Journal of Food Composition and Analysis最新文献

{"title":"A unique cuvette and near-infrared spectral imaging for fast and accurate quantification of milk compositions","authors":"Yuanyang Zhu ,&nbsp;Tao Sheng ,&nbsp;Chaoqun Huang ,&nbsp;Sheng Liu","doi":"10.1016/j.jfca.2024.107035","DOIUrl":"10.1016/j.jfca.2024.107035","url":null,"abstract":"<div><div>Analyzing the nutritional compositions of milk using traditional methods is costly, time-consuming, and impractical for rapid field measurements, resulting in delays in quality control procedures. This paper presents a rapid, accurate, and easy-to-use method for quantitative analysis of finished milk compositions using a low-cost, portable, and environmentally friendly measurement system. The system uses a near-infrared (NIR) broadband digital camera to capture spectral images of milk after it is placed in a customized cuvette in the short-wave NIR region (700–1050 nm). A machine learning algorithm that combines image edge detection and gradient-boosted decision trees then regresses these images to predict the protein and fat content of the milk. Each measurement requires a maximum of 1.75 mL of milk sample with no additional consumables and takes 0.1 s to complete. The coefficient of determination (R²_CV) for the fat detection model was 0.999 and the root mean square error (RMSE_CV) was 0.026 g/100 mL. For protein detection, the R²_CV was 0.957 and the RMSE_CV was 0.058 g/100 mL. The experimental results show that the system achieves high precision and stability while realizing miniaturization and portability.</div></div>","PeriodicalId":15867,"journal":{"name":"Journal of Food Composition and Analysis","volume":"138 ","pages":"Article 107035"},"PeriodicalIF":4.0,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744958","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}

{"title":"Exploring the effects of barley (Hordeum vulgare L.) germination on chemical composition, phytic acid, and potential malt prebiotic properties","authors":"Franco Van de Velde ,&nbsp;María P. Méndez-Galarraga ,&nbsp;Micaela Albarracín ,&nbsp;Antonela G. Garzón ,&nbsp;Marilin Aquino ,&nbsp;Raúl E. Cian ,&nbsp;Gabriel Vinderola ,&nbsp;Silvina R. Drago","doi":"10.1016/j.jfca.2024.107016","DOIUrl":"10.1016/j.jfca.2024.107016","url":null,"abstract":"<div><div>Germination is a complex process that triggers physical, chemical, and structural changes in grains, including macromolecule hydrolysis such as fiber components like β-glucans, and phenolic compound liberation, which may exhibit prebiotic effects. This work studies the impact of varied germination conditions on barley chemical composition, phytic acid content, and phenolic compound profile to obtain a potential prebiotic source. A combination of two temperatures (20 and 25°C) and times (35 and 72 h) was evaluated. Ungerminated barley and malt obtained under traditional brewing conditions (20°C for 95.5 h) were also analyzed. <em>Bifidobacterium animalis subsp. lactis</em> INL1 and <em>B. lactis</em> BB-12® were used to assess the potential prebiotic capacity. Barley germination at 25°C for shorter times (35–72 h) induced less starch, sugars, and β-glucans degradation than brewing malt. However, only brewing malt effectively reduced the content of phytic acid. Germination at 25°C produced a higher release of phenolic compounds. Malt obtained after germination at 20°C for 35 h was sufficient to produce a fermentable substrate by probiotic bacteria and did not stimulate pathogen-like strains. These results highlight the prebiotic potential of barley malt and uncover previously unexplored properties of this cereal, laying the groundwork for further investigation.</div></div>","PeriodicalId":15867,"journal":{"name":"Journal of Food Composition and Analysis","volume":"138 ","pages":"Article 107016"},"PeriodicalIF":4.0,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744851","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}

{"title":"S-methyl-L-cysteine sulfoxide and glucosinolate levels in Australian-sourced Brassica vegetables before and after domestic cooking","authors":"Caroline R. Hill ,&nbsp;Armaghan Shafaei ,&nbsp;Mary C. Boyce ,&nbsp;Liezhou Zhong ,&nbsp;Lois Balmer ,&nbsp;Joshua R. Lewis ,&nbsp;Jonathan M. Hodgson ,&nbsp;Lauren C. Blekkenhorst","doi":"10.1016/j.jfca.2024.107015","DOIUrl":"10.1016/j.jfca.2024.107015","url":null,"abstract":"<div><div>Currently no data exists on <em>S</em>-methyl-L-cysteine sulfoxide (SMCSO) levels in Australian-sourced vegetables and limited data exists for glucosinolates. The effect of various cooking methods on the retention of SMCSO and glucosinolates in Australian-sourced vegetables is also limited. This study measured SMCSO and ten glucosinolates in a selection of Australian-sourced <em>Brassica</em> vegetables, both raw and after steaming. We additionally measured SMCSO and glucosinolate levels in broccoli after microwaving, stir-frying and boiling. SMCSO contributed greater dry weight (0.6–1.9 %) than total glucosinolates combined (0.3–1.2 %) in these raw cruciferous vegetables. SMCSO levels from highest to lowest were: Brussels sprouts &gt; broccoli &gt; red cabbage &gt; kale &gt; cauliflower &gt; white cabbage &gt; Chinese cabbage; and glucosinolate levels were: Brussels sprouts &gt; white cabbage &gt; broccoli &gt; kale &gt; red cabbage &gt; Chinese cabbage &gt; cauliflower. Both SMCSO and the ten main glucosinolates quantified were relatively stable after light steaming across all vegetables measured, and after microwaving broccoli. Boiling and stir-frying broccoli led to significant losses in SMCSO and the two dominant glucosinolates, glucoraphanin and glucobrassicin (all <em>p</em> &lt; 0.05). Mild steaming and/or microwaving were preferable in retaining SMCSO and glucosinolates, whilst boiling and stir-frying were least favorable.</div></div>","PeriodicalId":15867,"journal":{"name":"Journal of Food Composition and Analysis","volume":"138 ","pages":"Article 107015"},"PeriodicalIF":4.0,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Research on rapid determination methods for main compositions and sensory quality of pumpkins based on hyperspectral imaging technology","authors":"Guangxia Zhao ,&nbsp;Zhuopin Xu ,&nbsp;Liwen Tang ,&nbsp;Xiaohong Li ,&nbsp;Zuyun Dai ,&nbsp;Zhao Xie ,&nbsp;Yilang Jiang ,&nbsp;Yuejin Wu ,&nbsp;Pengfei Zhang ,&nbsp;Qi Wang","doi":"10.1016/j.jfca.2024.107028","DOIUrl":"10.1016/j.jfca.2024.107028","url":null,"abstract":"<div><div>Rapid detection of pumpkin quality is of great significance for pumpkin production and breeding. In this study, hyperspectral imaging technology was utilized to facilitate the rapid detection of moisture content, starch content, and sensory quality in pumpkins, as well as to investigate their distribution within the pumpkin. The hyperspectral imaging data acquired from pumpkin slices was extracted and averaged. The models for moisture content and starch content in pumpkin built under Multiple Scatter Correction (MSC) pretreatment and Ridge regression proved to be the best ones, whose determination coefficients for cross-validation (<span><math><msub><mrow><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow><mrow><mi>cv</mi></mrow></msub></math></span>) were 0.968 and 0.869, and the root mean square error for cross-validation (<span><math><msub><mrow><mi>RMSE</mi></mrow><mrow><mi>cv</mi></mrow></msub></math></span>) were 1.142 and 0.365, respectively. Based on the moisture and starch values of pumpkin slices predicted by these models, the sensory quality scores of pumpkin slices can be further estimated. The sensory quality evaluation equation of pumpkin has a correlation of 0.934 to the sensory quality score of pumpkin obtained from the cooking experiment. Additionally, distribution maps summarizing the moisture, starch, and sensory quality of the pumpkin slices were generated, which could well reflect the spatial distribution characteristics of pumpkin quality indexes.</div></div>","PeriodicalId":15867,"journal":{"name":"Journal of Food Composition and Analysis","volume":"138 ","pages":"Article 107028"},"PeriodicalIF":4.0,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744846","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}

{"title":"Comparative analysis of lipid profile, and nutritional quality of eight Moroccan varieties of Punica granatum","authors":"Mohammed Amakhmakh ,&nbsp;Chaimae El Kourchi ,&nbsp;Ahmed Hajib ,&nbsp;Hicham Harhar ,&nbsp;Mohammed El Asri ,&nbsp;Jyoti Singh ,&nbsp;Abdelaaty A. Shahat ,&nbsp;Riaz Ullah ,&nbsp;Abdelhakim Bouyahya ,&nbsp;Jamal Charafi ,&nbsp;Abdeslam Meliani","doi":"10.1016/j.jfca.2024.107008","DOIUrl":"10.1016/j.jfca.2024.107008","url":null,"abstract":"<div><div>The purpose of this study was to investigate the nutritional value of eight varieties of <em>Punica granatum</em> seeds grown in Morocco (INRA station) as a source of vegetable oil. To this end we have investigated the impact of cultivars on lipophilic bioactive compounds, including Fatty acid (FA), phytosterol, and tocopherols, as well as the qualitative, nutritional and metabolic potential of the seeds of this varieties. The lipid profile analysis of pomegranate seed oils from the eight varieties revealed a predominance of unsaturated fatty acids, notably punicic acid (77.49–82.93 %). In terms of sterols, β-sitosterol scored the highest values among the sterols identified (520.31–726.82 mg/100 g). The chemical composition of tocopherols showed γ-tocopherol to be the major component (343.22–567.40 mg/100 g), with the red pomegranate showing the highest γ-tocopherol value, while the yellow pomegranate marked the highest concentration of total tocopherols. Nutritional indices calculated on the basis of fatty acid composition show favorable profiles for the Sefri and Mollar Ossin Hueso varieties.</div></div>","PeriodicalId":15867,"journal":{"name":"Journal of Food Composition and Analysis","volume":"138 ","pages":"Article 107008"},"PeriodicalIF":4.0,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744847","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}

{"title":"Classification of “Ricotta” whey cheese from different milk and Designation of Origin-protected samples through infrared spectroscopy and chemometric analysis","authors":"Martina Foschi,&nbsp;Alessandra Biancolillo,&nbsp;Samantha Reale,&nbsp;Francesco Poles,&nbsp;Angelo Antonio D’Archivio","doi":"10.1016/j.jfca.2024.107019","DOIUrl":"10.1016/j.jfca.2024.107019","url":null,"abstract":"<div><div>Whey cheeses are produced in various parts of the world, such as Portugal, Spain, and Turkey. In Italy, whey cheese goes under the name “ricotta”. This study investigates the classification of ricotta whey cheese derived from various milk sources (either protected designation of origin (PDO) or not) using an Attenuated Total Reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy combined with chemometric analysis. Employing the SPORT-LDA method, which can incorporate Variable Importance in Projection (VIP) analysis, 287 samples of ricotta cheese produced using milk from four different animals (sheep, cow, goat, and water buffalo) were classified according to the animal origin. This led to the correct classification of 97 % of the test samples (3 misclassified samples over 97). VIP analysis revealed that the spectral ranges of 3300–3100 cm⁻¹, 2900–2800 cm⁻¹, and 1700–1300 cm⁻¹ are consistently relevant across all milk sources, thanks to the key molecular vibrations associated with protein structures, lipid content, and water. Eventually, the analysis was circumscribed to sheep ricotta cheeses, because some of these present the PDO quality mark. SIMCA was used to classify PDO samples with respect to the Non-PDO sheep ricotta individuals. The application of SIMCA to model class PDO led to 82.1 % of sensitivity and 82.7 % of specificity (in external validation). The findings underscore the robustness of ATR-FTIR spectroscopy and chemometrics in maintaining the integrity of PDO products and ensuring quality control.</div></div>","PeriodicalId":15867,"journal":{"name":"Journal of Food Composition and Analysis","volume":"138 ","pages":"Article 107019"},"PeriodicalIF":4.0,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142724048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Aroma profiling of Chinese Chrysanthemum (Chrysanthemum morifolium Ramat.) using flavoromics analysis","authors":"Yan Gao ,&nbsp;Junyi Wang ,&nbsp;Mingyan Li ,&nbsp;Jing Wang ,&nbsp;Lina Qiao ,&nbsp;Ning Zhang ,&nbsp;Zhenhao Li ,&nbsp;Haitao Chen ,&nbsp;Jie Sun ,&nbsp;Shuqi Wang","doi":"10.1016/j.jfca.2024.107014","DOIUrl":"10.1016/j.jfca.2024.107014","url":null,"abstract":"<div><div><em>Chrysanthemum</em> flower (<em>Chrysanthemum morifolium Ramat.</em>), a traditional plant with both edible and medicinal properties in China, is widely used in the food and pharmaceutical industries. In this work, various representative <em>chrysanthemum</em> flowers, including Hangju (Taiju, TJ; Duoju, DJ), Chuju (CJ), and Gongju (GJ), were selected to investigate their aroma profiles via flavoromics analysis. Sensory analysis revealed that floral and grassy aroma were dominant in all samples, followed by sourness. Specifically, the note of caramel/sweet was most prominent in TJ, floral in DJ, sour in CJ, and minty in GJ. Gas chromatography-mass spectrometry (GC-MS) analysis identified terpenes as the major chemical components. Additionally, 94 aroma-active compounds were identified using gas chromatography-olfactometry-mass spectrometry (GC-O-MS) and aroma extract dilution analysis (AEDA), and the major odorants with the highest flavor dilution (FD) values of TJ, DJ, CJ, and GJ were 6-methyl-5-hepten-2-one, <em>β</em>-bisabolene, borneol, and 1,8-cineole, respectively. Accordingly, 1,8-cineole, borneol, (<em>E</em>)-<em>β</em>-farnesene, <em>β</em>-elemene, and <em>β</em>-caryophyllene were identified as key compounds contributing to aroma differences through PLS-DA combined with AEDA. In general, this work provides a theoretical basis for the quality control and industrial production of Chinese <em>chrysanthemum</em> flowers.</div></div>","PeriodicalId":15867,"journal":{"name":"Journal of Food Composition and Analysis","volume":"138 ","pages":"Article 107014"},"PeriodicalIF":4.0,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744850","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}

{"title":"Advancements in understanding and improving duck egg odor: Mechanisms, influential factors, and innovative strategies","authors":"Qishan Dong ,&nbsp;Lizhi Lu ,&nbsp;Yangying Sun ,&nbsp;Daodong Pan ,&nbsp;Yong Tian ,&nbsp;Jun He ,&nbsp;Tao Zeng","doi":"10.1016/j.jfca.2024.107020","DOIUrl":"10.1016/j.jfca.2024.107020","url":null,"abstract":"<div><div>Duck eggs, holding significant nutritional and commercial value, often face limitations due to their characteristic unpleasant fishy odor, predominantly originating from the egg yolk. Advancing the development and utilization of duck eggs requires a comprehensive understanding of the mechanisms behind odor formation and effective mitigation strategies. This review consolidates current research on the sources, detection methods, and formation mechanisms of duck egg odor, emphasizing factors such as dietary feed, breeding systems, and processing methods. It delves into the roles of gut microbiota, genetic factors such as flavin-containing monooxygenase 3 (FMO3) gene mutations, trimethylamine (TMA), and lipid and protein oxidation in odor development. Advanced processing and storage technologies, including physical treatments, protein modification, enzymatic processing, and coating preservation, are highlighted as promising approaches to reducing odor. Future research priorities include developing more sophisticated detection methods and gaining deeper insights into the genetic factors influencing odor formation.</div></div>","PeriodicalId":15867,"journal":{"name":"Journal of Food Composition and Analysis","volume":"138 ","pages":"Article 107020"},"PeriodicalIF":4.0,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744860","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}

{"title":"Characterization and classification of odorous raw milk: Volatile profiles and algorithm model perspectives","authors":"Weizhe Wang ,&nbsp;Ruirui Liu ,&nbsp;Yufang Su ,&nbsp;Suozai Ren ,&nbsp;Yanmei Xi ,&nbsp;Yun Huang ,&nbsp;Juan Wang ,&nbsp;Lixiang Lan ,&nbsp;Xuelu Chi ,&nbsp;Baoguo Sun ,&nbsp;Nasi Ai","doi":"10.1016/j.jfca.2024.107030","DOIUrl":"10.1016/j.jfca.2024.107030","url":null,"abstract":"<div><div>Odorous raw milk poses a growing threat to dairy product quality, negatively impacting both producers and consumers. However, methods for effectively identifying odorous raw milk have not been systematically established. In this study, 30 raw milk samples (RMSs) collected from different pastures were classified into 18 fresh RMSs and 12 odorous RMSs through sensory evaluation. Quantitative datasets of volatile compounds in RMSs were obtained using HS-SPME–GC–MS. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models identified nine key differential volatile compounds distinguishing fresh from odorous RMSs. Among these, hexanal and octanal were identified as potent odorants contributing to the off-odor in raw milk. Based on nine key difference volatile compounds, support vector machine (SVM), multilayer perceptron (MLP), and random forest (RF) algorithmic models were successfully constructed to classify RMSs to identify odorous RMSs. All models achieved classification accuracy exceeding 0.9, with the RF model performing the best, achieving an accuracy of 1.0. This work provides a reference and available workflow for identifying and labeling odorous RMSs.</div></div>","PeriodicalId":15867,"journal":{"name":"Journal of Food Composition and Analysis","volume":"138 ","pages":"Article 107030"},"PeriodicalIF":4.0,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744856","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}

{"title":"A method for constructing optical detection model of wheat seed purity based on sample generation and contrastive learning strategy","authors":"Shengqi Yan ,&nbsp;Xin Zhao ,&nbsp;Qibing Zhu ,&nbsp;Min Huang ,&nbsp;Xinnian Guo","doi":"10.1016/j.jfca.2024.107022","DOIUrl":"10.1016/j.jfca.2024.107022","url":null,"abstract":"<div><div>Seed purity is an essential indicator of seed quality, and use of optical techniques for seed purity testing has been extensively reported. Currently, most optical detection models for seed purity rely on the assumptions that the training set used to develop detection model contains all possible impurity varieties, and that the number of positive (the variety of interest) and negative samples (all possible impurities contained in that variety) in the training set is balanced. This assumption is often difficult to fulfil in practice due to the complexity of the seed production process. To address this issue, an optical detection model construction method for wheat seed purity based on sample generation and contrastive learning strategy was proposed in this study. The proposed method firstly employed a linear generation strategy to expand the impurity samples in training set, thus enhancing the diversity of impurity samples and improving the unbalance between the positive and negative samples. Thereafter, the contrastive learning loss function was introduced to train the optical detection model based on the deep convolutional neural network, so as to enhance the feature differences between positive and negative samples, and to improve the model's recognition accuracy for unknown impurity samples. Hyperspectral images of 4200 wheat seeds from six varieties were acquired, and a purity detection model for each variety was built by using the average spectra of the seed as input. The proposed method achieved average accuracy of 95.33 %, with improvements of 21.18 % over SVDD (78.67 %), 12.13 % over LSSVM (85.02 %), and 13.06 % over CNN (84.2 %), respectively. Further studies shown that the proposed method still maintains good detection accuracy under the condition that the test set contains multiply unknown impurities. The proposed method provides a feasible way for the construction of an optical detection model for seed purity in a real scenario.</div></div>","PeriodicalId":15867,"journal":{"name":"Journal of Food Composition and Analysis","volume":"138 ","pages":"Article 107022"},"PeriodicalIF":4.0,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744858","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}