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Abstract Uneven rainfall and high temperature cause drought in tropical and subtropical regions which is a major challenge to cultivating summer mung bean. Potassium (K), a major essential nutrient of plants can alleviate water stress (WS) tolerance in plants. A field trial was executed under a rainout shelter with additional K fertilization including recommended K fertilizer (RKF) for relieving the harmful impact of drought in response to water use efficiency (WUE), growth, yield attributes, nutrient content, and yield of mung bean at the Regional Agricultural Research Station, BARI, Ishwardi, Pabna in two successive summer season of 2018 and 2019. Drought-tolerant genotype BMX-08010-2 (G1) and drought-susceptible cultivar BARI Mung-1 (G2) were grown by applying seven K fertilizer levels (KL) using a split-plot design with three replications, where mung bean genotypes were allotted in the main plots, and KL were assigned randomly in the sub-plots. A considerable variation was observed in the measured variables. Depending on the different applied KL and seed yield of mung bean, the water use efficiency (WUE) varied from 4.73 to 8.14 kg ha−1 mm−1. The treatment applying 125% more K with RKF (KL7) under WS gave the maximum WUE (8.14 kg ha−1 mm−1) obtaining a seed yield of 1093.60 kg ha−1. The treatment receiving only RKF under WS (KL2) provided the minimum WUE (4.73 kg ha−1 mm−1) attaining a seed yield of 825.17 kg ha−1. Results showed that various characteristics including nutrients (N, P, K, and S) content in stover and seed, total dry matter (TDM) in different growth stages, leaf area index (LAI), crop growth rate (CGR), root volume (RV), root density (RD), plant height, pod plant−1, pod length, seeds pod−1, seed weight, and seed yield in all pickings increased with increasing K levels, particularly noted with KL7. The highest grain yield (32.52%) was also obtained from KL7 compared to lower K with RKF. Overall, yield varied from 1410.37 kg ha−1 using 281 mm water (KL1; well-watered condition with RKF) to 825.17 kg ha−1 using 175 mm water (KL2). The results exhibited that the application of additional K improves the performance of all traits under WS conditions. Therefore, mung beans cultivating under WS requires additional K to diminish the negative effect of drought, and adequate use of K contributes to accomplishing sustainable productivity.

Abstract Background and Aim Gastric cancer is a health concern and contributes to cancer‐related deaths. Gastric intestinal metaplasia (GIM) is a premalignant lesion of gastric cancer. Currently, factors associated with GIM regression are under‐investigated. This study aims to assess the rate of GIM regression and identify factors associated with it. Methods This study was conducted at Medstar Washington Hospital Center. We included patients who had GIM between January 2015 and December 2020. Population was divided into GIM persistence or regression. Data included demographics, esophagogastroduodenoscopy findings, Helicobacter pylori status, and laboratory results. Statistical analyses included Kaplan–Meier and Cox proportional models to explore predictors of GIM regression. Results Among 2375 patients, 9.1% had GIM. Notably, 85 patients had GIM regression and 132 patients had persistent GIM. African Americans constituted (75%) of the regression group and (76%) of the persistence group. Peptic ulcer disease (PUD) was noted in 12.9% of the regression group at baseline, and 5.9% at follow‐up; the persistence group showed 11.4% at baseline and 5.3% at follow‐up (P = 0.89). Regression analysis revealed that the presence of PUD was associated with a higher rate of regression (hazard ratio [HR] 2.46, P = 0.013). Smoking status showed lower rates of regression (HR 0.54 and 0.62, P = 0.038 and 0.169). On gastric mapping, African Americans, Hispanics, and individuals of other races/ethnicities displayed lower rates of GIM regression (HR 0.68, 0.78 and 0.69). Conclusion PUD was associated with a higher rate of GIM regression, while smoking showed lower regression rates. Results provide insights into factors influencing GIM regression in African American population and may inform future surveillance and treatment strategies.

Cadmium (Cd) contamination in agricultural soils and its accumulation in plant organs have become a global issue due to its harmful effects on human health. The in-situ stabilizing technique, which involves using organic amendments, is commonly employed for removing Cd from agricultural soils. Thus, the current study investigated the effect of vermicompost (VC) on soil properties and plant physio-biochemical attributes, leaf ultrastructure analysis, antioxidant defense mechanisms, and grain yields of two different fragrant rice cultivars, Xiangyaxiangzhan (XGZ) and Meixiangzhan-2 (MXZ-2), under Cd-stress conditions. The results showed that Cd toxicity deteriorates soil quality, the plant’s photosynthetic apparatus, and the plant’s antioxidant defense mechanism. Moreover, under Cd stress, both cultivars produced significantly lower (p

In this research, we used the Revised Universal Soil Loss Equation (RUSLE) and Geographical Information System (GIS) to predict the annual rate of soil loss in the District Chakwal of Pakistan. The parameters of the RUSLE model were estimated using remote sensing data, and the erosion probability zones were determined using GIS. The estimated length slope ($LS$), crop management ($C$), rainfall erosivity ($R$), soil erodibility ($K$), and support practice ($P$) range from 0–68,227, 0–66.61%, 0–0.58, 495.99–648.68 $\; MJ/mm.t.ha^{-1}.year^{-1}\comma \;$ 0.15–0.25 $MJ/mm.t.ha^{-1}.year^{-1}$, and 1 respectively. The results indicate that the estimated total annual potential soil loss of approximately 4,67,064.25 $t.ha^{-1}.year^{-1}$ is comparable with the measured sediment loss of 11,631 $t.ha^{-1}.year^{-1}\;$ during the water year 2020. The predicted soil erosion rate due to an increase in agricultural area is approximately 164,249.31 $t.ha^{-1}.year^{-1}$. In this study, we also used Landsat imagery to rapidly achieve actual land use classification. Meanwhile, 38.13% of the region was threatened by very high soil erosion, where the quantity of soil erosion ranged from 365487.35 $t.ha^{-1}.year^{-1}$. Integrating GIS and remote sensing with the RUSLE model helped researchers achieve their final objectives. Land-use planners and decision-makers use the result's spatial distribution of soil erosion in District Chakwal for conservation and management planning.

Precision agriculture which facilitates and enables crop management through site-specific recommendations, is essential to optimize agricultural inputs in space and time. In this study, we used Landsat and MODIS-NDVI product data with climatic, topographic data and laboratory-analyzed soil samples to map the spatial distribution of seven soil properties; soil texture (T), electrical conductivity (EC), potential hydrogen (pH), nitrogen (N), phosphorus (P), potassium (K), and organic matter (OM) in the Punjab, Pakistan from 2000 to 2020. We examined and compared three statistical prediction models: the support vector machine (SVM), the random forest regression (RFR), and the multiple linear regression (MLR). The predictions were validated against a separate set of soil samples while considering the modeling region and an extrapolation area. Model performance statistics showed that the RFR often provided the highest accuracy, with the machine learning algorithms performing slightly better than the MLR. It was discovered that one obstacle to accurately forecasting soil parameters at unsampled areas with MLR was its inability to handle non-linear connections between independent and dependent variables. The results indicate that the cultivated area decreased from 43.16 % in 2000 to 38.24% in 2020. The soil has a high level of EC due to salinity. In general, the soils contained

Abstract Satellite remote sensing is widely being used by the researchers and geospatial scientists due to its free data access for land observation and agricultural activities monitoring. The world is suffering from food shortages due to the dramatic increase in population and climate change. Various crop genotypes can survive in harsh climatic conditions and give more production with less disease infection. Remote sensing can play an essential role in crop genotype identification using computer vision. In many studies, different objects, crops, and land cover classification is done successfully, while crop genotypes classification is still a gray area. Despite the importance of genotype identification for production planning, a significant method has yet to be developed to detect the genotypes varieties of crop yield using multispectral radiometer data. In this study, three genotypes of wheat crop (Aas-‘2011’, ‘Miraj-‘08’, and ‘Punjnad-1) fields are prepared for the investigation of multispectral radio meter band properties. Temporal data (every 15 days from the height of 10 feet covering 5 feet in the circle in one scan) is collected using an efficient multispectral Radio Meter (MSR5 five bands). Two hundred yield samples of each wheat genotype are acquired and manually labeled accordingly for the training of supervised machine learning models. To find the strength of features (five bands), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Nonlinear Discernment Analysis (NDA) are performed besides the machine learning models of the Extra Tree Classifier (ETC), Random Forest (RF), Support Vector Machine (SVM), Decision Tree (DT), Logistic Regression (LR), k Nearest Neighbor (KNN) and Artificial Neural Network (ANN) with detailed of configuration settings. ANN and random forest algorithm have achieved approximately maximum accuracy of 97% and 96% on the test dataset. It is recommended that digital policymakers from the agriculture department can use ANN and RF to identify the different genotypes at farmer's fields and research centers. These findings can be used for precision identification and management of the crop specific genotypes for optimized resource use efficiency.

Abstract Cereal/legume intercropping is becoming a popular production strategy for higher crop yields and net profits with reduced inputs and environmental impact. However, the effects of different spatial arrangements on the growth, grain yield, nitrogen uptake, and land-use advantage of wheat/soybean relay intercropping are still unclear, particularly under arid irrigated conditions. Therefore, in a three-year field study from 2018 to 2021, soybean was relay intercropped with wheat in different crop configurations (0.9 m, narrow strips; 1.8 m, medium strips; and 2.7 m, wide strips), and the results of intercropping systems were compared with their sole systems. Results revealed that intercrops with wide strips outperformed the narrow and medium strips, when the objective was to obtain higher total leaf area, dry matter, nitrogen uptake, and grain yield on a given land area due to reduced interspecific competition between intercrops. Specifically, at maturity, wide strips increased the dry matter accumulation (37% and 58%) and its distribution in roots (37% and 55%), straw (40% and 61%), and grains (30% and 46%) of wheat and soybean, respectively, compared to narrow strips. This enhanced dry matter in wide strips improved the soybean’s competitive ability (by 17%) but reduced the wheat’s competitive ability (by 12%) compared with narrow strips. Noticeably, all intercropping systems accumulated a significantly higher amount of nitrogen than sole systems, revealing that wheat/soybean relay intercropping requires fewer anthropogenic inputs (nitrogen) and exerts less pressure on the ecosystem than sole systems. Overall, in wide strips, intercropped wheat and soybean achieved 62% and 71% of sole wheat and soybean yield, respectively, which increased the greater total system yield (by 19%), total land equivalent ratio (by 24%), and net profit (by 34%) of wide strips compared to narrow strips. Our study, therefore, implies that the growth parameters, grain yields, nutrient accumulation, and land-use advantage of intercrop species could be improved with the proper spatial arrangement in cereal/legume intercropping systems.

Abstract Background and Aims Contrast‐enhanced cross‐sectional imaging is the cornerstone in the diagnosis, staging, and management of HCC, including eligibility for liver transplantation (LT). Radiological‐histopathological discordance may lead to improper staging and may impact patient outcomes. We aimed to assess the radiological‐histopathological discordance at the time of LT in HCC patients and its impact on the post‐LT outcomes. Methods We analyzed further the effect of 6‐month waiting policy on the discordance. Using United Network for Organ Sharing—Organ Procurement and Transplantation Network (UNOS‐OPTN) database, we examined the discordance between pre‐LT imaging and explant histopathology for all adult HCC patients who received liver transplants from deceased donors between April 2012 and December 2017. Kaplan–Meier methods and Cox regression analyses were used to evaluate the impact of discordance on 3‐year HCC recurrence and mortality. Results Of 6842 patients included in the study, 66.7% were within Milan criteria on both imaging and explant histopathology, and 33.3% were within the Milan based on imaging but extended beyond Milan on explant histopathology. Male gender, increasing numbers of tumors, bilobar distribution, larger tumor size, and increasing AFP are associated with increased discordance. Post‐LT HCC recurrence and death were significantly higher in patients who were discordant, with histopathology beyond Milan (adj HR 1.86, 95% CI 1.32–2.63 for mortality and 1.32, 95% CI 1.03–1.70 for recurrence). Graft allocation policy with 6‐month waiting time led to increased discordance (OR 1.19, CI 1.01–1.41), although it did not impact post‐LT outcome. Conclusion Current practice for staging of HCC based on radiological imaging features alone results in underestimation of HCC burden in one out of three patients with HCC. This discordance is associated with a higher risk of post‐LT HCC recurrence and mortality. These patients will need enhanced surveillance to optimize patient selection and aggressive LRT to reduce post‐LT recurrence and increase survival.

Oat (Avena nuda L.) is a globally important cereal crop grown for its nutritious grains and is considered as moderately salt-tolerant. Studying salinity tolerant mechanisms of oats could assist breeders in increasing oat production and their economic income in salt-affected areas, as the total amount of saline land in the world is still increasing. The present study was carried out to better understand the salt tolerance mechanism of the naked oat line Bayou1. A soil experiment was conducted on 17 days-old Bayou1 seedlings treated with varying concentrations of NaCl for a period of 12 days. Bayou1 plants grew optimally when treated with 50 mM NaCl, demonstrating their salinity tolerance. Reduced water uptake, decreased Ca2+, Mg2+, K+, and guaiacol peroxidase activity, as well as increased Na+ concentration in leaves, all contributed to a reduction in shoot growth. However, the damage to ionic homeostasis caused by increased Na+ concentrations and decreased K+ concentrations in the roots of Bayou1 did not inhibit its root growth, indicating that the main salt-tolerant mechanism in Bayou1 existed in its roots. Further, a hydroponic experiment found that increasing Na+ concentration in root cell sap enhanced root growth, while maintaining the integrity of root cell membranes. The accumulated Na+ may have facilitated the root growth of Bayou1 exposed to NaCl by effectively adjusting cellular osmotic potential, thereby ensuring root cell turgor and expansion.

We used the Cellular Automata Markov (CA-Markov) integrated technique to study land use and land cover (LULC) changes in the Cholistan and Thal deserts in Punjab, Pakistan. We plotted the distribution of the LULC throughout the desert terrain for the years 1990, 2006 and 2022. The Random Forest methodology was utilized to classify the data obtained from Landsat 5 (TM), Landsat 7 (ETM+) and Landsat 8 (OLI/TIRS), as well as ancillary data. The LULC maps generated using this method have an overall accuracy of more than 87%. CA-Markov was utilized to forecast changes in land usage in 2022, and changes were projected for 2038 by extending the patterns seen in 2022. A CA-Markov-Chain was developed for simulating long-term landscape changes at 16-year time steps from 2022 to 2038. Analysis of urban sprawl was carried out by using the Random Forest (RF). Through the CA-Markov Chain analysis, we can expect that high density and low-density residential areas will grow from 8.12 to 12.26 km2 and from 18.10 to 28.45 km2 in 2022 and 2038, as inferred from the changes occurred from 1990 to 2022. The LULC projected for 2038 showed that there would be increased urbanization of the terrain, with probable development in the croplands westward and northward, as well as growth in residential centers. The findings can potentially assist management operations geared towards the conservation of wildlife and the eco-system in the region. This study can also be a reference for other studies that try to project changes in arid are as undergoing land-use changes comparable to those in this study.

AbstractThis research compares the use of the SAR (Sentinel-1) and Optical (Sentinel-2) sensors in identifying and mapping burnt and unburnt scars are rising during a bushfire in southeastern Australia and Margalla Hills, Islamabad, Pakistan, in 2019 and 2020. In order to evaluate the backscatter strength along with the Polarimetric decomposition portion, the C-band dual-polarized Sentinel-1 data was investigated to determine the magnitude of the burnt areas of forest cover in the study area. We could derive texture measurements from locally-based statistics using the Grey Level Co-occurrence Matrix (GLCM) and the backscatter coefficient. This was because of how well it picked up on differences in texture between burned and unburned scars. In contrast, Sentinel-2 optical remote sensing was employed to evaluate the extent of the burnt intensity levels for both regions utilizing the differential Normalized Burnt Ratio (dNBR). A Support Vector Machine (SVM) and Markov Random Field (MRF) classifier were utilized to investigate the study’s context. The ideal smoothing parameter is the result of incorporating the image’s spectral characteristics and spatial meaning. Sentinel-2 images were used as a foundation for both the test and training datasets, which were built from images of both unburned and burned areas broken down pixel by pixel. In both types, including spectral sensitivity and sensitivity of Polarimetric for the two groups identified after classification, the experimental findings showed a clear association between them. The algorithm’s efficiency was evaluated using the kappa coefficient and F-score calculation. Except for Sentinel-1 data in Pakistan, all fire areas have more than 0.80 accuracies. The highest precision of both Sentinel-1 and Sentinel-2 was also provided by the performance of users’ and producers’ accuracy. The entropy alpha decomposition helped define the target given by the H-a plane based on its physical properties. After the burn, the entropy and alpha values diminished and formed a pattern. However, the findings in this field validate the effectiveness of SAR sensors data and optical satellite in forest applications. The related sensitivity is highly dependent on the composition of the landscape, the geographical nature of the study area, and the severity of the burn.

Adequate soil moisture around the root zone of the crops is essential for optimal plant growth and productivity throughout the crop season, whereas excessive as well as deficient moisture is usually detrimental. A field experiment was conducted on cotton (Gossipium hirsuttum) with three water regimes (viz. well-watered (control); rainfed after one post-sowing irrigation (1-POSI) and rainfed after two post-sowing irrigations (2-POSI)) in main plots and application of eight osmoprotectants in sub plots of Split plot design to quantify the loss of seed cotton yield (SCY) under high and mild moisture stress. The DSSAT-CROPGRO-cotton model was calibrated to validate the response of cotton crop to water stress. Results elucidated that in comparison of well watered (control) crop, 1-POSI and 2-POSI reduced plant height by 13.5–28.4% and lower leaf area index (LAI) by 21.6–37.6%. Pooled analysis revealed that SCY under control was higher by 1,127 kg ha−1 over 1-POSI and 597 kg ha−1 than 2-POSI. The DSSAT-CROPGRO-cotton model fairly simulated the cotton yield as evidenced by good accuracy (d-stat ≥ 0.92) along with lower root mean square error (RMSE) of ≤183.2 kg ha−1; mean absolute percent error (MAPE) ≤6.5% under different irrigation levels. Similarly, simulated and observed biomass also exhibited good agreement with ≥0.98 d-stat; ≤533.7 kg ha−1 RMSE; and ≤4.6% MAPE. The model accurately simulated the periodical LAI, biomass and soil water dynamics as affected by varying water regimes in conformity with periodical observations. Both the experimental and the simulated results confirmed the decline of SCY with any degree of water stress. Thus, a well calibrated DSSAT-CROPGRO-cotton model may be successfully used for estimating the crop performance under varying hydro-climatic conditions.

ABSTRACT Infectious Bronchitis Virus (IBV) is a highly contagious pathogen that causes a serious illness with global circulation. While there is extensive data available on the virus’s existence and transmission in commercial chickens in Saudi Arabia, there is a lack of such information regarding guineafowls. Therefore, this study aimed to investigate possible IBV infection among guineafowls in the Al-Hassa Governorate of the Eastern Province, Saudi Arabia. Oropharyngeal and cloacal swabs were collected from several unvaccinated flocks of guinea fowls without respiratory clinical symptoms in November and December 2022, totaling 350 samples. Total RNA was extracted from the swab samples, and a conventional reverse transcription-polymerase chain reaction was employed to detect IBV. The results revealed varying amounts of IBV in oropharyngeal and cloacal swabs at different points in time, suggesting that IBV may be widely distributed among guineafowls without exhibiting any symptoms. These findings indicate that guineafowls could act as reservoirs, influencing the ecology and epidemiology of the disease. Notably, this study reports the first occurrence of IBV in the province of Al-Ahsa, highlighting that guineafowls have been naturally exposed to the virus. To support the development of effective vaccination techniques and control measures for the disease in Saudi Arabia, the recommendation for future research endeavors is conducting ongoing surveillance, viral isolation, sequencing, phylogenetic tree analysis, and serotype characterization of IBV in guineafowls.

Background Heavy metal pollution has become a global environmental issue. Heavy metals are contaminating the agro-soils, growing crops, and vegetables through different agricultural practices. In this study, besides the phytoremediation potential of maize, the role of chromium (Cr) and lead (Pb) on crop and soil health has been investigated. Methods Two maize varieties, Pak-Afgoi and Neelem, were grown under varying concentrations of Cr (50–300 ppm) and Pb (30–300 ppm) and different growth parameters i.e., seed germination, leaf size/number, stem girth, plant height, biomass, chlorophyll content, relative growth rate (RGR), and net assimilation rate (NAR) were studied under Cr and Pb stress. Likewise, the effect of metals was also assessed on different soil characteristics including soil texture, pH, EC, soil organic matter, urease activity and nutrients. Results Studied plant attributes were adversely affected by heavy metals toxicity. Affected values of RGR and NAR showed a linear correlation with affected growth and dry matter yield of maize. Heavy metals impacted different soil parameters including soil microbial performance and revealed a declining trend as compared to control soil. Maize varieties showed a significant phytoremediation potential i.e., uptake of Cr and Pb was 33% and 22% in Pak-Afgoi, while Neelem showed 38% and 24% at 300 ppm, respectively. Data regarding metal translocation factor (TF), bioaccumulation factor (ACF), and biomagnification ratio (BMR) significantly revealed the potential of maize varieties in the removal of Cr and Pb metals from affected soils. However, Cr-accumulation was higher in shoots, and Pb accumulated in plant roots showed a differential behavior of metal translocation and affinity with the varieties. These maize varieties may be recommended for general cultivation in the Cr and Pb-contaminated areas.

Soil compaction under repetitive tillage and surface flood method of irrigation (SFMI) are significant hurdles for sustaining crop production in India, necessitating the adoption of efficient soil and water management strategies. Hence, a 3-year field study was conducted at two diverse agro-climatic locations (Abohar and Faridkot) to investigate the impact of subsurface drip (SUSD) fertigation on crop and water productivity of cotton-wheat cropping system (CWCS), over traditional practice (TP) (conventional tillage with SFMI and manual application of nutrients). The experiment was conducted in a factorial randomized complete block design with three levels of subsurface drip irrigation (SUSDI) [100, 80, and 60% of crop evapotranspiration (ETc)] and two fertigation levels [75% recommended dose of nutrients (RDN) and 100% RDN], where TP and surface drip (SD) fertigation at 80% ETc coupled with 100% RDN (Control 2), served as two control treatments. Cotton was raised through reduced tillage, while zero till drill was used for sowing wheat. The results revealed that, barring SUSDI at 60% ETc, both crops exhibited improved yield under all drip combinations of reduced or zero tillage over TP. Better mass and higher length of cotton roots in drip fertigation were evident due to improved steady-state infiltration rates (SSIR) and reduced bulk density (BD) under conservation tillage. When 100% RDN was applied, the 100% and 80% ETc SUSDI resulted in 26.7% and 24.7% higher seed cotton yield (SCY) than TP. Similarly, wheat yield with 100% RDN was improved by 10.5% and 14.4% under SUSDI of 80% and 100% ETc, respectively, over the TP. The results indicated that SUSD can be clubbed with reduced tillage for better soil health, improved crop yield, and higher apparent water productivity. The improved benefit to cost (B:C) owing to enhanced monetary returns over TP also substantiated that reduced tillage with SUSD is a viable and remunerative practice for CWCS. The study elucidated that reduced tillage exercised a beneficial effect on physical soil properties by lowering BD and improving SSIR. At the same time, SUSD could save huge amounts of irrigation water besides enhanced input use efficiency leading to higher crop productivity.

Globally, salinity and drought are severe abiotic stresses that presently threaten vegetable production. This study investigates the potential exogenously-applied glutathione (GSH) to relieve water deficits on Phaseolus vulgaris plants cultivated in saline soil conditions (6.22 dS m−1) by evaluating agronomic, stability index of membrane, water satatus, osmolytes, and antioxidant capacity responses. During two open field growing seasons (2017 and 2018), foliar spraying of glutathione (GSH) at 0.5 (GSH1) or 1.0 (GSH1) mM and three irrigation rates (I100 = 100%, I80 = 80% and I60 = 60% of the crop evapotranspiration) were applied to common bean plants. Water deficits significantly decreased common bean growth, green pods yield, integrity of the membranes, plant water status, SPAD chlorophyll index, and photosynthetic capacity (Fv/Fm, PI), while not improving the irrigation use efficiency (IUE) compared to full irrigation. Foliar-applied GSH markedly lessened drought-induced damages to bean plants, by enhancing the above variables. The integrative I80 + GSH1 or GSH2 and I60 + GSH1 or GSH2 elevated the IUE and exceeded the full irrigation without GSH application (I100) treatment by 38% and 37%, and 33% and 28%, respectively. Drought stress increased proline and total soluble sugars content while decreased the total free amino acids content. However, GSH-supplemented drought-stressed plants mediated further increases in all analyzed osmolytes contents. Exogenous GSH enhanced the common bean antioxidative machinery, being promoted the glutathione and ascorbic acid content as well as up-regulated the activity of superoxide dismutase, catalase, ascorbate peroxidase, and glutathione peroxidase. These findings demonstrate the efficacy of exogenous GSH in alleviating water deficit in bean plants cultivated in salty soil.

Abstract Timely and accurate estimation of rice-growing areas and forecasting of production can provide crucial information for governments, planners, and decision-makers in formulating policies. While there exists studies focusing on paddy rice mapping, only few have compared multi-scale datasets performance in rice classification. Furthermore, rice mapping of large geographical areas with sufficient accuracy for planning purposes has been a challenge in Pakistan, but recent advancements in Google Earth Engine make it possible to analyze spatial and temporal variations within these areas. The study was carried out over southern Punjab (Pakistan)-a region with 380,400 hectares devoted to rice production in year 2020. Previous studies support the individual capabilities of Sentinel-2, Landsat-8, and Moderate Resolution Imaging Spectroradiometer (MODIS) for paddy rice classification. However, to our knowledge, no study has compared the efficiencies of these three datasets in rice crop classification. Thus, this study primarily focuses on comparing these satellites’ data by estimating their potential in rice crop classification using accuracy assessment methods and area estimation. The overall accuracies were found to be 96% for Sentinel-2, 91.7% for Landsat-8, and 82.6% for MODIS. The F1-Scores for derived rice class were 83.8%, 75.5%, and 65.5% for Sentinel-2, Landsat-8, and MODIS, respectively. The rice estimated area corresponded relatively well with the crop statistics report provided by the Department of Agriculture, Punjab, with a mean percentage difference of less than 20% for Sentinel-2 and MODIS and 33% for Landsat-8. The outcomes of this study highlight three points; (a) Rice mapping accuracy improves with increase in spatial resolution, (b) Sentinel-2 efficiently differentiated individual farm level paddy fields while Landsat-8 was not able to do so, and lastly (c) Increase in rice cultivated area was observed using satellite images compared to the government provided statistics.

Abstract Slow release nitrogenous fertilizers can improve crops production and reduce the environmental challenges in agro-ecosystem. There is a need to test the efficiency and performance under arid climatic conditions. The study investigates the effect of slow-release fertilizers (urea, neem coated urea (NCU), sulfur coated urea (SCU) and bioactive sulfur coated urea (BSCU)) on the growth, productivity and grain nutritional qualities of wheat crop. Slow-release fertilizers (SRF) with nitrogen levels (130,117,104 and 94 kg ha−1) were applied with equal splits at sowing, 20 and 60 days after sowing (DAS). Research showed that the BSCU with 130 kg ha−1 increased dry matter accumulation (1989 kg ha−1) after anthesis and grain yield 4463 kg ha−1. The higher plant height (102 cm) was attained by 130 kg N ha−1 SCU while the minimum (77.67 cm) recorded for 94 kg N ha−1 as urea source. Maximum grain NPK concentrations (3.54, 0.66 and 1.07%) were recorded by BSCU 130 kg N ha−1 application. While, the minimum NPK (0.77, 0.19 and 0.35%) were observed by Urea 94 kg N ha−1. The high irrigation water use efficiency (WUE) recorded (20.92 kg ha−1 mm−1) and a crop index of 25.52% by BSCU 130 kg N ha−1 application. Research findings show that generally all SRF but particularly BSCU proved effective and can be recommended for wheat crop under arid environment.

Drought stress is one of the major limitations to the growth and yield productivity of cereal crops. It severely impairs the early growing and grain -filling stages of wheat. Therefore, cost- effective and eco-friendly approaches for alleviating drought stress in cereal crops are in high demand. Polyamines, such as putrescine, have a significant effect on improving crop yield under drought- stress conditions. Therefore, the current study was executed with the aim of exploring the significance of putrescine in alleviating drought stress and improving yield- related traits in wheat. Two distinct wheat cultivars (Fakhar-e-Bhakkar and Anaj-2017) were treated with the foliar application of different concentrations (control, 0.5, 1.0, and 1.5 PPM) of putrescine (put) under two moisture conditions (well- watered and terminal drought stress). The results demonstrate that the imposition of terminal drought stress significantly reduces different physiological and yield- related traits of both wheat cultivars. The reduction of relative water content (RWC%), membrane stability index (MSI), leaf area, tillers per plant, biomass yield, number of spikelets per spike, 100-grain weight, grain yield per plant, and straw yield was greater in Anaj-2017 than in Fakhar-e-Bhakkar cultivar. The results further explain that the foliar application of increased concentrations of putrescine from 0.0 to 1.0 PPM gradually improved physiological and yield traits, whereas these traits declined with the application of putrescine at the highest dose (1.5 PPM). The exogenous application of 1.0 PPM putrescine improved the relative water content (19.76%), specific leaf area (41.47%), and leaf area ratio (35.84%) compared with the controlled treatment. A higher grain yield (28.0 g plant-1) and 100-grain weight (3.8 g) were obtained with the foliar application of 1.0 PPM putrescine compared with controlled treatments. The findings of this study confirm the protective role of putrescine against terminal drought stress. It is therefore recommended to use putrescine at a concentration of 1.0 PPM, which could help alleviate terminal drought stress and attain better wheat yield.

PurposeThe Polygonum equisetifome is a prospective plant source of high protein, unsaturated fatty acids, and useful safe bioactive molecules. Therefore, the aim of this study was to optimize the ultrasonic aqueous extraction of phenols from P. equisetifome roots using Box-Behnken design based statistical modeling, and to evaluate the antioxidant and antibacterial efficiencies of P. equisetifome root extracts against pathogenic bacteria.MethodsIn this study, the box-behnken design was used to optimize the extraction of phenols. The extraction temperature (30–70°C), ultrasound assisted extraction (UAE) time (1–9 min), and liquid-solid ratio (35–45 mL/g) were investigated as the factors that influence the phenolic yield (Y1) and their DPPH (1,1-diphenyl-2-picrylhydrazyl) scavenging activity (Y2).ResultsThe optimal conditions for both responses were 50°C, 5 min, and 40 mL/g. At these conditions, Y1 reached its maximum to be 45.321 mg GAE/g dry weight and Y2 to be 120.354 μmol Trolox/g dry weight. The P. equisetifome roots contained water soluble phenol, high anthocyanin, and condensed tannins. Interestingly, the P. equisetifome extracts showed a relation to its antioxidant and antibacterial activities, FRAP (Ferric-reducing/antioxidant power), and ABTS scavenging activity were determined. The morphological and physico-chemical features of the extract were analyzed using SEM-EDX, FT-IR, and minimum inhibitory concentration (MIC) was analyzed against several pathogenic bacteria. The antibacterial activity of the extract showed that the extract is more efficient against Staphylococcus aureus, while the P. equisetifome extracts showed efficient MIC against S. aureus, followed by Bacillus cereus.SuggestionsThe relation of P. equisetifome extracts to its antioxidant, and antibacterial efficiencies open a new avenue of their potential uses in the food and pharmaceutical industries.

Adaptive e-learning is viewed as stimulation to support learning and improve student engagement, so designing appropriate adaptive e-learning environments contributes to personalizing instruction to reinforce learning outcomes. The purpose of this paper is to design an adaptive e-learning environment based on students' learning styles and study the impact of the adaptive e-learning environment on students' engagement. This research attempts as well to outline and compare the proposed adaptive e-learning environment with a conventional e-learning approach. The paper is based on mixed research methods that were used to study the impact as follows: Development method is used in designing the adaptive e-learning environment, a quasi-experimental research design for conducting the research experiment. The student engagement scale is used to measure the following affective and behavioral factors of engagement (skills, participation/interaction, performance, emotional). The results revealed that the experimental group is statistically significantly higher than those in the control group. These experimental results imply the potential of an adaptive e-learning environment to engage students towards learning. Several practical recommendations forward from this paper: how to design a base for adaptive e-learning based on the learning styles and their implementation; how to increase the impact of adaptive e-learning in education; how to raise cost efficiency of education. The proposed adaptive e-learning approach and the results can help e-learning institutes in designing and developing more customized and adaptive e-learning environments to reinforce student engagement.

Abstract Background Tomato, Solanum lycopersicum L. (Solanales: Solanaceae) is the second most important vegetable crop in Egypt and is infested with many insect pests. The cotton leafworm, Spodoptera littoralis (Boisd.) causes severe economic losses in tomatoes and many other crops. Many management strategies were developed in order to manage the economic losses obtained. In this context, the present study was conducted to evaluate the effectiveness using a mixture of Emamectin benzoate and lufenuron or using them solely against the 2nd and 4th instar larvae of S. littoralis under semi-field conditions. Results The obtained results showed that the mixture compound show high initial killing effect against 2nd and 4th instar larvae in both growing seasons. Furthermore, the residual effect of the tested compounds also showed the efficiency of the mixture over the solitary active ingredients. In addition, the treatment of the 4th instar larvae with the LC50 of the tested compounds showed significant impacts against the soluble protein, carbohydrate, lipid contents, and the detoxification enzymes. Conclusion In conclusion, the results showed that the emamectin benzoate and lufenuron could be safe and effective substitute for conventional insecticides either applied solely or in combination.

Flooding stress declines oxygen availability in roots that induce hypoxia stress in plants, thereby severely decline plant growth. Study was undertaken to clarify how potassium supplementation alleviates flooding stress in cotton plants. We applied potassium (K) fertilizer in pot soils at different levels; K0 = Control (No K), K1 = 30 mg kg−1, K2 = 60 mg kg−1 and K3 = 80 mg kg−1 with different duration of flooding stress s. D0 = Normal irrigation (0 day flooding), D1 = three days flooding, D2 = six days flooding, D3 = nine days flooding, D4 = twelve days flooding. The K supplementation (80 mg kg−1) in soil with 3-day flooding stress showed better combination for mitigating flooding stress. The supplementation of K3 dose (80 mg kg−1) alleviated flooding against 3-day initial flooding (D1) of which physiological traits showed better response compared to prolonged flooding stress (12-day flooding stress). The result suggests that K-involving flooding stress mitigation strategy in cotton plants was active for initial flooding stress (3-day flooding stress), while it was not fully active for pronged (upto 12-day flooding stress). Furthermore, we found K significantly improved antioxidant enzymes, photosynthetic performance, yield attributes, and lint quality. [ABSTRACT FROM AUTHOR]

Salinity stress represents a major threat to crop production by inhibiting seed germination, growth of seedlings, and final yield and, therefore, to the social and economic prosperity of developing countries. Recently, plant growth‐promoting substances have been widely used as a chemical strategy for improving plant resilience towards abiotic stresses. This study aimed to determine whether melatonin (MT) and glycine betaine (GB) alone or in combination could alleviate the salinity‐induced impacts on seed germination and growth of maize seedlings. Increasing NaCl concentration from 100 to 200 mM declined seed germination rate (4.6–37.7%), germination potential (24.5–46.7%), radical length (7.7–40.0%), plumule length (2.2–35.6%), seedling fresh (1.7–41.3%) and dry weight (23.0–56.1%) compared to control (CN) plants. However, MT and GB treatments lessened the adverse effects of 100 and 150 mM NaCl and enhanced germination comparable to control plants. In addition, results from the pot experiments show that 200 mM NaCl stress disrupted the osmotic balance and persuaded oxidative stress, presented by higher electrolyte leakage, hydrogen peroxide, superoxide radicals, and malondialdehyde compared to control plants. However, compared to the NaCl treatment, NaCl+MT+GB treatment decreased the accumulation of malondialdehyde (24.2–42.1%), hydrogen peroxide (36.2–44.0%), and superoxide radicals (20.1–50.9%) by up‐regulating the activity of superoxide dismutase (28.4–51.2%), catalase (82.2–111.5%), ascorbate peroxidase (40.3–59.2%), and peroxidase (62.2–117.9%), and by enhancing osmolytes accumulation, thereby reducing NaCl‐induced oxidative damages. Based on these findings, the application of MT+GB is an efficient chemical strategy for improving seed germination and growth of seedlings by improving the physiological and biochemical attributes of maize under 200 mM NaCl stress. [ABSTRACT FROM AUTHOR]

Background: Relapsing seizures following discontinuation of antiseizure drugs (ASDs) has been the focus of several researches in recent years. This research aimed to identify the predictive factors of seizure recurrence after anti-seizure drugs withdrawal among epileptic patients who had achieved two years seizures remission. Methods: A total of 60 epileptic patients who had achieved two years seizures remission and began ASDs withdrawal were followed prospectively for one year. The patients were divided into two groups; patients with and without relapsed seizures. Clinical and demographic details were recorded. National Hospital Seizure Severity Scale (NHS3) was used to assess theseverity of epilepsy. Regular Electroencephalogram (EEG) monitoring was done. Anxiety and depressive symptoms were assessed by using generalized anxiety disorder 7 (GAD7) and Neurological Disorders Depression Inventory for Epilepsy (NDDI-E) scales respectively. Results: Risk of post-withdrawal relapsed seizures increased with; history of status epilepticus (p=0.002), focal seizures (p=0.005), late remission of initial epileptic seizures (p=0.002), delay of ASD therapy (p<0.001), Poly-therapy (p<0.001), post-withdrawal epileptiform EEG (p<0.001), high NHS3, GAD7, NDDI-E scores (p<0.001) Conclusions: Risk of relapsing seizures after ASDs withdrawal during the first year was 60%. The decision to withdraw ASDs necessitates individual evaluation of each case with accurate assessment of risk factors associating with relapsed seizures. [ABSTRACT FROM AUTHOR]

Sesame is one of the important oilseeds across the globe for edible, pharmaceutical and cosmetic purposes. Sesame is low water requiring crop and grows well on marginal land with less inputs. The study aimed to evaluate the growth, yield and oil content of three sesame varieties TS-3, TS-5 and TH-6 in response to various foliar applications of salicylate (50 mgL-1), ascorbate (50 mgL-1), hydrogen peroxide (40 µML-1) and L-Methionine (150 mgL-1). Field trial was executed during May 2021 at Agronomic Research Farm, University of Agriculture, Faisalabad by employing factorial design and three replications. Irrigation was applied first at 25 days after sowing and second after 70 days while as the foliar amendments of growth promoters was applied at 50, 60 and 70 days of crop life. From the results of this experiment, it is concluded that, the variety TH-6 is short duration as compared to other varieties. Effect of foliar application showed significant impact on sesame varieties. The best results were recorded under salicylic acid treatments followed by ascorbic acid and L-methionine while as the least response was recorded without foliar application. The number of seeds per pod, harvest index, thousand seed weight, seed yield kgha-1 and oil contents were recorded maximum under variety TH-6 when exposed to salicylic acid treatment while as the minimum response was showed in variety TS-3. Moreover, the highest phenolic content was determined by employing ascorbic acid (50 mgL-1) followed by salicylic acid (50 mgL-1) and the lowest findings were recorded where without foliar application. However, the emerged proline content was assessed in all sesame varieties with control treatment whereas the least findings were recorded from L-Methionine (150 mgL-1) treatment. [ABSTRACT FROM AUTHOR]