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| Spatiotemporal Characteristics and the Prediction of Risk Areas for Wheat (Triticum aestivum) Fusarium Head Blight in Hebei Province Based on MaxEnt Model |
| TAO Bu1,*, QI Yong-Zhi1,*, ZHAO Xu-Sheng1, CAO Zhi-Yan1, ZHEN Wen-Chao2,** |
1 College of Plant Protection, Hebei Agricultural University, Baoding 071001, China;
2 College of Agronomy, Hebei Agricultural University/State Key Laboratory of North China Crop Improvement and Regulation/Key Laboratory of Regulation and Control of Crop Growth of Hebei, Baoding 071001, China |
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Abstract Fusarium head blight (FHB), a serious threat to wheat production, has become a worldwide problem affecting the sustainable development of wheat (Triticum aestivum). Since the middle of 1990s, the disease occurred from spots to large areas and become one of the main diseases of wheat in Hebei province, with an average annual occurrence area of 267 000 hm2 or more. In order to provide the basis for scientific prevention and control FHB, MaxEnt model was used to predict the risk area of the disease in Hebei province in this study. Z-score method was used to standardize the occurrence area and area ratio of FHB in Hebei province from 2003 to 2018, and the features in time and space of FHB occurrence were analyzed. Based on the distribution characteristics of FHB in Hebei and the data of environmental variables, MaxEnt model was used to predict the potential risk area of FHB in Hebei. The area under the curve (AUC) of receiver operating characteristic (ROC) was used to evaluate the accuracy of the prediction model. The occurrence and prevalence of FHB in Hebei had a certain periodicity and spatial correlation, and the AUC value of MaxEnt model was 0.816, which indicated that the predicted distribution area of FHB had a good fit with the actual distribution area. The high and middle risk areas of FHB accounted for 14.98% and 10.19% of the total area of the whole province, respectively, mainly concentrated in the middle and south of Hebei. Among them, 66 counties were high risk areas, including the south of Baoding, the middle and east of Shijiazhuang, Hengshui, the middle and East of Xingtai, and the middle and east of Handan. The results of environmental variables analysis showed that the mean temperature of the warmest quarter (bio 10), the max temperature of the warmest month (bio 5), the mean temperature of the coldest quarter (bio 11) and the minimum temperature of the coldest month (bio 6) had a greater impact on the potential distribution of FHB. Among them, the relative contribution rate of bio10 was the important, accounting for 67.9%, and its importance accounted for 22.2%. The high and middle risk areas of FHB in Hebei accounted for 25.17% of the total area of the whole province, mainly concentrated in the central and southern part of Hebei. The occurrence of the disease has a high risk in Hebei. The establishment of the FHB prediction model will provide the basis for disease prediction and effective prevention and control.
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Received: 24 February 2021
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Corresponding Authors:
** wenchao@hebau.edu.cn
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| About author:: * These authors contributed equally to this work |
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