The performance of five cauliflower cultivars in conventional and alternative phytosanitary management—without the use of synthetic pesticides—was evaluated. Two experiments were conducted at Epagri, Ituporanga Experimental Station in February 2018 and 2019. A randomized block design with four repetitions was adopted, with twenty plants of each cultivar as plots. The seedlings were transplanted on millet and mucuna straw at a spacing of 0.5 m × 0.8 m. We evaluated agronomic yield, inflorescence quality, pest damage and plant diseases, especially bacterial and fungal rots. The cauliflower hybrids Vera, Verona and Serena stood out in productivity and quality, being the most indicated for sowing in off-season crops, in the Alto Vale do Itajaí region. The most productive cultivars were less damaged by bacterial diseases and defoliating caterpillars and without interference of whitefly infestation on yield. The results also reveal that it is possible to control pests and diseases with phytosanitary products of lower toxicity, i.e., with lower residues of synthetic pesticides.
The interest in smart grids and new technologies is growing around the world. Countries are investing in the development of new technologies that will help achieve environmental goals, energy supply efficiency, improve energy efficiency and increase consumer involvement in the energy generation. One of such technology is a blockchain. It is believed that the blockchain, combined with a smart grid, provides an opportunity to integrate the activities of all stakeholders, including: generators, distributors and consumers of electricity. The aim of the article is to identify the key research areas discussed by the researchers of both the smart grid and the blockchain issues. An analysis of the Scopus database from 2015 to 2023 was conducted. Using a created bibliometric query, a systematic literature review was conducted. 476 scientific publications relating to the issues addressed were identified. Using the VOSviewer software, a bibliometric analysis was performed using the author’s keywords. The bibliometric maps obtained allowed for the identification of key research areas. The article also presents potential future directions of scientific considerations, which should be focused on the issue of green smart grid and green blockchain. The results presented in the article can inspire researchers looking for research gaps or describing the current state of knowledge in the field of the smart grid and the blockchain issues.
Zero-valent iron is a moderately reducing reagent that is both non-toxic and affordable. In the present work, iron nanoparticles were synthesized using bitter guard leaf extract (Momordica charantia L.) (BGL-Fe NP). Using leaf samples from bitter protectant extract, iron nanoparticles were synthesized with secondary metabolites such as flavonoids and polyphenols acting as capping and reducing agents. Polyphenols reduce Fe2+/Fe3+ to nanovalent iron or iron nanoparticles. Iron nanoparticles were synthesized by reducing iron chloride as a precursor with bitter protective leaf extract in an alkaline environment. The obtained BGL-Fe NPs were calcined for 4 h at various temperatures of 400 °C, 500 °C, and 600 °C. The obtained samples were coded as BGL-Fe NPs-4, BGL-Fe NPs-5, and BGL-Fe NPs-6, respectively. The synthesized BGL-Fe NPs were systematically characterized by XRD, SEM, FTIR, UV-Vis and TG-DTA analysis. The obtained BGL-Fe NPs were then used as an adsorbent to remove the aqueous solution of basic methylene blue (MB) dye. MB concentration was monitored using UV-Vis spectroscopy.
Purpose: This article explores the adoption of Artificial Intelligence (AI) in Human Resource Management (HRM) in the UAE, focusing on the critical challenges of fairness, bias, and privacy in recruitment processes. The study aims to understand how AI is transforming HR practices in the UAE, highlighting the issues of bias and privacy while examining real-world applications of AI in recruitment, employee engagement, talent management, and learning and development. Methodology: Through case study methodology, detailed insights are gathered from these companies to understand real-world applications of AI in HRM. A comparative analysis is conducted, comparing AI-driven HRM practices in UAE-based organizations with international examples to highlight global trends and best practices. Findings: The research reveals that while AI holds significant potential to streamline HR functions such as recruitment, onboarding, performance monitoring, and talent management, it also discusses challenges and strategies companies face and develop in integrating AI into their HRM processes, reflecting the broader context of AI adoption in the UAE’s HR landscape. Originality: This paper contributes to the growing body of literature on AI in HRM by focusing on the unique context of the UAE, a rapidly developing market with a highly diverse workforce. It highlights the specific challenges and opportunities faced by organizations in the UAE when implementing AI in HRM, particularly regarding fairness, bias, and data privacy.
The cultivation of sugar beet (Beta vulgaris L.) for table or horticultural purposes is largely carried out in the conventional way which is characterized by intense mechanization causing soil degradation and high labor costs. New cultivation techniques are being employed in the production of vegetables aiming to ensure improvements in environmental and economic conditions, such as the no-till farming system. Thus, the objective of this work was to evaluate the vegetable classification and physicochemical characteristics of beets from different corn planting densities. The experiment was conducted in the period from October 2018 to June 2019 in the municipality of Nova Laranjeiras (PR). Corn was used as a cover plant and the vegetable used was beet cultivar Early Wonder Tall Top. The experimental design used was in interspersed blocks in unifactorial scheme (corn densities 40, 60, 80, 100 thousand plants/ha and control) with four blocks, with plots 3.60 m long and 1.20 m wide. The parameters evaluated 60 days after planting were: commercial classification (class, group, subgroup, category), length, diameter, mass, pulp firmness, soluble solids, titratable acidity, pH and ratio, phenolic compounds. Of which the variables that were not significant at 0.5 probability were length, category (defects), firmness, subgroup (flesh color), soluble solids and phenolic compounds. It is concluded that high densities of corn as mulch for SPDH of sugar beet crop negatively affect the grade and physicochemical characterization of the products.
This study aims to determine the effect of Human Capital Management (HCM) and work ethics on the performance of life insurance agents mediated by Organizational Citizenship Behavior-Organization (OCB-O) and Organizational Citizenship Behavior-Individual (OCB-I). The data was collected from 103 respondents who had entered the category of having won the Top Agent Awards (TAA) using a survey approach with questionnaires. The population consisted of life insurance agents who had won the TAA/MDRT, a 5 Likert scale questionnaire, and analyses using the SEM-AMOS-21 program. The results prove HCM has a positive significant effect on work ethics; HCM does not have a substantial impact on OCB-O and OCB-I; Work Ethics have a considerable effect on OCB-I and OCB-O; OCB-O and OCB-I have no significant impact on performance; HCM does not have a substantial effect on performance; Work Ethics does not have a considerable impact on performance, however, if OCB-I mediates HCM it will strengthening agent Performance, likewise, Work Ethics if mediated by OCB-I, will strengthening Performance. The findings of this study are that for insurance agents to perform well, companies can treat agents as HCM and work ethics, and it is essential to pay attention to OCB-I as mediation in improving agent performance.
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