Agriculture encompasses the study, practice, and discipline of plant cultivation. Agriculture has an extensive history dating back thousands of years. Depending on climate and terrain, it began independently in various locations on the planet. In comparison to what could be sustained by foraging and gathering, agriculture has the potential to significantly increase the human population. Throughout the twenty-first century, precision farming (PF) has increased the agricultural output. precision agriculture (PA) is a technology-enabled method of agriculture that assesses, monitors, and evaluates the needs of specific fields and commodities. The primary objective of this farming method, as opposed to conventional farming, is to increase crop yields and profitability through the precise application of inputs. This work describes in depth the development and function of artificial intelligence (AI) and the internet of things (IoT) in contemporary agriculture. Modern day-to-day applications rely extensively on AI and the IoT. Modern agriculture leverages AI and IoT for technological advancement. This improves the accuracy and profitability of modern agriculture. The use of AI and IoT in modern smart precision agricultural applications is highlighted in this work and the method proposed incorporates specific steps in PF and demonstrates superior performance compared to existing classification methods. It achieves a remarkable accuracy of 98.65%, precision of 98.32%, and recall rate of 97.65% while retaining competitive execution time of 0.23 s, when analysing PF using the FAOSTAT benchmark dataset. Additionally, crucial equipment and methods used in PF are described and the vital advantages and real-time tools utilised in PA are covered in detail.
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http://dx.doi.org/10.1515/biol-2022-0713 | DOI Listing |
Plant Dis
January 2025
Kashi, Xinjiang, China, China;
Fig (Ficus carica L.) holds economic significance in Atushi, Xinjiang, but as fig cultivation expands, disease prevalence has risen. In July 2024, approximately 22% of harvested fig (cv.
View Article and Find Full Text PDFMicrobiol Spectr
January 2025
College of Animal Science and Technology, Jilin Agricultural University, Changchun, China.
The rumen microbiota plays a vital role in the nutrient metabolism affecting the growth of velvet antler. However, the fermentation patterns and dynamics of the rumen microbiota across growth stages of velvet antler remain largely unexplored. Here, we employed an fermentation approach to assess fermentation parameters and microbial composition in the rumen liquid of sika deer during the early growth (EG), metaphase growth (MG), and fast growth (FG) phases .
View Article and Find Full Text PDFmSystems
January 2025
Key Laboratory of Pig Genetic Resources Evaluation and Utilization (Nanjing), Ministry of Agriculture and Rural Affairs, Institute of Swine Science, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China.
Unlabelled: Although metagenomic investigations into microbial fiber-degrading capabilities are currently prevalent, there is a notable gap in research concerning the regulatory mechanisms underpinning host-microbiota interactions that confer tolerance to high-fiber diets in pigs. In this study, 28 Meishan (MS) and 28 Large White (LW) pigs were subjected to feeding experiments involving various fiber levels. Subsequently, multi-omics was employed to investigate the influence of host-microbiota interactions on the fiber degradation of pigs.
View Article and Find Full Text PDFmSphere
January 2025
School of Medicine, Southern University of Science and Technology, Shenzhen, China.
The universal bacterial second messenger bis-(3'-5')-cyclic dimeric guanosine monophosphate (c-di-GMP) plays critical roles in regulating a variety of bacterial functions such as biofilm formation and virulence. The metabolism of c-di-GMP is inversely controlled by diguanylate cyclases (DGCs) and phosphodiesterases (PDEs). Recently, increasing studies suggested that the protein-protein interactions between DGCs/PDEs and their partners appear to be a common way to achieve specific regulation.
View Article and Find Full Text PDFEur Phys J C Part Fields
January 2025
A measurement of the dijet production cross section is reported based on proton-proton collision data collected in 2016 at by the CMS experiment at the CERN LHC, corresponding to an integrated luminosity of up to 36.3 . Jets are reconstructed with the anti- algorithm for distance parameters of and 0.
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