PDF(Pubmed)
Abstract：
Cotton (Gossypium spp. L., Malvaceae) is the world\'s largest source of natural fibers. Virus outbreaks are fast and economically devasting regarding cotton. Identifying new viruses is challenging as virus symptoms usually mimic nutrient deficiency, insect damage, and auxin herbicide injury. Traditional viral identification methods are costly and time-consuming. Developing new resistant cotton lines to face viral threats has been slow until the recent use of molecular virology, genomics, new breeding techniques (NBT), remote sensing, and artificial intelligence (AI). This perspective article demonstrates rapid, sensitive, and cheap technologies to identify viral diseases and propose their use for virus resistance breeding.
摘要：
棉花（棉属。L.,锦葵科）是世界上最大的天然纤维来源。关于棉花，病毒爆发速度很快，而且在经济上造成了破坏。识别新病毒具有挑战性，因为病毒症状通常模仿营养缺乏，昆虫损害,和生长素除草剂伤害。传统的病毒鉴定方法是昂贵且耗时的。在最近使用分子病毒学之前，开发新的抗性棉花品系以应对病毒威胁一直很缓慢，基因组学，新育种技术(NBT)，遥感,人工智能（AI）。这篇透视文章展示了快速，敏感,和廉价的技术来识别病毒疾病，并提出将其用于病毒抗性育种。
