Mung bean is recognized for its abundant high-quality protein content. For human consumption, it is a high-quality protein source and also serves various purposes crops, its arvested residue is used for green manuring and also used for fodder purposes. The research aimed to assess the impact of foliar micronutrient application on primed mung bean (Vigna radiata). The experimental procedures were executed in the sandy loam soil prevalent in the central plain region of Punjab. The investigation was conducted during the Zaid season 2022, focusing on the (SML-1827) mung bean variety. Specifically, the research assessed the impact of foliar micronutrient applications involving zinc and boron at 15 and 45 days after sowing (DAS) on primed mung bean growth characteristics. The experimental design employed a Randomized Block Design, incorporating 11 distinct treatment combinations, each replicated thrice. The investigation revealed that foliar micronutrient treatment on primed mung bean substantially influenced growth and yield parameters. Growth indicators for mung bean exhibited a positive trend when zinc and boron were jointly applied to primed seeds with gibberellic acid, followed by a decline in the control group, which experienced typical growth conditions devoid of growth regulators and micronutrients. Specifically, the highest recorded plant height was 70.1 cm in the T9 (GA(50 mg.L-1) + ZnSO4 (0.5%) + B (1%)) treatment, while the lowest height was 58 cm in the T0 (control) treatment. Similarly, the most significant fresh weight was observed in T9 (GA(50 mg.L-1) + ZnSO4 (0.5%)+ B (1%)) treatments at 136.8 g, with the lowest weight recorded in T0 (control) treatments at 86.6g. the most significant grain yield was achieved in T9 112 g.m-2, followed by T10 (SA(150 mg.L-1)+ ZnSO4 (0.5%)+B (1%)) at 105.7 g.m-2. This study suggests micronutrients and growth regulators can be sustainable agricultural inputs to enhance soil health and productivity.

Marginal land has low nutrient content (nitrogen, phosphorus, potassium). Addressing nutrient deficiencies on marginal land requires a strategic approach. Biological fertilizers like Arbuscular Mycorrhizal Fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) enhance nutrient availability through symbiotic interactions. In addition, organic fertilizers such as compost could provide organic matter and improve soil structure to increase plant growth and productivity. Combining these three fertilizers with the addition of low doses of NPK fertilizer can increase the growth and productivity of maize crops on sub-marginal land. This study aims to determine the effect of AMF, consortium of PGPR, and a low dose of NPK on the growth and productivity of maize and soil nutrients on sub-marginal land by measuring plant growth up to 8 WAP (week after planting) (parameters: plant height, stem diameter, number of leaves, leaf area, chlorophyll content, stomatal density) and productivity (parameters: cob length, cob weight with husk, fresh weight, dry weight) and levels of N, P, and K elements at 8 WAP in the soil after planting. All treatments showed an increase in the level of N and K elements, while the P element showed a decrease compared to the control (soil without treatment). Moreover, each parameter did not show a significant difference, but the P2 (Compost + PGPR consortium + AMF + 50% of NPK) treatment showed the best growth and productivity. Overall, the data showed the utilization of PGPR and AMF combination was able to reduce the usage of chemical fertilizer by 50%.

The dye effluents released from the textile and printing industries contain strong colorants, inorganic salts, and other toxic compounds. The conventional coagulation technique of dye effluent treatment is plagued with issues of low removal rate of color, generation of large quantities of sludge, and toxic end-products. Recently electrocoagulation technique gained immense attention due to its high efficiency. This technique involves the dissolution of the sacrificial anodes to provide an active metal hydroxide as a strong coagulant that destabilizes the pollutants and removes them by precipitation or flocculation. This study is about the efficiency of the electrocoagulation process using titanium coated - aluminum and mild steel electrodes to treat industrial dye wastewater. Effects of parameters such as current density & initial dye concentration were investigated. It was observed that, for the same current density, electrode consumption was higher with TiO2/Al electrode than with mild steel electrode, resulting in more color removal efficiency (CRE) using TiO2/Al electrode. The settling rate of the flocs was higher in the rector having TiO2/Al electrode at the 100 mL with current density (2.5 mL.min-1 to 5.3 mL.min-1), while in the reactor with mild steel electrode, the settling rate was very less. The results showed that dye removal was 95.11% and 92.1% for mild steel and titanium-coated electrodes, respectively. It was observed that 50 % of Aluminum was removed from the treated effluent after the final stage of filtration. Based on the multicriteria analysis to identify the optimum operational parameters to be applied at the field level, it was observed that maximum CRE may be obtained with TiO2/Al electrode and the applied current of 1 Amps with a flow rate of 100 mL.min-1. It can be concluded that electrocoagulation is a highly efficient and the fastest method to treat dye effluents from industries.

Nature reserves have played a crucial role in biodiversity conservation for decades. Rapid urban sprawl has increased the amount of solid waste created by littering and illegal dumping in metropolitan nature reserves. This paper examines how two nature reserves, Wolfgat Nature Reserve and Witzands Aquifer Nature Reserves, can combine community conservation with waste management. To determine aspects such as the socioeconomic impact of the nature reserves on the surrounding communities, questionnaires with a specific focus on the topic were distributed to the surrounding communities and subsequently administered. Data was collected using semi-structured interviews with key informants from the nature reserve staff and observational methods, and SPSS was used to analyze the data. Consistent with previous research, this study revealed that ignoring local populations frequently results in people disobeying the appropriate regulations in these protected areas and that education does not guarantee conservation support. Despite this, the survey revealed an absence of community participation; conservators were more reactive than proactive. In this study, the level of education, which in some studies is always associated with knowledge, was contradicted; those with post-secondary education knew little about these areas, and the vast majority of participants were unaware of the protected areas just a few kilometers away from their communities.

Biochar can be a good soil amendment to reduce the soil pH, increase crop growth rate, and improve the efficient use of fertilizer. Other than that, silicon fertilizer also would promote photosynthetic ability on plant development that would help to produce high yield. In this work, a series of experiments was conducted to observe the effect of rice husk biochar and silicon fertilizer on the maize growth rate and soil pH. A 45-day pot experiment in the greenhouse with three replicates of 9 experimental treatment combinations of RHB at two rates (5 and 2.5 t.ha-1) with silicon fertilizer at three rates (125%, 100%, 75%), sole biochar (10 t.ha-1), sole silicon fertilizer (100%) and control (NPK) to observe the best rate and combination to improve growth rate and change in soil chemical in acid soil. The result showed that the co-application of sole biochar and biochar with Silicon significantly improved growth development, increased photosynthesis rate, altered soil pH, and reduced Fe concentration compared to control. The plant height increased 88.35% from T4 (5 t.ha-1 RHB + 100% Si) compared to the control and the conductance was higher in T4 (0.53) followed by T8 (0.438) while T1 (0.071) recorded the lowest conductance. The shoot fresh weight was higher in T4 (127.83 g) followed by T8 (57.14 g). However, the weight increased by 343.7% at T4 followed by T8 (2.5 t.ha-1 RHB + 75% Si) at 98.33%. The highest pH increment of 1.24 units (T1 = 5.53, T4 = 6.77) of soil pH was noted from T4 (5 t.ha-1 RHB + 100% Si) compared to control (NPK), and the highest total Fe in soil was observed from T1 (442.30 mg.kg-1). The current study results showed that T4 (50% RHB + 100% Silicon) was the best treatment over the other rates of RHB and silicon increased plant height, photosynthetic rate, and biomass.

Amid the COVID-19 outbreak, the accumulation of household waste continued to rise as the number of COVID-19 patients increased. COVID-19 can survive and be transmitted from contaminated surfaces, making waste pickers more vulnerable and at risk of contracting and spreading the virus through contact with infected household waste. The study assessed safety practices and risks related to waste picking during the COVID-19 pandemic at two selected dumping sites in the north of Pretoria. Structured questionnaires were used to collect data from 81 waste pickers at these landfill sites. Results showed that 100.0% of waste pickers at Site A and 86.7% at Site B collected plastics; 96.7% at Site A and 90.5% at Site B collected bottles; and 100% at Site B and 95.5% at Site A collected metals. The majority, 92.0% at Site A and 90.0% at Site B, were aware of the dangers and risks associated with waste handling if protective gear was not worn. From sites A and B, 97.0% and 90% of the waste pickers respectively had heard of COVID-19, although 51.9% from both sites believed they could not contract COVID-19 while handling waste. Only 18.0% of waste pickers from Site A and 82.0% from Site B faced challenges with purchasing their own PPE. All waste pickers at Site A wore facial masks, whereas 86.0% at Site B did so. Regarding testing for COVID-19, 22.0% from Site A and 19.0% from Site B were tested, with 2.0% from Site A and none (0.0%) from Site B testing positive. It is recommended that all waste pickers be educated about COVID-19 transmission and provided with PPE during the pandemic.

Phytoremediation is one of the non-energy consuming processes of remediating polluted water. However, the disposal of post-remediated plants poses a threat of the re-introduction of pollutants back into the ecosystem. Re-routing remediated pollutants for commercial application could be one way to reduce the re-introduction of pollutants in an ecosystem. Heavy metal pollution in water bodies is one issue, which can be mitigated to an extent with phytoremediation. In the current study, the effect of heavy metal phytoremediation on the phytochemical fingerprint and bioactivity of Pistia stratiotes L. was investigated. Pistia stratiotes L. was subjected to different concentrations of iron (Fe) and lead (Pb), in the range of 5-20 ppm. Different parameters such as heavy metal estimation (in plants and water post-treatment), thin layer chromatography (TLC), antioxidant activity, and antiurolithic activity were measured. Post remediation, heavy metal concentration was found to be comparatively higher in roots (16.515 ± 0.008 mg.g-1 and 5.25 ± 0.086 mg.g-1 when treated with 15 ppm iron and lead respectively). TLC revealed differences between the fingerprints of treated and untreated plants. Some bands increased in intensity as the concentration of heavy metal increased, while some bands which were present in untreated, were absent in treated plant samples. Antioxidant activity of treated plants shows lesser IC50 values, compared to untreated, in that, treated leaves show better activity (IC50 = 1.8 ± 0.5220 mg.mL-1 of leaf treated with 2 ppm iron as opposed to IC50 > 5 mg.mL-1 of untreated leaf extract). The treated plants revealed good antiurolithic activity compared to untreated, in that, the percentage inhibition showed by Iron treated leaves and roots was better (96.87% and 98.95% exhibited by iron-10 ppm treated leaves and roots respectively), while the untreated showed a maximum of only 68.75% inhibition. The results suggest that the bioactivity of the plant extracts increases post-remediation. Potential applications of these extracts can be explored such as nanoparticle synthesis, drug discovery, etc.

This study presents a comprehensive investigation into the production of amylase, a crucial enzyme with wide-ranging industrial applications, using locally sourced substrates from Kachchh, Gujarat. The research employed the Bacillus licheniformis strain and substrates such as coconut, rice husk, wheat bran, paddy straw, and maize straw. The study found paddy straw to be the most promising substrate for amylase production. The research also systematically optimized various process parameters for amylase production in Solid-State Fermentation (SSF) using the One Variable at a Time (OVAT) method. These parameters included incubation period, temperature, inoculum level, additional carbon sources, starch concentrations, additional nitrogen sources, initial pH, different mineral salt ions, initial moisture level, and surfactants. The results showed that the optimal conditions for maximum amylase yield were an incubation period of 48 hours, an incubation temperature of 35°C, an inoculum level of 10%, starch as the additional carbon source, a starch concentration of 2.5%, yeast extract as the additional nitrogen source, an initial pH of 7, NaCl as the mineral salt, an initial moisture level of 75%, and Tween 80 as the surfactant. This research provides a reliable and sustainable approach to enzyme production, offering valuable insights for the optimization of the solid-state fermentation process for maximum amylase production.

This study aimed to compare the ability of five plant species, including (Conocarpus erectus, Acacia sensu lato (s.l.), Melaleuca viminalis, Dodonaea viscosa and Lantana camara) to absorb and accumulate heavy elements in their tissues, which were grown in the central islands in the city of Diwaniyah. This included areas of street in front of the medical college, Umm Al Khail First Street, Umm Al-Khail Street, near Abbas Attiwi Bridge, Al-Adly Street in the Euphrates District, and Clock Field Street, respectively. Results showed that soil samples S1 and S3 were contaminated by Pb, and the rest of the sites were contaminated with nickel only. This indicates through the table findings a rise in these heavy metals’ concentrations with a rise in traffic momentum. Thus, the Pb concentrations in the growing plants’ shoot parts with respect to this research had surpassed the allowed critical limit of 5.00 mg.kg-1 dry matter, in which the highest value was recorded at the site with respect to S3 as well as S2. Meanwhile, the findings indicate that Cd concentrations in S3 and S1 had increased and exceeded the allowable limit of 0.20 mg.kg-1 dry matter. In the meantime, the nickel concentrations were within the permissible limits of 67.90 mg.kg-1 dry matter. The Zn concentration exceeded the permitted limits of 60.00 mg.kg-1 dry matter except for plants (Acacia s.l. and Lantana camara) in sites S5 and S2. The results confirmed that the values of Heavy Metals Bioaccumulation Coefficient (BAC) for most of the study elements had recorded the highest value in the Dodonaea plant for Zn, Cd, and Pb, except for Ni. It was more accumulated in the Melaleuca viminalis plant, which indicates the superiority of the Dodonaea plant in accumulating Pb, Cd, and Zn over the rest of the study plants, as they took the following order: Lantana camara < Acacia s.l. < Conocarpus erectus < Melaleuca viminalis < Dodonaea viscosa. The best plants accumulated nickel in the following order: Acacia s.l. < Lantana camara < Conocarpus erectus < Dodonaea viscosa < Melaleuca viminalis.

Outdoor air pollution causes a lot of health problems for humans. Particulate Matter 2.5 (PM2.5), due to its small size, can enter the human respiratory system with ease and cause significant health effects on humans. This makes PM2.5 significant among the various air pollutants. Hence, it is important to measure the value of PM2.5 accurately for better management of air quality. Algorithms for deep learning and machine learning can be used to forecast air quality data. A model that minimizes the prediction error of the PM2.5 forecast is needed. In this paper, a PM2.5 concentration estimation model using Bi-LSTM (Bidirectional Long Short-Term Memory) with meteorological data as predictor variables is proposed. For a better estimation of PM2.5 values, the hyperparameters of the Bi-LSTM model used are tuned using the Osprey Optimization Algorithm (OOA), a recent meta-heuristic algorithm. The model that works with the optimal values of hyperparameters identified by OOA performed better than the other models when they are compared based on evaluation metrics like Mean-Squared Error and R2.