New techniques for the remote sensing of foliar nitrogen concentration in forest ecosystems.

During my Doctoral study I researched about the remote detection of canopy N concentration in forest stands, its potentials and problems, under many overlapping perspectives. The study consisted of three parts. In S. Rossore 2000 dataset analysis, I tested regressions between N concentration and NIR reflectances derived from different sources (field samples, airborne and satellite sensors). The analysis was further expanded using a larger dataset acquired in year 2009 as part of a new campaign funded by the ESA. In both cases, a good correlation was observed between Landsat NIR, using both TM (2009) and ETM+ (2000) imagery, and N concentration measured by a CHN elemental analyzer. Concerning airborne sensors I did not obtain the same good results, mainly because of the large FOV of the two instruments, and to the anisotropy of vegetation reflectance. We also tested the relation between ground based ASD measures and nitrogen concentration, obtaining really good results. Thus, I decided to expand my study to the regional level, focusing only on field and satellite measures. I analyzed a large dataset for the whole of Catalonia, Spain; MODIS imagery was used, in consideration of its spectral characteristics and despite its rather poor spatial resolution. Also in this case a regression between nitrogen concentration and reflectances was found, but not so good as in previous experiences. Moreover, vegetation type was found to play an important role in the observed relationship. We concluded that MODIS is not the most suitable satellite sensor in realities like Italy and Catalonia, which present a patchy and inhomogeneous vegetation cover; so it could be utilized for the parameterization of eco-physiological and biogeochemical models, but not for really local nitrogen estimate. Thus multispectral sensors similar to Landsat Thematic Mapper, with better spatial resolution, could be the most appropriate sensors to estimate N concentration.

Advanced Spectroscopy for the Study of Colourants in Cultural Heritage

Colourants are substances used to change the colour of something, and are classified in three typology of colorants: a) pigments, b) dyes, and c) lakes and hybrid pigments. Their identification is very important when studying cultural heritage; it gives information about the artistic technique, can help in dating, and offers insights on the condition of the object. Besides, the study of the degradation phenomena constitutes a framework for the preventive conservation strategies, provides evidence of the object's original appearance, and contributes to the authentication of works of art. However, the complexity of these systems makes it impossible to achieve a complete understanding using a single technique, making necessary a multi-analytical approach. This work focuses on the set-up and application of advanced spectroscopic methods for the study of colourants in cultural heritage. The first chapter presents the identification of modern synthetic organic pigments using Metal Underlayer-ATR (MU-ATR), and the characterization of synthetic dyes extracted from wool fibres using a combination of Thin Layer Chromatography (TLC) coupled to MU-ATR using AgI@Au plates. The second chapter presents the study of the effect of metallic Ag in the photo-oxidation process of orpiment, and the influence of the different factors, such as light and relative humidity. We used a combination of vibrational and synchrotron radiation-based X-ray microspectroscopy techniques: µ-ATR-FT-IR, µ-Raman, SR-µ-XRF, µ-XANES at S K-, Ag L3- and As K-edges and SR-µ-XRD. The third chapter presents the study of metal carboxylates in paintings, specifically on the formation of Zn and Pb carboxylates in three different binders: stand linseed oil, whole egg, and beeswax. We used micro-ATR-FT-IR, macro FT-IR in total reflection (rMA-FT-IR), portable Near-Infrared spectroscopy (NIR), macro X-ray Powder Diffraction (MA-XRPD), XRPD, and Gas Chromatography Mass-Spectrometry (GC-MS). For the data processing, we explored the data from rMA-FT-IR and NIR with the Principal Component Analysis (PCA).

Modeling systems and vis/NIR device to improve peach and nectarine pre and post-harvest fruit maturity management

During the last decade peach and nectarine fruit have lost considerable market share, due to increased consumer dissatisfaction with quality at retail markets. This is mainly due to harvesting of too immature fruit and high ripening heterogeneity. The main problem is that the traditional used maturity indexes are not able to objectively detect fruit maturity stage, neither the variability present in the field, leading to a difficult post-harvest management of the product and to high fruit losses. To assess more precisely the fruit ripening other techniques and devices can be used. Recently, a new non-destructive maturity index, based on the vis-NIR technology, the Index of Absorbance Difference (IAD), that correlates with fruit degreening and ethylene production, was introduced and the IAD was used to study peach and nectarine fruit ripening from the “field to the fork”. In order to choose the best techniques to improve fruit quality, a detailed description of the tree structure, of fruit distribution and ripening evolution on the tree was faced. More in details, an architectural model (PlantToon®) was used to design the tree structure and the IAD was applied to characterize the maturity stage of each fruit. Their combined use provided an objective and precise evaluation of the fruit ripening variability, related to different training systems, crop load, fruit exposure and internal temperature. Based on simple field assessment of fruit maturity (as IAD) and growth, a model for an early prediction of harvest date and yield, was developed and validated. The relationship between the non-destructive maturity IAD, and the fruit shelf-life, was also confirmed. Finally the obtained results were validated by consumer test: the fruit sorted in different maturity classes obtained a different consumer acceptance. The improved knowledge, leaded to an innovative management of peach and nectarine fruit, from “field to market”.