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Plants are primary resources for oxygen and foods whose production is fundamental for our life. However, diseases and pests may interfere with plant growth and cause a significant reduction of both the quality and quantity of agriculture products. Increasing agricultural productivity is crucial for poverty reduction and food security improvements. For this reason, the 2030 Agenda for Sustainable Development gives a central role to agriculture by promoting a strong technological innovation for advancing sustainable practices at the plant level. To accomplish this aim, recently, wearable sensors and flexible electronics have been extended from humans to plants for measuring elongation, microclimate, and stressing factors that may affect the plant’s healthy growth. Unexpectedly, fiber Bragg gratings (FBGs), which are very popular in health monitoring applications ranging from civil infrastructures to the human body, are still overlooked for the agriculture sector. In this work, for the first time, plant wearables based on FBG technology are proposed for the continuous and simultaneous monitoring of plant growth and environmental parameters (i.e., temperature and humidity) in real settings. The promising results demonstrated the feasibility of FBG-based sensors to work in real situations by holding the promise to advance continuous and accurate plant health growth monitoring techniques.

A pervasive assessment of air quality in an urban or mobile scenario is paramount for personal or city-wide exposure reduction action design and implementation. The capability to deploy a high-resolution hybrid network of regulatory grade and low-cost fixed and mobile devices is a primary enabler for the development of such knowledge, both as a primary source of information and for validating high-resolution air quality predictive models. The capability of real-time and cumulative personal exposure monitoring is also considered a primary driver for exposome monitoring and future predictive medicine approaches. Leveraging on chemical sensing, machine learning, and Internet of Things (IoT) expertise, we developed an integrated architecture capable of meeting the demanding requirements of this challenging problem. A detailed account of the design, development, and validation procedures is reported here, along with the results of a two-year field validation effort.

Sommario 1. Introduzione 3. Progetti 3.1.1 Fonte di finanziamento 3.1.2 Ambiti di ricerca 3.1.3 Repository 3.1.4 Personale 3. Competenze 3.1.1 Ambiti 3.1.2 ALTRO 3.1.3 COMPETENZE VERTICALI 3.1.4 SUGGERIMENTI 5. CONCLUSIONI ALLEGATI A. PROGETTI PER AMBITI DI RIFERIMENTO B. RICOGNIZIONE CAWI (COMPUTER ASSISTED WEB INTERVIEW) C. SCHEDE INVIATE PER LA COMPILAZIONE ON-LINE

Single primer enrichment technology (SPET) is a new, robust, and customizable solution for targeted genotyping. Unlike genotyping by sequencing (GBS), and like DNA chips, SPET is a targeted genotyping technology, relying on the sequencing of a region flanking a primer. Its reliance on single primers, rather than on primer pairs, greatly simplifies panel design, and allows higher levels of multiplexing than PCR-based genotyping. Thanks to the sequencing of the regions surrounding the target SNP, SPET allows the discovery of thousands of closely linked, novel SNPs. In order to assess the potential of SPET for high-throughput genotyping in plants, a panel comprising 5k target SNPs, designed both on coding regions and introns/UTRs, was developed for tomato and eggplant. Genotyping of two panels composed of 400 tomato and 422 eggplant accessions, comprising both domesticated material and wild relatives, generated a total of 12,002 and 30,731 high confidence SNPs, respectively, which comprised both target and novel SNPs in an approximate ratio of 1:1.6, and 1:5.5 in tomato and eggplant, respectively. The vast majority of the markers was transferrable to related species that diverged up to 3.4 million years ago (

The environment has a profound influence on the organoleptic quality of tomato (Solanum lycopersicum) fruit, the extent of which depends on a well-regulated and dynamic interplay among genes, metabolites and sensorial attributes. We used a systems biology approach to elucidate the complex interacting mechanisms regulating the plasticity of sensorial traits. To investigate environmentally challenged transcriptomic and metabolomic remodeling and evaluate the organoleptic consequences of such variations we grown three tomato varieties, Heinz 1706, whose genome was sequenced as reference and two "local" ones, San Marzano and Vesuviano in two different locations of Campania region (Italy).Responses to environment were more pronounced in the two "local" genotypes, rather than in the Heinz 1706. The overall genetic composition of each genotype, acting in trans, modulated the specific response to environment. Duplicated genes and transcription factors, establishing different number of network connections by gaining or losing links, play a dominant role in shaping organoleptic profile. The fundamental role of cell wall metabolism in tuning all the quality attributes, including the sensorial perception, was also highlighted.Although similar fruit-related quality processes are activated in the same environment, different tomato genotypes follow distinct transcriptomic, metabolomic and sensorial trajectories depending on their own genetic makeup.

Four breeding piggeries and eight growing-fattening piggeries were analyzed to estimate potential environmental impacts of heavy pig production (160kg of live height at slaughtering). Life Cycle Assessment methodology was adopted in the study, considering a system from breeding phase to growing fattening phase. Environmental impacts of breeding phase and growing-fattening phase were accounted separately and then combined to obtain the impacts of heavy pig production. The functional unit was 1kg of live weight gain. Impact categories investigated were global warming (GW), acidification (AC), eutrophication (EU), abiotic depletion (AD), and photochemical ozone formation (PO). The total environmental impact of 1kg of live weight gain was 3.3kg CO2eq, 4.9E-2kg SO2eq, 3.1E-2kg PO4(3-)eq, 3.7E-3kg Sbeq, 1.7E-3kg C2H4eq for GW, AC, EU, AD, and PO respectively. Feed production was the main hotspot in all impact categories. Greenhouse gases responsible for GW were mainly CH4, N2O, and CO2. Ammonia was the most important source of AC, sharing about 90%. Nitrate and NH3 were the main emissions responsible for EU, whereas P and NOx showed minor contributions. Crude oil and natural gas consumption was the main source of AD. A large spectrum of pollutants had a significant impact on PO: they comprised CH4 from manure fermentation, CO2 caused by fossil fuel combustion in agricultural operations and industrial processes, ethane and propene emitted during oil extraction and refining, and hexane used in soybean oil extraction. The farm characteristics that best explained the results were fundamentally connected with performance indicators Farms showed a wide variability of results, meaning that there was wide margin for improving the environmental performance of either breeding or growing-fattening farms. The effectiveness of some mitigation measures was evaluated and the results that could be obtained by their introduction have been presented.