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. 2025 Oct 28;15(1):37674.
doi: 10.1038/s41598-025-21562-w.

Cold stress resilience in rice: genotypic variation, yield traits, and GGE biplot insights

Tanaya Bala  1 , Sarita Pradhan  2 , Twinkle Jena  3 , Sujatha Patta  4 , Simanta Mohanty  1 , Kamini Kaushal  5 , Megha Kumari  3 , Sandeep Kumar Mallik  1 , Manoj Kumar Rout  1
Affiliations

Cold stress resilience in rice: genotypic variation, yield traits, and GGE biplot insights

Tanaya Bala et al. Sci Rep. .

Abstract

Rice (Oryza sativa L.), a staple food for over half of the global population, is highly sensitive to low temperatures, particularly during early growth stages, resulting in significant yield losses. Addressing cold stress during the early stages of rice cultivation by screening rice genotypes can ensure optimal crop establishment and subsequent growth. An experiment was carried out by selecting ten rice genotypes for evaluation for cold tolerance through laboratory-based germination assays followed by subsequent screening with respect to biometric and biochemical parameters. Meher exhibited the highest germination rate (95%) under cold stress conditions, while Jajati and Ranidhana showed minimal variation in germination (2-7%). PERCOL (Percentage of seeds with coleoptile superior to 5 mm) and REDCOL (Percentage of reduction in coleoptile length) values remained consistent for Jajati and Pradeep. Cold stress led to notable reductions in plant height (9.2-31.1%) and the number of productive tillers per plant (36.8-37.1%). Samanta and Birupa recorded the highest number of productive tillers under control and cold stress conditions, respectively. Panicle exsertion was marginally impacted in Ranidhana (2.9%) and substantial decline recorded in Meher (19.2%), highlighting genotype-specific resilience. Spikelet fertility and 100-seed weight declined by 5.2-7.2% and 15-18%, respectively, in Samanta, and Jajati. Seed yield per plant was highest in Birupa (12.25 g/plant) under cold stress conditions. GGE biplot analysis indicated Kharavela and Birupa as high yielders under control and cold stress, respectively. Highest proline (4.6 mg/g) and carbohydrate content (18.08%) were noted in Samanta. Ranidhana and Samanta resulted in stable yield across environments indicating broader adaptability.

Keywords: Cold stress; Genotype; PERCOL; REDCOL; Scoring; Tolerant.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests. Consent for publication: All the authors have provided informed consent for publication of the manuscript.

Figures

Fig. 1
Fig. 1
Response of different genotypes under control and cold stress conditions.
Fig. 2
Fig. 2
PERCOL and REDCOL of genotypes under cold stress conditions.
Fig. 3
Fig. 3
Effect of varied temperature treatment on growth attributes of rice in pot culture.
Fig. 4
Fig. 4
Effect of cold stress on yield attributes and yield of rice in pot culture.
Fig. 5
Fig. 5
Correlation analysis of seedling and yield parameter among genotypes [V1: Germination (%), V2: PERCOL (%),V3: REDCOL (%), V4: Days to 50% flowering ,V5: Days to complete flowering,V6:Panicle exsertion%,V7: Plant height (cm),V8:No. of tiller/plant,V9: No. of Productive tillers/plant, V10 :Panicle length (cm), V11: Spikelet fertility (%),V12: 100 seed weight (g), V13: yield per plant (g). The size and color intensity of each circle indicate the strength of the Pearson correlation coefficient between variable pairs. Blue circles represent positive correlations, whereas red circles denote negative correlations. Darker and larger circles correspond to stronger correlations, while lighter and smaller circles indicate weaker associations.]
Fig. 6
Fig. 6
GGE biplot analysis for germination percentage of genotypes under varied conditions.
Fig. 7
Fig. 7
GGE biplot analysis for yield of genotypes under varied conditions.
Fig. 8
Fig. 8
Response of various biochemical parameters among genotypes under under cold stress condition on a temporal scale.
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References

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