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Association Analysis in Rice Germplasm Lines for High Temperature Tolerance

R. Mahendran1, J. Vanitha1,*, M. Jegadeeswaran1, M. Kanimoli Mathivathana2, A. Mohammed Ashraf3
1Department of Genetics and Plant Breeding, College of Agricultural Sciences, SRM Institute of Science and Technology, Vendhar Nagar, Chengalpattu, Baburayanpettai-603 201, Tamil Nadu, India.
2Department of Plant Breeding and Genetics, College of Agricultural Technology, Theni-625 562, Tamil Nadu, India.
3Department of Agronomy, College of Agricultural Sciences, SRM Institute of Science and Technology, Vendhar Nagar, Chengalpattu District, Baburayanpettai-603 201, Tamil Nadu, India.
Background: Relative to other abiotic factors like salinity and drought, breeding rice cultivars that are resistant of high temperatures has received a little attention. The purpose of this study is to find parents and genotypes that are suitable for utilizing in high temperature stress breeding program. 

Methods: The genetic material for this study comprised of a set of germplasm collections (293 accessions) from different sources such as International Rice Research Institute germplasm. These populations were raised at the Department of Rice, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore. The Heat tolarance Indices (TOL) viz., Heat tolerance index (HTI) and Heat susceptibility index (HSI) and association analysis were estimated among germplasm lines for yield attributes under normal and high temperature stress condition.

Result: Out of 293 genotypes, sixty nine genotypes significantly exceeded for both HTI and HSI. Association studies revealed that, single plant yield had highly significant and positive association with panicle exertion, number of total tillers per plant, number of productive tillers per plant, panicle length, number of filled grains per panicle and total dry matter production. Spikelet sterility and high temperature susceptibility index had highly significant and negative association with single plant yield. Number of productive tillers had significant and positive correlation with total dry matter production, panicle length, number of filled grains per panicle, days to maturity, hundred grain weight, grain breadth and high temperature susceptible index. Hence these traits may be considered as selection indices for yield and high temperature tolerance improvement programme. Hence it may be possible to combine single plant yield and heat susceptibility index by specific breeding programme for high temperature tolerance in rice.
DFF- Days to fifty per cent flowering; DM- Days to maturity; GB- Grain breadth; G- Grain length; GLBR- Grain length  breadth ratio; GFR- Grain filling rate; HGW- Hundred grain weight; HTI- Heat tolerance index; HIS- Heat susceptibility index; NTT- Number of total tillers; NPT- Number of productive tillers; NFG- Number of filled grains per panicle; PE- Days to panicle exsertion; PH- Plant height; PL- Panicle length; SPY- Single plant yield; SS-Spikelet sterility percentage.
Rice is the prime crop in research and developmental activities in Asia from green revolution to gene revolution. The crop is grown in a wide range of environments starting from higher elevations as upland rice to shallow lowlands and deep water situations. Due to global climatic changes, the crop has to withstand higher temperatures in the near future (Mahendran et al., 2015).

When exposed to high temperatures, rice germplasm shows significant variation. The ability of a plant to tolerate heat stress under field conditions depends on a number of physiological factors and mechanisms, including amendments to critical processes like photosynthesis, chlorophyll content, canopy temperature depression and concurrent increases in transcripts encoding protective protein. Higher photosynthetic rates, enhanced membrane thermostability and heat avoidance are frequently traits of a heat-tolerant variety (Nagarajan et al., 2010; Scafaro et al., 2010). Identification of heat tolerant germplasm lines were used in several breeding programmes to exploit the variation in both genotypic and morphological characters associated with heat tolerance. The majority of popular rice varieties are extremely sensitive to high temperatures during flowering, according to a research of those varieties conducted in high temperature conditions (Vanitha et al., 2023; Baidya et al., 2020). To increase high temperature tolerance in present cultivars, a number of strategies should be actively employed, including as the identification and use of new genes and alleles, increased breeding effectiveness and marker-assisted selection (Vanitha and Mahendran 2022). Although there have been limited observations on specific high temperature stress in tropical and subtropical areas, there has not yet been a comprehensive study on monitoring and evaluating heat stress-induced yield losses globally (Matsushima et al., 1982; Osada et al., 1973).
The field experiment was conducted at Department of Rice, Centre for  Plant  Breeding  and  Genetics  (CPBG),  Tamil  Nadu  Agricultural  University, Coimbatore during kharif 2016 control (S1) and summer 2017; summer 2018 high temperature conditions (S2 and S3) (Table 1). This area is situated at latitude of 11°N and longitude of 77°E with clayey soil of pH 7.8. The  experiment  was  laid  out  in  randomized complete  block  design  with  two replication, a spacing  of  20 X 20 cm.

Observations were recorded on five plants selected at random from a row in each accession. Data were recorded for 16 quantitative characters viz, days to panicle exsertion (PE- days), plant height (PH- cm), days to fifty per cent flowering (DFF- days), number of total tillers (NTT- No.), number of productive tillers (NPT- No.), panicle length (PL- cm), number of filled grains per panicle (NFG- No.), days to maturity (DM- days), hundred grain weight (HGW- g), spikelet sterility percentage (SS%), total dry matter production (TDMP- g), grain length (GL- mm), grain breadth (GB- mm), grain length breadth ratio (GLBR- mm), grain filling rate (GFR- g d-1), single plant yield (SPY- g) and 8 physiological characters viz, chlorophyll meter (SPAD) readings at fifty per cent flowering stage and grain filling stage, leaf gas exchange parameters, leaf temperature (T: °C), panicle temperature (T: °C), ambient temperature (T: °C), stay green for rice, canopy temperature depression (CTD) for leaf and CTD for panicle.

Table 1: Details of season, mean temperature and temperature range at grain filling stage.


 
Heat tolerance indices (TOL)
 
Heat tolerance index (HTI)
 
The Heat tolerance index (HTI) was calculated for all the genotypes under stress conditions using the formula suggested by Rosielle and Hamblin (1981).
 
HTI= xp-xs
 
Where:              
xs=  Trait value of the genotype under stress.
xp= Trait value of the genotype under non-stress.
 
Heat susceptibility index (HSI)
 
The Heat susceptibility index (HSI) was calculated for all the genotypes under stress conditions using the formula suggested by Fischer and Maurer (1978).
 
                                                 
 
Where:              
xs=  Trait value of the genotype under stress.
xp= Trait value of the genotype under non-stress.
Xs= Mean values of the trait of all the genotypes under stress.
Xp=  Mean values of the trait of all the genotypes under non-stress.
 
Association analysis
 
The genotypic correlations between yield and its component traits and among themselves as well as between characters were worked out as per the methods suggested by Johnson et al., (1955).
 
Genotypic correlation coefficient
 
 
Where:
r(xy)= Genotypic correlation coefficients.
Covg (xy)= Genotypic covariance between the traits ‘x’ and ‘y’.
= Genotypic variance of the trait ‘x’.
= Genotypic variance of the trait ‘y’.
x= Dependent variable x and
y= Independent variable y.

The significance of genotypic correlation coefficient was tested by referring to the standard table given by Snedecor (1961).
In rice, extreme maximum temperature is particularly important during flowering which usually lasts for 2-3 weeks. Exposure to high temperature for a few hours can greatly reduce pollen viability and therefore cause yield loss (Mirza, 2011; Raghunath and Beena, 2021). In comparison, breeding rice cultivars resistant to salinity and drought has gotten more attention than breeding types resistant to high temperatures. Only region-specific breeding initiatives have attempted to address rice’s high temperature tolerance since a thorough study conducted in the early 1980s, with limited success. (Mackill, 1981; Mackill et al., 1982; Mackill and Ni, 2001). The periods of high temperature negatively affected the sexual reproduction in rice (Zakaria et al., 2022). Hence, there is an urgent need to address high temperature induced yield losses in rice to face a changing climate.

Heat tolerance is influenced by several genes rather than a single gene (Mackill, 1981; Maestri et al., 2002). According to Mackill and Ni (2001), several genes have an impact on the recessive genetic regulation of excessive pollen shedding in rice. Yoshida et al., (1981), in contrast, noted that the majority of the genetic variation related to pollen shedding is additive. Their results showed significant broad sense and narrow sense heritabilities of 76 and 71%, respectively, while finding a high correlation between spikelet fertility and pollen shedding.
 
Evaluation of germplasm lines under control (S1) and high temperature conditions (S2 and S3)
 
Each growth phase of the rice plant is primarily defined by its cultivars, although the plant’s growth environment also influences the source-sink dynamics of the plant as a whole. The grain yield per unit area is used to evaluate the performance of various cultivars in rice. This is a significant trait, but other indicators, such as stability and efficiency, are also becoming more significant in considering climate change and the impending energy and water shortages (Saikia et al., 2022).
 
Heat tolerance index
 
Heat tolerance indices were calculated under stress with relation to performance under control and presented in Table 2. A358 recorded minimum value for heat tolerant index of 0.02. The germplasm line A424 recorded higher HTI values of 40.21 under stress condition. Among the germplasm lines mean value recorded of 6.07 and it was significantly exceeded by sixty nine genotypes.

Table 2: Estimation of Heat tolarance Indices (TOL and HSI) of 293 germplasm lines.


 
Heat susceptibility index
 
Heat susceptibility index were calculated for stress condition and presented in Table 2. A358 (0.004) recorded the minimum HSI. A424 recorded lower HSI values of 2.88. One sixty nine genotypes exceeded the general mean (0.93) significantly. Out of 293 genotypes, sixty nine genotypes significantly exceeded for both HTI and HS I (Fig 1).

Fig 1: Relationship between TOL and HSI.



Every year, the temperature rises and experiences significant changes, which pose a huge challenge to agricultural productivity. Only genotypes that are physiologically efficient or resistant can be used to produce crops under such conditions (Saikia et al., 2022). Hence it may be possible to combine single plant yield and heat susceptibility index by specific breeding programme for high temperature tolerance in rice. 
 
Correlation among yield components
 
The nature and extent of association that existed between the single plant yield and other yield component traits and also the association among the high temperature stress components were studied through correlation analysis. Character correlation studies enable clarify the strength and scope of character association in a crop. The inter relationship of component characters of yield provided the information about the consequences of selection for simultaneous improvement of desirable characters under selection.

The present study indicated that the single plant yield had highly significant and positive association with the traits viz., panicle exertion, number of total tillers per plant, number of productive tillers, panicle length, number of filled grains per panicle and total dry matter production (Table 3). Nor et al. (2014) for number of productive tillers and number of total tillers per plant Rao et al. (2014) for panicle length and for total dry matter production was reported by Venkanna et al., (2014). Spikelet sterility and heat susceptibility index had negative and significant correlation with single plant yield. Rice plants at the reproductive stage, including the processes of panicle initiation, male and female gametophyte development, anthesis, pollination and fertilization, are more susceptible to heat stress than at the vegetative stage (Xu et al., 2021). Hence it may be possible to combine single plant yield and heat susceptibility index by specific breeding programme for high temperature tolerance in rice. The information on the correlation among the yield components shows the nature and extent of relationship with each other. This will help in the simultaneous improvement of high temperature tolerance traits along with single plant yield in the breeding programmes.

Table 3: Genotypic correlation coefficient among component traits and high temperature stress indices.



Number of productive tillers had significant and positive correlation with total dry matter production. Panicle length, number of filled grains per panicle, days to maturity, hundred grain weight, grain breadth and heat susceptible index had significant and negative correlation. Lakshmi et al. (2014) reported that the correlation between number of productive tillers per plant and panicle length was negatively correlated. Grain breadth recorded significant and negative correlation with grain length breadth ratio. Similar findings were reported by Venkanna et al. (2014) and Kiran et al. (2016). Spikelet sterility had negative and significant association with grain breadth.
 
From the foregoing discussion, it can be concluded that the traits such as panicle exertion, number of total tillers per plant, number of productive tillers per plant, panicle length, number of filled grains per panicle, total dry matter production, heat tolerance index and heat susceptibility index are the major yield component traits with positive effect on single plant yield and the improvement of these traits would result in increased yield with high temperature tolerance in rice. It suggests that, increase in spikelet sterility will reduce the single plant yield. We can get desirable genotypes with high temperature tolerance and yield components from the present set of experimental materials.
All Authors declare that they have no conflict of interest.

  1. Baidya, A., Pal, A.K., Ali, M.A. and Nath, R. (2020). High temperature stress and the fate of pollen germination and yield in lentil (Lens culinaris M.). Indian Journal of Agricultural Research. 55: 144-150. doi: 10.18805/IJARe.A-5440.

  2. Fischer, R.A. and Maurer, R. (1978). Drought resistance in spring wheat cultivars. I. Grain yield responses. Australian Journal of Agricultural Research. 29: 897-916.

  3. Johnson, H.W., Robinson, H.F. and Comstoc, R.E. (1955). Estima ­tion of genteic and environmental variability in soyabean (Glycine max). Agronomy Journal. 47(4): 314-318.

  4. Kiran, B.A., Venkatesh Dore, M. and Megha, B.R. (2016). Relationship of flowering pattern and pollen sterility on productivity of chickpea genotypes under temperature regimes. Indian Journal of Agricultural Research. 50(6). https://doi.org/ 10.18805/ijare.v50i6.6669.

  5. Lakshmi, M.V., Suneetha, Y., Yugandhar, G. and Venkatalakshmi, N. (2014). Correlation studies in rice (Oryza sativa). International Journal of Genetic Engineering and Biotechnology. 5(2): 121-126.

  6. Mackill, D. (1981). Rice pollination characteristics related to high temperature tolerance. IRRN. 6(5): 11-12.

  7. Mackill, D. and Ni, J. (2001). Molecular mapping and marker- assisted selection for major-gene traits in rice. Rice genetics IV. International Rice Research Institute, Science Publ, Philippines. 137-151.

  8. Mackill, D.J., Coffman, W.R. and Rutger, J.N. (1982). Pollen shedding and combining ability for high temperature tolerance in rice. Crop Sci. 22: 730-733.

  9. Maestri, E., Klueva, N., Perrotta, C. et al. (2002). Molecular genetics of heat tolerance and heat shockproteins in cereals. J. Plant. Mol. Biol. 48: 667-668.

  10. Mahendran, R., Veerabadhiran, P., Robin, S., Raveendran, M. (2015). Genetic variability in rice germplasm lines for high temperature tolerance related traits. Annual of Plant and Soil Research. 5: 483-486.

  11. Matsushima, S., Ikewada, H., Maeda, A., Honda S. and Niki, H. (1982). Studies on rice cultivation in the tropics. Yielding and ripening responses of the rice plant to the extremely hot and dry climate in Sudan. Japanese Journal of Tropical Agriculture. 26(1): 19-25. 

  12. Mirza, M.M.Q. (2011). Climate change, flooding in South Asia and implications. Regional Environmental Change. 11(1): 95-107.

  13. Nagarajan, S., Jagadish, S., Prasad, A., Thomar, A., Anand A. and Pal, M. (2010). Local climate affects growth, yield and grain quality of aromatic and non-aromatic rice in north western India. Agriculture, Ecosystems and Environment. 138: 274-281.

  14. Nor, N.M.N., Shamsiah, A., Abdulrahim, H., Noraishah, H., Haslinda, A.M. and Wan. W.A. (2014). Correlation analysis on agronomic characters in F2 population derived from mr64 and pongsu seribu. Journal of Applied Science and Agriculture. 9(18): 143-147.

  15. Osada, A., Saciplapa, V., Rahong, M., Dhammanuvong, S. and Chakrabandho, H. (1973). Abnormal occurrence of empty grains of indica rice plants in the dry, hot season in Thailand. Japanese Journal of Tropical Agriculture. 42(1): 103-109.  

  16. Raghunath, M.P. and Beena, R. (2021). Manipulation of flowering time to mitigate high temperature stress in rice (Oryza sativa L.). Indian Journal of Agricultural Research. doi: 10.18805/IJARe.A-5707. 

  17. Rao, V., Thirumala, Y., Chandramohan, D., Bhadru, D., Bharathi and Venkanna, V. (2014). Genetic variability and association  analysis in rice. Crop Research. 5(2): 63-65.

  18. Rosielle, A.A. and Hamblin, J. (1981). Theoretical aspects of selection for yield in stress and non stress environments. Crop Science. 21: 943-946.

  19. Saikia, K., Dey, P.C. and Lipika, T. (2022). Assessment of growth and heat susceptibility index of different rice genotypes subjected to heat stress. The Pharma Innovation Journal. 11(5S): 1757-1761.

  20. Scafaro, A., Haynes, P. and Atwell, A. (2010). Physiological and molecular changes in Oryza meridionalis heat-tolerant species of wild rice. Journal of Experimental Botany. 61: 191-202. 

  21. Vanitha, J. and Mahendran, R. (2022). Heat tolerance and effect of high temperature on floral biology and physiological parameters in rice: A review. Agricultural Reviews. doi: 10.18805/ag.R-2353.

  22. Vanitha, J., Mahendran, R., Raveendran M. and Jegadeeswaran. M. (2023). Vegetos springer.  Marker assisted backcross analysis for high temperature tolerance in rice. https:// doi.org/10.1007/s42535-023-00705-2.

  23. Venkanna, V., Rao, M.V.B., Raju, C.S., Rao V.T. and Lingaiah, N. (2014). Association analysis of F2 generation in rice (Oryza sativa). International Journal of Pure and Applied Bioscience. 2(2): 278-283.

  24. Xu, Y., Chu, C. and Yao, S. (2021). The impact of high-temperature stress on rice: Challenges and solutions. The Crop Journal. 9(5): 963-976.

  25. Yoshida, S., Satake, T. and Mackill, D.S. (1981). High temperature stress in rice. IRRI Research. 67.

  26. Zakaria, S., Rustam, E., Basyah, B. and Kurniawan, T. (2022). The relationship between pollen viability and filled grains in native Indonesian rice cultivars under high temperature at flowering stage. Indian Journal of Agricultural Research. 56(6): 677-682. doi: 10.18805/IJARe.AF-684.

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