基于热量指数的东北春玉米冷害指标

Indicators of Chilling Damage for Spring Maize Based on Heat Index in Northeast China

构建春玉米冷害指标是冷害研究的基础,对我国春玉米安全生产和品种布局具有重要参考意义。以我国东北三省春玉米为研究对象,以具有明确生物学意义的热量指数为春玉米冷害指示因子,利用气象资料、春玉米生育期资料和冷害灾情资料,计算春玉米不同生育阶段平均热量指数,建立春玉米冷害样本序列,基于K-S分布拟合检验和95%置信区间上限阈值的方法,厘定春玉米冷害指标阈值,构建我国东北春玉米不同生育阶段冷害指标,并采用独立的春玉米冷害灾情样本验证指标的合理性。研究结果表明:东北三省春玉米冷害指标在生殖生长和营养生长与生殖生长并进期热量指数的阈值较高,营养生长期略低;指标验证结果与历史灾情记录完全吻合的比率为80. 0%,完全吻合和相差1级的比率为100%,且各灾害程度验证得到的准确率均高于75%。

Chilling damage is one of the most destructive disasters for spring maize in Northeast China(Heilongjiang Province, Jilin Province, and Liaoning Province). Proper indicators of spring maize chilling damage are important for understanding the spatio-temporal distribution characteristics of disaster, dynamic monitoring, early warning, and conducting risk assessment. Therefore, it is of great scientific significance for the safe production and reasonable spatial planting of spring maize in China. Daily time series of air temperature during the past 55 years(1961 - 2015) at 82 meteorological stations, phenology at different developmental stages of spring maize from 1981 to 2013 at 61 agro-meteorological stations, and historical chilling damage records during the past 55 years(1961 - 2015) are jointly used to establish chilling damage indicators of spring maize at different developmental stages. The heat index with significant biological basis is selected as a factor, and its average at different developmental stages of spring maize is calculated based on three physiological temperatures. And then, 15 heat index sets of spring maize chilling damage samples collected from historical disaster records are built in the context of the combinations of five developmental stages of spring maize(seedling to clover, clover to jointing, jointing to blossom, blossom to milk, milk to physiological maturity) and three chilling damage levels(light,moderate,and severe). KolmogorovSmirnov(K-S) test method is used in checking the best distribution fitting functions of the heat index sets,and 15 normal distribution functions are established by comparing three fitting functions, including normal distribution,exponent distribution, and evenly distribution. Each critical threshold of spring maize chilling damage levels at different developmental stages is determined by using the upper limit of 95% confidence interval. The rationality of the spring maize chilling damage indicator is validated by using 25 independent samples. Results show that the verification based on the spring maize chilling damage level indicators is detected to be basically consistent with historical records, with 80% assessment being thoroughly consistent and all the errors of validation samples being within one level. Meanwhile, consistent rates of chilling damage indicators for three chilling damage levels are all above 75%.