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. 2020 Aug 7;10:13382. doi: 10.1038/s41598-020-70267-9

Table 1.

Environmental means, Root Mean Squared Error (RMSE) and the Pearson correlation between predicted and observed days to heading (DTH) for 112 rice genotypes tested in 51 environments in Japan.

CV00 CV0
Mean RMSE Corr Mean RMSE Corr
Real CB GS CB GS CB GS C C C
Tsukubamirai 2004 Late 79.4 76.7 85.9 7.0 12.6 0.86 0.70 76.3 4.6 0.99
Tsukubamirai 2004 Early 87.5 93.2 84.1 10.0 12.9 0.84 0.55 92.2 6.4 0.97
Tsukubamirai 2005 Early 98.5 102.1 87.1 6.9 14.0 0.87 0.75 101.0 3.5 0.98
Tsukubamirai 2005 Late 76.7 74.8 84.8 5.7 12.4 0.86 0.68 73.7 3.4 0.99
Kasai 2006 87.4 83.8 88.3 7.9 8.8 0.85 0.75 82.8 6.8 0.93
Fukuyama 2006 80.6 83.0 82.5 5.6 13.4 0.87 0.29 82.0 2.0 0.99
Fukuyama 2007 84.1 83.4 86.6 5.0 6.1 0.87 0.84 82.5 2.9 0.98
Tsukuba 2008 104.5 107.7 87.2 9.1 19.2 0.87 0.85 107.3 4.0 0.98
Kasai1st 2008 102.2 99.9 88.7 9.0 17.8 0.89 0.71 99.2 4.3 0.99
Fukuyama 2008 77.8 82.2 85.6 7.8 11.1 0.86 0.77 81.3 4.5 0.98
Tsukuba 2009 103.9 107.7 87.1 8.6 19.0 0.89 0.81 108.0 5.2 0.98
Kasai1st 2009 101.9 100.6 89.4 7.6 15.1 0.89 0.83 100.0 2.7 0.99
Fukuyama 2009 78.7 78.7 89.6 5.2 13.2 0.86 0.83 77.8 1.5 0.99
Tsukuba 2010 Late 83.5 89.1 88.9 8.4 11.1 0.86 0.66 88.4 5.9 0.97
Kasai1st 2010 100.6 100.7 89.5 7.1 14.3 0.88 0.77 100.1 1.9 0.99
Fukuyama 2010 76.2 79.5 88.2 5.9 15.3 0.86 0.50 78.1 2.6 0.99
Fukuyama 2010 Late 59.0 65.4 87.7 9.2 29.7 0.84 0.82 62.5 4.2 0.96
Tsukuba 2011 Early 105.9 109.9 85.5 9.9 23.9 0.87 0.66 109.9 5.3 0.98
Tsukuba 2011 Late 82.8 80.8 90.0 5.9 11.9 0.86 0.78 80.4 4.1 0.95
Tsukuba 2011 Middle 94.7 95.7 90.9 6.5 11.1 0.88 0.67 95.4 3.0 0.98
Kasai 2011 101.4 100.6 89.3 7.8 15.7 0.89 0.76 100.0 2.4 0.99
Fukuyama 2011 75.7 79.4 91.1 6.4 16.9 0.87 0.83 78.6 3.1 0.99
Fukuyama 2011 Late 66.4 72.7 97.9 8.9 32.4 0.68 0.58 66.2 2.9 0.95
Tsukuba 2012 Early 97.1 96.0 86.9 5.7 12.4 0.81 0.74 101.1 5.8 0.97
Tsukuba 2012 Late 84.3 81.6 88.2 6.1 7.5 0.86 0.80 81.0 4.3 0.96
Tsukuba 2012 Middle 92.6 95.4 88.4 6.3 8.3 0.87 0.82 94.8 3.7 0.97
Kasai 2012 103.8 102.7 86.4 7.9 21.3 0.89 0.60 102.1 2.7 0.99
Fukuyama 2012 75.2 78.8 89.9 6.2 16.3 0.87 0.83 78.0 3.1 0.99
Fukuyama 2012 Late 71.5 77.0 103.1 7.5 32.4 0.70 0.66 68.6 3.4 0.98
Fukuoka 2012 79.6 76.0 89.1 6.7 13.0 0.84 0.69 75.4 5.2 0.96
Akita 2012 113.1 115.9 90.1 8.3 26.1 0.86 0.54 114.5 2.8 0.98
Kasai 2013 104.8 104.1 87.3 8.0 20.1 0.90 0.80 103.5 3.2 0.98
Fukuyama 2013 74.9 80.1 89.4 7.4 16.3 0.87 0.82 79.3 4.6 0.99
Fukuyama 2013 Late 62.1 64.8 85.7 6.3 27.1 0.83 0.36 64.1 3.6 0.93
Fukuoka 2013 77.4 77.3 93.3 5.7 17.5 0.86 0.77 76.7 1.9 0.99
Akita 2013 116.6 115.8 91.1 8.5 28.1 0.88 0.66 115.1 2.4 0.99
Kasai 2014 102.4 105.1 88.9 8.4 18.0 0.90 0.66 104.4 2.8 0.99
Fukuyama 2014 79.6 82.1 87.9 5.9 12.1 0.88 0.68 81.3 2.1 0.99
Fukuyama 2014 Late 67.6 64.5 88.1 6.7 21.4 0.83 0.79 62.9 5.1 0.98
Fukuoka 2014 81.8 77.7 80.4 6.7 11.5 0.87 0.45 77.1 5.4 0.97
Akita 2014 115.2 116.2 89.6 9.2 28.5 0.88 0.68 115.6 2.2 0.99
Fukuyama 2015 76.3 72.6 88.1 6.5 14.4 0.86 0.63 71.9 4.6 0.99
Akita 2015 118.1 119.8 89.4 7.7 29.9 0.81 0.76 117.6 2.5 0.99
Kasai 2016 102.3 101.2 85.6 7.2 20.4 0.90 0.61 100.7 3.1 0.98
Fukuyama 2016 79.1 81.1 85.2 6.0 8.9 0.86 0.82 80.8 2.4 0.99
Fukuyama 2016 Late 67.5 65.2 89.6 6.8 26.1 0.79 0.63 64.6 4.5 0.95
Tsukubamirai 2016 Late 73.6 77.9 84.6 7.0 13.6 0.90 0.80 77.2 4.9 0.98
Kasai 2017 108.6 106.2 85.7 8.3 26.3 0.89 0.56 105.5 4.3 0.98
Fukuyama 2017 77.4 80.2 87.7 6.3 16.3 0.88 0.42 79.6 2.7 0.99
Fukuyama 2017 Late 68.4 67.7 88.8 6.0 22.9 0.82 0.69 67.0 3.0 0.97
Tsukubamirai 2017 Late 69.5 73.1 86.9 6.8 19.8 0.87 0.65 72.2 4.3 0.98
Mean 7.2 17.5 0.86 0.69 3.7 0.98

Two cross-validation schemes were implemented for mimicking realistic prediction scenarios: CV0 corresponds to the scenario of predicting tested genotypes in unobserved environments; CV00 considers the prediction of untested genotypes in unobserved environments. For CV0, the C method was used combining phenotypic and day length information (DL) of genotypes tested in other environments (one at a time). For CV00, two methods were considered: (i) the conventional GS implementation; and (ii) the CB method, which combines phenotypic and DL information from tested genotypes (training set) and genomic BLUP values g^ from untested genotypes (testing set). In both cases, the prediction procedure was conducted by leaving one genotype out across environments and by deleting all phenotypic information from the target environment.