The use of bioproducts, economically viable, are of extreme importance in the protection and stimulation of germination in vegetable crops. This work evaluated the effect of the microorganisms Azospirillum brasiliense, Bacillus sub-tilis, Trichoderma harzianum and the commercial seed treatment product (Fipronil + Pilaclostrobin and Methyl Thiophanate) on seeds and seedlings of lettuce (Lactuca sativa), carrot (Daucus carota) and tomato (Solanum lycopersicum). The seeds were inoculated before being submitted to the germination test. The chemical treatment proved ineffective in protecting the seed of all crops and stimulating germination. T. harzianum increased the germination index of lettuce seeds, had better values in root system size in tomato crop and stimulated radicle emission in carrot. B. subtilis stood out in dry matter accumulation in tomato crop. The microorganisms B. subtilis and T. harzianum present potential for vegetable seed treatment.

With the development and progress of the era, digital construction has become an important topic for enterprise development in the new era. Practice has shown that by actively carrying out corresponding digital construction work, enterprises can more comprehensively and systematically analyze the industry development and market prospects, which helps to promote the reasonable adjustment
of internal and external management work modes and the improvement of management efficiency, and has a positive guiding role for the healthy development cycle of enterprises. In this article, the author combines a large amount of research cases to conduct research on the effect of digital construction on enterprise development in the new era and proposes corresponding optimization measures, hoping to further promote the full play of information technology value, in order to safeguard the development of enterprises.

Land suitability analysis using geographic information systems (GIS) is one of the most widely used method today. In this type of studies, GIS and geo-spatial statistical tools are used to evaluate land units and present the results in suitability maps. The present work aims to characterize the suitability of soils in the province of Catamarca for pecan nut production according to the variables: rockiness, salinity, risk of water-logging, depth, texture and drainage described in the Soil Map of Argentina at a scale of 1:500,000 published by the National Institute of Agricultural Technology. A classification of the suitability of the soil cartographic units was made according to crop requirements, applying the methodology proposed by FAO. The standardization of variables made by omega score and the calculation of the spatial classification score were carried out as a result of the synthesis of the spatial distribution of soil suitability. The applied methodology allowed obtaining the soil suitability map resulting in a total of 60,662 km² suitable for pecan nut production, which accounts for 59.8% of the total area of the province.

This study conducted a systematic literature review on current and emerging trends in the use of artificial intelligence (AI) for community surveillance, using the PRISMA methodology and the paifal.ai tool for the selection and analysis of relevant sources. Five main thematic areas were identified: AI technologies, specific applications, societal impact, regulations and public policy. Our findings revealed exponential growth in the development and implementation of AI technologies, with applications ranging from public safety to environmental monitoring. However, this advancement poses significant challenges related to privacy, ethics and governance, driving a debate on the need for appropriate regulations. The analysis also highlighted the disparity in the adoption of these technologies among different communities, suggesting a need for inclusive policies to ensure equitable benefits. This study contributes to the understanding of the current scenario of AI in community policing, providing a solid foundation for future research and developments in the field.

Targeted Poverty Alleviation refers to the targeted funding work completed in the process of higher education development. However, at present, in the process of implementing the requirements of Targeted Poverty Alleviation in China's universities, some students' families are difficult to complete identification, and there are also some problems in the information management of the funders, which has seriously affected the funding for students with financial difficulties in their families during the period of higher education in China. With the rapid development and progress of Big data technology, through the establishment of a sound information technology system, we must help students actively change the funding model in the future and greatly improve the funding, which is of great significance to the development of university funding supervision and management.