Abstract:A sensitive and rapid method was developed to evaluate the flavonoids, iridoid glycosides, and phenolic acids in Gardenia jasminoides J. Ellis (GJE) from various regions, utilizing multiple reaction monitoring (MRM) of UFLC/QTRAP-MS in conjunction with principal component analysis (PCA) for simultaneous quantification. The findings revealed that all target constituents were accurately identified in GJE samples, confirming the method's efficacy for the concurrent determination of 21 chemicals. Notable discrepancies in the content of GJE from various places were noted, indicating that geographical differences and similarities, together with processing methods and harvesting time, significantly impact GJE composition. The PCA findings corresponded with the quantitative analysis. GJE from Jurong City, Jiangsu Province, was chosen as the herbal material for further tests due to its active ingredient composition, with Jiangsu Province recognized as the ideal location for GJE cultivation. This study offers a methodological framework for the optimal selection and thorough assessment of GJE quality in various locales.
Abstract:The development of the circular economy model in Vietnam is still facing several shortcomings. One of the main issues is the lack of participation from farmers, which varies significantly among different localities and regions. This poses a significant challenge for researchers and policymakers who must collaborate to find effective solutions. To address this issue, a study was conducted using survey data from 600 farmers in the Mekong Delta region of Vietnam. By applying a Binary Logistic Regression model, the study identified nine key factors that affect farmers` participation in the circular economy. These factors include their attitude towards the circular economy, access to credit, level of interaction with agricultural extension staff, subjective norms, agricultural land area, non-agricultural income, education level, age of the household head, and distance from home to the nearest market.
Abstract:Gastric cancer, another name for stomach cancer, is a kind of cancer that begins as a cell growth in the stomach and has a poor diagnosis. The world`s pathologist shortage offers a unique chance to implement AI support systems to cut down on labor and boost diagnostic accuracy. It is believed that genetic instability, manifesting as either chromosomal instability or microsatellite instability, is a precursor to stomach carcinogenesis in the majority of cases of stomach cancer. The new categorization of stomach cancers based on histologic features, genetics and molecular phenotypes has improved early identification, prevention and therapy by illuminating the features of each subtype. Located directly below the ribs in the upper central region of the abdomen is the stomach. This research develops a solution using deep learning algorithms to aid in the pathological diagnosis of gastric cancer over Gastric Histopathology Sub-size Image Database, a publicly available database for medical image analysis. An advanced algorithm is created by combining three different algorithms, and it is then used to diagnose cancer more accurately. The combination of these three algorithms-Multitask Net, Fusion Net, and Global Net-creates a powerful ensemble model that leverages the strengths of each approach, leading to improved gastric cancer classification performance. This hybrid approach can aid in early diagnosis and treatment planning, ultimately improving patient outcomes.
Abstract:Assyrian plum or Lasura (Cordia myxa L.) is a widely recognized as diverse traditional medicinal plant. Different parts of this species have been utilized for the treatment of various diseases. However, information about the bioactive compounds and antimicrobial properties of Assyrian plum is scarce. This study was designed to analyze bioactive compounds, such as total antioxidants, phenolics, flavonoids, alkaloids, tannins, terpenoids, and saponins in 20% ethanol, methanol, acetone and aqueous extracts from different segments of Assyrian plum. The investigation revealed substantial amounts of these bioactive compounds in the studied segments, indicating the plant's potential therapeutic value. In addition, the highest amount of total protein content was found in ethanol extracts of root, fruit, leaves and stem (34.7 ± 1.08 mg/ml, 34.2 ± 1.16 mg/ml, 34.1 ± 1.12 mg/ml, 30.0 ± 0.02 mg/ml) respectively. Methanol extract of fruit exhibited the maximum quantity of total sugar (54.0 ± 0.32 mg/mL), while methanol extract of fruit displayed significantly higher levels of reducing sugar (0.159 ± 0.0004 mg/ml) compared to other parts of Assyrian plum extracts. The extracts of different parts of Assyrian plum strongly inhibited the growth of human pathogenic bacteria Escherichia coli and Staphylococcus aureus. Furthermore, 20% extracts of different segments of Assyrian plum also successfully ceased the growth of Aspergillus fumigatus and Aspergillus niger. This study provides valuable information about the bioactive composition of Assyrian plum and highlights its potential as a source of natural antimicrobial agents, supporting its traditional medicinal applications.
Abstract:Some sources of nitrogen fertilizer can be easily lost in the soil and result with yield reduction in grain sorghum. The objective of this study was to determine the effects of nitrogen fertilizer sources and field conditions on yield of grain sorghum. A 2 x 5 x 2 factorial field experiment arranged in a split-split plot design was executed in North-West University experimental farm during 2018/19 and 2019/20 planting seasons. The main plots were two field conditions (irrigated and rainfed), the subplots were two sorghum cultivars (Titan and Avenger) and the sub-subplots were nitrogen sources (LAN, Urea, ammonium sulphate, ammonium sulphate nitrate and control). The measured yield parameters were plant population, field biomass yield, panicle mass, grain yield and 1000 grain mass. Though no significant differences were observed amongst the nitrogen sources, sorghum treated with limestone ammonium nitrate showed a higher panicle mass of 6173.14 and 5979.08 kg/ha during the 2018/19 and 2019/20 planting seasons respectively. During the 2018/19 planting season, sorghum treated with limestone ammonium nitrate and ammonium sulphate nitrate had a higher grain yield of 4132.43 and 4088.33 kg/ha respectively. During the 2019/20 planting season, sorghum treated with ammonium sulphate nitrate, limestone ammonium nitrate and urea had a higher grain yield of 4656 kg/ha each. Field condition had a significant effect on sorghum panicle mass and grain yield during the 2018/19 and 2019/20 planting seasons. Sorghum planted under irrigation had a significantly higher panicle mass of 6316.53 and 6781.75 kg/ha during both planting seasons respectively. Sorghum planted under irrigation had a significantly higher grain yield of 4198.02 and 4823.59 kg/ha during both planting seasons respectively. In this study, limestone ammonium nitrate and urea are recommended to farmers since both fertilizers were found to improve sorghum biomass, panicle mass and grain yields. Irrigation field condition was found to enhance panicle mass and grain yield of sorghum.
Abstract:One of today's most quickly developing technologies is the Internet of Things (IoT). There are now more threats and risks to its security than ever before. In order to tackle present and future IoT issues, machine learning is an effective technology that can be used to identify risks and threats in intelligent systems. In today’s world, credit card is the most popular payment mode for both online and offline. Consumers rely on online shopping and online bill payment, which cases of fraud associated with it are also increasing. With the developments in the communication channels, fraud is spreading all over the world resulting in huge financial losses. Fraud detection is the essential tool and probably the best way to stop fraud types. There is a technique of finding an optimal solution for a problem and implicitly generate the results using machine learning and genetic algorithm. The aim is to develop a model to detect fraudulent transactions and improves a credit card fraud detection solution with some machine learning algorithms such as GA, DT, LR, KNN, SVC, and ANN based on the RUST and SMOTE techniques. The experiments are conducted on the BCCFDD and DCCCD datasets to analyze the model using the dimension reduction transformers (T-SNE, PCA, and Truncated SVD). The performance of the classification model analyzed in terms of confusion matrix, the model ROC curve analysis, and accuracy. The evaluation finding is analyzed and compared. As proof of concept, a Credit Card Fraud Detection System (CCFDS) is developed to detect the credit card fraud based on the principles of the GA and showed the effectiveness of proposed approach. This algorithm is an optimization technique and evolutionary search based on the principles of genetic and natural selection, heuristic used to solve high complexity computational problems.
Abstract:Salinity is one of the major constraints prevailing in the environment, affecting plant growth, agricultural productivity, and soil fertility. The application of beneficial silicon-rich bio-stimulants presents an alternative strategy to ensure agricultural sustainability, as their use and expansion can help mitigate the adverse effects of salinity and reduce the excessive use of synthetic chemicals. The objective of this study was to evaluate the interaction between salinity levels and the use of Farina di Basalto Type XF (FdBXF) on the germination and early seedling growth of two alfalfa (Medicago sativa L.) varieties (Gabes and Azzura). Five levels of sodium chloride (0, 50, 100, 150, and 200 mM) and five levels of Farina di Basalto Type XF (0, 1, 3, 5, and 10%) were tested in 30 treatments under a completely random design. Germination percentage, mean germination time, radicle length, hypocotyl and cotyledon length, and biomass were measured at the end of the experiments. Sodium chloride significantly reduced all germination and seedling growth parameters. The reduction in the measured parameters was inversely proportional to increasing concentrations of NaCl. The application of Farina di Basalto Type XF mitigated the negative effects of NaCl (p<0.01). The most significant attenuation was recorded for a 3% concentration of Farina di Basalto Type XF. This study provides insights into the role of Farina di Basalto Type XF in salt stress tolerance in M. sativa.
Abstract:Pathogens infect rice plants during vegetative and generative growth and can cause a decrease in rice production were estimated Root-knot nematode (RKN). This study aimed to identify pathogen infected rice paddy field in West Papua Province and to reveal genetic relationships among isolates using the ITS rDNA sequence data. The RKN isolates were isolated from rice plantations centre in West Papua Province and other RKN rDNA sequences were retrieved from the GenBank. Based od ITS rDNA sequence data, RKN infects rice faddy field in West Papua Province were identified species of Meloidogyne graminicola and were observed four genotypes, namely genotype-1 for Prafi-1 isolates, genotype-2 for Prafi-2 isolates, genotype-3 for Sidey isolates, and genotype-4 for Oransbary isolates. M. garminicola is closely related with M. garminicola from Thailand-1 (MT271020.1), Thailand-2 (MT271021.1), Nepal-1 (DQ909035.1), Nepal-3 (DQ909038.1), and Nepal-7 (DQ909049.1) with genetic distance range from 0.28 to 2.14 and being in the same sub-clades. This pest is first reported infects rice paddy field in West Papua Province and need awareness so that unspread to any rice faddy field.
Abstract:Nepovirus Grapevine FanLeaf Virus (GFLV) is among the viruses that cause the infectious degeneration of grapevines. It is transmitted by the ectoparasitic nematode Xiphenema index. This study aimed to investigate the GFLV virus in 25 vineyards located in north-central Algeria and occupied by nine different grape varieties. Several surveys were carried out during the period 2015-2023, to collect samples presenting typical symptoms of a possible GFLV infection. Immunological screening for GFLV in the 376 samples collected was carried out using the specific DAS-ELISA technique. Our results showed the presence of typical GFLV symptoms in all the vineyards surveyed. Statistical analysis using the FACM technique demonstrated that the most discriminating symptoms are growth retardation, developmental anomalies, and flower abortion. Anomalies display correlations with deformation and growth delays at proportions of 65.3% and 61%, respectively. Similarly, sagging correlates with these symptoms at a rate of 69.5%. Furthermore, growth delay exhibits a notable correlation of 78.6% with the symptom of flower aboration. The DAS-ELISA serological test shows an infection rate of 43.35% on 376 samples tested. Dattier Beyrouth and Dabouki grape varieties are the most infected, with infection rates of 25.15% and 22.70%, respectively, which represents almost half of all the samples tested. The SO4 rootstock has the highest infection rate, with a 52.15% infection rate.
Abstract:Sustainable agriculture plays an important role in agricultural productivity in that it seeks to reduce chemical fertilizers use and promote the use of alternative, low-cost and environmentally friendly sources. In this sense, basalt dust has shown potential to improve soil fertility and crop nutrition. Thus, an experiment was carried out with the goal to evaluate the potential impact of a basaltic rock flour "Farina di Basalto" type XF on growth parameters of tomato crop under greenhouse. Total leaves content of flavonoids, polyphenols and antioxidant activity were also investigated. Experiments were carried out in a pot system using substrate drenches to apply the basalt flour at different levels, (0%, 1.5%, 3% and 4.5%). The growing media chosen for the trials consisted of a mixture of soil, perlite and potting soil (1:1:1:). The results showed that increasing basalt flour to 4.5%, increased significantly growth parameters of tomato plants. However, for plant height and shoot length, increasing dose from 3% to 4.5% was not significant. Results showed also that leaves dry matter, flavonoids and polyphenols contents were negatively affected when increasing dose to 4.5%. Although, applying of 3% of basalt flour was the most effective in improving antioxidant compounds in tomato plants, the higher antioxidant activity was obtained by applying of 4.5% basalt flour. These results showed the usefulness of basalt flour in improving plant growth parameters and phytochemical compounds offering the possibility of using it as both a natural fertilizer and a biostimulant in sustainable agriculture.