Screening of barley resistance against powdery mildew by simultaneous high-throughput enzyme activity signature profiling and multispectral imaging

Research output: Contribution to journalJournal articlepeer-review

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Screening of barley resistance against powdery mildew by simultaneous high-throughput enzyme activity signature profiling and multispectral imaging. / Kuska, Matheus T.; Behmann, Jan; Grosskinsky, Dominik K.; Roitsch, Thomas Georg; Mahlein, Anne Katrin.

In: Frontiers in Plant Science, Vol. 9, 1074, 2018, p. 1-12.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Kuska, MT, Behmann, J, Grosskinsky, DK, Roitsch, TG & Mahlein, AK 2018, 'Screening of barley resistance against powdery mildew by simultaneous high-throughput enzyme activity signature profiling and multispectral imaging', Frontiers in Plant Science, vol. 9, 1074, pp. 1-12. https://doi.org/10.3389/fpls.2018.01074

APA

Kuska, M. T., Behmann, J., Grosskinsky, D. K., Roitsch, T. G., & Mahlein, A. K. (2018). Screening of barley resistance against powdery mildew by simultaneous high-throughput enzyme activity signature profiling and multispectral imaging. Frontiers in Plant Science, 9, 1-12. [1074]. https://doi.org/10.3389/fpls.2018.01074

Vancouver

Kuska MT, Behmann J, Grosskinsky DK, Roitsch TG, Mahlein AK. Screening of barley resistance against powdery mildew by simultaneous high-throughput enzyme activity signature profiling and multispectral imaging. Frontiers in Plant Science. 2018;9:1-12. 1074. https://doi.org/10.3389/fpls.2018.01074

Author

Kuska, Matheus T. ; Behmann, Jan ; Grosskinsky, Dominik K. ; Roitsch, Thomas Georg ; Mahlein, Anne Katrin. / Screening of barley resistance against powdery mildew by simultaneous high-throughput enzyme activity signature profiling and multispectral imaging. In: Frontiers in Plant Science. 2018 ; Vol. 9. pp. 1-12.

Bibtex

@article{8a1e0a71574449f4b166b4ed1d938e0f,
title = "Screening of barley resistance against powdery mildew by simultaneous high-throughput enzyme activity signature profiling and multispectral imaging",
abstract = "Molecular marker analysis allow for a rapid and advanced pre-selection and resistance screenings in plant breeding processes. During the phenotyping process, optical sensors have proved their potential to determine and assess the function of the genotype of the breeding material. Thereby, biomarkers for specific disease resistance traits provide valuable information for calibrating optical sensor approaches during early plant-pathogen interactions. In this context, the combination of physiological, metabolic phenotyping and phenomic profiles could establish efficient identification and quantification of relevant genotypes within breeding processes. Experiments were conducted with near-isogenic lines of H. vulgare (susceptible, mildew locus o (mlo) and Mildew locus a (Mla) resistant). Multispectral imaging of barley plants was daily conducted 0–8 days after inoculation (dai) in a high-throughput facility with 10 wavelength bands from 400 to 1,000 nm. In parallel, the temporal dynamics of the activities of invertase isoenzymes, as key sink specific enzymes that irreversibly cleave the transport sugar sucrose into the hexose monomers, were profiled in a semi high-throughput approach. The activities of cell wall, cytosolic and vacuole invertase revealed specific dynamics of the activity signatures for susceptible genotypes and genotypes with mlo and Mla based resistances 0–120 hours after inoculation (hai). These patterns could be used to differentiate between interaction types and revealed an early influence of Blumeria graminis f.sp. hordei (Bgh) conidia on the specific invertase activity already 0.5 hai. During this early powdery mildew pathogenesis, the reflectance intensity increased in the blue bands and at 690 nm. The Mla resistant plants showed an increased reflectance at 680 and 710 nm and a decreased reflectance in the near infrared bands from 3 dai. Applying a Support Vector Machine classification as a supervised machine learning approach, the pixelwise identification and quantification of powdery mildew diseased barley tissue and hypersensitive response spots were established. This enables an automatic identification of the barley-powdery mildew interaction. The study established a proof-of-concept for plant resistance phenotyping with multispectral imaging in high-throughput. The combination of invertase analysis and multispectral imaging showed to be a complementing validation system. This will provide a deeper understanding of optical data and its implementation into disease resistance screening.",
keywords = "Blumeria graminis f.sp, Classification, Crop resistance, Hordei, Invertase, Multispectral imaging, Phenolab, Phenotyping, Support vector machine",
author = "Kuska, {Matheus T.} and Jan Behmann and Grosskinsky, {Dominik K.} and Roitsch, {Thomas Georg} and Mahlein, {Anne Katrin}",
year = "2018",
doi = "10.3389/fpls.2018.01074",
language = "English",
volume = "9",
pages = "1--12",
journal = "Frontiers in Plant Science",
issn = "1664-462X",
publisher = "Frontiers Media S.A.",

}

RIS

TY - JOUR

T1 - Screening of barley resistance against powdery mildew by simultaneous high-throughput enzyme activity signature profiling and multispectral imaging

AU - Kuska, Matheus T.

AU - Behmann, Jan

AU - Grosskinsky, Dominik K.

AU - Roitsch, Thomas Georg

AU - Mahlein, Anne Katrin

PY - 2018

Y1 - 2018

N2 - Molecular marker analysis allow for a rapid and advanced pre-selection and resistance screenings in plant breeding processes. During the phenotyping process, optical sensors have proved their potential to determine and assess the function of the genotype of the breeding material. Thereby, biomarkers for specific disease resistance traits provide valuable information for calibrating optical sensor approaches during early plant-pathogen interactions. In this context, the combination of physiological, metabolic phenotyping and phenomic profiles could establish efficient identification and quantification of relevant genotypes within breeding processes. Experiments were conducted with near-isogenic lines of H. vulgare (susceptible, mildew locus o (mlo) and Mildew locus a (Mla) resistant). Multispectral imaging of barley plants was daily conducted 0–8 days after inoculation (dai) in a high-throughput facility with 10 wavelength bands from 400 to 1,000 nm. In parallel, the temporal dynamics of the activities of invertase isoenzymes, as key sink specific enzymes that irreversibly cleave the transport sugar sucrose into the hexose monomers, were profiled in a semi high-throughput approach. The activities of cell wall, cytosolic and vacuole invertase revealed specific dynamics of the activity signatures for susceptible genotypes and genotypes with mlo and Mla based resistances 0–120 hours after inoculation (hai). These patterns could be used to differentiate between interaction types and revealed an early influence of Blumeria graminis f.sp. hordei (Bgh) conidia on the specific invertase activity already 0.5 hai. During this early powdery mildew pathogenesis, the reflectance intensity increased in the blue bands and at 690 nm. The Mla resistant plants showed an increased reflectance at 680 and 710 nm and a decreased reflectance in the near infrared bands from 3 dai. Applying a Support Vector Machine classification as a supervised machine learning approach, the pixelwise identification and quantification of powdery mildew diseased barley tissue and hypersensitive response spots were established. This enables an automatic identification of the barley-powdery mildew interaction. The study established a proof-of-concept for plant resistance phenotyping with multispectral imaging in high-throughput. The combination of invertase analysis and multispectral imaging showed to be a complementing validation system. This will provide a deeper understanding of optical data and its implementation into disease resistance screening.

AB - Molecular marker analysis allow for a rapid and advanced pre-selection and resistance screenings in plant breeding processes. During the phenotyping process, optical sensors have proved their potential to determine and assess the function of the genotype of the breeding material. Thereby, biomarkers for specific disease resistance traits provide valuable information for calibrating optical sensor approaches during early plant-pathogen interactions. In this context, the combination of physiological, metabolic phenotyping and phenomic profiles could establish efficient identification and quantification of relevant genotypes within breeding processes. Experiments were conducted with near-isogenic lines of H. vulgare (susceptible, mildew locus o (mlo) and Mildew locus a (Mla) resistant). Multispectral imaging of barley plants was daily conducted 0–8 days after inoculation (dai) in a high-throughput facility with 10 wavelength bands from 400 to 1,000 nm. In parallel, the temporal dynamics of the activities of invertase isoenzymes, as key sink specific enzymes that irreversibly cleave the transport sugar sucrose into the hexose monomers, were profiled in a semi high-throughput approach. The activities of cell wall, cytosolic and vacuole invertase revealed specific dynamics of the activity signatures for susceptible genotypes and genotypes with mlo and Mla based resistances 0–120 hours after inoculation (hai). These patterns could be used to differentiate between interaction types and revealed an early influence of Blumeria graminis f.sp. hordei (Bgh) conidia on the specific invertase activity already 0.5 hai. During this early powdery mildew pathogenesis, the reflectance intensity increased in the blue bands and at 690 nm. The Mla resistant plants showed an increased reflectance at 680 and 710 nm and a decreased reflectance in the near infrared bands from 3 dai. Applying a Support Vector Machine classification as a supervised machine learning approach, the pixelwise identification and quantification of powdery mildew diseased barley tissue and hypersensitive response spots were established. This enables an automatic identification of the barley-powdery mildew interaction. The study established a proof-of-concept for plant resistance phenotyping with multispectral imaging in high-throughput. The combination of invertase analysis and multispectral imaging showed to be a complementing validation system. This will provide a deeper understanding of optical data and its implementation into disease resistance screening.

KW - Blumeria graminis f.sp

KW - Classification

KW - Crop resistance

KW - Hordei

KW - Invertase

KW - Multispectral imaging

KW - Phenolab

KW - Phenotyping

KW - Support vector machine

U2 - 10.3389/fpls.2018.01074

DO - 10.3389/fpls.2018.01074

M3 - Journal article

C2 - 30083181

AN - SCOPUS:85050794476

VL - 9

SP - 1

EP - 12

JO - Frontiers in Plant Science

JF - Frontiers in Plant Science

SN - 1664-462X

M1 - 1074

ER -

ID: 201261305