The present study investigates the effect of the TiO2 nanofluid on the formation of hydrocarbon, carbon-monoxide, nitrogen oxide and smoke emission from a neat mustard oil methyl ester fueled diesel engine. TiO2 nano particle with an average size of 50 nm was synthesized by sol-gel route. The synthesized particles are dispersed with mustard oil methyl ester at various concentrations (100 and 200 ppm) by the means of a mechanical homogenizer and an ultrasonicator. Experiments were conducted in a four-stroke, single-cylinder, diesel-engine, fuelled with diesel, neat mustard oil methyl ester and nanofluid incorporated methyl ester. From the obtained results, it can be recognized that methyl ester from mustard oil is potential candidate as an alternative fuel in existing diesel engine. Further, it is also observed that TiO2 nanofluid associated to mustard oil methyl ester reduced various emissions over neat mustard oil methyl ester.

Frying affects the nutritional quality of fish detrimentally. In this study, using Catla catla and mustard oil, experiments were carried out in varying temperatures (140–240 °C), times (5–20 min), and oil amounts (25–100 ml/kg of fish) which established drastic reduction of 44.97% and 99.40% for polyunsaturated fatty acid (PUFA)/saturated fatty acids (SFA) and index of atherogenicity (IA) profile, respectively. Artificial neural network (ANN) was implemented successfully to provide an association between the independent inputs with dependent outputs (values of R² were 0.99 and 0.98; RMSE were 0.038 and 0.046; and performance were 0.038 and 0.067 for PUFA/SFA and IA, respectively) by exhaustive search of various algorithms and activation functions available in literature. ANN model–based meta-heuristic, stochastic optimization formalisms, genetic algorithm (GA) and particle swarm optimization (PSO), were applied to optimize the combination of cooking parameters for improving the nutritional quality of food which improved the nutritional value by maximizing the PUFA/SFA profile up to 63.05% and minimizing the IA profile to 99.64%. Multi-objective genetic algorithm (MOGA) was also employed to tune the inputs by maintaining a balance between the contrasting outputs and enhance the overall food value simultaneously with multi-objective (beneficial for health, economic, and environment-friendly) proposal. MOGA was able to improve the PUFA/SFA profile up to 44.76% and reduce the IA profile to 92.94% concurrently with the reduction of wastage of culinary media and energy consumption, following the optimized cooking condition (118.92 °C, 6.06 min, 40 ml oil/kg of fish).

The aim of the present study was to investigate biosurfactant production ability of five different polyaromatic hydrocarbon (PAH)-metabolizing bacteria, such as Ochrobactrum anthropi IITR07, Pseudomonas mendocina IITR46, Microbacterium esteraromaticum IITR47, Pseudomonas aeruginosa IITR48, and Stenotrophomonas maltophilia IITR87. These bacteria showed biosurfactant production using 2% glucose as rich substrate; strain IITR47 yielded the highest with 906 and 534 mg/L biosurfactant in the presence of naphthalene and crude oil as the unique carbon sources. P. aeruginosa IITR48 showed the least surface tension at 29 N/m and the highest emulsification index at 63%. The biosurfactants produced were identified as glycolipid and rhamnolipid based on Fourier transform infrared spectroscopy analysis. In particular, the biosurfactant produced by bacteria S. maltophilia IITR87 efficiently emulsified mustard oil with an E24 value of 56%. It was observed that, all five biosurfactants from these degrader strains removed 2.4-, 1.7-, 0.9-, 3.8-, and 8.3-fold, respectively, crude oil from contaminated cotton cloth. Rhamnolipid derived from IITR87 was most efficient, exhibiting highest desorption of crude oil. These biosurfactants exhibited good stability without significantly losing its emulsification ability under extreme conditions, thus can be employed for bioremediation of PAHs from diverse contaminated ecosystem. Graphical Abstract

Ruminant livestock production processes are the major sources of methane production in agriculture sector triggering global environmental pollution. Above 90% of world buffalo population present in Asian countries, India ranks first and contributes significantly to the environmental pollution by enteric methane emissions. In this study, we examined the effect of dietary composite feed additive supplementation on ruminal methane production, nutrient utilization, milk production and immune status of buffaloes (Bubalus bubalis). Eighteen lactating Murrah (Bubalus bubalis) buffaloes at early stage of lactation were divided into two groups of nine animals and fed a composite feed additive [consisted of (%, w/w) dried and ground leaves of Cordia dichotoma and Holoptelea integrifolia, 31.4 each; garlic oil, 0.6; sodium nitrate, 3.1; magnesium sulphate, 8.4; mustard oil, 12.6 and cottonseed oil, 12.5] which contained an ideal combinations of methane inhibitors, alternate hydrogen sinks and rumen stimulating agents to treatment (CFA) group animals along with basal feed of chaffed green sorghum (Sorghum bicolor) fodder, chaffed wheat straw and concentrate mixture for maintenance and milk production. The results showed a decrease (44.6%) in methane concentration in exhaled air of CFA group buffaloes with increase (p < 0.05) in digestibility of feed in comparison to control (CON). Total digestible nutrient (TDN) content of the ration fed to buffaloes of CFA group was significantly (p < 0.05) increased. The daily milk yield, 6% fat corrected milk (FCM) yield and immune response were also increased (p < 0.05) in CFA group. The study suggests that the supplementation of composite feed additive was effective to reduce enteric methane emissions and improvement in production performance and immune status of buffaloes.