Dataset Information

Evaluation of genotype by environment interaction and adaptability in lowland irrigated rice hybrids for grain yield under high temperature.

ABSTRACT: Recent predictions on climate change indicate that high temperature episodes are expected to impact rice production and productivity worldwide. The present investigation was undertaken to assess the yield stability of 72 rice hybrids and their parental lines across three temperature regimes over two consecutive dry seasons using the additive main effect and multiplicative interaction (AMMI), genotype and genotype × environment interaction (GGE) stability model analysis. The combined ANOVA revealed that genotype × environment interaction (GEI) were significant due to the linear component for most of the traits studied. The AMMI and GGE biplot explained 57.2% and 69% of the observed genotypic variation for grain yield, respectively. Spikelet fertility was the most affected yield contributing trait and in contrast, plant height and tiller numbers were the least affected traits. In case of spikelet fertility, grain yield and other yield contributing traits, male parent contributed towards heat tolerance of the hybrids compared to the female parent. The parental lines G74 (IR58025B), G83 (IR40750R), G85 (C20R) and hybrids [G21 (IR58025A × KMR3); G3 (APMS6A × KMR3); G57 (IR68897A × KMR3) and G41 (IR79156A × RPHR1005)] were the most stable across the environments for grain yield. They can be considered as potential genotypes for cultivation under high temperature stress after evaluating under multi location trials.

SUBMITTER: Senguttuvel P

PROVIDER: S-EPMC8338964 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Evaluation of genotype by environment interaction and adaptability in lowland irrigated rice hybrids for grain yield under high temperature.

Senguttuvel P P Sravanraju N N Jaldhani V V Divya B B Beulah P P Nagaraju P P Manasa Y Y Prasad A S Hari ASH Brajendra P P Gireesh C C Anantha M S MS Suneetha K K Sundaram R M RM Madhav M Sheshu MS Tuti M D MD Subbarao L V LV Neeraja C N CN Bhadana V P VP Rao P R PR Voleti S R SR Subrahmanyam D D

Scientific reports 20210804 1

Recent predictions on climate change indicate that high temperature episodes are expected to impact rice production and productivity worldwide. The present investigation was undertaken to assess the yield stability of 72 rice hybrids and their parental lines across three temperature regimes over two consecutive dry seasons using the additive main effect and multiplicative interaction (AMMI), genotype and genotype × environment interaction (GGE) stability model analysis. The combined ANOVA reveal ...[more]

PMID: 34349182

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Project description:Multi environment testing helps identify stable genotypes especially for adverse abiotic stress situations. In the era of climate change and multiple abiotic stresses, it becomes important to analyze stability of rice lines under both irrigated and stress conditions. Mutants are an important genetic resource which can help in revealing the basis of natural variation. We analyzed 300 EMS induced mutants of aus rice cultivar Nagina22 (N22) for their G × E interaction and stability under low phosphorus (P), water limited and irrigated conditions. Environmental effect and interaction were more significant than genotypic contribution on grain yield (GY), productive tillers (TN) and plant height (PH) under these three environmental conditions in dry season, 2010. GY and TN were more affected by low P stress than by water limited condition, but PH was not significantly different under these two stresses. Mutants G17, G209, G29, G91, G63 and G32 were stable for GY in decreasing order of stability across the three environments but G254 and G50 were stable only in low P, G17 and G45 only in water limited and G295 and G289 only in normal irrigated condition. We then selected and evaluated 3 high yielding mutants, 3 low yielding mutants and N22 for their stability and adaptability to these 3 environments in both wet and dry seasons for six years (2010-2015). The most stable lines based on the combined analysis of 12 seasons were G125 (NH210) under normal condition, G17 (NH686), G176 (NH363) and G284 (NH162) in low P condition and G176 (NH363) under water limited condition. G176 was the best considering all 3 conditions. When screened for 15 Pup1 gene-specific markers, G176 showed alleles similar to N22. While two other low-P tolerant lines G17 and G65 showed N22 similar alleles only at k-1 and k-5 but a different allele or null allele at 13 other loci. These stable mutants are a valuable resource for varietal development and to discover genes for tolerance to multiple abiotic stresses.

Project description:IntroductionApproximately 50% of irrigation water is saved during drip-irrigation of rice, which has tremendous potential for water-saving agriculture, particularly in areas where water resources are scarce. However, the grain yield and quality of drip-irrigated rice are adversely affected.MethodsIn this study, we investigated the effects of different irrigation strategies on the grain yield and quality of drip-irrigated rice using field experiments. Four irrigation treatments were studied: whole growing season flooding (FI), whole growing season normal drip irrigation (DI, soil relative moisture (RSM) was maintained in the range of 90-100%), pre-anthesis drip irrigation and post-anthesis water stress (SAF, the RSM was maintained in the range of 80-90% after anthesis), pre-anthesis drip irrigation, and post-anthesis flooding (FAF).ResultsThe results showed that grain yield, harvest index, seed setting rate and 1000 grain weight in DI and SAF were significantly lower than in FI and FAF. These parameters were not significantly different between FI and FAF but were significantly greater in DI than in SAF. Compared with FI and FAF, the source capacity, source activity time, and sink activity of DI and SAF decreased, and the sink-source difference increased. The sink-source difference had a significant negative correlation with rice yield and 1000 grain weight. The activities of ADP-glucose pyrophosphorylase, starch branching enzyme, and amylopectin content in grains in the middle panicles of FAF were significantly higher than those of DI and SAF. SAF resulted in increased amylose/amylopectin ratio and total protein content in grains but decreased proportion of glutenin in total protein. Irrigation after anthesis of drip-irrigated rice narrowed the difference between sink sources in rice plants, increased the grain yield and harvest index by 29.2% and 11%, respectively, compared to DI, increased water productivity by 19% compared to FI, and improved the grain quality of drip-irrigated rice.DiscussionThis study highlights that post-anthesis sufficient irrigation of drip-irrigated rice plays a positive role in maintaining the source-sink balance. This study serves as a foundation for the development of more effective rice farming methods that conserve water, while increasing the grain yield and quality of drip-irrigated rice.

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Project description:Multi-parent Advanced Generation Inter-crosses (MAGIC) lines have mosaic genomes that are generated shuffling the genetic material of the founder parents following pre-defined crossing schemes. In cereal crops, these experimental populations have been extensively used to investigate the genetic bases of several traits and dissect the genetic bases of epistasis. In plants, genomic prediction models are usually fitted using either diverse panels of mostly unrelated accessions or individuals of biparental families and several empirical analyses have been conducted to evaluate the predictive ability of models fitted to these populations using different traits. In this paper, we constructed, genotyped and evaluated a barley MAGIC population of 352 individuals developed with a diverse set of eight founder parents showing contrasting phenotypes for grain yield. We combined phenotypic and genotypic information of this MAGIC population to fit several genomic prediction models which were cross-validated to conduct empirical analyses aimed at examining the predictive ability of these models varying the sizes of training populations. Moreover, several methods to optimize the composition of the training population were also applied to this MAGIC population and cross-validated to estimate the resulting predictive ability. Finally, extensive phenotypic data generated in field trials organized across an ample range of water regimes and climatic conditions in the Mediterranean were used to fit and cross-validate multi-environment genomic prediction models including G×E interaction, using both genomic best linear unbiased prediction and reproducing kernel Hilbert space along with a non-linear Gaussian Kernel. Overall, our empirical analyses showed that genomic prediction models trained with a limited number of MAGIC lines can be used to predict grain yield with values of predictive ability that vary from 0.25 to 0.60 and that beyond QTL mapping and analysis of epistatic effects, MAGIC population might be used to successfully fit genomic prediction models. We concluded that for grain yield, the single-environment genomic prediction models examined in this study are equivalent in terms of predictive ability while, in general, multi-environment models that explicitly split marker effects in main and environmental-specific effects outperform simpler multi-environment models.

Dataset Information

Evaluation of genotype by environment interaction and adaptability in lowland irrigated rice hybrids for grain yield under high temperature.

Publications

Evaluation of genotype by environment interaction and adaptability in lowland irrigated rice hybrids for grain yield under high temperature.

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