Heterosis, Combining Ability, Genetic Diversity and their Interrelationship in Pigeonpea [Cajanus cajan (L.) Millspaugh]

The exploitation of heterosis resulted in the development of several high-yielding hybrids in various crops. In pulses the research on hybrid breeding started first in faba bean followed by pigeonpea and soybean (Bond et al., 1966 and Palmer et al., 2010). The success however, had come only from pigeonpea when India developed first genetic male sterility (GMS) based pigeonpea hybrid ICPH-8 in 1991 (Saxena et al., 1992). Recently a new early maturing pigeonpea hybrid IPH 15-03 has been released for commercial cultivation for North West Plain Zone (NWPZ) of India (Saxena et al., 2021). The global productivity of pigeonpea remained stagnant at around 800 kg/ha and became a major challenge for its breeders to further improve it. Hybrid varieties have the potential to break this yield plateau (Bohra et al., 2020).
               
The scanty knowledge about genetic mechanism governing heterosis remains a major issue in hybrid breeding. The magnitude of heterosis relies on the combination of parental genotype which together emerged as a heterotic combination. In order to choose the lines which produce superior heterotic combinations without making all possible crosses among them, different methods including parental per se performance, SCA effects, GCA effects and genetic diversity had been tried (Huang et al., 2015). The per se performance of parents may be is used as a parameters as it is assumed that, in general, the parents having high yield produce a large frequency of high yielding hybrids as compared to low yielding parents (Mohammadi et al., 2008). The presence of genetic diversity between the parents used in hybridization is considered as an important parameter for obtaining significant heterosis in hybrids (Tecklewold and Becker, 2006). Combining ability was also used by several workers to predict the extent of heterosis (Devi and Singh, 2011). Hence the present study was conducted with the objectives (i) to estimate combining ability and heterosis in pigeonpea (ii) to estimate the magnitude of genetic diversity among the parents and to measure correlation between per se performance of parents, combining ability, genetic diversity and heterosis.

Plant materials and field experiments
 
The eight elite pigeonpea genotypes viz., UPAS 120, Pusa 992, Pant A 421, Pant A 477, RKPV 492-01, Pusa 2017-1, Pusa 2013-1 and Pusa 2013-2 were crossed in half diallel fashion during the kharif 2017-18 to produce 28 F1’s. Thus, the 36 genotypes including 8 parents and 28 F1’s, were grown during kharif 2018-19 at N.E.B. C.R.C, of GBPUAT, Pantnagar (Uttarakhand) using randomized block design with three replications. The observations were recorded for eight different characters including days to 50 per cent flowering, days to maturity, plant height (cm), number of primary branches/plant, number of pods/plant, number of seeds/pod, 100-seed weight (g) and seed yield/plant (g).
 
Statistical analysis
 
The analysis of variance for eight characters was carried out as given by Fisher (1920). The combining ability was evaluated by Griffing’s (1956), Method II, Model I (Fixed effects). If the GCA and SCA effects were significant in desirable direction than these effects were considered as good (G) and those significant towards undesirable direction were considered as poor (P) while non-significant effects were designated as average (A). Similarly in case of per se (PM) performance if mean of line is found above overall parental mean than such lines were considered as good (G) but if mean of a parental line was below the overall parental mean than these lines were classified as poor (P). The heterosis over mid parent (MPH) and better parent (BPH) were estimated for seed yield and the significance of heterosis was tested with t test.  The GCA effects obtained from both parental lines of a hybrid were averaged to determine the mean GCA (MGCA) effect of the parents (Kumar et al., 2015). The genetic diversity was estimated for various yield and related traits by using the D² statistics (Mahalanobis, 1936) and for preparation of clusters, Tocher’s method as proposed by Rao (1952) was used.  By using the method of Arunachalam (1984) the parents were classified into three diversity classes i.e. low, medium and high. The Pearson’s correlation coefficients were used to estimate the relation between PM, SCA, MGCA, GD, MPH and BPH. To estimate the combining ability and heterosis and Mahalanobis D² statistics data were analysed using the INDOSTAT software (IndoStat Inc. Hyderabad, India).

Estimation of combining ability
 
A close perusal of Table 1 indicated that genotypic differences were significant for all characters which indicated the preponderance of sufficient genetic variability. The diallel ANOVA indicated that MSS due to GCA effects were highly significant (p<0.01) for all the characters, however, SCA effects were significant for all the characters except for number of seeds per pod (Table 2). The significance of GCA and SCA indicated the presence of additive and non-additive gene actions. For all characters the estimates of SCA variance were found to be higher than the corresponding GCA variance indicating the presence of non additive gene action. Average degree of dominance was found to be more than unity for all the characters which indicated the presence of over dominance.  The presence of dominance gene effect in governing these characters was also reported earlier by Gedam et al., (2013) and Tikle et al., (2016). The parent Pant A 421 and Pant A 477 can be ranked as the best parent as they had a good GCA effects for all yield attributes except plant height for Pant A 421 and number of seeds per pod for Pant A 477 (Table 3). A critical analysis of Table 3 indicated that the parents that were showing good GCA for seed yield per plant also showing positive and significant GCA effects for yield related traits and hence provides a clue that the combining ability for seed yield may be under the influence of combining ability of its components. Therefore, to increase yield in pigeonpea simultaneous improvement in yield components is also required. The hybrids Pant A 421 × RKPV 492-01 exhibited good SCA effects for maximum number of traits i.e. six including seed yield (Table 4). In case of seed yield, out of twenty eight hybrids, seventeen and six hybrids exhibited significant and positive MPH and BPH respectively.
 

 

 

 

 
Estimation of magnitude of genetic diversity among parents
 
The estimation of genetic diversity among parents revealed that four different clusters were present (Table 5). The cluster I was largest and contain five parents while the cluster II, III and cluster IV each contains single genotype. The inter cluster distance was greater than the intra cluster distance indicating sufficient genetic diversity among the genotypes. The maximum inter cluster distance was found between cluster II and IV (90.676) and minimum between cluster III and IV (43.013). Thus the parents used in present study exhibited considerable amount of genetic diversity. The existence of large morphological diversity in pigeonpea was also reported earlier by Verma et al., (2018).
 

 
Relationship between PM, SCA, MGCA, MPH and BPH for seed yield
 
Both MPH and BPH (r=0.87*) were significantly and positively correlated with each other (Table 6 and Table 7).  The SCA effects were positively and significantly correlated with the MPH (r=0.91**) and BPH (r=0.81**), respectively.  The significant linear regression of SCA effects on MPH and BPH and very high R² value further revealed that SCA was a good determinant of heterosis (Fig 1). In case of MPH, out of 17 heterotic hybrids, 12 hybrids (70.58%) exhibited average SCA and 5 hybrids (29.41%) exhibited good SCA effects (Table 8). In case of BPH, out of six hybrids, 4 hybrids had good SCA (66.66%) while two hybrids (33.33%) had average SCA. Present finding indicated that high frequency of heterotic hybrids were obtained if crosses possessed average or good SCA. These results further indicated that SCA is the most important factor for determination of heterosis and is supported by earlier findings of Pandey et al., (2015). This strong relationship may be due to the reason that both SCA and heterosis are function of non- additive gene action. The MGCA effects were found to be positively and significantly correlated with MPH (r=0.76**) and BPH (r=0.69**), respectively. The significant linear regression of MGCA on MPH and BPH along with high R² value revealed that MGCA was also a good determinant of heterosis (Fig  2).  A close perusal of Table 8 indicated that in case of MPH highest heterotic frequency (52.94%) was observed by crossing parents having good × poor GCA effects combination while the poor × poor GCA combination showed no heterotic frequency. The good × good and good × average combination each produced 17.64% heterotic frequency while poor × average produced 11.76 % heterotic frequency. In case of BPH the good × good, good × average and good × poor each showed a heterotic frequency of 33.33 %.  These results further indicated that if the parents had good × poor GCA effects, it results in yielding high heterosis frequency, however, the parents having good × good and good x average GCA effects produced a moderate level of heterotic hybrids. The present study revealed that the GCA effects of parental lines have potential application in hybrid development programmes and supported the earlier findings of Saxena and Sawargaonkar (2014). The PM was found to be negatively and non-significantly correlated with the MPH (r=-0.30) and BPH (r=-0.22) and hence it indicated that PM was not a reliable criteria to predict heterosis (Fig 3). A critical insight of Table 8  indicated that in case of mid parent highest frequency of heterotic hybrids (64.70%) was observed when parents having high and low means were crossed together i.e. high × low combination, the high × high combination showed 35.29% of heterotic frequency while the low × low showed no heterotic frequency for mid parent heterosis. In case of BPH highest frequency of heterotic hybrids (66.66%)  was reported when parents having high and high mean were crossed i.e. high × high combination, the high × low combination showed 33.33% of heterotic frequency while the low x low showed no heterotic frequency for BPH. These results indicated that parental mean cannot be used as reliable parameters for heterosis estimation and supported by the findings of Devi and Singh (2011). The GD was found to be negatively and non- significantly correlated with MPH (r=-0.28) and BPH (r=-0.24). The linear regressions of GD on heterosis were found to be non-significant (Fig 4). In case of MPH the highest frequency of heterotic hybrids were produced when parents having moderate amount of diversity were crossed (52.94%) followed by parents with low diversity (47.05%) while the parents having high level of GD results in no heterotic hybrids. In case of better parent heterosis equal frequency of heterotic hybrids (50 %) were produced when parents having moderate and low amount of diversity were crossed together. These results indicated that high genetic diversity did not lead to heterosis in pigeonpea and well supported by the findings of Pandey et al., (2015).
 

 

 

 

 

 

 

The SCA variance was higher than the corresponding GCA variance for all characters and average degree of dominance was more than unity for all the characters which indicated the presence of over dominance. The SCA and MGCA emerged as the most reliable parameters to predict the heterosis in pigeonpea. The high per se performance of parents and high genetic diversity does not lead to higher heterosis in pigeonpea. The parents having high × low or high × high per se performance, good × poor GCA effects and with medium genetic diversity resulted in high frequency of heterotic hybrids.
 

The authors are highly thankful to the Joint Director CRC, Pantnagar for providing the necessary resources for the present study.