請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/704
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 羅敏輝(Min-Hui Lo) | |
dc.contributor.author | Yu-Lien Chen | en |
dc.contributor.author | 陳玉蓮 | zh_TW |
dc.date.accessioned | 2021-05-11T04:59:51Z | - |
dc.date.available | 2019-08-06 | |
dc.date.available | 2021-05-11T04:59:51Z | - |
dc.date.copyright | 2019-08-06 | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019-08-04 | |
dc.identifier.citation | Ashardionoa, F and M. Cassim. 2014. “Climate Change Adaptation for Agro-Forestry Industries: Sustainability Challenges in Uji Tea Cultivation.” Procedia Environmental Sciences 20: 823-831.
Barasuriya, J. 1999. “Shoot population density and shoot weight of clonal tea (Camellia sinensis) at different altitudes in Sri Lanka.” European Journal of Agronomy 11: 123-130. Cannell M. G. R. and R. I. Smith. 1983. “Thermal Time, Chill Days and Prediction of Budburst in Picea sitchensis.” Journal of Applied Ecology 20(3): 951-963. Ceglar, A., R. van der Wijngaart, A. de Wit, R. Lecerf, H. Boogaard, L. Seguini, M. van den Berg, A. Toreti, M. Zampieri, D. Fumagalli, and B. Baruth. 2018. “Improving WOFOST model to simulate winter wheat phenology in Europe: Evaluation and effects on yield.” Agricultural Systems. https://doi.org/10.1016/j.agsy.2018.05.002 Chen, C. S., NOW News, April 23, 2018. https://www.nownews.com/news/20180423/2740953 (in traditional Chinese; translated by the author). Chen, X., M. L. Lin, I. Z. Chen, and X. G. Zeng. 1991. “Investigation of the Influence of Climate Factors on the Growth Period and Tea Quality of Tea Cultivar Chingshin-Oolong.” Reports on the Studies and Utilization of Agro-Climate Resources in Taiwan Area:1-22 (in traditional Chinese; translated by the author). (陳玄、林木連、陳右人、曾信光,1991,〈氣候因子對青心烏龍種茶樹生長週期與茶菁品質之影響調查〉。《臺灣地區農業氣象災害調查與資源應用研究報告專輯》:1-22。) Chou, J., W. T. Chen, M. H. Lo, M. A. Li, H. X. Xu, Z. C. Hong, Z. H. Zou, M. M. Lu, Z. W. Hong, Z. D. Chen, and Z. Z. Zheng. 2017. Climate Change in Taiwan: Scientific Report 2017 -- Volume 1: Physical Phenomena and Mechanisms: 383-508 (in traditional Chinese). (周佳、陳維婷、羅敏輝、李明安、許晃雄、洪志誠、鄒治華、盧孟明、洪致文、陳正達、鄭兆尊,2017,《臺灣氣候變遷科學報告。第一冊:物理現象與機制》:383-508。) Collier, N., F. M. Hoffman, D. M. Lawrence, G. Keppel-Aleks, C. D. Koven, W. J. Riley, M. Mu, and J. T. Randerson. 2018. “The International Land Model Benchmarking (ILAMB) system: design, theory, and implementation.” Journal of Advances in Modeling Earth Systems 10: 2731-2754. Duncan, J. M. A., S. D. Saikia, N. Gupta and E. M. Biggs. 2016. “Observing climate impacts on tea yield in Assam, India.” Applied Geography 77: 64-71. Dutta, R. 2013. “Monitoring green leaf tea quality parameters of different TV clones grown in northeast India using satellite data.” Food Chemistry 139: 689-694. Dutta, R., A. Stein, and Bhagat R.M. 2011. “Integrating satellite images and spectroscopy to measuring green and black tea quality.” Food Chemistry 127: 866-874. FAO, Food and Agriculture Organization of the United Nations. http://www.fao.org/faostat/en/#compare Franch B., E. F. Vermote, I. Becker-Reshef, M. Claverie, J. Huang, C. Justice and J. A. Sobrino. 2015. “Improving the timeliness of winter wheat production forecast in the United States of America, Ukraine and China using MODIS data NCAR Growing Degree Day information.” Remote Sensing of Environment 161: 131-148. Gordon R. and A. Bootsma. 1993. “Analyses of growing degree-days for agriculture in Atlantic Canada.” Climate Research 3: 169-176. Gunathilaka, R. P. D., J. C. R. Smart, and C. M. Fleming. 2017. “The impact of changing climate on perennial crops: the case of tea production in Sri Lanka.”Climatic Change 140: 577–592. Iizumi, T., Y. Shin, W. Kim, M. Kim, and J. Choi. 2018. “Global crop yield forecasting using seasonal climate information from a multi-model ensemble.” Climate Services 11: 13-23. Japan Meteorological Agency, 1996. “New Flowering Forecast of Cherry Blossom.” Japan Meteorological Agency Commentary Material No. 24. (in Japanese; translated by the author). (日本気象庁,1996。〈新しいサクラの開花予想〉。《気象庁解説資料第24號》。) Li, X.., L. Zhang, G. J. Ahammed, Z. X. Li, J. P. Wei, C. Shen, P. Yan, L. P. Zhang, and W. Y. Han. 2017. “Stimulation in primary and secondary metabolism by elevated carbon dioxide alters green tea quality in Camellia sinensis L.” Scientific Reports 7(1):7937. Lin, Y. H., C. Y. Hu, C. H. Chang, C. N. Lai, I. Z. Chen. 2016. “Establishing a Prediction Model of Tea Harvest Date.” Taiwan Tea Research Bulletin 35:1-20 (in traditional Chinese). (林義豪、胡智益、張振厚、賴正南、陳右人,2016,〈茶樹產期預測模式之建構〉。《臺灣茶業研究彙報》35:1-20。) Liu, C. M., 2015. Global Environmental Change (in traditional Chinese). Lou, W. P., S. L. Sun, L. H. Wu, and K. Sun. 2015. “Effects of climate change on the economic output of the Longjing-43 tea tree, 1972–2013.” International Journal of Biometeorology 59: 593–603. Mäkinen, H., J. Kaseva, M. Trnka, J. Balek, K.C. Kersebaum, C. Nendel, A. Gobin, J. E. Olesen, M. Bindi, R. Ferrise, M. Moriondo, A. Rodríguez, M. Ruiz-Ramos, J. Takáč, P. Bezák, D. Ventrella, F. Ruget, G. Capellades, and H. Kahiluoto. 2018. “Sensitivity of European wheat to extreme weather.” Field Crops Research 222: 209-217. McMaster, G. S. and W. W. Wilhelm. 1997. “Growing Degree-Days: One Equation, Two Interpretations.” Agricultural and Forest Meteorology 87: 291-300. Othieno, C. O., W. Stephens, and M. K. V. Carr. 1992. “Yield variability at the Tea Research Foundation of Kenya.” Agricultural and Forest Meteorology 61: 237-252. Owuor, P. O., F. N. Wachira, and W. K. Ngetich. 2010. “Influence of region of production on relative clonal plain tea quality parameters in Kenya.” Food Chemistry 119: 1168-1174. Perry K. B., S. M. Blankenship and C. R. Unrath. 1987. “Predicting harvest date of delicious and golden delicious apple using heat unit accumulation.” Agriculture and Forest Meteorology 39: 81-88. Samarasinghe, G. B. 2003. “Growth and yields of Sri Lanka's major crops interpreted from public domain satellites.” Agricultural Water Management 58: 145-157. Squire, G. R., S. M. O. Obaga, and C. O. Othieno. 1993. “Altitude, temperature and shoot production of tea in the Kenyan Highlands.” Experimental Agriculture 29(1): 107-120. Toreti, A., A. Maiorano, G. de Sanctis, H. Webber, A. C. Ruane, D. Fumagalli, A. Ceglar, S. Niemeyer, and M. Zampieri. 2018. “Using reanalysis in crop monitoring and forecasting systems.” Agricultural Systems. https://doi.org/10.1016/j.agsy.2018.07.001 TRES. 1987. Lectures on Technical Training in Tea Industry: 281-289. Taoyuan County: TRES. TRES. 2016. Introduction to Tea Industry: 3-2 Environment for Tea Cultivation. Tea Research and Extension Station. https://www.youtube.com/watch?v=0SaWi1M5j14&feature=youtu.be (in traditional Chinese; translated by the author). (茶業改良場,2016。《茶業入門篇:3-2茶樹的栽培環境》。) Wang, J. Y. 1960. “A Critique of the Heat Unit Approach to Plant Response Studies.” Ecology 41(4): 785-790. Wu, G. Y. 2003. “Current Circumstances and Prospects of Taiwan Tea Industry.” Agricultural Administration and Circumstances 128. Council of Agriculture, Executive Yuan, R.O.C. https://www.coa.gov.tw/ws.php?id=4354 (in traditional Chinese; translated by the author). Yang, S. S., J. Logan, and D. L. Coffey. 1995. “Mathematical formulae for calculating the base temperature for growing degree days.” Agricultural and Forest Meteorology 74: 61-74. Zheng, C. W., Y. X. Liao, and X. Y. Peng. UDN Video, January 24, 2016. https://video.udn.com/news/431723?fbclid=IwAR0sXw0Bym8ZCymMTNKVP39Tz3VYqhrps0JjcegMQ9gJQUk19qKUT5A59W4 (in traditional Chinese; translated by the author). | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/handle/123456789/704 | - |
dc.description.abstract | 臺灣茶產業的韌性議題在面對氣候變遷的洪流是刻不容緩,因此亟需「最適茶採收等時線圖」的建立。本研究採取歷史悠久並廣受運用的生長度日積溫模型,作為茶採收時間的視覺性評估之方法。在獲得了茶業改良場的茶葉相關紀錄與臺灣氣候變遷推估資訊平台的氣溫資料後,參考日本櫻花前線預測的資料視覺化策略,獲得「最適茶採收等時線圖」的結果。氣候變遷的氣溫上升效應對於茶採收產生了效期縮短的影響。最後,本研究提供了一種以茶園管理為目標的視覺化途徑;倘若後續的資料搜集、記錄和積溫模型優化可被妥善執行,本研究途徑將可被應用、推廣至常民生活之中。 | zh_TW |
dc.description.abstract | Climate change is adversely affecting the resilience of the tea industry, which is why the establishment of Optimal Tea HArvest Isochrone Maps (OTHAIMs) is needed. In this study, we categorize tea growth into three dimensions: yield, quality, and timing. And we provide insights into the trend of tea harvest in Taiwan in the future when the scenario of business-as-usual is to be expected. The profound and well-cited Growing Degree-Day (GDD) model is utilized in this study to evaluate the visualization of the timing of tea in Taiwan. Using data from the Tea Research and Extension Station (TRES) and the Taiwan Climate Change Projection and Information Platform (TCCIP), the outcomes of OTHAIMs are acquired with pruning date geneses in analogy with Sakura Zensen, cherry blossom blooming frontline maps, from Japan. Results indicate that the warming of climate change thus results in the shortened durations of tea harvest. In conclusion, this study provides a visualization approach for the government and the academia for further investigation of tea harvest and management, while extensive records of tea data and optimization of GDD model afterward may help this approach be put into application. | en |
dc.description.provenance | Made available in DSpace on 2021-05-11T04:59:51Z (GMT). No. of bitstreams: 1 ntu-108-R06247010-1.pdf: 7324960 bytes, checksum: f44f4764cae225bd54a70ce9e71b5e6e (MD5) Previous issue date: 2019 | en |
dc.description.tableofcontents | 口試委員會審定書 i
誌謝 ii 摘要 iii Abstract iv List of Contents v List of Figures vii List of Tables viii List of Appendixes ix 1 Introduction 1 1.1 Tea as An Essential Economic Crop 1 1.2 The Three Dimensions in Tea Growth: Yield, Quality, and Timing 2 1.3 The Well-known and Widespread Formula: Growing Degree-Day 3 1.4 Climate Change as An Adversity for Tea Growth 3 1.5 The Question: Climate Change v.s. Harvest Timing of Tea 4 2 Methodology 7 2.1 Methods 7 2.1.1 Growing Degree-Day (GDD) 8 2.1.2 Pruning Date Genesis 8 2.2 Materials 9 2.2.1 Tea Data 9 2.2.2 Temperature Data 10 3 Results 12 3.1 The Story Demonstrated in the Data 12 3.2 From the Past to the Future 14 3.3 When the Hypothesis Meets the Reality 14 4 Discussion 16 4.1 Conclusion 19 4.2 Limitation 20 4.2.1 Scarcity of Tea Data 20 4.2.2 Uncertainty of GDD formula 20 4.3 Future Work 21 4.3.1 Extensive Collection of Tea Data 21 4.3.2 Optimization of GDD model 22 4.4 Application 22 References 24 Figures 30 Tables 40 Appendixes 50 | |
dc.language.iso | en | |
dc.title | 氣候變遷下臺灣包種春茶累積溫量的適採期地圖化 | zh_TW |
dc.title | Mapping the Growing-Degree-Day of the Optimal Harvest Timing of Spring Pouchong Tea in Taiwan under Climate Change | en |
dc.date.schoolyear | 107-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 林博雄,陳右人,莊振義,黃倬英 | |
dc.subject.keyword | 茶,臺灣地區暖化現象,最適茶採收等時線圖,生長度日積溫模型, | zh_TW |
dc.subject.keyword | Camellia sinensis (L.) O. Kuntze,reginal warming in Taiwan,Optimal Tea HArvest Isochrone Maps (OTHAIMs),heat accumulation unit, | en |
dc.relation.page | 68 | |
dc.identifier.doi | 10.6342/NTU201902084 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2019-08-05 | |
dc.contributor.author-college | 理學院 | zh_TW |
dc.contributor.author-dept | 氣候變遷與永續發展國際學位學程 | zh_TW |
顯示於系所單位: | 氣候變遷與永續發展國際學位學程(含碩士班、博士班) |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-108-1.pdf | 7.15 MB | Adobe PDF | 檢視/開啟 |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。