Variability plays an important role in crop breeding material ensures the better chance of producing desirable crop plant. The results of range, mean, genotypic coefficient of variation (GCV), phenotypic coefficient of variation (PCV), heritability (h2), genetic
Table 1. Mean, Range and genetic parameters in F2 population of the tomato hybrid Arka Vikas × EC 519809
Table 2. Simple correlation coefficient between fruit yield and yield components traits in F2 generation of the cross Arka Vikas × EC 519809
Table 3. Path co efficient on fruit yield per plant in F2 generation of the cross Arka Vikas × EC 519809
Heritability and Genetic Advance
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The highest value of heritability was noticed in fruit yield per plant (91.84%), followed by individual fruit weight (77.14%), pericarp thickness (76.60%), TSS (70.15%), and number of primary branches per plant (65.93%).
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The results confirmed the involvement of additive gene action in these traits with less environmental influence.
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The lowest value of heritability was recorded for number of fruits per cluster (15.01%), fruit set percent (26.53%), and number of locules per fruit (26.92%).
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Genetic advance as percent of mean was highest (68.79%), followed by number of primary branches per plant (48.68%), pericarp thickness (41.54%), number of fruits per plant (35.14%), individual fruit weight (32.62%), and total phenol (30.04%).
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Lower values for GA% were observed in number of fruits per cluster (4.20%), number of locules per fruit (5.75%), fruit set percent (6.04%), number of flowers per cluster (6.58%), fruit diameter (7.33%), days to first flowering (8.21%), fruit length (10.01%), TSS (10.23%), and plant height (12.97%).
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High estimates of heritability with high genetic advance as percent over mean were recorded for fruit yield per plant, individual fruit weight, pericarp thickness, and number of primary branches per plant.
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These findings are similar to those of Mehta and Asati (2008), Reddy et al. (2013), Ullah et al. (2015), and Rai et al. (2016).
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It might be assigned to be under the control of additive genes, and phenotypic selection for their improvement could be achieved by simple breeding methods.
Correlation Studies
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The correlation between fruit yield per plant with different yield attributes is presented in Table 2.
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The correlation coefficient among different characters indicated that yield per plant was significant and positively associated with:
- Plant height (0.142)
- Number of flowers per cluster (0.221)
- Percent fruit set (0.163)
- Fruit length (0.258)
- Fruit diameter (0.200)
- Individual fruit weight (0.426)
- Number of fruits per plant (0.803)
- Total phenol (0.272)
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These results are in agreement with findings of Meena et al. (2015), Phom et al. (2015), Ullah et al. (2015), Meena and Bahadur (2015), Rahman et al. (2015), and Hazim et al. (2016) in tomato.
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Plant height exhibited positive and significant relationship with individual fruit weight (0.258).
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Number of primary branches per plant showed positive and significant association with number of flowers per cluster (0.148) and fruit length (0.147).
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Similar results were also obtained by Mayavel et al. (2005).
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Number of flowers per cluster had positive and significant correlation with:
- Number of fruits per cluster (0.600)
- Fruit length (0.220)
- Fruit weight (0.269)
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These results are in accordance with the reports of Ullah et al. (2015) and Rahman et al. (2015).
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Number of fruits per cluster was positively and significantly correlated to percent fruit set (0.712) and individual fruit weight (0.139).
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These results conform with the findings of Sherpa et al. (2014).
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Fruit length had positive and significant association with fruit diameter (0.150), average fruit diameter (0.350), and number of fruits per plant (0.142).
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This result agrees with the findings of Mahapatra et al. (2013) and Rahman et al. (2015).
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Fruit diameter recorded positive and significant correlation with individual fruit weight (0.156) and number of fruits per plant (0.191).
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Similar studies reported by Mahapatra et al. (2013), Kumar et al. (2013), and Chernet et al. (2013) align with these findings.
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Individual fruit weight was positively and significantly correlated with number of fruits per plant (0.323) and total phenol (0.314).
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These results conform with the findings of Mahapatra et al. (2013).
Path Coefficient Analysis
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Although correlation studies help in determining components of yield, with more variables included, the indirect association becomes more complex.
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Two characters may show correlation because they correlate with a common third one.
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Under such circumstances, path analysis helps in partitioning correlation coefficients into direct and indirect effects, permitting a critical examination of the relative importance of each trait.
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The path coefficient analysis in Table 3 revealed that:
- High positive direct effect on fruit yield per plant was exerted by number of fruits per cluster (0.339) and number of fruits per plant (0.727).
- The highest negative direct effect on fruit yield per plant was noted in percent fruit set (-0.328).
- Individual fruit weight recorded lowest positive direct effect of 0.105 on fruit yield.
- The lowest negative direct effect on fruit yield per plant was exerted by number of flowers per cluster (-0.155).
- This high direct effect on yield per plant indicates that direct selection for these traits might be effective, with a possibility of improving yield per plant through selection based on these characters.
- Similar results of direct positive effects for these traits were reported by Meena and Bahadur (2015), Ullah et al. (2015), and Nagariya et al. (2015).
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On the other hand, positive indirect effects of:
- Number of flowers per cluster
- Percent fruit set
- Fruit length
- Fruit diameter
- Individual fruit weight
- Total phenol
Through number of fruits per plant to yield per plant were also observed.
- Similar results for indirect effects were recorded by Islam et al. (2010) and Meena and Bahadur (2015).
