Sequential asymmetric third order rotatable designs (SATORDs).

Rotatable designs that are available for process/ product optimization trials are mostly symmetric in nature. In many practical situations, response surface designs (RSDs) with mixed factor (unequal) levels are more suitable as these designs explore more regions in the design space but it is hard to get rotatable designs with a given level of asymmetry. When experimenting with unequal factor levels via asymmetric second order rotatable design (ASORDs), the lack of fit of the model may become significant which ultimately leads to the estimation of parameters based on a higher (or third) order model. Experimenting with a new third order rotatable design (TORD) in such a situation would be expensive as the responses observed from the first stage runs would be kept underutilized. In this paper, we propose a method of constructing asymmetric TORD by sequentially augmenting some additional points to the ASORDs without discarding the runs in the first stage. The proposed designs will be more economical to obtain the optimum response as the design in the first stage can be used to fit the second order model and with some additional runs, third order model can be fitted without discarding the initial design.

Identification of Differentially Expressed Genes in RNA-seq Data of Arabidopsis thaliana: A Compound Distribution Approach.

Gene expression is the process by which information from a gene is used in the synthesis of a functional gene product, which may be proteins. A gene is declared differentially expressed if an observed difference or change in read counts or expression levels between two experimental conditions is statistically significant. To identify differentially expressed genes between two conditions, it is important to find statistical distributional property of the data to approximate the nature of differential genes. In the present study, the focus is mainly to investigate the differential gene expression analysis for sequence data based on compound distribution model. This approach was applied in RNA-seq count data of Arabidopsis thaliana and it has been found that compound Poisson distribution is more appropriate to capture the variability as compared with Poisson distribution. Thus, fitting of appropriate distribution to gene expression data provides statistically sound cutoff values for identifying differentially expressed genes.

Bioefficacy of novel cyanobacteria-amended formulations in suppressing damping off disease in tomato seedlings.

Biological control of plant pathogens is receiving increasing relevance, as compared to chemical methods, as they are eco-friendly, economical and indirectly improve plant quality and yield attributes. An investigation was undertaken to evaluate the potential of antagonistic cyanobacteria (Anabaena variabilis RPAN59 and A. oscillarioides RPAN69) fortified formulations for suppressing damping off disease in tomato seedlings challenged by the inoculation of a fungal consortium (Pythium debaryanum, Fusarium oxysporum lycopersici, Fusarium moniliforme and Rhizoctonia solani). Treatment with A. variabilis amended formulations recorded significantly higher plant growth parameters, than other treatments, including biological control (Trichoderma formulation) and chemical control (Thiram-Carbendazim). The A. variabilis amended compost-vermiculite and compost formulations exhibited 10-15 % lower disease severity and 40-50 % higher values than chemical and biological control treatments in terms of fresh weight and height of the plants. In future, in depth analyses regarding the mechanism involved in biocontrol by cyanobacteria and evaluation of these formulations under field conditions are proposed to be undertaken.

Optimal Circular Block Designs for Neighbouring Competition Effects.

Competition or interference occurs when the responses to treatments in experimental units are affected by the treatments in neighbouring units. This may contribute to variability in experimental results and lead to substantial losses in efficiency. The study of a competing situation needs designs in which the competing units appear in a predetermined pattern. This paper deals with optimality aspects of circular block designs for studying the competition among treatments applied to neighbouring experimental units. The model considered is a four-way classified model consisting of direct effect of the treatment applied to a particular plot, the effect of those treatments applied to the immediate left and right neighbouring units and the block effect. Conditions have been obtained for the block design to be universally optimal for estimating direct and neighbour effects. Some classes of balanced and strongly balanced complete block designs have been identified to be universally optimal for the estimation of direct, left and right neighbour effects and a list of universally optimal designs for v<20 and r<100 has been prepared.