Performance of a selected Trichoderma strain as plant pathogen inhibitor and biofertilizer

Aims@#The application of beneficial microbes is a suitable alternative to synthetic pesticides and fertilizers for agriculture. This study was aimed to evaluate the potential of a selected Trichoderma strain as a biocontrol agent against Rhizoctonia sp. and as a biofertilizer to improve paddy growth.@*Methodology and results@#Four Bipolaris strains were identified via DNA barcoding as the cause of brown spot disease, whereas two Rhizoctonia strains were similarly identified as the cause of sheath blight disease in Brunei Darussalam. Eight Trichoderma strains were initially screened using confrontation assay and were found to substantially inhibit the growth of Rhizoctonia sp. Hybrid rice named BDR5 was treated with Trichoderma sp. UBDFM01 and/or Rhizoctonia sp. It was found that the selected strain showed the potential as a biofertilizer by significantly increasing the vigour index I, chlorophyll a, chlorophyll b, total chlorophyll and dry shoot weight of the rice plants. The pathogen negatively affected the plants by significantly reducing the vigour index II, chlorophyll a, chlorophyll a/b ratio, total chlorophyll, and total weight of grains. Trichoderma strain showed the potential as a biocontrol agent by significantly diminishing the negative effects of the pathogen on the chlorophyll a, chlorophyll a/b ratio and total chlorophyll.@*Conclusion, significance and impact of study@#This study highlights the potential of Trichoderma sp. UBDFM01 as a biocontrol agent against Rhizoctonia sp. and also as a biofertilizer for rice plants. In addition, this study is the first to provide DNA-based evidence of Bipolaris sp. and Rhizoctonia sp. as the fungi that caused rice diseases in Brunei Darussalam.

Mind the gap: an analysis of core capacities of the international health regulations (2005) to respond to outbreaks in Yemen.

BACKGROUND: Yemen that has been devastated by war is facing various challenges to respond to the recent potential outbreaks and other public health emergencies due to lack of proper strategies and regulations, which are essential to public health security. The aim of this study is to assess the implementation of the International Health Regulations (IHR 2005) core capacities under the current ongoing conflict in Yemen. METHODS: The study simulated the World Health Organization (WHO) Joint External Evaluation (JEE) tool to assess the IHR core capacities in Yemen. Qualitative research methods were used, including desk reviews, in-depth interviews with key informants and analysis of the pooled data. RESULT: Based on the assessment of the three main functions of the IHR framework (prevention, detection, and response), Yemen showed a demonstrated or developed capacity to detect outbreaks, but nevertheless limited or no capacity to prevent and respond to outbreaks. CONCLUSION: This study shows that there has been poor implementation of IHR in Yemen. Therefore, urgent interventions are needed to strengthen the implementation of the IHR core capacities in Yemen. The study recommends 1) raising awareness among national and international health staff on the importance of IHR; 2) improving alignment of INGO programs with government health programs and aligning both towards better implementation of the IHR; 3) improving programmatic coordination, planning and implementation among health stakeholders; 4) increasing funding of the global health security agenda at country level; 5) using innovative approaches to analyze and address gaps in the disrupted health system, and; 6) addressing the root cause of the collapse of the health services and overall health system in Yemen by ending the protracted conflict situation.

Optimum Feature Selection with Particle Swarm Optimization to Face Recognition System Using Gabor Wavelet Transform and Deep Learning.

In this study, Gabor wavelet transform on the strength of deep learning which is a new approach for the symmetry face database is presented. A proposed face recognition system was developed to be used for different purposes. We used Gabor wavelet transform for feature extraction of symmetry face training data, and then, we used the deep learning method for recognition. We implemented and evaluated the proposed method on ORL and YALE databases with MATLAB 2020a. Moreover, the same experiments were conducted applying particle swarm optimization (PSO) for the feature selection approach. The implementation of Gabor wavelet feature extraction with a high number of training image samples has proved to be more effective than other methods in our study. The recognition rate when implementing the PSO methods on the ORL database is 85.42% while it is 92% with the three methods on the YALE database. However, the use of the PSO algorithm has increased the accuracy rate to 96.22% for the ORL database and 94.66% for the YALE database.

Ethnobotanical review and pharmacological properties of selected medicinal plants in Brunei Darussalam: Litsea elliptica, Dillenia suffruticosa, Dillenia excelsa, Aidia racemosa, Vitex pinnata and Senna alata

The aim of the current study is to review the medicinal properties of the plants found in Brunei Darussalam namely Litsea elliptica, Dillenia suffruticosa, Dillenia excelsa, Aidia racemosa, Vitex pinnata and Senna alata. The known phytochemical constituents of these plants and their ability to bring about a range of biological activities are included in this review. These plants have been used traditionally for a multitude of diseases and illnesses. There is a lot of untapped potential in these medicinal plants which could cure multiple diseases.

Chemical constituents and their antibacterial and antifungal activity from the Egyptian herbal medicine Chiliadenus montanus.

Phytochemical investigations of the CH2Cl2/MeOH (1:1) extract of air-dried aerial parts of Chiliadenus montanus afforded eight metabolites, in addition to eight other previously reported compounds, of which two were isolated for the first time as free acids. Structures were established by spectroscopic methods, including HREIMS, (1)H, (13)C, DEPT, (1)H-(1)H COSY, HMQC and HMBC NMR analysis. Antimicrobial activity against an array of common bacterial and fungal strains was measured via a colorimetric assay with minimal growth inhibition observed in the µg/mL range for one of the tested metabolites.

Nor-ent-kaurane diterpenes and hydroxylactones from Antennaria geyeri and Anaphalis margaritacea.

In a study of Pacific Northwest plants of the Asteraceae family, a nor-ent-kaurane diterpene and a known diterpene, both displaying antibacterial activities, were isolated together with scopoletin and sitosterol-3-O-beta-glucopyranoside from the aerial parts of Antennaria geyeri. Anaphalis margaritacea afforded two hydroxylactones. The structures were established by one and two dimensional NMR techniques, IR and CIMS.