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The Council Agricultural Research and Economics, Research Centre for Agriculture and Environments of Florence, (CREA-AA), National Soil Archive (ARCAN) is an important resource for current and future soil research. ARCAN holds 32,612 archived specimens, collected from 13,156 sites across Italy. The ARCAN is also very relevant from a historical and agroecological point of view, collecting soil samples from surface and subsurface horizons, in some cases taken before Chernobyl and almost all after Chernobyl (1986-2021). In particular, 7,000 agricultural samples are representative of all regions of Italy, collected in the same year (1994), with the same standard sampling and analysis protocol. In this work we show up a new database management system (DATA-RAS) to achieve Vis-Nir spectroscopy data and environment radioactivity data on ARCAN soil samples. Combined use of Vis-Nir and gamma ray spectroscopy to predict soil properties offers a task to populate the database. After that it is possible to obtain a digital soil map of artificial or natural radioactivity of Italian soils. The main purpose of this work is show up an Entity Relationship model of DATA-RAS, that represents other than a database a Smart Data Exchange a system to better managing ARCAN and rapidly exchanging information with other national and European partners. The ultimate goal is to use the most advanced information and communication technologies to create an innovative platform that digitally manages open data with 3D methods and augmented and virtual reality techniques (AR and VR). The DATA-RAS platform will be integrated with scientific information systems and a natural language interface for knowledge communication.

Information and Communication Technologies (ICT) play a key role for improving the implementation of sustainable forest management at local, regional, and global level. The ICT potential to easily exploit a wider and more up-to-date set of information on the economic, environmental, and so- cial value of forests is of relevant help for the daily work of technicians, land owners, and companies in boosting the efficiency and effectiveness of forest management. The concept of “Precision Forestry” (PF) was developed from the early 2000s, as a branch of precision farming or precision agriculture. PF includes the use of ICT, remote and proximal sensing technologies, and other devices to coordinate and control several processes on a spatial scale (“Precision”) for monitoring, planning, and managing forest resources (“Forestry”). The aim of this monography is to collect and describe some of the most important PF experiences applied or potential- ly useful for the Italian forestry sector. It may represent a reference guide for the stakeholders, such as forest owners, professional technicians, public administrators, and policy makers. The book includes eleven chapters reviewing the main tech- nological tools available in the Italian context and the most recent advances of ICT in forestry, also focusing on the strengths and weaknesses of their practical implementation. The opportunities and challenges of implementing PF meth- ods, practices and technologies are also discussed. In the first two chapters the precision forestry concept and its historical development are introduced. In the third chap- ter some basic elements of ICT, GIS, Global Navigation Satellite Systems (GNSS), remote/proximal sensing, and related technologies which are essential for a better compre- hension of PF applications are recalled. In chapter 4 recent advances in large scale forest inventories with a focus on mapping and on the spatial estimation of forest variables integrating field surveys and multisource re- motely sensed data are described. Current advancements in the acquisition of field information including Terrestrial La- ser Scanning (TLS), new digital dendrometers, tree-talkers, terrestrial cameras, and APP for portable devices such as smartphones or tablets for dendrometric tree measures and new citizen science applications to support quantitative and qualitative spatial estimation of forest variables over large areas (i.e., forest health, fuel types) are also presented. The chapter ends up with the description of some experiences in the implementation of Forest Information Systems in Italy to provide a simple open-access to such new generation of spatial forest information. In chapter 5 PF tools, instruments, and technologies to sup- port sustainable forest management are illustrated. APPs developed to acquire field plots data to simulate manage- ment operations, the application of photogrammetric tech- nologies from Unmanned Aerial Vehicles and TLS data for monitoring with high-spatial scale forest monitoring and for acquiring indicators at single tree level are presented. A de- tailed description of new user-friendly tools for forest roadplanning, design and construction, as well as forest opera- tion planning is also included. Precision forest tree farming (with particular reference to poplar cultivation), useful to promote and increase the prof- itability and sustainability of forest plantations within the Italian context is described in chapter 6. The innovation and enhancement within the supply chain of wood plantations (from planting to harvesting, including monitoring and identification of stress) by soil proximal sensing techniques, Early Warning Systems, and specific software are highlight- ed. Considering the even higher market demands, promoted by the large-scale planting programs for climate changes mit- igation and the demands for propagation material for en- vironmental recovery, innovative techniques and methods supported by ICT in the forest nursery sector are described in chapter 7. In chapter 8 available technologies related to precision har- vesting are analyzed and described taking into consideration the wood chain efficiency, by means of improved commu- nications between the owner/buyer and operators as well as among machineries used in forest operations, health and safety of forest operators, environmental impacts mitigation and recovery, and operators training. Advanced communi- cation systems and sensors for the exchange of data and information between machines, machine-equipments and/or machine-operators, teleoperations and automation are also described. Chapters 9 and 10 are related to wood products traceabil- ity, timber quality assessment as well as the technologies for the optimization of wood transformation processes. The concepts of wood product traceability and tracing, togeth- er with latest digital technologies for the identification and tracking of the logs (i.e., fingerprinting and RFID), are de- tailly reported. Chapter 11 is finally dedicated to the relationship between the EU policy framework and the digitalization process in both agricultural and forestry sectors. The book summarizes, under a proactive and homogeneous framework, PF methods, tools and technologies in relation with the digital transition of the Italian forestry sectors. The authors hope this book will be useful for improving the implementation of sustainable forest management practic- es at all levels in Italy, providing a comprehensive review useful for policy makers, technicians, forestry owners and students.

The economic evaluation of a land parcel is mainly based on the local economy, as well as on the topography, distance to the main streets, distance to the river, and presence of irrigation. Spatial variability of soil features and functionalities are often left behind during economic land evaluation, probably due to a scarce awareness of soil function&rsquo, s economic value. The paper shows an approach for economic land evaluation of irrigated croplands in the Po River plain (Northern Italy), based on spatial variability of soil functions, namely biomass production and carbon sequestration, as well as taking into account the river flood risk. The soil spatial variability was mapped using proximal sensing technology and few calibration points (one every 5 hectares). Biomass production of the main crops of the area, namely maize, soybean, and sorghum, was monitored and mapped for three years (2016, 2017, and 2018) using precision agriculture technologies. The results showed that the available water capacity (AWC) reached the highest correlation with biomass production, additionally, soil texture and cation exchange capacity were significantly correlated. Economic evaluation of the land parcels was computed considering the mean land market value of the area, the site-specific deviations due to the spatial variability of the biomass production by capitalization rate, and carbon sequestration soil functions, applying a natural capital approach by the mean annual value of the carbon market. This site-specific methodology could be applied to many other arable lands.

A three year experiment was carried out to test the possibility of using the carbon isotope ratio ( δ 13 C) measured in wine, combined with data of proximal and remote soil sensors, to assess viticultural and oenological suitability for Sangiovese. Two specialized vineyards on similar geomorphological conditions were investigated. Twelve plots were positioned differently along slopes. The soils were similar, except for structure, porosity and related hydrological characteristics, and salinity of the deeper horizons. Soil electrical conductivity and resistivity were measured at three different depths, as well as cumulative soil moisture down to the root-limiting layer. Satellite images were analyzed to obtain the NDVI. Soil water content in the plots was monitored at different depths. Yield, phenological phases, and chemical analysis of grapes were determined. Stem water potential was measured during summer. Grapes of each plot were collected for wine making in small barrels. The wines obtained were analyzed and submitted to a blind organoleptic testing. The wine was also analyzed for its δ 13 C isotopic ratio. Almost all plots had rather high amounts of transpirable water, even during the driest time of the year. However, only yield components of Sangiovese were influenced by water availability. Wine quality was instead significantly improved by the moderate salinity of the deeper horizons, which increased plant water stress during berry ripening and reduced production. The moderate physiological stress affecting vines was reflected in stem water potentials and δ 13 C values. δ 13 C was correlated with several viticultural and oenological parameters, and also with panel test evaluations of wine quality. The threshold between good and bad scores corresponded to a δ 13 C value of −26.7 ± 1.2‰. Soil salinity affected the geophysical survey and its relationship with the viticultural and oenological result. In particular, the electromagnetic conductivity measured at the beginning of the experiment was functional in distinguishing the two vineyards, but it was not useful for a more detailed prediction of Sangiovese performance. However, electromagnetic resistivity in the first 0.5 m was not influenced by salinity of the deep soil horizons, but only by clay content, and permitted a significant estimation of the Sangiovese anthocyanins content, colour intensity, and must acidity. The outcomes of this study recommend the use of δ 13 C in combination with electromagnetic resistivity to map soil suitability for Sangiovese. The favourable performance of Sangiovese in moderately saline soils may encourage diffusion of the cultivar outside its traditional areas of cultivation.

This study presents the main results and the methodology used in the creation of the atlas of the risk of desertification in Italy. A desertified area was defined as an unproductive area for agricultural or forestry use, due to soil degradation processes. An area at risk of desertification was a tract of the earth's surface which is vulnerable or sensitive to the processes of desertification. In a vulnerable land, environmental characteristics are close to that of a desertified area, but some factors (e.g. vegetation cover or irrigation), successfully mitigate the desertification process. On the other hand, sensitive land is a surface where the process leading to desertification is active, although the land is not yet unproductive. The DPSIR (Driving force-Pressure-State-Impact-Response) framework has been adopted as a reference. Using the national soil information system and socio-economic layers, an atlas of indicators of desertification risks was created, which was organized into different soil degradation systems. 51.8 per cent of Italy was considered to be at potential risk of desertification. Some 21.3 per cent of Italy (41.1 per cent of the area at potential risk) featured land degradation phenomena. Specifically, 4.3 per cent of Italy is already unproductive; 4.7 per cent is sensitive and 12.3 per cent is vulnerable. In the territory at potential risk of desertification, unproductive lands, plus areas vulnerable or sensitive to soil erosion, are at least the 19 per cent. Areas affected by aridity also sum up to 19 per cent. Salt-affected soils in Italy are estimated to cover >1 million ha. Irrigation can mitigate soil aridity and salinization, nevertheless, only about 15 per cent of the sensitive and vulnerable lands of southern Italy are actually equipped with irrigation networks. Copyright © 2009 John Wiley & Sons, Ltd.

Soils generally vary in a quite complex way. To assess and model spatial variability, several variables can be sampled in addition to the target used to quantify and describe the main phenomenon under study. One of the major advantages of geostatistics over simpler spatialization methods is that sparsely observations of the primary attribute can be complemented by secondary attributes that are more densely sampled. Two methods were applied to incorporate dense secondary information: multicollocated cokriging, which restricts the neighbourhood to the only secondary data collocated with the available data of the primary variable and simple cokriging with varying local means related to crisp classes. The objective of this paper was to find the method that best improves the estimation of primary attributes through dense secondary information for the study area, which was the province of Siena in central Italy, an area of about 3820 km2. Soil samples were taken at 742 locations and depth, sand and clay contents and available water capacity were determined. A multivariate geostatistical analysis was performed using the four soil properties and elevation from a digital elevation model of 20 × 20 m resolution as auxiliary variable. The variables were interpolated using three different approaches: cokriging, multicollocated cokriging, multicollocated simple kriging with local mean, estimated by averaging over the soil unit occurring at each node of the interpolation grid. These methods were compared in terms of precision, through cross-validation, and of accuracy, through a validation test, using an independent data set of 170 soil depth measurements. The results did not show clear differences among the methods.

This study aimed at setting up a comprehensive approach on viticultural and olive tree cultivation environmental impact, through soil and landscape change analysis at the years 1965, 1990, 1994 and 2000, both at the catchment and province scales. The study area was the province of Siena, in central Italy. Following a DPSIR approach, the State indicators checked the Impact of agricultural policies (Drivers), which have increased the Pressure of specialized crops, and suggested Response actions. The indicators selected for the catchment scale stressed the consequences of land use change on soil quality, capability and suitability. They were: (1) land use and land cover; (2) soil and water conservation management system, (3) soil hydrological group, (4) land capability; (5) land suitability for wine grape production. At the province level, four original indicators highlighted at the reconnaissance scale the impact of the two crops on soil conservation and management – (6) soil erosion risk, (7) soil management – as well as on visual attractiveness of landscape – (8) slope length of vineyards, (9) crop saturation of the landscape unit and its variation in time. The results showed that, at the catchment level, the twenty-fold increase in specialized viticulture and olive tree cultivation, along with the generalised adoption of the “up and down slope” soil and water conservation system, caused the impairment of soil hydrological group, land capability and suitability for growing quality wine. At the province level, soil erosion risk and soil management difficulty almost doubled in the transition from the traditional mixed to the new specialized tree cultivation. The areas traditionally producing wine protected by appellation of origin (DOCG) determined the distribution of land use and all the other impact indicators. Slope length of vineyards showed that the enlargement of the surface covered by vines preferentially affected lands close to already established DOCG farms. DOCG areas resulted somewhat saturated by vineyards, but not by olive tree groves. The response should foresee the following actions: (i) when planting new olive groves and vineyards, measures should be taken to avoid the complete removal of the subsurface soil B horizon; (ii) new plantations should maintain slope degree of less than 21% in any part of the field; (iii) the shape of new plantations should conform to slope morphology, thus avoiding the creation of long, wide and uniform slopes. The aim should be to limit the length of the fields to less than 150–300 m and to adopt or preserve the contour management systems.

Internal drainage class is an interpretative soil quality that derives from the field evaluation of other soil qualities and characteristics, i.e. soil permeability, texture, structure, redoximorphic features, and may not match the results of measurements of the actual soil water status. The aim of this work was to investigate whether a better characterization of standard field assessments of internal drainage of 12 soils in vineyards and olive groves could be achieved through the qualitative and quantitative micromorphological analyses. The results of field and laboratory analyses, as well as of 34 months of monitoring of soil moisture and temperature, and 21 months of water table and redox potential, were related to the micromorphological estimation of the hydromorphy degree, following the methodology of Aguilar et al. (2003) [Aguilar, J., Fernandez, J., Dorronsoro, C., Stoops, G., Dorronsoro, B., 2003. Hydromorphy in soils. http://edafologia.ugr.es/hidro/indexw.htm ], and to the quantification of porosity using image analysis. It was found that soils were only occasionally saturated with water and for short periods, although redox potentials during autumn and winter indicated probable Mn reduction. Water content monitoring differentiated soils with values far beyond field capacity throughout the year, and soils with values close to, or higher than, field capacity during rainy seasons. Results showed that hydromorphy degree was related to seasonal soil water content and redox potential. An improvement in this method should consider the presence and the nature of calcite pedofeatures. The statistical analysis associated the abundance of elongated and irregular macropores, which favor water drainage, to scarceness of macro- and microhydromorphic features and lower bulk density. The quantity of regular pores, which are less efficient for downward water transmission, was on the other hand correlated to an average high soil water content and to lower mean redox potentials. The relevance of elongated and irregular macropores for the internal drainage of this kind of soil (intensively cultivated, poorly structured, and with low total macroporosity) was also confirmed by the proportion of elongated and irregular macropores to total macroporosity (PR index). In soils of vineyards and olive groves, optimal drainage conditions in Mediterranean climate seem to be ensured by PR higher than 0.80. The study demonstrated, by means of a field experiment, the unfavorable effect of the common practice of deep plowing before tree planting in increasing the formation of redoximorphic features, micritic calcite nodules and infillings, within the deeper horizons of calcareous soils.

The assessment of class frequency in soil map legends is affected by uncertainty, especially at small scales where generalization is greater. The aim of this study was to test the hypothesis that data mining techniques provide better estimation of class frequency than traditional deterministic pedology in a national soil map. In the 1:5,000,000 map of Italian soil regions, the soil classes are the WRB reference soil groups (RSGs). Different data mining techniques, namely neural networks, random forests, boosted tree, classification and regression tree, and supported vector machine (SVM), were tested and the last one gave the best RSG predictions using selected auxiliary variables and 22,015 classified soil profiles. The five most frequent RSGs resulting from the two approaches were compared. The outcomes were validated with a Bayesian approach applied to a subset of 10% of geographically representative profiles, which were kept out before data processing. The validation provided the values of both positive and negative prediction abilities. The most frequent classes were equally predicted by the two methods, which differed however from the forecast of the other classes. The Bayesian validation indicated that the SVM method was more reliable than the deterministic pedological approach and that both approaches were more confident in predicting the absence rather than the presence of a soil type.

This work aimed at setting up a multivariate and geostatistical methodology to map viticultural terroirs at the province scale (1:125,000). The methodology is based upon the creation of a GIS storing all the viticultural and oenological legacy data of experimental vineyards (1989–2009), long-term climate data, digital elevation model, soilscapes (land systems) and legacy data of soil profiles.Environmental parameters related to viticulture, selected by an explorative PCA, were: elevation, mean annual temperature, mean soil temperature, annual precipitation, clay, sand and gravel content of soils, soil water availability, redoximorphic features and rooting depth.The variables interpolated using geostatistical methods, were used for a k-means clustering aimed to map the Natural Terroir Units (NTU). Vineyards of the province of Siena was subdivided into 9 NTU.Both the historical DOCG (Chianti Classico, Brunello di Montalcino and Nobile di Montepulciano) and other DOCs were characterized by three or four NTU, whereas the wider Chianti and Chianti Colli senesi DOCG was mainly constituted by seven NTU.

This research considered the varieties 'Frantoio' and 'Moraiolo' growing in rainfed olive trees (Olea europaea) and took place in Tuscany, central Italy. Soil moisture was monitored during the very meteorologically contrasting years 2002 and 2003 in two nearby olive groves. The plots had the same morphological and climatic conditions, but different soil types. Monocultivar oil samples were analyzed to determine fatty acids, minor polar compounds, and tocopherols content and were submitted to organoleptic analysis by a panel of trained tasters. The results highlighted that soil water regimen affects some nutraceutical components and the sensory evaluation of olive oil. Cultivar also affected yield components, polyphenols, and tocopherols content, but less than soil water availability. The plants on the soil inducing a relatively more intense and longer water deficit during summer (a Skeleti Calcaric Regosol) had an early ripening and gave the best results in terms of phenolic compounds and, consequently, antioxidant properties of the olive oil. The sensorial properties of the oil obtained from both cultivars on the Regosol were superior in both years of the trial.

The adoption of precision agriculture in viticulture could be greatly enhanced by the diffusion of straightforward and easy to be applied hydropedological models, able to predict the spatial variability of available soil water. The Lin's and Host hydropedological models were applied to standard soil series descriptions and hillslope position, to predict the distribution of hydrological functional units in two vineyard and their relevance for grape yield and wine quality. A three-years trial was carried out in Chianti (Central Italy) on Sangiovese. The soils of the vineyards differentiated in structure, porosity and related hydropedological characteristics, as well as in salinity. Soil spatial variability was deeply affected by earth movement carried out before vine plantation. Six plots were selected in the different hydrological functional units of the two vineyards, that is, at summit, backslope and footslope morphological positions, to monitor soil hydrology, grape production and wine quality. Plot selection was based upon a cluster analysis of local slope, topographic wetness index (TWI), and cumulative moisture up to the root limiting layer, appreciated by means of a detailed combined geophysical survey. Water content, redox processes and temperature were monitored, as well as yield, phenological phases, and chemical analysis of grapes. The isotopic ratio δ13C was measured in the wine ethanol upon harvesting to evaluate the degree of stress suffered by vines. The grapes in each plot were collected for wine making in small barrels. The wines obtained were analysed and submitted to a blind organoleptic testing. The results demonstrated that the combined application of the two hydropedological models can be used for the prevision of the moisture status of soils cultivated with grape during summertime in Mediterranean climate. As correctly foreseen by the models, the amount of mean daily transpirable soil water (TSW) during the growing season differed considerably between the vineyards and increased significantly along the three positions on slope in both vineyards. The water accumulation along slope occurred in every year, even during the very dry 2006. The installation of indicators of reduction in soils (IRIS) tubes allowed confirmation of the occurrence of reductive processes in the most shallow soil. Both Sangiovese grape yield and quality of wine were influenced by the interaction between TSW content and salinity, sometimes contrary to expectations. Therefore, the studied hydropedological models were not relevant to predict grape yield and wine quality in all the hydrological functional units. The diffusion of hydropedological models in precision viticulture could be boosted considering salinity along with topography and soil hydrological characteristics.