Can allelopathic potentialities of Mediterranean plant species reduce the spread of invasive plant species, Acacia dealbata and Ailanthus altissima?

Beyond ecological and health impacts, invasive alien plant species can generate indirect and direct costs, notably through reduced agricultural yields, restoration, and management of the invaded environment. Acacia dealbata and Ailanthus altissima are invasive plant species that cause particularly significant damage to the railway network in the Mediterranean area. The allelopathic properties of Mediterranean plant species could be used as nature-based solutions to slow down the spread of such invasive plant species along railway borders. In this context, a mesocosm experiment was set-up: (i) to test the potential allelopathic effects of Cistus ladanifer, Cistus albidus, and Cotinus coggygria leaf aqueous extracts on seed germination and seedling growth of A. dealbata and A. altissima; (ii) to evaluate whether these effects depend on the extract dose; and finally, (iii) to estimate whether these effects are modified by soil amendment. Leaf aqueous extracts of the three native plant species showed negative effects on both seed germination and seedling growth of the two invasive species. Our results show that the presence of allelochemicals induces a delay in seed germination (e.g., A. dealbata germination lasted up to 269% longer in the presence of high-dose leaf aqueous extracts of C. coggygria), which can lead to a decrease in individual recruitment. They also highlight a decrease in seedling growth (e.g., high-dose C. coggygria leaf aqueous extracts induced a 26% decrease in A. dealbata radicle growth), which can alter the competitiveness of invasive species for resource access. Our results also highlight that compost addition limits the inhibitory effect of native Mediterranean plants on the germination of invasive alien plants, suggesting that soil organic matter content can counteract allelopathic effects on invasive alien plants. Thus, our findings revealed that the allelopathic potential of certain Mediterranean plant species could be a useful tool to manage invasive plant species.

Authentication and Chemometric Discrimination of Six Greek PDO Table Olive Varieties through Morphological Characteristics of Their Stones.

Table olives, the number one consumed fermented food in Europe, are widely consumed as they contain many valuable ingredients for health. It is also a food which may be the subject of adulteration, as many different olive varieties with different geographical origin, exist all over the word. In the present study, the image analysis of stones of six main Greek protected designation of origin (PDO) table olive varieties was performed for the control of their authentication and discrimination, with cv. Prasines Chalkidikis, cv. Kalamata Olive, cv. Konservolia Stylidas, cv. Konservolia Amfissis, cv. Throuba Thassos and cv. Throuba Chios being the studied olive varieties. Orthogonal partial least square discriminant analysis (OPLS-DA) was used for discrimination and classification of the six Greek table olive varieties. With a 98.33% of varietal discrimination, the OPLS-DA model proved to be an efficient tool to authentify table olive varieties from their morphological characteristics.

Chemometric Discrimination of the Geographical Origin of Three Greek Cultivars of Olive Oils by Stable Isotope Ratio Analysis.

Α stable isotope ratio mass spectrometer was used for stable isotope ratio (i.e., δ13C, δ18O, and δ2H) measurements, achieving geographical discrimination using orthogonal projections to latent structures discriminant analysis. A total of 100 Greek monovarietal olive oil samples from three different olive cultivars (cv. Koroneiki, cv. Lianolia Kerkyras, and cv. Maurolia), derived from Central Greece and Peloponnese, were collected during the 2019-2020 harvest year aiming to investigate the effect of botanical and geographical origin on their discrimination through isotopic data. The selection of these samples was made from traditionally olive-growing areas in which no significant research has been done so far. Samples were discriminated mainly by olive cultivar and, partially, by geographical origin, which is congruent with other authors. Based on this model, correct recognition of 93.75% in the training samples and correct prediction of 100% in the test set were achieved. The overall correct classification of the model was 91%. The predictability based on the externally validated method of discrimination was good (Q2 (cum) = 0.681) and illustrated that δ18O and δ2H were the most important isotope markers for the discrimination of olive oil samples. The authenticity of olive oil based on the examined olive varieties can be determined using this technique.

Statistical approach to evaluate effect of temperature and moisture content on the production of antioxidant naphtho-gamma-pyrones and hydroxycinnamic acids by Aspergillus tubingensis in solid-state fermentation.

Non-ochratoxigenic Aspergillus tubingensis G131 is a filamentous fungus that can produce naphtho-gamma-pyrones (NγPs), polyketide pigments that exhibit interesting antioxidant properties. This study aims to investigate the effect of two critical parameters, temperature and moisture content on the fungus grown in solid-state fermentation using agricultural by-products (vine shoots and wheat bran) as sole medium. From the kinetic productions of secondary metabolites NγPs (asperpyrone E, dianhydroaurasperone C, fonsecin, fonsecin B and ustilaginoidin A), alkaloids (nigragilin and aspernigrin A), degradation products from the solid medium (ß-D-glucose, p-coumaric acid and trans-ethyl ferulate), ergosterol and conidia obtained for different temperatures and moisture contents, a principal component analysis (PCA) was carried out to highlight the production patterns of these compounds. This approach allowed us to determine that fonsecin, the compound of higher interest-exhibiting the most interesting antiradical potential-is particularly more produced at 25 °C and 66% of moisture content. This study underlines the importance of temperature and moisture content on naphtho-gamma-pyrones and hydroxycinnamic acid production using solid-state fermentation and contributes to the development of agroindustrial by-product valorization.

Infrared spectroscopy as a useful tool to predict land use depending on Mediterranean contrasted climate conditions: A case study on soils from olive-orchards and forests.

Soil chemical properties depend on various environmental factors such as above ground vegetation, climate and the parent rock substratum. Land use, and the associated management practices, is one of the major drivers which can deeply impact soil properties. To better understand the dynamics of soil chemical properties and to assess potential impact of land use, an improved monitoring of chemical signature in organo-mineral topsoils is necessary. Here, we explored how land use (forests or agrosystems i.e. olive-tree orchards) may shape soil chemical signature and whether it depends i) on the type of agricultural or sylvicultural practices, ii) on contrasted Mediterranean climate conditions at different spatial scales. We measured variations in soils properties by FTIR-ATR (Fourier-Transformed Infrared - Attenuated Total Reflectance) spectroscopy and elemental concentrations. FTIR showed that the aromatic fraction of organic matter and CaCO3 discriminated soils under different land uses (orchards or forests) and this depended on climate (sub-humid vs humid climate). Moreover, the chemical signatures of soils varied with the practices applied. For agrosystems, soils complemented with olive-mill wastes were characterized by aromatics compared to soils under natural grass or tillage. For forests, soils from Pinus spp. stands and Quercus spp. stands were discriminated by CaCO3 and aromatics respectively. Contrasted climate conditions at local scale, i.e. northern vs southern slopes for forests and distance from the sea (coastal vs inland area) for agrosystems, had an effect on soil chemical signature. The AcomDIM interpretation of FTIR-ATR signals showed that factors "land use", "practices" and "climate" and their interactions could have a significant impact on soil chemical signature. PLS modeling also confirmed that FTIR-ATR is a useful tool to predict a type of land use depending on climate.

NIR spectroscopy for the quality control of Moringa oleifera (Lam.) leaf powders: Prediction of minerals, protein and moisture contents.

A rapid methodology was developed to simultaneously predict water content and activity values (aw) of Moringa oleifera leaf powders (MOLP) using near infrared (NIR) signatures and experimental sorption isotherms. NIR spectra of MOLP samples (n = 181) were recorded. A Partial Least Square Regression model (PLS2) was obtained with low standard errors of prediction (SEP of 1.8% and 0.07 for water content and aw respectively). Experimental sorption isotherms obtained at 20, 30 and 40 °C showed similar profiles. This result is particularly important to use MOLP in food industry. In fact, a temperature variation of the drying process will not affect their available water content (self-life). Nutrient contents based on protein and selected minerals (Ca, Fe, K) were also predicted from PLS1 models. Protein contents were well predicted (SEP of 2.3%). This methodology allowed for an improvement in MOLP safety, quality control and traceability.

Prediction of source rock origin by chemometric analysis of fourier transform infrared-attenuated total reflectance spectra of oil petroleum: evaluation of aliphatic and aromatic fractions by self-modeling mixture analysis.

This study describes a new methodology for the interpretation of Fourier transform infrared (FT-IR) attenuated total reflectance (ATR) spectra of Algerian, Brazilian, and Venezuelan crude oils. It is based on a comparative study between a chemometric treatment and the classical one, which refers to indices calculation. In fact, the combined use of FT-IR indices and principal component analysis (PCA) has led to the classification of the studied samples in terms of geographic distribution. Quantitative analysis has been successfully realized by the supervised method partial least squares (PLS), which has permitted the prediction of the locations of oils. We have also applied another mathematical processing method, simple-to-use interactive self-modeling mixture analysis (SIMPLISMA), to evaluate the aromatic and aliphatic composition of the oils by extracting pure spectra representative of the different fractions.