Development and optimization of NIRS prediction models for simultaneous multi-trait assessment in diverse cowpea germplasm
Cowpea (Vigna unguiculata (L.) Walp.) is one such legume that can facilitate achieving sustainable nutrition and climate change goals. Assessing nutritional traits conventionally can be laborious and time-consuming. NIRS is a technique used to rapidly determine biochemical parameters for large germp...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-09-01
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| Series: | Frontiers in Nutrition |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnut.2022.1001551/full |
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| author | Siddhant Ranjan Padhi Racheal John Arti Bartwal Kuldeep Tripathi Kavita Gupta Dhammaprakash Pandhari Wankhede Gyan Prakash Mishra Sanjeev Kumar Jai Chand Rana Amritbir Riar Rakesh Bhardwaj |
| author_facet | Siddhant Ranjan Padhi Racheal John Arti Bartwal Kuldeep Tripathi Kavita Gupta Dhammaprakash Pandhari Wankhede Gyan Prakash Mishra Sanjeev Kumar Jai Chand Rana Amritbir Riar Rakesh Bhardwaj |
| author_sort | Siddhant Ranjan Padhi |
| collection | DOAJ |
| description | Cowpea (Vigna unguiculata (L.) Walp.) is one such legume that can facilitate achieving sustainable nutrition and climate change goals. Assessing nutritional traits conventionally can be laborious and time-consuming. NIRS is a technique used to rapidly determine biochemical parameters for large germplasm. NIRS prediction models were developed to assess protein, starch, TDF, phenols, and phytic acid based on MPLS regression. Higher RSQexternal values such as 0.903, 0.997, 0.901, 0.706, and 0.955 were obtained for protein, starch, TDF, phenols, and phytic acid respectively. Models for all the traits displayed RPD values of >2.5 except phenols and low SEP indicating the excellent prediction of models. For all the traits worked, p-value ≥ 0.05 implied the accuracy and reliability score >0.8 (except phenol) ensured the applicability of the models. These prediction models will facilitate high throughput screening of large cowpea germplasm in a non-destructive way and the selection of desirable chemotypes in any genetic background with huge application in cowpea crop improvement programs across the world. |
| first_indexed | 2024-04-11T11:40:38Z |
| format | Article |
| id | doaj.art-ec55891cc5d0473a9f3658b7078c5a70 |
| institution | Directory Open Access Journal |
| issn | 2296-861X |
| language | English |
| last_indexed | 2024-04-11T11:40:38Z |
| publishDate | 2022-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Nutrition |
| spelling | doaj.art-ec55891cc5d0473a9f3658b7078c5a702022-12-22T04:25:50ZengFrontiers Media S.A.Frontiers in Nutrition2296-861X2022-09-01910.3389/fnut.2022.10015511001551Development and optimization of NIRS prediction models for simultaneous multi-trait assessment in diverse cowpea germplasmSiddhant Ranjan Padhi0Racheal John1Arti Bartwal2Kuldeep Tripathi3Kavita Gupta4Dhammaprakash Pandhari Wankhede5Gyan Prakash Mishra6Sanjeev Kumar7Jai Chand Rana8Amritbir Riar9Rakesh Bhardwaj10Division of Plant Genetic Resources, ICAR-Indian Agricultural Research Institute, New Delhi, IndiaDivision of Germplasm Evaluation, ICAR-National Bureau of Plant Genetic Resources, New Delhi, IndiaDivision of Germplasm Evaluation, ICAR-National Bureau of Plant Genetic Resources, New Delhi, IndiaDivision of Germplasm Evaluation, ICAR-National Bureau of Plant Genetic Resources, New Delhi, IndiaDivision of Plant Quarantine, ICAR-National Bureau of Plant Genetic Resources, New Delhi, IndiaDivision of Genomic Resources, ICAR-National Bureau of Plant Genetic Resources, New Delhi, IndiaDivision of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, IndiaDivision of Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, IndiaAlliance of Bioversity International and CIAT, Region-Asia, India Office, New Delhi, IndiaDepartment of International Cooperation, Research Institute of Organic Agriculture FiBL, Frick, SwitzerlandDivision of Germplasm Evaluation, ICAR-National Bureau of Plant Genetic Resources, New Delhi, IndiaCowpea (Vigna unguiculata (L.) Walp.) is one such legume that can facilitate achieving sustainable nutrition and climate change goals. Assessing nutritional traits conventionally can be laborious and time-consuming. NIRS is a technique used to rapidly determine biochemical parameters for large germplasm. NIRS prediction models were developed to assess protein, starch, TDF, phenols, and phytic acid based on MPLS regression. Higher RSQexternal values such as 0.903, 0.997, 0.901, 0.706, and 0.955 were obtained for protein, starch, TDF, phenols, and phytic acid respectively. Models for all the traits displayed RPD values of >2.5 except phenols and low SEP indicating the excellent prediction of models. For all the traits worked, p-value ≥ 0.05 implied the accuracy and reliability score >0.8 (except phenol) ensured the applicability of the models. These prediction models will facilitate high throughput screening of large cowpea germplasm in a non-destructive way and the selection of desirable chemotypes in any genetic background with huge application in cowpea crop improvement programs across the world.https://www.frontiersin.org/articles/10.3389/fnut.2022.1001551/fullMPLS regressiongermplasm screeningnutritional compositionRPDRSQexternal |
| spellingShingle | Siddhant Ranjan Padhi Racheal John Arti Bartwal Kuldeep Tripathi Kavita Gupta Dhammaprakash Pandhari Wankhede Gyan Prakash Mishra Sanjeev Kumar Jai Chand Rana Amritbir Riar Rakesh Bhardwaj Development and optimization of NIRS prediction models for simultaneous multi-trait assessment in diverse cowpea germplasm Frontiers in Nutrition MPLS regression germplasm screening nutritional composition RPD RSQexternal |
| title | Development and optimization of NIRS prediction models for simultaneous multi-trait assessment in diverse cowpea germplasm |
| title_full | Development and optimization of NIRS prediction models for simultaneous multi-trait assessment in diverse cowpea germplasm |
| title_fullStr | Development and optimization of NIRS prediction models for simultaneous multi-trait assessment in diverse cowpea germplasm |
| title_full_unstemmed | Development and optimization of NIRS prediction models for simultaneous multi-trait assessment in diverse cowpea germplasm |
| title_short | Development and optimization of NIRS prediction models for simultaneous multi-trait assessment in diverse cowpea germplasm |
| title_sort | development and optimization of nirs prediction models for simultaneous multi trait assessment in diverse cowpea germplasm |
| topic | MPLS regression germplasm screening nutritional composition RPD RSQexternal |
| url | https://www.frontiersin.org/articles/10.3389/fnut.2022.1001551/full |
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