Development of biosensor monitoring technology and construction of production-marketing service system

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Project title

Code/計畫編號

110農科-8.3.2-子-C1

Translated Name/計畫中文名

生物感監測技術、產銷服務系統

Funding Organization/主管機關

Council of Agriculture,Executive Yuan

Co-Investigator(s)/共同執行人

劉滄棽(計畫主持人)
周國隆
黃政龍
林彥蓉
周承復
吳昭正
林金樹
林裕彬
鍾嘉綾
張耀聰
陳林祈
陳柱中
陳建銘
陳盈丞
蔡恕仁
林秀橤
歐陽盟
吳姿嫺
賴巧娟
劉偉名
徐培修
姚銘輝
歐陽彥杰
李濡夙
陳泰元
陳本翰
黃維廷
石憲宗
林達德
郭展宏
方煒
張廖伯勳
陳世芳
姚美吉
劉耿豪
張倚瓏
蔡宛育
陳祈男
劉力瑜
曹嘉惠
張翊庭
吳雅芳
胡智傑
呂椿棠
楊滿霞

Department/Unit

Taiwan Agricultural Research Institut,COA,Executive Yuan

Website

https://www.grb.gov.tw/search/planDetail?id=13918400

Year

2021

Start date/計畫起

01-01-2021

Expected Completion/計畫迄

31-12-2021

Co-Investigator(s)

Fan-Hua Nan
Yi-Zeng Hsieh
Shih-Syun Lin
Shyi-Chyi Cheng

Bugetid/研究經費

54656千元

ResearchField/研究領域

其他（農）

本計畫為結合農業試驗改良場所、經濟部工業研究院及大學院校共同研究之計畫，110年以整合生物感監測技術、建構產銷服務系統為目標，分別以農業無人機具具應用系統研究、大數據分析智慧管理、非破壞性檢測技術開發、AI影像分析支援專家系統開發等四大工作項目進行研發，檢討以往年度工作成果，並擴大應用目標，工作重點包括：(1)農業無人機具具應用系統研究：開發無人機（包含無人飛機以及地面載具）進行田間監測、施藥作業以及智慧化設備系統整合等作業，促使管理效率提升，。(2)大數據分析智慧管理：藉由田間大數據分析進行智慧化管理，以解決產銷服務問題及作物產量預警支援系統之開發，以提升農業資訊服務推播之準確度與即時性，及作物生理調控技術之自動化自動管理能力，開發目標包含資料田間IoT蒐集方法開發、使用者資訊分析、作物環控參數及控制研發等(3)非破壞性檢測技術開發：開發非破壞性檢測技術應用於農產品品質選別、生長栽培輔助以及農藥檢測作業上，包含整合高光譜成像技術於番石榴及印度棗等果品包裝流水線上及番茄健康種苗田間栽培作業中，以改善目前現有產業的檢測方法；以音波檢測技術開發判釋鳳梨釋迦果實後熟程度，取代人工按壓不耐貯運之軟果方法；開發微型多重光學檢測設備於小葉菜之農藥篩檢作業上。(4)AI影像分析支援專家系統：導入AI影像分析技術以輔助專家人工判讀工作，以提升作業能量、效率及準確度並降低作業成本，並提升產業支援服務及預警能力，提供服務支援能力以及作物逆境預警能力兩種應用，包含應用於作物病蟲害診斷辨識專家系統；應用於蝴蝶蘭DNA品種鑑定技術提高侵權品種性狀判定精準度及效率；判斷土壤營養源含量與專家肥力系統分析以快速提供建議作物追肥施肥方針；應用於種子活力檢測試驗提供傳統發芽試驗外另一預測該批種子於田間之表現之參考；應用於自動監測蜂蟹蟎密度，建構即時防治預警系統，減少農藥使用與蜂群損失；以熱紅外線影像預防柑橘日燒發生提升果實品質與產量。 This project is a joint research project combining agricultural experiment and improvement sites, the Industrial Research Institute of the Ministry of Economic Affairs, and universities and colleges. In 110 years, it aims at integrating biological sensing monitoring technology and constructing a production and marketing service system, and researches on the application system of agricultural drones. , Big data analysis and smart management, non-destructive detection technology development, AI image analysis support expert system development and other four major work projects to carry out research and development, review the work results of the past years, and expand the application goals. The focus of the work includes:(1)Research on the application system of agricultural UAV equipment: develop UAVs (including unmanned aircraft and ground vehicles) for field monitoring, pesticide application operations, and intelligent equipment system integration and other operations to promote management efficiency.(2)Big data analysis and smart management: Intelligent management is carried out by field big data analysis to solve production and sales service problems and the development of crop yield early warning support system to improve the accuracy and real-time of agricultural information service promotion, and crop physiology Automatic management capabilities of control technology, development goals include data field IoT collection method development, user information analysis, crop environmental control parameters and control research and development, etc.(3)Development of non-destructive testing technology: developing non-destructive testing technology for agricultural product quality selection, growth and cultivation assistance, and pesticide testing operations, including the integration of hyperspectral imaging technology on fruit packaging lines such as guava and Indian dates, and tomato health In the field cultivation of seedlings, to improve the current detection methods of the current industry; use the sound wave detection technology to develop and interpret the maturity of the pineapple custard apple fruit, replacing the method of manually pressing the soft fruit that is not resistant to storage and transportation; develop a miniature multiple optical detection equipment for small leaf vegetables The pesticide screening operation.(4)AI image analysis support expert system: Introduce AI image analysis technology to assist experts in manual interpretation work, to improve operating energy, efficiency and accuracy, and reduce operating costs, and to enhance industry support services and early warning capabilities, provide service support capabilities and crops Two applications of adversity early warning capabilities, including application to crop pests and diseases diagnosis and identification expert system; application of Phalaenopsis DNA variety identification technology to improve the accuracy and efficiency of infringing variety trait determination; determination of soil nutrient source content and expert fertility system analysis to quickly provide recommendations for crops Topdressing fertilization policy; applied to seed vigor testing to provide another reference for predicting the performance of the batch of seeds in the field in addition to traditional germination testing; used to automatically monitor the density of bee crab mites, construct an immediate warning system for prevention and control, and reduce pesticide use and bee colony loss ; Use thermal infrared imaging to prevent citrus sunburn and improve fruit quality and yield.

Keyword(s)

無人飛行載具
病蟲害整合管理
發光二極管
小黃薊馬
蜜蜂
蓮花
機器學習
薊馬族群預測模式
大數據分析
物聯網
聊天機器人模組
果實表面溫度
種子品質
電照
植物生理
洋桔梗
生產履歷農產品
病蟲害判別
熱影像
光周期
燈照
蓮葉受害監測
生物炭
蓮葉受害程度分級
預警監測
日燒
青花菜
無人機
產量
波段選擇
洋蔥
檢測系統
蓮花作物
UAV多光譜遙測資料
篩選系統
智能感測模組
知識圖譜
害蟲諮詢小幫手
預警模型
高光譜影像
專家系統
知識本體
柑橘
產期預測
智能害蟲監測
品質
生理病害
離子選擇電
Unmanned aircraft system
Integrated pest and disease management
LED
Scitothrips dorsalis Hood
Honey bee
Nelumbo nucifera
Machine learning
chilli thrips population model
big data anaytics
Internet of things
Chatbot module
fruit surface temperature
Seed qua

DSpace CRIS

Development of biosensor monitoring technology and construction of production-marketing service system

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