Fumigation is the most reliable method for pest control in a confined space. However, all current fumigants available are either highly toxic to mammalsharmful to the atmosphere. We provide a new technology, including novel fumigantsa rapid evaporating device. With its wide effectiveness to various insects, low toxicity to mammals, friendly to the environment, etc., our technology may attract users in custom quarantine, warehousing, home pest control, etc. We provide a novel fumigation technology that potentially satisfies the global demand of new fumigants.

We have displayed AChE on insect cell membrane for the detection of OPCB pesticide residue. Compared to GC-MSLC-MS analysis, the cost of our system is much lower with time-saving comparing with conventional biochemical detection method, the enzyme extractionpurification from flies is not necessary in our system. Therefore, this is a fast, accurateeconomical choice for residue screening.

This study built an automatic insect pest image identification system based on tiny Yolov3 deep learning model. By optimizing the tiny Yolov3 detection model, images of insect pests on scanned sticky paper can be automatically identified. The system achieves a testing accuracy of 0.93, 0.90 for whitefliesthrips respectively.

A microfluidic diffraction device is developed for determination of CTC/bacteria from human whole blood with a home-constructed laser beam system. We design the optical structuretransfer the structure to transparent plastic substrate. The plastic diffraction die is modified with antibodies of the target to combine a fluidic system as a microfluidic diffraction chip. When human whole blood with CTCs/bacteria flows through the chip, the number of cells/bacteria can be obtained directly with label-free. The devices has been applied in clinical diagnosis of oesophagealendometrial cancer.

Surface-enhanced Raman spectroscopy (SERS) is a useful analytical technique for detecting extremely small amounts of molecules. Herein, we designed a paper-based quasi-three-dimensional SERS substrate (P-SERS) that can provide potential to improve Raman analyses for food safety, pesticide poisoning, precision medicine, drug abuse and DNA/RNA testing. The sensitive, low-cost, flexible and disposable SERS substrate could be easily fabricated by physical deposition of gold nanoparticles array onto a filter paper. In this case, we are able to create non-continuous Au islands on the fiber surfaces, where the gaps between AuNPs can dramatically generate the high electric field to enhance Raman signal of target molecules.

By integration of professions including phytopathology, pesticides analysis, aquaticlivestock management, microbial fermentation, epidemiology,artificial intelligence, our interdisciplinary team jointly have developed microbial products for multi-industry applications including crop health care, circular agriculture, livestockaquaculture. The intelligent monitoring modelsmanagement technology for evaluating the efficacy of microbial products are implemented to provide key time pointdecision support for microbial products application,in turns to enhance the application efficacy. The developed microbial agentstechnology would greatly reduce the use of chemical pesticidesantibioticsenhance agricultural output valuemarket competitiveness.

(1) Image recognition3D positioning of the pest: Modularize the system for testing on the orchard. (2) High efficiency laser pest control scanning system: It was developed to be suitable for windlessbreezy environments. (3) Enhance the economic tracked vehicle for hillside field: Self-developed power designsteering control based on dynamic model,(4) Field UGV control platform: Based on the preciseaccurate positioning in field, when robot operates on the reference path which planned by map, it can do path trackingdynamically obstacle avoiding in real-time.

The sweet pepper cultivationplant protection robot developed includes three parts: the intelligent image identificationpositioning system of sweet pepper diseasesinsect pests is composed of YOLO4 deep learning modelimage 3D vision integration. It can perform disease detectionspatial positioning,guide the robotic arm spraying device to accurately spray the diseased. The automatic walking system can use GPS to plan the movement path of the plant protection robot in the field, search for plants infected with pestsdiseases,perform the tasks of pest control.

Here we developed a fastgreen process of micro-plasma system for three-dimensional porous nanomaterials on low-cost paper substrates. The characteristics are low-cost, flexible,high-stability. It has three major applications, including increasing Raman measument, the detection process can be used with portable Raman spectroscopy for fast sensing,it can quickly analyze pesticides, food, drugs, etc. In addition, it can be equipped with boron nitride for high hydrogen productionhigh pollution biodegradationother applications.

This project integrated with industrial foresight technologies, including UAV, artificial intelligenceimage recognition, to collect real-time images, apply algorithm in evaluation, link the technology of IOT (Internet of Things)environment sensing,use unmanned vehicle to conduct controlling work.

We develop the new neural network architecture to improve execution speedaccuracy. The result shows that our AI detection system can run on a microcomputer in real-time, meanwhile its accuracy 90. We put that microcomputer on a dronereturn the result to smartphone App in real-time.

This technology multiple research to integrates the developed production system of the "smart integrated production system". Using AI to identify pestsdiseases,identify the high temperature resistant varieties,developed Root temperature control system,using IOT to establish Big data. An adopted robot will be used to assist sprayingharvesting in the future.