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Environmental Factors Associated With Nitrogen Fixation Prediction in Soybean
Biological nitrogen (N)-fixation is the most important source of N for soybean [Glycine max (L.) Merr.], with considerable implications for sustainable intensification. Therefore, this study aimed to investigate the relevance of environmental factors driving N-fixation and to develop predictive mode...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8239404/ https://www.ncbi.nlm.nih.gov/pubmed/34211487 http://dx.doi.org/10.3389/fpls.2021.675410 |
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author | de Borja Reis, André Froes Moro Rosso, Luiz Purcell, Larry C. Naeve, Seth Casteel, Shaun N. Kovács, Péter Archontoulis, Sotirios Davidson, Dan Ciampitti, Ignacio A. |
author_facet | de Borja Reis, André Froes Moro Rosso, Luiz Purcell, Larry C. Naeve, Seth Casteel, Shaun N. Kovács, Péter Archontoulis, Sotirios Davidson, Dan Ciampitti, Ignacio A. |
author_sort | de Borja Reis, André Froes |
collection | PubMed |
description | Biological nitrogen (N)-fixation is the most important source of N for soybean [Glycine max (L.) Merr.], with considerable implications for sustainable intensification. Therefore, this study aimed to investigate the relevance of environmental factors driving N-fixation and to develop predictive models defining the role of N-fixation for improved productivity and increased seed protein concentration. Using the elastic net regularization of multiple linear regression, we analyzed 40 environmental factors related to weather, soil, and crop management. We selected the most important factors associated with the relative abundance of ureides (RAU) as an indicator of the fraction of N derived from N-fixation. The most relevant RAU predictors were N fertilization, atmospheric vapor pressure deficit (VPD) and precipitation during early reproductive growth (R1–R4 stages), sowing date, drought stress during seed filling (R5–R6), soil cation exchange capacity (CEC), and soil sulfate concentration before sowing. Soybean N-fixation ranged from 60 to 98% across locations and years (n = 95). The predictive model for RAU showed relative mean square error (RRMSE) of 4.5% and an R(2) value of 0.69, estimated via cross-validation. In addition, we built similar predictive models of yield and seed protein to assess the association of RAU and these plant traits. The variable RAU was selected as a covariable for the models predicting yield and seed protein, but with a small magnitude relative to the sowing date for yield or soil sulfate for protein. The early-reproductive period VPD affected all independent variables, namely RAU, yield, and seed protein. The elastic net algorithm successfully depicted some otherwise challenging empirical relationships to assess with bivariate associations in observational data. This approach provides inference about environmental variables while predicting N-fixation. The outcomes of this study will provide a foundation for improving the understanding of N-fixation within the context of sustainable intensification of soybean production. |
format | Online Article Text |
id | pubmed-8239404 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82394042021-06-30 Environmental Factors Associated With Nitrogen Fixation Prediction in Soybean de Borja Reis, André Froes Moro Rosso, Luiz Purcell, Larry C. Naeve, Seth Casteel, Shaun N. Kovács, Péter Archontoulis, Sotirios Davidson, Dan Ciampitti, Ignacio A. Front Plant Sci Plant Science Biological nitrogen (N)-fixation is the most important source of N for soybean [Glycine max (L.) Merr.], with considerable implications for sustainable intensification. Therefore, this study aimed to investigate the relevance of environmental factors driving N-fixation and to develop predictive models defining the role of N-fixation for improved productivity and increased seed protein concentration. Using the elastic net regularization of multiple linear regression, we analyzed 40 environmental factors related to weather, soil, and crop management. We selected the most important factors associated with the relative abundance of ureides (RAU) as an indicator of the fraction of N derived from N-fixation. The most relevant RAU predictors were N fertilization, atmospheric vapor pressure deficit (VPD) and precipitation during early reproductive growth (R1–R4 stages), sowing date, drought stress during seed filling (R5–R6), soil cation exchange capacity (CEC), and soil sulfate concentration before sowing. Soybean N-fixation ranged from 60 to 98% across locations and years (n = 95). The predictive model for RAU showed relative mean square error (RRMSE) of 4.5% and an R(2) value of 0.69, estimated via cross-validation. In addition, we built similar predictive models of yield and seed protein to assess the association of RAU and these plant traits. The variable RAU was selected as a covariable for the models predicting yield and seed protein, but with a small magnitude relative to the sowing date for yield or soil sulfate for protein. The early-reproductive period VPD affected all independent variables, namely RAU, yield, and seed protein. The elastic net algorithm successfully depicted some otherwise challenging empirical relationships to assess with bivariate associations in observational data. This approach provides inference about environmental variables while predicting N-fixation. The outcomes of this study will provide a foundation for improving the understanding of N-fixation within the context of sustainable intensification of soybean production. Frontiers Media S.A. 2021-06-15 /pmc/articles/PMC8239404/ /pubmed/34211487 http://dx.doi.org/10.3389/fpls.2021.675410 Text en Copyright © 2021 de Borja Reis, Moro Rosso, Purcell, Naeve, Casteel, Kovács, Archontoulis, Davidson and Ciampitti. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science de Borja Reis, André Froes Moro Rosso, Luiz Purcell, Larry C. Naeve, Seth Casteel, Shaun N. Kovács, Péter Archontoulis, Sotirios Davidson, Dan Ciampitti, Ignacio A. Environmental Factors Associated With Nitrogen Fixation Prediction in Soybean |
title | Environmental Factors Associated With Nitrogen Fixation Prediction in Soybean |
title_full | Environmental Factors Associated With Nitrogen Fixation Prediction in Soybean |
title_fullStr | Environmental Factors Associated With Nitrogen Fixation Prediction in Soybean |
title_full_unstemmed | Environmental Factors Associated With Nitrogen Fixation Prediction in Soybean |
title_short | Environmental Factors Associated With Nitrogen Fixation Prediction in Soybean |
title_sort | environmental factors associated with nitrogen fixation prediction in soybean |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8239404/ https://www.ncbi.nlm.nih.gov/pubmed/34211487 http://dx.doi.org/10.3389/fpls.2021.675410 |
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