In the last decade, research on Corylus avellana has focused on improving field techniques and hazelnut quality; however, climatic change and sustainability goals call for new agronomic management strategies. Precision management technologies could help improve resource use efficiency and increase grower income, but research on remote sensing systems and especially on drone devices is still limited. Therefore, the hazelnut is still linked to production techniques far from the so-called Agriculture 4.0. Unmanned aerial vehicles platforms are becoming increasingly available to satisfy the demand for rapid real-time monitoring for orchard management at spatial, spectral, and temporal resolutions, addressing the analysis of geometric traits such as canopy volume and area and vegetation indices. The objective of this study is to define a rapid procedure to calculate geometric parameters of the canopy, such as canopy area and height, by methods using NDVI and CHM values derived from UAV images. This procedure was tested on the young Corylus avellana tree to manage a hazelnut orchard in the early years of cultivation. The study area is a hazelnut orchard (6.68 ha), located in Bernalda, Italy. The survey was conducted in a six-year-old irrigated hazelnut orchard of Tonda di Giffoni and Nocchione varieties using multispectral UAV. We determined the Projected Ground Area and, on the Corylus avellana canopy trough, the vigor index NDVI (Normalized Difference Vegetation Index) and the CHM (Canopy Height Model), which were used to define the canopy and to calculate the tree crown area. The projection of the canopy area to the ground measured with NDVI values > 0.30 and NDVI values > 0.35 and compared with CHM measurements showed a statistically significant linear regression, R2 = 0.69 and R2 = 0.70, respectively. The ultra-high-resolution imagery collected with the UAV system helped identify and define each tree crown individually from the background (bare soil and grass cover). Future developments are the construction of reliable relationships between the vigor index NDVI and the Leaf Area Index (LAI), as well as the evaluation of their spatial-temporal evolution.

Agriculture, and the related food systems, represents one of the sectors that use most of the available water resources and is responsible for a large part of the greenhouse gases increase in Earth’s atmosphere. The aim of the present research was to estimate the three dimensions of sustainability—identified by the 2030 Agenda—of the olive oil supply chain in a typical production area within Campania Region (South Italy), through the analysis of seven different olive oil systems: four certified as organic, two of which irrigated (BIO1, BIO2, BIO-IRR1, BIO-IRR2); two integrated (INT1, INT2); and one hobbyist (HOBB). The novelty of the research was the broad-spectrum sustainability evaluation of these systems, through the estimation of their water and carbon footprints, and some economic and social aspects, to classify them in sustainability classes. So, the Life Cycle Thinking approach was used to quantify the environmental impacts and the social issues, as well as the costs of production of 1 litre of packed oil produced. Environmental impacts were assessed thought the life cycle assessment methodology, with a focus on the global warming and the water footprint, using the SimaPro 9.0 software and Hoekstra methodology, respectively. The cost production evaluation was performed by the life cycle costing methodology, while a primordial approach of social sustainability estimation was built identifying the stakeholders involved and suitable impact categories. Results showed that, per litre of oil, HOBB and BIO2 were the systems that emitted less CO2 eq (0.73 and 1.50 kg, respectively); BIO-IRR1 and BIO1 were the systems with the smallest water footprint (2.97 and 3.65 m3, respectively); HOBB and BIO1 were the systems with the lowest production costs (3.11 and 3.87 €, respectively). From a social point of view, INT1 and INT2 were the most pro-social systems. Overall, BIO1 was in absolute the most sustainable system under the various aspects considered. Hence the need to spread more and more (a) organic production methods, characterized by the use of self-produced fertilizers (on-farm compost); (b) more efficient machines use, for saving fuel; (c) balanced nitrogen fertilization to lower the water footprint.