Selection indices for yield, yield components and resistance to late leaf spot in groundnut (Arachis hypogaea L.)

Introduction

Groundnut (Arachis hypogaea L.) is one of the most economic oilseed crops of the world. It is considered as the world's fourth largest source of edible oil and third most important source of vegetable protein (Desai et al., 1999) [4] . Yield in crops is a quantitative trait and has a complex genetic control mechanism and hence, direct selection is not much effective on it. Since the economic part of groundnut known as pod is developed under the soil, the prediction of its performance based on aerial morphological characters is almost difficult (Weiss, 2000) [15] . The most desirable approach to improve characteristics such as pod yield is simultaneous selection based on related traits (Bos and Caligri, 2007) [1] . This can be done using selection index, which is multiple regressions of genotypic values on phenotypic values of several traits (Falconer, 1996) [6] . The use of selection index is superior in improving complex traits (Hasel and Lush, 1942) [9] . Furthermore, the selection indices approach aimed at determining the most suitable combination of traits with the intention of indirectly improving the pod yield in groundnut was well documented (Dobariya et al., 2008) [5] . Certain desired plant characteristics are considered while selecting for particular genotype with varying weightage given to different traits for arriving on decisions. The better way of exploiting genetic correlations with several traits having high heritability is to construct an index which combines information on all the characters associated with yield. This suggests the use of selection index, which gives proper weight to each of the two or more characters to be considered. Selection index was proposed for the first time by Smith (1936) [14] on the basis discriminant function of Fisher (1936) [7] . Hazel and Lush (1943) [10] and Robinson et al. (1951) [13] showed that the selection based on such an index is more efficient than selecting individually for the various characters. Few studies on selection indices in (2008) [5] ; Babariya et al. (2014) [2] and Gupta et al. (2015) [8] . However, in order to have a more comprehensive knowledge about genetic variability for yield and its attributing traits, it is important to find out a suitable selection indices for the improvement of pod yield in groundnut. Keeping these facts in view, the present study was undertaken in order to construct selection indices for efficient selection in groundnut breeding programme.

Materials and Methods

Thirty one genotypes of groundnut were sown in a Randomized Block Design (RBD) with three replications during kharif 2023. Each genotype was sown in 2 rows of 3 m length with a spacing of 30 cm between rows and 10 cm between plants within the row. The crop was raised under irrigated conditions and recommended dose of chemical fertilizers at the rate of 20 kg of N, 40 kg of P 2 O 5 and 50 kg K 2 O ha -1 in the form of urea, single super phosphate, murate of potash, respectively were applied during final ploughing operation and gypsum was added at the rate of 500 kg ha -1 at peak flowering stage followed by one hand weeding to remove weeds and to mix the gypsum properly in the soil.

Apart from these cultural operations, need based plant protection measures were taken to control insect pests.

Observations were recorded for all the genotypes separately on randomly chosen five competitive plants in each genotype in each replication for all the characters except for days to 50% flowering and days to maturity which were recorded on plot basis. Data were recorded for 15 characters viz., days to 50% flowering, days to maturity, plant height at harvest, number of primary branches/plant, number of secondary branches/plant, number of mature pods/plant, number of immature pods/plant, pod yield/plant, dry haulm yield/plant, harvest index percent, shelling percent, kernel yield/plant, sound mature kernel percent, hundred kernel weight, disease scoring of late leaf spot disease at 75 DAS and 90 DAS. Discriminant function analysis described by Dabholkar (1992) [3] was used to construct the selection indices involving six characters, pod yield/plant (X 1 ), number of primary branches/plant (X 2 ), 100-kernel weight (X 3 ), biological yield/plant (X 4 ), harvest index (X 5 ) and days to maturity (X 6 ). For computing selection indices, pod yield/plant was considered as the dependent variable with the relative efficiency of 100%. The model suggested by Robinson et al. (1951) [13] was used for the construction of genetic advance as well as selection indices and development of a required discriminant function using six characters along with pod yield/plant.

Results and Discussion

High genetic advance coupled with high heritability estimates offers the most suitable condition for selection which indicates the presence of additive genes in the trait and further suggest reliable crop improvement through selection of traits (Ogunniyan and Olakojo, 2014) [11] . Therefore, total six characters out of fifteen characters under study with high genetic advance coupled with high heritability were used for construction of selection indices. A total of sixty three selection indices (Table 1) based on six characters constructed in all possible combinations revealed that the selection efficiency was high over straight selection when selection was based on individual components. Dry haulm yield/plant (g) showed a genetic advance of 23.17%, which was higher than those calculated for other characters including pod yield/plant suggested that dry haulm yield/plant (g) proved to be better selection index based on one character. The highest genetic gain (Table 1) of 34.45% was obtained when selection was simultaneously based on discriminant function of two characters, e.g. pod yield/plant (X 1 ) and dry haulm yield/plant (X 3 ). When three characters, e.g. number of primary branches/plant (X 2 ), dry haulm yield/plant (X 3 ) and kernel yield/plant (X 4 ) were taken together, the genetic advance increased to 38.14%. Index based on combination of four characters, i.e. number of primary branches/plant (X 2 ), dry haulm yield/plant (X 3 ), late leaf spot at 75 DAS (X 5 ) and late leaf spot at 90 DAS (X 6 ) recorded high genetic gain of 46.82%. Index based on combination of five characters, i.e. number of primary branches/plant (X 2 ), dry haulm yield/plant (X 3 ), kernel yield /plant (X 4 ), late leaf spot at 75 DAS (X 5 ) and late leaf spot at 90 DAS (X 6 ) recorded high genetic gain of 49.01%. The maximum gain of 52.04% was achieved by taking six characters at a time, i.e. pod yield/plant (X 1 ), number of primary branches/plant (X 2 ), dry haulm yield/ plant (X 3 ), kernel yield/plant (X 4 ), late leaf spot at 75 DAS (X 5 ) and late leaf spot at 90 DAS (X 6 ). Thus, the current study revealed that the index which includes more than one character, gave high genetic advance, suggesting the utility of constructing of selection indices for effecting simultaneous improvement in several characters. Hazel and Lush (1943) [10] stated that the superiority of selection based on index increases with an increase in the number of characters under selection. Smith (1936) [14] , Rao (1974) [12] , Dobariya et al. (2008) [5] , Babariya et al. (2014) [2] and Gupta et al. (2015) [8] also with same opinion that inclusion of characters one by one in the function resulted in increasing genetic advance and that the selection indices improve the efficiency than the straight selection for yield alone. The relative efficiency (RE%) of various selection indices presented in Table 1 indicated that when relative efficiency of single character index was measured over straight selection for pod yield/plant, the efficiency was declined to less than 100%. This observation indicated that the indirect selection through individual traits over straight selection for pod yield/plant alone would not be effective. Therefore, an increase in number of characters in combination with yield would be effective.

It is interesting to note that selection efficiency (Table 2) improved with an increase in number of characters in combination with yield. For example, average selection efficiency of 108.74%, when one character was included in selection function. Similarly, the selection efficiency was 236.27% for two characters, 341.16% for three characters, 458.11% for four characters, 488.40% for five characters and 532.01% for six characters selection indices improve the selection efficiency than the straight selection for yield alone with an increase in the number of characters under selection. Selection indices with six characters, i.e. pod yield/plant (X 1 ), number of primary branches/plant (X 2 ), dry haulm yield/plant (X 3 ), kernel yield/plant (X 4 ), late leaf spot at 75 DAS (X 5 ) and late leaf spot at 90 DAS (X 6 ), therefore, appear to be more useful. It can be seen that number of primary branches/plant (X 2 ), dry haulm yield/plant (X 3 ) and kernel yield/plant (X 4 ) were the characters being commonly involved in more number of the combinations, the next being pod yield/plant (X 1 ), late leaf spot at 75 DAS (X 5 ) and late leaf spot at 90 DAS (X 6 ) in order (Table 3). Keeping in view, the basic idea of saving time and labour in a selection programme, it would be desirable to base the selection of few characters. In the present study, selection index based on six characters gave maximum genetic gain and high efficiency over straight selection, but practically it is more cumbersome to use in the selection exercise. However, in practice, the plant breeder might be interested in maximum gain with minimum number of characters. In the present study, selection index based on four characters (number of primary branches/plant + dry haulm yield/plant + late leaf spot at 75 DAS + late leaf spot at 90 DAS) showing genetic gain (46.82%) and selection efficiency (516.94%) comparable to some extent of those based on five or more characters, which is more desirable and practically possible to use breeder than the index that includes more number of characters.

Conclusion

From this investigation, it is concluded that improvement of pod yield in groundnut could be achieved by selecting the parents with these four characters; number of primary branches/plant + dry haulm yield/plant + late leaf spot at 75 DAS + late leaf spot at 90 DAS.

References

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