Noxious plants pose a significant threat to human and livestock health, as well as to the safety of agricultural and forestry ecosystems. Accurate and rapid identification of these plants is crucial for risk prevention. This paper explores for the first time the development and application of a rapid detection technology for noxious plants based on a novel isothermal amplification technique. We targeted the seeds, leaves, and grain impurities of four major noxious weeds: Amaranthus palmeri, the A.tuberculatus complex, Rhaponticum repens, and Euphrosyne xanthiifolia, we designed and screened primers and probes suitable for this isothermal amplification method, determined their limit of detection, optimized the genomic DNA extraction methods, and verified the method. We developed genomic DNA extraction methods for single tissue components of plant seeds and leaves, as well as for mixed tissue components. Ultimately, we established standardized detection protocols for different tissue forms of each species, significantly enhancing detection efficiency. This study enables the detection positive samples in seeds or leaves within 10 to 15 minutes and positive samples from mixtures within 12 to 18 minutes. The entire process, from sample collection, genomic DNA preparation to reaction completion, takes approximately 35 minutes. This detection technology, which marks the first development of an isothermal amplification-based method for noxious plants, meets the needs for on-site rapid testing, aiding in the timely identification of risks and the implementation of corresponding prevention and control measures.

The impact of invasive alien species (IAS) on nature and society is increasing globally. It is crucial to utilize information systems for evidence-based management, enabling the assessment and supporting survey and control actions. However, the lack of accessible and comprehensive baseline IAS data often impedes the ability to prioritize and allocate resources efficiently. Despite the increased public awareness of biological invasions in China over the past decades, the critical importance of data requirements has not been fully recognized, leading to gaps in available data. Here, we outline the key data demands for the management of biological invasions and highlight the current lack of high-quality data for invasion management in China, and critically assess data gaps in IAS distribution, inventory, and impact. Additionally, we propose a conceptual framework to illustrate the data requirements throughout the invasion management process, along with indicators to assess data quality within three dimensions: relevance, resolution, and reliability.