This study reviews the techniques and tools used for automatic disease identification, state-of-the-art DL models, and recent trends in DL-based image analysis, and evaluates various DL architectures, providing guidance on the suitability of these models for production environments.
The green synthesis of nanoparticles from biomass and waste with a focus on synthetic mechanisms and applications in energy production and storage, medicine, environmental remediation, and agriculture and food is reviewed.
It is suggested that dietary patterns rich in plant-based foods, with moderate inclusion of healthy animal-based foods, may enhance overall healthy aging, guiding future dietary guidelines.
This review provides a comprehensive examination of the bioactive roles of tannins, their nutritional implications, and their sensory effects, highlighting their importance in both dietary applications and overall well-being.
This work synthesize and discuss the logical and implemented approaches used to design and assemble SynComs, highlighting important principles, challenges, and trends in utilizing SynComs as alternatives to agrochemicals.
The number of illnesses, hospitalizations, and deaths in the United States caused by 7 major foodborne pathogens by using surveillance data and other sources, adjusted for underreporting and underdiagnosis is estimated by using surveillance data and other sources.
A thorough literature review was conducted, drawing from recent peer-reviewed studies and guidelines from key health authorities, and highlights the roles of specific compounds such as probiotics and prebiotics in modulating the gut microbiome, flavonoids and polyphenols in anti-inflammatory processes, omega-3 fatty acids in cardiometabolic regulation, and vitamins and minerals in supporting immune function.
The role of AI, machine learning (ML) and other emerging technologies to overcome current and future crop management challenges are reviewed, emphasizing the transformative potential of these technologies in improving agricultural productivity and tackling global food security issues.
The review highlights that state-of-the-art deep learning models have achieved impressive accuracies, with classification tasks often exceeding 95% and detection and segmentation networks demonstrating precision rates above 90% in identifying plant diseases and pest infestations.
The integration of omics technologies, genome editing and protein design with artificial intelligence (AI) promises rapid advances in the field of crop improvement that will improve global food security.
An advanced method for plant disease detection utilizing a modified depthwise convolutional neural network integrated with squeeze-and-excitation blocks and improved residual skip connections is proposed, highlighting its effectiveness and potential as a practical tool for disease identification in agricultural applications.
This review aims to provide a comprehensive overview of bioactive plant compounds by examining their extraction methods, biological and immunological activities, nutritional significance, food applications, and health benefits for humans.
Arrangements have been made with the Cambridge University Press for the production of a quarterly journal, the British Journal of Nutrition, which will be devoted to the publication of original work in all branches of nutrition.
This feature review focuses on the statistical machine learning methods and software that are democratizing GS methodology and outlines the principles of genomic-enabled prediction and discusses how statistical ML tools enhance GS efficiency with big data.
Effective detection techniques and promising solutions to the global contamination of food with Aspergillus mycotoxins are provided, which is of great significance to ensuring food security and protecting people's lives and health.
Examining the transformative potential of IoT provides valuable insights for researchers and practitioners seeking to enhance agricultural productivity, optimize resource use, and improve sustainability.
The review examines factors driving resistance, such as evolutionary pressure and excessive pesticide use, and provides a detailed analysis of mechanisms, including detoxifying enzyme overproduction and target site mutations, and provides an analysis of potential solutions.
The study compared a wide range of study subjects to investigate scientific approaches for smart irrigation, and focuses on the key components of smart irrigation, such as real-time irrigation scheduling, IoT, the importance of an internet connection, smart sensing, and energy harvesting.
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