Investigating stress indices to discriminate the physiologically efficient heat tolerant genotypes of mungbean [Vigna radiata (L.) Wilczek]

Mungbean [Vigna radiata (L.) Wilczek] is one of the important short duration, self pollinated, grain legumes of Asia. It is cultivated in kharif, rabi as well as zaid season. But now a days, farmers prefer the cultivation of mungbean in zaid season because of its short crop duration which fits well to rice-wheat cropping system resulting in enhansed cropping intensity. It is a good substitute for meat in most Asian diet (Srinives et al., 2000; Rudy et al., 2006) and excellent source of proteins and minerals. It also improves the soil health (Jat et al., 2012). But, in summer, heat stress is one of the prime factor affecting production of mungbean in summer. Non availability of varieties resistant to heat stresses is also a major issue.
       
Among the various weather parameters, temperature is considered as the most influential as every chemical, physiological and biological processes in plants are dependent on temperature (Sunil and Sharma, 2005, Devi et al., 2015 ). High temperature stress conditions create a water deficit in plant tissues, which in turn lead to injury of cell membranes, reduction in rate of transpiration, enzymes and ion uptake and transport (Khalil et al., 2009), reduction in shoot dry mass, growth and net assimilation rates (Wahid et al., 2007), cell death, protein denaturation, inactivation of enzymes, pre- and post-harvest damages including scorching of leaves, burning, leaf senescence and abscission, flower dropping, seed discoloration, seed damage and finally reduced yield (Pranusha et al., 2012). In higher plants, heat stress significantly alters cell division and cell elongation rates which affect the leaf size, weight (Hasanuzzaman et al., 2013), stem growth and plant height (Prasad et al., 2006).
       
Increasing heat stress is becoming the major concern for plant scientists worldwide due to the changing climate (Hasanuzzaman et al., 2013).Various researchers try to escape the erratic climatic condition i.e. high temperature by shifting the sowing dates of mungbean. But they were not much successful in managing the effect of heat. Some plants have evolved strategies like modulation of different enzymes (Thind et al., 1997) for preventing damage caused by rapid changes in temperature (Kumar et al., 2007). Thus, there is dire need to identify the elite lines of mungbean with outstanding performance to develop high temperature tolerant varieties. Improvement through hybridization and recombination need special attention along with identifying genetic donors for high temperature tolerance/ resistance, which provide a powerful means.
       
Considering a challenging task to develop the heat tolerant lines of mungbean, first we need to understand the genetic architecture among available genotypes in relation to heat to identify the suitable donors. Owing to the complexity, the significance of stress index approach may be more suitable in formulating a successful breeding programme aimed at yield improvement under heat stress.
 
Keeping the above facts under consideration, the present investigation was done to identify heat tolerant genotypes using some selection indices based on mathematical equations between stress and non-stress conditions.

Plant material and field experimentation
 
The present investigation comprised 35 genotypes of mungbean received from Pulse Breeding Section, Department of Plant Breeding and Genetics, Tirhut College of Agriculture, Dholi, Munzaffarpur, Bihar, India. The breeding materials consisted of released varieties, advance lines and local land races developed by eight different centres (research centres and agricultural universities)which were collected from six different states of India. The list of genotypes and their geographical origin are presented in Table 1. The experiment was conducted at Crop Research Farm of TCA, Dholi, which is situated (25.5°N, 35.4°E, 52.12 m MSL) in district Muzaffarpur of North Bihar, India. Field experiments were performed in randomized complete block design (RCBD) with three replications in summer, 2012 and 2013 and Kharif, 2012 and 2013. The crop raised in summer season was considered as heat stress environment and kharif crop is considered as normal environment. Each genotype was sown in six rows in plot of 4 m length with 30 x 10 cm plant geometry. The recommended package of practices was followed to raise the healthy crop in both conditions. Total amount of nitrogenous, phosphoric and potassium fertilizers were applied (@20 kg N and 40 kg P₂O₅ and 40 K Kg/ ha) as basal dose. Observations were recorded for grain yield on 10 randomly selected competitive plants for each entry in each replication in both environments.
 

 
Calculation of indices
 
Seven heat tolerance indices including mean productivity (MP), geometric mean productivity (GMP), yield index (YI), tolerance index (TOL), stress susceptibility index (SSI), superiority measure (SM) were estimated by the following formula:
Geometric Mean Productivity = 
Yield Index = Ysi/Ys
Mean Productivity = (Ypi + Ysi)/2
Stress Susceptibility Index = {1- (Ysi/Ypi)}/ SI
Tolerance Index = Ypi-Ysi
 
Superiority Measure = 
 
In above mentioned equations, Ysi and Ypi are the seed yield of genotypes in heat stress and non-stress environment; SI is stress intensity, where SI = 1-(Ys/Yp); Y_s = Total seed yield mean in stress condi­tion; Y_p = total seed yield mean in normal condition; n = number of environments; Xij = Grain yield of i^th genotype at the j^th environment, and M_j = Seed yield of the genotype with maximum yield at j^th environment.
 
Statistical analysis
 
The pooled data of both years for respective environments were subjected to analysis of variance, co-variances and correlation by using online statistical computer software OPSTAT. Based on predominant stress indices a 3-D diagram was plotted using statistical package SPSS version 6.0 to select the heat tolerant genotype(s) for utilizing in mungbean breeding programme.

Environmental characterization
 
In normal environment, maximum temperature was ranged from 30.5 – 34.3 in 2012 and 30.17 – 34.8 in 2013 with the average of 31.95 – 34.2, whereas in stress environment, it ranged from 32.4 - 41.2 in 2012 and 31.10 – 39.2 in 2013 with an average of  34.10 – 38.65, clearly indicated that mungbean grown in summer season faced serious heat stress (Fig 1-2).
 

 

 
Analysis of variance
 
The pooled analysis of variance for yield based heat tolerance indices was carried out. The significant differences among the genotypes for all the stress indices indicated the existence of sufficient genetic variation (Table 2) and further analysis was carried out.
 

 
Per se performance
 
A wide range of variation was observed among the different stress indices for all 35 genotypes of mungbean (Table 3). Out of 35 mungbean genotypes, a total of five genotypes namely HUM-12, Pusa Vishal, Pusa 1131, NDM 12-308 & IPM 99-01-10 for Ypi; seven genotypes namely Pusa Vishal, Pusa 1131, PM 08-2, DMS 02-11-13, IPM 99-394, IPM 99-01-10 & Pusa 1132 for STI; eight genotypes namely Pusa Vishal, Pusa 1131, PM 08-2, NDM 12-308, IPM 99-394, IPM 2K-14-9, IPM 99-01-10 & Pusa 1132 for Yi were found significantly superior than the heat tolerant check Samrat. Three genotypes namely IPM 02-4, NDM 12-308 & SML 668 exhibited less than one (<1) values for SSI, indicated that these genotypes were less influenced by the heat stress. These genotypes were showed the possibility of direct selection for respective traits in relation to heat stress. But direct selection may mislead, therefore, indirect selection was also taken care off.
 

 
Correlation analysis
 
Correlation analysis between heat tolerant in­dices on the basis of grain yield under non stress and heat stress condition was performed (Table 4). The genotypic correlation was found higher than the corresponding phenotypic correlation coefficient for all the stress indices, indicated that the less influence of environment in expression of the traits concerned (genotypic data not shown). Similar finding have earlier been reported by Rathor et al., (2015). By exploiting the estimates of desirable correlations, the breeder would be able to decide the breeding methods for improvement and the undesirable ones can be modified by generating fresh variability to obtain new recombinants (Rahor et al., 2015). Indices which had significant correlation with seed yield under both heat stressed and non stressed environments had been selected as best ones, because of its ability to separate and identify the genotypes with high seed yield in both environments.
 
  
 
It was observed that the indices i.e. GMP, MP, STI and YI had significant and positive correlation with seed yield under both heat stressed and non stress environments. Therefore genotypes, which showed high extent of these indices were identified as most tolerant genotypes, these genotypes may further be utilize as donors for heat stress breeding programmes. STI exhibited negative and significant  correlation with seed yield under heat stressed environment whereas positive and significant correlation in non stressed environment. Hence it cannot be a proper index for selecting the genotypes, which have a high yield in both stress and normal conditions (Jabbari et al., 2008). Superiority measure (SM) had significant negative correlation with all the stress indices except SSI. The low indices value of SSI can be used as an index for screening of heat tolerance genotype with high grain yield in both conditions. MP also exhibited significant and positive association with GMP, STI and YI. Likewise, GMP had significant and positive association with STI and YI. STI was positively and significantly related with yield under both heat stressed and non stressed environments, MP, GMP and YI, indicated their suitability for using as selection criteria for yield improvement under heat stress environment. Among all the stress indices MP, GMP and STI can be used to discriminate the heat tolerant genotypes for their utilization in breeding programme.
 
Discrimination of donors for heat by tolerance
 
To select heat tolerant geno­types, three dimensional plots were drawn (Fig 3) using the three predominant stress indices i.e. GM, GMP and STI. Due to tight association of these indices, they can be used as selection criterion for heat tolerant genotypes. Parihar et al., (2012) also used the three dimensional plot of stress indices for isolating drought tolerant lines of maize. In three dimensional plots the genotypes were divided in different groups. These plots can be used effectively to differentiate the physiologically efficient genotypes with regards to heat tolerance. Based on this plot; three genotypes namely SML 1186, NDM 12-308 and IPM 02-4 were found with high stress indices score and they clustered nearby the heat tolerant check Samrat, indicated that these genotypes might be utilized in developing heat tolerant promising varieties.