Abstract
Terminal heat stress (THS) is a major abiotic stress causing reduction in grain weight, size, number and quality of wheat crop. Most of the earlier studies have focused on identifying THS-tolerant genotypes mainly by late sowing, which generally has gradual increase in temperature. But the recent climate change demands for the genotypes to withstand for both gradual and sudden rise in THS. Thus, the present study was undertaken to identify high-yielding and more stable genotypes for both gradual and sudden rise in THS. In this study, 26 wheat genotypes were screened under three sowing conditions, viz., timely sown (TS), late sown (LS) for gradual increase in THS and temperature-controlled phenotyping facility (TCPF), to impose sudden THS during 2017–2018 and 2018–2019. The experiment was laid out in Alpha-lattice design with uniform plot size (0.80 m × 0.80 m2) containing 4 rows with 20-cm distance between each row and replicated twice. To study the nature of relationship among traits, Pearson correlation analysis was done and GGE-biplot analysis was used to discriminate the genotypes with superior yield and stability. ANOVA revealed significant (p = ≤ 0.05) effect of the genotypes, condition and genotype × condition on grain yield and other parameters. Pearson correlation revealed positive interaction of grain yield with thousand grain weight and harvest index, while days to heading and maturity had a negative association under normal and heat-stressed conditions. GGE-biplot efficiently explained 91.03% of the interaction effect, and ideal view model ranked genotype as DBW71 > AKW2862-1 > DBW173 > DBW107 > HD2932 > WH730 > KKR1043 > other lines. Which-won-where model of GGE revealed DBW71 with comparatively high yield (LS = 330.1 g m−2, TCPF = 194.5 g m−2) as wining genotype in both gradual and sudden stress conditions. Whereas, with the mean-versus-stability model, DBW173 (LS = 337.2 g m−2, TCPF = 167.0 g m−2) and WH730 (LS = 334.8 g m−2, TCPF = 236.9 g m−2) analysed as highly stable genotypes across both type of stress conditions. From this study, DBW71, DBW173 and WH730 were identified as the most stable genotypes for both sudden and gradual rise in THS and these stable genotypes can serve in identifying the most reliable molecular markers for improving climate resilience in wheat under heat stress condition.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Ahmad A, Diwan H, Abrol Y (2009) Global climate change, stress and plant productivity. In: Abiotic stress adaptation in plants: physiological, molecular and genome foundation. Springer, Dordrecht, pp 503–521
Aktaş H (2016) Tracing highly adapted stable yielding bread wheat (Triticum aestivum L.) genotypes for greatly variable South-Eastern Turkey. Appl Ecol Environ Res 14:159–176. https://doi.org/10.15666/aeer/1404_159176
Alam MN, Bodruzzaman M, Hossain MM, Sadekuzzaman M (2014) Growth performance of spring wheat under heat stress conditions. Int J Agric Res 4:91–103. Available via. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.652.9450&rep=rep1&type=pdf. Accessed 20 July 2020
Balla K, Karsai I, Bónis P, Kiss T, Berki Z, Horváth Á, Mayer M, Bencze S, Veisz O (2019) Heat stress responses in a large set of winter wheat cultivars (Triticum aestivum L.) depend on the timing and duration of stress. PLoS One 14:e0222639. https://doi.org/10.1371/journal.pone.0222639
Baye A, Berihun B, Bantayehu M, Derebe B (2020) Genotypic and phenotypic correlation and path coefficient analysis for yield and yield-related traits in advanced bread wheat (Triticum aestivum L.) lines. Cogent Food Agric 6:1–17. https://doi.org/10.1080/23311932.2020.1752603
Bernier J, Atlin GN, Serraj R, Kumar A, Spaner D (2008) Breeding upland rice for drought resistance. J Sci Food Agric 88:927–939. https://doi.org/10.1002/jsfa.3153
Bernier J, Kumar A, Ramaiah V, Spaner D, Atlin G (2007) A large-effect QTL for grain yield under reproductive-stage drought stress in upland rice. Crop Sci 47:507–516
Bhullar S, Jenner C (1983) Responses to brief periods of elevated temperature in ears and grains of wheat. Funct Plant Biol 10:549–560
Bishwas K, Poudel M, Regmi D (2021) AMMI and GGE biplot analysis of yield of different elite wheat line under terminal heat stress and irrigated environment. Heliyon 7:1–10
Chatrath R, Kumar S, Gupta V, Singh S, Mamrutha H, Jasrotia P, Kashyap P, Gangwar O, Mishra C, Gopalareddy K et al (2019) Variety DBW 173. Indian J Genet 79:635–635. Available via. https://www.isgpb.org/article/variety-dbw-173. Accessed 19 Aug 2020
Chauhan YS, Douglas C, Rachaputi R, Agius P, Martin W, King K, Skerman A (2010) Physiology of mungbean and development of the mungbean crop model. In: George-Jaeggli B, Jordan DJ (eds) 1st Australian Summer Grains Conference. Gold Coast, Australia. Grains Research and Development Corporation. Available via. www.grdc.com.au/uploads/documents/2010ASGCEditedPapersPDF/Chauhan.MungbeanCropModel.edited.paper.pdf. Accessed 29 June 2020
Cheabu S, Moung-Ngam P, Arikit S, Vanavichit A, Malumpong C (2018) Effects of heat stress at vegetative and reproductive stages on spikelet fertility. Rice Sci 25:218–226. https://doi.org/10.1016/j.rsci.2018.06.005
Dhanda S, Munjal R (2012) Heat tolerance in relation to acquired thermotolerance for membrane lipids in bread wheat. Field Crops Res 135:30–37. https://doi.org/10.1016/j.fcr.2012.06.009
FAO (2021) Food and Agriculture Organization of the United Nations. World food situation. Available via. http://www.fao.org/worldfoodsituation/csdb/en/. Accessed 10 Jan 2022
Farooq M, Bramley H, Palta J, Siddique K (2011) Heat stress in wheat during reproductive and grain-filling phases. Crit Rev Plant Sci 30:491–507. https://doi.org/10.1080/07352689.2011.615687
Frutos E, Galindo M, Leiva V (2014) An interactive biplot implementation in R for modeling genotype-by-environment interaction. Stoch Environ Res Risk Assess 28:1629–1641. https://doi.org/10.1007/s00477-013-0821-z
Fu G, Feng B, Zhang C, Yang Y, Yang X, Chen T, Zhao X, Zhang X, Jin Q, Tao L (2016) Heat stress is more damaging to superior spikelets than inferiors of Rice (Oryza sativa L.) due to their different organ temperatures. Front Plant Sci 7. https://doi.org/10.3389/fpls.2016.01637
Galili T (2015) dendextend: an R package for visualizing, adjusting and comparing trees of hierarchical clustering. Bioinformatics 31:3718–3720. https://doi.org/10.1093/bioinformatics/btv428
Gupta A, Singh C, Kumar V, Tyagi B, Tiwari V, Chatrath R, Singh GP (2018a) Wheat varieties notified in India since 1965. ICAR- Indian Institute of Wheat & Barley Research, Karnal- 132001, India. http://www.iiwbr.org/wpcontent/uploads/2018/08/wheat-varieties-notified-in-india.pdf. Accessed 14 Mar 2020
Gupta A, Singh C, Kumar V et al (2018b) An Inventory of Registered Wheat and Barley Genetic Stocks in India. ICAR-Indian Institute of Wheat & Barley Research, Karnal – 132001 (Haryana) India. http://www.iiwbr.org/wpcontent/uploads/2018/08/genetic-stocks-book.pdf. Accessed 15 Mar 2020
Gupta OP, Pandey GC, Gupta RK, Sharma I, Tiwari R (2013) Comparative behavior of terminal heat tolerant (WH 730) and intolerant (Raj 4014) hexaploid wheat genotypes at germination and growth at early stage under varying temperature regimes. Afr J Microbiol Res 7:3953–3960
Hatfield JL, Prueger JH (2015) Temperature extremes: Effect on plant growth and development. Weather Clim Extremes 10:4–10. https://doi.org/10.1016/j.wace.2015.08.001
Hoshikawa K (1962) Studies on the ripening of wheat grain: 4. Influence of temperature upon the development of the endosperm. Jpn J Crop Sci 30:228–231. https://doi.org/10.1626/jcs.30.228
Hawker J, Jenner C (1993) High temperature affects the activity of enzymes in the committed pathway of starch synthesis in developing wheat endosperm. Funct Plant Biol 20:197–209
Iqbal M, Raja NI, Yasmeen F, Hussain M, Ejaz M, Shah MA (2017) Impacts of heat stress on wheat: a critical review. Adv Crop Sci Technol 5:1–9. https://doi.org/10.4172/2329-8863.1000251
Jenner C (1991a) Effects of exposure of wheat ears to high temperature on dry matter accumulation and carbohydrate metabolism in the grain of two cultivars. I. Immediate responses. Funct Plant Biol 18:165–177
Jenner C (1991b) Effects of exposure of wheat ears to high temperature on dry matter accumulation and carbohydrate metabolism in the grain of two cultivars. II. Carry-over effects. Funct Plant Biol 18:179–190
Joshi A, Mishra B, Chatrath R, Ferrara GO, Singh RP (2007) Wheat improvement in India: present status, emerging challenges and future prospects. Euphytica 157:431–446. https://doi.org/10.1007/s10681-007-9385-7
Kamoshita A, Babu RC, Boopathi NM, Fukai S (2008) Phenotypic and genotypic analysis of drought-resistance traits for development of rice cultivars adapted to rainfed environments. Field Crops Res 109:1–23. https://doi.org/10.1016/j.fcr.2008.06.010
Kassambara A, Mundt F (2017) Factoextra: extract and visualize the results of multivariate data analyses. R package version 1:337–354
Kaushal N, Bhandari K, Siddique KH, Nayyar H (2016) Food crops face rising temperatures: an overview of responses, adaptive mechanisms, and approaches to improve heat tolerance. Cogent Food Agric 2:1134380. https://doi.org/10.1080/23311932.2015.1134380
Kirigwi FM, Van Ginkel M, Brown-Guedira G, Gill BS, Paulsen GM, Fritz AK (2007) Markers associated with a QTL for grain yield in wheat under drought. Mol Breed 20:401–413. https://doi.org/10.1007/s11032-007-9100-3
Kumar P, Gupta V, Singh G, Singh C, Tyagi BS, Singh GP (2021) Assessment of terminal heat tolerance based on agro-morphological and stress selection indices in wheat. Cereal Res Commun 49:217–226. https://doi.org/10.1007/s42976-020-00112-2
Kumudini S, Andrade FH, Boote K et al (2014) Predicting maize phenology: intercomparison of functions for developmental response to temperature. Agron J 106:2087–2097. https://doi.org/10.2134/agronj14.0200
Maechler M, Rousseeuw P, Struyf A, Hubert M et al (2013) Package ‘cluster.’ Dosegljivona. http://cran.r-project.org/web/packages/cluster/cluster.pdf. Accessed 15 May 2020
Mamrutha HM, Khobra R, Sendhil R, Munjal R et al (2020) Developing stress intensity index and prioritizing hotspot locations for screening wheat genotypes under climate change scenario. Ecol Indic 118:106714. https://doi.org/10.1016/j.ecolind.2020.106714
Meena RP, Karnam V, Sendhil R, Rinki, Sharma RK, Tripathi SC, Singh GP (2019) Identification of water use efficient wheat genotypes with high yield for regions of depleting water resources in India. Agric Water Manag 223:105709. https://doi.org/10.1016/j.agwat.2019.105709
Meena VK, Sharma RK, Yadav S, Kumar N, Gajghate R, Singh A (2021) Selection parameters for improving grain yield of bread wheat under terminal heat stress. Indian J Agric Sci 91:468–473
Modarresi M, Mohammadi V, Zali A, Mardi M (2010) Response of wheat yield and yield related traits to high temperature. Cereal Res Commun 38:23–31. https://doi.org/10.1556/crc.38.2010.1.3
Mohan D, Mamrutha H, Tyagi B (2017) Weather conditions favouring wheat (Triticum aestivum) productivity in hot climate of central India and congenial environment of north-western plains. Indian J Agric Sci 87(2):278–281
Mondal S, Joshi AK, Huerta-Espino J, Singh RP (2015) Early maturity in wheat for adaptation to high temperature stress. In: Ogihara Y, Takumi S, Handa H (eds) Advances in Wheat Genetics: From Genome to Field. Springer Japan, Tokyo, pp 239–245
Msundi EA, Owuoche JO, Oyoo ME, Macharia G, Singh RP, Randhawa MS (2021) Identification of bread wheat genotypes with superior grain yield and agronomic traits through evaluation under rust epiphytotic conditions in Kenya. Sci Rep 11:1–11. https://doi.org/10.1038/s41598-021-00785-7
Narayanan S (2018) Effects of high temperature stress and traits associated with tolerance in wheat. Open Access J. Sci 2:177–186. https://doi.org/10.15406/oajs.2018.02.00067
Okechukwu EC, Agbo CU, Uguru MI, Ogbonnaya FC (2016) Germplasm evaluation of heat tolerance in bread wheat in Tel Hadya, Syria. Chil J Agric Res 76:9–17. https://doi.org/10.4067/S0718-58392016000100002
Oral E, Kendal E, Dogan Y (2018) Selection the best barley genotypes to multi and special environments by AMMI and GGE biplot models. Fresenius Environ Bull 27:5179–5187
Ortiz FG, Joshi A, Chand R et al (2007) Partnering with farmers to accelerate adoption of new technologies in South Asia to improve wheat productivity. Euphytica 157:399–407. https://doi.org/10.1007/s10681-007-9353-2
Prasad PV, Djanaguiraman M (2014) Response of floret fertility and individual grain weight of wheat to high temperature stress: sensitive stages and thresholds for temperature and duration. Funct Plant Biol 41:1261–1269. https://doi.org/10.1071/FP14061
Price AH, Cairns JE, Horton P, Jones HG, Griffiths H (2002) Linking drought-resistance mechanisms to drought avoidance in upland rice using a QTL approach: progress and new opportunities to integrate stomatal and mesophyll responses. J Exp Bot 53:989–1004. https://doi.org/10.1093/jexbot/53.371.989
Qaseem MF, Qureshi R, Shaheen H (2019) Effects of pre-anthesis drought, heat and their combination on the growth, yield and physiology of diverse wheat (Triticum aestivum L.) genotypes varying in sensitivity to heat and drought stress. Sci Rep 9:1–12. https://doi.org/10.1038/s41598-019-43477-z
Rakshit S, Ganapathy K, Gomashe S, Swapna M, More A, Gadakh S, Ghorade R, Kajjidoni S, Solanki B, Biradar B et al (2014) GGE biplot analysis of genotype × environment interaction in rabi grain sorghum [Sorghum bicolor (L.) Moench]. Indian J Genet 74:558–563. https://doi.org/10.5958/0975-6906.2014.00889.X
Reynolds M, Foulkes MJ, Slafer GA, Berry P, Parry MAJ, Snape JW, Angus WJ (2009) Raising yield potential in wheat. J Exp Bot 60:1899–1918. https://doi.org/10.1093/jxb/erp016
Samyuktha SM, Malarvizhi D, Karthikeyan A, Dhasarathan M, Hemavathy AT, Vanniarajan C, Sheela V, Hepziba SJ, Pandiyan M, Senthil N (2020) Delineation of genotype × environment interaction for identification of stable genotypes to grain yield in mungbean. Front Agron 2:577911. https://doi.org/10.3389/fagro.2020.577911
Sandhu N, Kumar A (2017) Bridging the rice yield gaps under drought: QTLs, genes, and their use in breeding programs. Agron 7:27. https://doi.org/10.3390/agronomy7020027
Sareen S, Tyagi BS, Sarial AK, Tiwari V, Sharma I (2014) Trait analysis, diversity, and genotype x environment interaction in some wheat landraces evaluated under drought and heat stress conditions. Chil J Agric Res 74:135–142. https://doi.org/10.4067/S0718-58392014000200002
Sareen S, Tyagi BS, Sharma I (2012) Response estimation of wheat synthetic lines to terminal heat stress using stress indices. J Agric Sci 4:97–104. https://doi.org/10.5539/jas.v4n10p97
Sehgal A, Sita K, Siddique KHM, Kumar R, Bhogireddy S, Varshney RK, Hanumantha RB, Nair RM, Prasad PV, Nayyar H (2018) Drought or/and heat-stress effects on seed filling in food crops: Impacts on functional biochemistry, seed yields, and nutritional quality. Front Plant Sci 9:1705. https://doi.org/10.3389/fpls.2018.01705
Sharma D, Chandra Pandey G, Mamrutha HM, Singh R, Singh NK, Singh GP, Rane J, Tiwari R (2019) Genotype–phenotype relationships for high-temperature tolerance: an integrated method for minimizing phenotyping constraints in wheat. Crop Sci 59:1973–1982. https://doi.org/10.2135/cropsci2019.01.0055
Sharma RC, Morgounov AI, Braun HJ, Akin B, Keser M, Bedoshvili D, Bagci A, Martius C, van Ginkel M (2010) Identifying high yielding stable winter wheat genotypes for irrigated environments in Central and West Asia. Euphytica 171:53–64. https://doi.org/10.1007/s10681-009-9992-6
Shenoda JE, Sanad MNME, Rizkalla AA, El-Assal S, Ali RT, Hussein MH (2021) Effect of long-term heat stress on grain yield, pollen grain viability and germinability in bread wheat (Triticum aestivum L.) under field conditions. Heliyon 7:1–15. https://doi.org/10.1016/j.heliyon.2021.e07096
Singh S, Chatrath R, Tiwari V, Rao NG et al (2013) DBW 71: a new wheat variety for late sown irrigated conditions of north western plains zone of India. J Wheat Res 5:72–73. Available via. https://sawbar.in/wp-content/uploads/2018/07/36772-84476-1-SM-1.pdf. Accessed 15 June 2020
Singh C, Gupta A, Gupta V, Kumar P, Sendhil R, Tyagi B, Singh G, Chatrath R, Singh G (2019) Genotype x environment interaction analysis of multi-environment wheat trials in India using AMMI and GGE biplot models. Crop Breed Appl Biotechnol 19:309–318. https://doi.org/10.1590/1984-70332019v19n3a43
Stone P, Nicolas M (1994) Wheat cultivars vary widely in their responses of grain yield and quality to short periods of post-anthesis heat stress. Funct Plant Biol 21:887–900
Tadesse W, Manes Y, Singh RP, Payne T, Braun HJ (2010) Adaptation and performance of CIMMYT spring wheat genotypes targeted to high rainfall areas of the world. Crop Sci 50:2240–2248. https://doi.org/10.2135/cropsci2010.02.0102
Venkatesh K, Gupta V, KM S, HM M, Singh G, Singh GP (2020) Mitigating heat stress in wheat: integrating omics tools with plant breeding. In: Jha UC, Nayyar H, Gupta S (eds) Heat Stress In: Food Grain Crops: Plant Breeding and Omics Research. Bentham Science Publishers, pp 1–27. https://doi.org/10.2174/97898114739821200101
Wahid A, Gelani S, Ashraf M, Foolad M (2007) Heat tolerance in plants: an overview. Environ Exp Bot 61:199–223. https://doi.org/10.1016/j.envexpbot.2007.05.011
Yan W (2001) GGE-biplot—a Windows application for graphical analysis of multi-environment trial data and other types of two-way data. Agron J 93:1111–1118. https://acsess.onlinelibrary.wiley.com/journal/14350645. Accessed 18 May 2020
Yan W, Kang MS (2002) GGE biplot analysis: a graphical tool for breeders, geneticists, and agronomists. CRC Press, Boca Raton. https://doi.org/10.1201/9781420040371
Yan W, Tinker NA (2006) Biplot analysis of multi-environment trial data: principles and applications. Can J Plant Sci 86:623–645. https://doi.org/10.4141/P05-169
Yang RC, Crossa J, Cornelius PL, Burgueño J (2009) Biplot analysis of genotype × environment interaction: Proceed with caution. Crop Sci 49:1564–1576. https://doi.org/10.2135/cropsci2008.11.0665
Zhang G, Liu S, Dong Y, Liao Y, Han J (2022) A nitrogen fertilizer strategy for simultaneously increasing wheat grain yield and protein content: mixed application of controlled-release urea and normal urea. Field Crops Res 277:108405. https://doi.org/10.1016/j.fcr.2021.108405
Zadoks JC, Chang TT, Konzak CF et al (1974) A decimal code for the growth stages of cereals. Weed Res 14:415–421. https://doi.org/10.1111/j.1365-3180.1974.tb01084.x
Funding
The authors gratefully acknowledge the financial support in carrying out this research work from ICAR-Network Project on Functional Genomics and Genetic Modification in Crops “Project Code OXXO1347 and the in-house project CRSCIIWBRSIL 201500400185.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of Interest
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Supplementary file4
Fig. S1 Overview of the study conducted under field conditions (Timely sown; TS & late sown; LS) and temperature controlled phenotyping facility (TCPF) representing planting for TCPF and TS was done in November while for LS it was in December. Effects of gradual (LS condition) and sudden (TCPF) heat shock measured w.r.t. non-stress condition (TS) (JPG 577 kb)
Supplementary file5
Fig. S2 Monthly total rainfall (RF) at Indian Institute of Wheat and Barley Research, Karnal, during experimental years (2017-18 and 2018-19) compared with long term averages (LTA) (1972–2018) (PNG 371 kb)
Supplementary file6
Fig. S3 Boxplot of BLUEs for wheat days to heading (DH), days to maturity (DM), plant height (PH) (cm), tiller number per four plant (TNFP) and spikelets per spike (SpPS) under timely sown (TS) and heat stress conditions viz. late sown (LS) and temperature controlled phenotyping facility (TCPF); horizontal bars present mean value of the respective genotypes and vertical line gives the range of corresponding traits represents comparative behaviour of the genotypes for specific trait in three growing condition observed by 3 graphs arranged in horizontal plane (PNG 398 kb)
Supplementary file7
Fig. S4 Boxplot of BLUEs for wheat spike length (SL) (cm), thousand grain weight (TGW) (g), biomass per meter square (BMPM) (kg m-2), grain yield (GY) (g m-2) and harvest index (HI) (%) under timely sown (TS) and heat stress conditions viz. late sown (LS) and temperature controlled phenotyping facility (TCPF); horizontal bars present mean value of the respective genotypes and the vertical line gives the range of corresponding traits represents comparative behaviour of the genotypes for specific trait in three growing condition observed by 3 graphs arranged in horizontal plane (PNG 251 kb)
Rights and permissions
About this article
Cite this article
Devi, K., Chahal, S., Venkatesh, K. et al. Identification of Wheat Genotypes Resilient to Terminal Heat Stress Using GGE Biplot Analysis. J Soil Sci Plant Nutr 22, 3386–3398 (2022). https://doi.org/10.1007/s42729-022-00894-w
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s42729-022-00894-w