Food Analytical Methods最新文献

{"title":"Extraction and Characterization of Pectins from Ripe Grape Pomace Using Both Ultrasound Assisted and Conventional Techniques","authors":"Kianoush Vakilian,&nbsp;Leila Nateghi,&nbsp;Afshin Javadi,&nbsp;Navideh Anarjan","doi":"10.1007/s12161-024-02710-w","DOIUrl":"10.1007/s12161-024-02710-w","url":null,"abstract":"<div><p>Ripe grape pomace is a waste of grape juice processing that can be considered a valuable source for pectin extraction. The pectin was extracted via optimization using both ultrasound-assisted procedure (UAE-PRGP) and conventional extraction procedure (CE-PRGP). The pH values were 1.0, 2.0, and 3.0 for both techniques, the temperatures were set at 50, 60, and 70 °C for UAE, and 60, 75, and 90 °C for CE. The process time levels of the selected techniques were also different as 10, 20, and 30 min for UAE and 60, 90, and 120 min for CE. The yield (EY) of pectin extraction, the esterification degree (DE), and galacturonic acid (GA) were determined for optimization. The optimum values of pH, temperature, and time for UAE were 2.99, 58.82 °C, and 30 min, respectively, and for CE were 2.99, 66.42 °C, and 120 min, respectively. The optimum values (w/w %) for EY, DE, and GA were 16.45%, 42.97%, and 52.05%, respectively, in CE, and 24.25%, 27.78%, 61.39%, respectively, for UAE. Fourier transform infrared spectroscopy (FTIR) showed that UAE-PRGP had lower DE than CE-PRGP. Differential scanning calorimetry (DSC) revealed that UAE-PRGP had slightly greater thermal stability than CE-PRGP while commercial pectins (apple and citrus) had higher thermal stability than both extracted pectins. The apparent viscosity values of commercial pectins were higher than those of CE-PRGP and UAE-PRGP while all pectins indicated pseudoplastic manner. The UAE-PRGP showed higher stability and emulsifying activity than CE-PRGP, while lower than commercial pectins. UAE-PRGP with more GA and EY and less DE can be potentially used in various dairy foods.</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":"18 2","pages":"305 - 323"},"PeriodicalIF":2.6,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583574","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}

{"title":"A SERS and Fluorescence Dual-Signal Aptasensor for AFB1 Detection Based on DTNB Labeled AuNPs and CdTe Quantum Dots","authors":"Xiaoyuan Ma,&nbsp;Jinxiang Wei,&nbsp;Caiyun Jiang,&nbsp;Zhouping Wang","doi":"10.1007/s12161-024-02715-5","DOIUrl":"10.1007/s12161-024-02715-5","url":null,"abstract":"<div><p>Herein, an aptasensor with stable surface-enhanced Raman scattering (SERS) and fluorescence dual-signal output had been developed for the detection of aflatoxin B₁ (AFB₁). The quantum dots were encapsulated within silica to ensure the stability of fluorescence signal. The gold nanoparticles (AuNPs) were modified with SERS signal molecule DTNB and the complementary sequence (cDNA) of AFB₁ aptamer and then connected on the surface of silica to obtain the signal probes. In the meantime, Fe₃O₄ was coated with silica which was modified with aptamer to gain capture probes. The two probes could bind specifically based on the base complementary pairing principle. Then, the mixture was separated and gathered by an external magnet. At this time, the maximum SERS signal could be detected in the precipitate, and there was no fluorescence signal in the supernatant. Upon introduction of AFB₁ into the system, the signal probes would be released, resulting in fluorescence recovery in the supernatant while SERS signal weakened in the precipitate. The developed method showed a linear relationship of AFB₁ for the SERS signal in the range of 10⁻⁴–10³ ng/mL, with a detection limit of 0.087 pg/mL. The linear range for the fluorescence signal was from 10⁻⁴ to 10² ng/mL, with a detection limit of 0.100 pg/mL. The proposed technique was highly sensitive and accurate, which showed promising application prospects in food safety detection.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"18 2","pages":"293 - 304"},"PeriodicalIF":2.6,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583572","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}

{"title":"Development of a Method for the Rapid Determination of 17 Veterinary Drug Residues in Foods of Animal Origin by UPLC-MS/MS Combined with Pass-Through SPE Cartridge","authors":"Qianran Sun,&nbsp;Jun Liu,&nbsp;Yuan Gou,&nbsp;Wei Dong,&nbsp;Tao Wang,&nbsp;Huidan Deng,&nbsp;Yi Hua,&nbsp;Yicheng Shi","doi":"10.1007/s12161-024-02712-8","DOIUrl":"10.1007/s12161-024-02712-8","url":null,"abstract":"<div><p>In this study, a method was developed for the rapid determination of 17 veterinary drug residues in foods of animal origin using pass-through solid-phase extraction (SPE) coupled with ultra–high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Two grams of the sample was extracted ussing 8 mL of acetonitrile to water (85:15). An Oasis® HLB cartridge was selected for the clean-up of the sample without activation/calibration and elution. The separation was performed on an Acquity UPLC HSS T3 column (2.1 mm*100 mm, 1.8 μm) with a gradient elution using methanol–0.2% formic acid aqueous solution as the mobile phase. The analytes were detected in polarity switching electrospray ionization (ESI + / −) and multiple reaction monitoring (MRM) modes. The quantification was conducted using a matrix-matched standard solution external standard method. The performance of the employed UPLC-MS/MS method was observed to be satisfactory. The recoveries of the tests were within the range of 65.1–114.4%, with the relative standard deviations (RSDs) being lower than 12.3%. The limits of quantification (LOQs) of the target compounds ranged from 0.3 to 2.0 μg/kg (<i>S</i>/<i>N</i> ≥ 10), which complied with the relevant matrix limits mentioned in the food safety standards of Korea, the United States, and Canada in recent years. Positive samples of pentetrazol were identified in two batches of fish and one batch of chicken. However, the levels did not exceed the maximum residue level (MRL). This method has been successfully employed for the detection of a number of food products of animal origin in the local market, providing a methodological reference in cross-border food safety and testing.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"18 2","pages":"264 - 280"},"PeriodicalIF":2.6,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583559","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}

{"title":"Verification Analyses for the Detection of Bovine and Porcine Species in Foods Containing Animal Gelatin with Q-Exactive ORBITRAP Device","authors":"Nuray Gamze Yörük,&nbsp;Feridun Yılmaz,&nbsp;Adem Soycan","doi":"10.1007/s12161-024-02717-3","DOIUrl":"10.1007/s12161-024-02717-3","url":null,"abstract":"<div><p>Animal-derived gelatins are widely used in a variety of foods such as biscuits, chewing gum, chocolate, jelly beans, and confectionery, as well as medicines and food supplements. However, high temperatures, chemical treatments, and other methods used in the production process can damage the animal genes in the gelatin. This makes it difficult to extract DNA from gelatin-containing products and prevents the detection of animal species by technological methods such as real-time polymerase chain reaction (RT-PCR). This problem clearly demonstrates the need for new and more advanced technologies for species identification. In such cases where traditional methods are inadequate, more sensitive and reliable technological approaches should be developed. In this study, verification studies were conducted for species detection on 124 animal gelatin–containing products that could not be identified by RT-PCR due to DNA degradation. This was achieved using Quadrupole (Q) Exactive Orbitrap, a new generation molecular technology. As a result of the study, 62 samples containing bovine gelatin were spiked with 1% pork gelatin, and 62 of the samples were found to be positive for porks by Orbitrap. Similarly, 62 of the 62 samples containing pork gelatin spiked with 1% bovine gelatin were detected as bovine positive by Orbitrap. In this context, successful results were obtained in the detection of beef and pork species with LOD 1% level. The developed method was verified in terms of sensitivity, accuracy, and precision. As a result, limits of quantification (LOQ) were ranging from 10.0 µg/L. As a result, the limit of detection (LOD) was found to be 1%. Furthermore, this method was successfully applied to positive and negative controls.</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":"18 2","pages":"281 - 292"},"PeriodicalIF":2.6,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583507","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}

{"title":"Optimization of the Combined Use of Z-Sep Plus and EMR-Lipid in QuEChERS Procedure for the Analysis of Eight Pesticides in Real Milk Samples","authors":"Hatem I. Mokhtar,&nbsp;Ghada M. Salama,&nbsp;Alaa El Gindy,&nbsp;Eman A. Abdel Hameed","doi":"10.1007/s12161-024-02702-w","DOIUrl":"10.1007/s12161-024-02702-w","url":null,"abstract":"<div><p>One of the most applied procedures for the determination of trace analytes in complex matrices is QuEChERS (an acronym for Quick, Easy, Cheap, Effective, Rugged, and Safe). QuEChERS procedures include an extraction step followed by a dispersive solid-phase extraction (dSPE) for analytes cleaning-up from the matrix components. A challenging task in QuEChERS procedures is extracting and determining pesticides from samples of high fat such as milk samples. This challenge induced the innovation of new adsorbents for the clean-up step such as Z-Sep Plus® and EMR-Lipid® to enable removal of fatty matrix components without affecting the recovery of hydrophobic analytes. This work aims to apply experimental design to optimize the combined application of both QuEChERS clean-up adsorbents; Z-Sep Plus® and EMR-Lipid® in addition to other QuEChERS parameters in the determination of eight pesticides: hexachlorocyclohexane, dichlorodiphenyldichloroethane, dichlorodiphenyltrichloroethane, primiphos ethyl, diazinon, malathion, endrin, and dimethoate in milk matrix. This was augmented by optimization of GC–MS/MS and UPLC-MS/MS to detect and determine analytes in extracts. The experimental design of QuEChERS procedure enabled the optimization of Z-Sep Plus®- and EMR-Lipid®-added adsorbent amounts with other method parameters to enable the maximum recovery of analytes. Furthermore, the optimized methods enabled low detection limits of the studied pesticides within a short analysis time (28 min for GC and 12 min for LC methods, respectively). The procedure was validated according to European SANTE/11312/2021 Guideline. Quantitation limit ranged from 1.7 to 3.2 ng/mL for GC–MS/MS method and from 1.7 to 3 ng/mL for UPLC-MS/MS method. Greenness assessment of the methods followed four approaches indicating an excellent value of greenness for the proposed methods. Furthermore, 45 real milk samples collected from the Egyptian market were tested with the developed procedure for the presence of pesticides.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"18 2","pages":"245 - 263"},"PeriodicalIF":2.6,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12161-024-02702-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583557","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}

{"title":"VisDist-Net: A New Lightweight Model for Fruit Freshness Classification","authors":"Semih Demirel,&nbsp;Oktay Yıldız","doi":"10.1007/s12161-024-02716-4","DOIUrl":"10.1007/s12161-024-02716-4","url":null,"abstract":"<div><p>Agricultural production is of vital importance for humanity and the agricultural economy. Enhancing food security in agriculture can increase agricultural production and also help alleviate food scarcity. Also, the early detection of plant diseases can be crucial for quality agricultural products. The use of embedded software in Internet of Things devices for quality control processes has become quite widespread. These software applications require lightweight models. Therefore, a new model named the vision distillation network (VisDist-Net) has been developed to address real-world problems in agricultural production. This model aims to increase agricultural productivity by classifying three different fruits as rotten and fresh. An open-source dataset was used for this classification. VisDist-Net is a model created based on knowledge distillation. In the VisDist-Net model, knowledge is distilled from a vision transformer to a hybrid convolutional neural network (cnn). The strengths of both models have been combined by creating a hybrid student convolutional neural network through the fusion of feature vectors from resnet18 and mobilenetv1 models. This distillation process enables the creation of a high-performance lightweight model suitable for real-world applications. The VisDist-Net model has yielded quite promising results in this endeavor, achieving an f1-score of 0.9945 and an area under the curve (AUC) score of 0.9967.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"18 2","pages":"229 - 244"},"PeriodicalIF":2.6,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583560","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}

{"title":"Detection of Antibiotics in Migratory Goat Milk Using QuEChERS-HPLC Approach and Human Health Risk Assessment in Himalayan Region, India","authors":"Abhishek Sharma,&nbsp;Atul Kumar","doi":"10.1007/s12161-024-02713-7","DOIUrl":"10.1007/s12161-024-02713-7","url":null,"abstract":"<div><p>Antibiotic residue in milk poses significant risks to consumers’ health and economies. The current investigation aimed to analyze the occurrence of tetracycline residues in raw milk obtained from goats reared under a migratory system by nomadic pastoralists of Western Himalayan region, India, using the QuEChERS approach. The method was found to be accurate (recoveries, 87.07 to 97.70%), precise (RSD &lt; 10%), and sensitive (CCα, 1.61–9.40 ng/mL) as per European Commission guidelines. Quantitative analyses of 223 milk samples by validated high-performance liquid chromatography revealed that 18 samples (8.07%) had oxytetracycline and tetracycline residues in the concentration range of ND–307.5 ng/mL and 08 samples (3.6%) exceeded the maximum residual limits (MRLs) of 100 ng/mL for tetracycline in milk as set by the European Union and Codex Alimentarius Commission. The health risk assessments based on estimated daily consumer intake revealed that the hazard index for detected antibiotics is &lt; 1, indicating negligible acute risks at current contamination levels. However, the detection of antibiotics even in trace levels in migratory goat milk is a matter of solicitude and therefore requiring attention. This study highlights the importance of antimicrobial surveillance through green chemistry–based approaches like “QuEChERS” and awareness programs for shepherds to protect and promote human, animal, and environmental health.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"18 2","pages":"218 - 228"},"PeriodicalIF":2.6,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583518","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}

{"title":"Identification of Goat Milk Adulterated with Cow Milk Based on Total Synchronous Fluorescence Spectroscopy Combined with CNN","authors":"Xiaoyan Wang,&nbsp;Tao Wang,&nbsp;Rendong Ji,&nbsp;Huichang Chen,&nbsp;Hailin Qin,&nbsp;Zihan Huang","doi":"10.1007/s12161-024-02714-6","DOIUrl":"10.1007/s12161-024-02714-6","url":null,"abstract":"<div><p>Goat milk is rich in short-chain fatty acids, which are beneficial to health; however, the adulteration of goat milk with cow milk in the market poses a significant risk to individuals allergic to cow milk. This study utilizes the differences in total synchronous fluorescence spectra (TSFS) between cow milk and goat milk, combined with convolutional neural network (CNN), to detect goat milk adulteration. An improved algorithm was introduced: a Wasserstein generative adversarial network with gradient penalty (WGAN-GP) incorporating a convolutional attention mechanism. Data filtering was performed using a combination of Mahalanobis distance and K-means algorithm. Four classical CNN classifiers—AlexNet, DenseNet121, VGG16, and ResNet50—were evaluated under consistent training conditions. Comparative analysis shows that using a 1:2 sample enhancement ratio in conjunction with AlexNet plus WGAN-GP is most effective, achieving an accuracy of 97.78% after hyperparameter optimization. This study demonstrates that integrating TSFS with CNN offers a robust method for milk fingerprint recognition.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"18 2","pages":"202 - 217"},"PeriodicalIF":2.6,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583517","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}

{"title":"Development of IoT Enabled Deep Learning Model for Indian Food Classification: An Approach Based on Differential Evaluation","authors":"Mohit Agarwal,&nbsp;Amit Kumar Dwivedi,&nbsp;Dibyanarayan Hazra,&nbsp;Suneet Kumar Gupta,&nbsp;Deepak Garg","doi":"10.1007/s12161-024-02701-x","DOIUrl":"10.1007/s12161-024-02701-x","url":null,"abstract":"<div><p>Due to its extensive use in several areas, deep learning has attracted much interest in the past 10 years. Furthermore, decision-making applications for IoT devices are required, and the number of such devices is growing exponentially. Conversely, IoT devices are subject to resource constraints such as limited power, memory, and computation power. As a result, deep learning models that require less storage space and have a shorter inference time are more popular than traditional models. In the proposed article, we have discussed a differential evaluation-based approach for optimizing the storage space with a significant decrease in inference time without compromising the accuracy too much. We used an openly available Indian food dataset for the experimental work, using popular pre-trained architectures for classification purposes. We then compress the trained models using the differential evaluation approach. The simulation results show that the VGG16 architecture is compressed by 46.15%, with a decrease in precision of 1.91%.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"18 2","pages":"172 - 189"},"PeriodicalIF":2.6,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583446","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}

{"title":"Quantitative Detection of Zn2+ in Infant Formula and Living Cells Using Quinoline-Based Fluorescent Probes","authors":"Wen Lu,&nbsp;Jichao Chen,&nbsp;Jiongya Tang,&nbsp;Yutian chen,&nbsp;Yingying Ma,&nbsp;Wuhan Sang,&nbsp;Sicheng Feng,&nbsp;Shilong Yang,&nbsp;Yanqin Wang,&nbsp;Xu Li","doi":"10.1007/s12161-024-02709-3","DOIUrl":"10.1007/s12161-024-02709-3","url":null,"abstract":"<div><p>Zinc is an essential trace element and its deficiency has been related to skin conditions, Alzheimer’s disease, and some types of cancer. Therefore, detecting zinc ions in the human body with high sensitivity is important. Here, two “turn-on” quinoline-based fluorescent probes (<i>E</i>)-2-((2-(quinolin-2-yl) hydrazono) methyl) phenol (<b>QSP-H</b>) and (<i>E</i>)-4-chloro-2-((2-(quinolin-2-yl) hydrazono) methyl) phenol (<b>QSP-Cl</b>) were fabricated for the detection of Zn²⁺. Both the <b>QSP-H</b> and <b>QSP-Cl</b> revealed low LOD (71 nM for <b>QSP-H</b>, 67 nM for <b>QSP-Cl</b>) and high selectivity, and worked across a broad pH range (3 ‒12 for <b>QSP-H</b>, 3 ‒11 for <b>QSP-Cl</b>). The HRMS, ¹H NMR titration, DFT calculations and Job’s plot analysis were employed to explore the mechanism of Zn²⁺ detection through <b>QSP-H</b> and <b>QSP-Cl</b>. <b>QSP-H</b> and <b>QSP-Cl</b> were effectively applied to the quantitative assessment of Zn²⁺ in two infant formula samples and to the bioimaging-based detection of exogenous Zn²⁺ in living cells.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"18 2","pages":"190 - 201"},"PeriodicalIF":2.6,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583447","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}