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The need to focus on traditional crops for food security has been realized across the globe. ‘Bhat’ is an indigenous soybean variety from the Indian Himalayan Region that has been neglected in recent times due to changing agricultural choices. The present study was conducted on 52 indigenous soybean accessions collected from different villages of Uttarakhand, a hilly state in Northern India, to determine the concentrations of various macro- and microelements in the crop. The analysis used the HHXRF (handheld X-ray fluorescence) spectroscopic technique and atomic absorption spectroscopy (AAS). The findings reveal that the ‘bhat’ is an extremely nutrient-rich crop with calcium being the most significant macronutrient (highest concentration of 27,300 ppm), followed by phosphorus, potassium, and sulphur found in the bhat seeds. The study suggests that samples from Pauri Garhwal (Gwad Khirsu, Bironkhal, Sripur), Tehri (PratapNagar, Singoli), Chamoli (Paini, and Agastyamuni) villages were rich in all the major macronutrients. Among the micronutrients, silicon was found to be the most dominant with the highest concentration of 1920 ppm. This was followed by the dominance of iron, zinc, and manganese in descending order of abundance. Tipri, Chandola Rai Goonth, Chopdiun, and Paini villages were found to have the highest concentrations of microelements. The statistical data analysis confirms that seed samples from different regions are significantly similar in terms of nutrient concentrations, except for Si and Fe, thereby indicating that ‘bhat’ from any of the villages is equally good for consumption. However, seed samples from certain regions were found to be contaminated with heavy metals, indicating soil pollution, which demands attention towards current agricultural practices. The findings show that the crop is an exceptional source of essential and quasi-essential elements and should be promoted to benefit the hill populations.

Since the COVID-19 outbreak, the severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) virus has evolved into variants with varied infectivity. Vaccines developed against COVID-19 infection have boosted immunity, but there is still uncertainty on how long the immunity from natural infection or vaccination will last. The present study attempts to outline the present level of information about the contagiousness and spread of SARS-CoV-2 variants of interest and variants of concern (VOCs). The keywords like COVID-19 vaccine types, VOCs, universal vaccines, bivalent, and other relevant terms were searched in NCBI, Science Direct, and WHO databases to review the published literature. The review provides an integrative discussion on the current state of knowledge on the type of vaccines developed against SARS-CoV-2, the safety and efficacy of COVID-19 vaccines concerning the VOCs, and prospects of novel universal, chimeric, and bivalent mRNA vaccines efficacy to fend off existing variants and other emerging coronaviruses. Genomic variation can be quite significant, as seen by the notable differences in impact, transmission rate, morbidity, and death during several human coronavirus outbreaks. Therefore, understanding the amount and characteristics of coronavirus genetic diversity in historical and contemporary strains can help researchers get an edge over upcoming variants.

Abstract Organic effluent enrichment in water may selectively promote algal growth, resulting in water pollution and posing a threat to the aquatic ecosystem. Recent harmful algal blooms (HABs) incidents have highlighted information gaps that still exist, as well as the heightened need for early detection technology developments. Although previous research has demonstrated the importance of deep learning in the identification of algal genera, it is still a challenge to identify or to develop the best-suited convolution neural network (CNN) model for effective monitoring of bloom-forming algae. In the present study, efficiency of deep learning models (MobileNet V-2, Visual Geometry Group-16 (VGG-16), AlexNet, and ResNeXt-50) have been evaluated for the classification of 15 bloom-forming algae. To obtain a high level of accuracy, different convolution layers with adaptive moment estimation (Adam), root-mean-square propagation (RMSprop) as optimizers with softmax and rectified linear unit (ReLU) as activation factors have been used. The classification accuracies of 40, 96, 98, and 99% have been achieved for MobileNet V-2, VGG-16, AlexNet, and ResNeXt-50 model, respectively. We believe that the ResNeXt-50 has the potential to identify algae in a variety of situations with high accuracy and in real time, regardless of the underlying hardware. Such studies pave the path for future AI-based cleaner technologies associated with phycological studies for a sustainable future.

Abstract In today's fast-paced society, environmental breakdown is an ecumenical concern. This dilemma is tangled up with the unaccountable anthropogenic activities that are causing significant public health issues. Because of the rapid pace of development, urban soil and water pollution is progressively acting as a sink for a variety of contaminants, including heavy metals, pesticides, petroleum waste, radioactive moieties, etc. Phytoremediation is a low-cost, high-efficient method of extracting or removing pollutants from the environment. Water is transpired by green plants in order to move nutrients from the soil to the site of photosynthesis. During this process, pollutants in the water are also taken up and sequestered, digested, or drained out. This technique has many benefits over conventional approaches which is aesthetically pleasing and has long-term applicability. Phytoremediation could be a viable option to decontaminate heavy metal-polluted sites, particularly when the biomass produced during the process could be economically utilized in the form of bioenergy. Depending on the method used and nature of the contaminant involved, phytoremediating areas where metals and other inorganic compounds exist may utilize one of several techniques as discussed in the present study which are phytodegradation, phytoextraction, phytostimulation, phytostabilization, phytofiltration, phytovolatalization, etc. Phytoremediation is an emerging technology that employs the natural, biological, chemical, or physical processes of plants to remove, detoxify, or immobilize environmental contaminants in a growth matrix. This approach is hence an innovative tool with a great potential to decontaminate soil and water. Phytoremediation is a promising technique for ensuring the sustainability of future generations and reducing pollution.

The production and disposal of plastics have become significant concerns for the sustainability of the planet. During the past 75 years, around 80% of plastic waste has either ended up in landfills or been released into the environment. Plastic debris released into the environment breaks down into smaller particles through fragmentation, weathering, and other disintegration processes, generating microplastics (plastic particles ≤ 5 mm in size). Although marine and aquatic ecosystems have been the primary focus of microplastic pollution research, a growing body of evidence suggests that terrestrial ecosystems are equally at risk. Microplastic contamination has been reported in various terrestrial environments from several sources such as plastics mulch, pharmaceuticals and cosmetics, tire abrasions (tire wear particles), textiles industries (microfibers), sewage sludge, and plastic dumping. Recent studies suggest that the soil has become a significant sink for pollutants released into terrestrial ecosystems and is often contaminated with a mixture of organic and inorganic pollutants. This has gradually caused adverse impacts on soil health and fertility by affecting soil pH, porosity, water-holding capacity, and soil microbial enzymatic activities. Microplastics can interact with the co-existing pollutants of the environments by adsorbing the contaminants onto their surfaces through various intermolecular forces, including electrostatic, hydrophobic, non-covalent, partition effects, van der Waals forces, and microporous filling mechanisms. This subsequently delays the degradation process of existing contaminants, thereby affecting the soil and various ecological activities of the ecosystem. Thus, the present article aims to elucidate the deleterious impact of microplastics and their interactions with other pollutants in the terrestrial ecosystem. This review also addresses the impact of microplastics in disrupting the soil sustainability of the planet.