Background: High yielding rice varieties are usually low in grain iron (Fe) and zinc (Zn) content. These two micronutrients are involved in many enzymatic activities, lack of which cause many disorders in human body. Biofortification is a cheaper and easier way to improve the content of these nutrients in rice grain. Results: A population panel was prepared representing all the phenotypic classes for grain Fe-Zn content from 485 germplasm lines. The panel was studied for genetic diversity, population structure and association mapping of grain Fe-Zn content in the milled rice. The population showed linkage disequilibrium showing deviation of Hardy-Weinberg's expectation for Fe-Zn content in rice. Population structure at K = 3 categorized the panel population into distinct sub-populations corroborating with their grain Fe-Zn content. STRUCTURE analysis revealed a common primary ancestor for each sub-population. Novel quantitative trait loci (QTLs) namely qFe3.3 and qFe7.3 for grain Fe and qZn2.2, qZn8.3 and qZn12.3 for Zn content were detected using association mapping. Four QTLs, namely qFe3.3, qFe7.3, qFe8.1 and qFe12.2 for grain Fe content were detected to be co-localized with qZn3.1, qZn7, qZn8.3 and qZn12.3 QTLs controlling grain Zn content, respectively. Additionally, some Fe-Zn controlling QTLs were co-localized with the yield component QTLs, qTBGW, OsSPL14 and qPN. The QTLs qFe1.1, qFe3.1, qFe5.1, qFe7.1, qFe8.1, qZn6, qZn7 and gRMm9-1 for grain Fe-Zn content reported in earlier studies were validated in this study. Conclusion: Novel QTLs, qFe3.3 and qFe7.3 for grain Fe and qZn2.2, qZn8.3 and qZn12.3 for Zn content were detected for these two traits. Four Fe-Zn controlling QTLs and few yield component QTLs were detected to be colocalized. The QTLs, qFe1.1, qFe3.1, qFe5.1, qFe7.1, qFe8.1, qFe3.3, qFe7.3, qZn6, qZn7, qZn2.2, qZn8.3 and qZn12.3 will be useful for biofortification of the micronutrients. Simultaneous enhancement of Fe-Zn content may be possible with yield component traits in rice.

Laboratory incubation and pot culture experiments conducted with five laterite, two red, two alluvial and one calcareous black, rice-growing soils showed that the power of extraction of silica both from dry and wet soils was in the descending order 0.2 N HC1, 0.025 M citric acid, N NaOAc at pH 4 and distilled water. Flooding increased the silica extracted by these four extractants which reached a peak in 20 days after which there was either no change or a slight decrease during the next forty days. The silica content and uptake in the crop was low in all except the black soil. The silica content of the dry-season crop was higher than that of the wet-season crop possibly because of more favourable climatic conditions prevailing during dry season which enhanced absorption. Correlation studies between silica extracted by different solutions both in dry and flooded soils and content and uptake of silica by the rice plant indicated that 0.025 M citric acid was the best extractant which could be used in the evaluation of the silicon supplying power of rice soils.

A, direct method of estimation of silica in rice plant tissues is reported. This involves the digestion of finely ground plant samples with concentrated nitric acid in corning-glass conical flasks followed by dissolution in Na~CO3 in stainless-steel beakers; the plant silica is thereby converted into molybdenum reactive form which is estimated colorimetrically. This method represents an improvement over the time consuming fusion procedure followed ordinarily and also dispenses with use of platinumware.

An attempt to derive a relation between spectral data of rice canopies and their grain yield has been made in the Cuttack and Puri districts of Orissa for Kharifrice using Landsat MSS digital data of three years (1984)(1985)(1986). Necessary sensor-to-sensor transformations of Landsat MSS to IRS LISS-I and acquisition date normal::zation with respect to a typical rice growth profile were also carried out. Using srch an empirical relation, rice yield was estimated for Kharif in 1988 using IRS-IA LISS-I data at district level. Deviation of the estimated yields from the reported figures varied from 2 per cent to 14 per cent at the district-aggregated level.

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