Background: Soft-shelled turtle iridovirus (STIV) is the causative agent of severe systemic diseases in cultured soft-shelled turtles (Trionyx sinensis). To our knowledge, the only molecular information available on STIV mainly concerns the highly conserved STIV major capsid protein. The complete sequence of the STIV genome is not yet available. Therefore, determining the genome sequence of STIV and providing a detailed bioinformatic analysis of its genome content and evolution status will facilitate further understanding of the taxonomic elements of STIV and the molecular mechanisms of reptile iridovirus pathogenesis.

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Large-scale, high-resolution mapping of crop patterns is useful for the assessment of food security and agricultural sustainability but is still limited. This study attempted to establish remote sensing-based crop classification models for specific cropping systems using the decision trees method and monitored the distribution of the major crop species using Sentinel-2 satellites (10 m) in 2017. The results showed that the cropping areas of maize, rice, and soybean on the Northeast China Plain were approximately 12.1, 6.2, and 7.4 million ha, respectively. The cropping areas of winter wheat and summer maize on the North China Plain were 13.4 and 16.9 million ha, respectively. The cropping areas of wheat, rice, and rape on the middle-lower Yangtze River plain were 2.2, 6.4 and 1.3 million ha, respectively. Estimated images agreed well with field survey data (average overall accuracy = 94%) and the national agricultural census data (R2 = 0.78). This indicated the applicability of the Sentinel-2 satellite data for large-scale, high-resolution crop mapping in China. We intend to update the crop mapping datasets annually and hope to guide the adjustment and optimization of the national agricultural structure.