Loading…
Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean
Soybean emergence and yield may be affected by many factors. A better understanding of the cultivar x sowing date x environment interactions could shed light into the competitiveness of soybean with other crops, notably, to help manage major biotic and abiotic factors that limit soybean production....
Saved in:
Published in: | Frontiers in plant science 2020-09, Vol.11, p.558855-558855 |
---|---|
Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c473t-caddcb0ec240aec7ac4418581b1453bd959e977b4e437da0d7ee1be02b0df5f13 |
---|---|
cites | cdi_FETCH-LOGICAL-c473t-caddcb0ec240aec7ac4418581b1453bd959e977b4e437da0d7ee1be02b0df5f13 |
container_end_page | 558855 |
container_issue | |
container_start_page | 558855 |
container_title | Frontiers in plant science |
container_volume | 11 |
creator | Lamichhane, Jay Ram Aubertot, Jean-Noël Champolivier, Luc Debaeke, Philippe Maury, Pierre |
description | Soybean emergence and yield may be affected by many factors. A better understanding of the cultivar x sowing date x environment interactions could shed light into the competitiveness of soybean with other crops, notably, to help manage major biotic and abiotic factors that limit soybean production. We conducted a 2-year field experiments to measure emergence dynamics and final rates of three soybean cultivars from different maturity groups, with early and conventional sowing dates and across three locations. We also measured germination parameter values of the three soybean cultivars from different maturity groups under controlled experiments to parametrize the SIMPLE crop emergence model. This allowed us to assess the prediction quality of the model for emergence rates and to perform simulations. Final emergence rates under field conditions ranged from 62% to 92% and from 51% to 94% for early and conventional sowing, respectively. The model finely predicted emergence courses and final rates (root mean square error of prediction (RMSEP), efficiency (EF), and mean deviation (MD) ranging between 2% to 18%, 0.46% to 0.99%, and −10% to 15%, respectively) across a wide range of the sowing conditions tested. Differences in the final emergence rates were found, not only among cultivars but also among locations for the same cultivar, although no clear trend or consistent ranking was found in this regard. Modeling suggests that seedling mortality rates were dependent on the soil type with up to 35% and 14% of mortality in the silty loam soil, due to a soil surface crust and soil aggregates, respectively. Non-germination was the least important cause of seedling mortality in all soil types (up to 3% of emergence losses), while no seedling mortality due to drought was observed. The average grain yield ranged from 3.1 to 4.0 t ha −1 , and it was significantly affected by the irrigation regime (p < 0.001) and year (p < 0.001) but not by locations, sowing date or cultivars. We conclude that early sowing is unlikely to affect soybean emergence in |
doi_str_mv | 10.3389/fpls.2020.558855 |
format | article |
fullrecord | <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_ff4d4d406c054ddd83f047de6a7141dd</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_ff4d4d406c054ddd83f047de6a7141dd</doaj_id><sourcerecordid>2446992632</sourcerecordid><originalsourceid>FETCH-LOGICAL-c473t-caddcb0ec240aec7ac4418581b1453bd959e977b4e437da0d7ee1be02b0df5f13</originalsourceid><addsrcrecordid>eNpdkk1vEzEQhlcIRKvSO0cf4ZDgr12vL0hRCGmkICSgEpwsrz1OXO3ai70Jze_hj7LbVIhiHzz2vPOMNXqL4jXBc8Zq-c71bZ5TTPG8LOu6LJ8Vl6Sq-IxX9Pvzf-KL4jrnOzyuEmMpxcviglFZM0r4ZfF7GbvGBx92aHXfQ_IdhEG3SAeLPkUL7ZRZ9H2K2uwhoyGi22Ah5WFSrCHE4dQDukdf469J-kEP020Vjj7FMMHQJgyQtBl8DGjlHJghoynsIO0gGEBfxpr80HGdtA_oh4fWouhG5qkBHV4VL5xuM1w_nlfF7cfVt-XNbPt5vVkutjPDBRtmRltrGgyGcqzBCG04J3VZk4bwkjVWlhKkEA0HzoTV2AoA0gCmDbaudIRdFZsz10Z9p_pxFjqdVNRePTzEtFM6Dd60oJzjdty4Mrjk1tqaOcyFhUoLwom1I-v9mdUfmg6sGQeRdPsE-jQT_F7t4lEJLllF-Qh4ewbs_yu7WWzV9IapZILX4jh9_M1jsxR_HiAPqvPZQNvqAPGQFeW8kpJWjI5SfJaaFHNO4P6yCVaTrdRkKzXZSp1txf4AtYzDhQ</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2446992632</pqid></control><display><type>article</type><title>Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean</title><source>PubMed Central</source><creator>Lamichhane, Jay Ram ; Aubertot, Jean-Noël ; Champolivier, Luc ; Debaeke, Philippe ; Maury, Pierre</creator><creatorcontrib>Lamichhane, Jay Ram ; Aubertot, Jean-Noël ; Champolivier, Luc ; Debaeke, Philippe ; Maury, Pierre</creatorcontrib><description>Soybean emergence and yield may be affected by many factors. A better understanding of the cultivar x sowing date x environment interactions could shed light into the competitiveness of soybean with other crops, notably, to help manage major biotic and abiotic factors that limit soybean production. We conducted a 2-year field experiments to measure emergence dynamics and final rates of three soybean cultivars from different maturity groups, with early and conventional sowing dates and across three locations. We also measured germination parameter values of the three soybean cultivars from different maturity groups under controlled experiments to parametrize the SIMPLE crop emergence model. This allowed us to assess the prediction quality of the model for emergence rates and to perform simulations. Final emergence rates under field conditions ranged from 62% to 92% and from 51% to 94% for early and conventional sowing, respectively. The model finely predicted emergence courses and final rates (root mean square error of prediction (RMSEP), efficiency (EF), and mean deviation (MD) ranging between 2% to 18%, 0.46% to 0.99%, and −10% to 15%, respectively) across a wide range of the sowing conditions tested. Differences in the final emergence rates were found, not only among cultivars but also among locations for the same cultivar, although no clear trend or consistent ranking was found in this regard. Modeling suggests that seedling mortality rates were dependent on the soil type with up to 35% and 14% of mortality in the silty loam soil, due to a soil surface crust and soil aggregates, respectively. Non-germination was the least important cause of seedling mortality in all soil types (up to 3% of emergence losses), while no seedling mortality due to drought was observed. The average grain yield ranged from 3.1 to 4.0 t ha −1 , and it was significantly affected by the irrigation regime (p < 0.001) and year (p < 0.001) but not by locations, sowing date or cultivars. We conclude that early sowing is unlikely to affect soybean emergence in</description><identifier>ISSN: 1664-462X</identifier><identifier>EISSN: 1664-462X</identifier><identifier>DOI: 10.3389/fpls.2020.558855</identifier><identifier>PMID: 32983214</identifier><language>eng</language><publisher>Frontiers</publisher><subject>crop emergence ; genotype x environment interactions ; Glycine max ; Life Sciences ; non-emergence causes ; Plant Science ; seedbed conditions ; seedling mortality</subject><ispartof>Frontiers in plant science, 2020-09, Vol.11, p.558855-558855</ispartof><rights>Attribution</rights><rights>Copyright © 2020 Lamichhane, Aubertot, Champolivier, Debaeke and Maury 2020 Lamichhane, Aubertot, Champolivier, Debaeke and Maury</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c473t-caddcb0ec240aec7ac4418581b1453bd959e977b4e437da0d7ee1be02b0df5f13</citedby><cites>FETCH-LOGICAL-c473t-caddcb0ec240aec7ac4418581b1453bd959e977b4e437da0d7ee1be02b0df5f13</cites><orcidid>0000-0001-6048-1553 ; 0000-0002-1271-2334 ; 0000-0001-9780-0941 ; 0000-0002-4173-8170</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493624/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493624/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://hal.inrae.fr/hal-02937487$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Lamichhane, Jay Ram</creatorcontrib><creatorcontrib>Aubertot, Jean-Noël</creatorcontrib><creatorcontrib>Champolivier, Luc</creatorcontrib><creatorcontrib>Debaeke, Philippe</creatorcontrib><creatorcontrib>Maury, Pierre</creatorcontrib><title>Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean</title><title>Frontiers in plant science</title><description>Soybean emergence and yield may be affected by many factors. A better understanding of the cultivar x sowing date x environment interactions could shed light into the competitiveness of soybean with other crops, notably, to help manage major biotic and abiotic factors that limit soybean production. We conducted a 2-year field experiments to measure emergence dynamics and final rates of three soybean cultivars from different maturity groups, with early and conventional sowing dates and across three locations. We also measured germination parameter values of the three soybean cultivars from different maturity groups under controlled experiments to parametrize the SIMPLE crop emergence model. This allowed us to assess the prediction quality of the model for emergence rates and to perform simulations. Final emergence rates under field conditions ranged from 62% to 92% and from 51% to 94% for early and conventional sowing, respectively. The model finely predicted emergence courses and final rates (root mean square error of prediction (RMSEP), efficiency (EF), and mean deviation (MD) ranging between 2% to 18%, 0.46% to 0.99%, and −10% to 15%, respectively) across a wide range of the sowing conditions tested. Differences in the final emergence rates were found, not only among cultivars but also among locations for the same cultivar, although no clear trend or consistent ranking was found in this regard. Modeling suggests that seedling mortality rates were dependent on the soil type with up to 35% and 14% of mortality in the silty loam soil, due to a soil surface crust and soil aggregates, respectively. Non-germination was the least important cause of seedling mortality in all soil types (up to 3% of emergence losses), while no seedling mortality due to drought was observed. The average grain yield ranged from 3.1 to 4.0 t ha −1 , and it was significantly affected by the irrigation regime (p < 0.001) and year (p < 0.001) but not by locations, sowing date or cultivars. We conclude that early sowing is unlikely to affect soybean emergence in</description><subject>crop emergence</subject><subject>genotype x environment interactions</subject><subject>Glycine max</subject><subject>Life Sciences</subject><subject>non-emergence causes</subject><subject>Plant Science</subject><subject>seedbed conditions</subject><subject>seedling mortality</subject><issn>1664-462X</issn><issn>1664-462X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpdkk1vEzEQhlcIRKvSO0cf4ZDgr12vL0hRCGmkICSgEpwsrz1OXO3ai70Jze_hj7LbVIhiHzz2vPOMNXqL4jXBc8Zq-c71bZ5TTPG8LOu6LJ8Vl6Sq-IxX9Pvzf-KL4jrnOzyuEmMpxcviglFZM0r4ZfF7GbvGBx92aHXfQ_IdhEG3SAeLPkUL7ZRZ9H2K2uwhoyGi22Ah5WFSrCHE4dQDukdf469J-kEP020Vjj7FMMHQJgyQtBl8DGjlHJghoynsIO0gGEBfxpr80HGdtA_oh4fWouhG5qkBHV4VL5xuM1w_nlfF7cfVt-XNbPt5vVkutjPDBRtmRltrGgyGcqzBCG04J3VZk4bwkjVWlhKkEA0HzoTV2AoA0gCmDbaudIRdFZsz10Z9p_pxFjqdVNRePTzEtFM6Dd60oJzjdty4Mrjk1tqaOcyFhUoLwom1I-v9mdUfmg6sGQeRdPsE-jQT_F7t4lEJLllF-Qh4ewbs_yu7WWzV9IapZILX4jh9_M1jsxR_HiAPqvPZQNvqAPGQFeW8kpJWjI5SfJaaFHNO4P6yCVaTrdRkKzXZSp1txf4AtYzDhQ</recordid><startdate>20200902</startdate><enddate>20200902</enddate><creator>Lamichhane, Jay Ram</creator><creator>Aubertot, Jean-Noël</creator><creator>Champolivier, Luc</creator><creator>Debaeke, Philippe</creator><creator>Maury, Pierre</creator><general>Frontiers</general><general>Frontiers Media S.A</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>1XC</scope><scope>VOOES</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-6048-1553</orcidid><orcidid>https://orcid.org/0000-0002-1271-2334</orcidid><orcidid>https://orcid.org/0000-0001-9780-0941</orcidid><orcidid>https://orcid.org/0000-0002-4173-8170</orcidid></search><sort><creationdate>20200902</creationdate><title>Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean</title><author>Lamichhane, Jay Ram ; Aubertot, Jean-Noël ; Champolivier, Luc ; Debaeke, Philippe ; Maury, Pierre</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c473t-caddcb0ec240aec7ac4418581b1453bd959e977b4e437da0d7ee1be02b0df5f13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>crop emergence</topic><topic>genotype x environment interactions</topic><topic>Glycine max</topic><topic>Life Sciences</topic><topic>non-emergence causes</topic><topic>Plant Science</topic><topic>seedbed conditions</topic><topic>seedling mortality</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lamichhane, Jay Ram</creatorcontrib><creatorcontrib>Aubertot, Jean-Noël</creatorcontrib><creatorcontrib>Champolivier, Luc</creatorcontrib><creatorcontrib>Debaeke, Philippe</creatorcontrib><creatorcontrib>Maury, Pierre</creatorcontrib><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>Frontiers in plant science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lamichhane, Jay Ram</au><au>Aubertot, Jean-Noël</au><au>Champolivier, Luc</au><au>Debaeke, Philippe</au><au>Maury, Pierre</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean</atitle><jtitle>Frontiers in plant science</jtitle><date>2020-09-02</date><risdate>2020</risdate><volume>11</volume><spage>558855</spage><epage>558855</epage><pages>558855-558855</pages><issn>1664-462X</issn><eissn>1664-462X</eissn><abstract>Soybean emergence and yield may be affected by many factors. A better understanding of the cultivar x sowing date x environment interactions could shed light into the competitiveness of soybean with other crops, notably, to help manage major biotic and abiotic factors that limit soybean production. We conducted a 2-year field experiments to measure emergence dynamics and final rates of three soybean cultivars from different maturity groups, with early and conventional sowing dates and across three locations. We also measured germination parameter values of the three soybean cultivars from different maturity groups under controlled experiments to parametrize the SIMPLE crop emergence model. This allowed us to assess the prediction quality of the model for emergence rates and to perform simulations. Final emergence rates under field conditions ranged from 62% to 92% and from 51% to 94% for early and conventional sowing, respectively. The model finely predicted emergence courses and final rates (root mean square error of prediction (RMSEP), efficiency (EF), and mean deviation (MD) ranging between 2% to 18%, 0.46% to 0.99%, and −10% to 15%, respectively) across a wide range of the sowing conditions tested. Differences in the final emergence rates were found, not only among cultivars but also among locations for the same cultivar, although no clear trend or consistent ranking was found in this regard. Modeling suggests that seedling mortality rates were dependent on the soil type with up to 35% and 14% of mortality in the silty loam soil, due to a soil surface crust and soil aggregates, respectively. Non-germination was the least important cause of seedling mortality in all soil types (up to 3% of emergence losses), while no seedling mortality due to drought was observed. The average grain yield ranged from 3.1 to 4.0 t ha −1 , and it was significantly affected by the irrigation regime (p < 0.001) and year (p < 0.001) but not by locations, sowing date or cultivars. We conclude that early sowing is unlikely to affect soybean emergence in</abstract><pub>Frontiers</pub><pmid>32983214</pmid><doi>10.3389/fpls.2020.558855</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0001-6048-1553</orcidid><orcidid>https://orcid.org/0000-0002-1271-2334</orcidid><orcidid>https://orcid.org/0000-0001-9780-0941</orcidid><orcidid>https://orcid.org/0000-0002-4173-8170</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1664-462X |
ispartof | Frontiers in plant science, 2020-09, Vol.11, p.558855-558855 |
issn | 1664-462X 1664-462X |
language | eng |
recordid | cdi_doaj_primary_oai_doaj_org_article_ff4d4d406c054ddd83f047de6a7141dd |
source | PubMed Central |
subjects | crop emergence genotype x environment interactions Glycine max Life Sciences non-emergence causes Plant Science seedbed conditions seedling mortality |
title | Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-03T15%3A41%3A05IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Combining%20Experimental%20and%20Modeling%20Approaches%20to%20Understand%20Genotype%20x%20Sowing%20Date%20x%20Environment%20Interaction%20Effects%20on%20Emergence%20Rates%20and%20Grain%20Yield%20of%20Soybean&rft.jtitle=Frontiers%20in%20plant%20science&rft.au=Lamichhane,%20Jay%20Ram&rft.date=2020-09-02&rft.volume=11&rft.spage=558855&rft.epage=558855&rft.pages=558855-558855&rft.issn=1664-462X&rft.eissn=1664-462X&rft_id=info:doi/10.3389/fpls.2020.558855&rft_dat=%3Cproquest_doaj_%3E2446992632%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c473t-caddcb0ec240aec7ac4418581b1453bd959e977b4e437da0d7ee1be02b0df5f13%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2446992632&rft_id=info:pmid/32983214&rfr_iscdi=true |