M
Mahalingam Govindaraj
Researcher at International Crops Research Institute for the Semi-Arid Tropics
Publications - 86
Citations - 1924
Mahalingam Govindaraj is an academic researcher from International Crops Research Institute for the Semi-Arid Tropics. The author has contributed to research in topics: Biofortification & Biology. The author has an hindex of 19, co-authored 70 publications receiving 1392 citations. Previous affiliations of Mahalingam Govindaraj include CGIAR & PSG College of Arts and Science.
Papers
More filters
Journal ArticleDOI
Importance of Genetic Diversity Assessment in Crop Plants and Its Recent Advances: An Overview of Its Analytical Perspectives
TL;DR: This paper comprehensively reviews the significance of plant genetic diversity (PGD) and PGR especially on agriculturally important crops; risk associated with narrowing the genetic base of current commercial cultivars and climate change; analysis of existing PGD analytical methods in pregenomic and genomic era; and modern tools available for PGD analysis in postgenomic era.
Journal ArticleDOI
Genetic enhancement of grain iron and zinc content in pearl millet
TL;DR: In this paper, the authors investigated some of the factors that can enhance breeding efficiency for these micronutrients and showed that effective selection for both iron and zinc content is possible without compromising on grain yield and seed size, and the rapid and cost-effective EDXRF screening technique can accelerate the breeding efficiency.
Journal ArticleDOI
Combining Ability and Heterosis for Grain Iron and Zinc Densities in Pearl Millet
Mahalingam Govindaraj,Kedar N. Rai,P. Shanmugasundaram,Sangam L. Dwivedi,Kanwar L. Sahrawat,A. R. Muthaiah,A. S. Rao +6 more
TL;DR: Results showed that simultaneous selection for both micronutri- ents is likely to be effective with respect to all these performance parameters, and consistency in the patterns of results implies that these results could be of wider application to the genetic improvement of Fe and Zn densities in pearl millet.
Journal ArticleDOI
Grain iron and zinc density in pearl millet: combining ability, heterosis and association with grain yield and grain size
Anand Kanatti,Kedar N. Rai,Kommineni Radhika,Mahalingam Govindaraj,K. L. Sahrawat,Aluri S. Rao +5 more
TL;DR: Breeding for high Fe and Zn densities with large grain size will be highly effective, however, combining high levels of these micronutrients with high grain yield would require growing larger breeding populations and progenies than breeding for grain yield alone, to make effective selection for desirable recombinants.
Journal ArticleDOI
Regression analysis and ANN models to predict rock properties from sound levels produced during drilling
TL;DR: In this paper, the authors used multiple regression, artificial neural network (MLP) and RBF models to predict rock properties using soft computing techniques such as multiple regression and artificial neural networks.