Recently, there has been considerable attention towards the production of environmentally friendly nanoparticles (NPs). In this investigation, the successful synthesis of cerium oxide nanoparticles (CeO2 NPs) was achieved by employing an eco-friendly technique that utilized an extract from the leaves of local plant quinoa (Chenopodium quinoa L.). The synthesized CeO2 NPs were subjected to characterization using state-of-the-art methods. The prepared CeO2 NPs contained a round shape with clusters and have a size of 7-10 nm. To assess how effective CeO2 NPs derived from C. quinoa were against Ustilago tritici, a fungal disease that negatively affects wheat crop globally, a study was performed on two varieties of wheat crop comprised of Arooj (V1) and Akber (V2), cultivated under field conditions. CeO2 NPs were applied foliarly twice to the wheat crop at four different concentrations: T0 (0 mg/L), T1 (50 mg/L), T2 (75 mg/L), and T3 (100 mg/L). The results revealed that the control group (T0) exhibited the highest disease severity index (DSI) with a value of 75% compared to the other concentrations of CeO2 NPs on both varieties. At a concentration of 100 mg/L of CeO2 NPs, the DSI dropped to a minimum of 35% and 37% on both V1 and V2 respectively. These findings indicated that an increase in the concentration of CeO2 NPs has a beneficial impact on disease severity. Similar patterns have also been observed with disease incidence (DI), with the greatest efficacy observed at a concentration of 100 mg/L of CeO2 NPs. Our investigation has shown that CeO2 NPs exhibitd significant antifungal potential against U. tritici which may be a promising strategy to mitigate fungal disease and crop losses globally.
Climate change is causing soil salinization, resulting in huge crop losses throughout the world. Multiple physiological and biochemical pathways determine the ability of plants to tolerate salt stress. Chili (Capsicum annum L.) is a salt-susceptible crop; therefore, its growth and yield is negatively impacted by salinity. Irreversible damage at cell level and photo inhibition due to high production of reactive oxygen species (ROS) and less CO2 availability caused by water stress is directly linked with salinity. A pot experiment was conducted to determine the impact of five NaCl salinity levels, i.e., 0,1.5, 3.0, 5.0 and 7.0 dS m-1 on growth, biochemical attributes and yield of two chili genotypes ('Plahi' and 'A-120'). Salinity stress significantly reduced fresh and dry weight, relative water contents, water use efficiency, leaf osmotic potential, glycine betaine (GB) contents, photosynthetic rate (A), transpiration rate (E), stomatal conductance (Ci), and chlorophyll contents of tested genotypes. Salinity stress significantly enhanced malondialdehyde (MDA) contents and activities of the enzymatic antioxidants such as superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD). In addition, increasing salinity levels significantly reduced the tissue phosphorus and potassium concentrations, while enhanced the tissue sodium and chloride concentrations. Genotype 'Plahi' had better growth and biochemical attributes compared to 'A-120'. Therefore, 'Plahi' is recommended for saline areas to improve chili production.
With the onset of the COVID-19 pandemic, the number of critically sick patients in intensive care units (ICUs) has increased worldwide, putting a burden on ICUs. Early prediction of ICU requirement is crucial for efficient resource management and distribution. Early-prediction scoring systems for critically ill patients using mathematical models are available, but are not generalized for COVID-19 and Non-COVID patients. This study aims to develop a generalized and reliable prognostic model for ICU admission for both COVID-19 and non-COVID-19 patients using best feature combination from the patient data at admission. A retrospective cohort study was conducted on a dataset collected from the pulmonology department of Moscow City State Hospital between 20 April 2020 and 5 June 2020. The dataset contains ten clinical features for 231 patients, of whom 100 patients were transferred to ICU and 131 were stable (non-ICU) patients. There were 156 COVID positive patients and 75 non-COVID patients. Different feature selection techniques were investigated, and a stacking machine learning model was proposed and compared with eight different classification algorithms to detect risk of need for ICU admission for both COVID-19 and non-COVID patients combined and COVID patients alone. C-reactive protein (CRP), chest computed tomography (CT), lung tissue affected (%), age, admission to hospital, and fibrinogen parameters at hospital admission were found to be important features for ICU-requirement risk prediction. The best performance was produced by the stacking approach, with weighted precision, sensitivity, F1-score, specificity, and overall accuracy of 84.45%, 84.48%, 83.64%, 84.47%, and 84.48%, respectively, for both types of patients, and 85.34%, 85.35%, 85.11%, 85.34%, and 85.35%, respectively, for COVID-19 patients only. The proposed work can help doctors to improve management through early prediction of the risk of need for ICU admission of patients during the COVID-19 pandemic, as the model can be used for both types of patients.
Wheat is an important global staple food crop; however, its productivity is severely hampered by changing climate. Erratic rain patterns cause terminal drought stress, which affect reproductive development and crop yield. This study investigates the potential and zinc (Zn) and silicon (Si) to ameliorate terminal drought stress in wheat and associated mechanisms. Two different drought stress levels, i.e., control [80% water holding capacity (WHC) was maintained] and terminal drought stress (40% WHC maintained from BBCH growth stage 49 to 83) combined with five foliar-applied Zn-Si combinations (i.e., control, water spray, 4 mM Zn, 40 mM Si, 4 mM Zn + 40 mM Si applied 7 days after the initiation of drought stress). Results revealed that application of Zn and Si improved chlorophyll and relative water contents under well-watered conditions and terminal drought stress. Foliar application of Si and Zn had significant effect on antioxidant defense mechanism, proline and soluble protein, which showed that application of Si and Zn ameliorated the effects of terminal drought stress mainly by regulating antioxidant defense mechanism, and production of proline and soluble proteins. Combined application of Zn and Si resulted in the highest improvement in growth and antioxidant defense. The application of Zn and Si improved yield and related traits, both under well-watered conditions and terminal drought stress. The highest yield and related traits were recorded for combined application of Zn and Si. For grain and biological yield differences among sole and combined Zn-Si application were statistically non-significant (p>0.05). In conclusion, combined application of Zn-Si ameliorated the adverse effects of terminal drought stress by improving yield through regulating antioxidant mechanism and production of proline and soluble proteins. Results provide valuable insights for further cross talk between Zn-Si regulatory pathways to enhance grain biofortification.
Nitrogen (N) fertilizer is an important yield limiting factor for sunflower production. The correlation between yield components and growth parameters of three sunflower hybrids (Hysun-33, Hysun-38, Pioneer-64A93) were studied with five N rates (0, 60, 120, 180, 240 kg ha(-1)) at three different experimental sites during the two consecutive growing seasons 2008 and 2009. The results revealed that total dry matter (TDM) production and grain yield were positively and linearly associated with leaf area index (LAI), leaf area duration (LAD), and crop growth rate (CGR) at all three sites of the experiments. The significant association of yield with growth components indicated that the humid climate was most suitable for sunflower production. Furthermore, the association of these components can be successfully used to predict the grain yield under diverse climatic conditions. The application of N at increased rate of 180 kg ha(-1) resulted in maximum yield as compared to standard rate (120 kg ha(-1)) at all the experimental sites. In this way, N application rate was significantly correlated with growth and development of sunflower under a variety of climatic conditions. Keeping in view such relationship, the N dose can be optimized for sunflower crop in a particular region to maximize the productivity. Multilocation trails help to predict the input rates precisely while taking climatic variations into account also. In the long run, results of this study provides basis for sustainable sunflower production under changing climate.