A New Approach to Select Doubled Haploid Rice Lines under Salinity Stress Using Indirect Selection Index

doi:10.1016/j.rsci.2021.05.007

Abstract

Abstract:

This study determined the indirect selection index of doubled haploid (DH) rice using a multivariate analysis approach to select lines adaptive to salinity stress, comprising three experiments. The first experiment involved the selection of good agronomic characters in a field experiment conducted at an experimental station in Bogor, Indonesia. The second experiment involved salinity tolerance screening through hydroponic cultures using 0 and 120 mmol/L NaCl, conducted at a greenhouse in Bogor. The third experiment involved the validation of the indirect adaptability selection index (IASI) through a field experiment in Sukra (saline area). Field experiments followed a randomized complete block design (RCBD), whereas an RCBD nested factorial design was used for the greenhouse experiment. The first and second experiments used 56 DH lines and four check varieties with three replications. In the second experiment, Pokkali and IR29 varieties were also added as tolerant and sensitive checks of salinity, respectively. The third experiment used 28 selected DH lines, Inpari 29 and one sensitive DH line. The good agronomic index (GAI) was 0.465 yield + 0.433 number of productive tillers + 0.31 number of filled grains. This generated 24 DH rice lines with good agronomic traits. The salinity tolerance index (SaTI) was developed through the average of standardized salinity tolerance score and salinity selection index based on discriminant analysis. This generated 34 DH rice lines with good salinity stress tolerance. The IASI (IASI = GAI - SaTI) selected 28 DH rice lines adaptive to salinity stress and it was considered effective by Sukra validation.

Key words: adaptability to salinity, doubled haploid, multivariate analysis, rice, selection index

Fuad Anshori Muhammad, Sapta Purwoko Bambang, Saraswati Dewi Iswari, Wahyuning Ardie Sintho, Bayuardi Suwarno Willy. A New Approach to Select Doubled Haploid Rice Lines under Salinity Stress Using Indirect Selection Index[J]. Rice Science, 2021, 28(4): 368-378.

Figures/Tables 14

References 54

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Character	NTT	NPT	GPH	DF	FLL	PL	NFG	NTG
NTT	0.02	0.39	0.01	0.00	0.00	-0.07	0.00	0.01
NPT	0.02	0.52	0.03	-0.14	0.02	-0.06	-0.06	0.02
GPH	0.00	-0.12	-0.13	0.23	0.06	0.16	0.36	-0.04
DF	0.00	-0.20	-0.08	0.37	0.00	0.06	0.29	-0.04
FLL	0.00	0.09	-0.07	-0.01	0.11	0.20	0.18	-0.02
PL	-0.01	-0.10	-0.07	0.08	0.07	0.29	0.24	-0.03
NFG	0.00	-0.06	-0.10	0.22	0.04	0.15	0.47	-0.04
NTG	0.00	-0.24	-0.09	0.29	0.03	0.19	0.36	-0.05

Character	NTT	NPT	GPH	DF	FLL	PL	NFG	NTG
NTT	0.02	0.39	0.01	0.00	0.00	-0.07	0.00	0.01
NPT	0.02	0.52	0.03	-0.14	0.02	-0.06	-0.06	0.02
GPH	0.00	-0.12	-0.13	0.23	0.06	0.16	0.36	-0.04
DF	0.00	-0.20	-0.08	0.37	0.00	0.06	0.29	-0.04
FLL	0.00	0.09	-0.07	-0.01	0.11	0.20	0.18	-0.02
PL	-0.01	-0.10	-0.07	0.08	0.07	0.29	0.24	-0.03
NFG	0.00	-0.06	-0.10	0.22	0.04	0.15	0.47	-0.04
NTG	0.00	-0.24	-0.09	0.29	0.03	0.19	0.36	-0.05

Predictors	Estimate	Standard Error	T-value	Probability (>\|t\|)
Intercept	-531.13	99.96	-5.313	1.93e-06^***
Number of productive tillers	32.64	4.26	7.659	2.82e-10^***
Number of filled grain	3.09	0.87	3.553	0.000781^***
Number of total grain	1.86	0.49	3.803	0.000355^***

Predictors	Estimate	Standard Error	T-value	Probability (>\|t\|)
Intercept	-531.13	99.96	-5.313	1.93e-06^***
Number of productive tillers	32.64	4.26	7.659	2.82e-10^***
Number of filled grain	3.09	0.87	3.553	0.000781^***
Number of total grain	1.86	0.49	3.803	0.000355^***

Parameter	PC1	PC2	PC3	PC4	PC5	PC6	PC7	PC8	PC9	PC10
VPH	0.275	-0.031	0.481	-0.207	0.196	0.288	-0.007	-0.403	0.302	-0.200
NTT	-0.151	-0.404	-0.290	0.330	0.107	0.479	0.501	0.161	0.208	-0.233
NPT	-0.224	-0.433	0.026	0.316	0.003	-0.031	-0.175	-0.434	-0.581	0.142
GPH	0.328	-0.198	-0.019	-0.322	0.259	0.458	0.025	-0.156	-0.258	0.295
DF	0.280	-0.026	-0.509	-0.125	0.127	0.075	-0.220	0.240	0.077	0.473
FLL	0.190	-0.329	0.422	0.168	0.314	-0.069	-0.291	0.647	-0.145	-0.147
PL	0.322	-0.118	0.290	0.255	-0.055	-0.367	0.565	-0.026	0.111	0.514
TGW	0.248	0.248	0.190	0.228	-0.668	0.483	-0.033	0.188	-0.247	0.053
NFG	0.276	-0.310	-0.145	-0.386	-0.287	-0.242	0.204	0.030	-0.243	-0.338
NUG	0.355	0.181	-0.195	0.262	0.150	-0.073	-0.014	-0.106	-0.053	-0.230
NTG	0.388	-0.030	-0.209	-0.014	-0.040	-0.174	0.093	-0.060	-0.166	-0.328
Yield	0.180	-0.465	-0.084	0.171	-0.376	-0.065	-0.446	-0.181	0.521	0.026
SD	2.44	1.68	1.32	0.98	0.75	0.61	0.44	0.39	0.31	0.29
Proportion cumulative	0.46	0.67	0.81	0.88	0.93	0.95	0.97	0.98	0.99	1.00
Eigenvalue	5.94	2.83	1.75	0.96	0.56	0.37	0.19	0.15	0.10	0.09