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Detection system of smart sprayers: Status, challenges, and perspectives

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International Journal of Agricultural and Biological Engineering 2012年第3期5卷 10-23页

作者： Sun Hong Li Minzan Qin Zhang Key laboratory of Modern precision agriculture System Integration Research China Agricultural UniversityBeijing 100083China Center for precision&Automated Agricultural Systems Washington State UniversityProsserWA 99350USA

A smart sprayer comprises a detection system and a chemical spraying *** this study,the development status and challenges of the detection systems of smart sprayers are discussed along with perspectives on these *** detection system of a smart sprayer is used to collect information on target areas and make spraying *** spraying system controls sprayer *** sensing technologies,such as machine vision,spectral analysis,and remote sensing,are used in target *** image processing,morphological features are employed to segment characteristics such as shape,structure,color,and *** spectral analysis,the characteristics of reflectance and multispectral images are applied in crop *** the remote sensing application,vegetation indices and hyperspectral images are used to provide information on crop *** sensors,such as thermography,ultrasonic,laser,and X-ray sensors,are also used in the detection system and mentioned in the *** the basis of this review,challenges and perspectives are *** findings of this study may aid the understanding of smart sprayer systems and provide feasible methods for improving efficiency in chemical applications.

关键词： smart sprayer target detection weed control disease detection chemical application

Rapid on-line non-destructive detection of the moisture content of corn ear by bioelectrical impedance spectroscopy

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International Journal of Agricultural and Biological Engineering 2015年第6期8卷 37-45页

作者： Zhao Pengfei Zhang Hanlin Zhao Dongjie Wang Zhijie Fan Lifeng Huang Lan Ma Qin Wang Zhongyi College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083China Modern precision agriculture System Integration Research Key laboratory Ministry of EducationBeijing 100083China Key laboratory of Agricultural Information Acquisition Technology(Beijing) Ministry of AgricultureBeijing 100083China

Moisture content of corn directly affects its quality and storage time,and the rapid on-line detection of the moisture content of corn ears not threshed or in vivo in the fields is *** of the special shape of corn ear,the rapid,low cost and non-destructive bioelectrical impedance measurement is more suitable for its moisture content *** the four-electrode method with the Agilent E4980A precision LCR meter,the electrical impedance spectroscopies of the sweet corn ears and waxy corn ears at different moisture contents were *** frequency range of the detection was from 20 Hz to 2 MHz and to enhance the contact,the attached-type electrodes were wrapped in cotton soaked with 0.1%NaCl *** impedance data over the frequency range from 300 Hz to 5 kHz were used to obtain the parameters of the bio-impedance Cole-Cole *** results showed a good linear correlation(coefficient of determination R2=0.960)between the equivalent parallel resistance R∞of sweet corn ear and the moisture content value determined by standard chemical *** research proved that the bioelectrical impedance spectroscopy can be used for detecting the moisture content of corn ear.

关键词： moisture content non-destructive detection bioelectrical impedance spectroscopy corn ear

A Time-Varying Parameter Estimation Method for Physiological Models Based on Physical Information Neural Networks

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Computer Modeling in Engineering & Sciences 2023年第12期137卷 2243-2265页

作者： Jiepeng Yao Zhanjia Peng Jingjing Liu Chengxiao Fan Zhongyi Wang Lan Huang College of Information and Electrical Engineering China Agricultural UniversityBeijing100083China Key laboratory of Agricultural Information Acquisition Technology(Beijing) Ministry of AgricultureBeijing100083China Key laboratory of Modern precision agriculture System Integration Research Ministry of EducationBeijing100083China

In the establishment of differential equations,the determination of time-varying parameters is a difficult problem,especially for equations related to life ***,we propose a new framework named BioE-PINN based on a physical information neural network that successfully obtains the time-varying parameters of differential *** the proposed framework,the learnable factors and scale parameters are used to implement adaptive activation functions,and hard constraints and loss function weights are skillfully added to the neural network output to speed up the training convergence and improve the accuracy of physical information neural *** this paper,taking the electrophysiological differential equation as an example,the characteristic parameters of ion channel and pump kinetics are determined using *** results demonstrate that the numerical solution of the differential equation is calculated by the parameters predicted by BioE-PINN,the RootMean Square Error(RMSE)is between 0.01 and 0.3,and the Pearson coefficient is above 0.87,which verifies the effectiveness and accuracy of ***,realmeasuredmembrane potential data in animals and plants are employed to determine the parameters of the electrophysiological equations,with RMSE 0.02-0.2 and Pearson coefficient above *** conclusion,this framework can be applied not only for differential equation parameter determination of physiological processes but also the prediction of time-varying parameters of equations in other fields.

关键词： Physics-informed neural network differential equation bioelectrical signals inverse problems

Measurement of soil electrical conductivity based on direct digital synthesizer(DDS)and digital oscilloscope

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International Journal of Agricultural and Biological Engineering 2019年第6期12卷 162-168页

作者： Xiaoshuai Pei Chao Meng Minzan Li Wei Yang Peng Zhou Key laboratory of Modern precision agriculture System Integration Research Ministry of EducationChina Agricultural UniversityBeijing 100083China Key laboratory of Agricultural Information Acquisition Technology Ministry of Agriculture and Rural AffairsChina Agricultural UniversityBeijing 100083China

A soil electrical conductivity(EC)measurement system based on direct digital synthesizer(DDS)and digital oscilloscope was *** system took the“current-voltage four-electrode method”as the design principal and adopted a six-pin structure of the probe,two center pins to measure the soil EC in shallow layer,two outside pins to measure the soil EC in deep layer,and two middle pins for inputting the driving current.A signal generating circuit using DDS technology was adopted to generate sine signals,which was connected with the two middle pins.A digital oscilloscope was used to record and store the two soil output signals with noises in microseconds,which were from the two center pins and two outside pins,*** a digital bandpass filter was used to filter the soil output signals recorded by the digital *** with the traditional analog filter circuit,the digital filter could filter out the noises of all frequency except for the frequency of the excitation *** could improve the effect of filtering and the accuracy of the soil EC measurement *** DDS circuit could provide more stable sine signals with larger *** use of digital oscilloscope enables us to analyze the soil output signals in microseconds and measure the soil EC more *** new soil EC measurement system based on DDS and digital oscilloscope can provide a new effective tool for soil sensing in precision agriculture.

关键词： soil electrical conductivity direct digital synthesizer digital oscilloscope precision agriculture current-voltage four-electrode method

Measurement and prediction of tomato canopy apparent photosynthetic rate

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International Journal of Agricultural and Biological Engineering 2019年第5期12卷 156-161页

作者： Jian Yin Xinying Liu Yanlong Miao Yang Gao Ruicheng Qiu Man Zhang Han Li Minzan Li Key laboratory of Modern precision agriculture System Integration Research Ministry of EducationChina Agricultural UniversityBeijing 100083China Key laboratory of Agricultural Information Acquisition Technology Ministry of Agriculture and Rural AffairsChina Agricultural UniversityBeijing 100083China

Given the lack of technical conditions and research methods,instruments that can measure the canopy apparent photosynthetic rate have low precision and are rarely *** studies on canopy apparent photosynthetic rate and single leaf photosynthetic rate are also relatively *** study aims to measure and predict the canopy apparent photosynthetic rate of tomato.A canopy apparent photosynthetic rate measuring system,which was comprised of a wireless sensor network(WSN),an assimilation chamber,and a LI-6400XT photosynthetic rate instrument was *** system was used to determine the greenhouse environmental parameters and CO2 absorptive capacity of the whole growth stage of tomato.A semi-closed assimilation chamber was designed as a side opening to conveniently measure the canopy apparent photosynthetic *** nodes were placed in the chamber to monitor environmental parameters,including air temperature,air humidity,and assimilation chamber temperature.A grid and pixel conversion method was used to measure the whole plant leaf areas of *** a semi-closed measurement system,the assimilation chamber was used to calculate the canopy apparent photosynthetic *** conduct a comparative research on the canopy apparent photosynthetic rate and the single leaf photosynthetic rate,the LI-6400XT portable photosynthesis system was used to measure the single leaf photosynthetic rate,and the support vector machine was used to establish the prediction model of canopy apparent photosynthetic *** experimental results indicated that the correlation coefficients of the photosynthesis prediction model in the seeding and flowering stages were 0.9420 and 0.9226,respectively,showing the high accuracy of the SVM model.

关键词： photosynthetic rate tomato assimilation chamber SVM photosynthesis prediction model

Tracking guided actions recognition for cows

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Quantitative Biology 2022年第4期10卷 351-365页

作者： Yun Liang Xiaoming Chen Guangzhou Key laboratory of Intelligent agriculture College of Mathematics and InformaticsSouth China Agricultural UniversityGuangzhou 510642China

Background:Cows actions are important factors of cows health and their *** monitoring the individual cows actions,we prevent cows diseases and realize modern precision cows ***,traditional cows actions monitoring is usually conducted through video recording or direct visual observation,which is time-consuming and laborious,and often lead to misjudgement due to the subjective consciousness or ***:This paper proposes a method of cows actions recognition based on tracked trajectories to automatically recognize and evaluate the actions of ***,we construct a dataset including 60 videos to describe the popular actions existing in the daily life of cows,providing the basic data for designing our actions recognition ***,eight famous trackers are used to track and obtain temporal and spatial information of ***,after studying and analysing the tracked trajectories of different actions about cows,a rigorous and effective constraint method is designed to realize actions recognition by ***:Many experiments demonstrate that our method of actions recognition performs favourably in detecting the actions of cows,and the proposed dataset basically satisfies the actions evaluation for ***:The proposed tracking guided actions recognition provides a feasible way to maintain and promote cows health and welfare.

关键词： public framework actions recognition visual tracking precision agriculture cows health

Universality of an improved photosynthesis prediction model based on PSO-SVM at all growth stages of tomato

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International Journal of Agricultural and Biological Engineering 2017年第2期10卷 63-73页

作者： Li Ting Ji Yuhan Zhang Man Sha Sha Li Minzan Key laboratory of Modern precision agriculture System Integration Research Ministry of EducationChina Agricultural UniversityBeijing 100083China Key laboratory of Agricultural Information Acquisition Technology Ministry of AgricultureChina Agriculture UniversityBeijing 100083China Beijing Research Institute of Uranium geology Beijing 100029China

CO_(2)concentration is an environmental factor affecting photosynthesis and consequently the yield and quality of *** this study,a photosynthesis prediction model for the entire growth stage of tomatoes was constructed to elevate CO_(2)level on the basis of crop requirements and to evaluate the effect of CO_(2)elevation on leaf *** effect of CO_(2)enrichment on tomato photosynthesis was investigated using two CO_(2)enrichment treatments at the entire growth stage.A wireless sensor network-based environmental monitoring system was used for the real-time monitoring of environmental factors,and the LI-6400XT portable photosynthesis system was used to measure the net photosynthetic rate of tomato *** input variables for the model,environmental factors were uniformly preprocessed using independent component ***,the photosynthesis prediction model for the entire growth stage was established on the basis of the support vector machine(SVM)*** particle swarm optimization(PSO)was also used to search for the best parameters c and g of ***,the relationship between CO_(2)concentration and photosynthetic rate under varying light intensities was predicted using the established model,which can determine CO_(2)saturation points at the various growth *** determination coefficients between the simulated and observed data sets for the three growth stages were 0.96,0.96,and 0.94 with the improved PSO-SVM and 0.89,0.87,and 0.86 with the original *** results indicate that the improved PSO-SVM exhibits a high prediction *** study provides a basis for the precise regulation of CO_(2)enrichment in greenhouses.

关键词： photosynthesis greenhouse tomato CO2 enrichment photosynthesis prediction model wireless sensor network environmental monitoring system

Identification of seedling cabbages and weeds using hyperspectral imaging

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International Journal of Agricultural and Biological Engineering 2015年第5期8卷 65-72,I0004页

作者： Deng Wei Yanbo Huang Zhao Chunjiang Wang Xiu Beijing Research Center of Intelligent Equipment for agriculture Beijing Academy of Agriculture and Forestry ScienceBeijing 100097China United States Department of agriculture Agricultural Research ServiceCrop Production Systems Research UnitStonevilleMississippiUSA National Research Center of Intelligent Equipment for agriculture Beijing 100097China Key laboratory of Agri-informatics Ministry of AgricultureBeijing 100097China Beijing Key laboratory of Intelligent Equipment Technology for agriculture Beijing 100097China

Target detection is one of research focuses for precision chemical *** study developed a method to identify seedling cabbages and weeds using hyperspectral *** processing the image data with ENVI software,after dimension reduction,noise reduction,de-correlation for high-dimensional data,and selection of the region of interest,the SAM(Spectral Angle Mapping)model was built for automatic identification of cabbages and *** the HSI(Hyper Spectral Imaging)Analyzer,the training pixels were used to calculate the average spectrum as the standard *** parameters of the SAM model,which had the best classification results with 3-point smoothing,zero-order derivative,and 6-degrees spectral angle,was determined to achieve the accurate identification of the background,weeds,and *** comparison,the SAM model can completely separate the plants from the soil background but not perfect for weeds to be separated from the *** conclusion,the SAM classification model with the HSI analyzer could completely distinguish weeds from background and cabbages.

关键词： hyperspectral imaging weed identification cabbage seedlings

Development of automatic and efficient immuno-separator of foodborne pathogenic bacteria using magnetophoresis and magnetic mixing

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International Journal of Agricultural and Biological Engineering 2019年第5期12卷 167-172页

作者： Yuhe Wang Gaozhe Cai Maohua Wang Jianhan Lin Key laboratory of Agricultural Information Acquisition Technology(Beijing) Ministry of Agriculture and Rural AffairsChina Agricultural UniversityBeijing 100083China Key laboratory of Modern precision agriculture System Integration Research Ministry of EducationChina Agricultural UniversityBeijing 100083China

In recent years,the outbreaks of foodborne diseases caused by pathogenic bacteria have made considerable economic losses and shown a threat to public *** key to prevent and control these diseases is fast screening of pathogenic bacteria,which is usually performed with three procedures:sample collection,bacteria separation and bacteria *** sample collection,the national standard methods are often *** bacteria detection,currently available methods such as Polymerase Chain Reaction and Enzyme Linked Immuno-Sorbent Assay are often *** bacteria separation,traditional methods such as filtration and centrifugation are not capable to specifically separate the target ***,food samples are very complicated and require efficient pretreatment for bacteria separation and concentration to achieve accurate and reliable *** conventional immune magnetic separation method can be used to specifically separate the bacteria,but it still cannot meet the requirements for food sample pretreatment due to very low concentration of target bacteria in ***,this study developed an automatic and efficient immuno-separator of foodborne bacteria based on magnetophoresis and magnetic mixing,and *** O157:H7 was used as research model.A magnetic mixer was applied to facilitate the immunoreaction between the immune magnetic nanoparticles and the target bacteria cells,and a magnetophoretic separation tubing was utilized for magnetophoretic separation of the magnetic *** the optimal mixing time of 20 min and the optimal flow rate of 50μL/min,the separation efficiency of *** O157:H7 could be more than 90%,showing that the developed immuno-separator is promising to be applied for efficient separation of foodborne bacteria and can be easily extended for separation of other biological targets by using their specific antibodies.

关键词： foodborne bacteria immuno-separator bacteria separation magnetophoresis magnetic mixing magnetic nanoparticles