{"title":"高光谱成像技术用于量化水稻基因型上的木格氏霉孢子。","authors":"Angeline Wanjiku Maina, Erich-Christian Oerke","doi":"10.1186/s13007-024-01215-1","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Precise evaluation of fungal conidia production may facilitate studies on resistance mechanisms and plant breeding for disease resistance. In this study, hyperspectral imaging (HSI) was used to quantify the sporulation of Magnaporthe oryzae on the leaves of rice cultivars grown under controlled conditions. Three rice genotypes (CO 39, Nipponbare, IR64) differing in susceptibility to blast were inoculated with M. oryzae isolates Guy 11 and Li1497. Spectral information (450-850 nm, 140 wavebands) of typical leaf blast symptoms was recorded before and after induction of sporulation of the pathogen.</p><p><strong>Results: </strong>M. oryzae produced more conidia on the highly susceptible genotype than on the moderately susceptible genotype, whereas the resistant genotype resulted in no sporulation. Changes in reflectance spectra recorded before and after induction of sporulation were significantly higher in genotype CO 39 than in Nipponbare. The spectral angle mapper algorithm for supervised classification allowed for the classification of blast symptom subareas and the quantification of lesion areas with M. oryzae sporulation. The correlation between the area under the difference spectrum (viz. spectral difference without and with sporulation) and the number of conidia per lesion and the number of conidia per lesion area was positive and count-based differences in rice - M. oryzae interaction could be reproduced in the spectral data.</p><p><strong>Conclusions: </strong>HSI provided a precise and objective method of assessing M. oryzae conidia production on infected rice plants, revealing differences that could not be detected visually.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"87"},"PeriodicalIF":4.7000,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11161989/pdf/","citationCount":"0","resultStr":"{\"title\":\"Hyperspectral imaging for quantifying Magnaporthe oryzae sporulation on rice genotypes.\",\"authors\":\"Angeline Wanjiku Maina, Erich-Christian Oerke\",\"doi\":\"10.1186/s13007-024-01215-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Precise evaluation of fungal conidia production may facilitate studies on resistance mechanisms and plant breeding for disease resistance. In this study, hyperspectral imaging (HSI) was used to quantify the sporulation of Magnaporthe oryzae on the leaves of rice cultivars grown under controlled conditions. Three rice genotypes (CO 39, Nipponbare, IR64) differing in susceptibility to blast were inoculated with M. oryzae isolates Guy 11 and Li1497. Spectral information (450-850 nm, 140 wavebands) of typical leaf blast symptoms was recorded before and after induction of sporulation of the pathogen.</p><p><strong>Results: </strong>M. oryzae produced more conidia on the highly susceptible genotype than on the moderately susceptible genotype, whereas the resistant genotype resulted in no sporulation. Changes in reflectance spectra recorded before and after induction of sporulation were significantly higher in genotype CO 39 than in Nipponbare. The spectral angle mapper algorithm for supervised classification allowed for the classification of blast symptom subareas and the quantification of lesion areas with M. oryzae sporulation. The correlation between the area under the difference spectrum (viz. spectral difference without and with sporulation) and the number of conidia per lesion and the number of conidia per lesion area was positive and count-based differences in rice - M. oryzae interaction could be reproduced in the spectral data.</p><p><strong>Conclusions: </strong>HSI provided a precise and objective method of assessing M. oryzae conidia production on infected rice plants, revealing differences that could not be detected visually.</p>\",\"PeriodicalId\":20100,\"journal\":{\"name\":\"Plant Methods\",\"volume\":\"20 1\",\"pages\":\"87\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2024-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11161989/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Plant Methods\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1186/s13007-024-01215-1\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Plant Methods","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s13007-024-01215-1","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
摘要
背景:精确评估真菌分生孢子的产生可促进抗病机制研究和植物抗病育种。本研究采用高光谱成像技术(HSI)来量化在受控条件下生长的水稻品种叶片上的木格氏球菌分生孢子。给三种对稻瘟病敏感性不同的水稻基因型(CO 39、Nipponbare 和 IR64)接种 M. oryzae 分离物 Guy 11 和 Li1497。在病原体孢子诱导前后记录典型叶瘟症状的光谱信息(450-850 nm,140 波段):结果:与中度易感基因型相比,高易感基因型上的 M. oryzae 产生了更多的分生孢子,而抗病基因型则没有分生孢子。在诱导分生孢子之前和之后记录到的反射光谱变化,基因型 CO 39 明显高于 Nipponbare。采用光谱角度映射器算法进行监督分类,可对稻瘟病症状亚区进行分类,并对有 M. oryzae 孢子的病害区域进行量化。差异光谱下的面积(即无孢子和有孢子的光谱差异)与每个病斑的分生孢子数和每个病斑面积的分生孢子数之间的相关性是正的,水稻与 M. oryzae 交互作用中基于计数的差异可在光谱数据中再现:HSI 提供了一种精确、客观的方法来评估受感染水稻植株上的 M. oryzae 分生孢子产量,揭示了肉眼无法发现的差异。
Hyperspectral imaging for quantifying Magnaporthe oryzae sporulation on rice genotypes.
Background: Precise evaluation of fungal conidia production may facilitate studies on resistance mechanisms and plant breeding for disease resistance. In this study, hyperspectral imaging (HSI) was used to quantify the sporulation of Magnaporthe oryzae on the leaves of rice cultivars grown under controlled conditions. Three rice genotypes (CO 39, Nipponbare, IR64) differing in susceptibility to blast were inoculated with M. oryzae isolates Guy 11 and Li1497. Spectral information (450-850 nm, 140 wavebands) of typical leaf blast symptoms was recorded before and after induction of sporulation of the pathogen.
Results: M. oryzae produced more conidia on the highly susceptible genotype than on the moderately susceptible genotype, whereas the resistant genotype resulted in no sporulation. Changes in reflectance spectra recorded before and after induction of sporulation were significantly higher in genotype CO 39 than in Nipponbare. The spectral angle mapper algorithm for supervised classification allowed for the classification of blast symptom subareas and the quantification of lesion areas with M. oryzae sporulation. The correlation between the area under the difference spectrum (viz. spectral difference without and with sporulation) and the number of conidia per lesion and the number of conidia per lesion area was positive and count-based differences in rice - M. oryzae interaction could be reproduced in the spectral data.
Conclusions: HSI provided a precise and objective method of assessing M. oryzae conidia production on infected rice plants, revealing differences that could not be detected visually.
期刊介绍:
Plant Methods is an open access, peer-reviewed, online journal for the plant research community that encompasses all aspects of technological innovation in the plant sciences.
There is no doubt that we have entered an exciting new era in plant biology. The completion of the Arabidopsis genome sequence, and the rapid progress being made in other plant genomics projects are providing unparalleled opportunities for progress in all areas of plant science. Nevertheless, enormous challenges lie ahead if we are to understand the function of every gene in the genome, and how the individual parts work together to make the whole organism. Achieving these goals will require an unprecedented collaborative effort, combining high-throughput, system-wide technologies with more focused approaches that integrate traditional disciplines such as cell biology, biochemistry and molecular genetics.
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