Genetic Variability Induced by Gamma Rays and Preliminary Results Of Low-Cost TILLING On M2 Generation Of Chickpea (Cicer arietinum L.).

In order to increase genetic variability for chickpea improvement, the Kabuli genotype, variety Ghab4 was treated with 280 Grays of gamma rays (Cobalt 60). Field characterization began with the M2 generation. A total of 135 M2 families were sown in the field resulting in approximately 4000 plants. Traits related to phenology (days to flowering, days to maturity), plant morphology of vegetative part (plant height, height of first pod, number of primary branches per plant) and yield (number of seeds per pod, total number of pods per plant, total number of seeds per plant, seed yield and hundred seed weight) were recorded and analyzed to evaluate genetic variability. An evaluation of the efficacy of low-cost TILLING (Targeting Induced Local Lesions IN Genomes) to discover mutations in M2 generation was undertaken. The efforts were concentrated on genes involved in resistance to the two important diseases of chickpea; Aschochyta blight (AB) and Fusarium wilt (FW), as well as genes responsible for early flowering. The analysis of variance showed a highly significant difference among families for all studied traits. The higher estimates of genetic parameters (genotypic and phenotypic coefficient of variation, broad sense heritability and genetic advance) were recorded for number of seeds per plant and seed yield. Seed yield was highly significant and positively correlated with number of pods and seeds per plant. Path analysis showed that the total number of seeds per plant had the highest positive direct effect followed by hundred seed weight. One cluster from nine exhibited the highest mean values for total number of pods and seeds per plant and seed yield per plant. According to Dunnett’s test, 37 M2 families superior to the control were determined for 5 agronomical traits. Pilot experiments with low-cost TILLING show that the seed stock used for mutagenesis is homogeneous and that small mutations do not predominate at the dosage used. Keywords: Induced mutations, genetic parameters, path analysis, cluster analysis, yield components, selection, low-cost TILLING, background mutations