Rice biofortification: breeding and genomic approaches for genetic enhancement of grain zinc and iron contents

Autor: P. Senguttuvel, Padmavathi G, Jasmine C, Sanjeeva Rao D, Neeraja CN, Jaldhani V, Beulah P, Gobinath R, Aravind Kumar J, Sai Prasad SV, Subba Rao LV, Hariprasad AS, Sruthi K, Shivani D, Sundaram RM, Mahalingam Govindaraj

Publikováno v: Frontiers in Plant Science, Vol 14 (2023)

Rice is a highly consumed staple cereal cultivated predominantly in Asian countries, which share 90% of global rice production. Rice is a primary calorie provider for more than 3.5 billion people across the world. Preference and consumption of polish

Externí odkaz: https://doaj.org/article/21428990b5ed40248bd2da8372eb193a

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Linkage mapping and quantitative trait loci detection for seedling vigor and grain size in advanced backcross introgression lines from wild accessions of Oryza nivara.

Autor: Magudeeswari, P., Balakrishnan, Divya, Fukuta, Yoshimichi, Saito, Hiroki, Saitheja, D., Pranay, G., Padmashree, R., Barbadikar, Kalyani M, Badri, Jyothi, Senguttuvel, P., Sruthi, K., Ladhalakshmi, D., Padmavathi, G., Subbarao, L. V., Sundaram, R. M., Sarla, N.

Publikováno v: Genetic Resources & Crop Evolution; Aug2024, Vol. 71 Issue 6, p3163-3179, 17p

Secure Multicast Key Distribution for Mobile Ad Hoc Networks

Autor: SuganyaDevi, D., Padmavathi, G.

Many emerging applications in mobile adhoc networks involve group-oriented communication. Multicast is an efficient way of supporting group oriented applications, mainly in mobile environment with limited bandwidth and limited power. For using such a

Externí odkaz: http://arxiv.org/abs/1003.1799

A Performance Study of GA and LSH in Multiprocessor Job Scheduling

Autor: Vijayalakshmi, S. R., Padmavathi, G.

Publikováno v: International Journal of Computer Science Issues, IJCSI, Vol. 7, Issue 1, No. 1, January 2010, http://ijcsi.org/articles/A-Performance-Study-of-GA-and-LSH-in-Multiprocessor-Job-Scheduling.php

Multiprocessor task scheduling is an important and computationally difficult problem. This paper proposes a comparison study of genetic algorithm and list scheduling algorithm. Both algorithms are naturally parallelizable but have heavy data dependen

Externí odkaz: http://arxiv.org/abs/1002.1149