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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/87111
標題: | 設定DSSAT水稻品種參數並建立溫度與缺水之產量預警模型 Set the DSSAT Rice Genetic Parameters and Establish Models for Temperature and Water Shortage Warnings |
作者: | 吳均上 Chun-Shang Wu |
指導教授: | 盧虎生 Huu-Sheng Lur |
共同指導教授: | 劉力瑜 Li-yu Daisy Liu |
關鍵字: | 氣候變遷,水稻,DSSAT,作物模式,品種參數,產量,預警, climate change,rice,DSSAT,crop model,variety parameters,yield,early warning, |
出版年 : | 2022 |
學位: | 碩士 |
摘要: | 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。 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. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/87111 |
DOI: | 10.6342/NTU202210067 |
全文授權: | 未授權 |
顯示於系所單位: | 農藝學系 |
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