Mitigation of Moisture Stress through Foliar Spray of Thiourea, Salicylic Acid and Homobrassinolide in Chickpea Cicer arietinum L.

A field experiment was conducted at the Zonal Agricultural Research Station, Kalaburgi, University of Agricultural Sciences, Raichur to study the influence of foliar spray of thiourea, salicylic acid and homobrassinolide on crop growth and seed yield of chickpea (Cicer arietinum L.) under moisture stress conditions in rabi 2018-19. The experiment consisted of sixteen treatment combinations (four moisture stress with four foliar sprays) which was laid out in 2 factor RBD. Among the different treatments imposed, two foliar spray of thiourea @ 1000 ppm under no moisture stress (control) during flowering (45 DAS) and seed setting 75 DAS recorded significantly higher plant height (42.0 and 49.0 cm), leaf area index (3.020 and 2.003), number of primary branches plant-1 (9.1 and 10.7), chlorophyll content (SPAD values 64.4 and 56.6), number of pods plant-1 (64.3), 100 seed weight (25.0 g), drought tolerant efficiency 100.0 %, seed yield plant-1 (18.9 g) and hectare-1 (27.2 q) compared to other treatments.</jats:p

One-step synthesis of highly-biocompatible spherical gold nanoparticles using Artocarpus heterophyllus Lam. (jackfruit) fruit extract and its effect on pathogens

Introduction Novel approaches for the synthesis of gold nanoparticles (AuNPs) are of great importance due to its vast spectrum of applications in diverse fields, including medical diagnostics and therapeutics. Te presented study reports the successful AuNPs’ synthesis using Artocarpus heterophyllus Lam. extract, and provides detailed characterization and evaluation of its antibacterial potential. [b]Objective[/b]. The aim was to develop a cost-effective and environmentally friendly synthesis method of gold nanoparticles using aqueous fruit extract of Artocarpus heterophyllus Lam. as a reducing and capping agent, which has proven activity against human pathogens, such as microbial species [i]E.coli[/i] and Streptobacillu sps. Material and Methods Characterizations were carried out using ultraviolet-visible (UV-Vis) spectrophotometry, scanning electron microscopy (SEM), energy dispersive X-ray and Fourier-Transform infra-red spectroscopy (FT-IR). Results SEM images showed the formation of gold nanoparticles with an average size of 20–25 nm. Spectra collected while infra-red analysis contained broad peaks in ranges from 4000–400 cm -1 . Conclusions It can be concluded that the fruit of Artocarpus heterophyllus Lam. can be good source for synthesis of gold nanoparticles which showed antimicrobial activity against investigated microbes, in particul E. coli, and Streptobacillus. An important outcome of this study will be the development of value-added products from the medicinal plant Artocarpus heterophyllus Lam. for the biomedical and nanotechnology-based industries

Plant mediated synthesis of gold nanoparticles using fruit extracts of ananas comosus (L.) (pineapple) and evaluation of biological activities

Plant mediated synthesis of metallic nanoparticles is an increasing commercial demand due to the wide applicability in various areas such as electronics, catalysis, chemistry, energy, cosmetics and medicine. In the present investigation, synthesis of gold nanoparticles is done by using fruit extracts of Ananas comosus (L.). Nanoparticles were characterized by using UV visible absorption spectra. Their morphology, elemental composition and crystalline phase were determined by scanning electron microscopy, energy dispersive X-ray spectroscopy and selected area electron diffraction. FT-IR analysis was used to confirm the presence of gold nanoparticles in the extracts. The synthesized gold nanoparticles were generally found to be effective as antimicrobial agents against some important human pathogens like E.coli and Streptobacillus sp. which are affecting and cause diseases like food poisoning and rat-bite fever to human beings respectively

Development of the Keystroke Dynamics Recognition System

The paper is related to creating an algorithm for keystroke dynamics recognition and development of software, which is able to identify users according to their keystroke dynamics. Different characteristics of keystroke dynamics are considered. Probabilistic-statistical methods are compared with neural network algorithms for recognition. The algorithm for recognition was created and implemented. The software was tested with the help of some users. Their keystroke dynamics was analyzed in order to determine an efficiency of the created algorithm