外銷主力作物領航產業技術研發與應用

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計畫名稱: 外銷主力作物領航產業技術研發與應用
計畫主持人: 吳玉婷
共同計畫主持人: 寧方俞;陳俊仁;謝明憲;官青杉;江明耀;胡智益;周國隆;唐佳惠;蔡憲宗;徐敏記;黃維廷;陳柱中;陳琦玲;楊小瑩;劉滄棽;林儒宏;黃玉如;羅士凱;邱明賜;林秀橤;劉秋芳;蕭孟衿;戴佳如;蘇彥碩;劉千如
計畫編號: 109農科-11.2.6-子-Z1
計畫主管機構: 行政院農業委員會
計畫執行機構: 行政院農業委員會農糧署
全程計畫年: 2020
關鍵字: 貯藏;鳳梨;外銷主力產業;外銷;機械;智能化管理;智慧農業;農業加值;生產履歷;冷鏈;省工;溯源農產品;智慧農業;溯源茶產業;果實品質;生長模式;毛豆;萵苣;影像識別;結球萵苣;storage;pineapple;Export main industry;Exportation;Machinery;intelligent management;Smart agriculture;value-added agriculture;production traceability;cold chain;Labor-saving;traceable agri-products;smart agriculture;traceable tea industry;fruit quality;cr
摘要: 結球萵苣溯源生產智能管理之研發 臺灣自2002年開始形成外銷萵苣產業,歷經十餘年發展,目前農企業遭遇契作田管理不易、環境資訊無法掌握、外銷稽核作業耗費大量人力、外銷市場侷限及生產管理技術未能現代化的困境。隨著農業資通訊技術發展,新興技術的導入可望協助產業升級,提升產值及競爭力,本計畫擬建構以作物模型的預報方法的萵苣智慧化生產架構,發展自動化害蟲監測技術形成萵苣害蟲監測網,開發圖像化萵苣蟲害識別並整合至蟲害管理知識服務系統,從生產面建立智慧化栽培模式。導入溯源紀錄輔助系統,透過地理資訊系統整合環境、農地、耕作者與田間操作,減少溯源紀錄人力負擔並強化完整度。同時建立結球萵苣智慧冷鏈貯運管理模組,開發智能化長程冷鏈保鮮技術,協助拓展外銷市場。  鳳梨智能生產及採後處理技術改進 為提升鳳梨產業升級,減輕農村勞力缺乏、解決果實品質差異化,並推動產業溯源資料建立,本計畫擬改善果園作業機械化、栽培管理及採收後處理等智能化,包括開發輕量化盛裝容器包括建立各 項生理指標速測法,強化產地溯源資訊,完成產地氣候、栽培管理與果肉色澤劣變等關係之研究,並開發果實清潔系統,提升果品品質,與建置果園生產回饋系統,瞭解運輸末端之環境變化,促進臺灣鳳梨產業升級,提升國際競爭力。 外銷結球萵苣生產管理及省工作業輔具導入 結球萵苣為臺灣第二大之外銷蔬菜,年平均外銷量超過1萬公噸。外銷產業雖歷經18年發展,但生產從種植至採收作業仍仰賴人力作業及憑經驗管理為主。面對產區人力老化及缺乏有經驗人員支持,已危及產業永續發展。因此導入省工輔助機械及智慧決策管理應用為本計畫目的。2020年計畫主要工作項目接續省工輔助機械2017-2019年度所建立之作畦施肥同步作業及應用二行式移植機及採收機之整套省工作業應用,優先建置產量預測系統之運算模式,再導入智慧決策管理之合理施肥推薦系統及病害發生風險預警系統之運算模式的建置與修正。預期2020底前完成將合理施肥推薦系統之運算模式以技術移轉予產業正式應用。 毛豆產業智慧科技研發與應用 本計畫目標為建立毛豆外銷專區智慧型農業作業體系,解決農業勞動力短缺問題 ,提升專區的科學化管理及經營效率,提升我國毛豆產品在國際市場的競爭力。其重要工作項目包含(1) 建立智慧型GPS曳引機及多功能管理機田間生產技術。 (2) 建立毛豆採收機GPS車載式及病蟲害影像監測系統。 (3) 將以上智慧型技術結合在 毛豆外銷專區旗山示範場域進行生產測試優化,並配合雲端農業APP系統進行數據分 析及智慧生產管理,以提升毛豆大農場智慧化生產管理。其預期效益包含(1) 建立智慧型GPS曳引機 及多功能管理機田間測試 及優化1-2項,達成毛豆外銷專區精準耕作,可大幅節省人力30%,降低生產成本達 30%,提升作業效率,並節省用水、肥料及農藥等成本。 (2) 建立毛豆採收機 GPS車載及病蟲害蟲影像監測系統計2項,提升毛豆產品外銷品質。(3) 建置毛豆智 慧型生產示範場域1項,生產安全優質的毛豆原料,提升產品價值,預計每年可創造 台灣毛豆產品外銷產值達25億5千萬元以上,維持銷日冠軍的佳績。 溯源茶產業與智能化管理發展計畫 本研究發展智慧管理工具及溯源系統協助田間生產與商品溯源。今年度初步建立茶園自動滴灌系統、農用噴藥無人機、UAV 搭載多光譜NDVI及高畫素相機等自動化工具之使用,並持續藉由自動感測裝置及物聯網(IOT)模組於各生產資訊點收集茶園露天環境參數。為建立專家決策系統,持續累積茶園土壤檢測及病蟲害監測資料,並持續修正青心烏龍及臺茶12號預測模式,於作物優質生產整合資訊平台後臺預設低海拔青心烏龍及臺茶12號生產管理參數,以利適時提供建議讓茶農在田間管理上更加準確與有效。Study on intelligent management for traceable lettuce production system The export lettuce industry has formed since 2002 and becomes one of the most important agricultural industry in winter time in Taiwan after more than ten years of development. However as the expension the lettuce industry, it's now facing to different problems including difficult mangement for agricultural enterprises with the contract fields, complex environmental information to be taken care for, labor intensive for export audit work, limitation of export market and un-modernized production management technology. Due to the tevelopment of agricultural information technology in recent years, the introduction of modern technologies is expected to accelerate the upgrading of this industry, enhancing the production value and competitiveness. This project aim to to improve the problem by 6-years period to fulfill the smart croping system by introducing  crop model forecasting  as smart production framework, constracting lettuce pest automatic monitoring trap to form regional monitoring network, developing AI based identification system and conting with knowledge management system. Also we introduce IoT, GIS and informaiton management system into the traceability recording system in the inductry to reduce the labor reliability.  At the meanwhile,  the establishment the lettuce cold chain storage management technique to help expand the export market. Intelligent production and optimized postharvest handling technology of pineapple The smart agricultural practice of pineapple industry aim at reducing the labor requirement, unifying the fruit quality, and enhancing the tractability of field practice. To achieve this goal, the improvement  of the agricultural mechanics, cultivation management and post-harvest treatment will be enhanced in to the pineapple industry in this project. The studies in this project are to establish the quick measurement of physiological indexes, to introduce smart items on tracing system of local product, to investigate the interactions among local weather, cultivation management and fruit quality .Also, the development of fruit cleaning system and orchard production feedback system to monitor the environmental change are included. Through upgrade the pineapple industry by smart agricultural techniques, the promotion of the global competitiveness of pineapple business of Taiwan is expected.   Introduction of Auxiliary Machinery to Reduce Labor Costs for Exported Iceberg Lettuce production Iceberg lettuce is the second largest vegetable for export in Taiwan, but the production operations from transplant to harvest still mainly relies on manual labor. In the recent decade, an aging workforce and lack of experienced labor has endangered the sustainable development of the industry. In order to alleviate the risk of production mismanagement and reduce the labor demand, this project has previously established labor- saving machinery, such as a fertilizer application in ridges by using a fertilizing and furrowing machine, and an automated transplanter and harvester. The task of this project in 2020 will focus on establishing smart decision making systems to recommend fertilization and predict growth periods and yield on a demonstration farm. By the end of 2020, it is expected that the smart system can recommend the appropriate amount and type of fertilizer according to the long-term weather forecast and soil condition data, so as to avoid the physiological disorders caused by improper fertilizer application or the waste of excessive fertilization. In addition, it will able to predict harvesting dates and yields, which can improve a farm’s precision production to meet market demand. Smart Technology Development and Application on Vegetable Soybean Industry The project objectives for vegetable soybean are to establish smart agricultural operation system on the export professional fields to address the agricultural labor shortages, improve our products in the international market competitiveness. The experimental procedures contains are 1) to establish smart GPS tractor and multi-function machine to product technology on large farms; 2) to establish GPS and video monitoring system on vegetable soybean harvester and a growth and disease- pest monitoring system of field; 3) to combine the above smart technologies in the Qishan Demonstration Site to optimize production testing, and cooperate with the cloud-side agricultural APP system to enhance the smart production management on large farms. The experimental expectant benefits are 1) to establish the smart tractor GPS system to product technology on large farms to reach precision farming. It can save 30% of manpower, reduce production costs by 30%, improve operational efficiency, and save water, fertilizer and pesticides and other costs, 2) to establish a soybean harvester GPS and video monitoring system, to enhance the quality of vegetable soybean product, 3) to build a smart management system on large farms for production safe and high quality of vegetable soybean, will reach more than 2.55 billion dollars a year, to enhance Taiwanese competitiveness in the international market. The Development Plan of Traceable Tea Industry and Intelligence Management In this study, we develop the intelligent management tools and traceable system to assist field production and traceable requirements management. This year, the tea plantation automatic drip irrigation system, agricultural spray drone, UAV equipped with multi-spectral NDVI and high-pixel camera and other automated tools were used. And the automatic sensing device and Internet of Things (IOT) module were used for informatizing the production records in the main tea plantations in Taiwan. In order to establish an expert decision-making system, we will continue to accumulate soil analysis, pest monitoring and pesticide residues in tea. In addition, we continue to correct the prediction model of Qingxin Oolong and TTES No.12, and preset low-altitude Qingxin Oolong in the background of crop production management information system. The recommendations will help to build a more accuracy and effective field management.
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