Bayesian functional regression as an alternative statistical analysis of high-throughput phenotyping data of modern agriculture

Table 3 Prediction accuracy of grain yield with Pearson’s correlation for the 7 proposed methods with BRR prior distribution for different numbers of periods for the Fourier basis

Period	M3			M5			M7
Period	Mean		SE	Mean		SE	Mean		SE
51	0.4609	a	0.0224	0.4607	a	0.0219	0.4616	a	0.0218
57.38	0.4658	a	0.0211	0.4655	a	0.0213	0.4658	a	0.0214
65.57	0.4639	a	0.0201	0.4623	a	0.0206	0.4636	a	0.02
76.5	0.4706	a	0.0219	0.4666	a	0.0214	0.4705	a	0.0217
91.8	0.4757	a	0.019	0.4755	a	0.0192	0.4755	a	0.0191
114.75	0.4636	a	0.0204	0.4631	a	0.0202	0.4638	a	0.0201
153	0.4854	a	0.0276	0.4851	a	0.0275	0.4853	a	0.0276
229.5	0.4726	a	0.0214	0.4732	a	0.0213	0.4727	a	0.0214
459	0.4935	a	0.0238	0.4936	a	0.0239	0.4931	a	0.0239

Mean is the average Pearson’s correlation and SE is the standard error. Different letters by the columns indicate statistical differences between periods with the Tukey test at 5% level of significance

ISSN: 1746-4811