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Exploring long-term variety performance trials to improve environment-specific genotype x management recommendations: A case-study for winter wheat

dc.contributor.authorMunaro, L. B. [UNESP]
dc.contributor.authorHefley, T. J.
dc.contributor.authorDeWolf, E.
dc.contributor.authorHaley, S.
dc.contributor.authorFritz, A. K.
dc.contributor.authorZhang, G.
dc.contributor.authorHaag, L. A.
dc.contributor.authorSchlegel, A. J.
dc.contributor.authorEdwards, J. T.
dc.contributor.authorMarburger, D.
dc.contributor.authorAlderman, P.
dc.contributor.authorJones-Diamond, S. M.
dc.contributor.authorJohnson, J.
dc.contributor.authorLingenfelser, J. E.
dc.contributor.authorUneda-Trevisoli, S. H. [UNESP]
dc.contributor.authorLollato, R. P.
dc.contributor.institutionKansas State Univ
dc.contributor.institutionColorado State Univ
dc.contributor.institutionOklahoma State Univ
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-12-10T20:07:09Z
dc.date.available2020-12-10T20:07:09Z
dc.date.issued2020-09-15
dc.description.abstractThe complex and interactive effects of genotype (G), environment (E), and management (M) can be a barrier to the development of sound agronomic recommendations. We hypothesize that long-term variety performance trials (VPT) can be used to understand these effects and improve regional recommendations. Our objective was to explore long-term VPT data to improve management and variety-selection recommendations using winter wheat (Triticum aestivum L.) in the U.S. central Great Plains as a case-study. Data of grain yield, variety, and trial management were collected from 748 wheat VPT conducted in the states of Colorado, Kansas, and Oklahoma over nineteen harvest years (2000-2018) and 92 locations, resulting in 97,996 yield observations. Using 30-yr cumulative annual precipitation and growing degrees days, we partitioned the study region into 11 contiguous sub-regions, which we refer to as growing adaptation regions (GAR). We used variance component analysis, gradient boosted trees, and conditional inference trees to explore the management and variety trait effects within each GAR. For the variety trait analysis, the VPT dataset was reduced to account for varieties for which 17 agronomic traits and 11 disease/insect reaction ratings were available (65,264 yield observations). GAR accounted for 46 % of the total variation in grain yield, M for 32 %, residuals (including interactions) for 13 %, year for 7 %, and G for 2 %. Conditional inference trees identified interactions among management practices and their effects on yield within each GAR. For instance, water regime was the most important practice influencing wheat yield in the semi-arid western portion of the study region, followed by sowing date and fungicide. In dryland trials, there was typically an interaction between fungicide, sowing date, and tillage system, depending on GAR. Other management practices (e.g. dual-purpose management, crop rotation, and tillage practice) also significantly affected yield, depending on GAR. The main variety trait associated with increased yields depended on region and management combination. For instance, drought tolerance was the most important trait in dryland trials while stripe rust tolerance was more relevant in irrigated trials in the semi-arid region. In this research, we demonstrated an approach that uses widely available long-term VPT data to improve management and variety selection recommendations and can be used in other regions and crops for which long-term VPT data are available.en
dc.description.affiliationKansas State Univ, Dept Agron, Manhattan, KS 66506 USA
dc.description.affiliationKansas State Univ, Dept Stat, Manhattan, KS 66506 USA
dc.description.affiliationKansas State Univ, Dept Plant Pathol, Throckmorton Hall, Manhattan, KS 66506 USA
dc.description.affiliationColorado State Univ, Dept Soil & Crop Sci, Ft Collins, CO 80523 USA
dc.description.affiliationOklahoma State Univ, Dept Plant & Soil Sci, Stillwater, OK 74078 USA
dc.description.affiliationSao Paulo State Univ, Dept Crop Prod, Jaboticabal, SP, Brazil
dc.description.affiliationUnespSao Paulo State Univ, Dept Crop Prod, Jaboticabal, SP, Brazil
dc.description.sponsorshipKansas Wheat Alliance
dc.description.sponsorshipKansas Agricultural Experiment Station (KAES)
dc.description.sponsorshipIdKansas Wheat Alliance: GAGR004805BG5828
dc.format.extent15
dc.identifierhttp://dx.doi.org/10.1016/j.fcr.2020.107848
dc.identifier.citationField Crops Research. Amsterdam: Elsevier, v. 255, 15 p., 2020.
dc.identifier.doi10.1016/j.fcr.2020.107848
dc.identifier.issn0378-4290
dc.identifier.urihttp://hdl.handle.net/11449/197130
dc.identifier.wosWOS:000554909300004
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.ispartofField Crops Research
dc.sourceWeb of Science
dc.subjectG x E x M
dc.subjectLong-term data
dc.subjectExploratory analysis
dc.subjectConditional inference trees
dc.subjectManagement practices
dc.titleExploring long-term variety performance trials to improve environment-specific genotype x management recommendations: A case-study for winter wheaten
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dcterms.rightsHolderElsevier B.V.
dspace.entity.typePublication
unesp.departmentProdução Vegetal - FCAVpt

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