Arbuscular mycorrhizal fungi affect total phenolics content and antioxidant activity in leaves of oak leaf lettuce varieties

Plant secondary metabolites are considered key bioactive compounds for a healthy diet. Arbuscular mycorrhizal fungi (AMF) may interact with host plant metabolism, inducing the accumulation of health-promoting phytochemicals and antioxidant molecules. Lettuce is a largely consumed vegetable, which may interact with AMF to alter its content of secondary metabolites and natural antioxidants molecules, as previously shown in cultivars belonging to var. capitata or var. longifolia. In this study, the effects of red and green leaf Lactuca sativa var. crispa inoculation with different AMF species, Rhizoglomus irregulare and Funneliformis mosseae, were investigated, by assessing the total phenolics and anthocyanins content, and the antioxidant activity of leaf tissue. A significant increase of antioxidant activity and of phenolics were observed in plants of both cultivars inoculated with R. irregulare, compared to non inoculated plants. Likewise, anthocyanins (in red leaf lettuce) were more abundant in inoculated plants than in controls. Altogether, the results indicate that R. irregulare strain showed a stronger ability than F. mosseae in affecting plant metabolism and that mycorrhizal inoculation may be used to enhance concentration of phenolics in leaf type lettuces, provided that a suitable AMF is selected

Enabling adaptive pedestals in predictive transport simulations using neural networks

We present PEdestal Neural Network (PENN) as a machine learning model for tokamak pedestal predictions. Here, the model is trained using the EUROfusion JET pedestal database to predict the electron pedestal temperature and density from a set of global engineering and plasma parameters. Results show that PENN makes accurate predictions on the test set of the database, with R (2) = 0.93 for the temperature, and R (2) = 0.91 for the density. To demonstrate the applicability of the model, PENN is employed in the European transport simulator (ETS) to provide boundary conditions for the core of the plasma. In a case example in the ETS with varied neutral beam injection (NBI) power, results show that the model is consistent with previous studies regarding NBI power dependency on the pedestal. Additionally, we show how an uncertainty estimation method can be used to interpret the reliability of the predictions. Future work includes further analysis of how pedestal models, such as PENN, or other advanced deep learning models, can be more efficiently implemented in integrating modeling frameworks, and also how similar models may be generalized with respect to other tokamaks and future device scenarios

Studies of the non-axisymmetric plasma boundary displacement in JET in presence of externally applied magnetic field

Non-axisymmetric plasma boundary displacement is caused by the application of the external magnetic field with low toroidal mode number. Such displacement affects edge stability, power load on the first wall and could affect efficiency of the ICRH coupling in ITER. Studies of the displacement are presented for JET tokamak focusing on the interaction between error field correction coils (EFCCs) and shape control system. First results are shown on the direct measurement of the plasma boundary displacement at different toroidal locations. Both qualitative and quantitative studies of the plasma boundary displacement caused by interaction between EFCCs and shape control system are performed for different toroidal phases of the external field. Axisymmetric plasma boundary displacement caused by the EFCC/shape control system interaction is seen for certain phase values of the external field. The value of axisymmetric plasma boundary displacement caused by interaction can be comparable to the non-axisymmetric plasma boundary displacement value produced by EFCCs

Gelatin-based coating enriched with blueberry juice preserves the nutraceutical quality and reduces the microbial contamination of tomato fruit

To preserve quality and extend the shelf life of tomato, a bioactive edible coating was prepared using gelatin wastes from pharmaceutical industry and lyophilised blueberry juice (BJ). The effectiveness of gelatin-coating (G) and G enriched with blueberry juice (GB) was tested, monitoring carotenoids, polyphenols and flavonoids content, the antioxidant activity and the antimicrobial efficiency of coating against the native microflora. After 7 d of storage, coated fruit showed higher phenolic and flavonoids content and increased antioxidant activity, while carotenoids were unaffected by the treatments. The growth of mesophilic bacteria of GB, and the growth of coliform bacteria of G and GB were significantly reduced during the entire period. The results indicate that GB preserved the nutritional quality of tomatoes and that BJ was able to increase the antimicrobial activity of the coating. This paves the way for a possible use of this biodegradable waste polymer as an eco-friendly coating material