Search Results (240)

Polyphenol oxidases (PPOs) are enzymes that oxidize mono- and diphenolic compounds to o-quinones, facilitating pigment formation and protein crosslinking in food systems, thereby improving their techno-functional properties. However, most PPOs function optimally near neutral pH, limiting their application in acidic food products. This study aimed to extract acid-adapted PPOs from various fruit by-products, including Hass avocado seeds (pH 5.9), Anjou pears (pH 4.0), Bartlett pears (pH 4.0), Red Delicious apples (pH 4.0), and McIntosh apples (pH 3.3), and characterize PPO properties and its substrate specificity using colorimetric assay. SDS-PAGE was used to assess PPOs’ molecular weight and PPOs’ capacity for plant protein crosslinking. The results showed that PPOs from Anjou and Bartlett pear pomace exhibited the most robust acid-adapted activity, with effective catalytic performance in the pH ranges of 4.0–5.0 and 5.0–8.0, respectively, and an optimal temperature of 20 °C. SDS-PAGE analysis revealed bands at ~44 kDa and ~25.6 kDa, consistent with previously found pear PPO isoforms. Both pear pomace PPO oxidized L-DOPA and EGCG efficiently, but showed minimal activity toward L-tyrosine, gallic acid, caffeic acid, tannic acid, and ferulic acid. In the presence of EGCG, both pear pomace PPOs are capable of crosslinking plant proteins at pH 4.0. These findings provide the first evidence that agricultural by-products are a promising but underutilized source of acid-adapted PPO for modifying soy protein hydrolysates. Full article

Poor code locality in virtual memory systems significantly contributes to page faults, leading to degraded system performance. Although many solutions aim to minimize page faults, most rely on clustering techniques that do not quantify the approximation error relative to the optimal solution. In this work, we develop a novel mathematical model based on the Working Set strategy combined with a geometric interpretation of the computational process via a Hasse diagram. This approach enables the reduction of the problem dimensionality and facilitates identification of critical control states under realistic constraints. We formalize the minimization of expected page faults as a discrete optimization problem with well-defined functionals and constraints. Experimental evaluation demonstrates that our model achieves lower average page faults and execution times compared to classical algorithms, especially under poor code locality conditions. Our method also provides a foundation for obtaining ε-optimal solutions and paves the way for designing efficient and cost-effective page replacement algorithms with provable guarantees. These contributions establish both theoretical and practical advances in virtual memory management. Full article

Avocado is a unique fruit in which of seven-carbon (C7) sugars (notably D-mannoheptulose and perseitol) dominate the carbohydrate profile at harvest. Despite growing interest in sugar-mediated ripening processes, limited comparative data exist across cultivars. This work characterises the dynamic changes in non-structural carbohydrates in the mesotecarp of three commercially relevant avocado varieties—Bacon, Fuerte, and Hass—across four defined ripening stages, from unripe to overripe, with five biological replicates per stage. Using a validated hydrophilic interaction liquid chromatography–mass spectrometry (HILIC–MS) method, we quantified five key sugars and assessed their evolution through ripening. Concentrations varied among the studied samples within the following ranges: D-mannoheptulose, 0.4–49 mg/g dry weight (DW); perseitol, 0.5–23 mg/g DW; glucose, 0.8–5.3 mg/g DW; fructose, 0.6–4.5 mg/g DW; and sucrose, 0.5–3.4 mg/g DW. C7 sugar levels consistently declined, while C6 sugars increased—primarily between the intermediate and ready-to-eat stages—with distinct cultivar-specific patterns. Bacon maintained elevated C7 concentrations for a longer period; Fuerte exhibited a rapid transition from C7 to C6 sugars; and Hass displayed a more gradual and balanced shift. Multivariate analysis (partial least squares discriminant analysis, PLS-DA) effectively discriminated between cultivars at each ripening stage, confirming cultivar-specific metabolic signatures. These findings offer new insights into avocado carbohydrate metabolism, emphasising variety-dependent pathways that could inform breeding strategies, optimise postharvest ripening protocols, and support the nutritional characterisation of different avocado cultivars. Full article

This paper presents a dataset for a comparative analysis of direct (spectrophotometric) and indirect (multispectral imagery-based) methods for quantifying crop leaf chlorophyll content. The dataset originates from a study conducted in the Department of Cauca, Colombia, a region characterized by diverse agricultural production. Data collection focused on seven economically important crops, namely coffee (Coffea arabica), Hass avocado (Persea americana), potato (Solanum tuberosum), tomato (Solanum lycopersicum), sugar cane (Saccharum officinarum), corn (Zea mays) and banana (Musa paradisiaca). Sampling was conducted across various locations and phenological stages (healthy, wilted, senescent), with each leaf subdivided into six sections (A–F) to facilitate the analysis of intra-leaf chlorophyll distribution. Direct measurements of leaf chlorophyll content were obtained by laboratory spectrophotometry following the method of Jeffrey and Humphrey, allowing for the determination of chlorophyll A and B content. Simultaneously, indirect estimates of leaf chlorophyll content were obtained from multispectral images captured at the leaf level using a MicaSense Red-Edge camera under controlled illumination. A set of 32 vegetation indices was then calculated from these multispectral images using MATLAB. Both direct and indirect methods were applied to the same leaf samples to allow for direct comparison. The dataset, provided as an Excel (.xlsx) file, comprises raw data covering laboratory-measured chlorophyll A and B content and calculated values for the 32 vegetation indices. Each row of the tabular dataset represents an individual leaf sample, identified by plant species, leaf identifier, and phenological stage. The resulting dataset, containing 16,660 records, is structured to support research evaluating the direct relationship between spectrophotometric measurements and multispectral image-based vegetation indices for estimating leaf chlorophyll content. Spearman’s correlation coefficient reveals significant positive relationships between leaf chlorophyll content and several vegetation indices, highlighting its potential for a nondestructive assessment of this pigment. Therefore, this dataset offers significant potential for researchers in remote sensing, precision agriculture, and plant physiology to assess the accuracy and reliability of various vegetation indices in diverse crops and conditions, develop and refine chlorophyll estimation models, and execute meta-analyses or comparative studies on leaf chlorophyll quantification methodologies. Full article

Despite flies regularly visiting flowers, limited research has gone into their pollination ability on commercial crops. A national project in Australia aimed to identify fly species as potential managed pollinators for the horticultural industry and, in particular, avocado. This study investigated the ability of two calliphorids (Calliphora dubia and Calliphora vicina) and a syrphid (Eristalis tenax) fly species to pollinate Hass avocados in southwestern Australia. Four (4) field trials over three (3) years showed that each fly species (all found across Australia) was capable of pollinating Hass avocados when released into netted enclosures around multiple trees (12–26) during flowering. Trees enclosed with Eristalis tenax produced the highest fruit yield (18.0 kg/tree) outperforming trees pollinated by either C. dubia (11.6), managed honey bees in the open orchard (10.5) or C. vicina (6.8). Increasing fly numbers from 10,000 to 15,000 in the enclosures provided no additional pollination benefit. These results suggest that either E. tenax or C. dubia could be valuable managed pollinators for the avocado industry either with or without honey bees. Calliphora dubia was a significant pollinator during warmer flowering seasons and C. vicina was a useful pollinator during cold and wet flowering seasons. Full article

Background: The implementation of advanced agronomical strategies, including the use of antitranspirant, in order to mitigate the negative effects of environmental stress, particularly heat stress on plants, has become a focal area of research in the Mediterranean basin. This region is characterized by hot and dry summer that affects plant physiology. Methods: The experiment was carried out in Sicily (South Italy) on 12-year-old avocado cv. Hass grafted onto Walter Hole rootstock. Two subplots each of forty homogenous trees were selected and treated (1) with calcium carbonate (DECCO Shield^®) and (2) with water (control) at the following phenological phases: 711, 712 and 715 BBCH. The climatic parameters were recorded throughout the year. Physiological measurements (leaf transpiration, net photosynthesis, stomatal conductance, leaf water potential) were measured at 105, 131 and 168 days after full bloom. Fruit growth was monitored, and physico-chemical analyses were carried out at harvest. Results: The antitranspirant increased photosynthesis and stomatal conductance and reduced leaf transpiration (−26.1%). Fruit growth rate increased during summer, although no morphological and qualitative difference was observed at harvest. PCA highlighted the positive effect of the calcium carbonate on overall plant physiology. Conclusions: Antitranspirant foliar application reduced heat stress effects by improving physiological responses of avocado trees. Full article

Addressing global challenges such as climate change and inequality requires convergence competencies that enable learners to devise sustainable solutions. Such competencies have been emphasized in Science, Technology, Engineering, Mathematics (STEM) fields, but empirical research and assessment tools tailored to Humanities, Arts, and Social Sciences (HASS) remain scarce. This study aimed to develop and validate a self-assessment tool to measure convergence competencies among HASS learners. A three-round Delphi survey with domain experts was conducted to evaluate and refine an initial pool of items. Items with insufficient content validity were revised or deleted, and all retained items achieved a Content Validity Ratio (CVR) of ≥0.800, with most scoring 1.000. The validated instrument was administered to 455 undergraduates participating in a convergence education program. Exploratory factor analysis identified five key dimensions: Convergent Commitment, Future Problem Awareness, Future Efficacy, Convergent Learning, and Multidisciplinary Inclusiveness, explaining 69.72% of the variance. Confirmatory factor analysis supported the model’s goodness-of-fit (χ² (160) = 378.786, RMSEA = 0.054, CFI = 0.952), and the instrument demonstrated high internal consistency (Cronbach’s α = 0.919). The results confirm that the tool is both reliable and valid for diagnosing convergence competencies in HASS contexts, providing a practical framework for interdisciplinary learning and reflective engagement toward sustainable futures. Full article

A partially ordered set (or a poset, for short) is a set endowed with a partial order relation, i.e., with a reflexive, anti-symmetric, and transitive binary relation. As mathematical objects, posets have been intensively studied in the last century, coming to play essential roles in pure mathematics, logic, and theoretical computer science. More recently, they have been increasingly employed in data analysis, multi-criteria decision-making, and social sciences, particularly for building synthetic indicators and extracting rankings from multidimensional systems of ordinal data. Posets naturally represent systems and phenomena where some elements can be compared and ordered, while others cannot be and are then incomparable. This makes them a powerful data structure to describe collections of units assessed against multidimensional variable systems, preserving the nuanced and multi-faceted nature of the underlying domains. Moreover, poset theory collects the proper mathematical tools to treat ordinal data, fully respecting their non-numerical nature, and to extract information out of order relations, providing the proper setting for the statistical analysis of multidimensional ordinal data. Currently, their use is expanding both to solve open methodological issues in ordinal data analysis and to address evaluation problems in socio-economic sciences, from multidimensional poverty, well-being, or quality-of-life assessment to the measurement of financial literacy, from the construction of knowledge spaces in mathematical psychology and education theory to the measurement of multidimensional ordinal inequality/polarization. Full article

Dry matter (DM) is a critical parameter for avocado quality and commercialization, particularly in the ‘Hass’ cultivar, where it is closely associated with the oil content and flavor. This study evaluated the fatty acid composition and sensory attributes of ‘Hass’ avocados with varying DM levels (19%, 21%, 24%, and 27%) cultivated in the Canary Islands. Additionally, the impact of dehydration methods (oven and microwave) and sample preparation techniques on the oil content and lipid profiles were assessed. Six main fatty acids were identified, with oleic acid (38–43%) and palmitic acid (30–36%) being predominant. Higher DM levels were associated with increased concentrations of palmitoleic and linoleic acids. Drying methods did not significantly alter the fatty acid profile, supporting the crushed microwave-dried (CMW) method as a practical, low-cost approach for preserving lipid integrity. Consumer panelists showed a clear preference for avocados with higher DM contents (24–27%), associating the flavor (86.2%) and texture (59.6%) with the purchase intent. The high monounsaturated fatty acid content, particularly oleic acid, qualifies these avocados for the European nutritional claim ‘high in monounsaturated fat.’ This is the first study to characterize these parameters in ‘Hass’ avocados from the Canary Islands, contributing to both quality assessments and potential marketing strategies based on nutritional and sensory attributes. Full article

Avocado, a fruit consumed worldwide and essential for countries like Mexico and Chile, faces significant postharvest challenges, particularly during prolonged storage and transportation periods, where Botryosphaeriaceae and Glomerellaceae genera cause fruit rots that can generate substantial economic losses. This study investigated three Hass avocado orchards in the Valparaíso region of Chile to identify spore dispersion peaks, analyze the aerial dynamics of fungal inoculum, and evaluate the association with climatic conditions, as well as the incidence (I) and damage index (DI) of fruit rots. Spore traps were installed in symptomatic trees and monitored weekly over 13 months. Meteorological data were collected in parallel. Fruits from these orchards were sampled to evaluate postharvest rots, physiological maturity, and disease severity using molecular techniques, including DNA sequencing and phylogenetic analysis of isolated pathogens. The results revealed that spore peaks for both fungal families were closely associated with increased rainfall and high relative humidity, particularly from June to mid-September (winter season). The Santo Domingo orchard exhibited the highest disease pressure, with stem-end rot reaching an I of 44% and a DI of 17.25%, and anthracnose reaching an I of 23% and a DI of 12.25%. This study provides the first long-term, field-based evidence of airborne spore dynamics of Botryosphaeriaceae and Glomerellaceae in Chilean avocado orchards and their statistical relationship with environmental variables. These findings highlight the potential of incorporating climatic indicators—such as rainfall thresholds and humidity levels—into monitoring and early-warning systems to optimize fungicide application timing, reduce unnecessary chemical use, and improve postharvest disease management in avocado production. Full article

Ozonated oils have promise as biostimulants, positively affecting physiological processes that promote plant growth and biomass accumulation. However, additional research is required to clarify their mechanisms of action, optimize dosages, and define effective application strategies. This study aimed to evaluate the biostimulant effect of three concentrations of two oils, avocado (Persea maricana Mill cv Hass) (50, 100, and 200 meqO₂ kg⁻¹) and high-oleic palm (Elaeis guineensis Jacq.) (5, 10, and 20 meqO₂ kg⁻¹), on the “Bolo Verde” squash Cucurbita moschata. The experiment followed a completely randomized design with a three-factor factorial arrangement: Factor I—type of ozonated oil; Factor II—application concentration (low, medium, and high); Factor III—application method (drench or foliar). The trial consisted of 15 experimental units, each with 32 plants, totaling 480 plants. Data were analyzed using SAS software. A one-way ANOVA was performed, and means were compared using Tukey’s test p ≤ 0.05. The drench application of high-concentration ozonated avocado oil (200 meqO₂ kg⁻¹) produced the most favorable biostimulant response, significantly increasing plant height, leaf number, root length, root volume, and total dry weight. This was followed by the drench application of low-concentration ozonated high-oleic palm oil (5 meqO₂ kg⁻¹), which yielded the highest dry matter accumulation. For the net assimilation rate (NAR) and leaf area index (LAI), the drench application of ozonated avocado oil at a high concentration resulted in 4.29 g cm⁻² day⁻¹ NAR and 7957.99 LAI, while low-concentration high-oleic palm oil recorded 4.36 g cm⁻² day⁻¹ NAR and 7208.40 LAI. Both treatments showed statistically significant differences (p < 0.05) compared to the control 2.35 g cm⁻² day⁻¹ NAR and 6780.24 LAI, indicating improved photosynthetic efficiency and leaf expansion. Similar trends were observed for crop growth rate (CGR) and relative growth rate (RGR). The drench application of high-concentration ozonated avocado oil yielded a CGR of 6.77 × 10⁻⁴ g cm⁻² day⁻¹ and RGR 0.0441953 g g⁻¹ day⁻¹. Low-concentration high-oleic palm oil drench application resulted in the highest CGR of 7.35 × 10⁻⁴ g cm⁻² day⁻¹ and RGR 0.0454216 g g⁻¹ day⁻¹. These values were significantly higher than those of the control (CGR 4.14 × 10⁻⁴ g cm⁻² day⁻¹; RGR 0.0357569 g g⁻¹ day⁻¹). These results suggest that the drench application of ozonated oils not only enhances photosynthesis and leaf growth but also favors the incorporation and accumulation of biomass in “Bolo Verde” squash. Full article

The production of fruit crops plays a vital role in the agricultural sector, contributing significantly to the social and economic development of rural communities. In Brazil, fruit production is diverse due to favorable edaphoclimatic conditions, with avocado (Persea americana Mill.) emerging as an important crop. Its production continues to expand in both cultivated areas and yield, making it a key export to non-producing countries. However, despite its importance, nutritional management information, crucial for achieving high yields, remains limited. Current guidelines on nutrition monitoring are outdated, general, and based on data from other countries with different edaphoclimatic conditions, making them not directly applicable to Brazilian orchards. Furthermore, outdated nutritional information becomes less reliable over time, as climate change alters soil conditions and crop nutrient concentrations and requirements, reinforcing the need for the establishment of up-to-date and specific nutritional information. This study aimed to establish nutritional standards for ‘Hass’ avocado production using the Diagnosis and Recommendation Integrated System (DRIS) and Compositional Nutrient Diagnosis (CND) methodologies, and to define sufficiency ranges (SRs) and Critical Levels (CLs) for both macronutrients (N, P, K, Ca, Mg, and S) and micronutrients (B, Cu, Fe, Mn, and Zn). The analyses were based on yield (t ha⁻¹) and leaf nutrient content data from commercial orchards, with datasets divided into younger (4–9 years) and older (10–26 years) plant groups. The DRIS effectively established nutritional standards for younger plants, explaining 11% of yield variation through nutritional balance. CND, in turn, was effective for both groups, accounting for 14% of yield variation and outperforming DRIS in associating nutritional status with productivity. SRs and CLs for ‘Hass’ avocado production were defined using both DRIS and CND. Together, these indices and diagnostic parameters offer valuable tools for enhancing nutritional monitoring and fertilization strategies in Brazil. Notably, SRs and CLs varied according to plant age. Full article

México is the world’s leading producer of avocado, with 2,540,715 tons in the last year. Trametes spp. are macromycete fungi that rot wood. In 2022, in the state of Michoacán, México, sporomas of Trametes sp. were found in the trunks of avocado trees (Persea americana var. Hass) of 10 years old and older. The trees showed disease symptoms including yellowing of leaves, widespread defoliation, and wilting. It was observed that 10% of the infected trees were felled after heavy rains. In the place where the fungus settled, abundant cream-colored and cottony mycelium developed, causing “white rot”. The incidence of the disease in the sampled orchards was 60% in the tree population per hectare with 350 trees. The symptomatic trees studied were randomly selected from seven orchards. The collected fungal samples show typical structures corresponding to Trametes sp., including large sporomas, a pileus with a surface of concentric zones of various ocher tones, and a porous hymenium. The samples showed a 99% match with the species Trametes hirsuta. Laboratory bioassays of inoculation in fresh wood segments of avocado formed typical sporomas of the pathogen. Finally, the fungus was recovered and reisolated in vitro in PDA, and its identity was confirmed through the morphological characteristics and molecular tests. To the best of our knowledge, this article reports for the first time that P. americana cv. Hass and Mendez are new hosts for T. hirsuta. Therefore, the environmental and horticultural management conditions that favor the proliferation of T. hirsuta must be investigated. Full article

Identifying and ranking the key drivers of grassland conversion at the county level is crucial for developing targeted policies and improving protection efficiency. However, this process faces methodological challenges because of spatial and temporal variability. Partial order theory offers a robust framework for addressing these complexities. This study applies partial order theory (POT) combined with the Hasse diagram technique (HDT) to analyze grassland conversion in the Hohhot–Baotou–Ordos region during two time periods (2000–2010 and 2010–2020). First, patterns of grassland transformation are quantified, and the dominant driving factors of grassland conversion out (GCO) are identified and ranked, highlighting regional differences and temporal shifts. By integrating POT and HDT, this study offers a novel approach to handling complex, nonlinear, and hierarchical relationships among multiple drivers. The results provide scientific insight and policy recommendations for region-specific grassland management and sustainable land-use planning. The results show that (1) transitions between grasslands and other land-use types became more frequent across the two periods. Specifically, the rates of grassland conversion out and conversion increased from 2.1% and 3.5% during the period 2000–2010 to 4.7% and 4.8% during the period 2010–2020, respectively. (2) Urbanization was the primary driver of grassland conversion in 11 and 10 of the 18 counties during the first and second periods, respectively, followed by factors related to weather variables. (3) In the future, the eastern region of the study area needs to prioritize mitigating the impacts of urban development, while the western region should focus on enhancing ecological construction projects. This study recommends adopting region-specific ecological protection and economic strategies for balanced outcomes in conservation and development. Full article

Basketball games are characterized by the large number of lineups that can be used by the coach during a game, e.g., with 12 players there are 792 possible lineups. This has led to the development of several statistics for the combinations of players on the court since team performance depends on synergy among players. It is of primary importance for a basketball team to understand the team performance and aid the coaching staff in making the proper decisions. In this work, we apply data mining and knowledge extraction techniques to basketball analytics. In particular, we propose an algorithm for answering questions (including filtering and maximization) about the team performance when any K-Player lineup is on the court ($1\le K\le 5$). The algorithm uses a semilattice representation and a depth-first search traversal that incrementally computes the statistics by exploiting set theory properties. As a case study, we provide experiments by using lineups mainly from the EuroLeague Basketball but also from the National Basketball Association (NBA). Regarding the results, the proposed method is more than 30× faster than the baseline for the EuroLeague and 200× faster for the NBA. Indicatively, we can compute the key traditional cumulative and average statistics for all K-Player combinations of players of the EuroLeague of a single season in less than 1 s. Finally, we introduce indicative statistics using the computations mentioned. Full article