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Your search keyword '"Shilpa M. Naik"' showing total 2 results
Start Over Author "Shilpa M. Naik" Topic quantitative trait loci
2 results on '"Shilpa M. Naik"'

1. Molecular Mapping of QTLs Associated with Lodging Resistance in Dry Direct-Seeded Rice (Oryza sativa L.)

Author

Shailesh Yadav, Uma M. Singh, Shilpa M. Naik, Challa Venkateshwarlu, Perumalla J. Ramayya, K. Anitha Raman, Nitika Sandhu, and Arvind Kumar

Subjects
direct seeded rice, grain yield, lodging resistance, quantitative trait loci, SNP marker, Plant culture, SB1-1110
Abstract

Dry direct-seeded rice (DSR) is an alternative crop establishment method with less water and labor requirement through mechanization. It provides better opportunities for a second crop during the cropping season and therefore, a feasible alternative system to transplanted lowland rice. However, lodging is one of the major constraints in attaining high yield in DSR. Identification of QTLs for lodging resistance and their subsequent use in improving varieties under DSR will be an efficient breeding strategy to address the problem. In order to map the QTLs associated with lodging resistance, a set of 253 BC3F4 lines derived from a backcross between Swarna and Moroberekan were evaluated in two consecutive years. A total of 12 QTLs associated with lodging resistance traits [culm length (qCL), culm diameter (qCD), and culm strength (qCS)] were mapped on chromosomes 1, 2, 6, and 7 using 193 polymorphic SNP markers. Two major and consistent effect QTLs, namely qCD1.1 (with R2 of 10%) and qCS1.1 (with R2 of 14%) on chromosome 1 with id1003559 being the peak SNP marker (flanking markers; id1001973-id1006772) were identified as a common genomic region associated with important lodging resistance traits. In silico analysis revealed the presence of Gibberellic Acid 3 beta-hydroxylase along with 34 other putative candidate genes in the marker interval region of id1001973-id1006772. The positive alleles for culm length, culm diameter, and culm strength were contributed by the upland adaptive parent Moroberekan. Our results identified significant positive correlation between lodging related traits (culm length diameter and strength) and grain yield under DSR, indicating the role of lodging resistant traits in grain yield improvement under DSR. Deployment of the identified alleles influencing the culm strength and culm diameter in marker assisted introgression program may facilitate the lodging resistance under DSR.

Published
2017
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2. Genotype × environment interactions for grain iron and zinc content in rice

Author

Sankar Prasad Das, Challa Venkateshwarlu, Minnuru Nagamallika, Parminder Virk, Nimmai P Mandal, Ballagere Prabhu Mallikarjuna Swamy, Anitha Raman, Russell F. Reinke, Shailesh Yadav, Santosh Kumar, Tomizuddin Ahmed, Shravan K. Singh, Krishna Prasad, Arvind Kumar, Tajwar Izhar, Shilpa M. Naik, Suresh Prasad Singh, and Nitendra Kumar Singh

Subjects
Genotype, 030309 nutrition & dietetics, Iron, Quantitative Trait Loci, Biofortification, chemistry.chemical_element, Negative association, Zinc, High yielding, 03 medical and health sciences, 0404 agricultural biotechnology, Micronutrients, 0303 health sciences, Nutrition and Dietetics, Oryza, 04 agricultural and veterinary sciences, Micronutrient, 040401 food science, Trace Elements, Plant Breeding, Phenotype, chemistry, Seeds, Grain yield, Variance components, Gene-Environment Interaction, Nutrient deficiency, Agronomy and Crop Science, Food Science, Biotechnology, Nuclear chemistry
Abstract

Background Nutrient deficiency in humans, especially in children and lactating women, is a major concern. Increasing the micronutrient concentration in staple crops like rice is one way to overcome this. The micronutrient content in rice, especially the iron (Fe) and zinc (Zn) content, is highly variable. The identification of rice genotypes in which there are naturally high Fe and Zn concentrations across environments is an important target towards the production of biofortified rice. Results Phenotypic correlations between grain Fe and Zn content were positive and significant in all environments but a significant negative association was observed between grain yield and grain Fe and Zn. Promising breeding lines with higher Zn or Fe content, or both, were: IR 82475-110-2-2-1-2 (Zn: 20.24-37.33 mg kg-1 ; Fe: 7.47-14.65 mg kg-1 ); IR 83294-66-2-2-3-2 (Zn: 22-37-41.97 mg kg-1 ; Fe: 9.43-17.16); IR 83668-35-2-2-2 (Zn: 27.15-42.73 mg kg-1 ; Fe: 6.01-14.71); IR 68144-2B-2-2-3-1-166 (Zn: 23.53-40.30 mg kg-1 ; Fe: 10.53-17.80 mg kg-1 ) and RP Bio 5478-185M7 (Zn: 22.60-40.07 mg kg-1 ; Fe: 7.64-14.73 mg kg-1 ). Among these, IR82475-110-2-2-1-2 (Zn: 20.24-37.33 mg kg-1 ; Fe: 7.47-14.65 mg kg-1 ) is also high yielding with 3.75 t ha-1 . Kelhrie Cha (Zn: 17.76-36.45 mg kg-1 ; Fe: 7.17-14.77 mg kg-1 ), Dzuluorhe (Zn: 17.48-39.68 mg kg-1 ; Fe: 7.89-19.90 mg kg-1 ), Nedu (Zn: 18.97-43.55 mg kg-1 Fe: 8.01-19.51 mg kg-1 ), Kuhusoi-Ri-Sareku (Zn: 17.37-44.14 mg kg-1 ; Fe: 8.99-14.30 mg kg-1 ) and Mima (Zn: 17.10-45.64 mg kg-1 ; Fe: 9.97-17.40 mg kg-1 ) were traditional donor genotypes that possessed both high grain Fe and high Zn content. Conclusion Significant genotype × location (G × L) effects were observed in all traits except Fe. Genetic variance was significant and was considerably larger than the variance of G × L for grain Zn and Fe content traits, except grain yield. The G × L × year variance component was significant in all cases. © 2020 Society of Chemical Industry.

Published
2019

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