Breeding three line rice hybrids with good grain quality

Transcription

1 Research Article Breeding three line rice hybrids with good grain quality S. Manonmani*, D. Malarvizhi, S. Robin, M. Umadevi, M.Ameenal, R.Pushpam, K. Mohana Sundaram and K.Thiyagarajan Abstract Studies were conducted on 20 rice hybrids with checks to assess the genetic variability, heritability and correlation among the genotypes for fifteen grain quality characters and grain yield. Seeds collected from the thirteen hybrids and check varieties were used for grain quality analysis. To assess the cooking qualities, a total of 30 unbroken milled grains were measured for their length and breadth before cooking. After cooking the grains in water for 10 minutes, they were cooked in boiling water for 20 minutes. The cooked grains were drained by placing on motting paper. The ratio of kernel length after cooking to kernel breath after cooking was expressed as kernel elongation ratio. The linear elongation ratio and breadth-wise elongation ratio was calculated as ratio of kernal length after cooking to kernal length and ratio of kernal breadth after cooking to kernel breadth respectively. The ratio of volume expansion and the increase in weight after cooking of the kernels was also recorded. The hybrids viz., TNRH 160, TNRH 180, TNRH 174, TNRH 173, TNRH 179 recorded medium slender grain type, high head rice recovery, high milling percentage, high LER and low BER and intermediate GT. These hybrids are not having aroma which is preferred by south Indians. Hence, these hybrids will be exploited. Key words: Rice hybrids, quality characters, variability, amylose content. Introduction Rice is a major food of Indian people, with an average consumption of 75 kg per year per person. To meet the food demand for growing population, 5 Mt additional food is required out of which 2Mt share is of rice. Rice is probably the world s most diverse cereal crop. It occupies and will continue to occupy a pivotal place in global food and livelihood security systems. One in every three people depend on rice for more than half of their daily food (Kulkarni et al., 2000). Lester Brown and Halkane of world research Institute in 1995 predicted that India may be forced to import 40 million tones of food grains by 2030 A.D. Department of Rice, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore ,Tamil Nadu, India. * swamimano@yahoo.co.in to feed the expanding population. Hence, arises the urgent need to increase rice production and of the several available options, hybrid rice technology is the most practical and feasible one to increase production. Rice varieties with the improved quality traits should satisfy the traders and millers besides consumers in rice. The quality traits do mean the chemical properties alone, but comprises the physical milling, cooking and eating nutritional qualities etc. Rice unlike other cereals is consumed as a whole grain, therefore physical properties such as size, shape, uniformity and general appearance are important. Further, because most of the rices are milled, the important physical properties are determined primarily by the milled grains. Hence it is possible to develop rice hybrids of acceptable grain quality. Keeping this in view, twenty rice hybrids along with checks were used in the present study to find out the grain quality characters. 1265

2 MATERIALS AND METHODS Twenty entries were raised in randomized block design (RBD) with two replications during Kharif A spacing of 20 x 20 cm was adopted. The recommended package of practices was followed. Grains were harvested and sun dried for three days. Observations were recorded on sixteen characters viz., plot weight, kg /ha, kernel length, kernel breath, L/B ratio, kernel length after cooking, kernel breadth after cooking, linear elongation ratio, breadth wise expansion ratio, volume expansion, gelatinization temperature and amylose content as per the Standard Evaluation System (SES, 1996) descriptors suggested by IRRI. The mean data for each character individually was subjected to statistical analysis. Genetic parameters like variability, GCV, PCV, heritability and genetic advance were calculated by Johnson et al. (1955). The association between yield and component characters and among themselves was computed based on genotypic and phenotypic correlation coefficients (Goulden, 1952). RESULTS AND DISCUSSION The analysis of variance revealed highly significant differences among the genotypes for all the seventeen characters indicating the existence of significant amount of variability among the values for the characters studied. The hybrids viz., TNRH 174, TNRH 179, TNRH 180 and the check ADT 39 recorded significantly higher mean value for hulling per cent and milling per cent. Short and medium type grains produce high head rice recovery ( In the present study, the following genotypes viz., TNRH 179, TNRH 180, TNRH 185, TNRH 196, CORH 2, ADT 39 and ADT 45 are medium grain type and they recorded per cent head rice recovery. These results are in consistent with Asif B. Shikari et al., The hybrids TNRH 185, TNRH 192, TNRH 193, TNRH 196 and TNRH 199 showed significantly maximum mean value for kernel length, L/B ratio, L/B ratio after cooking. TNRH 160, TNRH 174, TNRH 180, TNRH 193, DRRH 2, ADT 39 and ADT 45 recorded intermediate value for gelatinization temperature, amylose content with soft gel consistency and superior performance for volume expansion ratio (Table 1). Linear elongation ratio less than 1.32 is undesirable (Dipti et al., 2003). In the present study, all the entries recorded highest linear elongation ratio. The extent of genetic variability existing in a crop is of great importance, since greater the diversity wider the scope for selection. The extent of character is measured by different statistics namely range, phenotypic coefficient of variation (PCV), genotypic coefficient of variation (GCV), heritability (h 2 ) and genetic advance (GA). Among PCV and GCV estimates comparison of characters based on GCV is more appropriate as it represents the heritable portion of total variability. PCV estimates include environmental effect also. Higher magnitude of genotypic variability in terms of GCV of more than 20 per cent was recorded for gel consistency and gelatinization temperature (Table 2). Vanaja and Babu (2006) reported high GCV values with respect to gel consistency. These traits showing high genotypic variability offer greater scope for genetic improvement through selection. Milling per cent, L/B ratio, L/B ratio after cooking, linear elongation ratio yield (kg/ha) recorded moderate level of GCV indicating considerable amount of variability expressed for these characters. Low GCV estimates were noticed in the present study for hulling per cent, head rice recovery, kernel length, kernel breadth, kernel length after cooking, kernel breadth after cooking, breadth wise expansion, volume expansion ratio and amylase content. Vanaja and Babu (2006) reported low GCV for hulling per cent. In the present study, all the grain quality traits recorded high heritable estimates. Besides showing heritability estimates the characters, gel consistency and gelatinization temperature also showed high GCV estimates, there by pointing to the improvement of these characters through simple phenotypic selection. Similar results were recorded by Krishnaveni and Shobha Rani (2008) for the traits linear elongation ratio, volume expansion ratio, water uptake, gel consistency, gelatinization temperature and amylose content. While considering heritability and genetic advance as per cent of mean together characters like, L/B ratio, L/B ratio after cooking, linear elongation ratio, gel consistency, gelatinization temperature and yield had recorded high heritability and high genetic advance. These results indicate the existence of greater scope for improvement of these characters through direct phenotypic selection by fixing additive gene effects. This is in accordance with Kundu et al. (2008) for number of grains per panicle and single plant yield. The studies on correlation of characters indicate the intensity and direction of character association in a crop. The quality chracters are not corrected with grain yield (Table 3). This agreed with the report of Vivekanandan (1993) that the kernel traits were independent of yield. The information on the inter- 1266

3 correlation among the yield components shows the nature and extent of relationship with each other. This will help in the simultaneous improvement of different characters along with grain yield in the breeding programmes. Milling per cent recorded highly significant positive correlation with head rice recovery and amylose content. Gelatinization temperature is significantly correlated with gel consistency and amylose content. From the foregoing discussion, it can be concluded that the traits viz., grain yield, gel consistency and gelatinization temperature possessing high GCV, heritability and genetic advance could be effectively used in selection. REFERENCES Asif B. Shikari, Syed Zameer Hussain, G.A. Parray, A.G. Rather and Shafiq A.Wani Physico-chemical and cooking properties of non-basmati temperate rice (Oryza sativa L.). Crop Improv., 35(2): Kulkarni, N., G.N. Devi and G. Sarojini Genotype x environment interactions for quality traits in mutants of Samba Mashuri. Oryza, 37(1): Dipti, S.S., Bari M.N and Kabir K.A Grain quality characteristics of some Beruin Rice varieties of Bangaladesh. Pakistan J. Nutri., 2(4): Vanaja, T and Babu L.C Variability in grain quality attributes of high yielding rice varieties (Oryza sativa L.) of diverse origin. J. Trop. Agriculture 44(1-2): Krishnaveni, B. and N. Shobha Rani Inheritance of grain size and shape in rice Oryza, 45(3): Kundu, A., B.K. Senapati, A. Bakshi and G.S. Mandal Genetic variability of panicle characters in tall indica aman rice. Oryza, 45(4): Goulden, C.H Methods of Statistical Analysis. John Wiley and Son. Inc., New York. Johnson, H.W., H.F. Robinson and R.E. Comstock Estimation of genteic and environmental variability in soyabean (Glycine max (L.) Merril.). Agron. J., 47(4): Vivekanandan, P Genetic analysis of grain quality traits in rice (Oryza sativa L.). Ph.D. Thesis, Tamil Nadu Agricultural University, Coimbatore. Standard Evaluation System IRRI (International Rice Research Institute). 1267

4 Table 1. Mean performance of hybrids with checks for grain quality traits Entries H % M % HRR % KL KB L/B KLAC KBAC L/B AC LER BWER VER GT GC TNRH ** ** 2.80** 3.56** 1.84** TNRH ** ** 60.5 TNRH ** 80.65** ** ** 5.00** ** TNRH ** 80.20** ** ** TNRH ** 76.20** ** TNRH ** ** ** ** ** 81.00** TNRH ** ** 9.90** ** 1.58** TNRH ** ** 9.10** ** TNRH ** ** 10.75** ** 1.72** ** TNRH ** ** 9.35** ** DRRH ** ** 71 CORH ** ** 5.90** 92.00** CORH ** ** ** 69 ADT ** 76.70** 59.15** ** ** ** ADT ** ** ** 70.5 ADT ADT ** 2.20** ** ** 91.50** CO (R) ** ** 82.00** 27 P ** ** BPT ** ** 1.58** 5.90** 4.90** 93.50** Mean S.E C.D (1%) Significant at 1 % level (GM+CD) H % - Hulling per cent, M % - Milling percent, HRR % - Head rice recovery per cent, KL - Kernel length, KB - Kernel breadth, L/B - Kernel length/breadth ratio, KLAC - Kernel length after cooking, KBAC - Kernel breadth after cooking, LER - Linear elongation ratio, BWER - Breadth wise expansion ratio, GT- Gelatinization temperature (Alkali spreading value), GC Gel consistency, VER - Volume expansion ratio, AMY Amylose content. 1268

5 Table 2. Estimates of parameters of variability for quality traits Characters Range Mean PV GV PCV % GCV % h 2 GA (%) Hulling per cent (H %) Milling per cent (M %) Head rice recovery (HRR %) Kernel length (KL-mm) Kernel breadth (KB-mm) L/B ratio (L/B) Kernel length after cooking (KLAC-mm) Kernel breadth after cooking (KBAC-mm) L/B ratio after cooking (L/B AC) Linear elongation ratio (LER) Breadth-wise expansion ratio (BWER) Volume expiation ratio (VER) Gelatinization temperature (GT) Gel consistency (GC-mm) Amylose content % (AC %) Yield (Kg/ha) Table 3. Genotypic correlation coefficient among yield and quality traits of 20 rice hybrids Characters H % M % HRR% L/B L/B AC LER BWER VER GT GC AC % YLD H % ** 0.806** ** * ** M % ** ** * ** HRR % ** ** L/B ** * ** L/B AC * ** ** ** LER * BWER * VER * 0.499* GT GC AC % YLD ** Significant at 1 % level * Significant at 5% level 1269