Food Physics最新文献_第2页

Comparative analysis of mathematical models and machine learning approaches for predicting dragon fruit seed mass 火龙果种子质量预测的数学模型与机器学习方法的比较分析

Food Physics

Pub Date : 2025-11-04 DOI: 10.1016/j.foodp.2025.100075

Pratik Madhukar Gorde, Charanjiv Singh Saini

This study evaluates the performance of traditional empirical models and machine learning approaches, specifically artificial neural networks (ANN), for predicting the mass of dragon fruit (Hylocereus spp.) seeds. Physical parameters of seeds were measured using a digital vernier caliper (P-VC) and a computer vision system with image processing (P-CV-IP). Mass prediction was conducted through mathematical models (MM-P-VC and MM-P-CV-IP) and ANN-based models (ANN-P-CV-IP). Results demonstrated that ANN models outperformed traditional mathematical approaches, achieving the highest coefficient of determination (R²) and the lowest root mean square error (RMSE), particularly in volume-based predictions. Among mathematical models, those based on physical dimensions provided the most reliable outcomes. Both P-VC and P-CV-IP measurements proved suitable for mass estimation; however, image-based quadratic models offered practical accuracy for routine applications. Digital image analysis further enabled rapid, non-destructive assessment of seed size and mass, while also capturing additional morphological attributes. Overall, the integration of image processing with ANN provides a precise, efficient, and resource-saving approach for dragon fruit seed mass modelling, offering potential for broader applications in agricultural product characterization.

本研究评估了传统经验模型和机器学习方法，特别是人工神经网络（ANN）在预测火龙果（Hylocereus spp.）种子质量方面的性能。采用数字游标卡尺（P-VC）和带图像处理的计算机视觉系统（P-CV-IP）测量种子的物理参数。通过数学模型（MM-P-VC和MM-P-CV-IP）和基于神经网络的模型（ANN-P-CV-IP）进行质量预测。结果表明，人工神经网络模型优于传统的数学方法，实现了最高的决定系数（R2）和最低的均方根误差（RMSE），特别是在基于体积的预测中。在数学模型中，基于物理维度的模型提供了最可靠的结果。P-VC和P-CV-IP测量都证明是适用于质量估计的；然而，基于图像的二次模型在日常应用中提供了实际的准确性。数字图像分析进一步实现了种子大小和质量的快速、非破坏性评估，同时还捕获了额外的形态属性。综上所述，图像处理与人工神经网络的结合为火龙果种子质量建模提供了一种精确、高效、节约资源的方法，在农产品表征方面具有广阔的应用前景。

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引用次数: 0

Modulating the texture of pea-based meat analogs: Influence of methylcellulose on mechanical and rheological properties of high moisture extrudates 调节豌豆基肉类类似物的质地：甲基纤维素对高水分挤出物的机械和流变特性的影响

Food Physics

Pub Date : 2025-10-30 DOI: 10.1016/j.foodp.2025.100074

Gabriela I. Saavedra Isusi , Laurids Pernice , Valentin Glubrecht , Valerie L. Stahl , Nico Leister

Adding hydrocolloids to plant-based meat analogs is a useful way to modulate the extrudates texture. However, it can alter the rheological properties of the melt, hence affect the extrusion process and change the extrudate’s structure in an unknown manner. This study focuses on the influence of methyl cellulose (MC) as a model hydrocolloid on the mechanical properties of pea protein extrudates produced through high-moisture extrusion cooking. MC was introduced in solutions with different molecular weights at varying concentrations during extrusion. The study aims to assess whether MC affects the anisotropic structure of pea extrudates due to protein interactions or melt viscosity effects. Observations included changes in specific mechanical energy and die pressure, mechanical and rheological characterizations, and protein solubility analyses. MC decreased the melt viscosity during extrusion by 20 % for all MC concentrations, although offline rheology measurements of protein-MC mixtures showed an increase dependent on concentration and type of MC. The meat analogs E-Moduli decreased due to MC addition by up to 75 %. Protein analysis revealed protein-MC complexation, regardless of the MC molecular structure. These results show that anisotropic structuring cannot be predicted alone through offline rheological characterization. Understanding these protein-hydrocolloid interactions can improve plant-based products.

向植物性肉类类似物中添加水胶体是调节挤出物质地的有效方法。然而，它可以改变熔体的流变特性，从而影响挤出过程，以一种未知的方式改变挤出物的结构。本文研究了甲基纤维素（MC）作为模型水胶体对高水分挤压蒸煮制备的豌豆蛋白挤出物力学性能的影响。在挤压过程中，MC被引入不同分子量、不同浓度的溶液中。该研究旨在评估MC是否由于蛋白质相互作用或熔体粘度效应而影响豌豆挤出物的各向异性结构。观察包括比机械能和模具压力的变化，机械和流变特性，以及蛋白质溶解度分析。在所有MC浓度下，MC在挤压过程中使熔体粘度降低了20% %，尽管蛋白质-MC混合物的离线流变学测量显示，随着MC的浓度和类型的增加，黏度有所增加。肉类类似物E-Moduli由于MC的加入而降低了75% %。蛋白质分析显示，无论MC分子结构如何，蛋白质-MC络合。这些结果表明，各向异性结构不能单独通过离线流变表征来预测。了解这些蛋白质-水胶体的相互作用可以改善植物性产品。

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引用次数: 0

Identification of maize seed varieties based on hyperspectral imaging combined with deep learning 基于高光谱成像和深度学习的玉米种子品种识别

Food Physics

Pub Date : 2025-10-10 DOI: 10.1016/j.foodp.2025.100073

Peng Xu , Lixia Fu , Ranbing Yang , Xiongfei Chen

Variety identification of seeds is crucial to guarantee crop quality and yield, as well as to ensure the quality and nutritional value of processed maize products. This study proposes a methodology for identifying maize seed varieties based on hyperspectral imaging (HSI) combined with deep learning. The mean spectra of the endosperm side (E1), non-endosperm side (N1), and both sides fused (F1) of maize seeds were extracted, followed by spectral pre-processing using Savitzky-Golay (SG) smoothing and multiplicative scatter correction (MSC), and feature wavelengths were selected from the spectral data using the competitive adaptive reweighted sampling (CARS) algorithm. K-nearest neighbor (KNN), decision tree (DT), support vector machine (SVM), random forest (RF), partial least squares discriminant analysis (PLS-DA), and convolutional neural networks with multi-scale feature fusion (CNN-MFF) were utilized to construct the discriminant models. The study results show that the model established using the spectra of F1 obtains better performance than E1 and N1, with an accuracy of more than 87.22 % on the prediction set. The CNN-MFF model built based on full and feature wavelengths obtained optimal results with accuracies of 97.78 % and 96.11 % on the prediction set, respectively, which proves that the CNN based on multi-scale feature fusion has better applicability and stability. In addition, visualization methods were used to demonstrate the recognition results to visualize the model's classification performance. In summary, using HSI and deep learning for the variety identification of maize seeds is feasible. The proposed method has significant potential for application in spectral analysis and can provide a reference for the online detection of seed quality in crops such as maize. Combining spectroscopic methods to analyze the distribution information of its internal nutrient elements can contribute to directing maize food processing and improving the utilization value of by-products.

种子品种鉴定是保证作物品质和产量，保证玉米加工产品质量和营养价值的关键。本研究提出了一种基于高光谱成像（HSI）和深度学习相结合的玉米种子品种识别方法。提取玉米种子胚乳侧（E1）、非胚乳侧（N1）和融合侧（F1）的平均光谱，采用Savitzky-Golay （SG）平滑和乘法散射校正（MSC）进行光谱预处理，并采用竞争自适应重加权采样（CARS）算法从光谱数据中选择特征波长。利用k近邻（KNN）、决策树（DT）、支持向量机（SVM）、随机森林（RF）、偏最小二乘判别分析（PLS-DA）和多尺度特征融合卷积神经网络（CNN-MFF）构建判别模型。研究结果表明，利用F1光谱建立的模型比E1和N1具有更好的预测性能，预测集的准确率达到87.22 %以上。基于全波长和特征波长构建的CNN- mff模型在预测集上分别获得了97.78 %和96.11 %的最优结果，证明基于多尺度特征融合的CNN具有更好的适用性和稳定性。此外，采用可视化方法对识别结果进行展示，使模型的分类性能可视化。综上所述，利用HSI和深度学习技术进行玉米种子品种鉴定是可行的。该方法在光谱分析中具有重要的应用潜力，可为玉米等作物种子质量在线检测提供参考。结合光谱学方法分析其内部营养元素的分布信息，有助于指导玉米食品加工，提高副产品的利用价值。

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引用次数: 0

Structural, thermal and functional properties of protein isolates from oyster mushroom (Pleurotus ostreatus) isolated by alkaline iso-electric, ultra-sonication and enzymatic extraction techniques 碱性等电、超音波及酶萃取法分离平菇蛋白的结构、热及功能特性

Food Physics

Pub Date : 2025-10-10 DOI: 10.1016/j.foodp.2025.100072

Ringshangphi Khapudang, Saleem Siddiqui

The protein isolates extracted from oyster mushroom by alkaline isoelectric precipitation, enzymatic and ultrasound assisted extraction methods were evaluated for their physicochemical and functional properties. Enzyme assisted extraction enhanced the zeta potential (-19.8 mV) and reduced particle size (288.5 nm) as compared to the standard alkaline isoelectric precipitation method having the values −5.95 mV and 621.8 nm, respectively. Enzymatic extraction with protease as well as ultrasound-assisted extraction led to a significant enhancement in the colloidal stability of the isolated proteins, attributable to improved dispersion and stronger electrostatic repulsion among protein molecules. Ultrasound assisted extraction showed a time- and amplitude-dependent effect. The highest values for water holding capacity (6.52 g/g), oil holding capacity (8.57 g/g), foaming capacity (52.17 %), and emulsifying activity (2.14 m²/g) were observed in the ultrasound-assisted extraction with 30 % for 10 min treatment, suggesting enhanced interfacial activity and surface functionality. Scanning electron microscopy confirmed structural disintegration and reduced aggregation in proteins isolated by enzymatic and ultrasound-assisted extraction methods. The findings demonstrate that both the enzyme- and ultrasound-assisted extraction methods are effective in enhancing the structural and functional quality of oyster mushroom protein isolates.

采用碱性等电沉淀法、酶法和超声辅助提取法对从平菇中提取的分离蛋白进行了理化性质和功能特性评价。与标准碱性等电沉淀法相比，酶辅助萃取法的zeta电位（-19.8 mV）和粒径（288.5 nm）分别提高了- 5.95 mV和621.8 nm。蛋白酶酶萃取和超声辅助萃取使分离蛋白的胶体稳定性显著增强，这是由于蛋白分子间的分散性改善和静电斥力增强。超声辅助提取具有时间依赖性和振幅依赖性。超声辅助萃取率为30 %、处理时间为10 min时，保水性（6.52 g/g）、保油量（8.57 g/g）、起泡量（52.17 %）和乳化活性（2.14 m²/g）最高，表明界面活性和表面功能增强。扫描电子显微镜证实，酶和超声辅助提取方法分离的蛋白质结构解体和聚集减少。结果表明，酶法和超声辅助提取方法均能有效提高平菇分离蛋白的结构和功能质量。

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引用次数: 0

To investigate the effects of controlled moisture levels on the peach (Prunus persica) kernels: Dimensional, gravimetrical, frictional, optical, and mechanical properties 研究控制水分水平对桃仁的影响：尺寸、重量、摩擦、光学和机械性能

Food Physics

Pub Date : 2025-09-18 DOI: 10.1016/j.foodp.2025.100071

Rajvinder Kour , Seerat Sharma , Mohammad Ubaid , Imran Sheikh , Mohd Aaqib Sheikh , Naseer Ahmed

Moisture content markedly influences the physical and mechanical properties of peach (Prunus persica) kernels, thereby affecting the performance of post-harvest handling and processing equipment. This study examined the effect of five controlled moisture levels (5.83 %, 9.86 %, 14.56 %, 20.12 %, and 25.26 %, wet basis) on the dimensional, frictional, optical, and mechanical properties of peach kernels. Dimensional measurements showed significant (p ≤ 0.05) increases of 3.42 %, 5.84 %, and 15.88 % in the major, medium, and minor axes, respectively, with rising moisture content. Static and dynamic frictional analyses indicated reduced flowability and increased resistance to movement at higher moisture levels. Optical assessment revealed total colour differences (ΔE) of 1.68, 4.70, 5.45, and 7.60 between moisture treatments, indicating moisture-induced changes in surface reflectance. Mechanical testing demonstrated that rupture force, hardness, deformation at rupture, and toughness decreased significantly (p ≤ 0.05) with increasing moisture content, with the lowest rupture force (1.86 N) recorded under horizontal loading. These results provide critical engineering parameters for designing and optimizing moisture-specific storage systems, conveying equipment, and cracking processes, thereby improving energy efficiency and product quality in peach kernel processing.

水分含量显著影响桃仁的物理机械性能，从而影响采后处理和加工设备的性能。本研究考察了五种控制湿度水平（5.83 %、9.86 %、14.56 %、20.12 %和25.26 %，湿基）对桃仁尺寸、摩擦、光学和机械性能的影响。尺寸测量结果表明，随着水分含量的增加，主轴、中轴和小轴分别显著增加了3.42 %、5.84 %和15.88 % （p ≤ 0.05）。静态和动态摩擦分析表明，在较高的水分水平下，流动性降低，运动阻力增加。光学评估显示水分处理之间的总色差（ΔE）为1.68、4.70、5.45和7.60，表明水分引起的表面反射率变化。力学试验表明，随着含水率的增加，破裂力、硬度、破裂变形和韧性显著降低（p ≤ 0.05），水平加载时破裂力最低（1.86 N）。这些结果为设计和优化湿度专用存储系统、输送设备和裂解工艺提供了关键的工程参数，从而提高了桃仁加工的能源效率和产品质量。

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引用次数: 0

Effect of a magnetic field on the production of Monascus pigments and citrinin via regulation of intracellular and extracellular iron content 磁场通过调节细胞内和细胞外铁含量对红曲红色素和柑桔素生产的影响

Food Physics

Pub Date : 2025-09-01 DOI: 10.1016/j.foodp.2025.100070

Yang Yang , Qian Liao , Jialan Zhang , Yingbao Liu , Li Li , Suo Chen , Mengxiang Gao

This study aims to elucidate the influences of magnetic fields (MFs) on the production of Monascus pigments (MPs) and citrinin by modulating both the intracellular and extracellular iron content in Monascus purpureus. The organism was treated with varying concentrations of L-allylglycine (L-AG), along with MFs of different intensities for 2 days during the early fermentation phase, as well as combinations of 1 mM L-AG and the MFs. The primary indicators assessed were the biomass, MPs production, citrinin production, and intracellular and extracellular iron content. The results indicate that exposure to MFs of varying intensities had no significant effect on the biomass of M. purpureus, while it significantly inhibited citrinin production. Conversely, exposure to a 1.6-mT MF significantly enhanced MPs production, while exposure to a 1.2- or 1.6-mT MF promoted the extracellular excretion of intracellular iron. Further, concentrations of 3 and 5 mM of L-AG significantly inhibited the growth of M. purpureus, whereas different concentrations of L-AG significantly inhibited MPs and citrinin production. Moreover, following treatment with both L-AG and MFs, all combinations exhibited a significant increase in MPs and citrinin production compared to L-AG treatment alone. In contrast, citrinin production in the group treated by L-AG with either a 1.2-mT or a 1.6-mT MF was significantly lower than that in the control group. Furthermore, intracellular iron content in the group treated by L-AG and a 1.6-mT or a 2.0-mT MF was reduced compared to that in the L-AG treatment group, with no significant difference from the control group. These findings suggest that appropriate exposure to MFs can decrease intracellular iron content and mitigate reductions in MPs and citrinin production induced by L-AG. Therefore, the regulation of MPs and citrinin synthesis induced by MFs in M. purpureus may be related to the intracellular iron content.

本研究旨在阐明磁场（mf）通过调节红曲霉胞内和胞外铁含量对红曲霉色素（MPs）和柑桔素（citrinin）产生的影响。在发酵早期，用不同浓度的l -烯丙基甘氨酸（L-AG）和不同强度的MFs处理2天，以及1 mM L-AG和MFs的组合。评估的主要指标是生物量、MPs产量、柑桔素产量以及细胞内和细胞外铁含量。结果表明，暴露于不同强度的MFs对M. purpureus的生物量没有显著影响，但显著抑制了柑桔素的产生。相反，暴露于1.6 mt MF显著增加MPs的产生，而暴露于1.2或1.6 mt MF促进细胞内铁的细胞外排泄。此外，浓度为3和5 mM的L-AG显著抑制了M. purpureus的生长，而不同浓度的L-AG显著抑制了MPs和柑桔素的产生。此外，与L-AG单独处理相比，L-AG和MFs联合处理后，所有组合都显示出MPs和柑桔蛋白产量的显著增加。相比之下，在120 mt或160 mt MF的L-AG处理组中，柠檬酸蛋白的产量显著低于对照组。此外，与L-AG处理组相比，L-AG和1.6 mt或2.0 mt MF处理组的细胞内铁含量降低，与对照组相比无显著差异。这些发现表明，适当暴露于MFs可以降低细胞内铁含量，减轻L-AG诱导的MPs和柠檬黄蛋白产生的减少。因此，MFs对紫癜分枝杆菌胞内铁含量的调控可能与胞内铁含量有关。

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引用次数: 0

Modeling of thermal effect in dynamic high-pressure microfluidization and its impact on heat sensitive components from fruit juice 动态高压微流化热效应建模及其对果汁热敏成分的影响

Food Physics

Pub Date : 2025-08-20 DOI: 10.1016/j.foodp.2025.100069

Yuling Sun , Mingying Wang , Jikai Wang , Li Dong , Hongchao Zhang

Dynamic high-pressure microfluidization (DHPM) offers advantages in continuous liquid foods processing compared to traditional thermal processes. While generally recognized as a non-thermal technique, the short-duration thermal effects occurred during DHPM and their impact on heat-sensitive components remain unclear. This study simulated the physical changes in the core part of DHPM, quantified cumulative thermal effects based on a chromogenic model, and compared DHPM’s thermal impact with pasteurization or high-pressure processing under comparable conditions. Results revealed that the instantaneous flow velocity during fluid collision at 400 MPa reached as high as 420 m/s, with the localized temperature of up to 107 °C. When the cooling temperature was set to 25℃, the total thermal effects generated by DHPM at 200 and 400 MPa corresponded to 4.8 and 13.2 s, respectively, as 72 ℃ equivalent treatment. Significantly increased (p < 0.05) equivalent treating times were observed for DHPM at 400 MPa without cooling. Under the testing condition, DHPM caused significant degradation of ascorbic acid (31.9–44.2 %) and polyphenol oxidase (PPO) (20.7–38.4 %) alone, and synergistically enhanced PPO inactivation with the presence of ascorbic acid in water. Findings indicated that, based on the model systems in the present work, DHPM at elevated pressure (above 400 MPa) might pose comparable thermal effects as short duration pasteurization. However, its impact on heat-sensitive components was also determined by complex physical actions, such as shear forces and fluid collisions. The information delivered is useful to design optimal DHPM processing with minimal impact on vital nutrients.

动态高压微流化（DHPM）与传统的热工艺相比，在连续液态食品加工中具有优势。虽然通常被认为是一种非热技术，但DHPM期间发生的短时间热效应及其对热敏成分的影响尚不清楚。本研究模拟了DHPM核心部分的物理变化，基于显色模型量化了DHPM的累积热效应，并在可比条件下比较了DHPM与巴氏灭菌或高压处理的热影响。结果表明，在400 MPa下，流体碰撞时的瞬时流速高达420 m/s，局部温度高达107℃；当冷却温度为25℃时，在72℃等效处理下，200和400 MPa下DHPM产生的总热效应分别为4.8和13.2 s。在400 MPa下，未经冷却的DHPM等效处理时间显著增加（p <； 0.05）。在测试条件下，DHPM单独对抗坏血酸（31.9 ~ 44.2% %）和多酚氧化酶（PPO）（20.7 ~ 38.4 %）具有显著的降解作用，并在抗坏血酸存在的情况下协同促进PPO失活。研究结果表明，基于本研究的模型系统，高压DHPM（高于400 MPa）可能会产生与短时间巴氏灭菌相当的热效应。然而，它对热敏成分的影响也取决于复杂的物理作用，如剪切力和流体碰撞。所提供的信息有助于设计对重要营养素影响最小的最佳DHPM处理方法。

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引用次数: 0

Deep learning model for precise and rapid prediction of tomato maturity based on image recognition 基于图像识别的番茄成熟度精确快速预测的深度学习模型

Food Physics

Pub Date : 2025-07-12 DOI: 10.1016/j.foodp.2025.100060

Muhammad Waseem , Muhammad Muzzammil Sajjad , Laraib Haider Naqvi , Yaqoob Majeed , Tanzeel Ur Rehman , Tayyaba Nadeem

Tomato maturity plays a pivotal role in optimizing harvest timing and ensuring product quality, but current methods struggle to achieve high accuracy along computational efficiency simultaneously. Existing deep learning approaches, while accurate, are often too computationally demanding for practical use in resource-constrained agricultural settings. In contrast, simpler techniques fail to capture the nuanced features needed for precise classification. This study aims to develop a computationally efficient tomato classification model using the ResNet-18 architecture optimized through transfer learning, pruning, and quantization techniques. Our objective is to address the dual challenge of maintaining high accuracy while enabling real-time performance on low-power edge devices. Then, these models were deployed on an edge device to investigate their performance for tomato maturity classification. The quantized model achieved an accuracy of 97.81 %, offering superior efficiency with an average classification time of 0.000975 s per image. The pruned and auto-tuned model also demonstrated significant improvements in deployment metrics, further highlighting the benefits of optimization techniques. These results underscore the potential for a balanced solution that meets the accuracy and efficiency demands of modern agricultural production, paving the way for practical, real-world deployment in resource-limited environments.

番茄成熟度对优化收获时机和保证产品质量起着至关重要的作用，但目前的方法难以同时实现高精度和计算效率。现有的深度学习方法虽然准确，但对于资源受限的农业环境的实际应用来说，往往对计算量要求过高。相比之下，更简单的技术无法捕捉精确分类所需的细微特征。本研究旨在利用通过迁移学习、修剪和量化技术优化的ResNet-18架构开发一个计算效率高的番茄分类模型。我们的目标是解决在低功耗边缘设备上保持高精度同时实现实时性能的双重挑战。然后，将这些模型部署在边缘设备上，研究它们对番茄成熟度分类的性能。量化模型的准确率为97.81 %，每张图像的平均分类时间为0.000975 s，效率很高。经过修剪和自动调优的模型还显示了部署指标的显著改进，进一步突出了优化技术的好处。这些结果强调了满足现代农业生产精度和效率要求的平衡解决方案的潜力，为在资源有限的环境中实际部署铺平了道路。

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引用次数: 0

Rice seed integrity evaluation: Developing a rapid onsite system to check seed fraud using a portable NIR spectroscopic device coupled with smartphone technology 水稻种子完整性评估：利用便携式近红外光谱设备与智能手机技术相结合，开发一种快速的现场系统来检查种子欺诈

Food Physics

Pub Date : 2025-07-11 DOI: 10.1016/j.foodp.2025.100059

Ernest Teye , Charles Lloyd Yeboah Amuah , Vida Gyimah Boadu , Kwadwo Anokye Dompreh , Maxwell Darko Asante , Francis Padi Lamptey , Stephen Narh , Daniel Dzorkpe Gamenyah , George Oduro Nkansah , Selorm Akaba

Rice seed integrity is critical in ensuring high yield and grain quality; however, seed fraud, particularly the misrepresentation of rice paddy (unhusked rice grain) as rice seed, is a growing concern that threatens sustainability efforts. This study investigates using a portable NIR spectroscopic device, combined with chemometric analysis, for rapid onsite identification of rice seed and paddy varieties for real-time verification of seed authenticity. A total of 280 rice samples, representing four varieties (Agra, Amankwatia, Legon 1, and Jasmine 85) across two categories (seeds and paddy), were analyzed. After applying various pre-processing techniques and principal component analysis (PCA), linear discriminant functions 1 and 2 successfully revealed distinct clustering patterns for both the varieties and categories (rice seed and paddy). Among the classification algorithms used, Random Forest (RF) achieved 100 % accuracy for rice seed identification and 97.38 % for paddy identification in the test sets. Support Vector Machine (SVM) demonstrated 98.15 % accuracy in distinguishing between rice seed and paddy for detecting seed fraud. These results suggest that a portable NIR device can reliably perform varietal identification and seed authenticity checks within the agricultural value chain. This technology has significant potential for use by seed inspectors, farmers, and regulatory officers, offering a non-destructive, real-time solution for the rice industry.

稻种完整性是确保高产和粮食品质的关键；然而，种子欺诈，特别是将稻谷（去壳的稻谷）谎称为水稻种子，是一个日益令人担忧的问题，威胁到可持续发展的努力。本研究利用便携式近红外光谱装置，结合化学计量分析，对水稻种子和水稻品种进行现场快速鉴定，实时验证种子的真伪。共280个水稻样本，代表四个品种（阿格拉、阿曼克瓦蒂亚、莱贡1号和茉莉85号），跨越两个类别（种子和水稻）进行分析。利用各种预处理技术和主成分分析（PCA），线性判别函数1和2成功地揭示了品种和类别（水稻种子和水稻）的不同聚类模式。在使用的分类算法中，随机森林（Random Forest， RF）对水稻种子的识别准确率为100 %，对水稻的识别准确率为97.38 %。支持向量机（SVM）对水稻种子和稻谷的识别准确率为98.15 %。这些结果表明，便携式近红外设备可以在农业价值链中可靠地进行品种识别和种子真实性检查。这项技术在种子检查员、农民和监管官员中具有巨大的应用潜力，为水稻行业提供了一种非破坏性的实时解决方案。

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引用次数: 0

Effect of high-intensity ultrasound-induced acoustic cavitation on enzymatic activity and quality attributes of granny smith apples during storage 高强度超声诱导声空化对青苹果贮藏过程中酶活性和品质属性的影响

Food Physics

Pub Date : 2025-07-04 DOI: 10.1016/j.foodp.2025.100058

Gulcin Yildiz , Gökçen Yıldız

This study investigates the effects of high-intensity ultrasound (HIU), chemical treatments (ascorbic acid and calcium chloride), and thermal treatment (water bath at 65°C) on metabolic, structural, and physical changes in Granny Smith apples during a 14-day cold storage period. HIU, a non-thermal physical processing method, utilizes acoustic cavitation and microstreaming to induce mechanical and oxidative stresses at the cellular level, thereby inhibiting enzymatic browning, reducing microbial load, and preserving bioactive compounds. Treated apples were stored at 4°C and analyzed on Days 0, 7, and 14 for antioxidant capacity using 2,2-diphenyl-1-picrylhydrazyl (DPPH), ferric reducing antioxidant power (FRAP), and oxygen radical absorbance capacity (ORAC) assays; total phenolic content (TPC); total flavonoid content (TFC); ascorbic acid levels; and enzymatic activities of polyphenol oxidase (PPO) and pectin methyl esterase (PME). Additional quality parameters included texture, colorimetric properties, microbial counts, and sensory quality. Compared to chemical and thermal treatments, HIU treatment significantly preserved firmness and color parameters, reduced enzymatic activity, and enhanced antioxidant retention (p < 0.05). Ultrasound-treated samples also exhibited minimized off-odor development and decay. These results demonstrate that HIU, through mechanisms such as acoustic cavitation and shear forces that alter cellular structure and inhibit enzymatic activity, offers a promising, non-thermal, scalable approach for extending shelf life and maintaining the nutritional and sensory quality of fresh produce, meeting the growing demand for clean-label, minimally processed foods.

本研究探讨了高强度超声（HIU）、化学处理（抗坏血酸和氯化钙）和热处理（65°C水浴）对青苹果14天冷藏期代谢、结构和物理变化的影响。HIU是一种非热物理处理方法，利用声空化和微流在细胞水平诱导机械和氧化应激，从而抑制酶褐变，减少微生物负荷，并保存生物活性化合物。处理后的苹果在4°C下保存，并在第0、7和14天使用2,2-二苯基-1-吡啶肼（DPPH）、铁还原抗氧化能力（FRAP）和氧自由基吸收能力（ORAC）测定分析其抗氧化能力；总酚含量（TPC）；总黄酮含量；抗坏血酸水平；多酚氧化酶（PPO）和果胶甲基酯酶（PME）的酶活性。其他质量参数包括质地、比色特性、微生物计数和感官质量。与化学处理和热处理相比，HIU处理显著保持了硬度和颜色参数，降低了酶活性，增强了抗氧化剂的保留（p <； 0.05）。超声波处理的样品也表现出最小的异味发展和腐烂。这些结果表明，HIU通过声空化和剪切力等机制改变细胞结构并抑制酶活性，为延长新鲜农产品的保质期、保持营养和感官质量提供了一种有前途的、非热的、可扩展的方法，满足了人们对清洁标签、最低加工食品日益增长的需求。

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