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DC Field | Value | Language |
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dc.contributor.author | Sinha, Ranjita | - |
dc.contributor.author | Irulappan, Vadivelmurugan | - |
dc.contributor.author | Patil, Basavanagouda S. | - |
dc.contributor.author | Reddy, Puli Chandra Obul | - |
dc.contributor.author | Ramegowda, Venkategowda | - |
dc.contributor.author | Mohan‑Raju, Basavaiah | - |
dc.contributor.author | Rangappa, Krishnappa | - |
dc.contributor.author | Singh, Harvinder Kumar | - |
dc.contributor.author | Bhartiya, Sharad | - |
dc.contributor.author | Senthil-Kumar, Muthappa | - |
dc.date.accessioned | 2021-04-01T05:53:06Z | - |
dc.date.available | 2021-04-01T05:53:06Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Scientific Reports, 11(1): 6568 | en_US |
dc.identifier.issn | 2045-2322 | - |
dc.identifier.other | https://doi.org/10.1038/s41598-021-85928-6 | - |
dc.identifier.uri | https://www.nature.com/articles/s41598-021-85928-6 | - |
dc.identifier.uri | http://223.31.159.10:8080/jspui/handle/123456789/1175 | - |
dc.description | Accepted date: 08 March 2021 | en_US |
dc.description.abstract | Rhizoctonia bataticola causes dry root rot (DRR), a devastating disease in chickpea (Cicer arietinum). DRR incidence increases under water defcit stress and high temperature. However, the roles of other edaphic and environmental factors remain unclear. Here, we performed an artifcial neural network (ANN)-based prediction of DRR incidence considering DRR incidence data from previous reports and weather factors. ANN-based prediction using the backpropagation algorithm showed that the combination of total rainfall from November to January of the chickpea-growing season and average maximum temperature of the months October and November is crucial in determining DRR occurrence in chickpea felds. The prediction accuracy of DRR incidence was 84.6% with the validation dataset. Field trials at seven diferent locations in India with combination of low soil moisture and pathogen stress treatments confrmed the impact of low soil moisture on DRR incidence under diferent agroclimatic zones and helped in determining the correlation of soil factors with DRR incidence. Soil phosphorus, potassium, organic carbon, and clay content were positively correlated with DRR incidence, while soil silt content was negatively correlated. Our results establish the role of edaphic and other weather factors in chickpea DRR disease incidence. Our ANN-based model will allow the location-specifc prediction of DRR incidence, enabling efcient decision-making in chickpea cultivation to minimize yield loss. | en_US |
dc.description.sponsorship | Chickpea combined stress projects at the M.S.-K lab are supported by the National Institute of Plant Genome Research core funding and by Department of Biotechnology, Governemnt of India (No. BT/Ag/Network/Chickpea/2019-20) under mission programme of on ‘Characterization of genetic resources’. RS and VI acknowledge CSIR for CSIR-SRA fellowship (SRA Pool No. 8917-A) and DBT- JRF (DBT/2015/NIPGR/430) respectively. We thank lab and feld assistants Mr. Rahim Hussain Tarafdar, Mr. Shankar Badaik, Mr. Sundar Solanki, and Mr. Ashok Mandal for their help at the laboratory and feld. We also thank Mr. Ashok Kumar for his technical help with CIF instruments. We acknowledge DBT-eLibrary Consortium (DeLCON) and NIPGR library for providing access to e-resources and NIPGR Plant Growth Facility for plant growth support/space. We thank Dr. Piyush Priya, Dr. Anupriya Singh, and Miss. Aanchal Choudhary for scrutinizing the raw data and internally reviewing the manuscript. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Springer Nature Publishing AG | en_US |
dc.subject | Plant sciences | en_US |
dc.subject | Biological techniques | en_US |
dc.subject | Low soil moisture predisposes | en_US |
dc.subject | chickpea | en_US |
dc.subject | dry root rot disease | en_US |
dc.title | Low soil moisture predisposes field-grown chickpea plants to dry root rot disease: evidence from simulation modeling and correlation analysis | en_US |
dc.type | Article | en_US |
Appears in Collections: | Institutional Publications |
Files in This Item:
File | Description | Size | Format | |
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Senthil-Kumar M_2021_3.pdf | 1.68 MB | Adobe PDF | ![]() View/Open |
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