Carvacrol Encapsulation in Chitosan-Carboxymethylcellulose-Alginate Nanocarriers for Postharvest Tomato Protection.

Advancements in polymer science and nanotechnology hold significant potential for addressing the increasing demands of food security, by enhancing the shelf life, barrier properties, and nutritional quality of harvested fruits and vegetables. In this context, biopolymer-based delivery systems present themselves as a promising strategy for encapsulating bioactive compounds, improving their absorption, stability, and functionality. This study provides an exploration of the synthesis, characterization, and postharvest protection applications of nanocarriers formed through the complexation of chitosan oligomers, carboxymethylcellulose, and alginate in a 2:2:1 molar ratio. This complexation process was facilitated by methacrylic anhydride and sodium tripolyphosphate as cross-linking agents. Characterization techniques employed include transmission electron microscopy, energy-dispersive X-ray spectroscopy, infrared spectroscopy, thermal analysis, and X-ray powder diffraction. The resulting hollow nanospheres, characterized by a monodisperse distribution and a mean diameter of 114 nm, exhibited efficient encapsulation of carvacrol, with a loading capacity of approximately 20%. Their suitability for phytopathogen control was assessed in vitro against three phytopathogens-Botrytis cinerea, Penicillium expansum, and Colletotrichum coccodes-revealing minimum inhibitory concentrations ranging from 23.3 to 31.3 µg·mL-1. This indicates a higher activity compared to non-encapsulated conventional fungicides. In ex situ tests for tomato (cv. 'Daniela') protection, higher doses (50-100 µg·mL-1, depending on the pathogen) were necessary to achieve high protection. Nevertheless, these doses remained practical for real-world applicability. The advantages of safety, coupled with the potential for a multi-target mode of action, further enhance the appeal of these nanocarriers.

Light Energy Efficiency in Lettuce Crop: Structural Indoor Designs Simulation.

Indoor agricultural offers efficient alternatives for intensive food production through automation technologies and controlled environments. Light plays a crucial role in plant development; however, photons captured by the crop are often wasted in empty spaces, resulting in low light efficiency and high energy costs. This research aims to simulate eight structural designs for an indoor lettuce crop, exploring different planting systems and light and culture bed combinations (static and mobile) to identify the most effective mechanism for light efficiency during crop growth. The simulations were carried out with spreadsheets based on applying formulas of yield in dry biomass per photosynthetic photons, lighting costs, harvest, and production. The results indicate that Circular Moving Light and Mobile Culture Bed with Quincunx Planting (CML-QM) and Circular Moving Light and Mobile Culture Bed with Linear Planting (CML-LPM) exhibit higher photon capture percentages (85% and 80%, respectively) and lower electricity consumption compared to static designs. The simulation results demonstrate the potential for significant improvements in photon capture and cost savings through optimized system designs. This investigation provides valuable insights for designing more efficient systems and reducing electricity consumption to enhance the capture of photosynthetic photons in indoor lettuce cultivation.

A Coating Based on Bioactive Compounds from Streptomyces spp. and Chitosan Oligomers to Control Botrytis cinerea Preserves the Quality and Improves the Shelf Life of Table Grapes.

Botrytis cinerea is the most harmful postharvest disease of table grapes. Among the strategies that can be envisaged for its control, the use of coatings based on natural products is particularly promising. The study presented herein focuses on the assessment of the antagonistic capacity of two Streptomyces species and their culture filtrates against B. cinerea. Firstly, the secondary metabolites were characterized by gas chromatography-mass spectrometry, with N1-(4-hydroxybutyl)-N3-methylguanidine acetate and 2R,3S-9-[1,3,4-trihydroxy-2-butoxymethyl]guanine acetate as the main compounds produced by S. lavendofoliae DSM 40217; and cyclo(leucyloprolyl) and cyclo(phenylalanylprolyl) as the most abundant chemical species for S. rochei DSM 41729. Subsequently, the capacity of S. lavendofoliae DSM 40217 and S. rochei DSM 41729 to inhibit the growth of the pathogen was tested in dual culture plate assays, finding 85-90% inhibition. In agar dilution tests, their culture filtrates resulted in effective concentration values (EC90) in the 246-3013 µg·mL-1 range. Upon the formation of conjugate complexes with chitosan oligomers (COS) to improve solubility and bioavailability, a synergistic behavior was observed, resulting in lower EC90 values, ranging from 201 to 953 µg·mL-1. Ex situ tests carried out on 'Timpson' and 'Red Globe' table grapes using the conjugate complexes as coatings were found to maintain the turgor of the grapes and delay the appearance of the pathogen by 10-15 days at concentrations in the 750-1000 µg·mL-1 range. Hence, the conjugate complexes of COS and the selected Streptomyces spp. culture filtrates may be put forward as promising protection treatments for the sustainable control of gray mold.

Daily Estimation of Global Solar Irradiation and Temperatures Using Artificial Neural Networks through the Virtual Weather Station Concept in Castilla and León, Spain.

In this article, the interpolation of daily data of global solar irradiation, and the maximum, average, and minimum temperatures were measured. These measurements were carried out in the agrometeorological stations belonging to the Agro-climatic Information System for Irrigation (SIAR, in Spanish) of the Region of Castilla and León, in Spain, through the concept of Virtual Weather Station (VWS), which is implemented with Artificial Neural Networks (ANNs). This is serving to estimate data in every point of the territory, according to their geographic coordinates (i.e., longitude and latitude). The ANNs of the Multilayer Feed-Forward Perceptron (MLP) used are daily trained, along with data recorded in 53 agro-meteorological stations, and where the validation of the results is conducted in the station of Tordesillas (Valladolid). The ANN models for daily interpolation were tested with one, two, three, and four neurons in the hidden layer, over a period of 15 days (from 1 to 15 June 2020), with a root mean square error (RMSE, MJ/m2) of 1.23, 1.38, 1.31, and 1.04, respectively, regarding the daily global solar irradiation. The interpolation of ambient temperature also performed well when applying the VWS concept, with an RMSE (°C) of 0.68 for the maximum temperature with an ANN of four hidden neurons, 0.58 for the average temperature with three hidden neurons, and 0.83 for the minimum temperature with four hidden neurons.

Prediction of Daily Ambient Temperature and Its Hourly Estimation Using Artificial Neural Networks in an Agrometeorological Station in Castile and León, Spain.

This study evaluates the predictive modeling of the daily ambient temperature (maximum, Tmax; average, Tave; and minimum, Tmin) and its hourly estimation (T0h, …, T23h) using artificial neural networks (ANNs) for agricultural applications. The data, 2004-2010, were used for training and 2011 for validation, recorded at the SIAR agrometeorological station of Mansilla Mayor (León). ANN models for daily prediction have three neurons in the output layer (Tmax(t + 1), Tave(t + 1), Tmin(t + 1)). Two models were evaluated: (1) with three entries (Tmax(t), Tave(t), Tmin(t)), and (2) adding the day of the year (J(t)). The inclusion of J(t) improves the predictions, with an RMSE for Tmax = 2.56, Tave = 1.65 and Tmin = 2.09 (°C), achieving better results than the classical statistical methods (typical year Tave = 3.64 °C; weighted moving mean Tmax = 2.76, Tave = 1.81 and Tmin = 2.52 (°C); linear regression Tave = 1.85 °C; and Fourier Tmax = 3.75, Tave = 2.67 and Tmin = 3.34 (°C)) for one year. The ANN models for hourly estimation have 24 neurons in the output layer (T0h(t), …, T23h(t)) corresponding to the mean hourly temperature. In this case, the inclusion of the day of the year (J(t)) does not significantly improve the estimations, with an RMSE = 1.25 °C, but it improves the results of the ASHRAE method, which obtains an RMSE = 2.36 °C for one week. The results obtained, with lower prediction errors than those achieved with the classical methods, confirm the interest in using the ANN models for predicting temperatures in agricultural applications.

Rhodamine B removal with activated carbons obtained from lignocellulosic waste.

By-products from the wax production process from carnauba palm (leaves), from the extraction of oil from macauba seeds (endocarp) and from pine nut production (shell) have been assessed for activated carbon production, using H3PO4 or CaCl2 for their chemical activation. The resulting activated charcoals have been thoroughly characterized by elemental and thermal analysis, X-ray diffraction, infrared spectroscopy, electron scanning microscopy and N2 adsorption behavior. Subsequently, their adsorption capacity for the removal of rhodamine B (RhB) from aqueous solutions has been evaluated by studying different parameters: contact time, pH, adsorbent dose, initial dye concentration and solution temperature. The adsorption of RhB followed Freundlich's model in all cases. Kinetic studies indicate that the pseudo-second order model can be used for describing the dynamics of the adsorption process. Thermodynamic parameters have also been evaluated, indicating its endothermic and spontaneous nature. Finally, a preliminary analysis of the impact of cellulose content in the carbon precursor materials has been conducted, by using a mixture of native cellulose with one of the lignocellulosic materials.

A kinetic study on microwave-assisted conversion of cellulose and lignocellulosic waste into hydroxymethylfurfural/furfural.

Native cellulose, lignocellulosic materials from Brazil (carnauba palm leaves and macauba pulp and shell) and pine nut shell from Spain have been studied as substrates for the production of HMF and furfural in a conventional microwave oven. In order to promote the dissolution of native cellulose, several ionic liquids, catalysts, organic solvents and water doses have been assessed. The most suitable mixture (5mL of choline chloride/oxalic acid, 2mL of sulfolane, 2mL of water, 0.02g of TiO2 and 0.1g of substrate) has been chosen to conduct kinetic studies at different reaction times (5-60min) and various temperatures (120-200°C) and to evaluate the best conditions for HMF+furfural production according to Seaman's model. The best production yields of HMF+furfural have been attained for native cellulose, with a yield of 53.24% when an ultrasonic pretreatment was used prior to a microwave treatment with stirring.

Seasonal and sex-related variations in serum steroid hormone levels in wild and farmed brown trout Salmo trutta L. in the north-west of Spain.

Serum steroid profiles were investigated in order to evaluate the potential use of circulating sex steroid levels as a tool for sex identification in brown trout. Changes in the serum concentrations of testosterone (T), progesterone (P), 17-ß-estradiol (E2), and cortisol (F) in wild and farmed mature female and male brown trout, Salmo trutta L., were measured in each season (January, May, July, and October) in six rivers and four hatcheries located in the north-west of Spain. Serum cortisol levels in farmed brown trout were significantly higher and showed a seasonal pattern opposite to that found in wild trout. Because levels of the hormones under study can be affected by disruptive factors such as exposure to phytoestrogens (which alters the hypothalamic-pituitary-gonadal axis) and infection with Saprolegnia parasitica (which alters the hypothalamic-pituitary-adrenal axis), both factors are taken into account.

Composting and vermicomposting experiences in the treatment and bioconversion of asphaltens from the Prestige oil spill.

This work illustrates the effectiveness of composting and vermicomposting in degrading fuel-in-water emulsions from oil spills (chapapote), and the isolation of potentially useful microorganisms for its biodegradation. Firstly, an alternative to the biodegradation of asphaltens from the Prestige oil spill (still present in some chapapote rafts in the Cantabrian coast) by means of the application of composting techniques to a microbial partnership acclimated to fuel-oil is offered. Our aim is that, after a relatively short period of time, the microorganisms can obtain its source of carbon and energy from asphaltens. The addition of metabolic co-substrates, like cow bed and potato peelings, allows the fragmentation of complex compounds into smaller structures, susceptible to further degradation. Afterwards, a maturation of the compost by means of a treatment with earthworms (Eisenia foetida) is necessary. Thus, through the vermicomposting it will be possible to obtain a valued product, useful in the processes of ground amendment, with little presence of asphaltens and occluded polycyclic aromatic hydrocarbons, rich in humus, and with an important bacterial flora of Bacillus genera, so that it can be typical of co-activators and accelerating products in composting processes. Along with this article, we show some parameters that control the evolution of the compost products (evolved gases, acidity, temperature and humidity); the chemical and microbiological analytical results; and the germination assays of vermicomposting. Results reveal that by using microorganisms living in either earthworm intestines (Stenotrophomonas maltophilia) or vermiculture substrates (Scedosporium apiospermium), it is possible to degrade and to eliminate the polycyclic asphaltens into CO(2) and H(2)O, helped by evaporation, dissolution and/or photo-oxidation processes. The obtained end product has contents of interesting vegetal nutrients and, mainly, it displays very high germination indices.