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RAPID SCREENING OF HUANGLONGBING-INFECTED CITRUS LEAVES BY NEAR-INFRARED REFLECTANCE SPECTROSCOPY

机译:近红外反射光谱法快速筛查受黄龙病感染的柑橘叶片

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摘要

The citrus disease Huanglongbing (HLB, or citrus greening), is one of the more serious diseases of citrus. An infected tree produces fruit that is unsuitable for sale as fresh fruit or for juice. The only definitive method to diagnose trees suspected of infection by citrus greening pathogens is by analysis of DNA, which is costly and time consuming. Near-infrared (NIR) reflectance spectroscopy may have the potential to detect HLB positive leaves. In this study, the primary differences in the visible spectra between HLB positive and negative leaves were the peaks associated with chlorophyll absorption, which decreased for the infected leaves. The NIR region of the spectra of HLB positive leaves revealed differences in carbohydrates and cuticle waxes, indicating that a change occurred in the amount, type, or structure of these chemical components. Partial least squares regression models were developed with 381 leaves from trees that were visually HLB positive or HLB negative with other known citrus disease and nutrient deficiencies. The models had an overall accuracy for true HLB positive and negative leaves ranging from 92% to 99% and a false rate of 1% to 8%.
机译:柑橘类疾病黄龙病(HLB或柑橘绿化)是柑橘较为严重的疾病之一。受感染的树木产生的水果不适合作为新鲜水果或果汁出售。诊断怀疑被柑橘类绿化病原体感染的树木的唯一确定方法是通过DNA分析,这既昂贵又费时。近红外(NIR)反射光谱法可能具有检测HLB阳性叶片的潜力。在这项研究中,HLB阳性和阴性叶片之间可见光谱的主要差异是与叶绿素吸收相关的峰,对于被感染的叶片,这些峰减小。 HLB阳性叶片光谱的NIR区域显示碳水化合物和表皮蜡的差异,表明这些化学成分的数量,类型或结构发生了变化。使用从视觉上HLB阳性或HLB阴性并带有其他已知柑橘病和营养缺乏症的树木中的381个叶子开发了偏最小二乘回归模型。这些模型对真实HLB正负叶的总体准确性为92%至99%,错误率为1%至8%。

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