Food Analytical Methods最新文献_第10页

Flavor Characterization and Discrimination of Different Honeysuckle Varieties: Key Aroma Compounds and Taste Profiles 不同金银花品种的风味特征和鉴别：主要香气化合物和味道特征

IF 3 3区农林科学

Food Analytical Methods Pub Date : 2026-08-07 DOI: 10.1007/s12161-026-03209-2

Yu-Mei Zhai, Yongcheng Liao, Hong Li, Hui-dan Xiang, Weiwei Wu, Min Gong, Xiao-Juan Tang, Yun-Guo Liu

{"title":"Flavor Characterization and Discrimination of Different Honeysuckle Varieties: Key Aroma Compounds and Taste Profiles","authors":"Yu-Mei Zhai, Yongcheng Liao, Hong Li, Hui-dan Xiang, Weiwei Wu, Min Gong, Xiao-Juan Tang, Yun-Guo Liu","doi":"10.1007/s12161-026-03209-2","DOIUrl":"10.1007/s12161-026-03209-2","url":null,"abstract":"<div><p>In this study, a model was utilized employing headspace-solid phase microextraction-gas chromatography-mass spectrometry, headspace-gas chromatography-ion mobility spectrometry, electronic nose, and electronic tongue technologies integrated with the random forest method to identify and analyze the flavor characteristics of seven different varieties of honeysuckle. The results indicated that there are significant differences in the types and concentrations of volatile compounds among different varieties of honeysuckle. Except for the overlap between Little Maohua and Leaf Qi samples, the other samples could be effectively distinguished. Combined analysis using headspace-solid phase microextraction-gas chromatography-mass spectrometry and headspace-gas chromatography-ion mobility spectrometry identified linalool as a key compound significantly contributing to the characteristic aroma of honeysuckle. Additionally, the content of amino acids and sugars showed a positive correlation with the taste characteristics of honeysuckle. This study not only provides a multi-dimensional analysis method for the quality evaluation of honeysuckle but also offers a solid foundation for variety identification and quality control, which is of great significance for the development and utilization of honeysuckle resources.</p><h3>Graphical Abstract</h3>\u0000<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148750624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Revisiting a GC–MS Method for Determination of Acrylamide in Wheat-Based Baked Products 气相色谱-质谱法测定小麦烘焙制品中丙烯酰胺的研究

IF 3 3区农林科学

Food Analytical Methods Pub Date : 2026-08-07 DOI: 10.1007/s12161-026-03186-6

Lovemore Nkhata Malunga, Lan Shi, Sijo Joseph Thandapily

引用次数: 0

A Sensitive Aptasensor for Ofloxacin Detection Based on Split crRNA with CRISPR/Cas12a-Powered Cascade Strand Displacement and Phosphorothioate-Modified G-quadruplex/triplex Concatemer Fluorescence Probe 基于CRISPR/ cas12a驱动的级联链置换和硫代修饰的g -四/三联体荧光探针的分裂crRNA检测氧氟沙星的灵敏适配体传感器

IF 3 3区农林科学

Food Analytical Methods Pub Date : 2026-08-03 DOI: 10.1007/s12161-026-03215-4

Hao Su, Jiaye Wei, Zhixiang Zhang, Yu Ling, Jiaxuan Chen, Jiali Chang, Kai Shi, Tao Jiang

{"title":"A Sensitive Aptasensor for Ofloxacin Detection Based on Split crRNA with CRISPR/Cas12a-Powered Cascade Strand Displacement and Phosphorothioate-Modified G-quadruplex/triplex Concatemer Fluorescence Probe","authors":"Hao Su, Jiaye Wei, Zhixiang Zhang, Yu Ling, Jiaxuan Chen, Jiali Chang, Kai Shi, Tao Jiang","doi":"10.1007/s12161-026-03215-4","DOIUrl":"10.1007/s12161-026-03215-4","url":null,"abstract":"<div><p>The realization of sensitive detection of ofloxacin (OFL) residues is a key measure to prevent environmental risks caused by improper use of antibiotics, ensure food safety and promote public health security. Utilizing split crRNA with CRISPR/Cas12a (SCas12a)-powered cascade strand displacement amplification (C-SDA) and using phosphorothioate-modified G-quadruplex/triplex (psG43) concatemer fluorescence probe, a strategy named SCCA was devised for OFL detection. Target OFL triggers the SCas12a-driven C-SDA, and then activates SCas12a’s <i>trans</i>-cleavage activity. The activated SCas12a system cleaves reporter probe and then releases the psG43 sequence, which then combines with thioflavin T (ThT) to emit a fluorescence signal. The SCCA strategy not only avoids the design of PAM required by traditional C-SDA, but also can specifically detect OFL as low as 0.1 pM. The anti-interference advantage of psG43 enables the utilization of the SCCA strategy for OFL detection in milk samples.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148750432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Development of a Rapid and Low-Cost Methods for Quantification of Potassium Bromate and Sugars in Breads Using Digital Image Analysis 基于数字图像分析的面包中溴酸钾和糖的快速低成本定量方法的发展

IF 3 3区农林科学

Food Analytical Methods Pub Date : 2026-08-03 DOI: 10.1007/s12161-026-03203-8

Luana Sant’Ana Lima, Bruna R. de S. Gomes, Aline de Melo Vieira, Jandyson M. Santos

{"title":"Development of a Rapid and Low-Cost Methods for Quantification of Potassium Bromate and Sugars in Breads Using Digital Image Analysis","authors":"Luana Sant’Ana Lima, Bruna R. de S. Gomes, Aline de Melo Vieira, Jandyson M. Santos","doi":"10.1007/s12161-026-03203-8","DOIUrl":"10.1007/s12161-026-03203-8","url":null,"abstract":"<div><p>Bread is one of the most widely consumed staple foods worldwide, and the use of chemical additives during its production represents a significant concern due to potential health risks. Among these additives, potassium bromate (KBrO<sub>3</sub>) is classified as a possible carcinogen and is banned in many countries, including Brazil. In addition, sugars (glucose and fructose) are commonly added to enhance the flavor, texture, and shelf life. These additives, in some cases, exceed recommended dietary limits, and analytical methods are used to monitor the regulatory levels of these compounds. To achieve this goal, traditional methods, although efficient, are mostly expensive and time-consuming. Thus, we developed a rapid, low-cost, and environmentally friendly methods based on smartphone-assisted digital image analysis (DIA) for the quantification of KBrO<sub>3</sub>, glucose, and fructose in 22 commercial bread samples. After optimizing the DIA parameters, we have determined saturation and red as the best-performing channels for KBrO<sub>3</sub> and sugars, respectively. The DIA methods were validated against UV–Vis spectrophotometry, showing no statistically significant differences. KBrO<sub>3</sub> was detected in ten samples (from 4.03 to 31.69 µg g⁻<sup>1</sup>), indicating regulatory non-compliance. Glucose was the predominant sugar, indicating nutritional variability and the need for monitoring. The DIA methods enabled rapid, eco-friendly routine quality control.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12161-026-03203-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148750433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Rapid Identification of Dendrobium officinale with Different Growth Years Based on Nano-electrospray Ionization Mass Spectrometry基于纳米电喷雾电离质谱技术对不同生长年限的铁皮石斛进行快速鉴定 Rapid Identification of Dendrobium officinale with Different Growth Years Based on Nano-electrospray Ionization Mass Spectrometry基于纳米电喷雾电离质谱技术对不同生长年限的铁皮石斛进行快速鉴定

IF 3 3区农林科学

Food Analytical Methods Pub Date : 2026-08-03 DOI: 10.1007/s12161-026-03214-5

Jinzhu Gu, Qiuning Wang, Wenjie Yu, Yuyang Guo, Liping Luo

{"title":"Rapid Identification of Dendrobium officinale with Different Growth Years Based on Nano-electrospray Ionization Mass Spectrometry基于纳米电喷雾电离质谱技术对不同生长年限的铁皮石斛进行快速鉴定","authors":"Jinzhu Gu, Qiuning Wang, Wenjie Yu, Yuyang Guo, Liping Luo","doi":"10.1007/s12161-026-03214-5","DOIUrl":"10.1007/s12161-026-03214-5","url":null,"abstract":"<p><i>Dendrobium officinale</i> is a renowned medicinal and edible plant, and its market value is closely related to its growth years<i>.</i> In this study, a nano-electrospray ionization mass spectrometry (Nano-ESI-MS) was established to rapidly obtain the chemical profiling and identify <i>D. officinale</i> with different growth years. The proposed method demonstrated high linearity (<i>R</i><sup>2</sup> > 0.9979), low LODs (0.03–0.26 mg·L<sup>−1</sup>) and LOQs (0.09–0.77 mg·L<sup>−1</sup>), high precision (RSD < 10%), and satisfactory recoveries (82.29%–117.13%). Through this validated protocol, fluctuations in the levels of monosaccharides and disaccharides were characterized, corresponding to the trends in total polysaccharide content. A total of 45 metabolites were detected, primarily consisting of amino acids, flavonoids, and phenolic acids. Multivariate analyses including principal component analysis and partial least squares discriminant analysis achieved distinct separation of samples from different growth years (1–3 years). Subsequently, 28 differential metabolites were screened based on VIP > 1 and <i>P</i> < 0.05. The levels of amino acids increased age-dependently, whereas flavonoids exhibited a maximum accumulation in 2-year-old samples. In summary, Nano-ESI-MS offers a rapid and sensitive approach for differentiating <i>D. officinale</i> of different growth years and identifying metabolic variations, providing significant practical value for quality evaluation and market authentication. </p>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148750701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Real-Time, Non-destructive Pork Freshness Monitoring: Automated Ternary Grading via Anthocyanin-Based Smart Sensor and Machine Vision 实时、无损猪肉新鲜度监测：基于花青素的智能传感器和机器视觉的自动三元分级

IF 3 3区农林科学

Food Analytical Methods Pub Date : 2026-07-31 DOI: 10.1007/s12161-026-03216-3

Zhiran Liang, Jingxuan Qiu, Caiyun Liu, Shoaib Younas, Xin Wang

{"title":"Real-Time, Non-destructive Pork Freshness Monitoring: Automated Ternary Grading via Anthocyanin-Based Smart Sensor and Machine Vision","authors":"Zhiran Liang, Jingxuan Qiu, Caiyun Liu, Shoaib Younas, Xin Wang","doi":"10.1007/s12161-026-03216-3","DOIUrl":"10.1007/s12161-026-03216-3","url":null,"abstract":"<div><p>Addressing the demand for rapid, non-destructive meat quality assessment, this study developed a Vision-Based Pork Freshness Detection System (VPFDS) that integrates an anthocyanin-based colorimetric hydrogel sensor with machine vision and deep learning. The hydrogel sensor exhibited distinct pH and ammonia-responsive color transitions associated with the accumulation of volatile basic nitrogen compounds during pork spoilage. Among the investigated formulations, GE/ZnO/MA2 showed the most pronounced color change, making it optimal for freshness monitoring. A dedicated machine vision platform with controlled illumination was constructed to ensure stable image acquisition and eliminate variations commonly encountered in smartphone-based detection. Four convolutional neural network (CNN) models were evaluated for automated ternary freshness classification (“fresh”, “less fresh”, and “spoiled”). EfficientNetB0 achieved the best performance, with an overall accuracy of 94%, precision values above 0.90 for all freshness categories, and F1-scores of 0.92, 0.91, and 0.99 for fresh, less-fresh, and spoiled pork, respectively. Rigorous validation under real-world conditions confirmed the system’s reliability: results delivered within 2 s show high agreement with standard TVB-N measurements. This work provides a practical, rapid alternative to traditional destructive methods, offering significant potential for intelligent meat quality control in industrial applications.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148615108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Optical Sensing Platform Based on Liquid Crystal Droplets for the Detection of Hydrogen Peroxide and Catalase in Food Safety 基于液晶液滴的食品安全中过氧化氢和过氧化氢酶检测光学传感平台

IF 3 3区农林科学

Food Analytical Methods Pub Date : 2026-07-31 DOI: 10.1007/s12161-026-03197-3

Haichao Yu, Jiayue Huang, Jinfeng Zhao, Wang Luo, Jianjun Li, Xiaojun Liu

{"title":"Optical Sensing Platform Based on Liquid Crystal Droplets for the Detection of Hydrogen Peroxide and Catalase in Food Safety","authors":"Haichao Yu, Jiayue Huang, Jinfeng Zhao, Wang Luo, Jianjun Li, Xiaojun Liu","doi":"10.1007/s12161-026-03197-3","DOIUrl":"10.1007/s12161-026-03197-3","url":null,"abstract":"<div><p>With the large-scale development of the food industry, hydrogen peroxide (H₂O₂), a potent oxidizing agent, has been illicitly used by some manufacturers for bleaching, decolorization, and preservation, making it a significant potential risk in the field of food safety. Therefore, elucidating the hazardous mechanisms of H₂O₂ residues in food is of paramount importance for strengthening food safety monitoring systems and safeguarding public health. In this study, a label-free and highly sensitive sensing platform based on 4-cyano-4'-pentylbiphenyl (5CB) liquid crystal (LC) microdroplets was developed for the detection of H₂O₂ and catalase (CAT). The sensor enables the detection of H₂O₂ and CAT by monitoring the distinct optical pattern transitions of dodecanal-doped 5CB liquid crystal microdroplets under various conditions using polarized optical microscopy (POM). The results demonstrate that under pH 11 conditions, the limit of detection (LOD) for H₂O₂ is 0.01% (w/v), and for CAT is 0.01 ng/mL. Fourier Transform Infrared Spectroscopy (FTIR) was employed to characterize the post-reaction system, verifying the chemical transformations. Furthermore, simulated testing on food samples was successfully conducted, suggesting that this sensor holds significant potential for applications in food safety, biomedicine, and analytical detection. However, the optical sensing platform is sensitive to changes in ambient humidity and temperature, which may limit its direct application in complex food matrices. Although the system enables intuitive interpretation of POM textures, future work should investigate matrix interference, quantitative image analysis, portable readout integration, and validation using authentic food samples.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148615098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

An Electrochemical Sensor Based on ZnWO4/γ-Fe2O3 for the Detection of Chloramphenicol in Milk 基于ZnWO4/γ-Fe2O3的电化学传感器检测牛奶中氯霉素

IF 3 3区农林科学

Food Analytical Methods Pub Date : 2026-07-31 DOI: 10.1007/s12161-026-03207-4

Xiaodong Tu, Mingcai Yao, Liang Dong

引用次数: 0

A Ratiometric Electrochemical Sensor Based on Polythionine/UiO-66/COOH-MWCNTs for Sensitive Determination of Tert-Butylhydroquinone in Edible Oils 基于聚硫氨酸/UiO-66/COOH-MWCNTs的比例电化学传感器灵敏测定食用油中叔丁基对苯二酚

IF 3 3区农林科学

Food Analytical Methods Pub Date : 2026-07-29 DOI: 10.1007/s12161-026-03208-3

Meilin Song, Sijia Zhao, Haida Zhao, Jing Wang, Tenghe Ma, Tengfei Li

{"title":"A Ratiometric Electrochemical Sensor Based on Polythionine/UiO-66/COOH-MWCNTs for Sensitive Determination of Tert-Butylhydroquinone in Edible Oils","authors":"Meilin Song, Sijia Zhao, Haida Zhao, Jing Wang, Tenghe Ma, Tengfei Li","doi":"10.1007/s12161-026-03208-3","DOIUrl":"10.1007/s12161-026-03208-3","url":null,"abstract":"<div><p>Tert-butylhydroquinone (TBHQ) is a synthetic antioxidant widely used to inhibit lipid oxidation in edible oils; however, excessive intake may pose potential health risks, necessitating accurate and reliable analytical methods for its determination. Herein, a self-calibrated ratiometric electrochemical sensor based on a polythionine (pThi)/UiO-66/carboxylated multiwalled carbon nanotube (COOH-MWCNT) composite was developed for the sensitive detection of TBHQ in edible oils. The UiO-66/COOH-MWCNT hybrid was characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), and electrochemical impedance spectroscopy (EIS). By integrating the high surface area of UiO-66 with the superior conductivity of COOH-MWCNTs, the hybrid significantly enhanced electron transfer and electrocatalytic performance. In this ratiometric sensing strategy, the oxidation peak current of TBHQ at + 0.03 V served as the analytical signal, while the reduction peak current of electropolymerized pThi at − 0.24 V served as a stable internal reference to compensate for environmental fluctuations. Under optimal conditions, the proposed sensor exhibited two linear response ranges (0.10–100 μM and 100–500 μM) with a low detection limit of 0.078 μM (S/N = 3). The method was successfully applied to commercial soybean oil samples, achieving recoveries of 91.0–94.0%, with results in good agreement with those obtained by high-performance liquid chromatography (HPLC). This robust ratiometric sensing platform provides a practical, sensitive, and reliable strategy for rapid TBHQ determination in edible oils, demonstrating considerable potential for routine food quality monitoring.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148614900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Comparative Analysis of CNN Architectures with Optuna-Assisted Hyperparameter Optimization for Classifying Drought-Stressed Soybean Seeds CNN架构与optuna辅助超参数优化在干旱胁迫下大豆种子分类中的比较分析

IF 3 3区农林科学

Food Analytical Methods Pub Date : 2026-07-29 DOI: 10.1007/s12161-026-03204-7

Rustem Ustun, Banu Ulu, Muhammad Amjid, Burak Ulu, Bulent Uzun, Necati Çetin

{"title":"Comparative Analysis of CNN Architectures with Optuna-Assisted Hyperparameter Optimization for Classifying Drought-Stressed Soybean Seeds","authors":"Rustem Ustun, Banu Ulu, Muhammad Amjid, Burak Ulu, Bulent Uzun, Necati Çetin","doi":"10.1007/s12161-026-03204-7","DOIUrl":"10.1007/s12161-026-03204-7","url":null,"abstract":"<p>The reduction in soybean yield and quality due to drought makes rapid and non-destructive grading at the seed level critical. In this study, five genotypes × four irrigation treatments (20 classes) were discriminated using RGB images in a scalable DL pipeline. ResNet-18, ConvNeXt-Tiny/Base, DenseNet-121, and EfficientNet-B1 were trained using transfer learning. HPO was performed with Optuna, and the accuracy, F1 score, ROC-AUC, and resource consumption were reported. On a held-out test set that was disjoint from model selection, EfficientNet-B1 achieved the best accuracy of 94.8% (AUC = 0.9990), followed by DenseNet-121 96.2% (AUC = 0.9993), ResNet-18 92.9% (AUC = 0.9985), ConvNeXt-Base 92.1% (AUC = 0.9981) and ConvNeXt-Tiny 94.0% (AUC = 0.9985). In terms of efficiency, ResNet-18 was balanced at 2232 s and 46.9 MB, with the lowest inference latency (15.5 ms). Grad-CAM foci pointed to the hilum, edge contours, and shell texture. The results showed that 20-class genotype × irrigation discrimination is possible with high accuracy using RGB images, while Grad-CAM provided qualitative support that the models generally focused on seed-related regions rather than background areas. EfficientNet-B1 is recommended when the highest accuracy with a small model footprint is required, whereas ResNet-18 provides the lowest latency on the tested workstation and may be a suitable candidate for future edge-device benchmarking. These capabilities point to potential future directions, including rapid pre-screening prototypes, human-in-the-loop active learning, multi-location validation, on-device inference tests, and RGB+NIR fusion, which remain to be demonstrated.</p>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148614902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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