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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 盧虎生 | zh_TW |
dc.contributor.advisor | Huu-Sheng Lur | en |
dc.contributor.author | 吳均上 | zh_TW |
dc.contributor.author | Chun-Shang Wu | en |
dc.date.accessioned | 2023-05-05T17:34:31Z | - |
dc.date.available | 2023-11-10 | - |
dc.date.copyright | 2023-05-05 | - |
dc.date.issued | 2022 | - |
dc.date.submitted | 2022-11-22 | - |
dc.identifier.citation | 丁文彥、林家玉、黃秋蘭、江瑞拱。2013。水稻新品種臺東33號之育成。臺東區農業改良場研究彙報 23:1-16。
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Accessed May 2, 2022. 陳守泓、李炳和、姚銘輝、申雍。2006。臺灣地區年際異常氣象狀況對農業生產之影響。作物、環境與生物資訊 3 (4):307-316。 陳俊仁、姚銘輝、陳宣蘋、廖芳瑾。2014。糧食生產評估系統之建置:以水稻生產為例。台灣農業研究 63 (1):84-90。 陳素娥、黃振增、林孟輝、鄭隨和。2004。水稻桃園 3 號之育成。桃園區農業改良場研究彙報 56:1-17。 陳榮坤、林彥蓉、羅正宗。2012。水稻新品種臺南16號之育成。臺南區農業改良場研究彙報 60:1-12。 楊純明。2010。因應氣候變遷水資源短缺情境下之水稻田灌溉策略-論通氣式及乾濕交替式水稻栽培策略。作物、環境與生物資訊 7 (3):212-220。 劉麗飛。1999。第六章 缺水及鹽分對水稻生產之影響。出自 "環境與稻作生產",楊純明主編,pp. 87-103。臺中:臺灣省農業試驗所。 盧虎生、劉韻華、中央氣象局第三組農業氣象科。2006。臺灣優質水稻栽培之環境挑戰與因應措施。作物、環境與生物資訊 3 (4):297-306。 盧虎生、劉韻華。2006。臺灣優質水稻栽培之環境挑戰與因應措施。作物、環境與生物資訊 3 (4):297-306。 盧虎生。1999。第七章 溫度對水稻穀粒充實發育及稻米品質的影響。出自 "環境與稻作生產",楊純明主編,pp. 105-119。臺中:臺灣省農業試驗所。 賴明信、李長沛、曾清山、黃惠娟、陳治官、郭益全。2001。水稻台農71號 (益全香米) 的育成。中華農業研究 50 (2):1-12。 Bannayan M, Kobayashi K, Kim H-Y, Lieffering M, Okada M, Miura S (2005) Modeling the interactive effects of atmospheric CO2 and N on rice growth and yield. Field Crops Res 93: 237-251 Boonjung H, Fukai S (1996) Effects of soil water deficit at different growth stages on rice growth and yield under upland conditions. 2. 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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/87111 | - |
dc.description.abstract | 近年來,由於全球氣候變遷,水稻的生產面臨新的挑戰。水稻生育期間遭逢極端高、低溫或缺水等逆境,可能導致作物產生不可逆的傷害,而使得最終產量減少,造成農民的損失。因此,水稻生產對於氣候狀況的及早應變越來越重要。本研究搜尋品種育成文獻,計算出五水稻品種臺稉9號、臺南11號、臺南16號、桃園3號以及臺農71號的DSSAT品種參數。以2010年至2020年農業試驗所氣象站歷史每日氣象資料,使用DSSAT作物模式模擬五水稻品種的生長發育情形與最終產量,進而建構出各品種的產量資料庫,用於產量預警。
本研究將產量預警分為溫度預警 (不缺水情境) 和雨量預警 (缺水情境)。其中,溫度預警 (不缺水情境) 以DSSAT作物模式模擬農業試驗所十年間每日作為插秧日的生長度日與最終產量,得出五水稻品種的產量資料庫。實際田間種植的每日生長度日,和產量資料庫內的每日生長度日進行比對獲得模擬產量。若減產達20%,便發出預警。雨量預警 (缺水情境) 以DSSAT作物模式模擬農業試驗所十年間每日作為插秧日的生長度日、乾旱逆境指標總和與最終產量,得出五水稻品種產量的線性迴歸關係式。實際田間種植的氣象站資料逐日匯入DSSAT作物模式得出數值,代入線性迴歸關係式獲得模擬產量。若減產達20%,便發出預警。 分品種的產量預警,能讓農民即時得知極端的氣候變化可能導致的減產風險,提供農民作為栽培管理的參考,以減少損失。 | zh_TW |
dc.description.abstract | In recent years, rice production has faced new challenges due to global climate change. Stress such as extreme heat, cold, or water shortage during rice growth may lead to irreversible damage to crops, resulting in reduced final yields and losses to farmers. Therefore, rice production is increasingly important for early response to climatic conditions. In this study, we searched the literature on variety breeding and calculated the DSSAT variety parameters of five rice varieties: Taiken 9, Tainan 11, Tainan 16, Taoyuan 3, and Tainung 71. Based on the historical daily meteorological data of the weather station of the Taiwan Agricultural Research Institute from 2010 to 2020, the DSSAT crop model was used to simulate the growth and development of five rice varieties and the final yield, and then the yield database of each variety was constructed for early warning.
In this study, the yield warning was divided into temperature warning (no water shortage scenario) and rainfall warning (water shortage scenario). Between them, the temperature warning (no water shortage scenario) used the DSSAT crop model to simulate the growing degree days and the final yield of every day as the day of planting date for ten years at the Taiwan Agricultural Research Institute. The yield database of five rice varieties was obtained. Daily growing degree days in the field were compared with those in the database to obtain the simulated yield. If the production was reduced by 20%, an early warning was issued. Rainfall warning (water shortage scenario) used the DSSAT crop model to simulate the growing degree days, the sum of water stress indicators, and the final yield of every day as the day of planting date for ten years at the Taiwan Agricultural Experiment Institute. The yield of five rice varieties was obtained from the linear regression models. The weather station data in the field was imported into the DSSAT crop model daily to obtain the numerical values, and the simulated yield was obtained by substituting it into the linear regression model. If the production was reduced by 20%, an early warning was issued. Yield early warning by variety could allow farmers to immediately know the risk of production reduction that might be caused by extreme climate change and provide farmers with a reference for cultivation management to reduce losses. | en |
dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-05-05T17:34:31Z No. of bitstreams: 0 | en |
dc.description.provenance | Made available in DSpace on 2023-05-05T17:34:31Z (GMT). No. of bitstreams: 0 | en |
dc.description.tableofcontents | 誌謝 i
中文摘要 ii ABSTRACT iii 目錄 v 圖目錄 viii 表目錄 ix 縮寫字對照表 x 第一章 前言 1 第二章 文獻回顧 2 2.1 全球氣候變遷 2 2.2 溫度與缺水逆境 2 2.2.1 溫度逆境 2 2.2.2 缺水 (乾旱) 逆境 3 2.3 全球氣候變遷對水稻種植的影響 3 2.4 災害預警 4 2.5 作物模式 4 第三章 材料與方法 6 3.1 作物設定 8 3.1.1 水稻品種 8 3.1.2 DSSAT品種參數 9 3.1.3 DSSAT品種參數驗證 13 3.2 環境設定 13 3.2.1 氣象 13 3.2.2 DSSAT各項設定 13 3.3 DSSAT產量預警資料庫建置 14 3.4 氣象站氣象資料處理 14 3.5 氣象檔模板 15 3.6 產量預警──溫度預警 (不缺水情境) 15 3.7 產量預警──雨量預警 (缺水情境) 16 第四章 結果 20 4.1 作物設定 20 4.1.1 水稻品種 20 4.1.2 DSSAT品種參數 20 4.1.3 DSSAT品種參數驗證 21 4.2 DSSAT產量預警資料庫建置 23 4.3 產量預警──溫度預警(不缺水情境) 23 4.3.1 臺稉9號的溫度預警 23 4.3.2 臺南11號的溫度預警 24 4.3.3 臺南16號的溫度預警 25 4.3.4 桃園3號的溫度預警 26 4.3.5 臺農71號的溫度預警 26 4.4 產量預警──雨量預警 (缺水情境) 27 4.4.1 臺稉9號的雨量預警 28 4.4.2 臺南11號的雨量預警 39 4.4.3 臺南16號的雨量預警 31 4.4.4 桃園3號的雨量預警 32 4.4.5 臺農71號的雨量預警 34 第五章 討論 36 5.1 DSSAT品種參數設定 36 5.2 產量預警──溫度預警 (不缺水情境) 37 5.3 產量預警──雨量預警 (缺水情境) 39 5.4 日射量 41 5.5 產量預警的調適策略 41 5.6 增產狀況的因應 42 第六章 結論 43 參考文獻 45 附錄 50 | - |
dc.language.iso | zh_TW | - |
dc.title | 設定DSSAT水稻品種參數並建立溫度與缺水之產量預警模型 | zh_TW |
dc.title | Set the DSSAT Rice Genetic Parameters and Establish Models for Temperature and Water Shortage Warnings | en |
dc.type | Thesis | - |
dc.date.schoolyear | 111-1 | - |
dc.description.degree | 碩士 | - |
dc.contributor.coadvisor | 劉力瑜 | zh_TW |
dc.contributor.coadvisor | Li-yu Daisy Liu | en |
dc.contributor.oralexamcommittee | 吳志文;姚銘輝;林泰佑 | zh_TW |
dc.contributor.oralexamcommittee | Chih-Wen Wu;Ming-Hwi Yao;Tai-Yu Lin | en |
dc.subject.keyword | 氣候變遷,水稻,DSSAT,作物模式,品種參數,產量,預警, | zh_TW |
dc.subject.keyword | climate change,rice,DSSAT,crop model,variety parameters,yield,early warning, | en |
dc.relation.page | 57 | - |
dc.identifier.doi | 10.6342/NTU202210067 | - |
dc.rights.note | 未授權 | - |
dc.date.accepted | 2022-11-23 | - |
dc.contributor.author-college | 生物資源暨農學院 | - |
dc.contributor.author-dept | 農藝學系 | - |
顯示於系所單位: | 農藝學系 |
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