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学者姓名：吴仁烨
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Abstract ：
Anthocyanin is a crucial reference indicator for evaluating the quality of rice varieties, making it significant to rapidly establish a non-destructive detection method for anthocyanin in rice grains. This study constructs a 1DDCGAN (One-dimensional deep convolutional generative adversarial network) strategy optimized for one dimensional spectral data and a 1D-CNN (One-dimensional convolutional neural network) model, achieving high-quality generated sample effects and more accurate anthocyanin predictions within a limited dataset. The SG (Savitzky-Golay)-1D-CNN significantly outperforms LSR (Least squares regression), SVM (Support vector machine) and BPNN (Backpropagation neural network) in the test set, with R2 (Determination coefficient), RMSE (Root mean square error) and RPD (Residual predictive deviation) values of 0.83, 10.99, and 2.45, respectively. Furthermore, using DCGAN-generated samples to train the SG-1D-CNN by adding a certain number of generated samples can enhance the model's performance in the test set. When the number of added samples is 60 (75% of the original training set sample size), the SG-DCGAN-1D-CNN (Savitzky-Golay deep convolutional generative adversarial network one dimensional convolutional neural network) exhibits the best performance, with R2, RMSE, and RPD reaching 0.87, 9.40, and 2.88, respectively. The DCGAN-1D-CNN (Deep convolutional generative adversarial network one dimensional convolutional neural network) method based on this strategy is expected to provide new insights into precise prediction for multi-variety rice seeds.
Keyword ：
Anthocyanin Anthocyanin Generative adversarial network Generative adversarial network Hyperspectral Hyperspectral Rice Rice
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| GB/T 7714 | Bao, Xingsheng , Huang, Deyao , Yang, Biyun et al. Combining deep convolutional generative adversarial networks with visible-near infrared hyperspectral reflectance to improve prediction accuracy of anthocyanin content in rice seeds [J]. | FOOD CONTROL , 2025 , 174 . |
| MLA | Bao, Xingsheng et al. "Combining deep convolutional generative adversarial networks with visible-near infrared hyperspectral reflectance to improve prediction accuracy of anthocyanin content in rice seeds" . | FOOD CONTROL 174 (2025) . |
| APA | Bao, Xingsheng , Huang, Deyao , Yang, Biyun , Li, Jiayi , Opeyemi, Atoba Tolulope , Wu, Renye et al. Combining deep convolutional generative adversarial networks with visible-near infrared hyperspectral reflectance to improve prediction accuracy of anthocyanin content in rice seeds . | FOOD CONTROL , 2025 , 174 . |
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Seeds are essential to the agri-food industry. However, their quality is vulnerable to biotic and abiotic stresses during production and storage, leading to various types of deterioration. Real-time monitoring and pre-sowing screening offer substantial potential for improved storage management, field performance, and flour quality. This study investigated diverse deterioration patterns in wheat seeds by analyzing 1000 high-quality and 1098 deteriorated seeds encompassing mold, aging, mechanical damage, insect damage, and internal insect infestation. Hyperspectral imaging (HSI) and computer vision (CV) were employed to capture surface data from both the embryo (EM) and endosperm (EN). Internal seed quality was further assessed using scanning electron microscopy, dissection, and standard germination tests. Both conventional machine learning algorithms and deep convolutional neural networks (DCNN) were employed to develop discriminative models using independent datasets. Results revealed that each data source contributed valuable information for seed quality assessment (validation set accuracy: 65.1-89.2 %), with the integration of HSI and CV showing considerable promise. A comparison of early and late fusion strategies led to the development of an end-to-end deep fusion model. The decision fusion-based DCNN model, integrating HSI-EM, HSI-EN, CV-EM, and CV-EN data, achieved the highest accuracy in both training (94.3 %) and validation (93.8 %) sets. Applying this model to seed lot screening increased the proportion of high-quality seeds from 47.7 % to 93.4 %. These findings were further supported by external samples and visualizations. The proposed end-to-end decision fusion DCNN model simplifies the training process compared to traditional two-stage fusion methods. This study presents a potentially efficient alternative for rapid, individual kernel quality detection and control during wheat production. (c) 2025 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keyword ：
Computer vision Computer vision Data fusion Data fusion Deep convolutional neural networks Deep convolutional neural networks Hyperspectral imaging Hyperspectral imaging Seed quality Seed quality
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| GB/T 7714 | Zhang, Tingting , Li, Jing , Tong, Jinpeng et al. End-to-end deep fusion of hyperspectral imaging and computer vision techniques for rapid detection of wheat seed quality [J]. | ARTIFICIAL INTELLIGENCE IN AGRICULTURE , 2025 , 15 (3) : 537-549 . |
| MLA | Zhang, Tingting et al. "End-to-end deep fusion of hyperspectral imaging and computer vision techniques for rapid detection of wheat seed quality" . | ARTIFICIAL INTELLIGENCE IN AGRICULTURE 15 . 3 (2025) : 537-549 . |
| APA | Zhang, Tingting , Li, Jing , Tong, Jinpeng , Song, Yihu , Wang, Li , Wu, Renye et al. End-to-end deep fusion of hyperspectral imaging and computer vision techniques for rapid detection of wheat seed quality . | ARTIFICIAL INTELLIGENCE IN AGRICULTURE , 2025 , 15 (3) , 537-549 . |
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During automated packaging of white tea, uneven tea pile thickness leads to reduced weighing accuracy, while traditional experimental methods struggle to reveal the underlying particle flow mechanisms, hindering equipment optimization. Addressing the lack of discrete element method (DEM) parameters for Baihao Yinzhen tea, this study calibrates its DEM parameters based on the DEM approach, providing input for virtual commissioning of packaging machinery. Through physical experiments, the static friction coefficient (0.546), restitution coefficient (0.326), and rolling friction coefficient (0.133) between tea leaves and steel plates were determined. A three-dimensional DEM model of tea leaves was established using slicing techniques and the multi-sphere aggregation method. The steepest-ascent method and Box-Behnken design were employed to optimize the simulation parameters, resulting in the following optimal parameter combination: inter-particle restitution coefficient (0.16), static friction coefficient (0.14), and rolling friction coefficient (0.15). Validation simulations demonstrated that the mean angle of repose of tea leaves under the optimized parameter combination was 22.51 degrees, with a relative error of only 1.29% compared to the actual experimental result of 22.80 degrees. The calibrated parameters can be directly applied to the simulation of the feeding system in white tea automatic packaging machines, enabling optimization of vibration parameters through prediction of pile behavior, thereby reducing weighing errors.
Keyword ：
angle of repose angle of repose discrete element method (DEM) discrete element method (DEM) parameter calibration parameter calibration white tea white tea
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| GB/T 7714 | Ye, Dapeng , Gao, Yuxuan , Qi, Yanlin et al. DEM Parameter Calibration and Experimental Definition for White Tea Granular Systems [J]. | AGRONOMY-BASEL , 2025 , 15 (8) . |
| MLA | Ye, Dapeng et al. "DEM Parameter Calibration and Experimental Definition for White Tea Granular Systems" . | AGRONOMY-BASEL 15 . 8 (2025) . |
| APA | Ye, Dapeng , Gao, Yuxuan , Qi, Yanlin , Wang, Hao , Wu, Renye , Weng, Haiyong . DEM Parameter Calibration and Experimental Definition for White Tea Granular Systems . | AGRONOMY-BASEL , 2025 , 15 (8) . |
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为对菌草微生物农业综合生产系统进行示范与推广，实现菌草资源综合循环利用。在福建省南平市延平区大横镇博爱村，通过种植12 hm
Keyword ：
发酵饲料 发酵饲料 微生物农业综合生产系统 微生物农业综合生产系统 微生物发酵床 微生物发酵床 水肥菌一体化 水肥菌一体化 现代设施农业 现代设施农业 菌草家园 菌草家园
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| GB/T 7714 | 包兴胜 , 刘平山 , 王志明 et al. 菌草家园—微生物农业综合生产系统的构建 [J]. | 中国农学通报 , 2025 , 41 (05) : 119-129 . |
| MLA | 包兴胜 et al. "菌草家园—微生物农业综合生产系统的构建" . | 中国农学通报 41 . 05 (2025) : 119-129 . |
| APA | 包兴胜 , 刘平山 , 王志明 , 刘欣 , 车建美 , 郑雪芳 et al. 菌草家园—微生物农业综合生产系统的构建 . | 中国农学通报 , 2025 , 41 (05) , 119-129 . |
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This study was based on ultrahigh liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) combined with the study of bioactivity to analyze the characteristic metabolites and their bioactivity changes of green tea prepared by adding phyllanthus emblica L. (PE). The results showed that there were significant differences among different green teas, and the addition of PE affected the composition of tea mainly through the biosynthesis pathway of flavonoids and anthocyanins, especially effectively retained the content of EGCG during tea processing, and reduced the loss of polyphenols in tea. In addition, the change of active ingredient content was positively correlated with the antioxidant effect. The addition of PE can improve the free radical scavenging ability, effectively inhibit the oxidative damage of RAW264.7 cells induced by H2O2, and the inhibition rate of HCT116 intestinal cancer cells is as high as 91.23%, which indicates that PE can improve the biological activity function of green tea. © 2024, The Authors. All rights reserved.
Keyword ：
Bioactivity Bioactivity Free radicals Free radicals Liquid chromatography Liquid chromatography Mass spectrometry Mass spectrometry Metabolites Metabolites
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| GB/T 7714 | Chen, Xiaoduan , Chen, Peng , Wu, Renye et al. Based on Metabolomics Analysis the Effect of Phyllanthus Emblica L. On Green Tea: Analysis of Bioactive Compounds and Bioactivity [J]. | SSRN , 2024 . |
| MLA | Chen, Xiaoduan et al. "Based on Metabolomics Analysis the Effect of Phyllanthus Emblica L. On Green Tea: Analysis of Bioactive Compounds and Bioactivity" . | SSRN (2024) . |
| APA | Chen, Xiaoduan , Chen, Peng , Wu, Renye , Xu, Ming , Pang, Jie , Wei, Yanfeng et al. Based on Metabolomics Analysis the Effect of Phyllanthus Emblica L. On Green Tea: Analysis of Bioactive Compounds and Bioactivity . | SSRN , 2024 . |
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In order to realize the accurate and reliable prediction of the change trend of dissolved oxygen (DO) content in California perch aquaculture water, this paper proposes a second-order hybrid optimization support vector machine (SVR) model based on Differential Evolution (DE) and Gray Wolf Optimizer (GWO), shortened to DE-GWO-SVR, to predict the DO content with the characteristics of nonlinear and non-smooth water quality data. Experimentally, data for the water quality, including pH, water temperature, conductivity, salinity, total dissolved solids, and DO, were collected. Pearson's correlation coefficient (PPMCC) was applied to explore the correlation between each water quality parameter and DO content. The optimal DE-GWO-SVR model was established and compared with models based on SVR, back-propagation neural network (BPNN), and their optimization models. The results show that the DE-GWO-SVR model proposed in this paper can effectively realize the nonlinear prediction and global optimization performance. Its R2, MSE, MAE and RMSE can be up to 0.94, 0.108, 0.2629, and 0.3293, respectively, which is better than those of other models. This research provides guidance for the efficient prediction of DO in perch aquaculture water bodies for increasing the aquaculture effectiveness and reducing the aquaculture risk, providing a new exploratory path for water quality monitoring.
Keyword ：
differential evolution differential evolution dissolved oxygen dissolved oxygen gray wolf optimizer gray wolf optimizer water quality prediction water quality prediction
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| GB/T 7714 | Bao, Xingsheng , Jiang, Yilun , Zhang, Lintong et al. Accurate Prediction of Dissolved Oxygen in Perch Aquaculture Water by DE-GWO-SVR Hybrid Optimization Model [J]. | APPLIED SCIENCES-BASEL , 2024 , 14 (2) . |
| MLA | Bao, Xingsheng et al. "Accurate Prediction of Dissolved Oxygen in Perch Aquaculture Water by DE-GWO-SVR Hybrid Optimization Model" . | APPLIED SCIENCES-BASEL 14 . 2 (2024) . |
| APA | Bao, Xingsheng , Jiang, Yilun , Zhang, Lintong , Liu, Bo , Chen, Linjie , Zhang, Wenqing et al. Accurate Prediction of Dissolved Oxygen in Perch Aquaculture Water by DE-GWO-SVR Hybrid Optimization Model . | APPLIED SCIENCES-BASEL , 2024 , 14 (2) . |
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To investigate the effects of pulse electric field stimulation on the photosynthetic electron transport chain and negative air ion (NAI) release capacity of snake plants, the chlorophyll content, fluorescence induction kinetics curve (OJIP curve), chlorophyll fluorescence parameters, and NAI release concentration of snake plants kept under identical greenhouse conditions under different pulse electric field stimulations were compared and analyzed. The experimental results show that (1) after pulse electric field stimulation, the chlorophyll content in treatment group T1 (5 kv) and T2 (7 kv) of snake plants increased by 6.30% and 6.70%, respectively, with significant differences observed between the two treatment groups and the control group (CK). (2) In both treatment groups, the OJIP curve exhibited higher values for the inflection point (I) and peak (P) compared to the origin (O) and inflection point (J) values, with the rising trend in the I-P segment being more gentle than that of the O-J segment. Additionally, the J band was above 0, with the peak value in the T2 group being higher than that in the T1 group. (3) The chlorophyll fluorescence parameters showed fluctuating variations. Specifically, Fm, TRo/CSo, ETo/CSo, and DIo/CSo showed ascending trends in the treatment groups. Fv/Fo, Sm, and ABS/RC exhibited descending trends; Fv/Fm, Vj, ETo/RC, and phi Eo showed relatively minor changes. The PIabs displayed a decreasing trend. The PItotal in the CK was greater than that in the T1 and T2 groups. (4) After 4 h of pulse electric field stimulation, the NAI concentration increased by 87.60% in the T1 group and by 62.09% in the T2 group, compared to the same measurement taken at 3 h. Pulse electric field impacts the photosynthetic electron transport chain of snake plants, thereby influencing their NAI release capacity. This study aims to elucidate the physiological responses of the chloroplasts in snake plants to pulsed electric field stimulation and to lay the foundation for enhancing the plant's release of negative air ion concentrations through physical and technological means.
Keyword ：
chlorophyll content chlorophyll content chlorophyll fluorescence parameters chlorophyll fluorescence parameters negative air ions negative air ions OJIP curve OJIP curve pulse electric field pulse electric field snake plants snake plants
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| GB/T 7714 | Liu, Jin , Huang, Deyao , Cheng, Zhiyuan et al. Impact of Pulse Electric Field Stimulation on Negative Air Ion Release Capacity of Snake Plants [J]. | AGRONOMY-BASEL , 2024 , 14 (10) . |
| MLA | Liu, Jin et al. "Impact of Pulse Electric Field Stimulation on Negative Air Ion Release Capacity of Snake Plants" . | AGRONOMY-BASEL 14 . 10 (2024) . |
| APA | Liu, Jin , Huang, Deyao , Cheng, Zhiyuan , Wu, Renye . Impact of Pulse Electric Field Stimulation on Negative Air Ion Release Capacity of Snake Plants . | AGRONOMY-BASEL , 2024 , 14 (10) . |
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Low-temperature stress is one of the factors affecting the growth and development of peanuts. Currently, biochemical detection technologies for crop freeze damage are well established. In the context of rapid development in optical sensing technology and smart agriculture, non-destructive crop freeze damage detection based on such technologies has gained increasing attention. The accurate detection, early warning, and targeted control of crop cold damage are particularly important. In this study, 70 peanut germplasm resources were collected and used for the research objectives. Indoor low-temperature seedling identification was conducted at 25 degrees C (the control group) and 5 degrees C (low-temperature stress group) for 7 days. Photosynthetic fluorescence values in leaves, as well as 13 indicators (Fo, Fm, Fv, Fv/Fm, Fv'/Fm', Phi PSII, NPQ, qP, Rfd, Pn, Gs, Ci, and Tr), were analyzed for their responses to low-temperature stress. The results showed that under low-temperature stress, the Pn and Ci of peanut seedlings exhibited an ascending trend, while Tr and other indicators showed a decreasing trend compared to the control group. Based on the relative coefficients of resistance to low temperature for each individual indicator, a comprehensive non-destructive evaluation of cold resistance was conducted using methods such as principal component analysis, cluster analysis, and stepwise regression. Through principal component analysis, the 13 individual physiological indicators were transformed into 3 comprehensive indicators. The 70 peanut varieties were divided into 4 categories based on their resistance to low temperature: sensitive materials, moderately sensitive materials, moderately cold-tolerant materials, and cold-tolerant materials. Additionally, a mathematical model for evaluating cold resistance in peanuts was established.
Keyword ：
germplasm resources germplasm resources low temperature low temperature peanut peanut seedling stage seedling stage
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| GB/T 7714 | Ye, Linmei , Wang, Tao , Wu, Renye et al. Evaluation of Cold Resistance at Seedling Stage for 70 Peanut Genotypes Based on Photosynthetic Fluorescence Characteristics [J]. | AGRONOMY-BASEL , 2024 , 14 (8) . |
| MLA | Ye, Linmei et al. "Evaluation of Cold Resistance at Seedling Stage for 70 Peanut Genotypes Based on Photosynthetic Fluorescence Characteristics" . | AGRONOMY-BASEL 14 . 8 (2024) . |
| APA | Ye, Linmei , Wang, Tao , Wu, Renye , Zheng, Conghui , Zhan, Liuqi , Chen, Jianhong et al. Evaluation of Cold Resistance at Seedling Stage for 70 Peanut Genotypes Based on Photosynthetic Fluorescence Characteristics . | AGRONOMY-BASEL , 2024 , 14 (8) . |
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为解决传统水稻稻瘟病抗性评估手段单一、效率低的问题，该研究提出一种无人机低空遥感技术结合YOLOv7模型的水稻穗颈瘟抗性鉴定方法。首先，将标注区域分割成小尺寸图像（≤1 240×1 240像素），将小尺寸图像进行旋转、缩放、平移、剪切和改变对比度处理。经数据清洗，去除分辨率过低的图像，扩充样本数量，以提高数据多样性。然后，将压缩注意力机制（squeeze-excitation attention）和可变形卷积（deformable convolution）引入YOLOv7模型，自适应调整感受野，以提升捕捉穗颈瘟病斑细粒度特征的能力。最后，构建穗颈瘟检测的YOLOv7＿Neckblast模型。研究结果表明，YOLOv7＿Neckblast能够有效检测穗颈瘟，计算出15个品种的穗颈瘟发病率和病害等级（1、3、5、7和9级的水稻品种分别有4、4、3、2和2个）。在交并比阈值为0.5时，YOLOv7＿Neckblast平均精度均值相较于YOLOv7、FCOS和RetinaNet分别提升了4.0、6.4和5.8个百分点，召回率和F1值分别提高了至少4.0和4.0个百分点，且浮点计算数和参数量最低。与育种专家判定的实际抗性水平相比，YOLOv7＿Neckblast模型对15个水稻品种的穗颈瘟抗性水平的平均评估准确率为86.67%，能较好地实现不同水稻品种穗颈瘟抗性的区分。无人机低空遥感融合人工智能技术可用于水稻黄熟期育种中穗颈瘟抗性的评估，也可为其他作物优势品种的选育提供参考。
Keyword ：
YOLOv7＿Neckblast模型 YOLOv7＿Neckblast模型 低空遥感 低空遥感 抗性评估 抗性评估 无人机 无人机 水稻 水稻 穗颈瘟 穗颈瘟
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| GB/T 7714 | 翁海勇 , 姚越 , 黄德耀 et al. 无人机低空遥感结合YOLOv7快速评估水稻穗颈瘟抗性 [J]. | 农业工程学报 , 2024 , 40 (21) : 110-118 . |
| MLA | 翁海勇 et al. "无人机低空遥感结合YOLOv7快速评估水稻穗颈瘟抗性" . | 农业工程学报 40 . 21 (2024) : 110-118 . |
| APA | 翁海勇 , 姚越 , 黄德耀 , 张玉婷 , 程组锌 , 叶大鹏 et al. 无人机低空遥感结合YOLOv7快速评估水稻穗颈瘟抗性 . | 农业工程学报 , 2024 , 40 (21) , 110-118 . |
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【目的】探明脉冲电场刺激对金边龙舌兰（Agave americana var.Marginata）光合电子传递链和释放负离子能力的影响。【方法】采用0 k V（对照，CK）、5 k V（T1）和7 k V（T2）3个不同脉冲电场处理刺激金边龙舌兰，比较和分析不同刺激下金边龙舌兰的叶绿素含量、快速叶绿素荧光诱导动力曲线（Rapid Chlorophyll Fluorescence Induction Kinetics Curve,OJIP曲线）、叶绿素荧光参数和负离子释放浓度的变化情况。【结果】（1）脉冲电场技术刺激金边龙舌兰后，两处理组叶绿素含量分别增长6.30%、6.70%，两处理组与CK组之间存在显著差异；（2）两处理组OJIP曲线，偏转（I）和最高峰（P）值均高于原点（O）和拐点（J）值，I-P段的上升趋势较O-J段平缓。同时，J-band均大于0,T2处理组峰值高于T1处理组；（3）叶绿素荧光参数均呈波动的变化趋势，其中最大荧光强度（F
Keyword ：
OJIP曲线 OJIP曲线 叶绿素含量 叶绿素含量 叶绿素荧光参数 叶绿素荧光参数 脉冲电场 脉冲电场 负离子 负离子 金边龙舌兰 金边龙舌兰
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| GB/T 7714 | 刘津 , 翁海勇 , 程致元 et al. 脉冲电场对金边龙舌兰光合电子传递链和释放负离子能力影响 [J]. | 福建农业学报 , 2024 , 39 (07) : 801-809 . |
| MLA | 刘津 et al. "脉冲电场对金边龙舌兰光合电子传递链和释放负离子能力影响" . | 福建农业学报 39 . 07 (2024) : 801-809 . |
| APA | 刘津 , 翁海勇 , 程致元 , 吴仁烨 . 脉冲电场对金边龙舌兰光合电子传递链和释放负离子能力影响 . | 福建农业学报 , 2024 , 39 (07) , 801-809 . |
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