000			03706nam a22003737a 4500
001			69657
003			MX-TxCIM
005			20251203103315.0
008			251201s2025 -uk||||| |||| 00| 0 eng d
040			_aMX-TxCIM
100	1		_aAtlin, G.N. _92252
245	1	0	_aEarly stage sparse testing can increase selection accuracy and genetic gain in plant breeding programmes
260			_aEdinburgh (CIMMYT) : _bEUCARPIA Biometrics in Plant Breeding Local Organising Committee, _c2025.
300			_a1 page
500			_aPresented at XIX Conference 2025, EUCARPIA: Biometrics Plant Breeding, 17-19 Sep, Edinburgh, UK.
520			_aLow-cost genome profiling allows information from relatives to be used to reduce replication of selection candidates while retaining selection accuracy, creating opportunities to redesign plant breeding pipelines. Early-stage sparse testing uses the genomic relationship matrix (GRM) to sample the target population of environments (TPE) more effectively by distributing related early-stage selection candidates across many testing locations to train a genomic selection (GS) model, rather than concentrating them in replicated trials at a few research stations. Using the GRM, data on related genotypes across farms can be connected and combined to enable genomic prediction across the entire TPE, not just a few sites. A similar redesign is possible in hybrid breeding programmes, where the GRM allows related selection candidates to be evaluated on several testers, permitting general combining ability (GCA) to be estimated early in the selection process. Simulations indicate that, if testing resources are held constant, sparse testing designs can increase selection accuracy both across environments and across testers. Apromising application of sparse testing is to move early-stage testing directly into farmers’ f ields. Most crop production in Sub-Saharan Africa (SSA) occurs on small farms characterized by low input use, multiple biotic and abiotic stresses, and diverse management factors. However, most CGIAR and national breeding programmes conduct early-stage phenotyping at only a few well-managed research stations. Early-stage on-farm sparse testing (OFST) addresses this issue by shifting the evaluation process from research stations to dozens or even hundreds of farms, treating each farm as an incomplete block. This can enhance genetic gain in farmers’ fields by increasing selection accuracy and intensity while shortening the generation interval. Early-stage OFST is currently being piloted in the CIMMYT maize and CIAT bean programmes in SSA.
546			_aText in English
600			_2
650		7	_aTesting _2AGROVOC _912144
650		7	_aGenetic gain _2AGROVOC _92091
650		7	_aPlant breeding _2AGROVOC _91203
650		7	_aBreeding programmes _2AGROVOC _921704
650		7	_aEarly selection _2AGROVOC _930704
700	1		_aBurgueño, J. _gGenetic Resources Program _8INT3239 _9907
700	0		_aTeshale Mamo _940793
700	1		_aBeyene, Y. _gGlobal Maize Program _8INT2891 _9870
700	1		_aDagne Wegary Gissa _gGlobal Maize Program _8INT3401 _9952
700	1		_aCairns, J.E. _gGlobal Maize Program _8INT2948 _9879
700	1		_8001712096 _aChivasa, W. _gGlobal Maize Program _919858
700	1		_aZaman-Allah, M. _gGlobal Maize Program _8I1705364 _9779
700	1		_8001712518 _aWerner, C.R. _gExcellence in Breeding _gBreeding Modernization and Innovation Platform _926661
773			_dEdinburgh (United Kingdom) : EUCARPIA Biometrics in Plant Breeding Local Organising Committee, 2025. _gp. 20 _tXIX Conference 2025 EUCARPIA, Biometrics In plant breeding, 17-19 Sep 2025 Edinburgh, UK. : Book of abstracts _w69661
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999			_c69657 _d69649