Lotan Kumar Bose

Use of AMMI and other stability statistics in the simultaneous selection of rice genotypes for yield and stability under direct-seeded conditions

Rice (Oryza sativa L.) is one of the most important cereal crops in the world. India is one of the largest rice-producing countries. Although more than 900 rice varieties have been released in India, many of them are no longer cultivated within a few years of release due to inconsistent performance in diverse environments; only a few varieties with stable performance continue to be under cultivation after 15 to 20 yr of their release. Development and adaptability of rice cultivars in a wide range of target environments are the eventual goals of plant breeders. An attempt has been made to estimate the level of genotype-environment interaction (GEI) and eliminate as much as possible the unexplainable and extraneous variability contained in the data. Therefore, several statistical techniques have been used to describe GEI and measure genotype stability. Field experiments were conducted with 12 genotypes under direct-seeded conditions (irrigated and rainfed) for three consecutive years (2009 to 2012) in a randomized complete block design with three replicates. The GEI was analyzed using additive main effects and multiplicative interaction (AMMI). Results of AMMI analysis indicated that the first three AMMI (AMMI1 to AMMI3) were highly significant (P < 0.05). The partitioning of TSS (total sum of squares) exhibited that the genotype effect was a predominant source of variation followed by GEI and environment, which suggests the possible existence of different environment groups. The AMMI stability value discriminated genotypes 11 and 12 as stable genotypes based on the yield stability index (YSI) and sustainability index (SI).

Genetic variability and association of yield attributing traits with grain yield in upland rice

A study was undertaken to find out the genetic variability and correlation between yield and other yield attributing characters of rice genotypes in upland ecology. The experiment was conducted with twenty two upland genotypes grown during Wet season under direct seeded condition in a randomized block design. Analysis of variance shows significance in all the traits indicating the presence of considerable amount of genetic variation among the genotypes. The traits like plant height, ear bearing tiller and yield has high genotypic coefficient of variance, phenotypic coefficient of variance and genetic advance. Plant height, ear bearing tiller, panicle length, panicle weight and length were positively and significantly correlated with yield. Plant height and grain per panicle, 50% flowering, thousand grain weight and ear bearing tiller has high direct effect on yield. Therefore, selection based on plant height, 50% flowering, thousand grain weight and ear bearing tiller could be more effective in upland rice.

New algorithm for multiple pattern matching using least count of pattern.

Rapid advances in genome research in the past have resulted in generation of large set of data for DNA and protein sequences from different prokaryotic and eukaryotic genomes. DNA is made up of four nitrogenous bases known as adenine (A), guanine (G), thymine (T) and cytosine (C). Pattern matching technique generally divides into two categories i.e. single pattern matching and multiple pattern matching. When it is required to find all occurrences of the pattern in the given string, it is known as single pattern matching. When more than one pattern are matched against the given string simultaneously, it is known as multiple pattern matching. The study of pattern matching is one of the applications in the field of bioinformatics. Many algorithms are available in literature for pattern matching. The purpose of pattern matching algorithm is to reduce the number of character comparisons. Hence, in this paper an algorithm Multiple Pattern Matching using Least Count of Pattern (MPMLCP) has been proposed for multiple pattern matching. The proposed algorithm has been compared with the available algorithm and it has been shown that the number of comparisons reduces over the available algorithms. SAS 9.3 software package has been used for calculating the number of comparisons.

Genotype by environment interactions for grain yield in upland breeding lines of rice under direct seeded conditions across multi-environments

Eighteen rainfed upland breeding lines were evaluated under four environments in randomized complete block design with three replications. Data on grain yield were subjected to combined ANOVA and AMMI analysis. The AMMI model was applied, with additive effects for the 18 breeding lines of rice genotypes (G) and four seasons of testing (Environments = E), and multiplicative term for genotype × environment interaction. The AMMI statistical model has shown that more than 50% proportion of the total variation in grain yield was attributed due to genotype × environment interaction. Most of the breeding lines showed environment specificity. CR2897-11-1 and CR28818-1 were found to be favorable during 2011 (En. 4) and CR2908-12-5-1 and CR2899-7-1 were found to be favorable in the year 2010 (En. 3) with grain yield more than 3 t ha–1.

Rhizosphere nitrogenase and Azospirillum sp. association with wild, trisomic and cultivated rice

Abstract The nitrogenase activity of rice rhizosphere and root associated Azospirillum sp. was evaluated in wild, trisomic and cultivated rices grown unde uniform field conditions. Wide variations in rhizosphere nitrogenase were noticed among the wild species of rice. The nitrogenase activity associated with rhizosphere was initially low and reached the maximum during the heading and reproductive phases of the rice plant. Oryza latifolia exhibited low nitrogenase compared to the six other wild species. The trisomic rices exhibited higher associative rhizosphere nitrogenase activity in comparison to normal cultivated rices. Similarly, Azospirillum sp. isolated from the trisomics exhibited higher nitrogenase activity compared with the isolates from normal ric roots. Although O. latifolia showed low rhizosphere nitrogenase, the Azospirillum sp. isolated from this had highest nitrogenase activity. In general, cultivated and trisomic rices supported considerable nitrogenase activity in the rhizosphere and as well harboured efficient Azospirillum sp. compared to wild rices.