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Crocus sativus L. is a crop grown for spice production, and large amounts of residues from the flowers are produced during the process. The underutilized by-product from saffron spice production, the C. sativus tepals, was investigated as a promising raw material of natural bioactive compounds using light spectrum manipulation in controlled environments. The plants were grown under either light-emitting diodes (LEDs) or natural light (NL, greenhouse). LED experiments were performed in controlled-environment chambers (120 µmol m–2 s–1of photosynthetically active radiation, 18 °C, 16-h photoperiod). The LED treatments used were as follows: (i) red ʎ = 660 nm (62%) and blue ʎ = 450 nm (38%) (RB); and (ii) red ʎ = 660 nm (50%), green ʎ = 500–600 nm (12%), and blue ʎ = 4 50 nm (38%) (RGB). Flower growth parameters, total phenols, total flavonoids, flavonols, flavonol glycosides, and antioxidant properties were measured in harvested tepals. Floral by-products from plants grown under the two LED treatments accumulated higher amounts of antioxidant compounds compared to those of plants grown under NL. The total flavonoids content was significantly enhanced in the RGB LED treatment, while the corolla fresh weight significantly declined in the same treatments. The higher content of bioactive secondary metabolites in plants grown under both RB and RGB light environments resulted in increased antioxidant capacity measured by DPPH free-radical scavenging capacity and the ferric reducing antioxidant power method. These results indicate that manipulation of LED spectra could boost secondary metabolites and antioxidant capacity to obtain phytochemically enriched floral by-products with superior functional quality.

This deliverable describes the whole Ruritage Resource Ecosystem (RRE), which is a distributed software platform establishing data ecosystem and open standards for information management aiming at providing different services and applications to address the needs of the different identified end-users. All data are made Findable, Accessible, Interoperable, Reusable (FAIR). The RRE has been designed to be deployed even into cloud systems compliant with the Infrastructure-as-a-Model paradigm. The platform is available online at the URL https://www.ruritage-ecosystem.eu/ The RRE is conceived as the shared digital common environment of the RURITAGE project for the storage, the development and the dissemination of RURITAGE knowledge on Heritage-led regeneration. The RRE hosts and integrates all the RURITAGE digital tools that are Atlas, Decision Support System (DSS), Digital Rural Heritage Hub (DRHH), Replication Toolbox, My Cult Rural Kit, Monitoring platform. To set up, populate and develop the RRE, thus, a strong collaboration with the other tasks of WP5 as well as WP1 (RM actions and Lesson learned and ATLAS), WP2 (Digital Rural Heritage Hub and knowledge sharing methods), WP3 (Replicators Action Plans and main methodology), WP4 (monitoring platform) and WP7 (photo contest photographs, website and dissemination and communication) were established, as they identified the main potential end-users and provided the main requirements for its design and development. In particular, WP1 defined the inputs (information sources, documents types and structure, data visualisation and data management and main semantic organization); WP2 provided the functional approach (community and capacity building approach for end users); WP3 provided Replicators with the needed tools for developing and implementing the Regeneration plan; WP4 registered and made available the results of the monitoring activities; WP7 provided crowdsourcing and communication (photographs collected by photo contest open concourse and further introduction with access from the project web site). The REE is also strictly linked with WP6 since its functioning will be maintained also after the end of the project, thus allowing the establishing and scaling up of the RURITAGE brand. The deliverable also provides a synthetic overview of the tools integrated in the RRE. In particular, it reports more extensively about the RURITAGE Atlastechnical architecture that has been also developed by Polito as part of Task 5.1. The Atlas is a WEB GIS platform with a synthetic and interconnected data representation and management available at the URL https://www.ruritage-ecosystem.eu/Atlas. It includes georeferenced information, a digital archive, a digital library. On the matter of the Atlas, this deliverable is to be linked to the complementary Atlas creative mapping (Task 1.3) with its development in WP1 delivered in D 1.3. ‘RURITAGE Atlas.’ The RRE has been conceived and designed for creating a strong integration of the tools which have been included. Although the tools have diverse finalisations and diverse developers, they re-use data and information developed by the project and made available via RRE. The RRE is designed, in fact, as the integrated digital environment for enabling functionalities of the RURITAGE project. It is conceived within RURITAGE as the main platform where to collect, store, analyse, show, select and use the data collected and analysed and usable information generated within the project for the scope of heritageled regeneration in rural territories. By doing so RRE enables and makes available for all kind of end users the knowledge generated by the research, its methodologies and achievements. RRE creates the shared digital environment for developing, addressing and exploiting the project approach and methodologies among research partners; moreover, it is the digital environment whereother final users can interact for easily grasping understandings on RURITAGE rural areas and actioning their regeneration processes thanks to the data and tools made available. For this purpose, it allows directly access specific and crosscutting functions for visualizing effective systems of data description, exchanging knowledge, supporting decisions, surveying assessing, monitoring and finally replicating the RURITAGE methodology with a proper knowledge. RRE, firstly, has been developed in strong collaboration with all other partners developers of digital tools that have been integrated in the platform. The developer partners are: ALMENDE (DSS), TECNALIA (Replication Toolbox), Plymouth (My Cult Rural Kit), Cartif (Monitoring platform), while the Atlas and Digital Rural Heritage Hub (DRHH) have been developed by POLITO. The guidelines and graphical improvements of RRE to provide a user-friendlyaccess to the RURITAGE digital environment with its functions are under development (Task 5.5) by UNESCO and will be delivered at Month 48 (D. 5.5). All these partners are the contributors of this deliverable. RRE, secondly, with its shared digital environment has capillary supported the project development through its diverse development in its WPs since its beginnings and will continue to provide this support through the maintenance. Beyond the technical and the facilitator partners, the main users of the RRE are the Replicators (Rs) and also the Additional Replicators (ARs) and the Additional & Digital Replicators (A&Rs) as well as the Role Models (RMs). Facilitator partners, Rs, ARs, A&DRs, RMs are the main test-bed for this platform and its functions to be made available to all kind of end users. During the development, we adopted the Agile methodology [2]. Agile is an approach to the project management which helps to respond to the unpredictability of building software through incremental, iterative work cadences, known as sprints. Agile development methodology provides the opportunity to assess the direction of a project throughout the development lifecycle. It does it through an iterative cycle to build and test followed by an assessment by the user/business until they are satisfied with the product. Thus, by focusing on the repetition of abbreviated work cycles as well as the functional product they yield; agile methodology could be described as iterative and incremental. Thus, following this methodology, software components of the RRE are periodically updated for bug fixing and/or new feature release. For this reason, T5.1 will guarantee the maintenance of the whole RRE, by ensuring consistence and usability of the platform across the whole duration of the project. A quality check on the integrity of the data will be performed, also considering that new data will be continuously generated and processed by the various tools of the ecosystem. The maintenance will include stability and resiliency checks performed on the distributed software infrastructure. The deliverable is organized as follows. Chapter 4 describes the RRE distributed software infrastructure as a whole. Chapter 5 introduces the main ICT enabling technologies i) to develop the RRE platform, ii) to store heterogeneous information into flexible databases and iii) to share information among the actors in the systems by exploiting standard data-formats. It is worth noting that such technologies are agnostic w.r.t. the specific dataset and information to be post-processed, stored and exchanged. Chapters 6 to 11 introduce the main interoperable software components developed for the different tools in the RRE. Finally, Chapter 12 provides the concluding remarks.

Predictive maintenance aims at proactively assessing the current condition of assets and performing maintenance activities if and when needed to preserve them in the optimal operational condition. This in turn may lead to a reduction of unexpected breakdowns and production stoppages as well as maintenance costs, ultimately resulting in reduced production costs. Empowered by recent advances in the fields of information and communication technologies and artificial intelligence, this chapter attempts to define the main operational blocks for predictive maintenance, building upon existing standards discusses and key data-driven methodologies for predictive maintenance. In addition, technical information related to potential data models for storing and communicating key information are provided, finally closing the chapter with different deployment strategies for predictive analytics as well as identifying open issues.

Microgreens are edible seedlings of vegetables and flowers species which are currently considered among the five most profitable crops globally. Light-emitting diodes (LEDs) have shown great potential for plant growth, development, and synthesis of health-promoting phytochemicals with a more flexible and feasible spectral manipulation for microgreen production in indoor farms. However, research on LED lighting spectral manipulation specific to microgreen production, has shown high variability in how these edible seedlings behave regarding their light environmental conditions. Hence, developing species-specific LED light recipes for enhancement of growth and valuable functional compounds is fundamental to improve their production system. In this study, various irradiance levels and wavelengths of light spectrum produced by LEDs were investigated for their effect on growth, yield, and nutritional quality in four vegetables (chicory, green mizuna, china rose radish, and alfalfa) and two flowers (french marigold and celosia) of microgreens species. Microgreens were grown in a controlled environment using sole-source light with different photosynthetic photon flux density (110, 220, 340 µmol m−2 s−1) and two different spectra (RB: 65% red, 35% blue; RGB: 47% red, 19% green, 34% blue). At harvest, the lowest level of photosynthetically active photon flux (110 µmol m−2 s−1) reduced growth and decreased the phenolic contents in almost all species. The inclusion of green wavelengths under the highest intensity showed positive effects on phenolic accumulation. Total carotenoid content and antioxidant capacity were in general enhanced by the middle intensity, regardless of spectral combination. Thus, this study indicates that the inclusion of green light at an irradiance level of 340 µmol m−2 s−1 in the RB light environment promotes the growth (dry weight biomass) and the accumulation of bioactive phytochemicals in the majority of the microgreen species tested.