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Prediction of the potential distribution and analysis of the freezing injury risk of winter wheat on the Loess Plateau under climate change
Qing Liang, Xujing Yang, Yuheng Huang, Zhenwei Yang, Meichen Feng, Mingxing Qing, Chao Wang, Wude Yang, Zhigang Wang, Meijun Zhang, Lujie Xiao, Xiaoyan Song
2024, 23 (9): 2941-2954.   DOI: 10.1016/j.jia.2024.02.006
Abstract81)      PDF in ScienceDirect      
Determining the suitable areas for winter wheat under climate change and assessing the risk of freezing injury are crucial for the cultivation of winter wheat.  We used an optimized Maximum Entropy (MaxEnt) Model to predict the potential distribution of winter wheat in the current period (1970–2020) and the future period (2021–2100) under four shared socioeconomic pathway scenarios (SSPs).  We applied statistical downscaling methods to downscale future climate data, established a scientific and practical freezing injury index (FII) by considering the growth period of winter wheat, and analyzed the characteristics of abrupt changes in winter wheat freezing injury by using the Mann-Kendall (M-K) test.  The results showed that the prediction accuracy AUC value of the MaxEnt Model reached 0.976.  The minimum temperature in the coldest month, precipitation in the wettest season and annual precipitation were the main factors affecting the spatial distribution of winter wheat.  The total suitable area of winter wheat was approximately 4.40×107 ha in the current period.  In the 2070s, the moderately suitable areas had the greatest increase by 9.02×105 ha under SSP245 and the least increase by 6.53×105 ha under SSP370.  The centroid coordinates of the total suitable areas tended to move northward.  The potential risks of freezing injury in the high-latitude and -altitude areas of the Loess Plateau, China increased significantly.  The northern areas of Xinzhou in Shanxi Province, China suffered the most serious freezing injury, and the southern areas of the Loess Plateau suffered the least.  Environmental factors such as temperature, precipitation and geographical location had important impacts on the suitable area distribution and freezing injury risk of winter wheat.  In the future, greater attention should be paid to the northward boundaries of both the winter wheat planting areas and the areas of freezing injury risk to provide the early warning of freezing injury and implement corresponding management strategies.


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Rapid detection of the rice false smut fungus Ustilaginoidea virens by lateral flow strip‑based recombinase polymerase amplification assay
Jiacheng Xi, Sanlian Wan, Yue Li, Yuandi Xu, Jing Yang, Ting Zhang, Jiajia Chen, Zhengguang Zhang, Danyu Shen, Haifeng Zhang
2024, 23 (11): 3763-3773.   DOI: 10.1016/j.jia.2023.09.027
Abstract117)      PDF in ScienceDirect      

Rice false smut, caused by Ustilaginoidea virens, is a devastating disease that greatly reduces rice yield and quality.  However, controlling rice false smut disease is challenging due to the unique infection mode of Uvirens.  Therefore, there is a need for early diagnosis and monitoring techniques to prevent the spread of this disease.  Lateral flow strip-based recombinase polymerase amplification (LF-RPA) overcomes the limitations of current Uvirens detection technologies, which are time-consuming, require delicate equipment, and have a high false-positive rate.  In this study, we used a comparative genomics approach to identify Uv_3611, a specific gene of Uvirens, as the target for the LF-RPA assay.  The designed primers and probe efffectively detected the genomic DNA (gDNA) of Uvirens and demonstrated no cross-reactivity with related pathogens.  Under optimal conditions, the LF-RPA assay demonstrated a sensitivity of 10 pg of Uvirens gDNA.  Additionally, by incorporating a simplified PEG-NaOH method for plant DNA extraction, the LF-RPA assay enabled the detection of Uvirens in rice spikelets within 30 min, without the need for specialized equipment.  Furthermore, the LF-RPA assay successfully detected Uvirens in naturally infected rice and seed samples in the field.  Therefore, the LF-RPA assay is sensitive, efficient, and convenient, and could be developed as a kit for monitoring rice false smut disease in the field.

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