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Plants evolve diverse mechanisms to eliminate the drastic effect of biotic and abiotic stresses. Drought is the most hazardous abiotic stress causing huge losses to crop yield worldwide. Osmotic stress decreases relative water and chlorophyll content and increases the accumulation of osmolytes, epicuticular wax content, antioxidant enzymatic activities, reactive oxygen species, secondary metabolites, membrane lipid peroxidation, and abscisic acid. Plant growth-promoting rhizobacteria (PGPR) eliminate the effect of drought stress by altering root morphology, regulating the stress-responsive genes, producing phytohormones, osmolytes, siderophores, volatile organic compounds, and exopolysaccharides, and improving the 1-aminocyclopropane-1-carboxylate deaminase activities. The use of PGPR is an alternative approach to traditional breeding and biotechnology for enhancing crop productivity. Hence, that can promote drought tolerance in important agricultural crops and could be used to minimize crop losses under limited water conditions. This review deals with recent progress on the use of PGPR to eliminate the harmful effects of drought stress in traditional agriculture crops.

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The deployment of methanol like alternative fuels in engines is a necessity of the present time to comprehend power requirements and environmental pollution. Furthermore, a comprehensive prediction of the impact of the methanol-gasoline blend on engine characteristics is also required in the era of artificial intelligence. The current study analyzes and compares the experimental and Artificial Neural Network (ANN) aided performance and emissions of four-stroke, single-cylinder SI engine using methanol-gasoline blends of 0%, 3%, 6%, 9%, 12%, 15%, and 18%. The experiments were performed at engine speeds of 1300–3700 rpm with constant loads of 20 and 40 psi for seven different fractions of fuels. Further, an ANN model has developed setting fuel blends, speed and load as inputs, and exhaust emissions and performance parameters as the target. The dataset was randomly divided into three groups of training (70%), validation (15%), and testing (15%) using MATLAB. The feedforward algorithm was used with tangent sigmoid transfer active function (tansig) and gradient descent with an adaptive learning method. It was observed that the continuous addition of methanol up to 12% (M12) increased the performance of the engine. However, a reduction in emissions was observed except for NOx emissions. The regression correlation coefficient (R) and the mean relative error (MRE) were in the range of 0.99100–0.99832 and 1.2%–2.4% respectively, while the values of root mean square error were extremely small. The findings depicted that M12 performed better than other fractions. ANN approach was found suitable for accurately predicting the performance and exhaust emissions of small-scaled SI engines.

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High-performance drilling fluid was designed for unconventional reservoirs to minimize the formation damage and borehole instability using organophilic clay treated with trimethyloctylammonium bromide, novel in-house synthesized gemini surfactant, and a high-molecular weight polymer. This gemini surfactant has not been reported in the literature for drilling fluid applications. The performance of designed drilling fluid was evaluated and compared with the base drilling fluid (4 w/v.% bentonite dispersion water). Shale dispersion, linear swelling, filtration, and rheological experiments were performed to investigate the effect of drilling fluids on borehole stability and formation damage. The combined use of organophilic clay and surfactant in the drilling fluid formulation reduced the shale dispersion up to 89%. The linear swelling experiment of shale sample shows 10% swelling of the core in the modified drilling fluid while in base fluid 13% swelling of shale was observed. It was found that modified drilling fluid interactions with shale were greatly reduced using a surfactant and associative polymer in the drilling fluid formulation. Rheological properties of drilling fluids were stable, and filtration characteristics showed that the filtrate volume was within the acceptable limit. The designed drilling fluid made a thin and impermeable filter cake that prevents the invasion of drilling fluid into the formation. This study opens a new direction to reduce the formation damage and borehole instability using organophilic clay, surfactant and high-molecular weight additive in water-based drilling fluid.