Vegetable Processing Research Articles

In Vitro and In Vivo Insights into a Broccoli Byproduct as a Healthy Ingredient for the Management of Alzheimer's Disease and Aging through Redox Biology.

Broccoli has gained popularity as a highly consumed vegetable due to its nutritional and health properties. This study aimed to evaluate the composition profile and the antioxidant capacity of a hydrophilic extract derived from broccoli byproducts, as well as its influence on redox biology, Alzheimer's disease markers, and aging in the Caenorhabditis elegans model. The presence of glucosinolate was observed and antioxidant capacity was demonstrated both in vitro and in vivo. The in vitro acetylcholinesterase inhibitory capacity was quantified, and the treatment ameliorated the amyloid-β- and tau-induced proteotoxicity in transgenic strains via SOD-3 and SKN-1, respectively, and HSP-16.2 for both parameters. Furthermore, a preliminary study on aging indicated that the extract effectively reduced reactive oxygen species levels in aged worms and extended their lifespan. Utilizing broccoli byproducts for nutraceutical or functional foods could manage vegetable processing waste, enhancing productivity and sustainability while providing significant health benefits.

Urban Ecohydrology: Accounting for Sub‐Grid Lateral Water and Energy Transfers in a Land Surface Model

AbstractAlthough urbanization fundamentally alters water and energy cycles, contemporary land surface models (LSMs) often do not include key urban vegetation processes that serve to transfer water and energy laterally across heterogeneous urban land types. Urban water/energy transfers occur when rainfall landing on rooftops, sidewalks, and driveways is redirected to lawns or pervious pavement and when transpiration occurs from branches overhanging impervious surfaces with the corresponding root water uptake takes place in nearby portions of yards. We introduce Noah‐MP for Heterogenous Urban Environments (Noah‐MP HUE), which adds sub‐grid water transfers to the widely used Noah‐MP LSM. We examine how sub‐grid water transfers change surface water and energy balances by systematically increasing the amount of simulated water transfer for four scenarios: tree canopy expanding over pavement (Urban Tree Expansion), tree canopy shifting over pavement (Urban Tree Shift), and directing impermeable runoff onto surrounding vegetation (Downspout Disconnection) or into an engineered pavement (Permeable Pavement). Even small percentages of sub‐grid water transfer can reduce runoff and enhance evapotranspiration and deep drainage. Event‐scale runoff reduction depends on storm depth, rainfall intensity, and antecedent soil moisture. Sub‐grid water transfers also tend to enhance (reduce) latent (sensible) heat. Results highlight the importance not only of fine‐scale heterogeneity on larger scale surface processes, but also the importance of urban management practices that enhance lateral water transfers and water storage–so‐called green infrastructure–as they change land surface fluxes and, potentially, atmospheric processes. This work opens a pathway to directly integrate those practices in regional climate simulations.

Changes in appearance during the spoilage process of fruits and vegetables: Implications for consumer use and disposal

People waste a lot of food, especially at the consumption stage in consumer households. Despite the urgency of this topic, little is known about how consumers use visual inspection to decide to throw away fruits and vegetables at different stages of ripening and spoilage. We presented 366 US consumers with images of a banana, mango, cucumber, and avocado in 5 stages of decay in an online study and we determined how signs of decay affected participants’ consumption, preparation and disposal behaviors. As expected, product attractiveness, freshness, healthiness, and nutritiousness decreased, while the degree of decay, overripeness, and disgust increased over time. The number of people willing to consume the product was linearly related to the perceived proportion of the product affected by decay, while the number of people wanting to cut off bad parts was highest when about 40% of the product was judged to be affected. As time went on, the banana was cooked and mashed more often, while the cucumber was peeled more often. As growing, ripening and decay differ considerably between agricultural products, it is important to take sensory and preparation differences into account when investigating consumption and disposal behaviors.

Editorial: Technological advancements for the processing and preservation of fruits and vegetables

Editorial: Technological advancements for the processing and preservation of fruits and vegetables

Case study of chemical and enzymatic degumming processes in soybean oil production at an industrial plant

The vegetable oil degumming process plays a critical role in refining edible oil. Phospholipids (PL) removal from crude extracted soybean oil (SBO) by the enzymatic degumming process has been investigated in this work. Enzymatic degumming of extracted SBO with microbial phospholipase A1 PLA-1 Quara LowP and Lecitase Ultra enzymes have also been studied comparatively. The main novelty of our work is the use of the enzymatic degumming process on an industrial scale (600 tons a day). Many parameters have been discussed to understand in detail the factors affecting oil losses during the degumming process. The factors such as chemical conditioning (CC) by phosphoric acid 85%, the enzyme dosage mg/kg (feedstock dependent), the enzymatic degumming reaction time, and the characteristics of the plant-processed SBO have been discussed in detail. As a main point, the degummed oil with a phosphorus content of < 10 mg/kg increases yield. Quara LowP and Lecitase Ultra enzymes are not specific for certain phospholipids PL; however, the conversion rate depends on the SBO phospholipid composition. After 4 h, over 99% of Phospholipids were degraded to their lysophospholipid LPL (lysolecithin). The results showed a significant effect of operating parameters and characteristics of different origins of SBO, fatty acids FFA content, Phosphorus content and total divalent metals (Calcium Ca, Magnesium Mg and Iron Fe mg/kg) content on the oil loss. The benefit of using enzymatic degumming of vegetable oils rather than traditional chemical refining is that the enzymatic degumming process reduces total oil loss. This decrease is known as enzymatic yield. The enzymatic degumming also decreases wastewater and used chemicals and running costs; moreover, it enables physical refining by lowering the residue phosphorus to < 10 mg/kg.

Simulations of flaming combustion and flaming-to-smoldering transition in wildland fire spread at flame scale

Our objective in the present study is to provide basic insights into the coupling between external-gas and solid biomass vegetation processes that control the dynamics of flame spread in wildland fire problems. We focus on a modeling approach that resolves processes occurring at vegetation and flame scales, i.e., the formation of flammable vapors due to the thermal degradation of the solid biomass, the subsequent combustion in ambient air, the thermal feedback to the biomass through radiative and convective heat transfer, and the possible transition from flaming combustion (taking place outside of the solid biomass) to smoldering combustion (taking place inside the solid biomass). The capability uses a multiphase combustion framework and treats external-gas processes through a Large Eddy Simulation solver and solid biomass processes through a discrete particle model. The discrete particle model adopts a one-dimensional porous medium formulation, includes descriptions of drying, thermal pyrolysis, oxidative pyrolysis, and char oxidation, as well as a description of the external-gas-to-solid-biomass diffusion of oxygen mass; the discrete particle model thereby provides a treatment of in-depth oxidative processes and allows the simulation of smoldering combustion. The modeling capability is applied to the simulation of fire spread across a surrogate biomass vegetation bed corresponding to a discrete array of cylindrical-shaped, vertically-oriented, pine wood sticks, characterized by a monomodal size distribution, in horizontal flat terrain and under wind-aided conditions. The numerical results demonstrate that the model can simulate successful flaming-to-smoldering transition followed by complete biomass consumption.Novelty and Significance statement:• A new computational model is proposed to simulate wildland fire behavior at high levels of resolution capable of capturing vegetation- and flame-scale phenomena.• Solid biomass vegetation processes are treated using a discrete particle model that features a porous medium formulation and includes a description of in-depth oxygen mass diffusion, and exothermic oxidative pyrolysis and char oxidation reactions.• The computational model is shown to be capable of simulating the transition from flaming to smoldering combustion, often observed in wildland fire spread problems.

The role of the food industry in the development of the agricultural sector

Food Industry has a significant place in the structure of the entire Industry. Depending on the level of economic and agricultural development, as well as the raw material base, about 60-80% of primary agricultural production is processed and prepared for final consumption in the food industry. The term food industry implies the processing of plant, animal and mineral raw materials in order to meet the dietary needs of people. Considering the development of production orientations of the food industry, it can be seen that this industry is expanding its activities beyond the framework of traditional food production and has an increasing focus on the production of a full range of its own raw materials and auxiliary materials; whereby, constantly connecting with other branches and areas, establishing more permanent and stronger integration ties in the process of social reproduction (vertical integration). The processing industry of agricultural raw materials is one of the leading branches of the economy and represents an important resource for the development, not only of the agricultural sector, but also of the RS economy as a whole. However, analyzing this segment of the economy, it can be concluded that the volume, processing, degree of finalization, export and connection in the business chain, etc. is not even remotely used. Observing the trend of realized production in the analyzed period through the basic index of physical volume, it can be concluded that the basic index of 1,11 was achieved in meat production and processing; in fruit and vegetable processing 0,68; dairy production 0,62; manufacturing of mill products 0,98; manufacturing of bakery products and pasta 1,25; manufacturing of any remaining food products 1,02; manufacturing of finished animal feed 1,08 and in the production of beverages 1,25. Based on the analysis and presented data, the strategic goals of the RS food industry would be to increase the level of raw material utilization, revitalization of capacities by modernization of existing capacities, introduction of quality standards, new equipment and new technologies.

PERSONALITY-RELATED DETERMINANTS OF ENTREPRENEURSHIP IN THE LIGHT OF OWN RESEARCH IN THE AGRIBUSINESS SECTOR

The aim of this article is to identify the personality traits that can characterise entrepreneurial people and to determine what they believe to be important in achieving success. Entrepreneurship is defined very broadly in the literature and researchers consider different approaches to this issue. Certainly, being entrepreneurial is a combination of knowledge, passion, hard work and active learning. What is more, in many studies there are hypotheses indicating a correlation between the possession of certain character traits, or even temperament, and the propensity to start a business. In this article, an analysis of the behavioural and attitude approach to entrepreneurship is undertaken, which means that some personal traits and behaviour of the entrepreneurial person are analysed, as well as their perceptions of the issue. A descriptive-inductive method was used, using simple statistical methods. A survey method was used to obtain empirical data. An online survey form was sent to agribusiness entrepreneurs from Poland, the entrepreneurs were randomly selected. The respondents were primarily active in industries such as fruit, vegetable processing, as well as meat. A total of 57 returns were received between January and March 2023. The questionnaire included questions on personality traits that may be conducive to an entrepreneurial attitude, as well as identifying attitudes towards certain management situations. The respondents rated themselves as extroverted and open-minded, confident in their abilities. Most respondents described themselves as sanguines. A number of scientific studies confirm that sanguines and extroverts are the people who are most successful as entrepreneurs. Considering the statements of the respondents, there was a significant difference in the inconsistency of the responses from those labelled choleric and phlegmatic. The most consistent statements were obtained from sanguinis. Sanguinis were the most likely of all respondents to believe in the strength of their predispositions and character traits. Cholerics, due to their explosive nature and not always good decisions, felt that it was appropriate to monotone external factors, as this was the basis for decision-making. As a result of the survey and the literature review, it can be confirmed that entrepreneurial personality traits play an important role when setting up one's own business and also when continuing to manage it, but also an external situation and business environment play an important role in decision-making process. All these factors should be correlated and a good entrepreneur should be able to use his/her strengths to exploit market opportunities. According to the authors of this article, it is necessary to integrate one's personality traits and aptitudes with market information and ongoing monitoring of the industry to achieve success. Key words: personal traits, entrepreneurship, business motives JEL code: Q13, L26

Meta-analysis shows that wild large herbivores shape ecosystem properties and promote spatial heterogeneity.

Megafauna (animals ≥45 kg) have probably shaped the Earth's terrestrial ecosystems for millions of years with pronounced impacts on biogeochemistry, vegetation, ecological communities and evolutionary processes. However, a quantitative global synthesis on the generality of megafauna effects on ecosystems is lacking. Here we conducted a meta-analysis of 297 studies and 5,990 individual observations across six continents to determine how wild herbivorous megafauna influence ecosystem structure, ecological processes and spatial heterogeneity, and whether these impacts depend on body size and environmental factors. Despite large variability in megafauna effects, we show that megafauna significantly alter soil nutrient availability, promote open vegetation structure and reduce the abundance of smaller animals. Other responses (14 out of 26), including, for example, soil carbon, were not significantly affected. Further, megafauna significantly increase ecosystem heterogeneity by affecting spatial heterogeneity in vegetation structure and the abundance and diversity of smaller animals. Given that spatial heterogeneity is considered an important driver of biodiversity across taxonomic groups and scales, these results support the hypothesis that megafauna may promote biodiversity at large scales. Megafauna declined precipitously in diversity and abundance since the late Pleistocene, and our results indicate that their restoration would substantially influence Earth's terrestrial ecosystems.

A hyperspectral deep learning attention model for predicting lettuce chlorophyll content

BackgroundThe phenotypic traits of leaves are the direct reflection of the agronomic traits in the growth process of leafy vegetables, which plays a vital role in the selection of high-quality leafy vegetable varieties. The current image-based phenotypic traits extraction research mainly focuses on the morphological and structural traits of plants or leaves, and there are few studies on the phenotypes of physiological traits of leaves. The current research has developed a deep learning model aimed at predicting the total chlorophyll of greenhouse lettuce directly from the full spectrum of hyperspectral images.ResultsA CNN-based one-dimensional deep learning model with spectral attention module was utilized for the estimate of the total chlorophyll of greenhouse lettuce from the full spectrum of hyperspectral images. Experimental results demonstrate that the deep neural network with spectral attention module outperformed the existing standard approaches, including partial least squares regression (PLSR) and random forest (RF), with an average R2 of 0.746 and an average RMSE of 2.018.ConclusionsThis study unveils the capability of leveraging deep attention networks and hyperspectral imaging for estimating lettuce chlorophyll levels. This approach offers a convenient, non-destructive, and effective estimation method for the automatic monitoring and production management of leafy vegetables.

Divergent trajectories of future global gross primary productivity and evapotranspiration of terrestrial vegetation in Shared Socioeconomic Pathways

Understanding the future trends of carbon and water fluxes between terrestrial ecosystems and the atmosphere is crucial for predicting Earth's climate dynamics. This study employs an advanced numerical approach to project global gross primary productivity (GPP) and evapotranspiration (ET) from 2001 to 2100 under various climate scenarios based on Shared Socioeconomic Pathways (SSPs). To improve predictions of vegetation dynamics, we introduce a novel model (CoLM-PVPM), an enhancement of the Common Land Model version 2014 (CoLM2014), incorporating a prognostic vegetation phenology model (PVPM). Compared to CoLM2014 that relies on satellite-based leaf area index (LAI) inputs, CoLM-PVPM predicts LAI time series using climate variables. Model validation using historical data from 2001 to 2010 demonstrates PVPM in capturing spatiotemporal variations in satellite LAI. Our modeling results indicate that annual averaged LAI and total GPP increase under SSP1–2.6 but decrease under SSP2–4.5, SSP3–7.0, and SSP5–8.5 by 2100. By comparison, annual total ET consistently increases under all SSP scenarios by 2100. Global annual averaged LAI is highly correlated with annual total GPP in all scenarios, while its correlation with annual total ET weakens in SSP2–4.5, SSP3–7.0, and SSP5–8.5. Global annual total vapor pressure deficit (VPD) and precipitation are highly correlated with annual total ET in all scenarios. As emission levels increase, the negative correlation between annual total VPD and GPP strengthens, while the correlation between annual total precipitation and GPP weakens. This research presents an improved model for predicting terrestrial vegetation processes and underscores the importance of low carbon emission scenarios in maintaining carbon-water balances in specific regions.

Traders’ behavioural practices and hygienic status of vegetable and meat processing surfaces in open markets in Benin city, Nigeria

ABSTRACT This study investigates the hygiene status, behavioral practices, and handling of cutting boards for meat and vegetable processing in selected open markets in Benin City. Utilizing a structured questionnaire and laboratory analysis for Escherichia coli and Aeromonas, the research found prevalent Escherichia coli in all samples, with varying concentrations of Aeromonas, more pronounced in vegetable processing areas. Analysis of the questionnaire revealed that 30% of traders leave cutting boards uncovered, 88% clean them before use (52% with water and detergent), and 12% dust boards before use. Furthermore, 80% of meat sellers store leftover meat in refrigerators, while 68% of vegetable sellers store leftovers in the open market. The findings underscore the importance of proper hygienic practices in handling cutting boards to mitigate food contamination risks, urging awareness among traders regarding effective cleaning and storage procedures.

Human intestinal enteroids and predictive models validate the operational limits of sanitizers used for viral disinfection of vegetable process wash water

Vegetables are globally associated with a considerable number of foodborne outbreaks caused by viral infections, specifically human norovirus. In fresh produce industry, washing represents a critical step for food safety as process wash water (PWW) needs to be maintained at appropriate microbial quality to prevent water-mediated cross-contamination. This study aimed to explore the disinfection efficacy of chlorine (free chlorine, FC), chlorine dioxide (ClO2) and peracetic acid (PAA) in PWW against infectious human norovirus and Tulane virus (TV). First, we tested the extent of TV inactivation in baby leaf, bell pepper, and vegetables mix PWW and monitored the viral decay by cell culture. Then, inactivation kinetics were defined for infectious human norovirus exposed to FC, ClO2 and PAA in baby leaves PWW using the human intestinal enteroids (HIE) system. Finally, kinetic inactivation models were fitted to TV reduction and decay of sanitizers to aid the implementation of disinfection strategies. Results showed that >8 log10 human norovirus and 3.9 log10 TV were inactivated by 20 ppm FC within 1 min; and by 3 ppm ClO2 in 1 min (TV) or 5 min (norovirus). PAA treatment at 80 ppm reduced ca. 2 log10 TV but not completely inactivated the virus even after 20 min exposure, while 5 min treatment prevented norovirus replication in HIE. TV inactivation in PWWs was described using an exponential decay model.Taking these data together, we demonstrated the value of applying the HIE model to validate current operational limits for the most commonly used sanitizers. The inactivation kinetics for human norovirus and TV, along with the predictive model described in this study expand the current knowledge to implement post-harvest produce safety procedures in industry settings.

Integrated, multi-scale and multi-objective design of batch food processing plants. Part 2: Application to a mobile fruit and vegetable processing unit

The design of food processing plants that are plug-and-play, reconfigurable, modular, mobile and containerised is a complex task. The "Methodology for the integrated, multi-scale and multi-objective design of systems" can be used to design such systems. This was developed and the various tasks that make it up presented in a previous article by Savoure et al. (2023) (references to be specified). The aim of this study is to assess the potential of this methodology to design a mobile fruit and vegetable processing unit. Firstly, a design support tool was developed to (i) simulate the behaviour and estimate the performances of design solutions, (ii) convert their performances into desirability indices using the decision maker's preferences and (iii) search for the design solution(s) that best satisfy the decision maker's design objectives. The results were then visualised and analysed to ensure that the resulting design solution was a satisfying, feasible and coherent trade-off. This analysis also helped to understand (i) which design variables, models and assumptions drove the design decision the most and (ii) which final products, design objectives, performance indicators and preference models influenced the optimisation process the most. In particular, it showed that one of the products (okra puree) limited the performance of the design solution. Finally, this work increased the level of understanding of the design problem and challenged the preferences of the decision maker.

Exploring the effects of temperature and light availability on the vegetative propagation processes of the non-native species Asparagopsis armata

Widespread generalist species, particularly the non-native invasive ones, are expected to be enhanced by climate change resulting in a biotic homogenization of ecosystems. The red seaweed Asparagopsis armata is a non-native opportunistic species, widely distributed in the European coasts of the North Atlantic, where it has been considered invasive. In this work, we examined the effects of temperature and irradiance on the vegetative propagation process of this species in a laboratory experiment. We considered vegetative propagation due to its implications in the invasion process (as it is considered one of the main sources of recruitment). In gametophytes, the process was characterized through the survival rates of hook-shaped specialized structures and the production and growth of new plantlets from hooks of 1-3cm in length. In tetrasporophytes, the growth and phycobiliprotein contents of previously excised tufts was analyzed. For gametophytes, results revealed how vegetative propagation for this species was conditioned by the low survival rates of hooks once detached from the main thallus. In our experiment, survival probabilities after 30 days of culture were always below 50%. Comparisons among environmental conditions showed lower survival rates under increasing levels of temperature and decreasing levels of irradiance. In fact, mass mortality was detected at 18°C and low irradiance, where almost any hook-shaped fragment survived. Nevertheless, patterns of appearance and growth of plantlets at different temperatures and irradiances were not clear. In the case of tetrasporophytes, only positive growth rates were registered at 15°C and 55-60 µmol/m2/s after 30 days of culture. Higher concentration of phycobiliproteins was detected at higher temperatures during the first days of culture, while not clear patterns were detected at the end. In the light of climate change, understanding these reproduction patterns is necessary in order to adopt better management actions in the future.

Investigation of early symptoms of tomato leaf disorder by using analysing image and deep learning models

Despite rapid population growth, agriculture feeds everyone. To feed the people, agriculture must detect plant illnesses early. Predicting crop diseases early is unfortunate. The publication educates farmers about cutting-edge plant leaf disease-reduction strategies. Since tomato is a readily accessible vegetable, machine learning and image processing with an accurate algorithm are used to identify tomato leaf illnesses. This study examines disordered tomato leaf samples. Based on early signs, farmers may quickly identify tomato leaf problem samples. Histogram Equalization improves tomato leaf samples after re sizing them to 256 × 256 pixels. K-means clustering divides data space into Voronoi cells. Contour tracing extracts leaf sample boundaries. Discrete Wavelet Transform, Principal Component Analysis, and Grey Level Co-occurrence Matrix retrieve leaf sample information.

Tomato plant response to heat stress: a focus on candidate genes for yield-related traits.

Climate change and global warming represent the main threats for many agricultural crops. Tomato is one of the most extensively grown and consumed horticultural products and can survive in a wide range of climatic conditions. However, high temperatures negatively affect both vegetative growth and reproductive processes, resulting in losses of yield and fruit quality traits. Researchers have employed different parameters to evaluate the heat stress tolerance, including evaluation of leaf- (stomatal conductance, net photosynthetic rate, Fv/Fm), flower- (inflorescence number, flower number, stigma exertion), pollen-related traits (pollen germination and viability, pollen tube growth) and fruit yield per plant. Moreover, several authors have gone even further, trying to understand the plants molecular response mechanisms to this stress. The present review focused on the tomato molecular response to heat stress during the reproductive stage, since the increase of temperatures above the optimum usually occurs late in the growing tomato season. Reproductive-related traits directly affects the final yield and are regulated by several genes such as transcriptional factors, heat shock proteins, genes related to flower, flowering, pollen and fruit set, and epigenetic mechanisms involving DNA methylation, histone modification, chromatin remodelling and non-coding RNAs. We provided a detailed list of these genes and their function under high temperature conditions in defining the final yield with the aim to summarize the recent findings and pose the attention on candidate genes that could prompt on the selection and constitution of new thermotolerant tomato plant genotypes able to face this abiotic challenge.

Forecasting greenhouse air and soil temperatures: A multi-step time series approach employing attention-based LSTM network

Greenhouses stand as key infrastructural components in contemporary agriculture, facilitating the perennial availability of vegetables. Harnessing accurate, real-time environmental data, particularly air and soil temperature, is pivotal to promoting the facility’s efficiency in pest and disease alarming and vegetable production. Nevertheless, despite consistent long-term temperature trends, short-term fluctuations prove to be considerably nonlinear, time-lagged, and multivariate-coupled due to the unique microclimate of the greenhouse. Addressing this, we propose a novel short-term multi-step prediction model that assimilates a range of environmental data including air temperature, humidity, soil temperature, and soil moisture content at diverse greenhouse heights. This model utilizes an Attention-LSTM based time series approach to accurately predict multi-step short-term temperature variations within the greenhouse. By employing a modest amount of historical data (approximately 48 h), the model provides future temperature forecasts within a range of 30 to 480 min with high accuracy. When benchmarked against renowned models such as RNN, GRU, and LSTM networks, our proposed models display impressive performance. It achieved R2 values of 0.93, 0.94, 0.95, and 0.86 for 1, 4, 8, and 16-step predictions, respectively, in the domain of air temperature forecasting. The corresponding MSE values stood at 0.42, 0.32, 0.27, and 0.81. In parallel, for soil temperature forecasts, our model recorded R2 values of 0.96, 0.94, 0.92, and 0.89 for 1, 4, 8, and 16-step predictions, respectively, alongside MSE values of 0.36, 0.48, 0.73, and 0.99 for the equivalent steps. To conclude, these results reveal the exceptional predictive aptitude of our model for both air and soil temperature forecasts within greenhouse environments, validating its standing as an effective tool for the optimization of vegetable farming practices. Consequently, our model demonstrates its ability to yield precise predictions of environmental variables within greenhouses, offering crucial early warning mechanisms for the enhancement of vegetable cultivation processes.

Techno-economic assessment of the use of Linear Fresnel Solar Collectors for the supply of heat in traditional fruits and vegetable processing industries in Almeria’s province

This study presents a techno-economic assessment of the use of Linear Fresnel Solar Collectors for the heat supply in traditional fruits and vegetable processing industries in Almeria’s province. This assessment is justified by the high availability of solar radiation in the area under study, the evaluation of complementary energy self-consumption modalities, and the suitability of using local resources for the preservation and improvement of traditional productive activities. The work starts with an identification of the potential user’s needs and their location in the province. Afterward, the solar radiation resources have been estimated as they constitute one of the basic inputs for sizing the proposed systems. Together with the above, representative thermal demands have been considered and different configurations of commercial Linear Fresnel Solar Collector thermal plants aimed to contribute to solarize the analyzed productive processes have been designed and the corresponding techno-economic assessment have been undertaken. Main findings advance the profitability that can be achieved with this technology, reaching, after an optimized integration of the solar plant in the industrial process, a solar fraction between 66-82 % and payback periods of the investment between 6-12 years.

Thymbra capitata L. hydrolate as a washing solution for controlling Listeria monocytogenes and spoilage microorganisms on rocket salad

Ready-to-eat (RTE) vegetables, including fresh-cut ones, are exposed to the risk of the foodborne pathogen Listeria monocytogenes. Nowadays, fresh-cut products are widely consumed because of their convenience. Nevertheless, effective washing treatments are required for their preparation, to maintain freshness and microbiological safety. Currently, natural substances are increasingly demanded as alternatives to traditional synthetic washing agents. Therefore, this study investigates the application of Thymbra capitata hydrolate as washing solution for rocket salad (Eruca sativa) stored at 4 °C for 48 h, to evaluate a potential application both during the production process of fresh-cut vegetables, and also at the domestic level. The hydrolate applied at a concentration of 500 μL/mL for 5 min allowed to reduce L. monocytogenes load of about 1 log CFU/g at each time of analysis, and to determine a significant reduction of microbial groups normally found on rocket salad, particularly total mesophilic and psychrotrophic counts. The treatment showed no negative effects on pH, aw, and colour of the rocket salad. At a sensory level, the differences among control and treated samples were minimally perceived only on the first day of analysis but disappeared over time. Therefore, this alternative washing treatment revealed to counteract L. monocytogenes growth and to help maintaining the quality of rocket salad. Hence, it could be optimized for a concrete application, also considering the enhancement of the antilisterial activity, the sustainability and low cost of the hydrolate, which represents a by-product from the production of essential oils.