陈超, 徐富贤, 庞艳梅, 李小兰, 郭晓艺. 西南区域水稻关键生育期界限温度起始期的预测研究[J]. 中国生态农业学报(中英文), 2019, 27(8): 1172-1182. DOI: 10.13930/j.cnki.cjea.180686
引用本文: 陈超, 徐富贤, 庞艳梅, 李小兰, 郭晓艺. 西南区域水稻关键生育期界限温度起始期的预测研究[J]. 中国生态农业学报(中英文), 2019, 27(8): 1172-1182. DOI: 10.13930/j.cnki.cjea.180686
CHEN Chao, XU Fuxian, PANG Yanmei, LI Xiaolan, GUO Xiaoyi. Prediction of threshold temperature start date for rice at critical development stages in Southwest China[J]. Chinese Journal of Eco-Agriculture, 2019, 27(8): 1172-1182. DOI: 10.13930/j.cnki.cjea.180686
Citation: CHEN Chao, XU Fuxian, PANG Yanmei, LI Xiaolan, GUO Xiaoyi. Prediction of threshold temperature start date for rice at critical development stages in Southwest China[J]. Chinese Journal of Eco-Agriculture, 2019, 27(8): 1172-1182. DOI: 10.13930/j.cnki.cjea.180686

西南区域水稻关键生育期界限温度起始期的预测研究

Prediction of threshold temperature start date for rice at critical development stages in Southwest China

  • 摘要: 保证作物安全生产是种植制度的根本要求,也是作物稳产、高产的基础。本文基于西南水稻种植区317个气象台站1961-2015年的日平均气温和最高气温资料,分析了近55年来该区域不同保证率下水稻安全播种期、水稻开花期高温热害和低温冷害的最早发生期,并建立了西南区域水稻各关键生育期界限温度起始期预测模型。预测结果表明:80%~95%保证率下,云南南部的水稻育秧安全播种期最早,平均在2月20日左右;云南北部、四川攀西南部和盆地中部、重庆大部和贵州部分地区在3月10日-4月10日;而其余大部地区在4月10日-5月20日。80%~95%保证率下中稻开花期高温热害主要发生在四川盆地、重庆、贵州北部和东南部,大部地区最早出现在7月15日-8月20日。80%~95%保证率下再生稻或晚稻开花期低温冷害最早出现在云南和贵州大部、四川攀西地区,平均在6月20日-7月15日;四川盆地西部、贵州东北部平均为8月1-20日;其余大部地区在8月20日-9月20日。基于纬度、经度和海拔高度建立的西南区域水稻各关键生育期界限温度起始期预测模型,简单实用,可为西南水稻安全生产、防灾减灾等提供理论依据。

     

    Abstract: Ensuring safe production is a fundamental requirement of the cropping system, being an important basis for stable and high yield of crops. Based on the daily average and maximum temperatures from 1961-2015 in 317 meteorological stations in the rice growing areas of southwestern China, the study analyzed safe sowing dates of rice under different guarantee rates (80%-95%) using the mean variance method. The earliest date of heat stress and chilling injury at rice flowering stage under different guarantee rates were analyzed too. A prediction model of the threshold temperature start date for rice at critical development stages in southwestern China was constructed using the stepwise regression method. At the 80%-95% guarantee rate, the earliest safe sowing date for rice was discovered in southern Yunnan, which was around February 20. The safe sowing dates in northern Yunnan, southwestern Sichuan, central Sichuan basin, most parts of Chongqing and parts of Guizhou were from March 10 to April 10. The safe sowing dates in the rest of southwestern China were from April 10 to May 20. At the 80%-95% guarantee rate, heat stress at flowering stage of middle-season rice occurred mainly in the Sichuan basin, Chongqing, northern and southeastern Guizhou, and the earliest occurrence dates were from July 15 to August 20. The earliest occurrence dates of chilling damage at ratooning or late rice flowering stage in most of Yunnan and Guizhou, and southwestern Sichuan were from June 20 to July 15. Meanwhile, the earliest occurrence dates of chilling damage in western Sichuan basin and northeastern Guizhou were from August 1 to August 20, and from August 20 to September 20 in the remaining areas. Based on the latitude, longitude and altitude, a model for predicting the threshold temperature initiation period for rice at critical development stages in southwestern China was established, which was simple and practical. In addition, using Hejiang of Sichuan and Meitan of Guizhou as the case study, the differences between the actual values and the simulated values of threshold temperature start date for rice were analyzed. The relative error between the actual values and the simulated values of threshold temperature start date for rice was less than 5.0%, which indicated that the model had a good simulation effect. In summary, the prediction of threshold temperature start date for rice at critical development stages can provide a theoretical basis for safe production, disaster prevention and mitigation options in rice production in southwestern China. On the one hand, according to the safe sowing period, the actual sowing period of rice can be adjusted in time, which is necessary to avoid hazards of meteorological disasters. On the other hand, the local major rice varieties can be selected through probabilistic decision-making, to ensure stable and high yield in rice production.

     

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