme criteria. Strong, positive, and statistically significant correlation was observed between specific ranked scores (p < 0,05). The findings highlight the importance of evaluating local dishes based on portion size and content of saturated fat, sodium, and added sugars. It is recommended to use NP models as objective tools to guide nutrition policies and support healthier food choices.

营养成分分析（NP）是一种基于营养成分评估食物的方法，与公共卫生干预措施有关。当地的菜系通常因其烹饪价值而受到评价，但它们对健康的影响也同样值得关注。本研究旨在使用五种不同的NP模型来评估泰国Afyonkarahisar的52道当地菜肴。所选择的NP模型是NRF9.3， sin - lim和Choices Programme，以及FSA-Ofcom的WXY和nutrition - score。由NP模型生成的分数被排序以进行比较评估。沙拉的NRF9.3得分最高，而汤的得分最低。根据FSA-Ofcom WXY的数据，63.46% %的菜肴更健康。SAIN-LIM模型将17.31 %的菜肴分类为1类（推荐），38.46 %的菜肴分类为4类（有限）。nutrition - score结果显示，26.92 %的菜肴为A类（最佳质量），无E类（最低质量）。同时，3.85 %的菜肴符合选择计划的标准。具体排名得分之间存在显著的正相关（p <； ，0.05）。研究结果强调了根据份量大小和饱和脂肪、钠和添加糖的含量来评估当地菜肴的重要性。建议使用NP模型作为指导营养政策和支持健康食品选择的客观工具。

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引用次数: 0

A collaborative study to validate in vitro assays for protein digestibility assessment using pH-drop and pH-stat methods 利用pH-drop和pH-stat方法验证体外蛋白质消化率评估的合作研究

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.2026.108918

Erin M. Goldberg , Amanda G.A. Sá , Adam J. Franczyk , Elaine S. Krul , Barbara Lyle , Mingyan Jing , Fiona Liu , Xin Wu , Nandika Bandara , Guillaume Brisson , Vicenta Garcia Campayo , Lingyun Chen , Sharon Hooper , Lamia L'Hocine , Mike Nickerson , Matthew Nosworthy , James D. House

The diversification of protein sources used in food formulation has increased the need to assess protein quality beyond traditional food forms. Protein digestibility is a key component of the Protein Digestibility Corrected Amino Acid Score (PDCAAS), the regulatory metric derived from rodent bioassays. Ethical concerns and the high cost of animal testing limit the ability of food formulators to screen protein ingredients and evaluate processing effects on digestibility. Findings from an international collaborative study are presented to position two in vitro methods, the pH-drop and pH-stat assays, as accredited approaches for determining protein digestibility. Nine laboratories participated in the study and analyzed 12 protein ingredients. Relative standard deviations for repeatability ranged from 0.8 to 2.1 % and 0.5–4.8 %, while reproducibility ranged from 1.2 to 3.6 % and 1.1–4.9 % for the pH-drop and pH-stat methods, respectively. Comparison between the two assays demonstrated strong correlation and moderate agreement, with the pH-stat assay yielding slightly lower digestibility values. In vitro protein digestibility coefficients aligned well with literature reported true faecal protein digestibility values for comparable, non-identical protein ingredients. Both methods received official AOCS Uniform Methods Committee approval, offering simple, affordable, reliable, and ethical tools to support informed decisions on protein digestibility during food formulation.

食品配方中使用的蛋白质来源的多样化增加了评估传统食品形式以外的蛋白质质量的需要。蛋白质消化率是蛋白质消化率校正氨基酸评分（PDCAAS）的关键组成部分，PDCAAS是来自啮齿动物生物测定的调节指标。伦理问题和动物试验的高成本限制了食品配方师筛选蛋白质成分和评估加工对消化率的影响的能力。一项国际合作研究的结果提出了定位两种体外方法，pH-drop和pH-stat测定，作为确定蛋白质消化率的认可方法。9个实验室参与了这项研究，分析了12种蛋白质成分。重复性的相对标准偏差为0.8 ~ 2.1 %和0.5 ~ 4.8 %，pH-drop法和pH-stat法的重复性为1.2 ~ 3.6 %和1.1 ~ 4.9 %。两种测定法之间的比较显示出很强的相关性和适度的一致性，pH-stat测定法产生的消化率值略低。体外蛋白质消化率系数与文献报道的可比较的、不相同的蛋白质成分的真实粪便蛋白质消化率值一致。这两种方法都获得了AOCS统一方法委员会的正式批准，提供了简单、负担得起、可靠和合乎道德的工具，以支持在食品配方过程中对蛋白质消化率的知情决策。

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引用次数: 0

Nutritional composition, phytochemistry, and mechanistic insights into the health-promoting properties of Termitomyces robustus: A comprehensive review 粗壮白蚁的营养成分、植物化学和促进健康的机理研究综述

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.2026.108903

Uche O. Arunsi , Eziuche A. Ugbogu , Chollom L. Israel , Victor C. Nwankwo , Chinonye C. Arunsi , Daniel C. Ezirim , Ahmad Altayyar , Tuba Esatbeyoglu , Solomon Owumi

Termitomyces robustus is a seasonal edible mushroom with significant nutritional and therapeutic potential. This review summarizes its nutritional content, phytochemical profile, and health-promoting properties based on research from ScienceDirect, Wiley, Springer, and PubMed. T. robustus contains various bioactive compounds, including gallic acid, chlorogenic acid, caffeic acid, ellagic acid, catechin, epicatechin, rutin, isoquercitrin, quercitrin, quercetin, and kaempferol, which have antioxidant, anti-inflammatory, antidiabetic, antimicrobial, and antifungal effects. The mushroom also provides a rich source of B vitamins, essential for carbohydrate metabolism. Toxicological studies confirm it is safe for consumption. Mechanistic evidence indicates these compounds influence key biological pathways such as Nrf2/KEAP1, TBK1, PPAR-γ, and α-amylase, supporting their potential medical use. However, research gaps remain, including optimal doses and effects on protein expression, which should be explored with high-throughput techniques. Additionally, studying new bioactive compounds in T. robustus could lead to new therapeutic options. This review emphasizes the nutritional and medicinal importance of T. robustus and supports its wider study in functional foods and pharmaceuticals.

粗犷白蚁菌是一种具有重要营养和治疗潜力的季节性食用菌。本文基于ScienceDirect、Wiley、b施普林格和PubMed的研究，综述了其营养成分、植物化学特征和促进健康的特性。粗竹含有多种生物活性化合物，包括没食子酸、绿原酸、咖啡酸、鞣花酸、儿茶素、表儿茶素、芦丁、异槲皮素、槲皮素和山奈酚，具有抗氧化、抗炎、抗糖尿病、抗菌和抗真菌作用。蘑菇还提供了丰富的B族维生素，对碳水化合物代谢至关重要。毒理学研究证实它可以安全食用。机制证据表明，这些化合物影响关键的生物途径，如Nrf2/KEAP1， TBK1， PPAR-γ和α-淀粉酶，支持其潜在的医疗用途。然而，研究空白仍然存在，包括最佳剂量和对蛋白质表达的影响，这应该用高通量技术来探索。此外，研究粗壮藤中新的生物活性化合物可能会带来新的治疗选择。本文强调了粗壮藤的营养和药用价值，并支持其在功能食品和药物领域的广泛研究。

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引用次数: 0

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。

{"title":"Non-destructive estimation of chlorophyll content in wasabi (Eutrema japonicum) leaves using spectral reflectance and deep learning models","authors":"Adenan Yandra Nofrizal , Rei Sonobe , Hiroto Yamashita , Akio Morita , Takashi Ikka","doi":"10.1016/j.jfca.2026.108919","DOIUrl":"10.1016/j.jfca.2026.108919","url":null,"abstract":"<div><div>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 (<em>Eutrema japonicum</em>), 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.</div></div>","PeriodicalId":15867,"journal":{"name":"Journal of Food Composition and Analysis","volume":"151 ","pages":"Article 108919"},"PeriodicalIF":4.6,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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