Investment in technological research is imperative to stimulate the development of sustainable solutions for the agricultural sector. Advances in Internet of Things, sensors and sensor networks, robotics, artificial intelligence, big data, cloud computing, etc. foster the transition towards the Agriculture 4.0 era. This fourth revolution is currently seen as a possible solution for improving agricultural growth, ensuring the future needs of the global population in a fair, resilient and sustainable way. In this context, this article aims at characterising the current Agriculture 4.0 landscape. Emerging trends were compiled using a semi-automated process by analysing relevant scientific publications published in the past ten years. Subsequently, a literature review focusing these trends was conducted, with a particular emphasis on their applications in real environments. From the results of the study, some challenges are discussed, as well as opportunities for future research. Finally, a high-level cloud-based IoT architecture is presented, serving as foundation for designing future smart agricultural systems. It is expected that this work will positively impact the research around Agriculture 4.0 systems, providing a clear characterisation of the concept along with guidelines to assist the actors in a successful transition towards the digitalisation of the sector.

At a whole plant level the effects of drought is usually perceived as a decrease in growth and photosynthetic carbon assimilation. That is why this review is focused mainly on recent information about the effects of drought on plant growth, water relations and photosynthesis, as well as mechanisms of adaptation. It is shown that plants have evolved a great number of adaptive mechanisms that allow the biochemical systems to cope with increased water deficit. The literature analyzed in this review shows the complexity of tolerance to water deficit and supports the statements of many authors that the flexibility of cell metabolism and its fast acclimation to changes in environmental conditions is a first essential step in stress avoidance.

Progress in agricultural productivity and sustainability hinges on strategic investments in technological research. Evolving technologies such as the Internet of Things, sensors, robotics, Artificial Intelligence, Machine Learning, Big Data, and Cloud Computing are propelling the agricultural sector towards the transformative Agriculture 4.0 paradigm. The present systematic literature review employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to explore the usage of Machine Learning in agriculture. The study investigates the foremost applications of Machine Learning, including crop, water, soil, and animal management, revealing its important role in revolutionising traditional agricultural practices. Furthermore, it assesses the substantial impacts and outcomes of Machine Learning adoption and highlights some challenges associated with its integration in agricultural systems. This review not only provides valuable insights into the current landscape of Machine Learning applications in agriculture, but it also outlines promising directions for future research and innovation in this rapidly evolving field.

Colour is one of the most relevant organoleptic attributes that directly affects consumers’ acceptance and food selection. However, as food colouring pigments are generally unstable and become modified during processing, in order to maintain or restore product colour uniformity, colourants are added to food products around the world. In this context, although they are still widely used, synthetic food colorants, due to their potential hazards, are being replaced by those obtained from natural origins. Indeed, numerous side effects and toxicities, at both the medium and long-terms—namely allergic reactions, and behavioral and neurocognitive effects—have been related to the use of synthetic colourants, whereas their naturally-derived counterparts seem to provide a somewhat high-quality and effective contribution as a health promoter. In order to further understand the implications of the use of synthetic and naturally derived food colourants, this review aims to provide a synoptical approach to the chemical characteristics, properties, uses and side effects on health of those which are currently allowed and applied during food processing.