Enhanced metabolite yield with compensatory biomass reduction revealed by moisture stress induction in Centella asiatica (L.)

The exposure to any kind of stress tends to accelerate the secondary metabolism in medicinal plants increasing the production of secondary metabolites. The present investigation was undertaken to study the effect of moisture stress (100, 75, 50, 25 and 10% pot capacity) and control (as without plant) on growth, yield and metabolite content of Centella asiatica var. ‘Arka Prabhavi’, for two growing seasons under polyhouse conditions. Results revealed that moisture stress treatments had a significant effect on all observed growth and yield traits. Plants maintained at 100% PC exhibited luxurious vegetative growth with maximum leaf length (6.28 cm), leaf breadth (8.14 cm), petiole length (22.32 cm) and fresh biomass yield (164 g/pot). Cumulative water transpired and water use efficiency of the plants was also observed to be maximum at 100% PC. In contrary to biomass yield, increased asiaticoside (1.864%, 1.892%), madecassoside (2.856%, 3.382%) and total triterpenoid content (5.356%, 5.578%) at higher moisture stress levels of 75% and 50% PC, respectively, was observed. Hence, it is appropriate to grow Centella either at 100% or 75% PC to get optimum biomass and metabolite yield on a commercial scale

Modelling the molecular mechanisms of ageing

This document is the Accepted Manuscript version of a published work that appeared in final form in Bioscience reports. To access the final edited and published work see http://www.bioscirep.org/content/37/1/BSR20160177.The ageing process is driven at the cellular level by random molecular damage which slowly accumulates with age. Although cells possess mechanisms to repair or remove damage, they are not 100% efficient and their efficiency declines with age. There are many molecular mechanisms involved and exogenous factors such as stress also contribute to the ageing process. The complexity of the ageing process has stimulated the use of computational modelling in order to increase our understanding of the system, test hypotheses and make testable predictions. As many different mechanisms are involved, a wide range of models have been developed. This paper gives an overview of the types of models that have been developed, the range of tools used, modelling standards, and discusses many specific examples of models which have been grouped according to the main mechanisms that they address. We conclude by discussing the opportunities and challenges for future modelling in this field

Breeding Resistance for Post Flowering Stalk rot (Macrophomina phaseolina) in Maize Identification of Resistance against Post Flowering Stalk Rot (Macrophomina phaseolina) in Maize

Maize is one of the most important staple food crops in the World. However, the yields of maize have been affected by various fungal infestations. Post flowering stalk rot is one of the devastating diseases and so, we planned our study to order to identify suitable resistance maize genotypes against post flowering stalk rot (PFSR) complex caused by Macrophomina phaseolina through in-vivo screening and toothpick method for creating artificial epiphytotics. A total of 20 maize inbreds were screened and crossed in Line × Tester mating design (15 × 5) during Kharif 2019, Six resistant inbred lines were identified and generated the 75 F1s (SCHs) at MRC, ARI, Rajendranagar, Hyderabad. All these 20 parents and 75 F1s along with three checks were evaluated by raising the crop in disease sick plot accompanied by toothpick inoculation during Rabi, 2019-20, in a Randomized Block Design with two replications. The field screening of maize genotypes by the standard toothpick method which needs about 40 days for expression of plant drying symptoms due to PFSR and data are possible to record only at the time of crop harvesting using 1-9 rating scale of PFSR for scoring disease severity in-vivo condition by splitting the stem of each plant. As a result, most of the genotypes were exhibited disease reaction varying from resistant (score 2) to moderately resistant (score 5) against M. phaseolina. While studying the genetics of PFSR, we found that interaction of lines and testers were proportionally contributed towards resistant, and degree of dominance is preferably non-additive gene action, it shows that the magnitude of dominance was higher than additive effect indicating that PFSR resistance is largely governed by dominance effect i.e., non additive component is not fixable for resistance. It is also found that the resistant genotypes also exhibited highest significant positive heterosis and combining ability effects (GCA and SCA). A considerable yield reduction in grain yield (10.5 to 28.3%) over checks was observed in susceptible lines. Most of the genotypes were found resistant as the reduction in yield is low. Hybrids developed using such lines exhibited high yields which are promoted for extensive testing to know their stability before release as commercial hybrids.</jats:p

Prediction of Stock with On-Go Billing Cart using IoT and Advanced Interdisciplinary Approaches

Modern technology has significantly improved the quality of life for humans. However, with the increase in technology usage, there has been a rise in the number of people visiting shopping malls. As a result, the billing process has become more time-consuming, and customers often have to wait in long queues to get their goods billed. To address this issue, we propose the development of a smart shopping cart system that uses RFID and Arduino to keep track of purchased products and generate bills automatically. The main objective of this paper is to reduce the time consumed in the billing process. Our On-go billing Cart with an Automatic Billing System will use an EM-18 RFID Module and Arduino