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Automatic detection of sow estrus using a lightweight real-time detector and thermal images

International Journal of Agricultural and Biological Engineering 2023年第3期16卷 194-207页

作者： Haibo Zheng Hang Zhang Shuang Song Yue Wang tonghai liu College of Computer and Information Engineering Tianjin Agricultural UniversityTianjin 300392China

Determination of ovulation time is one of the most important tasks in sow reproduction *** variation in the vulva of the sows can be used as a predictor of ovulation ***,the skin temperatures of sows in existing studies are obtained manually from infrared thermal images,posing an obstacle to the automatic prediction of ovulation *** this study,an improved YOLO-V5s detector based on feature fusion and dilated convolution(FDYOLOV5s)was proposed for the automatic extraction of the vulva temperature of sows based on infrared thermal *** the purpose of reducing the model complexity,the depthwise separable convolution and the modified lightweight ShuffleNet-V2 module were introduced in the ***,the feature fusion network structure of the model was simplified for efficiency,and a mixed dilated convolutional module was designed to obtain global *** experimental results show that FD-YOLOV5s outperformed the other nine methods,with a mean average precision(mAP)of 99.1%,an average frame rate of 156.25 fps,and a model size of only 3.86 MB,indicating that the method effectively simplifies the model while ensuring detection *** a linear regression between manual extraction and the results extracted using this method in randomly selected thermal images,the coefficients of determination for maximum and average vulvar temperatures reached 99.5%and 99.3%,*** continuous vulva temperature of sows was obtained by the target detection algorithm,and the sow estrus detection was performed by the temperature trend and compared with the manually detected estrus *** results showed that the sensitivity,specificity,and error rate of the estrus detection algorithm were 89.3%,94.5%,and 5.8%,*** method achieves real-time and accurate extraction of sow vulva temperature and can be used for the automatic detection of sow estrus,which could be helpful for the automatic prediction of ovulation ti

关键词： automatic estrus detection thermal images real-time detector vulva temperature mixed dilated convolutional

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Research on Plant Species Identification Based on Improved Convolutional Neural Network

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Phyton-International Journal of Experimental Botany 2023年第4期92卷 1037-1058页

作者： Chuangchuang Yuan tonghai liu Shuang Song Fangyu Gao Rui Zhang College of Computer and Information Engineering Tianjin Agricultural UniversityTianjin300392China

Plant species recognition is an important research area in image recognition in recent ***,the existing plant species recognition methods have low recognition accuracy and do not meet professional requirements in terms of recognition ***,ShuffleNetV2 was improved by combining the current hot concern mechanism,convolution kernel size adjustment,convolution tailoring,and CSP technology to improve the accuracy and reduce the amount of computation in this *** convolutional neural network models with sufficient trainable parameters were designed for differentiation *** SGD algorithm is used to optimize the training process to avoid overfitting or falling into the local *** this paper,a conventional plant image dataset TJAU10 collected by cell phones in a natural context was constructed,containing 3000 images of 10 plant species on the campus of Tianjin Agricultural ***,the improved model is compared with the baseline version of the model,which achieves better results in terms of improving accuracy and reducing the computational *** recognition accuracy tested on the TJAU10 dataset reaches up to 98.3%,and the recognition precision reaches up to 93.6%,which is 5.1%better than the original model and reduces the computational effort by about 31%compared with the original *** addition,the experimental results were evaluated using metrics such as the confusion matrix,which can meet the requirements of professionals for the accurate identification of plant species.

关键词： Deep learning convolutional neural network plant identification model improvement

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YOLO-CRD:A Lightweight Model for the Detection of Rice Diseases in Natural Environments

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Phyton-International Journal of Experimental Botany 2024年第6期93卷 1275-1296页

作者： Rui Zhang tonghai liu Wenzheng liu Chaungchuang Yuan Xiaoyue Seng Tiantian Guo Xue Wang Tianjin Key Laboratory of Intelligent Breeding of Major Crops Tianjin Agricultural UniversityTianjin300392China College of Computer and Information Engineering Tianjin Agricultural UniversityTianjin300392China

Rice diseases can adversely affect both the yield and quality of rice crops,leading to the increased use of pesticides and environmental *** detection of rice diseases in natural environments is crucial for both operational efﬁciency and quality *** learning-based disease identiﬁcation technologies have shown promise in automatically discerning disease ***,effectively extracting early disease features in natural environments remains a challenging *** address this issue,this study proposes the YOLO-CRD *** research selected images of common rice diseases,primarily bakanae disease,bacterial brown spot,leaf rice fever,and dry tip nematode disease,from Tianjin *** proposed YOLO-CRD model enhanced the YOLOv5s network architecture with a Convolutional Channel Attention Module,Spatial Pyramid Pooling Cross-Stage Partial Channel module,and Ghost *** former module improves attention across image channels and spatial dimensions,the middle module enhances model generalization,and the latter module reduces model *** validate the feasibility and robustness of this method,the detection model achieved the following metrics on the test set:mean average precision of 90.2%,accuracy of 90.4%,F1-score of 88.0,and GFLOPS of *** the speciﬁc diseases,the mean average precision scores were 85.8%for bakanae disease,93.5%for bacterial brown spot,94%for leaf rice fever,and 87.4%for dry tip nematode *** studies and comparative analyses veriﬁed the effectiveness and superiority of the proposed *** researchﬁnd-ings can be applied to rice disease detection,laying the groundwork for the development of automated rice disease detection equipment.

关键词： Convolutional neural network one stage training rice disease deep learning

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Underwater Sea Cucumber Target Detection Based on Edge-Enhanced Scaling YOLOv4

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Journal of Beijing Institute of Technology 2023年第3期32卷 328-340页

作者： Ziting Zhang Hang Zhang Yue Wang tonghai liu Yuxiang He Yunchen Tian College of Computer and Information Engineering Tianjin Agricultural UniversityTianjin 300380China

Sea cucumber detection is widely recognized as the key to automatic *** underwater light environment is complex and easily obscured by mud,sand,reefs,and other underwater *** date,research on sea cucumber detection has mostly concentrated on the distinction between prospective objects and the ***,the key to proper distinction is the effective extraction of sea cucumber feature *** this study,the edge-enhanced scaling You Only Look Once-v4(YOLOv4)(ESYv4)was proposed for sea cucumber *** emphasizing the target features in a way that reduced the impact of different hues and brightness values underwater on the misjudgment of sea cucumbers,a bidirectional cascade network(BDCN)was used to extract the overall edge greyscale image in the image and add up the original RGB image as the detected ***,the YOLOv4 model for backbone detection is scaled,and the number of parameters is reduced to 48%of the original number of *** results of 783images indicated that the detection precision of positive sea cucumber samples reached *** improvement reflects that the algorithm is more effective to improve the edge feature information of the *** thus contributes to the automatic multi-objective detection of underwater sea cucumbers.

关键词： sea cucumber edge extraction feature enhancement edge-enhanced scaling You Only Look Once-v4(YOLOv4)(ESYv4) model scaling

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Accurate detection method of pig's temperature based on non-point source thermal infrared image

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CAAI Transactions on Intelligence Technology 2021年第3期6卷 312-323页

作者： Zaiqin Zhang Hao Wang tonghai liu Yueqiang Wang Hang Zhang Feiyan Yuan Xue Yang Shunlai Xu Yuhuan Meng Chongqing Academy of Animal Sciences Scientific Observation and Experiment Station of Livestock Equipment Engineering in Southwest for Ministry of Agriculture and Rural AffairsChongqing402460China College of Computer and Information Engineering Tianjin Agricultural UniversityTianjin300384China Department of Scientific Research Tianjin Agricultural UniversityTianjin300384China

Body temperature measurement is a very important task in the sow breeding *** authors used an infrared camera to detect the temperature of the body surface of the sows,relying on calculating the average of the infrared image temperature in the ear root *** on the grayscale value of the target image of the infrared image and the corresponding temperature value of 180 infrared images,a G-T(Gray-Temperature)model was established by linear least squares method,which achieved temperature inversion of each pixel of the target *** the different growth stages and different breeds of sows,the R-square of the all established models is greater than *** average relative error of the model inversion of the body temperature was only 0.076977%.This means that the body temperature of the sows could be detected without relying on the *** on the G-T model,the authors design a kind of sow's ear root recognition and body surface temperature detection algorithm for different sow population scenarios.

关键词： image method breeding

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Study on body temperature detection of pig based on infrared technology: A review

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Artificial Intelligence in Agriculture 2019年第1期1卷 14-26页

作者： Zaiqin Zhang Hang Zhang tonghai liu School of Computer and Information Engineering Tianjin Agricultural UniversityTianjin 300384China

Body temperature is an important physiological indicator in the whole process of pig *** measurement is also an effective means to assist in disease diagnosis and pig health *** the conventional method of measuring body temperature,a mercury column is used to obtain the rectal *** operation of thismethod is complicated and requires a large amount of *** kind of temperature measurement method is contact and canmake the pig stressed,which is disadvantageous for the healthy growth of ***,rectal temperaturemeasurement no longer meets the needs of the large-scale pig industry in China's welfare *** recent years,the emerging pig body temperature detection technologies are electronic temperaturemeasurement technology,infrared temperature measurement technology and so *** temperature measurement technology has been the main means of measuring the temperature of pig body surface with its advantages of non-contact,long distance and *** present,infrared temperature measurement technology and infrared image processing technology used in pig breeding are still in the exploration ***,the infrared temperature measurement equipment based on point-by-point analysis represented by infrared thermometer and temperature measurement equipment based on full-field analysis represented by infrared thermal imager have been applied to pig breeding *** types of temperaturemeasurement are more in line with the needs of the pig breeding industry to transform and upgrade to the automation,in line with the development concept of welfare farming and smart agriculture,and its development prospects are very impressive.

关键词： Pig body temperature measurement Non-contact Infrared image processing

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A potent PGK1 antagonist reveals PGK1 regulates the production of IL-1βand IL-6

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Acta Pharmaceutica Sinica B 2022年第11期12卷 4180-4192页

作者： Liping Liao Wenzhen Dang Tingting Lin Jinghua Yu tonghai liu Wen Li Senhao Xiao Lei Feng Jing Huang Rong Fu Jiacheng Li Liping liu Mingchen Wang Hongru Tao Hualiang Jiang Kaixian Chen Xingxing Diao Bing Zhou Xiaoyan Shen Cheng Luo Deparment of Pharmacology&the Key Laboratory of Smart Drug Delivery Ministry of EeducaionSchool of PharmacyFudan UniversityShanghai 201203China State Key Laboratory of Drug Research Shanghai Institute of Materia MedicaChinese Academy of SciencesShanghai 201203China University of Chinese Academy of Sciences Bejing 10049China School of Pharmaceutical Science and Technology Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China School of Pharmaceutical Sciences Zhejiang Chinese Medical UniversityHangzhou 310053China

Glycolytic metabolism enzymes have been implicated in the immunometabolism field through changes in metabolic status. PGK1 is a catalytic enzyme in the glycolytic pathway. Here, we set up a high-throughput screen platform to identify PGK1 inhibitors. DC-PGKI is an ATPcompetitive inhibitor of PGK1 with an affinity of Kd= 99.08 nmol/L. DC-PGKI stabilizes PGK1in vitro and in vivo, and suppresses both glycolytic activity and the kinase function of PGK1. In addition,DC-PGKI unveils that PGK1 regulates production of IL-1β and IL-6 in LPS-stimulated ***, inhibition of PGK1 with DC-PGKI results in NRF2(nuclear factor-erythroid factor 2-related factor 2, NFE2L2) accumulation, then NRF2 translocates to the nucleus and binds to the proximity region of Il-1β and Il-6 genes, and inhibits LPS-induced expression of these genes. DC-PGKI ameliorates colitis in the dextran sulfate sodium(DSS)-induced colitis mouse model. These data support PGK1 as a regulator of macrophages and suggest potential utility of PGK1 inhibitors in the treatment of inflammatory bowel disease.

关键词： Glycolysis Phosphoglycerate kinasel Macrophages NRF2 Inflammation

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反应结晶过程中二水硫酸钙晶粒性能

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化工学报 2016年第6期67卷 2449-2455页

作者：窦焰刘同海沈浩郑之银刘荣崔鹏合肥工业大学化学与化工学院安徽合肥230009 安徽六国化工股份有限公司安徽铜陵244000

设计了CaHPO_4·2H_2O-H_2SO_4-H_3PO_4-H_2O体系结晶温度、液相SO_4^(2-)含量、液相P_2O_5含量、搅拌速率和结晶时间的五因素四水平正交实验,通过测量晶体平均粒径优化出平均粒径最大的工艺参数:结晶温度80℃、液相SO_4^(2-)含量50 g·... 详细信息

设计了CaHPO_4·2H_2O-H_2SO_4-H_3PO_4-H_2O体系结晶温度、液相SO_4^(2-)含量、液相P_2O_5含量、搅拌速率和结晶时间的五因素四水平正交实验,通过测量晶体平均粒径优化出平均粒径最大的工艺参数:结晶温度80℃、液相SO_4^(2-)含量50 g·L^(-1)、液相P_2O_5含量260 g·L^(-1)、搅拌速率50 r·min^(-1)和结晶时间2 h。在该工艺参数下进行结晶过程研究,通过分析液相SO_4^(2-)浓度和P_2O_5浓度,XRD、SEM、EDS和激光粒度分析仪表征晶体,研究发现:0~40 min为反应阶段,平均粒径减小;40 min之后结晶过程遵从Ostwald递变法则,从Ca SO4·0.5H2O过渡到Ca SO4·2H2O,平均粒径几乎不变。

关键词：二水硫酸钙反应结晶制备过程

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基于机器视觉的猪体质量估测模型比较与优化

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农业工程学报 2015年第2期31卷 155-161页

作者：李卓毛涛涛刘同海滕光辉中国农业大学水利与土木工程学院北京100083 天津农学院计算机科学与信息工程系天津300384

基于机器视觉的猪体质量估测模型较多,但模型缺乏在实用性、准确性的对比,最佳模型没有定论。该文总结了已有的估测算法,基于79组背部图像面积、实际面积、体长、体宽、体高、臀宽、臀高数据,使用线性回归、幂回归、二次回归、主成分线... 详细信息

基于机器视觉的猪体质量估测模型较多,但模型缺乏在实用性、准确性的对比,最佳模型没有定论。该文总结了已有的估测算法,基于79组背部图像面积、实际面积、体长、体宽、体高、臀宽、臀高数据,使用线性回归、幂回归、二次回归、主成分线性回归、RBF(radial basis function,径向基函数)神经网络等方法,重建了13种体质量估测模型,并比较了13种模型的估测精度。结果表明,基于体长、体宽、体高、臀宽和臀高的线性回归模型具有较好的估测精度,估测值与真值的相关系数达到了0.996。利用主成分法去掉体尺的共线性,利用曲线回归解决残差不均匀问题,更加符合猪体质量增长趋势,结果表明基于主成分的幂回归模型具有较高的相关系数和较低的标准估计误差,对于97组数据的估测平均相对误差为2.02%。使用猪场实测24组数据验证模型,估测质量与测量值相关系数为0.97,估测平均相对误差为2.26%,标准差为1.78%,优于基于面积和面积体高结合的估测模型,平均绝对误差为2.08 kg,优于面积体高结合方法的平均绝对误差。试验证明使用多个体尺的主成分幂回归体质量估测模型较为精确,可用于机器视觉估测猪体质量的应用中。

关键词：动物图像处理模型猪体质量估测

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人脐带动脉与脐带静脉血管内皮细胞在体外相同培养环境下的定性研究

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中国细胞生物学学报 2020年第4期42卷 656-663页

作者：刘倩刘通海叶进培山西大学生物医学研究院太原030006

血管内皮细胞受损与许多心脑血管疾病的发生和发展有关,已成为当今生命科学、药学领域的重要的研究对象。体外分离获得血管内皮细胞以及鉴定对于研究血管功能和为心脑血管疾病建立细胞模型极为重要。该研究通过了一种简便快捷、分离纯... 详细信息

血管内皮细胞受损与许多心脑血管疾病的发生和发展有关,已成为当今生命科学、药学领域的重要的研究对象。体外分离获得血管内皮细胞以及鉴定对于研究血管功能和为心脑血管疾病建立细胞模型极为重要。该研究通过了一种简便快捷、分离纯度高的人脐带动脉内皮细胞(human umbilical cord artery endothelial cells,HUAEC)和脐带静脉内皮细胞(human umbilical cord vein endothelial cells,HUVEC)的分离及培养体系,同时从形态特征、增殖活力、成管能力、表面抗原和特异基因的表达等方面检测了二者在体外相同培养环境下的动态变化与差异。该研究发现,HUAEC和HUVEC在体外连续传代培养过程中形态特征、成管能力、表面抗原(CD144、CD31、CD309、CD133、CD34)这几个方面作为内个皮细胞的基本特性没有明显差异,尽管HUAEC相对于HUVEC增殖活力更高。对于新鲜分离的HUAEC和HUVEC,二者特异性基因表达水平具有显著差异(HUAEC高表达EFNB2、DLL4、NRP1、CXCR4;HUVEC高表达EPHB4、COUP-TF II),然而随着培养时间的延长(传代次数的增加),HUAEC丧失其特异性基因(P6)的表达之后,HUVEC仍保持其特异性基因的高表达。因此HUVEC特异性表达基因EPHB4、COUP-TF II可以作为区分体外培养的人脐带动脉或者脐带静脉来源的内皮细胞的可靠鉴定标志基因。

关键词：人脐带动脉内皮细胞人脐带静脉内皮细胞成管功能表面抗原特异性基因内皮细胞定性

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