This work investigated the effect of variably formulated pesta granules containing wild and UV mutated Pseudomonas aeruginosa and Lasiodiplodia pseudotheobromae on the rate of CO evolution, organic carbon content, enzymatic activity (acidic and alkaline phosphatase, dehydrogenases, urease and protease) and representative soil microorganisms in the soils using different assay techniques. After the 35th day period of experiment, the pesta granule formulation BH4 showed the best evolution of CO (824 ± 6.2 mg CO kg soil hr) as against control treatment (689 ± 3.7 mg CO kg soil hr). Enzymes activities, organic carbon content of 3.8% on the 15th day of study and stable representation of microorganisms that include actinomycetes, fungi, heterogenous as well as soil nitrogen-mediatory bacteria were equally at their maximum level BH4 treatments. The phytotoxic assay showed no inhibitory effect on Solanum lycopersicum seeds and seedlings compared to the observed growth inhibition on the tested weeds (Amaranthus hybridus and Echinocholoa crus-galli) which corresponds with positive control glyphosate treatment. The glyphosate treated soil had the least critical results on parameters investigated during the study. The order of bioherbicidal activity is BH4>BH2>BH6>BH3>BH1>BH5>positive control. Results from this study confirmed the target efficacy of variably formulated pesta granules which is sustainable, cheap, ecologically suitable and recent. This is in addition to recognizing the microbial-derived formulations as characteristically potent alternative to chemical herbicides utility in agrosystems practice. Further study of the underlining factor responsible for the bioherbicidal performances of the variably formulated pesta granules and field trials are critical for their future commercialization.
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http://dx.doi.org/10.1016/j.chemosphere.2017.12.056 | DOI Listing |
Sci Rep
December 2024
Gateway Antarctica, University of Canterbury, Christchurch, New Zealand.
The Tibetan Plateau is home to numerous glaciers that are important for freshwater supply and climate regulation. These glaciers, which are highly sensitive to climatic variations, serve as vital indicators of climate change. Understanding glacier-fed hydrological systems is essential for predicting water availability and formulating climate adaptation strategies.
View Article and Find Full Text PDFTransl Anim Sci
December 2024
Department of International Development, School of Agriculture, Policy and Development, University of Reading, Reading RG6 6EU, UK.
The objective of this study was to determine the effects of dietary agro-industrial by-products (AIBP) with different amounts of metabolizable energy (ME) and crude protein (CP) on fermentation (96 h) and gas production (GP) kinetics in vitro, as well as acceptability, animal performance, digestibility, and blood parameters in lambs. The gas production technique (GPT) and fermentation characteristics were used in an in vitro trial. This experiment used diets with ME contents of 6.
View Article and Find Full Text PDFBMC Genomics
December 2024
School of Computer Science and Technology, Qingdao University, Ningxia Road, Qingdao, Shandong Province, 266071, China.
Background: Discontinuous transcription allows coronaviruses to efficiently replicate and transmit within host cells, enhancing their adaptability and survival. Assembling viral transcripts is crucial for virology research and the development of antiviral strategies. However, traditional transcript assembly methods primarily designed for variable alternative splicing events in eukaryotes are not suitable for the viral transcript assembly problem.
View Article and Find Full Text PDFFront Public Health
December 2024
School of Nursing, University of South China, Hengyang, China.
Objective: This study aimed to conduct a systematic review and meta-analysis, assessing the pooled prevalence and influencing factors of oral frailty in older people to assist healthcare professionals in enhancing their understanding of this condition and formulating efficient interventions.
Methods: This systematic review was performed based on the Preferred Reporting Items for Systematic Reviews and Meta-analyses Statement (PRISMA) guidelines. We searched PubMed, Web of Science, The Cochrane Library, Embase, CINAHL, ProQuest, the National Knowledge Infrastructure (CNKI), WAN FANG DATA, VIP Information, SinoMed and Scopus for literature published in English or Chinese from inception to June 19, 2024.
Front Oncol
December 2024
Department of Urology, Second Affiliated Hospital of Nanchang University, Nanchang, China.
Background And Purpose: Distant metastasis in bladder cancer is linked to poor prognosis and significant mortality. Machine learning (ML), a key area of artificial intelligence, has shown promise in the diagnosis, staging, and treatment of bladder cancer. This study aimed to employ various ML techniques to predict distant metastasis in patients with bladder cancer.
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