Water, a necessary component of cell protoplasm, plays an essential role in supporting life on Earth; nevertheless, extreme changes in climatic conditions limit water availability, causing numerous issues, such as the current water-scarce regimes in many regions of the biome. This review aims to collect data from various published studies in the literature to understand and critically analyze plants’ morphological, growth, yield, and physio-biochemical responses to drought stress and their potential to modulate and nullify the damaging effects of drought stress via activating natural physiological and biochemical mechanisms. In addition, the review described current breakthroughs in understanding how plant hormones influence drought stress responses and phytohormonal interaction through signaling under water stress regimes. The information for this review was systematically gathered from different global search engines and the scientific literature databases Science Direct, including Google Scholar, Web of Science, related studies, published books, and articles. Drought stress is a significant obstacle to meeting food demand for the world’s constantly growing population. Plants cope with stress regimes through changes to cellular osmotic potential, water potential, and activation of natural defense systems in the form of antioxidant enzymes and accumulation of osmolytes including proteins, proline, glycine betaine, phenolic compounds, and soluble sugars. Phytohormones modulate developmental processes and signaling networks, which aid in acclimating plants to biotic and abiotic challenges and, consequently, their survival. Significant progress has been made for jasmonates, salicylic acid, and ethylene in identifying important components and understanding their roles in plant responses to abiotic stress. Other plant hormones, such as abscisic acid, auxin, gibberellic acid, brassinosteroids, and peptide hormones, have been linked to plant defense signaling pathways in various ways.

/pdf/plants-physio-biochemical-and-phyto-hormonal-responses-to-1dxik3x7.pdf

Plants’ Physio-Biochemical and Phyto-Hormonal Responses to Alleviate the Adverse Effects of Drought Stress: A Comprehensive Review

The objective of this paper was to stress the possible potential toxic element (PTE) accumulation in the surface sediments of the Cavuslu Stream (CS), as well as examining the source identification of whether or not any association between garbage disposal facility (GDF) and ecotoxicity or human health risk in Giresun, Turkey. The sediment specimens were analyzed by inductively coupled plasma mass spectroscopy (ICP-MS) followed by microwave digestion. The descending order of metals (mg/kg) in sediments were as follows: Fe (38,791 ± 3269) > Al (27,753 ± 4051) > Mn (730.90 ± 114.60) > Cr (233.39 ± 53.32) > V (176.40 ± 19.66) > Cu (85.22 ± 6.06) > Ni (72.87 ± 11.50) > Zn (46.45 ± 3.68) > Co (21.96 ± 3.33) > Pb (12.17 ± 1.97) > As (3.12 ± 1.45) > Sb (0.22 ± 0.06) > Cd (0.17 ± 0.02) > Hg (0.04 ± 0.01). Among these elements, certain metals (V, Cr, Cu, and Ni) in the sediments were above the average shale. Cr and Ni levels were above their corresponding threshold effect level (TEL) and probable effect level (PEL) values while Cu concentration exceeding its TEL, indicating that benthic organisms in the sediment of CS have likely toxic responses. Based on the results from contamination factor (CF), enrichment factor (EF), and geo-accumulation factor (Igeo) values of PTEs, the sediment was frequently classified into moderate contamination, moderate enrichment, and unpolluted to moderately polluted group. Pollution load index (PLI), integrated pollution index (IPI), and ecological risk index (Eri) indicated low pollution or low potential ecological risk. Toxicity risk index (TRI) and toxic unit analysis (TUs) suggested moderate toxicity. The outcomes of hazard quotient (HQ), total hazard index (THI), and lifetime cancer risk (LCR) stressed out that PTEs would not pose a significant health risk when adults are exposed to sediments in CS. However, a non-cancerogenic health risk for children was considered as the collective effect of 14 PTE (THI = 1.47 > 1). Multivariate statistical analysis (principal component analysis (PCA), Pearson’s correlation coefficient (PCC), and hierarchical cluster analysis (HCA)) outlined that the metallic accumulation in the sediments of CS was related to lithological, geological, and anthropogenic impacts. Therefore, the GDF is likely a major reason in terms of anthropogenic pollution in the sediments of the CS.

Ecotoxicological risk assessment for sediments of Çavuşlu stream in Giresun, Turkey: association between garbage disposal facility and metallic accumulation

This research work was focused to evaluate the concentration of heavy metals (i.e., Cr, Pb, Mn, Cu and Fe) in sediment samples collected from the Dhaleshwari River near the area of a newly established tannery industrial estate, Savar, Bangladesh. The heavy metals in sediment samples were ascertained by the atomic absorption spectrophotometer (AAS). This study revealed that the metal concentration for chromium (Cr), lead (Pb), manganese (Mn), copper (Cu) and iron (Fe) were found to be 14.8–748 (186 ± 241) mg/kg, 2.38–21.1 (8.78 ± 6.15) mg/kg, 1.59–6.29 (3.12 ± 1.38) mg/kg, 0.36–4.75 (1.76 ± 1.47) mg/kg and 3.87–154 (42.7 ± 49.1) mg/kg (dry wt) respectively. The concentration of heavy metals in sediment samples descends with the following order: Cr > Fe > Pb > Mn > Cu. Sediment contamination was assessed on the basis of geo-accumulation index (Igeo), contamination factor (CF) and pollution load index (PLI). The average Igeo values for Cr, Pb, Mn, Cu and Fe were found to be (−0.44 ± 1.87), (−2.18 ± 1.20), (−8.80 ± 0.63), (−5.80 ± 1.36) and (1.59 ± 1.87) respectively. The Igeo values values of Cr and Fe for some sampling stations were found to be higher. The PLI value for all the sample stations (S1-S8) were 0.58, 0.66, 0.71, 0.69, 0.88, 0.86, 0.83 and 0.83 correspondingly. The CF values for Cr and Fe in some stations was observed at moderate, considerate and high contamination level. The spatial distribution of heavy metals in the study area was presented by interpolation technique. The results of spatial distribution pattern showed that the high concentrated zones of Cr was found at the dumping zone (~S5) of the leather industrial city. On the other hand, the spatial distribution pattern for the studied metals (Pb, Mn, Cu and Fe) showed that the maximum metals concentrations were found in the southeastern part, which was nearby effluent dumping zone. The ecological risk assessment in sediment samples revealed that there is no significant risk observed by the metal(oid)s at this moment. Considering Cr concentration, the modified hazard quotient (mHQ) showed that about 75% of the samples were low to severely polluted by Cr, while 25% of the samples were extremely polluted by Cr as well as mHQ ≤ 3.5. Based on PMF analysis, two potential sources of heavy metals were identified in the study region: first, biochemical and leather tanning industries (Cr); second, the mixed effect of geogenic sources and atmospheric deposition and traffic emission (Fe and Pb).

Assessment of heavy metal contamination in sediment at the newly established tannery industrial Estate in Bangladesh: A case study

Preliminary assessment of heavy metals in surface water and sediment in Nakuvadra-Rakiraki River, Fiji using indexical and chemometric approaches.

Ecological risks and controlling factors of trace elements in sediments of dam lakes in the Black Sea Region (Turkey)

Water resources pollution associated with risks of heavy metals from Vatukoula Goldmine region, Fiji.

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Satendra Kumar

Author Tools

Chat about Author

Papers

Preliminary assessment of heavy metals in surface water and sediment in Nakuvadra-Rakiraki River, Fiji using indexical and chemometric approaches.

Water resources pollution associated with risks of heavy metals from Vatukoula Goldmine region, Fiji.