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Plant gene transfer achieved in the early ‘80s paved the way for the exploitation of the potential of gene engineering to add novel agronomic traits and/or to design plants as factories for high added value molecules. For this latter area of research, the term "Molecular Farming" was coined in reference to agricultural applications in that major crops like maize and tobacco were originally used basically for pharma applications. The concept of the “green biofactory” implies different advantages over the typical cell factories based on animal cell or microbial cultures already when considering the investment and managing costs of fermenters. Although yield, stability, and quality of the molecules may vary among different heterologous systems and plants are competitive on a case-to-case basis, still the “plant factory” attracts scientists and technologists for the challenging features of low production cost, product safety and easy scale up. Once engineered, a plant is among the cheapest and easiest eukaryotic system to be bred with simple know-how, using nutrients, water and light. Molecules that are currently being produced in plants vary from industrial and pharmaceutical proteins, including medical diagnostics proteins and vaccine antigens, to nutritional supplements such as vitamins, carbohydrates and biopolymers. Convergence among disciplines as distant as plant physiology and pharmacology and, more recently, as omic sciences, bioinformatics and nanotechnology, increases the options of research on the plant cell factory. “Farming for Pharming” biologics and small-molecule medicines is a challenging area of plant biotechnology that may break the limits of current standard production technologies. The recent success on Ebola fighting with plant-made antibodies put a spotlight on the enormous potential of next generation herbal medicines made especially in the name of the guiding principle of reduction of costs, hence reduction of disparities of health rights and as a tool to guarantee adequate health protection in developing countries.Plant gene transfer achieved in the early ‘80s paved the way for the exploitation of the potential of gene engineering to add novel agronomic traits and/or to design plants as factories for high added value molecules. For this latter area of research, the term "Molecular Farming" was coined in reference to agricultural applications in that major crops like maize and tobacco were originally used basically for pharma applications. The concept of the “green biofactory” implies different advantages over the typical cell factories based on animal cell or microbial cultures already when considering the investment and managing costs of fermenters. Although yield, stability, and quality of the molecules may vary among different heterologous systems and plants are competitive on a case-to-case basis, still the “plant factory” attracts scientists and technologists for the challenging features of low production cost, product safety and easy scale up. Once engineered, a plant is among the cheapest and easiest eukaryotic system to be bred with simple know-how, using nutrients, water and light. Molecules that are currently being produced in plants vary from industrial and pharmaceutical proteins, including medical diagnostics proteins and vaccine antigens, to nutritional supplements such as vitamins, carbohydrates and biopolymers. Convergence among disciplines as distant as plant physiology and pharmacology and, more recently, as omic sciences, bioinformatics and nanotechnology, increases the options of research on the plant cell factory. “Farming for Pharming” biologics and small-molecule medicines is a challenging area of plant biotechnology that may break the limits of current standard production technologies. The recent success on Ebola fighting with plant-made antibodies put a spotlight on the enormous potential of next generation herbal medicines made especially in the name of the guiding principle of reduction of costs, hence reduction of disparities of health rights and as a tool to guarantee adequate health protection in developing countries.

plant molecular farming --- Metabolic Engineering --- transient expression --- Genetic Engineering --- recombinant protein --- biopharmaceuticals --- Plant factory --- Biobetter

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Agricultural techniques have always evolved by embracing the industry changes that took part according to the human technological evolution. Nowadays, Industry 4.0 represents the fourth industrial revolution leading to Agriculture 4.0. This last evolution is mainly defined by the fusion of many emerging technologies such as the Internet of things, advanced electronics and robotics, big data, and artificial intelligence. The new Agriculture 4.0 ecosystem is thus characterized by real-time farm management, a high degree of automation, and data-driven intelligent decision-making. The emerging smart plant factory concept is the real world realization of this new agricultural paradigm. This work proposes a new automation and intelligence platform that is defined as a basic hardware pattern and software structure upon which information and communication systems that serve as a base for various services are built. This platform has the objective of accommodating most functions needed by these state of the art farms. More precisely, the main target is to organize the communications and roles of each implemented module. To do so, a proof of concept of the monitoring hardware and a minimum viable product of the control software are implemented. Moreover, this project was tested with real world cultivation experiments thanks to a custom made cultivation tray. By having a multisectoral approach and by studying the modularity of the systems, the conducted development were shown to improve upon the currently available solutions regarding the technical documentation, edge and cloud computing compatibility, and hardware and software flexibility.

Hydroponics --- Vertical Farming --- Controlled Environment Agriculture --- Smart Plant Factory --- Electronics --- Raspberry Pi --- Agriculture 4.0 --- Indoor Growing System --- Automation And Intelligence Platform --- Ingénierie, informatique & technologie > Sciences informatiques

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In recent years, the industrial environment has been changing radically due to the introduction of concepts and technologies based on the fourth industrial revolution, also known as Industry 4.0. After the introduction of Industry 4.0 in large enterprises, SMEs have moved into the focus, as they are the backbone of many economies. Small organizations are increasingly proactive in improving their operational processes, which is a good starting point for introducing the new concepts of Industry 4.0. The readiness of SME-adapted Industry 4.0 concepts and the organizational capability of SMEs to meet this challenge exist only in some areas. This reveals the need for further research and action plans for preparing SMEs in a technical and organizational direction. Therefore, special research and investigations are needed for the implementation of Industry 4.0 technologies and concepts in SMEs. SMEs will only achieve Industry 4.0 by following SME-customized implementation strategies and approaches and realizing SME-adapted concepts and technological solutions. Thus, this Special Issue represents a collection of theoretical models as well as practical case studies related to the introduction of Industry 4.0 concepts in small- and medium-sized enterprises.

History of engineering & technology --- latent semantic analysis --- virtual quality management --- concept investigation --- concept disambiguation --- knowledge discovery --- sustainable methodologies --- small and medium sized enterprises --- material handling systems --- simulation --- ARENA®, time study --- overall equipment effectiveness --- manufacturing performance --- Industry 4.0 --- manufacturing sustainability --- manufacturing process model --- business process management --- hierarchical clustering --- similarity --- BPMN --- human factors --- cyber-physical systems --- cyber-physical production systems --- anthropocentric design --- Operator 4.0 --- human–machine interaction --- energy efficient operation --- manufacturing system --- stochastic event --- digital twin --- Max-plus Algebra --- MATLAB-Simulink --- advanced manufacturing --- industry 4.0 --- SME --- technology adoption model --- assembly supply chain --- sustainability --- complexity indicators --- testing criteria --- SMEs --- e-business modelling --- LSP Lifecycle Model --- Quality Function Deployment --- Best-Worst Method --- Internet of Things --- India --- awareness --- small and medium-sized enterprises --- assessment model --- collaborative robotics --- physical ergonomics --- human-robot collaboration --- human-centered design --- assembly --- small and medium sized enterprise --- positive complexity --- negative complexity --- infeasible configurations --- product platform --- customer’s perception --- assessment --- field study --- smart manufacturing --- cloud platform --- artificial intelligence --- machine learning --- deep learning --- smart logistics --- logistics 4.0 --- smart technologies --- sustainable agriculture --- plant factory --- latent semantic analysis --- virtual quality management --- concept investigation --- concept disambiguation --- knowledge discovery --- sustainable methodologies --- small and medium sized enterprises --- material handling systems --- simulation --- ARENA®, time study --- overall equipment effectiveness --- manufacturing performance --- Industry 4.0 --- manufacturing sustainability --- manufacturing process model --- business process management --- hierarchical clustering --- similarity --- BPMN --- human factors --- cyber-physical systems --- cyber-physical production systems --- anthropocentric design --- Operator 4.0 --- human–machine interaction --- energy efficient operation --- manufacturing system --- stochastic event --- digital twin --- Max-plus Algebra --- MATLAB-Simulink --- advanced manufacturing --- industry 4.0 --- SME --- technology adoption model --- assembly supply chain --- sustainability --- complexity indicators --- testing criteria --- SMEs --- e-business modelling --- LSP Lifecycle Model --- Quality Function Deployment --- Best-Worst Method --- Internet of Things --- India --- awareness --- small and medium-sized enterprises --- assessment model --- collaborative robotics --- physical ergonomics --- human-robot collaboration --- human-centered design --- assembly --- small and medium sized enterprise --- positive complexity --- negative complexity --- infeasible configurations --- product platform --- customer’s perception --- assessment --- field study --- smart manufacturing --- cloud platform --- artificial intelligence --- machine learning --- deep learning --- smart logistics --- logistics 4.0 --- smart technologies --- sustainable agriculture --- plant factory

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• Reference Manager
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In recent years, the industrial environment has been changing radically due to the introduction of concepts and technologies based on the fourth industrial revolution, also known as Industry 4.0. After the introduction of Industry 4.0 in large enterprises, SMEs have moved into the focus, as they are the backbone of many economies. Small organizations are increasingly proactive in improving their operational processes, which is a good starting point for introducing the new concepts of Industry 4.0. The readiness of SME-adapted Industry 4.0 concepts and the organizational capability of SMEs to meet this challenge exist only in some areas. This reveals the need for further research and action plans for preparing SMEs in a technical and organizational direction. Therefore, special research and investigations are needed for the implementation of Industry 4.0 technologies and concepts in SMEs. SMEs will only achieve Industry 4.0 by following SME-customized implementation strategies and approaches and realizing SME-adapted concepts and technological solutions. Thus, this Special Issue represents a collection of theoretical models as well as practical case studies related to the introduction of Industry 4.0 concepts in small- and medium-sized enterprises.

latent semantic analysis --- virtual quality management --- concept investigation --- concept disambiguation --- knowledge discovery --- sustainable methodologies --- small and medium sized enterprises --- material handling systems --- simulation --- ARENA®, time study --- overall equipment effectiveness --- manufacturing performance --- Industry 4.0 --- manufacturing sustainability --- manufacturing process model --- business process management --- hierarchical clustering --- similarity --- BPMN --- human factors --- cyber-physical systems --- cyber-physical production systems --- anthropocentric design --- Operator 4.0 --- human–machine interaction --- energy efficient operation --- manufacturing system --- stochastic event --- digital twin --- Max-plus Algebra --- MATLAB-Simulink --- advanced manufacturing --- industry 4.0 --- SME --- technology adoption model --- assembly supply chain --- sustainability --- complexity indicators --- testing criteria --- SMEs --- e-business modelling --- LSP Lifecycle Model --- Quality Function Deployment --- Best-Worst Method --- Internet of Things --- India --- awareness --- small and medium-sized enterprises --- assessment model --- collaborative robotics --- physical ergonomics --- human-robot collaboration --- human-centered design --- assembly --- small and medium sized enterprise --- positive complexity --- negative complexity --- infeasible configurations --- product platform --- customer’s perception --- assessment --- field study --- smart manufacturing --- cloud platform --- artificial intelligence --- machine learning --- deep learning --- smart logistics --- logistics 4.0 --- smart technologies --- sustainable agriculture --- plant factory