AgriFoodTech start-ups are coming to be seen as relevant players in the debate around and reality of the transformation of food systems, especially in view of emerging or already-established novel technologies (such as Artificial Intelligence, Sensors, Precision Fermentation, Robotics, Nanotechnologies, Genomics) that constitute Agriculture 4.0 and Food 4.0. However, so far, there have only been limited studies of this phenomena, which are scattered across disciplines, with no comprehensive overview of the state of the art and outlook for future research.
The challenges faced by agricultural innovation systems (A.I.S.) are complex to solve, however, the authors consider that understanding the processes of innovation and development (R&D), sustainability, use of information and communication technologies, training, and outreach, as the focus of discussion in this review, have great potential to close the gaps in the system; as well as exploring strategies, projects and best practices that dynamize the operation of the system. The objective of this article is to review the literature on A.I.S.A.
La Gestión de Tecnología e Innovación (GTI) juega un papel crucial en el avance del sector agropecuario de una nación, ya que promueve el mejoramiento de la productividad y competitividad en todas las regiones, consolidándose como una herramienta fundamental en su desarrollo. El propósito central de este estudio es proponer una nueva perspectiva en la gestión de la tecnología y la innovación para las Unidades de Producción Agropecuaria (UPA) de la provincia de Cotopaxi, presentando así una alternativa innovadora que busca resolver los retos existentes y futuros en esta materia.
La innovación se implementa en un entorno de objetivos de desarrollo productivo a través de un sistema que incluye incentivos, tecnología y redes público-privadas. El objetivo principal de este estudio es analizar la innovación en los agronegocios de El Oro y determinar cómo incide en la competitividad del sector agropecuario. La metodología utilizada en este estudio es descriptiva y documental, con carácter científico, además está enmarcada bajo el enfoque cuantitativo.
For most development organisations and funders, innovation remains a sprawling collection of activities, often energetic, but largely uncoordinated. To a dregree, this has also been the case for Iceland's development co-operation. Iceland, a comparatively small but energetic player in the international development co-operation system, provided the equivalent of 0.28% (roughly 67 million Euro) of it 2021 gross national income towards Official Development Assistance.
Despite the concept's widespread popularity, the terminology surrounding missions can come across as convoluted. This is understandable, given that the term - which denotes ambitious, time bound, cross-sectoral and measurable policy objectives to address grand societal challenges such as climate change mitigation, biosphere restoration or tackling health inequities - has proven to be both deceptively intricate and remarkably versatile.
Familiar mixed dairy sheep farm is the most widespread system in the Mediterranean basin, in Latin America and in developing countries (85%). There is a strong lack of technological adoption in packages of feeding and land use in small-scale farms. To increase competitiveness, it would be of great interest to deepen the knowledge of how innovation was selected, adopted, and spread. The objective of this research was to select strategic feeding and land use technologies in familiar mixed dairy sheep systems and later assess dairy sheep farms in Spain.
The potential beneficial and harmful social impacts generated by the introduction of novel technologies, in general, and those concerning nutrient recovery and the improvement of nutrient efficiency in agriculture, in particular, have received little attention, as shown in the literature. This study investigated the current social impacts of agricultural practices in Belgium, Germany and Spain, and the potential social impacts of novel technologies introduced in agriculture to reduce nutrient losses.
The digital transformation in agriculture introduces new challenges in terms of data, knowledge and technology adoption due to critical interoperability issues, and also challenges regarding the identification of the most suitable data sources to be exploited and the information models that must be used.
The determination of bunch features that are relevant for bunch weight estimation is an important step in automatic vineyard yield estimation using image analysis. The conversion of 2D image features into mass can be highly dependent on grapevine cultivar, as the bunch morphology varies greatly. This paper aims to explore the relationships between bunch weight and bunch features obtained from image analysis considering a multicultivar approach.