Green mold, caused by Penicillium digitatum, is the most damaging postharvest citrus fruit disease. Conventionally, it is managed with synthetic fungicides. This study evaluated a cell-free, non-viable, lactic acid bacteria (LAB)-activated lemon peel-derived formulation (LM + LAB), produced by fermenting a lemon peel-based medium with Lactiplantibacillus plantarum N3B2, under two application scenarios. LM + LAB was compared with imazalil (standard synthetic fungicide), the yeast Candida oleophila strain O, a potassium phosphite-based formulation, phosphorous acid, and an untreated control., Sweet orange fruit were treated either before inoculation or 4 h after inoculation with P. digitatum. Fruit were stored for 7 days at 6 °C and then at 18 °C until 14 days post-inoculation. Disease incidence was assessed at 7, 10, and 14 days, sporulation reduction at 14 days, and fruit quality throughout storage. Imazalil provided the most effective control. LM + LAB significantly reduced disease incidence under both application scenarios. At 14 days, incidence was reduced from 78% to 38% when LM + LAB was applied before inoculation and from 79% to 15% when it was applied 4 h after inoculation. Sporulation was reduced by 43% and 64%, respectively. When applied post-inoculation, LM + LAB was as effective as imazalil and C. oleophila in reducing disease incidence and suppressed sporulation more effectively than the yeast. Potassium phosphite and phosphorous acid were the least effective substances. None of the treatments caused weight loss or significantly affected firmness, total soluble solids, juice pH, or titratable acidity of fruit. Results show LM + LAB is a promising natural product for management of citrus green mold.
Bark beetles are fundamental drivers of forest ecosystem dynamics. However, some species within this group have recently also emerged as significant pests in environments managed by humans, including nurseries, orchards, and urban areas. Specifically, certain Scolytus species pose potential economic and ecological threats to stone fruit cultivation across the Mediterranean basin. Although the role of the mycobiome in mediating bark beetle–host interactions has been well documented for many forest models, the symbiotic associations between beetles and fungi in cultivated Mediterranean agroecosystems remain poorly understood. This study provides the first comprehensive characterization of the fungal community associated with the almond bark beetle Scolytus amygdali in southern Mediterranean almond orchards. Integrating culture-dependent isolations with culture-independent approaches, i.e., high-throughput sequencing, allowed us to assess the beetle mycobiome across beetle adults, gallery systems, and associated necrotic wood lesions. Molecular characterization revealed Geosmithia, Paecilomyces, and Quambalaria to be the dominant taxa within the S. amygdali mycobiome. Their frequent occurrence suggests that they may be recurrent associates in the gallery environment, although their functional roles remain unclear. Furthermore, metabarcoding analyses provided additional novel insights into the beetle mycobiome, identifying Candida and Yamadazyma yeasts as potential core constituents of the gut microbiome. Future research should prioritize elucidating the role of these putative fungal symbionts for the beetles, particularly the pathogenic potential on almonds, and the functional efficiency of S. amygdali as a vector. Overall, our findings elucidate the complex taxonomic diversity of these associations. Moreover, obtained results provide a foundational ecological framework to better understand to what extent these associations can threaten host plants and to develop future sustainable management strategies in managed ecosystems.
This research extends a previous investigation initiated by the authors focusing on the impact of geometric nonlinearity on the propagation of seismic waves in a two-dimensional model of the Aterno Valley, which includes the urban region of L'Aquila. Starting from a Cauchy continuum framework, this study undertakes a comparative analysis between a traditional linearized formulation, based on infinitesimal strain energy, and a nonlinear model that incorporates the Green-Lagrange strain tensor. The computational domain describes a detailed geological cross-section of the valley, comprising three primary stratigraphic layers. In addition, the upper layer incorporates mechanical segmentation. Furthermore, the excitation is represented as a spherical wavefront applied at the basal boundary, emulating a deep, high-energy source equivalent to an earthquake with a magnitude of Mw >= 6. Finite element simulations were performed in COMSOL using a generalized-alpha time integration scheme. An examination was conducted on two distinct configurations of Young's modulus distribution within the upper stratum. The first configuration comprised a homogeneous rigid top layer characterized by a unicum body, while the second configuration incorporated soft inclusions within the upper layer to emulate its fragmentation. A comparative analysis was conducted on nonlinear and linear simulations using normalized energy deviation parameters. This approach facilitated the quantification of the relative discrepancies between the deformation energy densities exhibited by the two models. The results indicate that, while the average deviations between the linear and nonlinear formulations are generally moderate, substantial local discrepancies are observed in regions near interfaces with pronounced stiffness contrasts. Specifically, energy deviations in these areas can exceed 100% in certain regions. The observed localized amplifications and redistributions of energy indicate that geometric nonlinearities might significantly affect the spatial distribution of wave energy propagation. This effect is particularly pronounced in scenarios where the shallow layers are mechanically segmented or incorporate compliant inclusions. The temporal evolution of energy at specific reference points within the urban area exhibits scenario-dependent variations, suggesting that linear assumptions may inaccurately characterize site response under conditions of high-intensity excitation. The results confirm the assumption that geometric nonlinearities are significant factors in strongly heterogeneous basins. This emphasizes the need for precise geometric representation and realistic modeling of stiffness distributions to improve predictive accuracy and reliability.
The Corvis tonometer is widely used to measure intraocular pressure in the cornea and contact lens. In this study, based on the results of finite element simulations from a previous study, the methodology for generating two types of metamodels is elaborated in detail, and the challenges associated with each is examined. In addition, the sensitivity of each metamodel category to its inputs is analyzed, and the influence of each parameter is thoroughly evaluated. The results show that, even under significant variations in the inputs, the changes in this parameter remain minimal, making it a worthy measure for estimating the projected pressure.
While developmental plasticity helps organisms to maintain fitness as environments change, such plasticity has limits. When novel environments exceed these limits and mean fitness declines, the extent of decline is expected to vary among genotypes, which could increase adaptive potential. We lack fundamental insights into whether genetic variation in early development is linked to adaptive potential in novel environments, which limits our ability to predict how natural populations will respond to global change. Using a breeding design, we generated c. 20,000 seeds of 2 ecologically contrasting Sicilian species of daisies (Senecio, Asteraceae) adapted to high and low elevations on Mount Etna. We planted the seeds across 4 elevations that included elevations within the native range of each species, the edge of their range, and a novel elevation. We tracked seedling mortality and measured development time as the number of days it took seedlings to establish. As predicted, genetic variance in survival increased at novel elevations, suggesting that adaptive potential consistently increases for contrasting species facing different novel environments. However, genetic variance in development time showed the opposite trend, decreasing at novel elevations. A strong negative genetic correlation between development time in the native range and survival at novel elevations suggested that genotypes with faster development in native environments survived better in novel environments. These results were consistent across the two ecologically contrasting species, suggesting that genetic variance in early development in native environments could be used to predict genotypes that increase adaptive potential in novel environments.
