Heilongjiang Province Institute of Meteorological Sciences, Harbin, China.
Innovation and Opening Laboratory of Regional Eco-Meteorology in Northeast, China Meteorological Administration, Harbin, China.
J Sci Food Agric. 2023 Jul;103(9):4573-4583. doi: 10.1002/jsfa.12570. Epub 2023 Apr 7.
Accurate and timely access to large-scale crop damage information provides an essential reference for responding to agricultural disaster prevention and mitigation needs and ensuring food production security. The present study aimed to reveal the new characteristics of low-temperature cold damage to maize in the context of climate warming. Heilongjiang, one of the provinces with the highest latitude, the most significant climate change and the largest maize production in China, was taken as the study area. We combined meteorological stations and MODIS remote sensing data to spatially identify the occurrence and intensity of cold damage to maize based on the growing season temperature distance level index, as well as to assess the extent of cold damage.
The main findings are: (i) The frequency and intensity range of cold damage in the growing season (May to September) in Heilongjiang Province from 1991 to 2020 against climate warming showed a decreasing trend. The average temperature from 1991 to 2000 was 17.777 °C, with seven occurrences of maize cold damage years, of which 5 years comprised widespread cold damage and 2 years comprised regional cold damage. The average temperature from 2000 to 2010 was 18.137 °C, with cold damage three times, of which 2 years comprised regional cold damage and 1 year comprised widespread cold damage. The average temperature from 2010 to 2020 was 18.130 °C, with one maize cold damage year occurring, which comprised regional cold damage. The frequency of maize chilling injury decreased significantly from 1991 to 2020, from 0.23 in 1991-2000 to 0.1 in 2000-2010 and, finally, to 0.03 in 2010-2020. (ii) The good consistency between MODIS_LST data and temperature data from meteorological stations suggests that MODIS_LST data can be used to build a temperature remote sensing estimation model for spatially extensive cold damage monitoring and intensity discrimination. (iii) Taking 2009 as an example of a large-scale cold damage year, the spatial discrimination of maize cold damage intensity shows that the spatial distribution of chilling injury intensity has no obvious geographical features. The intensity of cold damage was mainly mild cold damage. According to administrative regions, the scope of chilling injury was the largest in Mudanjiang City, Heihe City, and Jixi City, accounting for 91.56%, 86.25%, and 84.91%, respectively. The areas with the most extensive range of severe chilling injuries were the Great Khingan Mountains region, Heihe City, Mudanjiang City, Yichun City, and Jixi City.
In the context of climate warming, the frequency and intensity range of maize cold damage showed a decreasing trend from 1991 to 2020 in Heilongjiang Province. The results of cold damage identification based on MODIS_LST data are accurate and can improve the spatial accuracy. The results of the present study provide a reference and guidance for dealing with the occurrence and defence of spatially refined cold damage. © 2023 Society of Chemical Industry.
准确、及时地获取大规模作物损害信息,为应对农业防灾减灾需求、保障粮食生产安全提供了重要参考。本研究旨在揭示气候变暖背景下玉米低温冷害的新特征。黑龙江省是中国纬度最高、气候变化最显著、玉米产量最大的省份之一,被选为研究区域。我们结合气象站和 MODIS 遥感数据,基于生长季温度距离水平指数,对玉米低温冷害的发生和强度进行了空间识别,并评估了冷害的程度。
主要发现包括:(i)1991 年至 2020 年气候变暖背景下黑龙江省玉米生长季(5 月至 9 月)冷害的频率和强度范围呈下降趋势。1991 年至 2000 年的平均温度为 17.777°C,玉米冷害年有 7 次,其中 5 次为广泛冷害,2 次为区域冷害。2000 年至 2010 年的平均温度为 18.137°C,冷害发生了 3 次,其中 2 次为区域冷害,1 次为广泛冷害。2010 年至 2020 年的平均温度为 18.130°C,发生了一次玉米冷害,为区域冷害。1991 年至 2020 年,玉米冷害的频率显著下降,从 1991 年至 2000 年的 0.23 次下降到 2000 年至 2010 年的 0.1 次,最后到 2010 年至 2020 年的 0.03 次。(ii)MODIS_LST 数据与气象站温度数据具有良好的一致性,表明 MODIS_LST 数据可用于建立温度遥感估算模型,以进行广泛的冷害空间监测和强度判别。(iii)以 2009 年为例,对大范围冷害年份的玉米冷害强度进行了空间判别,结果表明冷害强度的空间分布没有明显的地域特征。冷害的强度主要为轻度冷害。按行政区划分,重度冷害的范围最大的是牡丹江市、黑河市和鸡西市,分别占 91.56%、86.25%和 84.91%。重度冷害范围最广的地区是大兴安岭地区、黑河市、牡丹江市、伊春市和鸡西市。
在气候变暖的背景下,1991 年至 2020 年黑龙江省玉米冷害的频率和强度范围呈下降趋势。基于 MODIS_LST 数据的冷害识别结果准确,可提高空间精度。本研究结果为精细化冷害时空发生规律的应对与防御提供了参考和指导。 © 2023 英国化学学会。