Search Results (153)

Quinoa (Chenopodium quinoa Willd.), a crop native to the Andean region, exhibits variable performance in yield components under rainfed Mediterranean conditions. Consequently, identifying varieties that demonstrate stability in key agronomic traits—regardless of environmental fluctuations—is essential for enhancing crop reliability and productivity. In this work, new five varieties belonging to the sea-level ecotype (Pangal, Nieves, Pincoya, Chucao and Regalona), with superior performance to local materials used by farmers in terms of uniformity, stability, yield characteristics, grain diameter, thousand-grain weight, protein percentage, and saponins, were established in three environments (Pichilemu 34°29′ S/72°01′ W, Coihueco 36°42′ S/72°42′ W, Cañete 37°51′ S/73°24′ W) during two consecutive seasons (2019/2020, 2020/2021). Data analysis confirmed narrow variability among the varieties analyzed and between season and environment in all characteristics evaluated. The Pichilemu area (close to the coast) was the most productive over the two years of cultivation studied, with grain yields reaching 2975 kg·ha⁻¹. In the Cañete (coastal) and Coihueco (foothill) environments, grain yields were 2892 and 2453 kg·ha⁻¹, respectively. The Pangal variety (pearl) had the highest grain yield, reaching 3162 kg·ha⁻¹ in all environments. Nieves (white) variety had the best grain diameter (GD = 1.88 mm) and the best thousand-grain weight (TGW = 3.10 g). Regarding grain protein concentration, the Pincoya (black) variety had the highest score (GP = 16.31%). The lowest concentration of Saponin was obtained in Chucao (red) variety (GS = 1.46%). The Additive Main Effects and Multiplicative Interaction (AMMI) analysis did not identify any variety that exhibited greater yield and stability. Consequently, over the two years of study, the Nieves and Pangal varieties presented the best yield in the Pichilemu environment, with 3673 and 3788 kg·ha⁻¹, respectively. These varieties also stood out in the Cañete environment as obtaining the best yields (3547 and 3169 kg·ha⁻¹); however, they did not obtain the highest yield in the Coihueco environment. The Chucao variety was considered to have greater stability obtaining average yield in all study environments. This study presents a comprehensive phenotypic characterization of newly developed varieties, offering insights into their adaptive relationships with Mediterranean environments. To further elucidate the influence of environmental stressors on agronomic performance and grain quality traits, future trials are recommended in more extreme ecological settings. Full article

A pivotal food crop in arid and semi-arid zones, proso millet boasts remarkable economic value, making the breeding of stable high-yield varieties critical for industrial sustainability. This study employed a randomized complete block design to conduct a two-year multi-environment trial on nine new varieties across six representative spring-sown test regions in China. Analytical tools, including additive main effects and multiplicative interaction (AMMI) biplots, AMMI stability values (ASV), genotype and genotype × environment (GGE) models, and genotype by yield–trait (GYT) biplots were utilized to assess genotype–environment (G × E) interactions and screen superior genotypes. AMMI variance analysis showed extremely significant effects of genotype, environment, and G × E on yield traits (p < 0.01). G × E principal component analysis identified JS8, PS3, PS6, and PM4 as dominant genotypes. Based on ASV indices, varietal stability rankings were PS5 > YS13 > JS8 > PS3 > PS6 > PM4 > others. GGE analysis indicated PM4 had the broadest adaptability across tested environments, while JS15 exhibited specific adaptability in Datong. Huairen and Shuozhou were validated as ideal testing environments via an ideal environment plot. GYT biplots further confirmed that YS13, JS15, PS3, and PM4 excelled in comprehensive yield–trait combinations. These findings offer a scientific foundation for ecological adaptability evaluation, breeding material selection, and commercial variety promotion. Full article

Healthcare is a dynamic and ever-changing phenomenon and is subject to multiple challenges, particularly concerning sustainability and cost issues. The literature identifies bed space and problems related to the lack of hospital beds as being directly or indirectly related to both admission and discharge processes, with delays in in-patient discharges being identified as a variable of significance when it comes to a health system’s overall performance. In this respect, the aim of this research was to explore factors related to delayed discharges in an acute hospital setting in Malta, a small European member state, through the perspectives of health professionals. This study followed a qualitative approach. Semi-structured interviews (n = 8) and focus groups (n = 2) were conducted with a diverse group of experienced health professionals. Informed consent was obtained from all participants, and all data were treated with strict confidentiality throughout the study. The sample was limited to professionals working in adult, non-specialized healthcare settings. Manual thematic analysis was carried out. Codes were grouped to derive seven main themes, which were identified after carrying out the thematic analysis process on the transcripts of the interviews/focus groups. The derived themes are the following: (a) a faulty system, which is open to abuse and inefficiency, (b) procedural delays directly impacting delayed discharges, (c) long-term care/social cases as a major cause of delayed discharges, (d) the impact of external factors on delayed discharges, (e) stakeholder suggestions to management to counteract delayed discharges, (f) the impact of COVID-19 on delayed discharges, and (g) inter-professional relationships. Factors related to delayed discharges and the effects of delayed discharges on the hospital emerged from the main findings, together with specific potential interventions to minimise delays in discharge. Health professional interactions and the effects of inter-professional relationship setbacks on delayed discharges were explored, and the impact of the COVID-19 pandemic on hospital dynamics and additional delays were also addressed. This information is intended to provide hospital administrators with data-driven internal organisational evidence to guide them through changes and to inform future decisions regarding hospital performance and efficiency from a discharge delay perspective. Full article

The transformative potential of self-driving vehicles (SDVs) in enhancing mobility and transportation safety is well documented, yet their adoption in developing countries remains understudied. While existing research has primarily focused on SDV adoption in developed nations using variance-based methods, limited attention has been given to understanding how multiple factors interact to influence adoption decisions in developing economies. This study addresses this gap by examining the determinants of SDV adoption intention in Ghana using fuzzy set qualitative comparative analysis (fsQCA). Drawing on the Technology Acceptance Model and incorporating additional constructs of perceived reliability, technological competence, and perceived risk, the study analyzed survey data from 1248 respondents across Ghana’s 16 regions. The findings reveal multiple pathways to high adoption intention, with the most effective combination being perceived reliability, perceived ease of use, and technological competence working together. For low adoption intention, two main configurations emerged, both highlighting how the combination of low technological competence and high perceived risk significantly hinders adoption. These findings provide valuable insights for policymakers and stakeholders in developing economies, emphasizing the need for targeted interventions that address both technological and socio-cultural factors influencing SDV adoption. Full article

Lactobacilli, as the main member of food microorganisms, is an important component of the intestinal microbial community and plays crucial roles in regulating the immune capacity of the body. This review provides a comprehensive exploration of the key components of Lactobacilli-mediated immune regulation effects, including the immunogenic components (peptidoglycan and lipoteichoic acid) and metabolites (short-chain fatty acids, bacteriocins, and exopolysaccharides), which can interact with host immune cell receptors to initiate complex immune signaling pathways. In addition, the immunomodulatory activity can be influenced by multiple factors including species differences, host-related factors (age, physiological conditions, and gut microbiota), and environmental factors (nutrient substrates, temperatures, etc.), and the application strategies including precision probiotic development, gene-editing driven engineering, and nanocarrier systems have also been proposed to enhance the immunomodulatory potential. Finally, this review provides the theoretical basis for microbial intervention in immune-related diseases and offers prospects for applications in the food and pharmaceutical industries. Full article

This paper introduces a novel numerical approach for solving fractional stochastic differential equations (FSDEs) using bilinear time-series models, driven by the Caputo–Katugampola (C-K) fractional derivative. The C-K operator generalizes classical fractional derivatives by incorporating an additional parameter, enabling the enhanced modeling of memory effects and hereditary properties in stochastic systems. The primary contribution of this work is the development of an efficient numerical framework that combines bilinear time-series discretization with the C-K derivative to approximate solutions for FSDEs, which are otherwise analytically intractable due to their nonlinear and memory-dependent nature. We rigorously analyze the impact of fractional-order dynamics on system behavior. The bilinear time-series framework provides a computationally efficient alternative to traditional methods, leveraging multiplicative interactions between past observations and stochastic innovations to model complex dependencies. A key advantage of our approach is its flexibility in handling both stochasticity and fractional-order effects, making it suitable for applications in a famous nuclear physics model. To validate the method, we conduct a comparative analysis between exact solutions and numerical approximations, evaluating convergence properties under varying fractional orders and discretization steps. Our results demonstrate robust convergence, with simulations highlighting the superior accuracy of the C-K operator over classical fractional derivatives in preserving system dynamics. Additionally, we provide theoretical insights into the stability and error bounds of the discretization scheme. Using the changes in the number of simulations and the operator parameters of Caputo–Katugampola, we can extract some properties of the stochastic fractional differential model, and also note the influence of Brownian motion and its formulation on the model, the main idea posed in our contribution based on constructing the fractional solution of a proposed fractional model using known bilinear time series illustrated by application in nuclear physics models. Full article

The seed yield of 28 bean (Phaseolus vulgaris) lines from different crosses and two check cultivars was evaluated under rainfed conditions in two sites in North-Central Mexico. The aim was to identify high-yielding lines with low genotype–environment interactions (GEIs). Trials were conducted under a 6 × 5 square lattice design with four replicates; due to the lack of rainfall in Zacatecas, the trial was helped with supplemental irrigation. Data were analyzed by location and combined to determine the effects of GEIs using the additive main effects and multiplicative interaction model (AMMI) model. The combined analysis showed that 75.45% of the yield variation among lines was due to the effect of the environment, 11.75% was due to genotypes, and 12.79% was due to GEIs. Lines 5 and 10 displayed the highest yield, which slightly surpassed the checks (2.1 and 0.11%, respectively) and showed greater stability than those in the test environments. The AMMI analysis allowed for the selection of stable and high-yielding lines under drought conditions. Data on the weight and yield per hectare of a hundred seeds between and within locations identified lines 5, 10, and 16 as outstanding and capable of being used as a parent in a future hybridization program or as a new cultivar with drought tolerance. Full article

Genotype by environment (G × E) interaction is a magnitude change in the performance of a genotype when grown in contrasting environments. The sensitivity of a genotype to different environmental conditions is an important determinant of its suitability for cultivation in a specific environment or across multiple environments. In many nations of the world, where the drive to achieve a net-zero CO₂ emission by 2030 has spurred significant investments in clean energy sources such as photovoltaics with a resultant conversion of some agricultural lands to photovoltaic facilities, there is a need to find the right balance between addressing the food and energy crises. Agri-photovoltaics (APV) offer a sustainable solution by allowing crops to grow underneath photovoltaic panels. However, selection efficiency and repeatability of APV experimental results could be marred by the presence of G × E interaction. The study objective was to identify mungbean genotype(s) with a high yield potential and broad adaptability across APV environments. Five mungbean (Vigna radiata L.) genotypes, Tvr18, Tvr28, Tvr65, Tvr79, and Tvr 83, were assessed under six contrasting APV environments, EPV-R, EPV-D, NPV-R, NPV-D, WPV-R, and WPV-D, at the Agri-PV Food and Energy Training Center, University of Nigeria, Nsukka. The experiment was a split-plot design, with the environment as the whole-plot factor while genotype was the sub-plot factor with five replications. The additive main effects and multiplicative interaction (AMMI) and the Finlay and Wilkinson joint regression analysis confirmed significant genotype, environment, and G × E interaction effects for mungbean seed yield. Two genotypes, Tvr28 and Tvr83 expressed broad adaptability to the APV environments with higher yields (2.60 and 2.50 t ha⁻¹), ranking first and second, respectively. In contrast, the Tvr79 genotype displayed the highest sensitivity (2.95) to environmental variation and was unstable across the environments with higher IPCA1 and ASV scores of −1.17 and 1.39, respectively. The EPV-R recorded the highest yield (2.61) with low interaction effect (0.38), whereas the WPV-D environment had the least yield (1.71) and was the most unstable (−0.48). Conclusively, the Tvr28 and Tvr83 genotypes and the EPV-R environment were the ideal genotypes and environment, respectively, and are therefore recommended for use in APV facilities. Full article

The high yield potential and stability of hybrid japonica rice varieties are crucial for sustainable agricultural development and food security. Rice varieties must undergo rigorous testing through multi-site regional trials before being introduced to the market in China. The assessment of these regional trials is essential for guiding rice breeding. In this study, we evaluated the yield performance of 13 hybrid japonica rice genotypes (g1–g13) across six regional trial sites (e1–e6) in Jiangsu province, China. Variance analysis revealed that genotype (G), environment (E), and genotype-by-environment (G × E) interactions significantly influenced the yield of hybrid japonica rice varieties. The effects of G × E interactions on the yield potential and stability of these tested rice varieties were further analyzed using Genotype plus Genotype-by-Environment interaction (GGE) biplot and additive main effects and multiplicative interaction (AMMI) model analyses. The results reveal that Zhegengyou2035 (g4) and Changyou20-2 (g3) exhibited superior yield potential and stability, while Huazhongyou9413 (g12) exhibited broad adaptability. Additionally, the assessment of discrimination and representativeness among regional trial sites revealed that the Wujin Rice Research Institute (e6) served as an optimal testing location. Our findings identify the most suitable rice varieties for the area and assess their potential as initial material in the selection processes for breeding new varieties. Additionally, this work contributes to the strategic selection of optimal testing locations. Full article

The use of buffalo meat in fermented sausage production represents a sustainable and innovative approach to enhancing the value of underutilized meat cuts. However, its high heme content and specific fatty acid composition makes the meat particularly sensitive to lactic fermentation with lipid oxidation phenomena and sensory character decay. Therefore, buffalo meat requires tailored fermentation strategies to ensure product stability. The aim of this study was to optimize fermentation strategies by exploring milder acidification processes and the fortification of buffalo meat with vegetable oils to reduce oxidation while maintaining microbiological quality. In particular, the effect of adding or omitting glucose and fortifying with pumpkin seed oil in Napoli-style buffalo salami was studied and the impact on the main quality parameters was evaluated. Pumpkin seed oil (0.5%) was selected for its antimicrobial and antioxidant properties and evaluated for its interaction with starter cultures through Minimum Inhibitory Concentration (MIC) tests and predictive microbiology models. Based on the findings, its use was validated in Napoli-style salami, produced with and without glucose. Microbial dynamics, physicochemical changes over time, oxidation indices, and sensory attributes were assessed. Results indicated that the sugar-free formulations combined with pumpkin seed oil achieved optimal sensory and safety attributes. The addition of glucose facilitated rapid lactic acid bacterial growth (about 2.5 ∆ log CFU/g), enabling pH reduction to safe levels (<5.2) and the effective inhibition of Enterobacteriaceae and coliforms. However, acidification in the control batch, as demonstrated by multiple variable regression analyses, induced pre-oxidative conditions, increasing lipid oxidation markers (TBARSs > 0.7 mg MAD/Kg), which negatively impacted flavor and color stability. The use of pumpkin seed oil confirmed its antimicrobial and antioxidant potential, making it a promising fortifying ingredient for producing slow-fermented, mildly acidified (pH > 5.4) buffalo meat salami, offering a novel strategy for improving the nutritional, sensorial, and safety quality of dry fermented meat. Full article

Neurological disorders are defined by a deterioration or disruption of the nervous system’s structure and function. These diseases, which include multiple sclerosis, Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and schizophrenia, are caused by intricate pathological processes that include excitotoxicity, neuroinflammation, oxidative stress, genetic mutations, and compromised neurotrophic signaling. Although current pharmaceutical treatments relieve symptoms, their long-term efficacy is limited due to adverse side effects and weak neuroprotective properties. However, when combined with other neuroprotective drugs or adjunct therapy, they may offer additional benefits and improve treatment outcomes. Phytochemicals have emerged as attractive therapeutic agents due to their ability to regulate essential neurotrophic pathways, especially the brain-derived neurotrophic factor (BDNF) signaling cascade. BDNF is an important target for neurodegenerative disease (ND) treatment since it regulates neuronal survival, synaptic plasticity, neurogenesis, and neuroprotection. This review emphasizes the molecular pathways through which various phytochemicals—such as flavonoids, terpenoids, alkaloids, and phenolic compounds—stimulate BDNF expression and modulate its downstream signaling pathways, including GSK-3β, MAPK/ERK, PI3K/Akt/mTOR, CREB, and Wnt/β-catenin. This paper also highlights how phytochemical combinations may interact to enhance BDNF activity, offering new therapeutic options for ND treatment. Despite their potential for neuroprotection, phytochemicals face challenges related to pharmacokinetics, blood–brain barrier (BBB) permeability, and absorption, highlighting the need for further research into combination therapies and improved formulations. Clinical assessment and mechanistic understanding of BDNF-targeted phytotherapy should be the main goals of future studies. The therapeutic efficacy of natural compounds in regulating neurotrophic signaling is highlighted in this review, providing a viable approach to the prevention and treatment of NDs. Full article

Background: The advent of virtual reality in psychiatry presents a wealth of opportunities for a variety of psychopathologies. Avatar Interventions are dialogic and experiential treatments integrating personalized medicine with virtual reality (VR), which have shown promising results by enhancing the emotional regulation of their participants. Notably, Avatar Therapy for the treatment of auditory hallucinations (i.e., voices) allows patients to engage in dialogue with an avatar representing their most persecutory voice. In addition, Avatar Intervention for cannabis use disorder involves an avatar representing a significant person in the patient’s consumption. In both cases, the main goal is to modify the problematic relationship and allow patients to regain control over their symptoms. While results are promising, its potential to be applied to other psychopathologies, such as major depression, is an exciting area for further exploration. In an era where VR interventions are gaining popularity, the present study aims to investigate whether technological advancements could overcome current limitations, such as avatar realism, and foster a deeper immersion into virtual environments, thereby enhancing participants’ sense of presence within the virtual world. A newly developed virtual reality platform was compared to the current platform used by our research team in past and ongoing studies. Methods: This study involved 43 subjects: 20 healthy subjects and 23 subjects diagnosed with severe mental disorders. Each participant interacted with an avatar using both platforms. After each immersive session, questionnaires were administered by a graduate student in a double-blind manner to evaluate technological advancements and user experiences. Results: The findings indicate that the new technological improvements allow the new platform to significantly surpass the current platform as per multiple subjective parameters. Notably, the new platform was associated with superior realism of the avatar (d = 0.574; p < 0.001) and the voice (d = 1.035; p < 0.001), as well as enhanced lip synchronization (d = 0.693; p < 0.001). Participants reported a significantly heightened sense of presence (d = 0.520; p = 0.002) and an overall better immersive experience (d = 0.756; p < 0.001) with the new VR platform. These observations were true in both healthy subjects and participants with severe mental disorders. Conclusions: The technological improvements generated a heightened sense of presence among participants, thus improving their immersive experience. These two parameters could be associated with the effectiveness of VR interventions and future studies should be undertaken to evaluate their impact on outcomes. Full article

The multi-environment evaluation of wheat genotypes for grain yield is an integral part of germplasm enhancement since it plays a pivotal role in sustainable production. A total of 178 winter wheat cultivars were evaluated across 20 environments in Sweden from 2016 to 2020, with 52 to 59 cultivars tested per year as part of the Swedish National Trials (Sverigeförsöken). The genotypes were evaluated for grain yield performance with and without fungicide treatments. Additive main-effects and multiplicative interaction (AMMI) and genotype plus genotype-by-environment interaction (GGE) biplot methods were explored to estimate the genotype-by-environment interaction (GEI) for grain yield performance. ANOVA revealed a significant variation between treatments, genotypes in all years, and GEI in all years except 2018. The majority of the explained variance came from the environment, with a range of 61–88% across the five-year trial. The 20 sites were grouped into two to four mega-environments in the yearly studies. From the fungicide-treated trials, G 0512LT3, Informer, SG SU1563-15, LG Imposanto, and Pondus were identified as the most stable and high-yielding cultivars each year. From the fungicide-untreated trials, Informer, Ancher Greece, RGT Saki, and Pondus were the best-performing cultivars and could be good candidates for organic wheat cultivation. Full article

Poland is one of the northernmost countries in the world where soybean breeding is actively conducted. A large collection of soybean genotypes was analyzed in three locations in Poland during the 2022–2023 growing seasons. The objective of this research was to determine the stability of yield, as well as the protein and fat content in the seeds of 280 genotypes. The phenotypic correlations across genotypes and environments were assessed using the Spearman coefficient. The statistical analysis was provided using the additive main effects and multiplicative interaction model. The stability of genotypes was assessed using the weighted average of absolute scores. The main factor differentiating the results between locations was the variation in weather conditions. The variety Karok, which ranks among the top 10% in genotype selection indices for yield and thousand-seed weight, is recommended based on studies conducted within the Post-Registration Variety Testing System in three voivodeships in Poland. Among the most stable genotypes, in terms of the traits analyzed in this paper, are many registered and currently grown soybean varieties such as Obelix Pompei, Coraline, Kapral, ES Mentor, NS Mercury, Pepita, Pollux, Silesia, and Heihe 45. The yield stability of soybean genotypes during the development of new varieties should be one of the factors analyzed by breeders. Full article

In this study, hydrogel films of biocomposite comprising bacterial cellulose (BC) and silk (S) were successfully fabricated through a simple, facile, and cost-effective method via biosynthesis by Acetobacter xylinum in a culture medium of coconut skim milk/mature coconut water supplemented with the powders of thin-shell silk cocoon (SC). Coconut skim milk/mature coconut water and SC are the main byproducts of coconut oil and silk textile industries, respectively. The S/BC films contain protein, carbohydrate, fat, and minerals and possess a number of properties beneficial to wound healing and tissue engineering, including nontoxicity, biocompatibility, appropriate mechanical properties, flexibility, and high water absorption capacity. It was demonstrated that silk could fill into a porous structure and cover fibers of the BC matrix with very good integration. In addition, components (fat, protein, etc.) in coconut skim milk could be well incorporated into the hydrogel, resulting in a more elastic structure and higher tensile strength of films. The tensile strength and the elongation at break of BC film from coconut skim milk (BCM) were 212.4 MPa and 2.54%, respectively, which were significantly higher than BC film from mature coconut water (BCW). A more elastic structure and relatively higher tensile strength of S/BCM compared with S/BCW were observed. The films of S/BCM and S/BCW showed very high water uptake ability in the range of 400–500%. The presence of silk in the films also significantly enhanced the adhesion, proliferation, and cell-to-cell interaction of Vero and HaCat cells. According to multiple improved properties, S/BC hydrogel films are high-potential candidates for application as biomaterials for wound dressing and tissue engineering. Full article