The progress of fermentation, an important step in spirit production, needs to be monitored regularly to detect possible faults. Automated monitoring of fermentation, however, is often limited to only a few parameters of the mash such as, and mainly, its temperature. With the advance of sensor technology and data analytics, various solutions to automated fermentation monitoring emerged, mainly for the beer and wine industry, however, these are not yet critically evaluated and compared. Thus, scientific articles on automated monitoring of alcoholic fermentation are reviewed and evaluated here according to the type of sensors used, the type of fermented material, and the reproducibility and feasibility of the presented solutions. Possible data analytics methods to utilize are introduced and their pros and cons are discussed. A critical evaluation from scientific and industrial perspectives is provided with prospects for the distilling industry where mashes of various states of matter, inhomogeneity and viscosity can appear. Key findings and conclusions of this review are: Electronic nose and electronic tongue biosensors are a promising direction in the area. A publicly available database on recorded data from e-nose and e-tongue as well as other sensors on fermentation monitoring is needed but still missing. Current solutions on automated fermentation monitoring are rather isolated studies, conducted in laboratories, yet to be evaluated and tested in industrial environments. The use of machine learning techniques in these studies, in general, does not comply with the well-established standards in data science and artificial intelligence.

One of the key issues in decision problems is the selection and use of the appropriate response scale. In this paper verbal expressions are converted into numerical scales for a subjective problem instance. The main motivation for our research was that verbal values in decision tasks are often mechanically converted into numbers, which thus typically do not fully represent the respondent's true evaluation. In our experiment, we conducted a color selection test with 462 subjects by testing six colors (red, green, blue, magenta, turquoise, yellow) defined from the Color Namer database on color-calibrated tablets in ISO standardized sensory test booths of a sensory laboratory. The colors were evaluated both in a pairwise comparison matrix (indirect ranking with four-item verbal category scale) and on a direct scoring basis. We determined scales that provide the closest results on average and individually to the direct scoring, based on the eigenvector and the logarithmic least squares methods. All results show that the difference between verbal expressions is much smaller than the one used by most of the common numerical scales. The respondents' inconsistency was also analyzed, even with a repeated question regarding their preference between a given pair of colors. It is shown that most decision makers answer fairly similarly for the second time, but there can be significant (even ordinal) differences. The respondents whose answers are further from the original tends to be more inconsistent in general.

The advancement of controlled environment agriculture (CEA) has amplified the importance of light quality in crop production, particularly for high-value horticultural crops like tomato (Solanum lycopersicum L.). The central research question is to analyse tomato targeted LED light settings focusing on seedling production, plant production and protection, nutritional value, tomato-specific light measurement, design, application, recommendations for growers, and future perspectives. This review synthesizes the latest technological developments in LED grow light applications for tomato cultivation, with a focus on light quality (spectral composition), light quantity (intensity), and light timing (photoperiod). In tomato cultivation, light intensity typically ranges from 200 to 400 mu mol center dot m-2 center dot s-1 with a 16-20 h photoperiod, supporting healthy early growth, while lower levels from 100 to 150 mu mol center dot m-2 center dot s-1 can sustain photosynthesis during seedling grafting. With an 18 h photoperiod, adding 2 h of night lighting further improved seedling health, biomass, and root activity. Emphasis is placed on how these parameters influence physiological processes and the accumulation of phytonutrients, while also addressing promising lighting strategies with roles in plant protection and post-harvest optimization. The highest lycopene and beta-carotene levels were obtained under a B:G:R ratio of 58:30:12 (460, 525, 630 nm) at 150 & micro;mol center dot m-2 center dot s-1. Blue light from 405 to 462 nm limits Botrytis spoilage, and UV-A/UV-C suppress Fusarium, Oidium, Penicillium. Key aspects of light design, monitoring, and measurement are also discussed, with emphasis on fresh tomato production. The most important light factors in different growing stages of tomato were identified. Coherences of light spectra, intensity, duration, LED-plant placement (geometry) and homogeneity aspects with productionbiological traits in fresh tomato CEA experiments were summarized. Plant protection LED applications were explored in depth. Future trends related to tomato CEA production driven by networked sensor systems (internet of things, IoT) based automated systems are discussed as well. Finally, LED light specific recommendations were proposed for tomato growers and consultants.

Pyrrolizidine alkaloids (PAs) are frequently occurring phytotoxins in honeys, however, representative data are limited to a few countries. In the current research, a citrate-buffered QuEChERS-based multicomponent HPLC-MS/MS method was validated for honey matrix, using a triple quadrupole mass analyzer. The greenness of the methodology was assessed using the Analytical GREEnness (AGREE) metric approach. Recovery and precision were evaluated at four concentration levels (1.5, 4.0, 8.0 and 20.0 & micro;g/kg). Satisfactory results were obtained for LOD (0.13-2.50 & micro;g/kg), LOQ (1.50-7.50 & micro;g/kg), linearity (0.984 2<0.999), and intra-day repeatability (<20%). Considerable matrix suppression was observed for certain analytes, which necessities matrix matched calibration. Recoveries exceeded 120% for three analytes, which were therefore excluded from validation. The method was applied to 50 Hungarian honeys from various botanical and geographical origins. Echimidine was detected in the majority of samples, mostly in trace amounts. Lycopsamine-type and senecionine-type PAs also occurred frequently at varying concentrations. Palynological evaluation revealed the presence of pollen from PA-producing plants in monofloral honeys, but pollen composition was not closely related to PA contamination. Results suggest that average honey consumption does not pose a significant food safety risk to adults. However, regular high intake of contaminated honeys may be a concern.

In Budapest, despite the city's high population density, valuable plant communities persist in various isolated fragments. Since 2006, restoration work has been ongoing in the Újpest Sea buckthorn Nature Conservation Area to preserve the open sandy grassland (Festucetum vaginatae), which provides habitat for Hippophae rhamnoides. The aim of this study was to assess the changes of vegetation after shrub removal. The effects of these interventions were studied in seven sample sites, each subjected to shrub removal in different years, by examining coenological data from 10 permanent quadrats per site. Non-parametric statistical method was used for multiple pairwise comparisons to analyse the cover values of Festuca species, and the distribution dynamics of them was characterised with the type of trend line. While in the undisturbed control site, Festuca vaginata was the dominant, Festuca pseudovaginata and Festuca tomanii emerged as the dominant grass species in the early phase in the joining sites, where shrubs have been eradicated. Simultaneously, gradually disappearing weeds were detected. Typical species of sandy grasslands appeared in the treated areas as early as the first phase. Our results have confirmed that, in the presence of a close propagule source, Pannonian open sand steppe is capable of regeneration when invasive woody plants are removed, and ongoing maintenance is carried out. Along the restoration timeline, the abundance of three dominant Festuca species, characteristic species and weeds proved to be reliable indicators of restoration success.

The Sniffin’ Sticks test is evaluated by summing the scores of threshold, discrimination, and identification subtests to establish an olfactory diagnosis (anosmia, hyposmia, normosmia). However, variations in thresholds, ranges and inconsistencies have been observed. Statistical analyses (distributions, quantiles), protocol simulation, and implementations of the Sniffin’ Sticks test were conducted. This study contributes a statistical revision: determining a cut-off point for the total TDI score, optimising the number of alternatives in the identification subtest, and equalising correct responses (frequency, balanced in time, subsequent pairs). The upper score threshold used to diagnose anosmia is lower than the typical first-order error thresholds applied in comparable assessments (anosmia ≤ 16.75 points, hyposmia ≥ 17 points at 90% confidence level). In the culturally adapted 16-pen Sniffin’ Sticks identification tests, the frequency of correct responses was aligned with that of the original test. However, the equalisation of the frequency of adjacent correct response pairs and the temporal occurrence of correct responses was not met in any test. The order of all correct answers that simultaneously satisfied all three matching conditions was determined. The practical significance of the results is that the recommended protocol of the Sniffin’ Sticks test system can be implemented in clinical practice with minimal modification.

(1) The primary objective was to determine whether, within this taxonomically challenging group, the closely related European species and their subspecies exhibit distinct inflorescence characters that allow for unambiguous differentiation. This study focuses on two closely related species within the genus Hierochloë: Hierochloë hirta (Schrank) Borbás and Hierochloë odorata (L.) Beauv. (2) For four subspecies, data were collected from 15 inflorescences each, while for one subspecies, 10 inflorescences were examined. From each inflorescence, six spikelets were selected. The statistical analyses were non-parametric methods, the Kruskal–Wallis test, and principal component analysis. (3) Morphological traits showed consistent patterns within each subspecies, indicating their suitability for taxonomic differentiation. The most reliable diagnostic traits were the length of the outer glume of the first flower and the lengths of the awns. (4) The study concludes that while some subspecies can be clearly distinguished based on inflorescence morphology, no single trait is sufficient to completely separate all taxa. The authors recommend recognizing Hierochloë odorata subsp. praetermissa as a subspecies rather than a distinct species and affirm the validity of the species names Hierochloë hirta and Hierochloë odorata.

The role of customized DLI maps in optimizing lighting strategies for controlled and open field crop production is gradually increasing, resulting in the creation of specialized DLI maps for more countries. Daily Light Integral (DLI) [mol·m−2·d−1] is an accumulation or integration of quantum flux measurements per second over one day (24 h), its spatial distribution will be visualized on maps. Our research objectives are: (1) to create 1 mol·m−2·d−1 resolution Slovakia DLI map and explore the seasonal and regional characteristics, (2) to create 2 and 5 mol·m−2·d−1 resolution DLI maps to show how the spatial resolution capabilities change in a local (country) and regional (Europe) context, (3) to summarize and compare the seasonal patterns for mountainous and lowland areas with characteristic DLI values (minimum, maximum, average, range). The current study shows how much light was available at different times of the year using monthly DLI threshold maps for 1 mol·m−2·d−1, 2 mol·m−2·d−1, and 5 mol·m−2·d−1. The data present a clear seasonal and regional pattern. In the seasons, the monthly total DLI maximum and minimum differences reached: 21 DLI units (38–17 mol·m−2·d−1) in spring, 17 DLI units (46–17 mol·m−2·d−1) in summer, 20 DLI units (26–6 mol·m−2·d−1) in autumn, 9 DLI units (13–4 mol·m−2·d−1) in winter. Slovakia is an East–West oriented country, which explains the use of the 1 mol·m−2·d−1 DLI map. DLI maps are of particular importance for plant cultivation technologies that are sensitive to the amount of light and its temporal and spatial distribution, such as greenhouse vegetables or certain fruit species. Spatial DLI data support lighting strategy and design, supplemented by lighting, shading management, and photosynthetically active radiation (PAR) availability and efficient use.

Consumer sensory testing is the basis for determining directions of product development in the food industry. However, while compliance assessment by trained and expert assessors is well developed, few information is available on testing consumer consistency. Therefore, we provide a statistical framework to rank assessors and attributes according to the level of inconsistency, as well as to identify inconsistent assessors, based on Kendall rank correlation coefficients. The detection of (in)consistency requires evaluations on two connected scales. The suggested approach is illustrated by data from sensory tests of biscuits enriched with three pollens at different levels. 100 consumers evaluated the samples on two different scales (nine category monotonic ascending hedonic response scale, five-category just about right (JAR) intensity scale). The 88 consistent assessors are found using a wider range of both the liking scale and JAR scale than the 12 inconsistent assessors whose evaluations do not have a significantly negative rank correlation. Future consumer tests are recommended to include multiple scales. The proposed framework aims to identify and even filter out the potentially biasing inconsistent evaluations. Questions on attributes leading to highly inconsistent responses should be reconsidered in future sensory tests on the same food product.

The Daily Light Integral (DLI) maps of Portugal are decision-support tools to provide objective assessments of light availability for plants. These maps allow for the analysis of the spatial and seasonal distribution patterns of photosynthetically active radiation (PAR, 400-700 nm). A semi-automatic DLI mapping workflow was elaborated and DLI maps with two different scales (2 and 5 molm-2d-1) were created for Portugal's mainland, analyzing from regional (Northern regions, Central regions, Southern regions) and seasonal (Spring, Summer, Autumn, Winter) perspectives. The DLI values and ranges in Portugal provide a clear spatial gradient from north to south, influenced by geographic location, topography, and climate. In autumn, the DLI values decrease (11-41 molm-2d-1) and the lowest DLI values are observed in the winter months (7-17 molm-2d-1). During spring, DLI values increase, reaching their peak in the summer months (41-57 molm-2d-1). In autumn the DLI range is narrow (11-13 molm-2d-1), as well as in winter (8-12 molm-2d-1), and it becomes broader during spring and summer (11-14 molm-2d-1). To enhance agricultural practices, future DLI maps should be integrated with agro-climatic maps and thematic layers such as soil, water, topography, temperature, and biodiversity. These integrated maps should then be incorporated into agricultural policy and decision-making to improve crop management strategies. Portugal's agricultural lighting strategy will utilize DLI maps alongside crop-specific recommendations, shading management, local conditions and market demands.

In this study, we compare two contrasting years within the 2020–2025 period—one characterized by extreme heat and drought, and another by unusually high precipitation. We used five years of climatic data provided by the Hungarian Meteorological Service (OMSZ), along with vegetation activity indices (NDVI—Normalized Difference Vegetation Index; NDWI—Normalized Difference Water Index) derived from Sentinel-2A satellite imagery. In parallel, during three years of the study period (2020, 2022, and 2025), we collected five phytosociological relevés in each of the five vegetation types subjected to different management regimes. For data analysis, we applied Principal Component Analysis (PCA), Detrended Correspondence Analysis (DCA), and the Additive Main Effects and Multiplicative Interaction (AMMI) model. Vegetation index patterns were compared with the relative water requirements of the constituent plant species. In the ungrazed dry sandy site, climatic fluctuations did not significantly affect vegetation composition and the habitat remained a stable open sandy grassland. Among the four grazed sites, grazing intensity remained unchanged during the study in three cases (N1, N2, and SZ). Thus, vegetation changes observed in these areas can be attributed to climatic factors. Vegetation composition shifted in N1 and N2, whereas no significant change was detected in the drier SZ site. This indicates higher resistance to grazing in SZ, which can therefore be sustainably used as pasture, while the N1–N2 sites responded sensitively to precipitation variability under identical grazing pressure and are better suited for use as meadows. The most pronounced changes occurred at the P site, which had previously functioned as an animal resting area and began regenerating after abandonment in 2022. Vegetation composition shifted markedly within two years, demonstrating that land-use practices exert a stronger influence on sandy grassland vegetation than climatic fluctuations. Overall, the drier habitats were more resilient to both grazing pressure and climatic variability and are suitable for grazing, whereas the moister vegetation types were more sensitive and should preferably be managed as hay meadows.

According to climate projections, the Pannonian region is expected to experience an increasing frequency of drought events. This trend affects not only agricultural areas but also natural grasslands. The Festuca wagneri species, selected for this study, is a dominant and well-adapted grass in dry natural habitats. A total of 54 Festuca wagneri individuals were examined across three soil types: sand, loam, and clay. In each soil type, 18 plants were assessed for drought tolerance. Water was applied at three dosage levels: 200, 300, and 400 mL. The experiment was conducted between 4 April and 18 July 2024, during which the total weight of the pots and the amount of drained water were measured regularly. All data processing and statistical analyses were performed in R version 4.3.2. A three-way factorial ANOVA was used to evaluate main and interaction effects. Model residuals were tested for normality (Shapiro–Wilk test) and homoscedasticity using diagnostic plots. The results showed that Festuca wagneri individuals tolerated even the lowest soil moisture levels induced by low water-holding capacity of the soil and low water input. This indicates that the species can be effectively used in grassland management and restoration under future climate change scenarios. The main differences were observed among soil types, highlighting the crucial importance of soil structure when establishing this species. Loam soils, already near optimal, respond best to moderate.

The tasks and objectives of grassland management have changed significantly in recent decades. One of the key elements of adapting to climatic and economic challenges is the optimal use and future sustainability of grasslands. Ferenc Balázs’s plant stand assessment method is a fast, efficient and widely applicable method for evaluating the quantitative and qualitative characteristics of forage in grasslands, as well as the economic value of pastures. This study is based on a three-dimensional coenological survey which is low-cost, does not require technical infrastructure, and empirically considers the species’ preference by livestock. As a result of our extended criteria approach, we assigned modified forage value (k-value) categories to 2310 vascular plant species. Based on our investigations in the presented case study, the Balázs method was proven to be well suited for estimating the yield of grasslands and determining the relative forage value of grasslands with a high degree of confidence in practice. As this method is non-destructive and involves little trampling, it is particularly suitable for monitoring grassland habitats with a high density of protected plant and animal species.

One of the essential issues in decision problems and preference modeling is the number of comparisons and their pattern to ask from the decision maker. We focus on the optimal patterns of pairwise comparisons and the sequence including the most (close to) optimal cases based on the results of a color selection experiment. In the test, six colors (red, green, blue, magenta, turquoise, yellow) were evaluated with pairwise comparisons as well as in a direct manner, on color-calibrated tablets in ISO standardized sensory test booths of a sensory laboratory. All the possible patterns of comparisons resulting in a connected representing graph were evaluated against the complete data based on 301 individual's pairwise comparison matrices (PCMs) using the logarithmic least squares weight calculation technique. It is shown that the empirical results, i.e., the empirical distributions of the elements of PCMs, are quite similar to the former simulated outcomes from the literature. The obtained empirically optimal patterns of comparisons were the best or the second best in the former simulations as well, while the sequence of comparisons that contains the most (close to) optimal patterns is exactly the same. In order to enhance the applicability of the results, besides the presentation of graph of graphs, and the representing graphs of the patterns that describe the proposed sequence of comparisons themselves, the recommendations are also detailed in a table format as well as in a Java application.

Different ranking methods have long been used in sensory testing. Their diffusion was mainly due to their simplicity, their standardized methods, their software support, and their wide range of applications. However, a number of research and industrial problems have emerged recently that cannot be adequately solved by the standard approaches, making it necessary to apply and adapt methods from other disciplines. This article discusses the ranking methods of international sensory standardization (single-, pair-ranking methods, balanced incomplete block design (BIBD) according to the structure of standardization). We overview ranking methods in international sensory competitions. We evaluate some potential applications of ranking methodological developments pair ranking, Analytic Hierarchy Process (AHP), multi-criteria decision making (MCDM), graph theory, developed and applied by other disciplines, which are less used in sensory sciences. The principles and applications of these methodologies are summarized, and factors affecting their effectiveness and limitations are discussed. Preference modeling and quantification are key questions of decision and sensory sciences. Both areas require true, unbiased individual responses as well as their appropriate aggregation. Competitions are typically multi-criteria problems, evaluated by several decision makers. To better understand consumer preferences and to explore complex consumer choices, different methods and software from other disciplines-decision and social choice theory, operations research, economics (e.g., ranking based on pairwise comparisons, AHP, MCDM, graph theory)-are adapted and disseminated. In addition to surveying latest trends, we propose some areas of future research development.

Wood pastures have been characteristic farming types in the Pannonian biogeographical region over the centuries. In the present work, we studied wood-pastures of typical geographical locations in the North Hungarian Mountain Range of Hungary characterized by similar environmental conditions but grazed by different livestock. The sample area of Cserépfalu was grazed by Hungarian Grey Cattle, while the Erdőbénye was grazed by Hungarian Racka Sheep. Coenological records of the sites were collected from 2012 to 2021 in the main vegetation period according to the Braun-Blanquet method with the application of 2 × 2 m sampling quadrats, where the coverage estimated by percentage for each present species was also recorded. To evaluate the state of vegetation, ’ecological ordering’ distribution, diversity, and grassland management values were used. Between the two areas, the grazing pressure of the two studied livestock produced different results. Based on the diversity values, woody–shrubby–grassland mosaic diversity values were high (Shannon diversity: 2.21–2.87). Cattle grazing resulted in a variable and mosaic-like shrubby area with high cover values. Based on our results, grazing by cattle provides an adequate solution for forming and conserving wood-pasture habitats in the studied areas of Hungary. However, if the purpose is to also form valuable grassland with high grassland management values, partly sheep grazing should be suggested.

These days, a growing consumer demand and scientific interest can be observed for nutraceuticals of natural origin, including apiculture products. Due to the growing emphasis on environmental protection, extensive research has been conducted on the pesticide and heavy metal contamination of bee products; however, less attention is devoted on other food safety aspects. In our review, scientific information on the less-researched food safety hazards of honey, bee bread, royal jelly, propolis, and beeswax are summarized. Bee products originating from certain plants may inherently contain phytotoxins, like pyrrolizidine alkaloids, tropane alkaloids, matrine alkaloids, grayanotoxins, gelsemium alkaloids, or tutin. Several case studies evidence that bee products can induce allergic responses to sensitive individuals, varying from mild to severe symptoms, including the potentially lethal anaphylaxis. Exposure to high temperature or long storage may lead to the formation of the potentially toxic 5-hydroxymethylfurfural. Persistent organic pollutants, radionuclides, and microplastics can potentially be transferred to bee products from contaminated environmental sources. And lastly, inappropriate beekeeping practices can lead to the contamination of beekeeping products with harmful microorganisms and mycotoxins. Our review demonstrates the necessity of applying good beekeeping practices in order to protect honeybees and consumers of their products. An important aim of our work is to identify key knowledge gaps regarding the food safety of apiculture products.

The Daily Light Integral (DLI) is a key metric to optimise plant cultivation, influence photosynthesis, morphology, yield, and nutritional quality. Our study focuses on (i) the creation of the spatiotemporal DLI map for a representative Mediterranean country, Spain, (ii) the presentation of the improved semi-automatic DLI mapping workflow, (iii) the challenge of the comparability of different DLI value scalings in global (continent) and local context (country). DLI maps provide essential insights into the spatial and temporal distribution of natural and artificial light, critical for optimizing agricultural practices and enhancing crop yields. Spain's diverse topography and climate create significant regional and seasonal variations in DLI values. Using data from SunTracker Technologies and global weather stations, we developed detailed DLI maps at 30-meter resolution. These maps reveal high DLI values in coastal and southern regions, especially in summer, and lower values in northern and interior regions during winter. Our findings emphasize the importance of tailored lighting strategies in agriculture, suggesting higher scaling (from 5 to 2 mol·m−2·d−1) resolution for European contexts. This research underpins the development of smart agricultural systems that both quantitatively and qualitatively regulate lighting conditions (supplementary light and shading management) to maximize crop productivity and sustainability. Integrating DLI maps with IoT and AI technologies offers predictive insights for precision agriculture, highlighting the need for advanced training to leverage these tools effectively.

In order to produce high-quality plant materials, it is necessary to consider a series of biotic and abiotic inputs. In this study, we focus on horticultural light climate mapping in Europe using earth and weather observation and information technologies. It is widely accepted that optimised light programmes and spectral recipes with dedicated wavelengths can most efficiently support the photoreceptors and the controlled plant production. By knowing the DLI (Daily Light Integral) for a particular area, growers can optimise their crop management strategies, such as selecting the most appropriate crops for the light levels, determining optimal planting times, and selecting the best location for their crops. Generating a sufficiently resolved DLI map usually demands both a spatial and spectral downscaling process. In our present research we thus focus on (i) the development of a semi-automatic DLI mapping workflow and (ii) a first exemplary visualisation of an all-season DLI map for a European country, which can easily be adapted to any other country based on the suggested approach. A special focus was put on the development of precise DLI values at a European scale, especially experiencing with 1 and 2 molm-2d-1 DLI value increments. Additional purposes of DLI mapping such as the adaption to climate changes and the efficient use of energy were also addressed as the present energy crisis documents the need to adapt future horticulture engineering systems both for indoor and outdoor production. Customised DLI maps are also useful secondary information sources for solar energy mapping, especially for renewable energy sources.