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Development of the automatic navigation system for combine harvester based on GNSS

International Journal of Agricultural and Biological Engineering 2021年第5期14卷 163-171页

作者： Shichao Li Man Zhang Ruyue Cao Yuhan Ji Zhenqian Zhang Han Li Yanxin Yin Key lab of Modern precision agriculture System Integration Research Ministry of EducationChina Agricultural UniversityBeijing 100083China National Research Center of Intelligent Equipment for agriculture Beijing 100097China

An automatic navigation system was developed to realize automatic driving for combine harvester,including the mechanical design,control method and software *** of all,for the harvester modified with the automatic navigation system,a dynamic calibration method of the rear wheel center position was *** control part included the navigation controller and the steering controller.A variable universe fuzzy controller was designed to the navigation controller,which used fuzzy control to change the fuzzy universe of input and output dynamically,that means,under the condition that the fuzzy rules remain unchanged,the fuzzy universe changes with the change of input,which is an adaptive fuzzy control method and can modify the control strategy in *** realize the automatic navigation of the harvester,the decision result of the navigation controller based on the variable universe fuzzy control was input into the steering controller,and then the electric steering wheel was controlled to *** test the performance of the designed automatic navigation system,the field experiment was carried *** the combine harvester was navigating linearly at a speed of 0.8 m/s,the overall root mean square error(RMSE)of the lateral deviation was 5.87 *** test results showed that the system was designed could make the combine track the preset path smoothly and stably,and the tracking accuracy was at the centimeter level.

关键词： automatic navigation system combine harvester GNSS development dynamic calibration variable universe adaptive fuzzy control

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A lab-on-a-disc platform based on nickel nanowire net and smartphone imaging for rapid and automatic detection of foodborne bacteria

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Chinese Chemical Letters 2022年第4期33卷 2091-2095页

作者： Xiaoting Huo Lei Wang Wuzhen Qi Na Rong Yingjia Liu Siyuan Wang Hong Duan Jianhan Lin Key laboratory of Agricultural Information Acquisition Technology Ministry of Agriculture and Rural AffairsChina Agricultural UniversityBeijing 100083China Key laboratory of Modern precision agriculture System Integration Research Ministry of EducationChina Agricultural UniversityBeijing 100083China

Foodborne pathogenic bacteria have been considered as a major risk factor for food safety. It is of great significance to carry out in-field screening of pathogenic bacteria to prevent the outbreaks of foodborne diseases. In this study, a portable lab-on-a-disc platform with a microfluidic disc was developed for rapid and automatic detection of Salmonella typhimurium using a nickel nanowire(Ni NW) net for effective separation of target bacteria, horseradish peroxidase nanoflowers(HRP NFs) for efficient amplification of biological signals, and a self-developed smartphone APP for accurate analysis of colorimetric images. First,the microfluidic disc was preloaded with reagents and samples and centrifuged to form one bacterial sample column, one immune Ni NW column, one HRP NF column, two washing buffer columns and one tetramethylbenzidine(TMB) column, which were separated by air gaps. Then, a rotatable magnetic field was specifically developed to assemble the Ni NWs into a net, which was automatically controlled by a stepped motor to successively pass through the sample column for specific capture of target bacteria, the HRP NF column for specific label of target bacteria, the washing columns for effective removal of sample background and non-specific binding NFs, and the TMB column for colorimetric determination of target bacteria. The color change of TMB from colorless to blue was finally analyzed using the smartphone APP to quantitatively determine the target bacteria. This lab-on-a-disc platform could detect Salmonella typhimurium from 5.6 × 10^(1) CFU/20 μL to 5.6 × 10^(5) CFU/20 μL in 1 h with a lower detection limit of 56 CFU/20 μL. The recovery of target bacteria in spiked chicken samples ranged from 97.5% to 101.8%. This portable platform integrating separation, labeling, washing, catalysis and detection onto a single disc is featured with automatic operation, fast reaction, and small size and has shown its potential for in-field detection of foodborne pathoge

关键词： lab-on-a-disk platform Nickel nanowire net Horseradish peroxidase nanoflowers Smartphone Bacteria detection

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Comparative analysis of SIMILAR to RCD ONE(SRO)family from tetraploid cotton species and their diploid progenitors depict their significance in cotton growth and development

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Journal of Cotton Research 2024年第1期7卷 45-57页

作者： SHABAN Muhammad TABASSUM Riaz RANA Iqrar Ahmad ATIF Rana Muhammad AZMAT Muhammad Abubakkar IQBAL Zubair MAJEED Sajid AZHAR Muhammad Tehseen Department of Plant Breeding and Genetics University of Agriculture FaisalabadSub-Campus BurewalaVehari 61010Pakistan Department of Chemistry and Biochemistry University of AgricultureFaisalabad 38400Pakistan Centre of Agricultural Biochemistry and Biotechnology University of AgricultureFaisalabad 38400Pakistan Department of Plant Breeding and Genetics University of AgricultureFaisalabad 38400Pakistan precision agriculture and analytics lab National Centre in Big Data and Cloud ComputingCentre for Advanced Studies in Agriculture and Food SecurityUniversity of Agriculture FaisalabadFaisalabad 38400Pakistan Department of Plant Pathology University of CaliforniaDavisCA 95616USA State Key laboratory of Cotton Biology Institute of Cotton ResearchChinese Academy of Agricultural SciencesAnyangHenan 455000China Federal Seed Certification and Registration Department Ministry of National Food Security and ResearchIslamabad 44090Pakistan School of agriculture Sciences Zhengzhou UniversityZhengzhou 450000China

Background SRO(Similar to RCD1)genes family is largely recognized for their importance in the growth,develop-ment,and in responding to environmental ***,genome-wide identification and functional characteri-zation of SRO genes from cotton species have not been reported so *** A total of 36 SRO genes were identified from four cotton *** analysis divided these genes into three groups with distinct *** and chromosomal distribution analysis indicated uneven distribu-tion of GaSRO,GrSRO,GhSRO,and GbSRO genes on A2,D5 genomes,Gh-At,Gh-Dt,Gb-At,and Gb-Dt subgenomes,*** duplication analysis revealed the presence of six duplicated gene pairs among GhSRO *** promoter analysis,several elements responsive to the growth,development and hormones were found in GhSRO genes,implying gene induction during cotton growth and *** miRNAs responsive to plant growth and abiotic stress were predicted to target 12 GhSRO ***-specific expression profiling demonstrated the roles of GhSRO genes in one or more *** addition,specific expression pattern of some GhSRO genes dur-ing ovule development depicted their involvement in these developmental *** The data presented in this report laid a foundation for understanding the classification and functions of SRO genes in cotton.

关键词： Cotton SRO miRNAs Gene duplications Gene expression Ovule development

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Insect classification and detection in field crops using modern machine learning techniques

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Information Processing in agriculture 2021年第3期8卷 446-457页

作者： Thenmozhi Kasinathan Dakshayani Singaraju Srinivasulu Reddy Uyyala Machine Learning and Data analytics lab Centre of Excellence in Artificial IntelligenceDepartment of Computer ApplicationsNational Institute of TechnologyTiruchirappalliTiruchirappalli 620015Tamil NaduIndia

The agriculture sector has an immense potential to improve the requirement of food and supplies healthy and nutritious *** insect detection is a challenging task for farmers as a significant portion of the crops are damaged,and the quality is degraded due to the pest *** insect identification has the drawback of requiring well-trained tax-onomists to identify insects based on morphological features *** were conducted for classification on nine and 24 insect classes of Wang and Xie dataset using the shape features and applying machine learning techniques such as artificial neural net-works(ANN),support vector machine(SVM),k-nearest neighbors(KNN),naive bayes(NB)and convolutional neural network(CNN)*** paper presents the insect pest detec-tion algorithm that consists of foreground extraction and contour identification to detect the insects for Wang,Xie,Deng,and IP102 datasets in a highly complex *** 9-fold cross-validation was applied to improve the performance of the classification *** highest classification rate of 91.5%and 90%was achieved for nine and 24 class insects using the CNN *** detection performance was accomplished with less com-putation time for Wang,Xie,Deng,and IP102 datasets using insect pest detection *** comparison results with the state-of-the-art classification algorithms exhibited considerable improvement in classification accuracy,computation time perfor-mance while apply more efficiently in field crops to recognize the *** results of classification accuracy are used to recognize the crop insects in the early stages and reduce the time to enhance the crop yield and crop quality in agriculture.

关键词： Crop pest classification Crop insect detection Image processing Machine learning Image segmentation

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Effects of hydroxyproline supplementation in low fish meal diets on collagen synthesis, myofiber development and muscular texture of juvenile Pacific white shrimp(Litopenaeus vannamei)

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Animal Nutrition 2024年第2期17卷 428-437页

作者： Menglin Shi Haoming Li Tianyu Chen Bocheng Huang Xiaoyue Li Xiaohui Dong Shuyan Chi Qihui Yang Hongyu Liu Junming Deng Beiping Tan Shuang Zhang Shiwei Xie laboratory of Aquatic Nutrition and Feed College of Fisheries Guangdong Ocean University Aquatic Animals precision Nutrition and High-Efficiency Feed Engineering Research Centre of Guangdong Province Key laboratory of Aquatic Livestock and Poultry Feed Science and Technology in South China Ministry of Agriculture Guangdong Provincial Key lab of Aquatic Animals Disease Control and Healthy Culture

This experiment aimed to evaluate the impact of dietary hydroxyproline(Hyp) supplementation on the muscle quality of juvenile Pacific white shrimp(Litopenaeus vannamei) fed a low fishmeal diet. Six formulated diets included one high fishmeal(HF; 25% fishmeal content) and five low fishmeal diets(10%fishmeal content) with 0%, 0.2%, 0.4%, 0.6% and 0.8% Hyp(LF0, LF2, LF4, LF6 and LF8, respectively). Each diet was assigned to four replicates, and 40 shrimp(0.32 ± 0.00 g) per replicate were fed four times a day for 8 weeks. Dietary Hyp supplementation had little effects on growth performance, but increased the contents of Hyp, prolyl 4-hydroxylases(P4Hs), and collagen. The meat yield, springiness, hardness,chewiness, and cohesiveness of muscle were the highest in the LF4 group among the low fishmeal groups(P < 0.05). Cooking loss and freezing loss of muscle were the lowest in the LF4 group(P < 0.05). Dietary supplementation with 0.4% Hyp increased the myofiber density and decreased the myofiber diameter of muscle(P < 0.05). Supplementation of Hyp in the diet up-regulated the mRNA expression of smyhc5,smyhc15, col1a1, col1a2, igf-1f, tgf-β and tor and down-regulated the mRNA expression of smyhc1, smyhc2,smyhc6a(P < 0.05). Supplementation of Hyp in the diet up-regulated the protein expression of P-4E-BP1,P-AKT, AKT and P-AKT/AKT(P < 0.05). These results suggested that the addition of 0.4% Hyp to low fishmeal diets improved the muscle quality of L. vannamei.

关键词： Hydroxyproline Collagen Muscle quality Litopenaeus vannamei

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In-situ soil texture classification and physical clay content measurement based on multi-source information fusion

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International Journal of Agricultural and Biological Engineering 2023年第1期16卷 203-211页

作者： Chao Meng Wei Yang Xinjian Ren Dong Wang Minzan Li Key lab of Smart agriculture Systems Ministry of EducationChina Agricultural UniversityBeijing 100083China

Soil texture is one of the most important soil characteristics that affect soil *** acquisition of soil texture information is of great significance for accurate farmland *** soil texture analysis methods are relatively complicated and cannot meet the requirements of temporal and spatial *** research introduced a self-developed vehicle-mounted in-situ soil texture detection system,which can predict the type of soil texture and the particle composition of the texture,and obtain real-time data during the measurement process without preprocessing the soil *** detection system is mainly composed of a conductivity measuring device,a camera,an auxiliary mechanical structure,and a control *** soil electrical conductivity(ECa)and the texture features extracted from the surface image were input into the embedded model to realize real-time texture *** order to find the best model suitable for the detection system,measurements were carried out in three test fields in Northeast and North China to compare the performance of different models applied to the detection *** results showed that for soil texture classification,ExtraTrees performed best,with precision,Recall,and F1 all being *** particle content of soil texture prediction,the R2 of ExtraTrees was 0.77,and RMSE and MAPE were 74.72 and *** was observed that ECa,Moment of inertia,and Entropy had larger weights in the drawn model influence weight map,and they are the main contributors to predicting soil *** results showed the potential of the vehicle-mounted in-situ soil texture detection system,which can provide a basis for fast,cost-effective,and efficient soil texture analysis.

关键词： soil texture soil sensor electrical conductivity soil surface image

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A volumetric change detection framework using UAV oblique photogrammetry–a case study of ultra-high-resolution monitoring of progressive building collapse

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International Journal of Digital Earth 2021年第11期14卷 1705-1720页

作者： Ningli Xu Debao Huang Shuang Song Xiao Ling Chris Strasbaugh Alper Yilmaz Halil Sezen Rongjun Qin Geospatial Data analytics lab The Ohio State UniversityColumbusOHUSA Photogrammetric Computer Vision lab The Ohio State UniversityColumbusOHUSA Department of Civil Environmental and Geodetic EngineeringThe Ohio State UniversityColumbusOHUSA Department of Electrical and Computer Engineering The Ohio State UniversityColumbusOHUSA Translational Data analytics Institute The Ohio State UniversityColumbusOHUSA Engineering Technology Services The Ohio State UniversityColumbusOHUSA

In this paper,we present a case study that performs an unmanned aerial vehicle(UAV)based fine-scale 3D change detection and monitoring of progressive collapse performance of a building during a demolition ***-temporal oblique photogrammetry images are collected with 3D point clouds generated at different stages of the *** geometric accuracy of the generated point clouds has been evaluated against both airborne and terrestrial LiDAR point clouds,achieving an average distance of 12 cm and 16 cm for roof and façade *** propose a hierarchical volumetric change detection framework that unifies multi-temporal UAV images for pose estimation(free of ground control points),reconstruction,and a coarse-to-fine 3D density change *** work has provided a solution capable of addressing change detection on full 3D time-series datasets where dramatic scene content changes are presented *** change detection results on the building demolition event have been evaluated against the manually marked ground-truth changes and have achieved an F-1 score varying from 0.78 to 0.92,with consistently high precision(0.92–0.99).Volumetric changes through the demolition progress are derived from change detection and have been shown to favorably reflect the qualitative and quantitative building demolition progression.

关键词： 3D change detection multitemporal data registration oblique photogrammetry

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Fast processing of foreign fiber images by image blocking

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Information Processing in agriculture 2014年第1期1卷 2-13页

作者： Yutao Wu Daoliang Li Zhenbo Li Wenzhu Yang Beijing Engineering&Technology Research Center for Internet of Things in agriculture China-EU Center for Information and Communication Technologies in Agriculture of China Agriculture UniversityBeijing100083PR China Key lab of Machine Learning and Computational Intelligence College of Mathematics and Computer ScienceHebei UniversityBaoding071002PR China

In the textile industry,it is always the case that cotton products are constitutive of many types of foreign fibers which affect the overall quality of cotton *** the foundation of the foreign fiber automated inspection,image process exerts a critical impact on the process of foreign fiber *** paper presents a new approach for the fast processing of foreign fiber *** approach includes five main steps,image block,image predecision,image background extraction,image enhancement and segmentation,and image *** first,the captured color images were transformed into gray-scale images;followed by the inversion of gray-scale of the transformed images;then the whole image was divided into several ***,the subsequent step is to judge which image block contains the target foreign fiber image through image *** we segment the image block via OSTU which possibly contains target images after background eradication and image ***,we connect those relevant segmented image blocks to get an intact and clear foreign fiber target *** experimental result shows that this method of segmentation has the advantage of accuracy and speed over the other segmentation *** the other hand,this method also connects the target image that produce fractures therefore getting an intact and clear foreign fiber target image.

关键词： Cotton Foreign fibers Fast image processing Image block Image pre-decision Image connection

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Detection and Identification of Tassel States at Different Maize Tasseling Stages Using UAV Imagery and Deep Learning

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Plant Phenomics 2024年第3期6卷 563-578页

作者： Jianjun Du Jinrui Li Jiangchuan Fan Shenghao Gu Xinyu Guo Chunjiang Zhao Information Technology Research Center Beijing Academy of Agriculture and Forestry SciencesBeijing 100097China Beijing Key lab of Digital Plants National Engineering Research Center for Information Technology in AgricultureBeijing 100097China College of Information Engineering Northwest A&F UniversityYanglingShanxi 712100 China

The tassel state in maize hybridization fields not only reflects the growth stage of the maize but also reflects the performance of the detasseling *** tassel detection models are primarily used to identify mature tassels with obvious features,making it difficult to accurately identify small tassels or detasseled *** study presents a novel approach that utilizes unmanned aerial vehicles(UAVs)and deep learning techniques to accurately identify and assess tassel states,before and after manually detasseling in maize hybridization *** proposed method suggests that a specific tassel annotation and data augmentation strategy is valuable for substantial enhancing the quality of the tassel training *** study also evaluates mainstream object detection models and proposes a series of highly accurate tassel detection models based on tassel categories with strong data *** addition,a strategy for blocking large UAV images,as well as improving tassel detection accuracy,is proposed to balance UAV image acquisition and computational *** experimental results demonstrate that the proposed method can accurately identify and classify tassels at various stages of *** tassel detection model optimized with the enhanced data achieves an average precision of 94.5%across all *** optimal model combination that uses blocking strategies for different development stages can improve the tassel detection accuracy to 98%.This could be useful in addressing the issue of missed tassel detections in maize hybridization *** data annotation strategy and image blocking strategy may also have broad applications in object detection and recognition in other agricultural scenarios.

关键词： identification different learning imagery detection deep maize stages states tasseling

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Vocal individuality and rhythm in male and female duet contributions of a nonhuman primate

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Current Zoology 2020年第2期66卷 173-186页

作者： Dena J.CLINK Johny S.TASIRIN Holger KLINCK Bioacoustics Research Program Cornell Lab of OrnithologyCornell UniversityIthacaNY14850USA Faculty of agriculture Sam Ratulangi UniversityManadoIndonesia

Duetting,or the stereotypical,repeated and often coordinated vocalizations between 2 individuals arose independently multiple times in the Order *** primate species,there exists substantial variation in terms of timing,degree of overlap,and sex-specificity of duet *** is increasing evidence that primates can modify the timing of their duet contributions relative to their partner,and this vocal flexibility may have been an important precursor to the evolution of human ***,we present the results of a fine-scale analysis of Gursky’s spectral tarsier Tarsius spectrumgurskyae duet phrases recorded in North Sulawesi,***,we aimed to investigate individual-level variation in the female and male contributions to the duet,quantify individual-and pair-level differences in duet timing,and measure temporal precision of duetting individuals relative to their *** were able to classify female duet phrases to the correct individual with an 80%accuracy using support vector machines,whereas our classification accuracy for males was lower at 64%.Females were more variable than males in terms of timing between *** tarsier phrases exhibited some degree of overlap between callers,and tarsiers exhibited high temporal precision in their note output relative to their *** provide evidence that duetting tarsier individuals can modify their note output relative to their duetting partner,and these results support the idea that flexibility in vocal exchanges—a precursor to human language—evolved early in the primate lineage and long before the emergence of modern humans.

关键词： primate vocal communication rhythm vocal plasticity vocal individuality

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