Chilling injury monitoring and intensity identification of dryland maize in Heilongjiang
Authors: Jiang Lanqi , Gong Lijuan , Jiang Lixia , Li Xiufen , Cheng Ming , Zhang Ximing 
Published: March 2023

AbstractBACKGROUNDAccurate 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.RESULTSThe 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.CONCLUSIONIn 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.