Rice is the life and the prince among cereals as this unique grain helps to sustain two thirds of the world’s population. Asia is the biggest rice producer, accounting for 90 per cent of the world’s production and consumption of rice (Anonymous, 2007). It is considered as the main staple food for more than 50 per cent of the world’s population. Rice provides 75 per cent of the calories and 55 per cent of the protein in the average daily diet of the people although it has an incomplete amino acid profile and comprises confined amount of essential micronutrients (Bhuiyan et al., 2002). The per capita consumption of rice is very high ranging from 62 to 190 kg/year (Graham et al., 1999). To be healthy, human beings require more than 20 mineral elements and more than 40 nutrients, particularly vitamins and essential amino acids, all of which can be supplied by an appropriate diet (Philip and Martin, 2005). However, human diets often lack one or more of essential nutrients and cause micronutrient malnutrition. Micronutrient malnutrition is recognized as a massive and rapidly growing public health issue especially among poor people living on an unbalanced diet dominated by a single staple grain such as rice. Among the major micronutrient deficiencies common in rice consuming countries , iron and zinc deficiencies (the so called “hidden hunger”), affect over three billion people worldwide, mostly in developing countries (Welch and Graham, 2004). Plant breeding to enhance the nutrient quality of staple food crops holds promise for a low cost and sustainable approach to alleviate the problem of micronutrient malnutrition among the poorest segments of the population of developing countries. This approach has been called biofortification. Biofortification reduces malnutrition by breeding essential micronutrients into staple crops. This approach bridges the fields of human nutrition, crop science and public health to develop a set of highly sustainable nutrition interventions in a cost-effective manner. Exploiting the genetic variation in crop plants for micronutrient content is one of the most powerful tools to change the nutrient balance of a given diet on a large scale.

In the present investigation ADT 37 x IR68144-3B-2-2-3 showed high mean value for the characters viz., kernel length, kernel breadth after cooking, iron content. TRY (R) 2 x Mapillaisamba had high mean value for the characters viz., zinc content, breadth wise expansion ratio. The genotypic and phenotypic coefficient of variability were low in both the crosses for the most of the traits viz., kernel length, kernel breadth, kernel L/B ratio, kernel length after cooking, kernel breadth after cooking, linear elongation ratio and breadth wise expansion ratio (Table 1). It indicated that all the crosses might have attained homozygosity in F₄ itself for these traits. These results were in accordance with Nandeshwar et al. (2010) whostudied F₂ progenies which were derived from the crosses IR-62 × Samba Mashuri and Kunti x Dudheswar and the report of Kumar et al. (2006) in rice F₂ generation for kernel length. Umadevi et al. (2010) recorded low genotypic and phenotypic coefficient of variability for kernel breadth in 110 rice genotypes.The findings of Vanaja and Babu (2006) recorded low genotypic and phenotypic coefficient of variability for kernel length after cooking and kernel breadth after cooking, breadth wise expansion ratio in 10 quality parameters in set of 56 high yielding diverse rice genotypes which is corroborates the current investigation. For iron and zinc content moderate GCV and PCV was observed in F₅ generation. Hence, these traits need one or more generations in order to attain homozygosity. These results were in parallel with the findings of Kalaimaghal (2011) who observed moderate GCV and PCV for iron content in the in F₂ and F₃ the cross ADT37 × IR68144-3B-2-2-3.

Table 1 Variability studies for quality traits in rice with high iron and zinc content in F4 & F5 Generation

High heritability coupled with high genetic advance was observed in ADT37 x IR68144-3B-2-2-3 only for iron and zinc content, except TRY(R) 2× Mapillaisamba which showed high heritability with moderate genetic advance. Hence, these traits were least influenced by environment and mostly governed by additive gene action. Therefore, there is scope for improvement of iron and zinc content by exercising selection pressure on these two characters. These results were in agreement with Shanmuga Sundara Pandian (2007), Purusothaman (2010) and Aswini Shamak et al. (2011) in F₄ and F₅ generation. Low heritability with low genetic advance as percentage of mean was observed for kernel length, kernel breadth and kernel L/B ratio in all the crosses in both the generations. The findings of Jayasree (2007) and Umadevi et al. (2010) in genotypes observed medium to high heritability with high genetic advance as percentage of mean for kernel length after cooking, kernel breadth after cooking, linear elongation ratioand breadth wise expansion ratio which in contrast with the result of current investigation. Based on mean, GCV & PCV, heritability and genetic advance, it was understood that the progenies of ADT 37 x IR68144-3B-2-2-3 would be more useful for improving grain iron content with the desirable quality traits viz., kernel length, kernel breadth after cooking. Similarly TRY (R) 2 × Mapillaisamba segregants could be used for improving the grain zinc content and breadth wise expansion ratio.

The ratio of mean length of cooked rice to mean length of milled rice was computed as linear elongation ratio (Juliano and Perez, 1984).

The zinc and iron content were determined by using Atomic Absorption Spectrophotometer as suggested by Jackson (1973). All the statistical analysis was done by using GENRES statistical software GEN STAT 2004.

Welch., R.M. and R.D., Graham. 2004, Breeding for micronutrients in staple food crops from a human nutrition perspective. J. Exp. Bot., 55: 353-364
http://dx.doi.org/10.1093/jxb/erh064