Correlation and Path Analysis for Iron and Zinc Content in Segregating Population of Rice  

Sala M1 , S. Geetha2
1. Agricultural College and Research Institute, Tamil Nadu Agricultural University, Madurai, India
2. Anbil Dharmalingam, Agricultural College &Research Institute, Trichy, India
Author    Correspondence author
Rice Genomics and Genetics, 2015, Vol. 6, No. 1   doi: 10.5376/rgg.2015.06.0001
Received: 21 Jan., 2015    Accepted: 05 Mar., 2015    Published: 11 Mar., 2015
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Preferred citation for this article:

Sala and Geetha, 2015, Correlation and Path Analysis for Iron and Zinc Content in Segregating Population of Rice, Rice Genomics and Genetics, Vol.6, No.1 1-5 (doi: 10.5376/rgg.2015.06.0001)

Abstract

Correlation and path analysis was carried out for yield and yield components in F4 generation. The correlation analysis indicated that the characters namelydays to fifty percent flowering, plant height, number of productive tillers per plant, hundred grain weight, kernel breadth and kernel L/B ratio, kernel breadth after cooking, breadth wise expansion ratio, linear elongation ratio and zinc content exhibited positive and significant correlation with grain yield. All these characters were also inter correlated among themselves. Iron content showed negative association with yield. Plant height, number of filled grains per panicle, hundred grain weight, kernel breadth, kernel L/B ratio and zinc content showed positive high to very high direct contribution with grain yield. So above traits might be given importance during selection which may result in yield improvement. Here plant height and days to fifty percent flowering and zinc content exhibited significant positive association in above two cross combinations. Zinc content had positive correlation with yield. So TRY (R) 2×Mapillai Samba cross used simultaneous improvement of zinc with grain yield.

Keywords
Biofortification; Correlation; Iron & Zinc content; Path analysis

Rice is the dominant cereal crop in many developing countries and also the staple food for more than half of the world’s population. Currently, polished rice contains an average of 2 parts per million (ppm) iron (Fe) content and 12 ppm of zinc (Zn) content. In many Asian countries, rice provides 50-80 percent of the energy intake of the poor but it does not provide enough essential micronutrients to eliminate “hidden hunger,” in particular Iron Deficiency Anemia (IDA) and zinc deficiency. In India the IDA affects nearly 60 percent of the population. Because of the high per capita consumption of rice in these countries, improving its nutritive value by increasing iron and zinc levels in the grain can have significant positive health outcomes for millions of people. Developing rice with high iron and zinc through the process of “biofortification” aims to combine high mineral content with grain quality and agronomic characteristics, such as high yield to ensure acceptability by farmers and consumers.
1 Materials and Methods
Seeds of F3 generation of two cross combinations generated from Anbil Dharmalingam Agricultural College and Research Institute, Trichy. viz., ADT 37×IR68144-3B-2-2-3, TRY (R) 2×Mapillaisamba were utilized as the experimental material in the present study. Among the parents viz., TRY (R) 2, ADT 37 and ADT 43 are high yielding commercial varieties, where IC 255787 (3.94 ppm) and IR68144-3B-2-2-3 (4.39 ppm) are the iron donors and Mapillaisamba (3.50 ppm) is a zinc donor these lines were used in earlier hybridization programme for introgression of high iron and zinc content in high yielding varieties Table 1. The F4 generation was raised during August to November, 2011 at Agricultural College and Research Institute, Madurai.The F4 progenies were raised along with their parents in randomized block design with two replications. A total of five families were selected from each cross combination based on high iron and zinc content in F3 population. For each family seventy five seedlings per replication were raised with a spacing of 20 cm between the rows and 15 cm between the plants. Each family had five rows of 15 single plants each. Each family had five rows of 15 single plants each. The recommended agronomic practices were followed throughout the crop growth period. Biometrical observations were recorded from five single plants per family per replication, randomly selected.

 

Table 1 Iron and zinc content in parents and cross cominations


The collected data in each F4 generation were subjected to estimate the correlation and path analysis as explained by Singh and Chaudhary (1985) where grain yield/plant was kept as resultant variable and other yield component characters as causal variables. The zinc and iron content were determined by using Atomic absorption spectrophotometer. All the statistical analysis were done by using GENRES statistical software.
1.1 Estimation of iron and zinc content:
The rice grain samples were air dried to 12%~14% moisture content and hand hulled using palm dehusker, finally the brown rice was obtained. Brown rice was polished by using sand paper (No.100). The polished rice grains were powdered and used for analysis.Half a gram of powdered rice grain sample with 12 ml of triple acid mixture (9:2:1 Nitric: Sulphuric: Perchloric acid) was kept for overnight digestion. The digested samples were kept on a hot plate till the solution turns colourless. The extract was diluted to 50 ml and fed to the Atomic Absorption Spectrophotometer. For the measurement of iron, FeSO4 was used as standard and for zinc, the standard was ZnSO4. The concentrations were expressed as parts per million (ppm).

2 Results and Discussion

2.1 ADT37×IR68144-3B-2-2-3
Grain iron content ranged from 3.420 ppm to 5.420mm in F4 generation of ADT37×IR68144- 3B-2-2-3 Table 1. Days to fifty per cent flowering (0.526), plant height (0.538) number of productive tillers per plant (0.448), number of filled grains per panicle (0.687), kernel breadth after cooking (0.376), breadth wise expansion ratio (0.240) and grain zinc content (0.344) exhibited positive and significant correlation with grain yield Table 2. These findings were supported by Nagesh et al. (2012) for number of productive tillers per plant in F1 and Kalaimaghal (2011) reported positive and significant association with yield for plant height, number of productive tillers (both the generations), hundred grain weight (both the generations), kernel length and kernel breadth in F2 population, iron content in F2 of the cross ADT37×IR68144-3B-2-2-3. In path analysis number of filled grains per panicle had positive and very high direct contribution with yield followed by kernel L/B ratio, and zinc content table3.In path analysis iron content had negatively high direct effect with yield. Purusothaman (2010) and Krishna et al. (2008) also reported that zinc content and kernel L/B ratio had positive direct effect with yield.

 

 

Table 2 Genotypic correlation between yield and yield components in F4 generation of TRY (R) 2×Mapillai Samba


2.2 TRY (R) 2×Mapillaisamba

Grain zinc content ranged from 1.62-1.86 ppm in F4 generation of TRY (R) 2×Mapillaisamba Table 1. Days to fifty per cent flowering (0.878), plant height (0.773), hundred grain weight (0.903) linear elongation ratio (0.940), kernel L/B ratio (0.676) and zinc content (0.584), exhibited significant and positive correlation with yield in F4 generation Table 2. Plant height, hundred grain weight, zinc content and kernel breadth and kernel breath after cooking exhibited high to very high positive direct effect with yield table 3. These results were supported by Nagesh et al. (2012) for plant height in hybrids, Kalaimaghal (2011) in F2, F3 generation for zinc content, Chakraborty et al. (2010) for hundred grain weight and Krishna et al. (2008) for kernel breadth. Linear elongation ratio had negative direct effect due to the high indirect effect of kernel length, kernel breadth after cooking, breadth wise expansion ratio and iron content. Hence, selection based on plant height, hundred grain weight, zinc content and kernel breadth of this cross will be useful for improvement in rice. 


3 Conclusion
The correlation analysis revealed that the characters viz., days to fifty percent flowering, plant height, number of productive tillers per plant, hundred grain weight, kernel length, kernel breadth, kernel L/B ratio, kernel breadth after cooking and zinc content exhibited positive and significant association with grain yield. Therefore selection pressure exerted on the positive side of these traits will automatically increase the yield. Iron content showed negative correlation with yield but zinc showed positive correlation with yield in TRY (R) 2 × Mapillai Samba cross combination. Here plant height and days to fifty percent flowering and zinc content exhibited significant and positive association in above two cross combinations. Zinc content had positive correlation with yield. So TRY (R) 2×Mapillai Samba cross used simultaneous improvement of zinc with grain yield.
References
Chakraborty S., Pradip K., Biswajit G., Kalyan V., and Bhubaneswar Barman., 2010, Quantitative genetic analysis for yield and yield components in boro rice (Oryza sativa L.), Nat. Sci. Biol., 2(1): 117-120
Kalaimaghal R., 2011, Studies on genetic variability of grain iron and zinc content in F2, F3 generation of rice (Oryza sativa L.),M.Sc. (Ag.) Thesis(Unpubl.), TNAU, Coimbatore
Krishnaveni B., and Shobha Rani. N., 2006, Association of grain yield with quality characteristics and other yield components in rice. Oryza, 43(4): 320-322
Krishna L., Raju Ch D., and Raju. Ch.S., 2008, Genetic variability and correlation in yield and grain quality characters of rice germplasm, The Andhra Agric. J., 55(3):27-279
Nagesh, Ravindrababu V., Usharani G., and Dayakar Reddy T., 2012, Grain iron and zinc association studies in rice (Oryza sativa L.) F1 progenies, Archives of Appl. Sci. Res., 4 (1): 696-702

Purusothaman R., 2010, Genetic analysis for high iron and zinc content in rice (Oryza sativa L.) grains, M.Sc., (Ag.) Thesis (Unpubl.), TNAU, Coimbatore
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