This paper explores contemporary approaches to preserving and promoting cultural heritage by integrating game elements and advanced technologies, such as Virtual Reality (VR) and Augmented Reality (AR). In an era increasingly shaped by digital innovation, preserving cultural heritage demands new strategies to sustain engagement with historical narratives and artifacts. Emerging technologies like VR and AR offer immersive, interactive experiences that appeal to modern audiences, especially younger generations accustomed to digital environments (Bekele and Champion). Gamification—the use of game design principles in non-game contexts—has gained significant traction in education and cultural heritage, providing new methods for increasing user engagement and retention (Werbach and Hunter). By incorporating gamified features, heritage can be made more accessible, fostering emotional connections and deeper understanding (Huotari and Hamari; Zichermann and Cunningham). This aligns with the shift toward interactive digital storytelling as a tool to transform static heritage presentations into dynamic, participatory experiences (Champion and Rahaman). Central to this research is the conceptualization and development of a mobile application leveraging VR and AR to enhance user engagement and education around cultural heritage. Drawing on the principles of self-determination theory (Deci and Ryan) and empirical findings on gamified learning (Landers and Landers), the application combines educational content with interactive elements, creating an immersive learning environment. By addressing both content accessibility and interactive immersion, this application bridges the gap between traditional heritage preservation and the expectations of a digitally native audience. The recent literature underscores the potential of VR and AR in cultural preservation, emphasizing their ability to transcend physical boundaries, simulate historical environments, and promote active participation (Milgram and Kishino, Addison; Azuma). As virtual environments evolve, platforms like the metaverse expand possibilities for experiencing cultural heritage in spaces free of geographical limitations (Cipresso et al.; Radianti et al.). Such advancements have already demonstrated significant educational and experiential benefits (Wu et al.; Akçayır and Akçayır). This study employs both quantitative and qualitative methods to examine the target group’s attitudes toward gamified technologies for cultural heritage preservation. The initial results indicate substantial interest and willingness among users to engage with applications employing VR and AR. This aligns with findings in the literature that suggest immersive experiences can enhance learning outcomes and foster long-term engagement (Merchant et al.; Speicher et al.). The project has garnered significant recognition, receiving the Rector’s Award for the best scientific paper in the technical field at the University of Zagreb and earning bronze medals at the ARCA Innovation Fair and the INOVA Fair. These accolades underscore the project’s innovative approach and its potential for real-world application. By presenting a robust framework for integrating gamification and immersive technologies into cultural heritage preservation, this paper contributes to the growing discourse on utilizing advanced digital tools to ensure the sustainability and relevance of cultural heritage for future generations.

Aphids are significant pests of winter wheat, causing damage by feeding on plant sap and reducing crop yield and quality. This study evaluates the potential of hyperspectral remote sensing (350–2500 nm) and machine learning (ML) models for classifying healthy and aphid-infested wheat canopies. Field-based hyperspectral measurements were conducted at three growth stages—T1 (stem elongation–heading), T2 (flowering), and T3 (milky grain development)—with infestation levels categorized according to established economic thresholds (ET) for each growth stage. Spectral data were analyzed using Uniform Manifold Approximation and Projection (UMAP); vegetation indices; and ML classification models, including Logistic Regression (LR), k-Nearest Neighbors (KNNs), Support vector machines (SVMs), Random Forest (RF), and Light Gradient Boosting Machine (LGBM). The classification models achieved high performance, with F1-scores ranging from 0.88 to 0.99, and SVM and RF consistently outperforming other models across all input datasets. The best classification results were obtained at T2 with an F1-score of 0.98, while models trained on the full spectrum dataset showed the highest overall accuracy. Among vegetation indices, the Modified Triangular Vegetation Index, MTVI (r_pb = −0.77 to −0.82), and Triangular Vegetation Index, TVI (r_pb = −0.66 to −0.75), demonstrated the strongest correlations with canopy condition. These findings underscore the utility of canopy spectra and vegetation indices for detecting aphid infestations above ET levels, allowing for a clear classification of wheat fields into “treatment required” and “no treatment required” categories. This approach provides a precise and timely decision making tool for insecticide application, contributing to sustainable pest management by enabling targeted interventions, reducing unnecessary pesticide use, and supporting effective crop protection practices.

Fusarium head blight (FHB) is a fungal disease of cereals including wheat, which results in significant economic losses and reductions in grain quality. Additionally, the presence of Fusarium spp. results in productions of mycotoxins/metabolites, some of which are toxic in low concentrations. The liquid chromatography with tandem mass spectrometry (LC-MS/MS) method was applied to 216 wheat samples from field conditions diseased with FHB. Data obtained show that out of 28 metabolites detected, deoxynivalenol (DON), deoxynivalenol-3-glucoside (D3G), enniatin B (ENN B), enniatin B1 (ENN B1), culmorin, 15-hydroxyculmorin, and aurofusarin were the most prevalent mycotoxins/metabolites over three years (2014–2016). In 2014–2016, 100, 100 and 96% of the samples were contaminated with zearalenone (ZEN). Of the masked mycotoxins, D3G occurred at a high incidence level of 100% in all three investigated years. Among emerging mycotoxins, moniliformin (MON), beauvericin (BEA) and enniatins (ENNs) showed high occurrences ranging from 27 and 100% during three investigated years. Co-occurrence of Fusarium mycotoxins/metabolites was high and almost all were highly correlated to each other but their possible synergistic, additive, or antagonistic effects of toxicity, should be taken into consideration. Our results demonstrated that modified and emerging mycotoxins/metabolites contributed substantially to the overall contamination of wheat grains. To avoid disparagement, it is necessary to analyse these forms in future mycotoxin monitoring programs and to set their maximum levels.

Soybean is generally grown as a rainfed crop worldwide and very often is exposed to drought and high temperatures. The objectives of this study were to determine the performance and stability of 32 elite soybean genotypes for seed protein and oil contents across six dry and eight normal environments and to determine the influence of environment on the relationship between the two traits. In the combined ANOVA, genotypes (G), environments (E) and G × E were significant for both traits with protein content being more sensitive to environmental changes than oil content. Mean seed protein content decreased by 4.5% under drought conditions compared to normal ones and ranged from 2.3% to 7.1% for individual genotypes. At the same time drought caused a slight increase in seed oil content of +1.2%, with a range of −1.3% to +4.5% for individual genotypes. Genotype stability in terms of regression coefficient (b) and coefficient of variation (CV) was in moderate to weak negative correlation with mean genotype performance for protein content, while no correlation was observed between genotype stability and mean genotype performance for oil content. Protein and oil content were significantly negatively correlated in normal environments (r = −0.33), while no correlation between the traits was observed in dry environments (r = −0.02).

Immersive technologies such as augmented reality (AR) and virtual reality (VR) have emerged as powerful tools in cultural heritage education and preservation. Building on prior work that demonstrated the effectiveness of gamified XR applications in engaging users with heritage content and drawing on existing studies in neuroscience and cognitive psychology, this study explores how immersive experiences support multisensory integration, emotional engagement, and spatial presence—all of which contribute to the deeper encoding and recall of heritage narratives. Through a theoretical lens supported by the empirical literature, we argue that the interactive and embodied nature of AR/VR aligns with principles of cognitive load theory, dual coding theory, and affective neuroscience, supporting enhanced learning and memory consolidation. This paper aims to bridge the gap between technological innovation and cognitive understanding in cultural heritage dissemination, identifying concrete design principles for memory-driven digital heritage experiences. While promising, these approaches also raise important ethical considerations, including accessibility, cultural representation, and inclusivity—factors essential for equitable digital heritage dissemination.

Breeding resistant wheat cultivars to Fusarium head blight (FHB), caused by Fusarium spp., is the best method for controlling the disease. The aim of this study was to estimate general combining ability (GCA) and specific combining ability (SCA) for FHB resistance in a set of eight genetically diverse winter wheat cultivars to identify potential donors of FHB resistance for crossing. FHB resistance of parents and F1 crosses produced by the half diallel scheme was evaluated under the conditions of artificial inoculation with F. graminearum and natural infection. Four FHB related traits were assessed: visual rating index (VRI), Fusarium damaged kernels (FDK), and deoxynivalenol and zearalenone content in the harvested grain samples. Significant GCA effects for FHB resistance were observed for the parental cultivars with high FHB resistance for all studied FHB resistance related traits. The significant SCA and mid-parent heterosis effects for FHB resistance were rare under both artificial inoculation and natural infection conditions and involved crosses between parents with low FHB resistance. A significant negative correlation between grain yield under natural conditions and VRI (r = −0.43) and FDK (r = −0.47) under conditions of artificial inoculation was observed in the set of the studied F1 crosses. Some crosses showed high yield and high FHB resistance, indicating that breeding of FHB resistant genotypes could be performed without yield penalty. These crosses involved resistant cultivars with significant GCA effects for FHB resistance indicating that that they could be used as good donors of FHB resistance.