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This review explores the agri-food residues of tomato and strawberry as sources of bacteria with bio-protective potential against different pathogenic and spoilage microorganisms for enhancing product shelf life and improving food safety. A comprehensive review of research highlights that Pseudomonas (e.g., P. fluorescens) and Bacillus (e.g., B. subtilis) are relevant genera in the microbiota of both tomato and strawberry plants, as opposed to lactic acid bacteria which are a minority in both plants. Interestingly, those dominant microbial groups have been reported to exhibit potential bio-protective capabilities. This work also discusses different innovative and sustainable methods, such as the use of protective coating or microencapsulation, and the importance of related factors (produce surface properties, bacterial adhesion, etc.) for applying bio-protective cultures in tomato and strawberry, emphasizing the pros and cons. As a conclusion, we suggest that bio-protective cultures are applied at an earlier stage, at crop, exploiting the antimicrobial abilities in the pre- and post-harvest continuum. This bio-protective approach contributes to a more bio-based strategy to sustainably preserve fruits and vegetables from farm to fork.

Listeria monocytogenes, the causative agent of listeriosis, is a relevant pathogen in dry fermented sausages (DFSs), and the application of antilisterial starter cultures is an effective intervention strategy to control the pathogen during DFS production. The effect of factors in relation to DFS formulation and production, NaCl (0–40 g/L), Mn (0.08–0.32 g/L), glucose (0–40 g/L) and temperature (3–37 °C), on the behaviour of L. monocytogenes when cocultured with Latilactobacillus sakei 23K (non-bacteriocinogenic) and CTC494 (bacteriocinogenic) strains was studied through a central composite design in meat simulation media. L. sakei and L. monocytogenes counts, pH, lactic acid production and bacteriocin activity were determined in mono and coculture. The pH decrease and lactic acid production were highly influenced by glucose, while production of sakacin K by L. sakei CTC494 was observed at moderate (10 and 20 °C), but not at the lowest (3 °C) and highest (37 °C), temperatures. Coculture growth had no effect on the acidification and bacteriocin production but inhibited and inactivated L. monocytogenes when L. sakei 23K entered the early stationary phase and when L. sakei CTC494 produced sakacin K. Optimal conditions for achieving a 5-log units reduction of L. monocytogenes were at 20 °C, 20 g/L of NaCl, 0.20 g/L of Mn and 40 g/L of glucose, those highlighting the importance of considering product formulation and fermentation conditions for bioprotective starter cultures application.

Despite significant efforts from government and industry, enteric foodborne diseases continue to pose a substantial public health challenge worldwide [...]

A survey was performed to gather information on the processing steps, conditions, and practices employed by industries processing ready-to-eat (RTE) leafy vegetables in Argentina. A total of seven industries participated in the survey. A cluster analysis of the data obtained was performed to identify homogeneous groups among the participating industries. The data collected were used as inputs of two predictive microbiology models to estimate Salmonella concentrations after chlorine washing, during storage and distribution of final products, and to rank the different practices according to the final estimated Salmonella levels. Six different clusters were identified by evaluating the parameters, methods, and controls applied in each processing step, evidencing a great variability among industries. The disinfectant agent applied by all participating industries was sodium hypochlorite, though concentrations and application times differed among industries from 50 to 200 ppm for 30 to 110 s. Simulations using predictive models indicated that the reductions in Salmonella in RTE leafy vegetables would vary in the range of 1.70–2.95 log CFU/g during chlorine-washing depending on chlorine concentrations applied, washing times, and vegetable cutting size, which varied from 9 to 16 cm2 among industries. Moreover, Salmonella would be able to grow in RTE leafy vegetables during storage and distribution, achieving levels of up to 2 log CFU/g, considering the storage and transportation temperatures and times reported by the industries, which vary from 4 to 14 °C and from 18 to 30 h. These results could be used to prioritize risk-based sampling programs by Food Official Control or determine more adequate process parameters to mitigate Salmonella in RTE leafy vegetables. Additionally, the information gathered in this study is useful for microbiological risk assessments.

Listeria monocytogenes is a foodborne pathogen characterized by its psychrotrophic and ubiquitous nature as well as its ability to survive and proliferate in a wide range of harsh environments and foods [...]

In this study, the growth of six L. monocytogenes strains isolated from different fish products was quantified and modeled in smoked salmon pâté at a temperature ranging from 2 to 20 °C. The experimental data obtained for each strain was fitted to the primary growth model of Baranyi and Roberts to estimate the following kinetic parameters: lag phase (λ), maximum specific growth rate (μmax), and maximum cell density (Nmax). Then, the effect of storage temperature on the obtained μmax values was modeled by the Ratkowsky secondary model. In general, the six L. monocytogenes strains showed rapid growth in salmon pâté at all storage temperatures, with a relatively short lag phase λ, even at 2 °C. The growth behavior among the tested strains was similar at the same storage temperature, although significant differences were found for the parameters λ and μmax. Besides, the growth variations among the strains did not follow a regular pattern. The estimated secondary model parameter Tmin ranged from −4.25 to −3.19 °C. This study provides accurate predictive models for the growth of L. monocytogenes in fish pâtés that can be used in shelf life and microbial risk assessment studies. In addition, the models generated in this work can be implemented in predictive modeling tools and repositories that can be reliably and easily used by the fish industry and end-users to establish measures aimed at controlling the growth of L. monocytogenes in fish-based pâtés.

Invasive alien plants are transforming the landscapes, threatening the most vulnerable elements of local biodiversity across the globe. The monitoring of invasive species is paramount for minimizing the impact on biodiversity. In this study, we aim to discriminate and identify the spatial extent of Acacia dealbata Link from other species using RGB-NIR Sentinel-2 data based on phenological spectral peak differences. Time series were processed using the Earth Engine platform and random forest importance was used to select the most suitable Sentinel-2 derived metrics. Thereafter, a random forest machine learning algorithm was trained to discriminate between A. dealbata and native species. A flowering period was detected in March and metrics based on the spectral difference between blooming and the pre flowering (January) or post flowering (May) months were highly suitable for A. dealbata discrimination. The best-fitted classification model shows an overall accuracy of 94%, including six Sentinel-2 derived metrics. We find that 55% of A. dealbata presences were widely widespread in patches replacing Pinus pinaster Ait. stands. This invasive alien species also creates continuous monospecific stands representing 33% of the presences. This approach demonstrates its value for detecting and mapping A. dealbata based on RGB-NIR bands and phenological peak differences between blooming and pre or post flowering months providing suitable information for an early detection of invasive species to improve sustainable forest management.

MCDM methods are useful to obtain information and generate knowledge useful for decision-making processes in multidisciplinary contexts. Particularly, when conflicts occur, knowledge is the key to start negotiation processes between stakeholders in order to achieve consensual solutions. The planning of protected areas is complex due to many competing uses of natural resources and the involvement of a large number of stakeholders. For the last ten years, participative MCDM methodologies have been carried out efficiently to reduce conflicts and allow to formalize stakeholder's participation in the policy development processes. In this paper, we propose a MCDM participative methodology in three levels that seeks to define management plans in protected areas. This method allows for the definition of management plans based on three levels of criteria that define the use of the natural area and provide a ranking of the main goals according to the stakeholders’ priorities. The model was tested in two Spanish protected areas: Parque Natural de Lago de Sanabria y alrededores and Parque Natural de los Arribes del Duero. Firstly, the individual preferences of the most representative stakeholder groups were collected (Farmers, Business owners, Government and Scientists) and analyzed using two multi-criteria methods: AHP and GP. Moreover, a conflict index between stakeholders’ groups was calculated. Results showed that conservation and development goals are the most preferred to consider for the planning of these areas. Furthermore, the most serious disagreement was found between farmers and scientists and between farmers and government about the wildlife conservation. JEL classification: Q20, C44, O39, O32, O38, Q28, Keywords: Protected areas, MCDM, AHP, Knowledge transfer, GP, Sustainable development

Resilient cities incorporate a social, ecological, and technological systems perspective through their trees, both in urban and peri-urban forests and linear street trees, and help promote and understand the concept of ecosystem resilience. Urban tree inventories usually involve the collection of field data on the location, genus, species, crown shape and volume, diameter, height, and health status of these trees. In this work, we have developed a multi-stage methodology to update urban tree inventories in a fully automatic way, and we have applied it in the city of Pamplona (Spain). We have compared and combined two of the most common data sources for updating urban tree inventories: Airborne Laser Scanning (ALS) point clouds combined with aerial orthophotographs, and street-level imagery from Google Street View (GSV). Depending on the data source, different methodologies were used to identify the trees. In the first stage, the use of individual tree detection techniques in ALS point clouds was compared with the detection of objects (trees) on street level images using computer vision (CV) techniques. In both cases, a high success rate or recall (number of true positive with respect to all detectable trees) was obtained, where between 85.07% and 86.42% of the trees were well-identified, although many false positives (FPs) or trees that did not exist or that had been confused with other objects were always identified. In order to reduce these errors or FPs, a second stage was designed, where FP debugging was performed through two methodologies: (a) based on the automatic checking of all possible trees with street level images, and (b) through a machine learning binary classification model trained with spectral data from orthophotographs. After this second stage, the recall decreased to about 75% (between 71.43 and 78.18 depending on the procedure used) but most of the false positives were eliminated. The results obtained with both data sources were robust and accurate. We can conclude that the results obtained with the different methodologies are very similar, where the main difference resides in the access to the starting information. While the use of street-level images only allows for the detection of trees growing in trafficable streets and is a source of information that is usually paid for, the use of ALS and aerial orthophotographs allows for the location of trees anywhere in the city, including public and private parks and gardens, and in many countries, these data are freely available.

Films formulated with polyvinyl alcohol (PVA) (synthetic biopolymer) were reinforced with lignocellulose nanofibres (LCNF) from residues of vegetable production (natural biopolymer). The LCNF were obtained by mechanical and chemical pre-treatment by 2,2,6,6-tetramethylpiperidine-1-oxyl radical (TEMPO) and added to the polyvinyl alcohol (polymer matrix) with the aim of improving the properties of the film for use in food packaging. The mechanical properties, crystallinity, thermal resistance, chemical structure, antioxidant activity, water barrier properties and optical properties (transparency and UV barrier), were evaluated. In general, with the addition of LCNF, an improvement in the studied properties of the films was observed. In terms of mechanical properties, the films reinforced with 7% LCNF TEMPO showed the best results for tensile strength, Young’s modulus and elongation at break. At the same LCNF proportion, the thermal stability (Tmax) increased between 5.5% and 10.8%, and the antioxidant activity increased between 90.9% and 191.8%, depending on the raw material and the pre-treatment used to obtain the different LCNF. Finally, a large increase in UV blocking was also observed with the addition of 7% LCNF. In particular, the films with 7% of eggplant LCNF showed higher performance for Young’s modulus, elongation at break, thermal stability and UV barrier. Overall, results demonstrated that the use of LCNF generated from agricultural residues represents a suitable bioeconomy approach able to enhance film properties for its application in the development of more sustainable and eco-friendly food packaging systems.

The installation of research or permanent plots is a very common task in growth and forest yield research. At young ages, tree height is the most commonly measured variable, so the location of individuals is necessary when repeated measures are taken and if spatial analysis is required. Identifying the coordinates of individual trees and re-measuring the height of all trees is difficult and particularly costly (in time and money). The data used comes from three Pinus pinaster Ait. and three Pinus radiata D. Don plantations of 0.8 ha, with an age ranging between 2 and 5 years and mean heights between 1 and 5 m. Five individual tree detection (ITD) methods are evaluated, based on the Canopy Height Model (CHM), where the height of each tree is identified, and its crown is segmented. Three CHM resolutions are used for each method. All algorithms used for individual tree detection (ITD) tend to underestimate the number of trees. The best results are obtained with the R package, ForestTools and rLiDAR. The best CHM resolution for identifying trees was always 10 cm. We did not detect any differences in the relative error (RE) between Pinus pinaster and Pinus radiata. We found a pattern in the ITD depending on the height of the trees to be detected: the accuracy is lower when detecting trees less than 1 m high than when detecting larger trees (RE close to 12% versus 1% for taller trees). Regarding the estimation of tree height, we can conclude that the use of the CHM to estimate height tends to underestimate its value, while the use of the point cloud presents practically unbiased results. The stakeout of forestry research plots and the re-measurement of individual tree heights is an operation that can be performed by UAV-based LiDAR scanning sensors. The individual geolocation of each tree and the measurement of heights versus pole and/or hypsometer measurement is highly accurate and cost-effective, especially when tree height reaches 1–1.5 m.

A biodegradable packaging film containing cellulose nanofibers from olive tree pruning, a by-product of olives production, was obtained using a solvent casting method. Nanocellulose was added to polyvinyl alcohol (PVA) to enhance the technological properties of the composite film as food packaging material. Nanocellulose was obtained from unbleached and bleached pulp through a mechanical and TEMPO pretreatment. Crystalline and chemical structure, surface microstructure, UV and gas barrier, optical, mechanical and antioxidant properties, as well as thermal stability were evaluated. Regarding optical properties, the UV barrier was increased from 6% for the pure PVA film to 50% and 24% for unbleached and bleached nanocellulose, respectively. The antioxidant capacity increased significantly in unbleached mechanical nanocellulose-films (5.3%) compared to pure PVA film (1.7%). In terms of mechanical properties, the tensile strength of the 5% unbleached mechanical nanocellulose films was significantly improved compared to the pure PVA film. Similarly, the 5% nanocellulose films had increased the thermal stability and improved barrier properties, reducing water vapor permeability by 38–59% and presenting an oxygen barrier comparable to aluminum layer and plastic films. Our results support the use of the developed films as a green alternative material for food packaging.

ABSTRACT: Decision-making in protected areas is often difficult due to an unclear definition of management objectives and indicators for their monitoring. This is frequently related to the coexistence of systems of protected areas at national and regional levels for which management objectives are ambiguous or that are not directly related to protected areas classification standards. In this study, we proposed a participative model based on PROMETHEE II to find consensual protected areas categories based on IUCN framework. This model involved the stakeholder’s assessments of management objectives in a protected area and their aggregation based on distance comparisons with objectives of international protected areas standards. The model was tested in the Albufera de Valencia Natural Park, a strongly human-modified wetland located in Eastern Spain and it allowed the identification of consensual management priorities and the IUCN category V as the equivalent international protected area category for this regional protected area.

Most of the foodborne microbial diseases are linked to foods of animal origin such as milk, meat, and poultry. Nowadays, the presence of multi-drug resistant (MDR) pathogens in foods is becoming an increasingly public health concern worldwide due to the overuse of antimicrobial drugs in animal feed. MDR pathogens can enter the food chain by posing a significant risk to both animals and consumers. MDR pathogens causing infections are untreatable due to their resistance to various antibiotics, primarily cephalosporin and carbapenems and to their extended-spectrum beta-lactamase (ESBL)-producing capability. In addition, foods of animal origin and food-related environments can be likely vehicles for spreading of multi-drug resistance genes, which accelerates the thriving of global antibiotic resistance. This paper reviews the role of foods of animal origin as a vehicle for MDR pathogens, stressing the contribution of food processes, environments, and storage conditions in dissemination and reduction of antimicrobial resistances (AMRs). Controlling the growth of MDR microorganisms and limiting the transmission/expression of AMR genes in food ecosystems could be an effective mitigation strategy, putting the focus on food processes as a part of the solution for AMR in foods. Bioprotective cultures are also a promising and environmentally friendly technology to reduce the incidence of MDR pathogens, though caution is taken as microbial starters and probiotics can also carry AMR. Finally, applying Whole Genome Sequencing (WGS) and predictive microbiology, within a Risk Assessment framework, is key to get insight into those mechanisms and conditions along the food chain favoring or reducing AMR.

Olea europaea L. leaves constitute a source of bioactive compounds with recognized benefits for both human health and technological purposes. In the present work, different extracts from olive leaves were obtained by the application of two extraction methods, Soxhlet and microwave-assisted extraction (MAE), and six solvents (distilled water, ethanolic and glycerol mixtures solvents). MAE was applied under 40, 60 and 80 °C for 3, 6.5 and 10 min. The effect of the extraction method, solvent and treatment factors (the latter in MAE) on the total phenol content (TPC), the antioxidant activity (AA) and the phenolic profile of the extracts were all evaluated. The extracts showed high values of TPC (up to 76.1 mg GAE/g DW) and AA (up to 78 mg TE/g DW), with oleuropein being the most predominant compound in all extracts. The Soxhlet extraction method exhibited better yields in TPC than in MAE, although both methods presented comparable AA values. The water MAE extract presented the strongest antimicrobial activity against five foodborne pathogens, with minimum inhibitory concentration (MIC) values ranging from 2.5 to 60 mg/mL. MAE water extract is proposed to be exploited in the food and nutraceutical industry in the frame of a sustainable economy.

There is an increasing interest in forest biomass for energy throughout Europe, which is seen as a way of promoting forest mobilization and economic development locally, in particular in regions where forest biomass is available but its use is limited by lack of demand. This study was conducted to define, evaluate and select viable forest industry scenarios to increasing forest mobilisation in the North of Portugal using AppTitude®, a Forest Management Decision Support Systems (FMDSS) considering spatially explicitly supply (biomass growth and yield), demand (industry), and supply–demand interactions (markets). The protocol followed combined a set of indicators of sustainable forest management to guide the selection of the best industry solutions in terms of location, dimension, forest biomass and other variables defined as objectives. The simulations allowed the selection of a small set of industry scenarios compatible with an existing plant outside the study area, increasing wood mobilization, preventing overexploitation and competition among industries but increasing value and price of forest biomass. The results of the application of this FMDSS showed that introducing new biomass plants in the region will increase sustainable forest mobilization and related local development. AppTitude® revealed to be a powerful and reliable tool to assist forest planning.

The aim of this study was to model the growth and survival behaviour of Salmonella Reading and endogenous lactic acid bacteria on fresh pre-cut iceberg lettuce stored under modified atmosphere packaging for 10 days at different temperatures (4, 8 and 15 °C). The Baranyi and Weibull models were satisfactorily fitted to describe microbial growth and survival behaviour, respectively. Results indicated that lactic acid bacteria (LAB) could grow at all storage temperatures, while S. Reading grew only at 15 °C. Specific growth rate values (μmax) for LAB ranged between 0.080 and 0.168 h−1 corresponding to the temperatures 4 and 15 °C while for S. Reading at 15 °C, μmax = 0.056 h−1. This result was compared with published predictive microbiology models for other Salmonella serovars in leafy greens, revealing that predictions from specific models could be valid for such a temperature, provided they were developed specifically in lettuce regardless of the type of serovars inoculated. The parameter delta obtained from the Weibull model for the pathogen was found to be 16.03 and 18.81 for 4 and 8 °C, respectively, indicating that the pathogen underwent larger reduction levels at lower temperatures (2.8 log10 decrease at 4 °C). These data suggest that this Salmonella serovar is especially sensitive to low temperatures, under the assayed conditions, while showcasing that a correct refrigeration could be an effective measure to control microbial risk in commercial packaged lettuce. Finally, the microbiological data and models from this study will be useful to consider more specifically the behaviour of S. Reading during transport and storage of fresh-cut lettuce, elucidating the contribution of this serovar to the risk by Salmonella in leafy green products.

Horticultural plant residues (tomato, pepper, and eggplant) were identified as new sources for lignocellulose nanofibers (LCNF). Cellulosic pulp was obtained from the different plant residues using an environmentally friendly process, energy-sustainable, simple, and with low-chemical reagent consumption. The chemical composition of the obtained pulps was analyzed in order to study its influence in the nanofibrillation process. Cellulosic fibers were subjected to two different pretreatments, mechanical and TEMPO(2,2,6,6-Tetramethyl-piperidin-1-oxyl)-mediated oxidation, followed by high-pressure homogenization to produce different lignocellulose nanofibers. Then, LCNF were deeply characterized in terms of nanofibrillation yield, cationic demand, carboxyl content, morphology, crystallinity, and thermal stability. The suitability of each raw material to produce lignocellulose nanofibers was analyzed from the point of view of each pretreatment. TEMPO-mediated oxidation was identified as a more effective pretreatment to produce LCNF, however, it produces a decrease in the thermal stability of the LCNF. The different LCNF were added as reinforcing agent on recycled paperboard and compared with the improving produced by the industrial mechanical beating. The analysis of the papersheets’ mechanical properties shows that the addition of LCNF as a reinforcing agent in the paperboard recycling process is a viable alternative to mechanical beating, achieving greater reinforcing effect and increasing the products’ life cycles.

Controlling vegetation fuels around human settlements is a crucial strategy for reducing fire severity in forests, buildings and infrastructure, as well as protecting human lives. Each country has its own regulations in this respect, but they all have in common that by reducing fuel load, we in turn reduce the intensity and severity of the fire. The use of Unmanned Aerial Vehicles (UAV)-acquired data combined with other passive and active remote sensing data has the greatest performance to planning Wildland-Urban Interface (WUI) fuelbreak through machine learning algorithms. Nine remote sensing data sources (active and passive) and four supervised classification algorithms (Random Forest, Linear and Radial Support Vector Machine and Artificial Neural Networks) were tested to classify five fuel-area types. We used very high-density Light Detection and Ranging (LiDAR) data acquired by UAV (154 returns·m−2 and ortho-mosaic of 5-cm pixel), multispectral data from the satellites Pleiades-1B and Sentinel-2, and low-density LiDAR data acquired by Airborne Laser Scanning (ALS) (0.5 returns·m−2, ortho-mosaic of 25 cm pixels). Through the Variable Selection Using Random Forest (VSURF) procedure, a pre-selection of final variables was carried out to train the model. The four algorithms were compared, and it was concluded that the differences among them in overall accuracy (OA) on training datasets were negligible. Although the highest accuracy in the training step was obtained in SVML (OA=94.46%) and in testing in ANN (OA=91.91%), Random Forest was considered to be the most reliable algorithm, since it produced more consistent predictions due to the smaller differences between training and testing performance. Using a combination of Sentinel-2 and the two LiDAR data (UAV and ALS), Random Forest obtained an OA of 90.66% in training and of 91.80% in testing datasets. The differences in accuracy between the data sources used are much greater than between algorithms. LiDAR growth metrics calculated using point clouds in different dates and multispectral information from different seasons of the year are the most important variables in the classification. Our results support the essential role of UAVs in fuelbreak planning and management and thus, in the prevention of forest fires.

With the aim of identifying new sources to produce cellulose nanofibers, olive tree pruning biomass (OTPB) was proposed for valorization as a sustainable source of cellulose. OTPB was subjected to a soda pulping process for cellulose purification and to facilitate the delamination of the fiber in the nanofibrillation process. Unbleached and bleached pulp were used to study the effect of lignin in the production of cellulose nanofibers through different pretreatments (mechanical and TEMPO-mediated oxidation). High-pressure homogenization was used as the nanofibrillation treatment. It was observed that for mechanical pretreatment, the presence of lignin in the fiber produces a greater fibrillation, resulting in a smaller width than that achieved with bleached fiber. In the case of TEMPO-mediated oxidation, the cellulose nanofiber characteristics show that the presence of lignin has an adverse effect on fiber oxidation, resulting in lower nanofibrillation. It was observed that the crystallinity of the nanofibers is lower than that of the original fiber, especially for unbleached nanofibers. The residual lignin content resulted in a greater thermal stability of the cellulose nanofibers, especially for those obtained by TEMPO-mediated oxidation. The characteristics of the cellulose nanofibers obtained in this work identify a gateway to many possibilities for reinforcement agents in paper suspension and polymeric matrices.

The Clostridium sp. is a large group of spore-forming, facultative or strictly anaerobic, Gram-positive bacteria that can produce food poisoning. The table olive industry is demanding alternative formulations to respond to market demand for the reduction of acidity and salt contents in final products. while maintaining the appearance of freshness of fruits. In this work, logistic regression models for non-adapted and acid-adapted Clostridium sp. strains were developed in laboratory medium to study the influence of pH, NaCl (%) and time on the probability of germination of their spores. A Clostridium sporogenes cocktail was not able to germinate at pH < 5.0, although the adaptation of the strains produced an increase in the probability of germination at 5.0−5.5 pH levels and 6% NaCl concentration. At acidic pH values (5.0), the adapted strains germinated after 10 days of incubation, while those which were non-adapted required 15 days. At pH 5.75 and with 4% NaCl, germination of the adapted strains took place before 7 days, while several replicates of the non-adapted strains did not germinate after 42 days of storage. The model was validated in natural green olive brines with good results (>81.7% correct prediction cases). The information will be useful for the industry and administration to assess the safety risk in the formulation of new processing conditions in table olives and other fermented vegetables.

Nowadays, microorganisms with probiotic or antimicrobial properties are receiving major attention as alternative resources for food preservation. Lactic acid bacteria are able to synthetize compounds with antimicrobial activity against pathogenic and spoilage flora. Among them, Lactobacillus plantarum ATCC 8014 has exhibited this capacity, and further studies reveal that the microorganism is able to produce bacteriocins. An assessment of the growth of L. plantarum ATCC 8014 at different conditions becomes crucial to predict its development in foods. A response surface model of the growth rate of L. plantarum was built in this study as a function of temperature (4, 7, 10, 13, and 16°C), pH (5.5, 6.0, 6.5, 7.0, and 7.5), and sodium chloride (0, 1.5, 3.0, 4.5, and 6.0%) and sodium lactate (0, 1, 2, 3, and 4%) concentrations. All the factors were statistically significant at a confidence level of 90% (p

Aim of the study: To introduce and describe ApkFor©, an Android Open-Source Project to generate basic mobile applications to transfer forest growth and yield models for even-aged stands. Material and methods: ApkFor© was developed in Android Studio using Java and XML languages integrating transition functions for dominant height and basal area, equations of tree and stand volume and structural models. The project was applied and validated for Pinus pinaster Ait. stands in Northeastern Portugal. Main results: ApkFor© is an Open-Source project freely available from the Source Force repository: https://sourceforge.net/projects/apkfor/, licensed under the GNU General Public License version 3.0 (GPLv3). Research highlights: This project has been designed and created to provide the code and promote its re-use and modification to develop simple growth and yield mobile applications in Android, and with it to transfer research results of forest modelling to forest managers. Moreover, an example of application of the compiled code is provided using the models of Pinus pinaster Ait. previously validated for the Northeastern Region of Portugal.

The planning of protected rural areas is usually defined by institutional decision-makers without considering the preferences of the local communities that live on the land, which frequently leads to conflicts in land management. This paper proposes a voting method based on the Borda count to rank the management goals of a protected rural area. The method was applied in a Spanish-Portuguese reserve called Iberian Plateau with the aim of collecting the preferences of institutional decision-makers (government and scientists) and rural landowners (farmers and businesspersons). Regarding the conservation and development objectives, the results show differences in spatial planning when only the preferences of institutional decision-makers are taken into consideration, as opposed to when the preferences of landowners are included within the analysis.

Diet is an important factor related to the development of numerous diseases. In developing countries like Ecuador, this aspect is not considered as priority however, the study of the incidence of certain diet-related diseases could help to assess consumption habits of a country from a Public Health perspective and support national nutrition policies and programs. The objective the present study is to investigate the mortality rate of certain diet-related diseases in Ecuador and its possible relationship with Ecuadorian consumption habits. For that, mortality rates (2001-2008) associated with five different disease groups related to dietary factors (cancer of colon, cerebrovascular diseases, cardiovascular diseases, diabetes mellitus and liver diseases) were collected, analyzed and compared to consumption patterns in Ecuador. According to results, Ecuador has a low level of cancer of colon in comparison with developed countries (e.g. Spain). The group with the highest number of deaths corresponded to cardiovascular diseases followed by cerebrovas-cular diseases. The mortality study per province revealed that Amazonian provinces showed few deaths in relation to other provinces in Ecuador. This could be due to different factors including fails in the disease surveillance information systems, environmental factors and consumption patterns. In this sense, further investigation on native products consumption such as "chontaduro" might help to find valuable foods contributing to healthier Ecuadorian diet. These results, though preliminary, evidence that a major effort should be made by national and international organisations to collect data on consumption patterns and nutritional aspects of the Ecuadorian population in order to better support the development of effective food security and nutrition policies.

Aim of the study: To introduce and describe FlorNExT®, a free cloud computing application to estimate growth and yield of maritime pine (Pinus pinaster Ait.) even-aged stands in the Northeast of Portugal (NE Portugal). Area of study: NE Portugal. Material and methods: FlorNExT® implements a dynamic growth and yield modelling framework which integrates transition functions for dominant height (site index curves) and basal area, as well as output functions for tree and stand volume, biomass, and carbon content. Main results: FlorNExT® is freely available from any device with an Internet connection at: http://flornext.esa.ipb.pt/. Research highlights: This application has been designed to make it possible for any stakeholder to easily estimate standing volume, biomass, and carbon content in maritime pine stands from stand data, as well as to estimate growth and yield based on four stand variables: age, density, dominant height, and basal area. FlorNExT® allows planning thinning treatments. FlorNExT® is a fundamental tool to support forest mobilization at local and regional scales in NE Portugal. Keywords: forest management; maritime pine; forest modelling; knowledge transfer tool.

Aim of study: To present the software utilities and explain how to use EucaTool®, a free cloud computing application developed to estimate the growth and production of seedling and clonal blue gum (Eucalyptus globulus Labill.) plantations in Galicia (NW Spain).Area of study: Galicia (NW Spain).Material and methods: EucaTool® implements a dynamic growth and production model that is valid for clonal and non-clonal blue gum plantations in the region. The model integrates transition functions for dominant height (site index curves), number of stems per hectare (mortality function) and basal area, as well as output functions for tree and stand volume, biomass and carbon content.Main results: EucaTool® can be freely accessed from any device with an Internet connection, from http://app.eucatool.com. In addition, useful information about the application is published on a related website: http://www.eucatool.com.Research highlights: The application has been designed to enable forest stakeholders to estimate volume, biomass and carbon content of forest plantations from individual trees, diameter classes or stand data, as well as to estimate growth and future production (indicating the optimal rotation age for maximum income) by measurement of only four stand variables: age, number of trees per hectare, dominant height and basal area.Keywords: forest management; biomass; seedling; clones; blue gum; forest tool.

Identyfikacja mikroorganizmów, głównie identyfikacja bakterii i wykrywanie patogenów jest niezwykle istotnym zagadnieniem w wielu dziedzinach mikrobiologii takich jak: diagnozowanie infekcji czy ochrona żywności. W tym artykule dokonano identyfikacji filtracji z pomocą bliskiej podczerwieni (długość fali od 900 nm do 2500 nm). Sprawdzono różne techniki klasyfikacji (CVA, ANN …). Osiągnięto 100% dokładność na ograniczonej liczbie próbek. Spektroskopia bliskiej podczerwieni (NIR) wydaje się być właściwą metodą do szybkiej identyfikacji bakterii. Metoda ta może być użyta do zabezpieczania żywności, w mikrobiologii, w walce przeciw bio-terroryzmowi, a także w badaniach środowiska.

Abstract The objective of this opinion was to determine if any wild caught fish species, originating from specific fishing grounds and consumed in the EU/EFTA could be considered free of zoonotic parasites. In this Opinion the term ‘fishery products’ only refers to fresh finfish. As there are multiple fish species and numerous potential parasites, Anisakis sp. was used as an indicator of zoonotic parasites in marine areas. This parasite species is particularly suited as it is common in marine environments, capable of infecting multiple fish species and is the subject of the majority of published studies. On the rare occasion where Anisakis sp. data were not available, or all tests were negative, other parasites such as Contracaecum osculatum (s.l.) and/or Phocanema spp. were considered. In freshwater systems, all zoonotic parasites were investigated. Consumption, import and landing data were used to determine the most relevant fish species and, where possible, the source fishing areas were identified. The most commonly consumed wild caught fish species in the EU/EFTA include tuna, cod, Alaskan pollock, hake, herring, sardines, mackerel, trout and saithe. Although the majority of these fish are caught in the Atlantic Ocean, the Mediterranean and the Black Sea (37) as well as several areas in the Indian Ocean, imported fish may originate from any global fishing areas, with the exception of Antarctica. Based on the data, at least one zoonotic parasite has been reported in at least one fish species in each of the FAO marine fishing areas. Thus, due to relative low fish host specificity of the zoonotic parasites, the panel concluded that all wild caught fish species may be exposed to and infected with zoonotic parasites. The same applies to freshwater fishing areas, with many areas having multiple studies reporting the presence of zoonotic parasites in the wild caught fish species.