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Prof. Jun Wang
College of Biosystems Engineering and Food Science, Zhejiang University, China

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Research paper
Published: 28 July 2021 in Analytical and Bioanalytical Chemistry
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In recent years, the invasive cypress bark beetle (Phloeosinus aubei) has caused extensive damage to Platycladus orientalis plants in China, but its infestation is hard to monitor in the early stages. In this study, gas chromatography-mass spectrometry (GC-MS) was initially employed to investigate the volatile organic compound (VOC) emissions of P. aubei-infested P. orientalis saplings. The emissions of total sesquiterpenes were dominating (84−86% of total VOCs) and increased by 3.09-fold in P. aubei-damaged P. orientalis samples compared to undamaged samples, and the monoterpenes, aromatic compounds, and ketone emissions also had varying degrees of increase between 1.39-fold and 5.65-fold. Based on this variation, gas chromatography-ion mobility spectrometry (GC-IMS) was applied, as an untargeted analytical approach, to discriminate P. orientalis samples with different invasive severity. Two different features derived from GC-IMS data were adopted as the input information for classification and prediction models. Results showed that grid search support vector machine (GS-SVM) combined with multilinear principal component analysis (MPCA) based on spectral fingerprint achieved the best classification performances (> 88.98%), and partial least squares discriminant analysis (PLSR) method can accurately predict the pest numbers (R2 > 0.9423 and RMSE < 0.9827). In a word, the VOC profiling-based approach had the potential for evaluating P. aubei invasive severity and pest management.

ACS Style

Chengyu Zheng; Qinan Zhou; Zhenhe Wang; Jun Wang. Behavioral responses of Platycladus orientalis plant volatiles to Phloeosinus aubei by GC-MS and HS-GC-IMS for discrimination of different invasive severity. Analytical and Bioanalytical Chemistry 2021, 1 -10.

AMA Style

Chengyu Zheng, Qinan Zhou, Zhenhe Wang, Jun Wang. Behavioral responses of Platycladus orientalis plant volatiles to Phloeosinus aubei by GC-MS and HS-GC-IMS for discrimination of different invasive severity. Analytical and Bioanalytical Chemistry. 2021; ():1-10.

Chicago/Turabian Style

Chengyu Zheng; Qinan Zhou; Zhenhe Wang; Jun Wang. 2021. "Behavioral responses of Platycladus orientalis plant volatiles to Phloeosinus aubei by GC-MS and HS-GC-IMS for discrimination of different invasive severity." Analytical and Bioanalytical Chemistry , no. : 1-10.

Journal article
Published: 15 July 2021 in Computers and Electronics in Agriculture
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Mechanical vibration response using a self-made hammering device was performed to non-destructively measure Chinese cabbage quality using multidirectional vibration indices. To obtain a wide range of texture and different chemical attributes in cabbages, experiments were conducted every 3 d over 16 d of storage. The vibration parameters of each cabbage were extracted from the optimized frequency-response curves in both X-axis and Z-axis directions. A total of 26 features were extracted from the time and frequency domain signals. Cabbage quality attributes were determined by compactness and chemical indicators (soluble solids content, moisture content, Vitamin C content, and crude fiber content), and the newly introduced indicator of compactness was determined by a self-made apparatus. Stepwise multiple linear regression methods were used to quantitatively and qualitatively analyze the cabbage quality. Results showed that the compactness indicator was applicable to evaluate the texture of Chinese cabbage. The method which utilized mechanical vibration response was capable of evaluating and predicting cabbage quality indicators except for soluble solids content, particularly for compactness (rp = 0.757, RMSEP = 0.002 MPa). The better detection method for the vibration test was to stimulate the point in the equatorial part of a Chinese cabbage, and then collected the response signals at the point 180° apart from the excitation point. The factors consist of the second resonant frequencies in X-axis and Z-axis directions were designated as the major factors, and the residual vibration signals contributed to improving the evaluation effects of cabbage quality, as well as the morphological index, mass, density, and logarithmic damping ratio in the Z-axis. The proposed approach provides a method for non-destructive detection of Chinese cabbage quality, and it may be applied to online inspection, grading, and quality judgment during the post-harvest process.

ACS Style

Jing Zhang; Jun Wang; Chengyu Zheng; Hui Guo; Fake Shan. Nondestructive evaluation of Chinese cabbage quality using mechanical vibration response. Computers and Electronics in Agriculture 2021, 188, 106317 .

AMA Style

Jing Zhang, Jun Wang, Chengyu Zheng, Hui Guo, Fake Shan. Nondestructive evaluation of Chinese cabbage quality using mechanical vibration response. Computers and Electronics in Agriculture. 2021; 188 ():106317.

Chicago/Turabian Style

Jing Zhang; Jun Wang; Chengyu Zheng; Hui Guo; Fake Shan. 2021. "Nondestructive evaluation of Chinese cabbage quality using mechanical vibration response." Computers and Electronics in Agriculture 188, no. : 106317.

Journal article
Published: 17 June 2021 in Applied Sciences
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Saturated soil shear strength is a primary factor that reflects the driving resistance of agricultural machinery in paddy soils. The determination of soil shear strength indicators, such as cohesion and internal frictional angle, is crucial to improve the walking efficiency of agricultural machinery in paddy soils. However, the measurement of these indicators is often costly and time-consuming. Soil moisture content, density, and clay content are crucial factors that affect the cohesion and internal friction angle, while very limited studies have been performed to assess the interactive effects of the three factors on soil shear characteristics, especially on paddy soils. In this study, eight soil samples were taken from eight paddy fields in Southeastern China, and the central composition rotatable design was used to classify the soil samples into five levels based on different clay content (X1), moisture content (X2), and density (X3). The direct shear tests were carried out indoors on the remolded paddy soil using a self-made shear characteristic measuring device. Then, both individual and interactive effects of X1, X2, and X3 on soil cohesion and internal friction angles on paddy soils were systematically investigated and analyzed using the regression analysis method in the data processing software Design-Expert. Our results indicated that the effects of the three environmental factors on soil cohesion were in the order of X1 >X2 >X3, while the order was X2 >X3 >X1 for the impact on internal friction angle. The interactive effects were in the order of X1X2 >X1X3 >X2X3 for cohesion and X1X2 >X2X3 >X1X3 for internal friction angle. Two prediction models were successfully established to quantify the soil cohesion and internal friction angle as affected by soil physical properties, and the coefficient of determination (R2) was 0.91 and 0.89 for the two equations, respectively. The model validations using new soil samples suggested that the models were capable of predicting the shear characteristic parameters under different physical parameters effectively, with errors between predicted and measured soil shear strength indicators within 15% and relative root mean square error less than 11%.

ACS Style

Qianjing Jiang; Ming Cao; Yongwei Wang; Jun Wang; Zhuoliang He. Estimation of Soil Shear Strength Indicators Using Soil Physical Properties of Paddy Soils in the Plastic State. Applied Sciences 2021, 11, 5609 .

AMA Style

Qianjing Jiang, Ming Cao, Yongwei Wang, Jun Wang, Zhuoliang He. Estimation of Soil Shear Strength Indicators Using Soil Physical Properties of Paddy Soils in the Plastic State. Applied Sciences. 2021; 11 (12):5609.

Chicago/Turabian Style

Qianjing Jiang; Ming Cao; Yongwei Wang; Jun Wang; Zhuoliang He. 2021. "Estimation of Soil Shear Strength Indicators Using Soil Physical Properties of Paddy Soils in the Plastic State." Applied Sciences 11, no. 12: 5609.

Journal article
Published: 22 May 2021 in Biosystems Engineering
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Relaxation tests were performed to determine the viscoelastic properties of intact Chinese cabbage under transverse and longitudinal loading using Maxwell models. The differences in the relaxation properties for different compression directions were evaluated and a variety of macroscopic deformation characteristics was described using a stereomicroscope. It was found that Chinese cabbage showed rheological properties and elasticity under low loading speed and small deformations, and the upper limit value of failure and deformation in transverse compression was greater than that for longitudinal compression. Additionally, relaxation rate in the transverse loading process was generally faster than that in the longitudinal process, and resistance to deformation and viscosity during the transverse loading process was stronger than that in the longitudinal process. This suggested that the relaxation parameters of cabbages greatly differed in different locations, and the loading directions seem to affect the Maxwell model parameters and peak force response. This is probably because of the differences in cell tissue structure and arrangement which changed in the intercellular space during the loading process. Moreover, the differences in relaxation behaviours under different loading directions could be explained by the micro-mechanical properties of their tissue's cell structure, which is consistent with the evaluation results of the relaxation rate. The precise description of the differences in rheological properties of Chinese cabbage under different loading directions could help optimise the packaging and storage strategies and determine the most appropriate process parameters to reduce mechanical damage during storage and processing operations.

ACS Style

Jing Zhang; Jun Wang; Yifeng Hao; Chengyu Zheng; Dongdong Du. Effects on relaxation properties of Chinese cabbage (Brassica campestris L.) subjected to different compression directions. Biosystems Engineering 2021, 207, 81 -91.

AMA Style

Jing Zhang, Jun Wang, Yifeng Hao, Chengyu Zheng, Dongdong Du. Effects on relaxation properties of Chinese cabbage (Brassica campestris L.) subjected to different compression directions. Biosystems Engineering. 2021; 207 ():81-91.

Chicago/Turabian Style

Jing Zhang; Jun Wang; Yifeng Hao; Chengyu Zheng; Dongdong Du. 2021. "Effects on relaxation properties of Chinese cabbage (Brassica campestris L.) subjected to different compression directions." Biosystems Engineering 207, no. : 81-91.

Journal article
Published: 13 April 2021 in Journal of Food Engineering
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Static rheological behaviors of Chinese cabbage have rarely been reported, and the quality are still mostly assessed by empirical methods. This study mainly aimed explore the feasibility of using relaxation characteristics to nondestructively evaluate the cabbage quality. Intact Chinese cabbages (Brassica pekinensis L.) were subjected to comprehensive stress relaxation tests and evaluation under storage conditions (at 10 ± 1 °C, 85 ± 2 % RH). The five-element Maxwell models (R2 > 0.99) were applied to effectively describe the relaxation behaviors of cabbages. Among the parameters of the relaxation model, the values in the first component were significantly higher than those values in the second component. Maxwell model parameters were correlated well with the quality parameters of cabbage. Meanwhile, the firmness, SSC, and crude fiber content could be effectively predicted by relaxation parameters, with the exception of VC content and moisture content. The predictive models of quality properties were effectively validated by t-test and multi-linear regression methods. The results corroborated the relationship between relaxation characteristics and quality properties, which indicated that the stress relaxation test was a feasible and nondestructive method to evaluate and predict the quality properties for Chinese cabbages.

ACS Style

Jing Zhang; Jun Wang; Shuang Gu; Chengyu Zheng; Dongdong Du. Relaxation characteristics for quality evaluation of Chinese cabbage. Journal of Food Engineering 2021, 306, 110635 .

AMA Style

Jing Zhang, Jun Wang, Shuang Gu, Chengyu Zheng, Dongdong Du. Relaxation characteristics for quality evaluation of Chinese cabbage. Journal of Food Engineering. 2021; 306 ():110635.

Chicago/Turabian Style

Jing Zhang; Jun Wang; Shuang Gu; Chengyu Zheng; Dongdong Du. 2021. "Relaxation characteristics for quality evaluation of Chinese cabbage." Journal of Food Engineering 306, no. : 110635.

Research article
Published: 10 January 2021 in Journal of the Science of Food and Agriculture
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BACKGROUND Rice grains can be easily contaminated by certain fungi during storage and market chain, thus generating risk for humans. Most classical methods are complex and time‐consuming for manufactures and consumers. However, E‐nose technology provides analytical information in a non‐destructive and environmentally friendly manner. Subsequently, two feature fusion data combined with chemometrics were employed for the determination of Aspergillus spp. contamination in milled rice. RESULTS Linear discriminant analysis (LDA) analysis indicated that the efficiency of fusion signals (‘80th s values’ and ‘area values’) outperformed that of independent E‐nose signals. Meanwhile, LDA showed a clearly discrimination to fungi species in stored milled rice for four group on day 2, and the discrimination accuracy reached 92.86% by using extreme learning machine (ELM). GC–MS analysis showed that the volatile compounds had close relationships with fungal species in rice. Quantification results of colony counts in milled rice showed that the monitoring models based on ELM and GA‐SVM (R2 = 0.924–0.983) achieved better performances than those based on PLSR (R2 = 0.877–0.913). The ability of E‐nose to monitor fungal infection at early stage would help to prevent contaminated rice grains from entering the food chains. CONCLUSIONS The results indicated that E‐nose coupled with ELM or GA‐SVM algorithm could be a useful tool for the rapid detection of fungal infection in milled rice to prevent contaminated rice from entering the food chain.

ACS Style

Shuang Gu; Zhenhe Wang; Wei Chen; Jun Wang. Early identification of Aspergillus spp. contamination in milled rice by E‐nose combined with chemometrics. Journal of the Science of Food and Agriculture 2021, 101, 4220 -4228.

AMA Style

Shuang Gu, Zhenhe Wang, Wei Chen, Jun Wang. Early identification of Aspergillus spp. contamination in milled rice by E‐nose combined with chemometrics. Journal of the Science of Food and Agriculture. 2021; 101 (10):4220-4228.

Chicago/Turabian Style

Shuang Gu; Zhenhe Wang; Wei Chen; Jun Wang. 2021. "Early identification of Aspergillus spp. contamination in milled rice by E‐nose combined with chemometrics." Journal of the Science of Food and Agriculture 101, no. 10: 4220-4228.

Journal article
Published: 09 December 2020 in Computers and Electronics in Agriculture
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Platycladus orientalis plants in China are experiencing a serious problem with wood-boring beetles, but conventional physical detection methods cannot perform well due to hidden larvae and less obvious symptoms in the early infestation. In this study, the volatile organic compounds (VOCs) of P. orientalis were investigated using gas chromatography-ion mobility spectrometry (GC-IMS) to identify its internal infestation. An image-based evaluation method of the degree of internal wood damage was proposed, the principal component analysis (PCA) based on specific markers was applied for natural clustering of samples, and unsupervised learning approaches based on specific markers and automatically located peaks were used to create predictive models for sample classification. The results showed that the herbivore-induced plant volatiles (HIPVs) of P. orientalis samples had two main characteristics compared with undamaged plants. One was the emergence of several compounds such as C3-C6 ketones, aldehydes, and alcohols, while the other was the obvious content variation of several monoterpenes and their derivatives. The classification models based on specific markers and automatically located peaks could correctly classify at least 89.5% and 87.9% of the samples, respectively. In a word, these results proved that GC-IMS based approaches combined with different feature extraction methods have the potential to identify the internal infestation of wood-boring beetles in P. orientalis.

ACS Style

Chengyu Zheng; Zhenhe Wang; Jing Zhang; Jun Wang; Jianli Zhong; Yongwei Wang. Discrimination of wood-boring beetles infested Platycladus orientalis plants by using gas chromatography-ion mobility spectrometry. Computers and Electronics in Agriculture 2020, 180, 105896 .

AMA Style

Chengyu Zheng, Zhenhe Wang, Jing Zhang, Jun Wang, Jianli Zhong, Yongwei Wang. Discrimination of wood-boring beetles infested Platycladus orientalis plants by using gas chromatography-ion mobility spectrometry. Computers and Electronics in Agriculture. 2020; 180 ():105896.

Chicago/Turabian Style

Chengyu Zheng; Zhenhe Wang; Jing Zhang; Jun Wang; Jianli Zhong; Yongwei Wang. 2020. "Discrimination of wood-boring beetles infested Platycladus orientalis plants by using gas chromatography-ion mobility spectrometry." Computers and Electronics in Agriculture 180, no. : 105896.

Journal article
Published: 04 December 2020 in Agronomy
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Soil penetration resistance (SPR) is an important indicator for soil strength which not only affects the growth of crop roots and crop yield but also is crucial in the design and selection of agricultural machinery. The determination of SPR in the laboratory is complex and time-consuming, while measuring SPR on-site shows high uncertainty at different times and locations due to soil heterogeneity. Therefore, this paper investigated the impact of soil parameters on SPR for paddy soils in the plastic state and then established a simple regression model to predict SPR using easy-to-obtain soil physical properties, including clay content, water content and density. Using the combined approaches of central composition rotatable design (CCRD) with response surface methodology (RSM), SPR of 20 soil samples from five paddy fields were measured in the laboratory. The results from the experiments showed that the contribution rate of each single factor to SPR from high to low was soil density, clay content and water content. Statistical analysis for the established equation suggested that the p-value for goodness of fit was significant (p < 0.001) and the p-value for lack of fit was insignificant (p > 0.05); meanwhile, the coefficient of determination (R2) was 0.95, indicating that the model was effective in predicting the SPR. Subsequently, the performance of the regression model was validated by comparing the estimated SPR with in situ field measurements, which showed high accuracy, with percent errors within 10%. Our study successfully proposed a method to estimate SPR using easy-to-measure soil properties that could be obtained from sensors in the soil or field investigations, including soil clay content, water content and wet bulk density.

ACS Style

Qianjing Jiang; Ming Cao; Yongwei Wang; Jun Wang. Estimating Soil Penetration Resistance of Paddy Soils in the Plastic State Using Physical Properties. Agronomy 2020, 10, 1914 .

AMA Style

Qianjing Jiang, Ming Cao, Yongwei Wang, Jun Wang. Estimating Soil Penetration Resistance of Paddy Soils in the Plastic State Using Physical Properties. Agronomy. 2020; 10 (12):1914.

Chicago/Turabian Style

Qianjing Jiang; Ming Cao; Yongwei Wang; Jun Wang. 2020. "Estimating Soil Penetration Resistance of Paddy Soils in the Plastic State Using Physical Properties." Agronomy 10, no. 12: 1914.

Journal article
Published: 11 November 2020 in Journal of The Electrochemical Society
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ACS Style

Luyi Zhu; Zhenbo Wei; Jun Wang; Jianli Zhong. An Electrochemical Biosensor Based on NiO Nanoflowers/ Polymethylene Blue Composite for Non-Enzymatic Glucose Detection. Journal of The Electrochemical Society 2020, 167, 1 .

AMA Style

Luyi Zhu, Zhenbo Wei, Jun Wang, Jianli Zhong. An Electrochemical Biosensor Based on NiO Nanoflowers/ Polymethylene Blue Composite for Non-Enzymatic Glucose Detection. Journal of The Electrochemical Society. 2020; 167 (14):1.

Chicago/Turabian Style

Luyi Zhu; Zhenbo Wei; Jun Wang; Jianli Zhong. 2020. "An Electrochemical Biosensor Based on NiO Nanoflowers/ Polymethylene Blue Composite for Non-Enzymatic Glucose Detection." Journal of The Electrochemical Society 167, no. 14: 1.

Journal article
Published: 30 October 2020 in Journal of Agricultural and Food Chemistry
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Conventional methods for detecting fungal contamination are generally time-consuming and sample-destructive, making them impossible for large-scale nondestructive detection and real-time analysis. Therefore, the potential of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) was examined for the rapid determination of fungal infection on wheat samples in a rapid and nondestructive manner. In addition, the validation experiment of detecting the percent A. flavus infection presented in simulated field samples was carried out. Because the dual separation of HS-GC-IMS could generate massive amounts of three-dimensional data, proper chemometric processing was required. In this study, two chemometric strategies including: (i) nontargeted spectral fingerprinting and (ii) targeted specific markers were introduced to evaluate the performances of classification and prediction models. Results showed that satisfying results for the differentiation of fungal species were obtained based on both strategies (>80%) by the genetic algorithm optimized support vector machine (GA-SVM), and better values were obtained based on the first strategy (100%). Likewise, the GA-SVM model based on the first strategy achieved the best prediction performances (R2 = 0.979-0.998) of colony counts in fungal infected samples. The results of validation experiment showed that GA-SVM models based on the first strategy could still provide satisfactory classification (86.67%) and prediction (R2 = 0.889) performances for percent A. flavus infection presented in simulated field samples at day 4. This study indicated the feasibility of HS-GC-IMS-based approaches for the early detection of fungal contamination in wheat kernels.

ACS Style

Shuang Gu; Zhenhe Wang; Wei Chen; Jun Wang. Targeted versus Nontargeted Green Strategies Based on Headspace-Gas Chromatography–Ion Mobility Spectrometry Combined with Chemometrics for Rapid Detection of Fungal Contamination on Wheat Kernels. Journal of Agricultural and Food Chemistry 2020, 68, 12719 -12728.

AMA Style

Shuang Gu, Zhenhe Wang, Wei Chen, Jun Wang. Targeted versus Nontargeted Green Strategies Based on Headspace-Gas Chromatography–Ion Mobility Spectrometry Combined with Chemometrics for Rapid Detection of Fungal Contamination on Wheat Kernels. Journal of Agricultural and Food Chemistry. 2020; 68 (45):12719-12728.

Chicago/Turabian Style

Shuang Gu; Zhenhe Wang; Wei Chen; Jun Wang. 2020. "Targeted versus Nontargeted Green Strategies Based on Headspace-Gas Chromatography–Ion Mobility Spectrometry Combined with Chemometrics for Rapid Detection of Fungal Contamination on Wheat Kernels." Journal of Agricultural and Food Chemistry 68, no. 45: 12719-12728.

Journal article
Published: 27 October 2020 in IEEE Transactions on Industrial Electronics
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In this study, an on-line microwave moisture sensing system (OM2S2) based on multi-frequency swept technique was developed to monitor the moisture content (MC) of corn in the fresh to dry state (MC ranged from 10.89% to 63.64%) in real time. Attenuation and phase-shift data were collected under a frequency swept signal containing 801 frequencies from 2.00 to 10.00 GHz with a 10 MHz interval. For removing the inefficient frequencies, the optimized frequencies were selected by a two-stage frequency selection framework: (1) 17 frequency subsets were generated by random forest-recursive feature elimination algorithm, and then (2) the optimal frequency set (including eight individual frequencies) was determined by voting strategies according to the results of 10-fold cross-validation. The attenuation and phase-shift data corresponding to the optimal frequency set was utilized as the input variables of six machine learning algorithms for MC prediction. A deep neural network (R2=0.997, RMSE=1.087, MAE=0.868) performed best according to Friedman test and Nemenyi post-hoc test and deployed to OM2S2. These results showed that OM2S2 was capable of measuring the MC of corn from fresh to dry state in real time, and it also exhibited potential usage for on-line determination of high MC in food processing and agriculture-related industries.

ACS Style

Jinyang Zhang; Yin Bao; Dongdong Du; Jun Wang; Zhenbo Wei. OM2S2: On-Line Moisture-Sensing System Using Multifrequency Microwave Signals Optimized by a Two-Stage Frequency Selection Framework. IEEE Transactions on Industrial Electronics 2020, 68, 11501 -11510.

AMA Style

Jinyang Zhang, Yin Bao, Dongdong Du, Jun Wang, Zhenbo Wei. OM2S2: On-Line Moisture-Sensing System Using Multifrequency Microwave Signals Optimized by a Two-Stage Frequency Selection Framework. IEEE Transactions on Industrial Electronics. 2020; 68 (11):11501-11510.

Chicago/Turabian Style

Jinyang Zhang; Yin Bao; Dongdong Du; Jun Wang; Zhenbo Wei. 2020. "OM2S2: On-Line Moisture-Sensing System Using Multifrequency Microwave Signals Optimized by a Two-Stage Frequency Selection Framework." IEEE Transactions on Industrial Electronics 68, no. 11: 11501-11510.

Journal article
Published: 30 September 2020 in Postharvest Biology and Technology
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This study described the rapid determination of potential aflatoxigenic fungi contamination on peanut kernels based on headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) coupled to fluorescence spectroscopy. Data-level and feature-level fusion strategies were introduced to integrate HS-GC-IMS and fluorescence spectra, aiming at improving the performances of identification and prediction models. The application of feature-level data fusion using first 10 PCs coupled with orthogonal partial least squares discriminant analysis (OPLS-DA) offered more accurate characterization (96.7 %) for aflatoxigenic and non-aflatoxigenic fungal infection on peanut samples. Regression models were established for predicting colony counts of peanuts infected with aflatoxigenic fungi based on independent and fused signals by partial least squares regression (PLSR). Feature-level data fusion using first 10 PCs achieved the best performances in colony counts predictions for A. flavus (R2 = 0.950) and A. parasiticus (R2 = 0.971). These results demonstrated that the combination of HS-GC-IMS and fluorescence spectra might offer the feasibility for early detection of potential aflatoxigenic risk in peanuts.

ACS Style

Shuang Gu; Wei Chen; Zhenhe Wang; Jun Wang. Rapid determination of potential aflatoxigenic fungi contamination on peanut kernels during storage by data fusion of HS-GC-IMS and fluorescence spectroscopy. Postharvest Biology and Technology 2020, 171, 111361 .

AMA Style

Shuang Gu, Wei Chen, Zhenhe Wang, Jun Wang. Rapid determination of potential aflatoxigenic fungi contamination on peanut kernels during storage by data fusion of HS-GC-IMS and fluorescence spectroscopy. Postharvest Biology and Technology. 2020; 171 ():111361.

Chicago/Turabian Style

Shuang Gu; Wei Chen; Zhenhe Wang; Jun Wang. 2020. "Rapid determination of potential aflatoxigenic fungi contamination on peanut kernels during storage by data fusion of HS-GC-IMS and fluorescence spectroscopy." Postharvest Biology and Technology 171, no. : 111361.

Original article
Published: 14 August 2020 in Journal of Food Science and Technology
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Tea is one of the most popular beverage with distinct flavor consumed worldwide. It is of significance to establish evaluation method for tea quality controlling. In this work, electronic nose (E-nose) was applied to assess tea quality grades by detecting the volatile components of tea leaves and tea infusion samples. The “35th s value”, “70th s value” and “average differential value” were extracted as features from E-nose responding signals. Three data reduction methods including principle component analysis (PCA), multi-dimensional scaling (MDS) and linear discriminant analysis (LDA) were introduced to improve the efficiency of E-nose analysis. Logistic regression (LR) and support vector machine (SVM) were applied to set up qualitative classification models. The results indicated that LDA outperformed original data, PCA and MDS in both LR and SVM models. SVM had an advantage over LR in developing classification models. The classification accuracy of SVM based on the data processed by LDA for tea infusion samples was 100%. Quantitative analysis was conducted to predict the contents of volatile compounds in tea samples based on E-nose signals. The prediction results of SVM based on the data processed by LDA for linalool (training set: R2 = 0.9523; testing set: R2 = 0.9343), nonanal (training set: R2 = 0.9617; testing set: R2 = 0.8980) and geraniol (training set: R2 = 0.9576; testing set: R2 = 0.9315) were satisfactory. The research manifested the feasibility of E-nose for qualitatively and quantitatively analyzing tea quality grades.

ACS Style

Min Xu; Jun Wang; Luyi Zhu. Tea quality evaluation by applying E-nose combined with chemometrics methods. Journal of Food Science and Technology 2020, 58, 1549 -1561.

AMA Style

Min Xu, Jun Wang, Luyi Zhu. Tea quality evaluation by applying E-nose combined with chemometrics methods. Journal of Food Science and Technology. 2020; 58 (4):1549-1561.

Chicago/Turabian Style

Min Xu; Jun Wang; Luyi Zhu. 2020. "Tea quality evaluation by applying E-nose combined with chemometrics methods." Journal of Food Science and Technology 58, no. 4: 1549-1561.

Journal article
Published: 19 July 2020 in Biosystems Engineering
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One of the critical barriers for whole-stalk sugarcane mechanical harvesting is the high proportion of impurities especially in the cane tops. In this study, a whole-stalk sugarcane conveying and top breaking system was developed and tested to improve top breaking performance. Effects of feeding roller speed, top breaking roller speed, stagger angle of upper and lower top breaking elements and distance between the upper and lower top breaking element on sugarcane top breaking rate, non-fracture rate and power requirement were explored. Central composite design combined with response surface method was employed to conduct experiments and explore the interaction effects of influence factors on indicators. The optimal structure and operating parameters were determined to be 305 rpm for feeding roller speed, 520 rpm for top breaking roller speed, 14° for the stagger angle and 10 mm for the distance. The predicted values for top breaking rate, non-fracture rate and power requirement were 85%, 83% and 690 W, respectively. Verification experiments demonstrated that the observed values were in agreement with the predicted values. Based on the optimised results, a rigid-flexible coupling model was established for sugarcane conveying and top breaking and the simulation results showed that the model was reliable in predicting the kinetic characteristics of sugarcane in conveying and top breaking processes. The maximum resultant striking force of the top breaking elements on the cane stalk was 807.68 N. Overall, the conveying and top breaking system developed in this study was effective for improving top cleaning performance in whole-stalk sugarcane harvesting.

ACS Style

Luxin Xie; Jun Wang; Shaoming Cheng; Bosheng Zeng; ZiZeng Yang. Optimisation and dynamic simulation of a conveying and top breaking system for whole-stalk sugarcane harvesters. Biosystems Engineering 2020, 197, 156 -169.

AMA Style

Luxin Xie, Jun Wang, Shaoming Cheng, Bosheng Zeng, ZiZeng Yang. Optimisation and dynamic simulation of a conveying and top breaking system for whole-stalk sugarcane harvesters. Biosystems Engineering. 2020; 197 ():156-169.

Chicago/Turabian Style

Luxin Xie; Jun Wang; Shaoming Cheng; Bosheng Zeng; ZiZeng Yang. 2020. "Optimisation and dynamic simulation of a conveying and top breaking system for whole-stalk sugarcane harvesters." Biosystems Engineering 197, no. : 156-169.

Journal article
Published: 15 July 2020 in Journal of Food Engineering
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In this work, a portable electronic nose (e-nose) equipped with a smartphone was developed to identify the Chinese dry-cured ham of three grades. The gas chromatography-ion mobility spectrometry (GC-IMS) was employed for detection of the volatile organic compounds of hams and optimization of the sensor array. A hybrid filter-wrapper method was proposed to optimize the feature set which included the time and frequency domain features. The proposed hybrid method included two parts: the filter method based on mutual information mixed evaluation (MIME) which was applied to eliminate the irrelevant features, and the wrapper method based on support vector machine-backward feature elimination with cross-validation (SVM-BFECV) which was applied to removing the multicollinear features. Both the principal component analysis and T-distribution stochastic neighbor embedding with the hybrid filter-wrapper method presented good results, and all the samples could be classified completely. SVM, K-nearest neighbors and logistic regression were applied for the prediction works. SVM based on the hybrid method presented the best results, and the prediction accuracy and consuming time was 96.06% and 17.32 s, respectively. Above all, the proposed filter-wrapper method performed well in optimizing the feature data, and the three grades of hams can be clearly identified by using the developed portable e-nose based on the optimized features.

ACS Style

Kang Qian; Yin Bao; Jianxi Zhu; Jun Wang; Zhenbo Wei. Development of a portable electronic nose based on a hybrid filter-wrapper method for identifying the Chinese dry-cured ham of different grades. Journal of Food Engineering 2020, 290, 110250 .

AMA Style

Kang Qian, Yin Bao, Jianxi Zhu, Jun Wang, Zhenbo Wei. Development of a portable electronic nose based on a hybrid filter-wrapper method for identifying the Chinese dry-cured ham of different grades. Journal of Food Engineering. 2020; 290 ():110250.

Chicago/Turabian Style

Kang Qian; Yin Bao; Jianxi Zhu; Jun Wang; Zhenbo Wei. 2020. "Development of a portable electronic nose based on a hybrid filter-wrapper method for identifying the Chinese dry-cured ham of different grades." Journal of Food Engineering 290, no. : 110250.

Journal article
Published: 04 July 2020 in LWT
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This study described the rapid detection of milled rice infected with Aspergillus spp. species based on headspace-gas chromatography ion-mobility spectrometry (HS-GC-IMS) and electronic nose (E-nose) combined with chemometrics, namely principal component analysis (PCA), k-nearest neighbor (kNN) and partial least squares regression (PLSR). 3D HS-GC-IMS imaging and their response differences enabled the discrimination among fungal species. kNN was used to differentiate rice samples with cdifferent levels of fungal infection and achieved correct classified rate of 94.44% and 91.67% by HS-GC-IMS and E-nose, respectively. PLSR method was used for quantitative regression of fungal colony counts in rice samples and good prediction performances were achieved by HS-GC-IMS (Rp2 = 0.909, RMSEP = 0.202) and E-nose (Rp2 = 0.864, RMSEP = 0.235). The results indicated that both HS-GC-IMS and E-nose approaches can potentially be implemented for the detection of fungal contamination levels in milled rice, and HS-GC-IMS fingerprinting coupled with chemometrics might be used as an alternative tool for a highly sensitive method. This research might provide scientific information on the rapid, non-destructive, and effective fungal detection system for rice grains.

ACS Style

Shuang Gu; Wei Chen; Zhenhe Wang; Jun Wang; Yujia Huo. Rapid detection of Aspergillus spp. infection levels on milled rice by headspace-gas chromatography ion-mobility spectrometry (HS-GC-IMS) and E-nose. LWT 2020, 132, 109758 .

AMA Style

Shuang Gu, Wei Chen, Zhenhe Wang, Jun Wang, Yujia Huo. Rapid detection of Aspergillus spp. infection levels on milled rice by headspace-gas chromatography ion-mobility spectrometry (HS-GC-IMS) and E-nose. LWT. 2020; 132 ():109758.

Chicago/Turabian Style

Shuang Gu; Wei Chen; Zhenhe Wang; Jun Wang; Yujia Huo. 2020. "Rapid detection of Aspergillus spp. infection levels on milled rice by headspace-gas chromatography ion-mobility spectrometry (HS-GC-IMS) and E-nose." LWT 132, no. : 109758.

Journal article
Published: 04 March 2020 in Journal of Food Quality
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The effect of storage time and packing method on dried Lycium fruits was studied through an electronic olfactory system with the metal oxide sensor array that provides an overall perception of the volatile compounds presented in the sample headspace. Principle component analysis (PCA), canonical discriminant analysis (CDA), and cluster analysis (CA) were used for freshness and packing methods discrimination of dried Lycium fruits. The stale samples of 2015 and 2016 could be separated with those of 2017 by PCA, CDA, and CA analysis. Better discrimination results were obtained by CDA, with samples of 2015 and 2016 separated with each other. For samples of 2017, the unpackaged samples of 2017-4 were distinguished with the vacuumed samples, while samples of grade C were separated with B and D. For quantitative analysis, predictive models for prediction of the storage years of dried Lycium fruits were built with methods of partial least square (PLS) analysis, multiple linear regression (MLR), and back propagation neural network (BPNN). The model built by BPNN showed the best predict ability with R2 = 0.9994, while PLS and MLR were also effective in the prediction of storage years of dried Lycium fruits, with high determination coefficients of 0.9316 and 0.9330. These findings showed that E-nose can be used in the discrimination of the storage time and package method of dried Lycium fruits.

ACS Style

Xiaojing Tian; Ming Long; Yuanlin Liu; Peng Zhang; Xiaoqin Bai; Jun Wang; Zhenbo Wei; Shien Chen; Zhongren Ma; Li Song; Li Luo. Effect of Storage Time and Packing Method on the Freshness of Dried Lycium Fruit Using Electronic Nose and Chemometrics. Journal of Food Quality 2020, 2020, 1 -8.

AMA Style

Xiaojing Tian, Ming Long, Yuanlin Liu, Peng Zhang, Xiaoqin Bai, Jun Wang, Zhenbo Wei, Shien Chen, Zhongren Ma, Li Song, Li Luo. Effect of Storage Time and Packing Method on the Freshness of Dried Lycium Fruit Using Electronic Nose and Chemometrics. Journal of Food Quality. 2020; 2020 ():1-8.

Chicago/Turabian Style

Xiaojing Tian; Ming Long; Yuanlin Liu; Peng Zhang; Xiaoqin Bai; Jun Wang; Zhenbo Wei; Shien Chen; Zhongren Ma; Li Song; Li Luo. 2020. "Effect of Storage Time and Packing Method on the Freshness of Dried Lycium Fruit Using Electronic Nose and Chemometrics." Journal of Food Quality 2020, no. : 1-8.

Journal article
Published: 21 February 2020 in Computers and Electronics in Agriculture
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Trunk borer cause serious damage to plants and it is hard to detect due to larvae mine inside. In this study, E-nose combined with gas chromatography and mass spectrometry (GC–MS) was employed to evaluate Semanotus bifasciatus infestation duration at 0 d, 30 d, 60 d and 90 d. GC–MS result indicated that the most abundant components were 3-carene, α-pinene, β-phellandrene, sabinene and longifolene. The correlation between E-nose sensor responses and VOCs was analyzed by ANNOVA-Partial least square regression (APLSR). Six different features derived from E-nose data were analyzed by principle components analysis (PCA) and grid search-support vector machine (GS-SVM) was used as an optimized classifier to discriminate pest infestation duration based on different feature dataset. The classification results based on wavelet entropy (WE) showed preferable classification performances in both calibration set (100%) and validation set (100%). GS-SVM was also applied to predict S. bifasciatus infestation duration. Result showed that the fitting correlation coefficients (R2) value of calibration set and validation set were 0.9987 and 0.9980, while the root mean square error (RMSE) of which were 0.4506 and 0.4961, respectively. It could be concluded that E-nose is a potential technique for evaluating trunk borer infestation and pest management.

ACS Style

Zhenhe Wang; Wei Chen; Shuang Gu; Yongwei Wang; Jun Wang. Evaluation of trunk borer infestation duration using MOS E-nose combined with different feature extraction methods and GS-SVM. Computers and Electronics in Agriculture 2020, 170, 105293 .

AMA Style

Zhenhe Wang, Wei Chen, Shuang Gu, Yongwei Wang, Jun Wang. Evaluation of trunk borer infestation duration using MOS E-nose combined with different feature extraction methods and GS-SVM. Computers and Electronics in Agriculture. 2020; 170 ():105293.

Chicago/Turabian Style

Zhenhe Wang; Wei Chen; Shuang Gu; Yongwei Wang; Jun Wang. 2020. "Evaluation of trunk borer infestation duration using MOS E-nose combined with different feature extraction methods and GS-SVM." Computers and Electronics in Agriculture 170, no. : 105293.

Journal article
Published: 15 February 2020 in Sensors
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Aroma and taste are the most important attributes of alcoholic beverages. In the study, the self-developed electronic tongue (e-tongue) and electronic nose (e-nose) were used for evaluating the marked ages of rice wines. Six types of feature data sets (e-tongue data set, e-nose data set, direct-fusion data set, weighted-fusion data set, optimized direct-fusion data set, and optimized weighted-fusion data set) were used for identifying rice wines with different wine ages. Pearson coefficient analysis and variance inflation factor (VIF) analysis were used to optimize the fusion matrixes by removing the multicollinear information. Two types of discrimination methods (principal component analysis (PCA) and locality preserving projections (LPP)) were used for classifying rice wines, and LPP performed better than PCA in the discrimination work. The best result was obtained by LPP based on the weighted-fusion data set, and all the samples could be classified clearly in the LPP plot. Therefore, the weighted-fusion data were used as independent variables of partial least squares regression, extreme learning machine, and support vector machines (LIBSVM) for evaluating wine ages, respectively. All the methods performed well with good prediction results, and LIBSVM presented the best correlation coefficient (R2 ≥ 0.9998).

ACS Style

Huihui Zhang; Wenqing Shao; Shanshan Qiu; Jun Wang; Zhenbo Wei. Collaborative Analysis on the Marked Ages of Rice Wines by Electronic Tongue and Nose based on Different Feature Data Sets. Sensors 2020, 20, 1065 .

AMA Style

Huihui Zhang, Wenqing Shao, Shanshan Qiu, Jun Wang, Zhenbo Wei. Collaborative Analysis on the Marked Ages of Rice Wines by Electronic Tongue and Nose based on Different Feature Data Sets. Sensors. 2020; 20 (4):1065.

Chicago/Turabian Style

Huihui Zhang; Wenqing Shao; Shanshan Qiu; Jun Wang; Zhenbo Wei. 2020. "Collaborative Analysis on the Marked Ages of Rice Wines by Electronic Tongue and Nose based on Different Feature Data Sets." Sensors 20, no. 4: 1065.

Journal article
Published: 12 February 2020 in IEEE Transactions on Instrumentation and Measurement
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ACS Style

Jinyang Zhang; Dongdong Du; Yin Bao; Jun Wang; Zhenbo Wei. Development of Multifrequency-Swept Microwave Sensing System for Moisture Measurement of Sweet Corn With Deep Neural Network. IEEE Transactions on Instrumentation and Measurement 2020, 69, 6446 -6454.

AMA Style

Jinyang Zhang, Dongdong Du, Yin Bao, Jun Wang, Zhenbo Wei. Development of Multifrequency-Swept Microwave Sensing System for Moisture Measurement of Sweet Corn With Deep Neural Network. IEEE Transactions on Instrumentation and Measurement. 2020; 69 (9):6446-6454.

Chicago/Turabian Style

Jinyang Zhang; Dongdong Du; Yin Bao; Jun Wang; Zhenbo Wei. 2020. "Development of Multifrequency-Swept Microwave Sensing System for Moisture Measurement of Sweet Corn With Deep Neural Network." IEEE Transactions on Instrumentation and Measurement 69, no. 9: 6446-6454.