Dataset Information

Detecting the Minimum Limit on Wheat Stripe Rust in the Latent Period Using Proximal Remote Sensing Coupled with Duplex Real-Time PCR and Machine Learning.

ABSTRACT: Wheat stripe rust (WSR) is an airborne disease that causes severe damage to wheat. The rapid and early detection of WSR is essential for the prevention and control of this disease. The minimum detection limit (MDL) is one of the most important characteristics of quantitative methods that can be used to determine the scope and applicability of a measurement technique. Three wheat cultivars were inoculated with Puccinia striiformis f.sp. tritici (Pst), and a spectrometer was used to collect the canopy hyperspectral data, and the Pst content was obtained via a duplex real-time polymerase chain reaction (PCR) during the latent period, respectively. The disease index (DI) and molecular disease index (MDI) were calculated. The regression tree algorithm was used to determine the MDL of the Pst based on hyperspectral feature parameters. The logistic, IBK, and random committee algorithms were used to construct the classification model based on the MDL. The results showed that when the MDL was 0.7, IBK had the best recognition accuracy. The optimal model, which used the spectral feature R_2nd.dv ((the second derivative of the original hyperspectral value)) and the modeling ratio 2:1, had an accuracy of 91.67% on the testing set and 90.67% on the 10-fold cross-validation. Thus, during the latent period, the MDL of Pst was determined using hyperspectral technology as 0.7.

SUBMITTER: Liu Q

PROVIDER: S-EPMC10420842 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Publications

Detecting the Minimum Limit on Wheat Stripe Rust in the Latent Period Using Proximal Remote Sensing Coupled with Duplex Real-Time PCR and Machine Learning.

Liu Qi Q Sun Tingting T Wen Xiaojie X Zeng Minghao M Chen Jing J

Plants (Basel, Switzerland) 20230729 15

Wheat stripe rust (WSR) is an airborne disease that causes severe damage to wheat. The rapid and early detection of WSR is essential for the prevention and control of this disease. The minimum detection limit (MDL) is one of the most important characteristics of quantitative methods that can be used to determine the scope and applicability of a measurement technique. Three wheat cultivars were inoculated with Puccinia striiformis f.sp. tritici (Pst), and a spectrometer was u ...[more]

PMID: 37570968

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Project description:Leaf rust and stripe rust are important wheat diseases worldwide causing significant losses where susceptible varieties are grown. Resistant cultivars offer long-term control and reduce the use of hazardous chemicals, which can be detrimental to both human health and the environment. Land races have been a valuable resource for mining new genes for various abiotic and biotic stresses including wheat rusts. Afghan wheat landrace "KU3067" displayed high seedling infection type (IT) for leaf rust and low IT for stripe rust; however, it displayed high levels of field resistance for both rusts when tested for multiple seasons against the Mexican rust isolates. This study focused on identifying loci-conferring seedling resistance to stripe rust, and also loci-conferring adult plant resistance (APR) against the Mexican races of leaf rust and stripe rust. A backcrossed inbred line (BIL) population advanced to the BC1F5 generation derived from the cross of KU3067 and Apav (triple rust susceptible line) was used for both, inheritance and QTL mapping studies. The population and parents were genotyped with Diversity Arrays Technology-genotyping-by-sequencing (DArT-Seq) and phenotyped for leaf rust and stripe rust response at both seedling and adult plant stages during multiple seasons in Mexico with relevant pathotypes. Mapping results identified an all-stage resistance gene for stripe rust, temporarily designated as YrKU, on chromosome 7BL. In total, six QTL-conferring APR to leaf rust on 1AS, 2AL, 4DL, 6BL, 7AL, and 7BL, and four QTL for stripe rust resistance on 1BS, 2AL, 4DL, and 7BL were detected in the analyses. Among these, pleiotropic gene Lr67/Yr46 on 4DL with a significantly large effect is the first report in an Afghan landrace-conferring resistance to both leaf and stripe rusts. QLr.cim-7BL/YrKU showed pleiotropic resistance to both rusts and explained 7.5-17.2 and 12.6-19.3% of the phenotypic variance for leaf and stripe rusts, respectively. QYr.cim-1BS and QYr.cim-2AL detected in all stripe environments with phenotypic variance explained (PVE) 12.9-20.5 and 5.4-12.5%, and QLr.cim-6BL are likely to be new. These QTL and their closely linked markers will be useful for fine mapping and marker-assisted selection (MAS) in breeding for durable resistance to multiple rust diseases.

Dataset Information

Detecting the Minimum Limit on Wheat Stripe Rust in the Latent Period Using Proximal Remote Sensing Coupled with Duplex Real-Time PCR and Machine Learning.

Publications

Detecting the Minimum Limit on Wheat Stripe Rust in the Latent Period Using Proximal Remote Sensing Coupled with Duplex Real-Time PCR and Machine Learning.

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