棉花障碍型冷害风险评估

doi:10.6048/j.issn.1001-4330.2019.08.008

新疆农业科学 ›› 2019, Vol. 56 ›› Issue (8): 1438-1448.DOI: 10.6048/j.issn.1001-4330.2019.08.008

• 作物遗传育种·物质资源·分子生物学 • 上一篇下一篇

棉花障碍型冷害风险评估

温馨馨¹, 韩忠玲², 程勇翔¹, 王秀珍³

1.石河子大学生命科学学院,新疆石河子 832000;
2.石河子大学信息科学与技术学院,新疆石河子 832000;
3.杭州师范大学遥感与地球科学研究院,杭州 311121

收稿日期:2019-06-25 出版日期:2019-08-20 发布日期:2019-10-10
通信作者: 程勇翔(1980-),男,山东郓城人,副教授,研究生导师,研究方向为农业遥感与信息技术,(E-mail)chengyongxiang_613@163.com
作者简介:温馨馨(1998-),女,新疆昌吉人,本科,研究方向为生物技术,(E-mail)837732774@qq.com
基金资助:
长江中下游水稻主要气象灾害监测技术方法研究(2017YFD0300402-3)

Risk Assessment of Cotton Sterile-Type Chilling Injury

WEN Xin-xin¹, HAN Zhong-ling², CHENG Yong-xiang¹, WANG Xiu-zhen³

College of Life Sciences, Shihezi University, Shihezi Xinjiang 832000, China;
2. College of Information Science and Technology, Shihezi University, Shihezi Xinjiang 832000, China;
3. Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou 311121, China

Received:2019-06-25 Online:2019-08-20 Published:2019-10-10
Correspondence author: CHENG Yong-xiang(1980-),male,associate professor ,(E-mail)chengyongxiang_613@163.com
Supported by:
Supported by Study on Monitoring Techniques and Methods of Main Meteorological Disasters in Rice in the Middle and Lower Reaches of the Yangtze River(2017YFD0300402-3)

摘要/Abstract

摘要： 【目的】评估新疆棉花障碍型冷害精细化风险,为新疆棉花种植业规避冷害提供科学依据。【方法】以1951~2015年新疆66个农业气象站点逐日数据为基础,利用并分析MODLT1M中国1KM地表温度月合成产品2000~2016年每年9月LTN AVG数据资料,以日平均气温连续3 d≤20^oC为棉花障碍型冷害判定指标。根据已有的冷害风险评估指标概念模型,计算冷害强度与频率分指标。通过将次冷害强度和次冷害频率升尺度为年冷害强度和冷害年频率构建综合冷害风险指标,将原本松散的冷害频率和强度关系突显出来,依据二者之间的稳定函数关系,确定冷害年频率等级来对应冷害年强度等级,划分冷害风险指标各临界阈值。以地理因子归一化加合趋势面+温度趋势面校正的方法,准确推算新疆棉花冷害风险指标。紧密结合风险等级划分与风险指标推算结果,评估新疆棉花冷害风险。【结果】新疆棉花障碍型冷害发生风险北疆高于南疆和东疆,北疆西部沿天山一带棉花种植区冷害风险自西向东逐渐增加。模型模拟冷害风险指标值与站点实测计算值之间无明显差异,两者散点图线性拟合R²为0.97,结果准确。【结论】研究构建的评估方法能够实现对新疆棉花障碍型冷害风险的客观评价,所构建的方法论不仅适用于棉花,还可适用于其他作物冷害的风险评估。

关键词: 棉花; 障碍型冷害; 风险评估

Abstract: 【Objective】 To realize the fine risk assessment of obstacle chilling injury of cotton in Xinjiang in the hope of providing scientific basis for avoiding chilling injury of cotton in Xinjiang.【Method】 Based on the daily data of 66 agricultural meteorological stations in Xinjiang from 1951 to 2015, the LTN AVG data of MODLT1M China 1KM surface temperature synthetic products from 2000 to 2016 were analyzed and used, and the daily average temperature ≤20℃ for 3 consecutive days was used as the determination index of cotton obstacle chilling injury. Based on the existing conceptual model of chilling injury risk assessment index, the indices of chilling injury intensity and frequency were calculated. By increasing the intensity and frequency of secondary chilling damage to the annual chilling damage intensity and the annual frequency of chilling damage, the comprehensive cold damage risk index was constructed, and the relationship between the original loose chilling damage frequency and intensity was highlighted on the basis of the stability of the function relation between the two. By determining the annual frequency grade of cold damage to correspond to the intensity grade of cold damage year, the objective division of each critical threshold of cold damage risk index was realized. By using the method of geographic factor normalization plus trend surface and temperature trend surface correction, the risk index of cotton chilling injury in Xinjiang was calculated accurately. The risk grade classification and risk index calculation results were closely combined to realize the risk assessment of cotton chilling injury in Xinjiang.【Result】 The risk of obstructed chilling injury of cotton in Xinjiang was higher in northern Xinjiang than in southern Xinjiang and eastern Xinjiang, and increased gradually in western Xinjiang along the Tangshan Mountains. The results proved that there was no significant difference between the model simulation chilling injury risk index value and the measured calculated value of the site, and the linear fitting R² of the scatter diagram of the two was 0.97, so the research results were accurate. 【Conclusion】 The evaluation method constructed in this study can achieve objective evaluation of the risk of obstacle type chilling injury of cotton in Xinjiang, and the methodology constructed is applicable not only to cotton, but also to other crops' risk assessment of chilling injury.

Key words: cotton; sterile-type chilling injury; risk assessment

中图分类号:

S426
S421

温馨馨, 韩忠玲, 程勇翔, 王秀珍. 棉花障碍型冷害风险评估[J]. 新疆农业科学, 2019, 56(8): 1438-1448.

WEN Xin-xin, HAN Zhong-ling, CHENG Yong-xiang, WANG Xiu-zhen. Risk Assessment of Cotton Sterile-Type Chilling Injury[J]. Xinjiang Agricultural Sciences, 2019, 56(8): 1438-1448.

参考文献

[1] 张正文. 新疆棉花产业发展研究[D]. 新疆大学, 2013.
ZHANG Zheng-wen.(2013). Research on cotton industry development in Xinjiang [D]. Master Dissertation. Xinjiang University, Urumqi. (in Chinese)
[2] 李彦斌,程相儒,李党轩,等. 北疆垦区棉花低温冷害初步研究[J]. 农业灾害研究, 2012, 2(5): 11-13.
LI Yan-bin, CHENG Xiang-ru, LI Dang-xuan, et al. (2012). Preliminary research on chilling injury of cotton in reclamation area of northern Xinjiang [J]. Agricultural Disaster Research, 2(5): 11-13. (in Chinese)
[3] 宋艳玲,张强,董文杰. 气候变化对新疆地区棉花生产的影响[J]. 中国农业气象, 2004,(3): 15-20.
SONG Yan-ling, ZHANG Qiang, DONG Wen-jie. (2004). Effects of climate change on cotton production in Xinjiang [J]. China Agricultural Meteorology, (3): 15-20. (in Chinese)
[4] 傅玮东,李新建,姚艳丽. 新疆棉花生长中期低温冷害指标的初步研究[J]. 干旱区研究, 2007,(4): 495-498.
FU Wei-dong, LI Xin-jian, YAO Yan-li. (2007). Preliminary study on low temperature chilling injury index of middle growth stage of cotton in Xinjiang [J]. Arid Zone Research,( 4): 495-498. (in Chinese)
[5] 刘勇,张玲,杨明凤. 2016年新疆石河子垦区影响棉花产量的气象因子分析[J]. 中国棉花, 2018, 45(6): 40-42.
LIU Yong, ZHANG Ling, YANG Ming-feng. (2018). Analysis of meteorological factors affecting cotton yield in Shihezi reclamation area of Xinjiang in 2016 [J]. China Cotton, 45(6): 40-42. (in Chinese)
[6] 李文亮,张冬有,张丽娟. 黑龙江省气象灾害风险评估与区划[J]. 干旱区地理, 2009, 32(5): 754-760.
LI Wen-liang, ZHANG Dong-you, ZHANG Li-juan. (2009). Risk assessment and regionalization of meteorological disasters in Heilongjiang province [J]. Arid Land Geography, 32(5): 754-760. (in Chinese)
[7] 傅玮东. 终霜和春季低温冷害对新疆棉花播种期的影响[J]. 干旱区资源与环境, 2001,(2): 38-43.
FU Wei-dong. (2001). Effects of last frost and spring low temperature injury on sowing time of cotton in Xinjiang [J]. Journal of Arid Land Resources and Environment, (2): 38-43. (in Chinese)
[8] 何雨芩,胡雪琼,朱勇. 云南省近50年水稻抽扬期低温冷害演变特征分析[J]. 南京信息工程大学学报(自然科学版), 2018,10(2): 225-231.
HE Yu-qin, HU Xue-qiong, ZHU Yong. (2018). Analysis of evolution characteristics of chilling injury during rice pumping in Yun-nan province in recent 50 years [J]. Journal of Nanjing University of Information Science & Technology (Natural Science Ed.), 10(2): 225-231. (in Chinese)
[9] 何燕,李政,徐世宏,等. GIS支持下的广西早稻春季冷害区划研究[J]. 自然灾害学报, 2009, 18(5): 178-182.
HE Yan, LI Zheng, XU Shi-hong, et al. (2009). Study on spring chilling injury zoning of early rice in Guangxi supported by GIS [J]. Chinese Journal of Natural Disasters, 18(5): 178-182. (in Chinese)
[11] Cheng, Y. X. , Huang, J. F. , Han, Z. L. , Guo, J. P. , & Guo, R. F. (2013). Cold damage risk assessment of double cropping rice in Hunan, China. Journal of Integrative Agriculture, 12(2):352-363.
[12] 李景林,普宗朝,张山清,等. 近52年北疆气候变化对棉花种植气候适宜性分区的影响[J]. 棉花学报, 2015, 27(1): 22-30.
LI Jing-lin, PU Zong-chao, ZHANG Shan-qing, et al. (2015). Effects of climate change in northern Xinjiang on climatic suitability of cotton planting in recent 52 years [J]. Acta Cotton Sinica, 27(1): 22-30. (in Chinese)
[13] 张丽文,刘志雄,肖玮钰,等. RS和GIS支持下的全天候气温构建在湖北水稻低温冷害监测中的应用[J]. 湖北农业科学, 2018,10(2): 225-231.
ZHANG Li-wen, LIU Zhi-xiong, XIAO Wei-yu, et al. (2018). Application of all-weather temperature construction supported by RS and GIS in monitoring chilling injury of rice in Hubei Province [J]. Hubei Agricultural Sciences, 10(2): 225-231. (in Chinese)
[14] 王春乙,姚蓬娟,张继权,等. 长江中下游地区双季早稻冷害、热害综合风险评价[J]. 中国农业科学, 2016, 49(13): 2 469-2 483.
WANG Chun-yi, YAO Peng-juan, ZHANG Ji-quan, et al. (2016). Comprehensive risk assessment of chilling injury and heat damage of early rice in middle and lower reaches of Yangtze River [J]. Scientia Agricultura Sinica, 49(13): 2,469-2,483. (in Chinese)
[15] 陈凯奇,米娜. 辽宁省玉米低温冷害和霜冻灾害风险评估[J]. 气象与环境学报, 2016,32(1): 89-94.
CHEN Kai-qi, MI Na. (2016). Risk assessment of low temperature chilling injury and frost disaster of maize in Liaoning Province [J]. Journal of Meteorology and Environment, 32(1): 89-94. (in Chinese)
[16] 段晓凤,官景得,赵兔祥,等. 基于GIS的县级精细化气候适宜性区划及灾害风险区划[J]. 中国农学通报, 2016, 32(10): 125-131.
DUAN Xiao-feng, GUAN Jing-de, ZHAO Tu-xiang, et al. (2016). Gis-based fine climate suitability regionalization and disaster risk regionalization at county level [J]. Chinese Agricultural Science Bulletin, 32(10): 125-131. (in Chinese)
[17] 马树庆,袭祝香,王琪. 中国东北地区玉米低温冷害风险评估研究[J]. 自然灾害学报, 2003,(3): 137-141.
MA Shu-qing, XI Zhu-xiang, WANG Qi. (2003). Risk assessment of corn chilling in northeast China [J]. Journal of Natural Disasters, (3): 137-141. (in Chinese)
[18] 胡春丽,李辑,焦敏,等. 东北地区水稻障碍型低温冷害变化对区域气候增暖的响应[J]. 气象科技, 2015, 43(4): 744-749.
HU Chun-li, LI Ji, JIAO Min, et al. (2015). Response to regional climate warming caused by rice barrier chilling injury in northeast China [J]. Meteorological Science and Technology, 43(4): 744-749. (in Chinese)
[19] 陈思宁,柳芳,黎贞发,等. 基于不同发育期的日光温室黄瓜低温冷害风险评估研究[J]. 中国农业资源与区划, 2016,37(2): 154-160.
CHEN Si-ning, LIU Fang, LI Zhen-fa, et al. (2016). Risk assessment of cucumber chilling injury in solar greenhouse based on different growth stages [J]. Chinese Journal of Agricultural Resources and Regional Planning, 37(2): 154-160. (in Chinese)
[20] 张丽文. 基于GIS和遥感的东北地区水稻冷害风险区划与监测研究[D]. 浙江大学, 2013.
ZHANG Li-wen. (2013). Risk regionalization and monitoring of rice chilling injury in northeast China based on GIS and remote sensing [D]. PhD Dissertation. Zhejiang University, Hangzhou. (in Chinese)
[21] 李雨鸿,张微玮,李琳琳,等. 辽宁水稻低温冷害分布特征及危险性评估[J]. 大麦与谷类科学, 2018,35(5): 47-52.
LI Yu-hong, ZHANG Wei-wei, LI Lin-lin, et al. (2018). Distribution characteristics and risk assessment of chilling injury in rice in Liaoning Province [J]. Barley and Cereal Sciences, 35(5): 47-52. (in Chinese)
[22] 李楠,陈辰,张继波. 基于信息扩散理论的山东省日光温室番茄低温冷害风险评估[J]. 山东农业科学, 2016, 48(12): 124-128.
LI Nan, CHEN Chen, ZHANG Ji-bo. (2016). Risk assessment of tomato chilling injury in solar greenhouse in Shandong province based on information diffusion theory [J]. Shandong Agricultural Sciences, 48(12): 124-128. (in Chinese)
[23] 张丽娟,李文亮,张冬有. 基于信息扩散理论的气象灾害风险评估方法[J]. 地理科学, 2009, 29(2): 250-254.
ZHANG Li-juan, LI Wen-liang, ZHANG Dong-you. (2009). Meteorological disaster risk assessment method based on information diffusion theory [J]. Scientia Geographica Sinica, 29(2): 250-254. (in Chinese)
[24] 张茂松,张加云,吉文娟,等. 基于GIS的水稻低温冷害精细化风险区划--以玉溪市红塔区为例[J]. 西南农业学报, 2014,27(4): 1 723-1 728.
ZHANG Mao-song, ZHANG Jia-yun, JI Wen-juan, et al. (2014). Gis-based fine risk regionalization of rice chilling injury from low temperature: a case study of hongta district, Yuxi City [J]. Journal of Southwest Agricultural Sciences, 27(4): 1,723-1,728. (in Chinese)
[25] 王玲,吕新. 基于DEM的新疆地势起伏度分析[J]. 测绘科学, 2009, 34(1): 113-116.
WANG Ling, L Xin. (2009). DEM based analysis of topography in Xinjiang [J]. Science of Surveying and Mapping, 34(1): 113-116. (in Chinese)
[26] 张扬,楚新正,杨少敏,等. 近56 a新疆北部地区气候变化特征[J]. 干旱区研究, 2019, 36(1): 212-219.
ZHANG Yang, CHU Xin-zheng, YANG Shao-min, et al. (2019). Characteristics of climate change in northern Xinjiang [J]. Arid Zone Research, 36(1): 212-219. (in Chinese)
[27] 甄熙,张超,李云鹏. 作物低温冷害指标研究进展[J]. 北方农业学报, 2017, 45(2): 94-98.
ZHEN Xi, ZHANG Chao, LI Yun-peng. (2017). Research progress on chilling injury index of crops [J]. Journal of Northern Agriculture, 45(2): 94-98. (in Chinese)
[28] 张丽文,王秀珍,李秀芬. 基于综合赋权分析的东北水稻低温冷害风险评估及区划研究[J]. 自然灾害学报, 2014, 23(2): 137-146.
ZHANG Li-wen, WANG Xiu-zhen, LI Xiu-fen. (2014). Risk assessment and regionalization of rice chilling injury in northeast China based on comprehensive weight analysis [J]. Journal of Natural Disasters, 23(2): 137-146. (in Chinese)

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棉花障碍型冷害风险评估

Risk Assessment of Cotton Sterile-Type Chilling Injury

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