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.
The green synthesis of nanoparticles from biomass and waste is reviewed with a focus on synthetic mechanisms and applications in energy production and storage, medicine, environmental remediation, and agriculture and food.
A pipeline for fine-tuning and RAG is proposed, and the tradeoffs of both are presented for multiple popular LLMs, including Llama2-13B, GPT-3.5, and GPT-4.
This review aims to highlight the main groups of microbial enzymes found in soil, their role in the global nutrient cycles of carbon, nitrogen, phosphorus, sulfur, carbon sequestration, and the influence of intensive agriculture on microbial enzymatic activity, and the variations in enzyme activity across different climate zones and soil ecosystems.
Genomic studies that have revealed genes involved in nutrient uptake and symbiosis development are reviewed, adaptations that are fundamental to the evolution of mycorrhizal lifestyles are discussed, and the ecosystem services provided by mycorrhizal networks are evaluated.
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.
Phages and phage-derived lytic proteins can be considered potential antimicrobials in the traditional farm-to-fork context, which include phage-based mixtures and commercially available phage products.
The association of the novel DI-GM with markers of gut microbiota diversity demonstrates the potential utility of this index for gut health-related studies.
The empirical results unequivocally establish the superior performance of XAI-CROP, an innovative algorithm that harnesses eXplainable artificial intelligence (XAI) principles to empower farmers with comprehensible insights into the recommendation process, surpassing the opaque nature of conventional machine learning models.
This study compiled and analysed the fragmented database on edible insects and identified potential drivers that elucidate insect consumption, globally, focusing on promoting a sustainable food system.
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.
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.
The results reveal that MiT-B0 demonstrates balanced but slightly overfitting behavior, MiT-B3 adapts rapidly with consistent training and validation performance, and MiT-B5 offers efficient learning with occasional fluctuations, providing robust performance.
Agriculture is rapidly transforming from conventional to digital farming, offering global solutions, efficient resource utilization, and minimized input costs while fostering farmer livelihoods and economic growth.
In view of the growing concern, it is necessary to develop new herbicides with greater selectivity or bio-based herbicide that can degrade after successful control of the intended weed population and minimize or eliminate the environmental hazards.
The barriers encountered in nanoparticle delivery to plants are highlighted, emphasizing the need for innovative approaches to optimize transport efficiency and the reliance on multiple detection methods for data validation is emphasized to enhance the reliability of the research findings.
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