Characterization and exploring genetic potential of landraces from Odisha with special emphasis on grain micronutrient content for benefaction of biofortification in rice.

Assessing genetic variability of micronutrient content in association with qualitative and quantitative traits in germplasm is prerequisite for effective biofortification programme. Odisha, a state of eastern India is considered as one of the most potential hot spot of diversity of cultivated rice for grain yield and nutritional traits. Significant variability for most of the qualitative and quantitative traits including Fe and Zn content was observed in a set of 293 germplasm with varying kernel colour encompassing 14 districts of Odisha. Mostly these landraces were low yielding with some exception (Haldigundi: AC 36454, 50.08 g/plant). These landraces were mostly represented by medium Fe (10-20 ppm)-medium Zn group (20-30 ppm). Fe and Zn content had positive association with each other and also with grain size. Landraces with red kernel colour were observed to have slightly higher average Zn content (26.30 ppm) as compared to white (25.87 ppm) grains. Diversity analysis of 14 districts revealed that Nayagarh, a south-eastern district was rich in Fe content while Deogarh, Keonjhar and Mayurbhanj, all north-western districts were rich in Zn content. This study identified 10 superior micronutrient dense genotypes with medium to high Fe and Zn content. This set of donors for micronutrient content was validated in another year. Champeisiali (AC 43368) and Gedemalati (AC 34306) with highest Fe (44.1 ppm) and Zn (40.48 ppm) content, respectively were detected over the environments. Identified donors and associated traits could be utilized in biofortificaion programme using appropriate breeding methodologies for enhancing micronutrients in high yielding background. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-021-01119-7.

Detection of stable QTLs for grain protein content in rice (Oryza sativa L.) employing high throughput phenotyping and genotyping platforms.

Lack of appropriate donors, non-utilization of high throughput phenotyping and genotyping platforms with high genotype × environment interaction restrained identification of robust QTLs for grain protein content (GPC) in rice. In the present investigation a  BC3F4 mapping population was developed using grain protein donor, ARC10075 and high-yielding cultivar Naveen and 190 lines were genotyped using 40 K Affimetrix custom SNP array with the objective to identify stable QTLs for protein content. Three of the identified QTLs, one for GPC (qGPC1.1) and the other two for single grain protein content (qSGPC2.1, qSGPC7.1) were stable over the environments explaining  13%, 14% and 7.8% of the phenotypic variances, respectively. Stability and repeatability of these additive QTLs were supported by the synergistic additive effects of multi-environmental-QTLs. One epistatic-QTL, independent of  the  main effect QTL was detected over the environment for SGPC. A few functional genes governing seed storage protein were hypothesised inside these identified QTLs. The qGPC1.1 was validated by NIR Spectroscopy-based high throughput phenotyping in BC3F5 population. Higher glutelin content was estimated in high-protein lines with the introgression of qGPC1.1 in telomeric region of short arm of chromosome 1. This was supported by the postulation of probable candidate gene inside this QTL region encoding glutelin family proteins.