Deriving genetic coefficients from variety trials to determine sorghum hybrid performance using the CSM‐CERES‐Sorghum model

2021 ◽  
Author(s):  
Xi Liang ◽  
Gerrit Hoogenboom ◽  
Stamatia Voulgaraki ◽  
Kenneth J. Boote ◽  
George Vellidis
Keyword(s):  
Hybrid Performance ◽  
Variety Trials

University of Florida Potato Variety Trials Spotlight: ‘LaChipper’

EDIS ◽  
2017 ◽  
Vol 2017 (4) ◽  
Author(s):  
Rodrick Z. Mwatuwa ◽  
Christian T. Christensen ◽  
Pam Solano ◽  
Lincoln Zotarelli
Keyword(s):  
Potato Variety ◽  
University Of Florida ◽  
Variety Trials

by Rodrick Z. Mwatuwa, Christian T. Christensen, Pam Solano, and Lincoln Zotarelli http://edis.ifas.ufl.edu/hs1297

Efficiency of Spatial Analyses of Field Pea Variety Trials

Crop Science ◽  
2004 ◽  
Vol 44 (1) ◽  
pp. 49 ◽  
Author(s):  
Rong-Cai Yang ◽  
Terrance Z. Ye ◽  
Stanford F. Blade ◽  
Manjula Bandara
Keyword(s):  
Field Pea ◽  
Spatial Analyses ◽  
Variety Trials

Block designs for variety trials

1978 ◽  
Vol 90 (2) ◽  
pp. 395-400 ◽  
Author(s):  
H. D. Patterson ◽  
E. R. Williams ◽  
E. A. Hunter
Keyword(s):  
Block Designs ◽  
Incomplete Block ◽  
Variety Trials ◽  
Rectangular Lattices

SummaryIn this paper we present a series of resolvable incomplete block designs suitable for variety trials with any number of varieties v in the range 20 ≤v ≤ 100. These designs usefully supplement existing square and rectangular lattices. They are not necessarily optimal in the sense of having smallest possible variances but their efficiencies are known to be high.

scholarly journals Multi-omics-based prediction of hybrid performance in canola

2021 ◽  
Author(s):  
Dominic Knoch ◽  
Christian R. Werner ◽  
Rhonda C. Meyer ◽  
David Riewe ◽  
Amine Abbadi ◽  
...  
Keyword(s):  
Hilbert Space ◽  
Genetic Markers ◽  
Reproducing Kernel ◽  
Prediction Models ◽  
Agronomic Traits ◽  
Reproducing Kernel Hilbert Space ◽  
Hybrid Performance ◽  
Hybrid Prediction ◽  
Gaussian Kernels ◽  
Breeding Programmes

Abstract Key message Complementing or replacing genetic markers with transcriptomic data and use of reproducing kernel Hilbert space regression based on Gaussian kernels increases hybrid prediction accuracies for complex agronomic traits in canola. In plant breeding, hybrids gained particular importance due to heterosis, the superior performance of offspring compared to their inbred parents. Since the development of new top performing hybrids requires labour-intensive and costly breeding programmes, including testing of large numbers of experimental hybrids, the prediction of hybrid performance is of utmost interest to plant breeders. In this study, we tested the effectiveness of hybrid prediction models in spring-type oilseed rape (Brassica napus L./canola) employing different omics profiles, individually and in combination. To this end, a population of 950 F1 hybrids was evaluated for seed yield and six other agronomically relevant traits in commercial field trials at several locations throughout Europe. A subset of these hybrids was also evaluated in a climatized glasshouse regarding early biomass production. For each of the 477 parental rapeseed lines, 13,201 single nucleotide polymorphisms (SNPs), 154 primary metabolites, and 19,479 transcripts were determined and used as predictive variables. Both, SNP markers and transcripts, effectively predict hybrid performance using (genomic) best linear unbiased prediction models (gBLUP). Compared to models using pure genetic markers, models incorporating transcriptome data resulted in significantly higher prediction accuracies for five out of seven agronomic traits, indicating that transcripts carry important information beyond genomic data. Notably, reproducing kernel Hilbert space regression based on Gaussian kernels significantly exceeded the predictive abilities of gBLUP models for six of the seven agronomic traits, demonstrating its potential for implementation in future canola breeding programmes.

Breeding Tetraploid Paspalum simplex : Hybridization, Early Identification of Apomicts, and Impact of Apomixis on Hybrid Performance

Crop Science ◽  
2019 ◽  
Vol 59 (4) ◽  
pp. 1617-1624 ◽  
Author(s):  
E. A. Brugnoli ◽  
E. J. Martínez ◽  
S. C. Ferrari Usandizaga ◽  
A. L. Zilli ◽  
M. H. Urbani ◽  
...  
Keyword(s):  
Early Identification ◽  
Hybrid Performance ◽  
Paspalum Simplex

scholarly journals Evaluating Hybrid Bermudagrass Using Spectral Reflectance under Different Mowing Heights and Trinexapac-ethyl Applications

2017 ◽  
Vol 27 (1) ◽  
pp. 45-53 ◽  
Author(s):  
Dana Sullivan ◽  
Jing Zhang ◽  
Alexander R. Kowalewski ◽  
Jason B. Peake ◽  
William F. Anderson ◽  
...  
Keyword(s):  
Spectral Reflectance ◽  
Management Practices ◽  
Cynodon Dactylon ◽  
Functional Performance ◽  
Lignin Content ◽  
Vegetation Indices ◽  
Variety Trials ◽  
Fiber Analysis ◽  
Green Cover ◽  
Aesthetic Performance

Quantitative spectral reflectance data have the potential to improve the evaluation of turfgrasses in variety trials when management practices are factors in the testing of turf aesthetics and functionality. However, the practical application of this methodology has not been well developed. The objectives of this research were 1) to establish a relationship between spectral reflectance and turfgrass quality (TQ) and percent green cover (PGC) using selected reference plots; 2) to compare aesthetic performance (TQ, PGC, and vegetation indices) and functional performance (surface firmness); and 3) to evaluate lignin content as an alternate means to predict surface firmness in turfgrass variety trials of hybrid bermudagrass [Cynodon dactylon × C. transvaalensis]. A field study was conducted on mature stands of three varieties (‘TifTuf’, ‘TifSport’, and ‘Tifway’) and two experimental lines (04-47 and 04-76) at two mowing heights (0.5 and 1.5 inch) and trinexapac-ethyl application (0.15 kg·ha−1 and nontreated control) treatments. Aesthetic performance was estimated by vegetation indices, spectral reflectance, visual TQ, and PGC. The functional performance of each variety/line was measured through surface firmness and fiber analysis. Regression analyses were similar when using only reference plots or all the plots to determine the relationship between individual aesthetic characteristics. Experimental line 04-47 had lower density in Apr. 2010, whereas varieties ‘TifTuf’, ‘TifSport’, and ‘Tifway’ were in the top statistical group for aesthetic performance when differences were found. ‘TifSport’ and ‘Tifway’ produced the firmest surfaces, followed by ‘TifTuf’, and finally 04-76 and 04-47, which provided the least firm surface. Results of leaf fiber analysis were not correlated with turf surface firmness. This study indicates that incorporating quantitative measures of spectral reflectance could reduce time and improve precision of data collection as long as reference plots with adequate range of green cover are present in the trials.

Hybrid performance and heterosis in strawberry (Fragaria × ananassaDuchesne), regarding acidity, soluble solids and dry matter content in fruits

2016 ◽  
Vol 135 (2) ◽  
pp. 232-238 ◽  
Author(s):  
Elżbieta Kaczmarska ◽  
Jacek Gawroński ◽  
Ewa Jabłońska-Ryś ◽  
Marta Zalewska-Korona ◽  
Wojciech Radzki ◽  
...  
Keyword(s):  
Dry Matter ◽  
Matter Content ◽  
Soluble Solids ◽  
Dry Matter Content ◽  
Hybrid Performance
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