Endophytic fungi are plant beneficial rhizospheric microorganisms often applied as bioinoculants for enhanced and disease-free crop production. The objectives of the present work were to develop a carrier-based formulation of root endophyte Piriformospora indica as a bioinoculant. Powder formulation of four different carrier materials viz., talcum powder, clay, sawdust and bioboost (organic supplement) were evaluated and a talc-based formulation was optimized for a longer shelf life with respect to microbial concentration, storage temperature and biological activity. Finally the effect of optimized talc formulation on plant productivity was determined. The application dosages were optimized by studies on plant growth parameters of Phaseolus vulgaris L. plants under green house conditions. Five percent formulation (w/w) of talcum powder was observed to be the most stable at 30 °C with 10(8) CFU g(-1) and effective for a storage period of 6 months. The application of this optimized formulation resulted in increase of growth parameters of P. vulgaris L. and better adaptation of plants under green house conditions.

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Miospore assemblages are, for the first time, recorded from the Talchir Boulder Bed and overlying Needle Shales in the South Rewa Basin: The Boulder Bed assemblage contains 13 genera and 20 species, while the Needle shales have 17 genera and 24 species. Both assemblages, having several common taxa, are predominated by monosaccate pollen as is generally characteristic of other known Talchir miofloras. In the details of composition, however, the Boulder Bed assemblage of South Rewa appears to be distinct from that recorded from similar sediments of the Jayanti Coalfield. The present findings lend further support to the existence of the Glossopteris Flora during course of the Gondwana glaciation.

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A manufacturing system is governed by its various processes upon which its efficiency is dependent. Since failure results in considerable losses, many manufacturing systems have certain redundancies for some processes. These redundancies cause the system to work under different efficiency states called multi-state elements. In this paper, various processes of metal sheet manufacturing unit have been categorized as subsystems to determine the multi-state probabilities of its different efficiency states. Artificial Neural Network Technique (ANN) has been used to estimate the change in these multi-state probabilities over time. The ANN has also been used to estimate variation in upstate and downstate probabilities of the system for a particular-time period. The results have been used to determine variation in profit over time for the system.