Explore the vast range of titles available.

Manual identification of tomato leaf diseases is a time-consuming and laborious process that may lead to inaccurate results without professional assistance. Therefore, an automated, early, and precise leaf disease recognition system is essential for farmers to ensure the quality and quantity of tomato production by providing timely interventions to mitigate disease spread. In this study, we have proposed seven robust Bayesian optimized deep hybrid learning models leveraging the synergy between deep learning and machine learning for the automated classification of ten types of tomato leaves (nine diseased and one healthy). We customized the popular Convolutional Neural Network (CNN) algorithm for automatic feature extraction due to its ability to capture spatial hierarchies of features directly from raw data and classical machine learning techniques [Random Forest (RF), XGBoost, GaussianNB (GNB), Support Vector Machines (SVM), Multinomial Logistic Regression (MLR), K-Nearest Neighbor (KNN)], and stacking for classifications. Additionally, the study incorported a Boruta feature filtering layer to capture the statistically significant features. The standard, research-oriented PlantVillage dataset was used for the performance testing, which facilitates benchmarking against prior research and enables meaningful comparisons of classification performance across different approaches. We utilized a variety of statistical classification metrics to demonstrate the robustness of our models. Using the CNN-Stacking model, this study achieved the highest classification performance among the seven hybrid models. On an unseen dataset, this model achieved average precision, recall, f1-score, mcc, and accuracy values of 98.527%, 98.533%, 98.527%, 98.525%, and 98.268%, respectively. Our study requires only 0.174 s of testing time to correctly identify noisy, blurry, and transformed images. This indicates our approach's time efficiency and generalizability in images captured under challenging lighting conditions and with complex backgrounds. Based on the comparative analysis, our approach is superior and computationally inexpensive compared to the existing studies. This work will aid in developing a smartphone app to offer farmers a real-time disease diagnosis tool and management strategies.

Nocturnal asthma (NA) is a high-prevalence disease that causes severe respiratory issues, leading to death from early midnight to early morning. In this research, nanoparticulate drug delivery system of methylprednisolone (MP) was developed using chitosan (CH) and pectin (PEC). MP is a synthetic corticosteroid medication widely used for its potent anti-inflammatory activity. Computational simulation study (AI-based blend analysis algorithm) was used to identify a better-mixing polymer with MP. MP nanoparticles were formulated by the ionic gelation method with the combination of CH and PEC. To modify the drug release properties, the formed beads were coated with chitosan succinate (CSSC). The morphological characteristics of the beads were determined by SEM analysis. The X-ray radiographic imaging study was used to observe the intactness of MP beads. Histopathological studies were also carried out to find out the toxicity of the beads in the organs of rats. Pectin and chitosan polymers were selected based on the computational simulation study. SEM analysis revealed that the beads had a spherical shape with a rough outer surface. CSSC-coated beads achieved sustained drug release for up to 24 h. X-ray imaging demonstrated the stability of the beads in acidic pH conditions. In vivo pharmacokinetic studies showed that CSSC-coated beads were more stable in the gastrointestinal tract (GIT) than PEC-CH beads and the pure drug. Histological evaluation confirmed that the beads are nontoxic and safe for use in rats. Based on the findings, it was concluded that CSSC-coated beads of MP exhibited superior release properties, making them suitable for a chronomodulated drug delivery system.

Alzheimer’s disease (AD) is a degenerative neurological condition that severely affects the elderly and is clinically recognised by a decrease in cognition and memory. The treatment of this disease has drawn considerable attention and sparked increased interest among the researchers in this field as a result of a number of factors, including an increase in the population of patients over time, a significant decline in patient quality of life, and the high cost of treatment and care. The current work was carried out for the synthesis of benzimidazole-oxazole hybrid derivatives as efficient Alzheimer’s inhibitors and as a springboard for investigating novel anti-chemical Alzheimer’s prototypes. The inhibition profiles of each synthesised analogue against acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) enzymes were assessed. All the synthesized benzimidazole-based oxazole analogues displayed a diverse spectrum of inhibitory potentials against targeted AChE and BuChE enzymes when compared to the reference drug donepezil (IC50 = 2.16 ± 0.12 M and 4.50 ± 0.11 µM, respectively). The most active AChE and BuChE analogues were discovered to be analogues 9 and 14, with IC50 values of 0.10 ± 0.050 and 0.20 ± 0.050 µM (against AChE) and 0.20 ± 0.050 and 0.30 ± 0.050 µM (against BuChE), respectively. The nature, number, position, and electron-donating and -withdrawing effects on the phenyl ring were taken into consideration when analysing the structure-activity relationship (SAR). Molecular docking studies were also carried out on the active analogues to find out how amino acids bind to the active sites of the AChE and BuChE enzymes that were being studied.

Culinary herbs and spices are widely used in daily diets. Pakistan’s flora is enriched with phytochemicals due to a diverse range of land. Phytochemicals, including volatile and non-volatile compounds, have captured much interest due to their numerous health advantages and significance in daily diet. The present study aimed to conduct in-depth metabolomic profiling of Pakistani-grown fenugreek leaves (Trigonella foenum-graecum), fennel seeds (Foeniculum vulgare), mint leaves (Mentha royleana), coriander seeds (Coriandrum sativum) and basil leaves (Ocimum basilicum) by using liquid chromatography–mass spectrometry (LC-MS/MS) and gas chromatography–mass spectrometry (GC-MS). The first study was conducted to optimize extraction using different solvents (methanol, ethanol, chloroform, acetone, and water). Total phenolic content (TPC), total flavonoid content (TFC), and total condensed tannins (TCT) were quantified along with the antioxidant and anti-diabetic activities. The highest TPC (125.42 ± 10.89 mg GAE/g) and the highest antioxidant and anti-diabetic potential were quantified in mint. Seventy-one phytochemical metabolites were identified using LC-MS/MS, while forty-nine volatile constituents were identified using GC-MS. A positive correlation was identified between phenolic contents and their biological activities. Furthermore, molecular docking helped to find drug molecules with more excellent anti-diabetic activity based on their binding affinities. This study suggests that selected herbs and spices from Pakistan have significant nutraceutical and phytopharmaceutical potential. This study could further help in drug discovery.

Micronutrient application has a crucial role in mitigating salinity stress in crop plants. This study was carried out to investigate the effect of zinc (Zn) and boron (B) as foliar applications on fenugreek growth and physiology under salt stress (0 and 120 mM). After 35 days of salt treatments, three levels of zinc (0, 50, and 100 ppm) and two levels of boron (0 and 2 ppm) were applied as a foliar application. Salinity significantly reduced root length (72.7%) and shoot length (33.9%), plant height (36%), leaf area (37%), root fresh weight (48%) and shoot fresh weight (75%), root dry weight (80%) and shoot dry weight (67%), photosynthetic pigments (78%), number of branches (50%), and seeds per pod (56%). Fenugreek’s growth and physiology were improved by foliar spray of zinc and boron, which increased the length of the shoot (6%) and root length (2%), fresh root weight (18%), and dry root weight (8%), and chlorophyll a (1%), chlorophyll b (25%), total soluble protein content (3%), shoot calcium (9%) and potassium (5%) contents by significantly decreasing sodium ion (11%) content. Moreover, 100 ppm of Zn and 2 ppm of B enhanced the growth and physiology of fenugreek by reducing the effect of salt stress. Overall, boron and zinc foliar spray is suggested for improvement in fenugreek growth under salinity stress.

Arid soils are often weak, low in fertility, and lack essential plant nutrients. Organic amendments might be a feasible solution to counter the detrimental impact and rehabilitate weak arid soil for the growth of legumes. The study aimed to investigate how organic amendments of compost and humic acid may affect winter field pea productivity in arid soil. Over 2 years of field experiments, a range of treatments were applied, including different amounts of compost and humic acid. The results showed higher microbial carbon (C), and nitrogen (N) biomass, root length, shoot length, grains pod −1 , and grain yield of pea, gained from the collective application of 8 Mg ha −1 compost and 15 kg ha −1 humic acid compared to all other treatments. Organic amendments increased soil microbial C density by 67.0 to 83.0% and N biomass by 46.0 to 88.0% compared with the control. The combined application of compost and humic acid increased soil microbial N biomass by 57.0 to 60.0% compared to the sole applications of compost-only and humic acid-only. It was concluded that organic amendments of 8 Mg ha −1 compost and 15 kg ha −1 humic acid in arid soil modulated microbial density, resulting in improved winter field pea productivity. This study suggests organic amendments of compost and humic acid might be a practicable solution to rehabilitate weak arid soil to grow legumes.

Corn stalk fibers were extracted from corn stalk using sodium hydroxide for textile application. The extraction conditions were optimized on the basis of the quality and quantity of extracted fibers. The optimum conditions were obtained by treating corn stalk with 5 g/L concentration of sodium hydroxide for 60 min at boiling temperature using a 1:50 material-to-liquor ratio. Extracted fibers were bleached and tested for different physical and chemical properties. Besides these properties, the characterization of extracted fibers was carried out by a scanning electron microscope (SEM), X-ray diffraction analysis (XRD) and Fourier–transform infrared (FTIR) analysis. SEM was used to study the morphological changes in the raw and bleached fibers. The crystallinity changes of the raw and bleached samples were measured with an X-ray diffractometer by peak height method. FTIR was used to examine the compositional changes in the bleaching process. It was found that raw fibers contained the cellular residues such as lignin and hemicelluloses, which cement the fibers together. The chemical treatments such as alkali and bleaching partially removed hemicelluloses, lignin, and amorphous fractions of cellulose. This led to the gradually increasing crystallinity of the treated fiber. Peak height values were obtained by measuring the transmittance of the spectra through FTIR analysis. Different physical and chemical properties of the extracted corn stalk fibers indicated that it can be used for making biodegradable composite materials.

Deficiencies of essential vitamins, iron (Fe), and zinc (Zn) affect over one-half of the world’s population. A significant progress has been made to control micronutrient deficiencies through supplementation, but new approaches are needed, especially to reach the rural poor. Agronomic biofortification of pulses with Zn, Fe, and boron (B) offers a pragmatic solution to combat hidden hunger instead of food fortification and supplementation. Moreover, it also has positive effects on crop production as well. Therefore, we conducted three separate field experiments for two consecutive years to evaluate the impact of soil and foliar application of the aforementioned nutrients on the yield and seed biofortification of mungbean. Soil application of Zn at 0, 4.125, 8.25, Fe at 0, 2.5, 5.0 and B at 0, 0.55, 1.1 kg ha−1 was done in the first, second and third experiment, respectively. Foliar application in these experiments was done at 0.3% Zn, 0.2% Fe and 0.1% B respectively one week after flowering initiation. Data revealed that soil-applied Zn, Fe and B at 8.25, 5.0 and 1.1 kg ha−1, respectively, enhanced the grain yield of mungbean; however, this increase in yield was statistically similar to that recorded with Zn, Fe and B at 4.125, 2.5 and 0.55 kg ha−1, respectively. Foliar application of these nutrients at flower initiation significantly enhanced the Zn contents by 28% and 31%, Fe contents by 80% and 78%, while B contents by 98% and 116% over control during 2019 and 2020, respectively. It was concluded from the results that soil application of Zn, Fe, and B enhanced the yield performance of mungbean; while significant improvements in seed Zn, Fe, and B contents were recorded with foliar application of these nutrients.

Improving cropping systems together with suitable agronomic management practices can maintain dry farming productivity and reduce water competition with low N inputs. The objective of the study was to determine the photosynthetic and yield responses of maize and peanut under six treatments: sole maize, sole peanut, maize–peanut intercropping, maize–peanut rotation–intercropping, 20% and 40% N reductions for maize in the maize–peanut rotation–intercropping. Maize–peanut intercropping had no land-use advantage. Intercropped peanut is limited in carboxylation rates and electron transport rate (ETR), leading to a decrease in hundred-grain weight (HGW) and an increase in blighted pods number per plant (N BP ). Intercropped peanut adapts to light stress by decreasing light saturation point (I sat ) and light compensation point (I comp ) and increasing the electron transport efficiency. Intercropped maize showed an increase in maximum photosynthetic rate (Pn max ) and I comp due to a combination of improved intercellular CO 2 concentration, carboxylation rates, PSII photochemical quantum efficiency, and ETR. Compare to maize–peanut intercropping, maize–peanut rotation–intercropping alleviated the continuous crop barriers of intercropped border row peanut by improving carboxylation rates, electron transport efficiency and decreasing I sat , thereby increasing its HGW and N BP . More importantly, the land equivalent ratio of maize–peanut rotation–intercropping in the second and third planting years were 1.05 and 1.07, respectively, showing obvious land use advantages. A 20% N reduction for maize in maize–peanut rotation–intercropping does not affect photosynthetic character and yield for intercropped crops. However, a 40% N reduction decreased significantly the carboxylation rates, ETR, I comp and Pn max of intercropped maize, thereby reducing in a 14.83% HGW and 5.75% lower grain number per spike, and making land-use efficiency negative.

Cobalt (Co) bioaccumulation, contamination, and toxicity in the soil environment, plant growth, and cattles’ health are becoming a severe matter that can cause unembellished consequences in environmental safety and human health. The present research was conducted for the assurance of cobalt (Co) amassing in three forage plant species ( Zea mays, Sorghum bicolor, Trifolium alaxandrium ), from four ecological sites, and sewage water and in buffaloes blood was investigated. The analysis of variance showed significant differences for Co concentration in the soil and sewage water collected from all ecological sites. Meanwhile, summer and winter seasons and forage ecotypes significantly influenced the quantity of Co. The forage pastures also vary significantly in the concentration of Co in the above-ground parts. The highest Co level was present in Trifolium alaxandrium at ecological site-5. Cobalt taken from wastewater had a higher concentration in Trifolium alaxandrium during the winter. The samples which are collected from site-V and site-IV have the maximum concentration of Co because these areas receive highly contaminated water for irrigation. Cobalt tends to be bioaccumulated in the food chain and can cause serious problems in humans and animals. Bioaccumulation of cobalt in collected samples could be accredited to anthropogenic activities. Pollution load index values for all samples fell in the range below 1. The health risk index indicated the probability of health damage caused by the ingestion of contaminated fodder. An increase of Co concentration in soil, fodder, and blood owing to wastewater irrigation to crops was indicated as an outcome of this investigation. The results indicate that the Co toxicity in forage crops is attributed to Co bioaccumulation, transfer, and pollution load in the soil–water-cattle triangle. Efforts should be extended to avoid contamination of the food chain via Co-rich sewage water. Other nonconventional water resources should be used for forage irrigation.