Search Results (4,063)

Imbalanced data situations exist in most fields of endeavor. The problem has been identified as a major bottleneck in machine learning/data mining and is becoming a serious issue of concern in food processing applications. Inappropriate analysis of agricultural and food processing data was identified as limiting the robustness of predictive models built from agri-food applications. As a result of rare cases occurring infrequently, classification rules that detect small groups are scarce, so samples belonging to small classes are largely misclassified. Most existing machine learning algorithms including the K-means, decision trees, and support vector machines (SVMs) are not optimal in handling imbalanced data. Consequently, models developed from the analysis of such data are very prone to rejection and non-adoptability in real industrial and commercial settings. This paper showcases the reality of the imbalanced data problem in agri-food applications and therefore proposes some state-of-the-art artificial intelligence algorithm approaches for handling the problem using methods including data resampling, one-class learning, ensemble methods, feature selection, and deep learning techniques. This paper further evaluates existing and newer metrics that are well suited for handling imbalanced data. Rightly analyzing imbalanced data from food processing application research works will improve the accuracy of results and model developments. This will consequently enhance the acceptability and adoptability of innovations/inventions. Full article

Porous starch has been created through hydrolysis by amyloglucosidase and α-amylase. However, little information is known about the precise evolution of multi-scale structures of starch during digestion. In this study, rice starch and potato starch, containing different crystalline structures, were hydrolyzed by amyloglucosidase and α-amylase for 20 and 60 min, respectively, and their resulting structural changes were examined. The digestion process caused significant degradation of the molecular structures of rice and potato starches. In addition, the alterations in the ordered structures varied between the two starches. Rice starch exhibited porous structures, thicker crystalline lamellae as determined by small-angle X-ray scattering, and enhanced thermostability after digestion using differential scanning calorimetry. For rice starch, the extent of crystalline structures was analyzed with an X-ray diffractometer; it was found to first increase after 20 min of digestion and then decrease after 60 min of digestion. In contrast, potato starch did not display porous structures but exhibited thicker crystalline lamellae and a reduction in ordered structures after digestion. These findings suggest that it is possible to intentionally modulate the multi-scale structures of starch by controlling the digestion time, thereby providing valuable insights for the manipulation of starch functionalities. Full article

Identifying and counting fish are crucial for managing stocking, harvesting, and marketing of farmed fish. Researchers have used convolutional networks for these tasks and explored various approaches to enhance network learning. Batch normalization is one technique that improves network stability and accuracy. This study aimed to evaluate machine learning for identifying and counting pirapitinga Piaractus brachypomus fry with different batch sizes. The researchers used one thousand photographic images of Pirapitinga fingerlings, labeled with bounding boxes. They trained the adapted convolutional network model with batch normalization layers added at the end of each convolution block. They set the training to one hundred and fifty epochs and tested batch sizes of 5, 10, and 20. Furthermore, they measured network performance using precision, recall, and [email protected]. Models with smaller batch sizes performed less effectively. The training with a batch size of 20 achieved the best performance, with a precision of 96.74%, recall of 95.48%, [email protected] of 97.08%, and accuracy of 98%. This indicates that larger batch sizes improve accuracy in detecting and counting pirapitinga fry across different fish densities. Full article

This study established novel and high-throughput strategies for the simultaneous analysis of 30 fluorinated emerging pollutants in different matrices from the shrimp aquaculture system in eastern China using UHPLC-MS/MS. The parameters of SPE for analysis of water samples and of QuEChERS methods for sediment and shrimp samples were optimized to allow the simultaneous detection and quantitation of 17 per- and polyfluoroalkyl substances (PFASs) and 13 fluoroquinolones (FQs). Under the optimal conditions, the limits of detection of 30 pollutants for water, sediment, and shrimp samples were 0.01–0.30 ng/L, 0.01–0.22 μg/kg, and 0.01–0.23 μg/kg, respectively, while the limits of quantification were 0.04–1.00 ng/L, 0.03–0.73 μg/kg, and 0.03–0.76 μg/kg, with satisfactory recoveries and intra-day precision. The developed methods were successfully applied to the analysis of multiple samples collected from aquaculture ponds in eastern China. PFASs were detected in all samples with concentration ranges of 0.18–0.77 μg/L in water, 0.13–1.41 μg/kg (dry weight) in sediment, and 0.09–0.96 μg/kg (wet weight) in shrimp, respectively. Only two FQs, ciprofloxacin and enrofloxacin, were found in the sediment and shrimp. In general, this study provides valuable insights into the prevalence of fluorinated emerging contaminants, assisting in the monitoring and control of emerging contaminants in aquatic foods. Full article

This systematic review, based on an adaptation of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement from 2020, focuses on studies of the atmospheric mechanisms underlying extreme precipitation events in mainland Portugal, as well as observed trends and projections. The 54 selected articles cover the period from 2000 to 2024, in which the most used keywords are “portugal” and “extreme precipitation”. Of the 54, 23 analyse trends and climate projections of precipitation events, confirming a decrease in total annual precipitation, especially in autumn and spring, accompanied by an increase in the frequency and intensity of extreme precipitation events in autumn, spring and winter. Several articles (twelve) analyse the relationship between synoptic-scale circulation and heavy precipitation, using an atmospheric circulation types approach. Others (two) establish the link with teleconnection patterns, namely the North Atlantic Oscillation (NAO), and still others (three) explore the role of atmospheric rivers. Additionally, five articles focus on evaluating databases and Numerical Weather Prediction (NWP) models, and nine articles focus on precipitation-related extreme weather events, such as tornadoes, hail and lightning activity. Despite significant advances in the study of extreme precipitation events in Portugal, there is still a lack of studies on hourly or sub-hourly scales, which is critical to understanding mesoscale, short-lived events. Several studies show NWP models still have limitations in simulating extreme precipitation events, especially in complex orography areas. Therefore, a better understanding of such events is fundamental to promoting continuous improvements in operational weather forecasting and contributing to more reliable forecasts of such events in the future. Full article

Within the European Union (EU), new plant varieties to be included in the Common catalog of a member state have to be registered on the national list after plant variety testing processes to establish whether the candidate variety is distinguishable, uniform, and stable (DUS) and meets the cultivation or use value requirement (VCU). Technical development, climate change, and changing consumer needs, including the detection of GMOs, necessitate the innovation of plant variety testing methods. In our study, we assessed new characters, testing methods, and inclusion of additional data for the potential to benefit the DUS and VCU protocols. To achieve our goal, we asked experts to fill in questionnaires for the DUS and VCU methods currently used for a selection of common crops, including potato, maize, lentil, oilseed rape, and perennial grass. Within the EU-funded “InnoVar” project, partners sent out questionnaires to 19 European Countries and to 3 countries outside Europe. Surveys were aimed at analyzing the strengths, weaknesses, opportunities, and threats (SWOT) of the current methods. With their help, it is possible to look for a new direction, opportunity, and strategy to incorporate, together with the innovative new techniques, into the development of the new methods. Our study demonstrated that the SWOT analysis could be used to achieve the set goals. Results obtained after evaluation of surveys confirmed that introduction of new characters such as cold tolerance, nitrogen and water efficiency, etc. has become necessary, as has the inclusion of new test methods (molecular markers, precision techniques, organic farming). The development of high-yielding, disease and/or pest-resistant plant varieties with good adaptability and the accurate evaluation of genotypes play a crucial role in ensuring that farmers can access high-performing plant varieties and contribute to sustainable food production. Full article

Commercially cultivated Prunus species are commonly grown in adjacent or mixed orchards and can be infected with unique or commonly shared viruses. Apple (Malus domestica), another member of the Rosacea and distantly related to Prunus, can share the same growing regions and common pathogens. Pollen can be a major route for virus transmission, and analysis of the pollen virome in tree fruit orchards can provide insights into these virus pathogen complexes from mixed production sites. Commercial honey bee (Apis mellifera) pollination is essential for improved fruit sets and yields in tree fruit production systems. To better understand the pollen-associated virome in tree fruits, metagenomics-based detection of plant viruses was employed on bee and pollen samples collected at four time points during the peak bloom period of apricot, cherry, peach, and apple trees at one orchard site. Twenty-one unique viruses were detected in samples collected during tree fruit blooms, including prune dwarf virus (PDV) and prunus necrotic ringspot virus (PNRSV) (Genus Ilarvirus, family Bromoviridae), Secoviridae family members tomato necrotic ringspot virus (genus Nepovirus), tobacco necrotic ringspot virus (genus Nepovirus), prunus virus F (genus Fabavirus), and Betaflexiviridae family member cherry virus A (CVA; genus Capillovirus). Viruses were also identified in composite leaf and flower samples to compare the pollen virome with the virome associated with vegetative tissues. At all four time points, a greater diversity of viruses was detected in the bee and pollen samples. Finally, the nucleotide sequence diversity of the coat protein regions of CVA, PDV, and PNRSV was profiled from this site, demonstrating a wide range of sequence diversity in pollen samples from this site. These results demonstrate the benefits of area-wide monitoring through bee pollination activities and provide new insights into the diversity of viruses in tree fruit pollination ecosystems. Full article

The main objective of this work was to develop a viewer with web output, through which the changes experienced by the mangroves of the Gran Humedal del Norte de Ciego de Avila (GHNCA) can be evaluated from remote sensors, contributing to the understanding of the spatiotemporal variability of their vegetative dynamics. The achievement of this objective is supported by the use of open-source technologies such as MapStore, GeoServer and Django, as well as Google Earth Engine, which combine to offer a robust and technologically independent solution to the problem. In this context, it was decided to adopt an action model aimed at automating the workflow steps related to data preprocessing, downloading, and publishing. A visualizer with web output (Geospatial System for Monitoring Mangrove Ecosystems or SIGMEM) is developed for the first time, evaluating changes in an area of central Cuba from different vegetation indices. The evaluation of the machine learning classifiers Random Forest and Naive Bayes for the automated mapping of mangroves highlighted the ability of Random Forest to discriminate between areas occupied by mangroves and other coverages with an Overall Accuracy (OA) of 94.11%, surpassing the 89.85% of Naive Bayes. The estimated net change based on the year 2020 of the areas determined during the classification process showed a decrease of 5138.17 ha in the year 2023 and 2831.76 ha in the year 2022. This tool will be fundamental for researchers, decision makers, and students, contributing to new research proposals and sustainable management of mangroves in Cuba and the Caribbean. Full article

Ensuring sustainability has increasingly become a significant concern not only in aquaculture but in the general agrifood sector. Therefore, it is imperative to investigate pathways to feed substitutes/best practices to enhance aquaculture sustainability. The application of fungi in aquaculture provides innovative methods to enhance the sustainability and productivity of aquaculture. Fungi play numerous roles in aquaculture, including growth, immunity enhancement and disease resistance. They also play a role in bioremediation of waste and bioflocculation. The application of fungi improves the suitability and utilization of terrestrial plant ingredients in aquaculture by reducing the fibre fractions and anti-nutritional factors and increasing the nutrients and mineral contents of plant ingredients. Fungi are good flotation agents and can enhance the buoyancy of aquafeed. Pigments from fungi enhance the colouration of fish fillets, making them more attractive to consumers. This paper, via the relevant literature, explores the multifaceted roles of fungi in aquaculture, emphasizing their potential to transform aquaculture through environmentally friendly and sustainable techniques. The effectiveness of fungi in reducing fibre fractions and enhancing nutrient availability is influenced by the duration of fermentation and the dosage administered, which may differ for various feed ingredients, making it difficult for most aquaculture farmers to apply fungi approximately. Therefore, the most effective dosage and fermentation duration for each feed ingredient should be investigated. Full article

The discarding of agri-food by-products is a stringent problem due to their high environmental impact. Recovery strategies can lead to a reduction of waste and result in new applications. Agri-food waste represents a source of bioactive molecules, which could promote health benefits. The primary goal of this research has been the assessment of the antioxidant activity of milk permeate, a dairy farm by-product, and the isolation and identification of peptide fractions endowed with antioxidant activity. The chromatographic extraction of the peptide fractions was carried out, and the peptides were identified by mass spectrometry. The fractions showed radical scavenging activity in vitro. Moreover, the results in the Caco-2 cell model demonstrated that the peptide fractions were able to protect from oxidative stress by stimulating the Keap1/Nrf2 antioxidant signaling pathway, increasing the transcription of antioxidant enzymes. In addition, the bioactive peptides can affect cellular metabolism, increasing mitochondrial respiration. The action of the peptide fractions was also assessed in vivo on a zebrafish model and resulted in the protection of the whole organism from the adverse effects of acute cold stress, highlighting their strong capability to protect from an oxidative insult. Altogether, the results unveil novel recovery strategies for food by-products as sources of antioxidant bioactive peptides that might be utilized for the development of functional foods. Full article

The accelerating impact of climate change on golf course conditions has led to a significant increase in pesticide dependency, underscoring the importance of innovative management strategies. The shift from Coupled Model Intercomparison Project Phase 5 (CMIP5) to the latest CMIP6 phase has drawn the attention of professionals, including engineers, decision makers, and golf course managers. This study evaluates how climate projections from CMIP6, using Canadian Earth System Models (CanESM2 and CanESM5), impact pesticide application trends on Quebec’s golf courses. Through the comparison of temperature and precipitation projections, it was found that a more substantial decline in precipitation is exhibited by CanESM2 compared to CanESM5, while the latter projects higher temperature increases. A comparison between historical and projected pesticide use revealed that, in most scenarios and projected periods, the projected pesticide use was substantially higher, surpassing past usage levels. Additionally, in comparing the two climate change models, CanESM2 consistently projected higher pesticide use across various scenarios and projected periods, except for RCP2.6, which was 27% lower than SSP1-2.6 in the second projected period (PP2). For all commonly used pesticides, the projected usage levels in every projected period, according to climate change models, surpass historical levels. When comparing the two climate models, CanESM5 consistently forecasted greater pesticide use for fungicides, with a difference ranging from 65% to 222%, and for herbicides, with a difference ranging from 114% to 247%, across all projected periods. In contrast, insecticides, growth regulators, and rodenticides displayed higher AAIR values in CanESM2 during PP1 and PP3, showing a difference of 28% to 35.6%. However, CanESM5 again projected higher values in PP2, with a difference of 1.5% to 14%. Full article

This study introduces a novel approach to analyze glycosidic linkages in unfractionated polysaccharides from alcohol-insoluble residues (AIRs) of five brown seaweed species. GC-MS analysis of partially methylated alditol acetates (PMAAs) enables monitoring and comparison of structural variations across different species, harvest years, and tissues with and without blanching treatments. The method detects a wide array of fucose linkages, highlighting the structural diversity in glycosidic linkages and sulfation position in fucose-containing sulfated polysaccharides. Additionally, this technique enhances cellulose quantitation, overcoming the limitations of traditional monosaccharide composition analysis that typically underestimates cellulose abundance due to incomplete hydrolysis of crystalline cellulose. The introduction of a weak methanolysis-sodium borodeuteride reduction pretreatment allows for the detection and quantitation of uronic acid linkages in alginates. Full article

The transition to sustainability in agriculture faces significant challenges, especially to balance environmental goals with the practical demands of food production. This paper examines two different case studies that reveal the complexities of agricultural regulation. The first case focuses on the valorization of agri-food residual biomasses, highlighting the potential to transform food waste into valuable bioproducts such as bioenergy and biofertilizers. Despite the clear environmental and economic benefits, the absence of specific European regulations hinders the widespread adoption of these practices. Without clear rules for achieving “end-of-waste” status, the development and marketing of bio-based products remain restricted. The second case study examines the European Union’s unsuccessful effort to implement the Sustainable Use of Pesticides Regulation (SUR), which aimed to reduce pesticide use by 50% by 2030. Although the regulation sought to align agricultural practices with the EU’s Green Deal, it triggered widespread protests from farmers concerned about the potential economic losses and decreased productivity. These two cases, one showing under-regulation and the other over-regulation, highlight the need for balanced and practical regulatory frameworks that promote sustainability without imposing unrealistic demands on stakeholders. This paper ends with recommendations to harmonize regulations across Europe, ensuring that both innovation in agricultural waste management and practical pesticide reduction strategies are implemented in a way that supports farmers and producers, minimizing economic disruptions and encouraging sustainable agricultural practices. Full article

In spite of the detrimental effects of climate change and decreasing resource efficiency, maize farming is essential to the world’s food and nutritional security. With regard to sustainable maize farming in this environment, conservation agriculture (CA) offers a framework that holds promise in terms of low soil disturbance, perennial soil cover, and sustainable crop rotation. In order to acquire more profound information on the research advancements and publication patterns related to maize under CA scenarios, a bibliometric analysis was conducted. This involved utilizing René Descartes’s Discourse Framework to extract and screen 2587 documents spanning the years 2001 to 2023 from the Dimensions.ai database. The mapping showed that different stakeholders were becoming more interested in maize research under various CA pathways, with a greater emphasis on reaching the second sustainable development target, or “zero hunger”. The most influential journals were “Soil and Tillage Research” and “Field Crops Research”, with 131 and 85 papers with 6861 and 6186 citations, respectively. The performance analysis found “Christian L. Thierfelder” and “Mangi Lal Jat” as the eminent researchers in the areas of maize research under CA. Thus, the International Maize and Wheat Improvement Center (CIMMYT) and the Indian Agricultural Research Institute (IARI) were identified as the important institutions in conducting research pertaining to maize under CA systems, while the United States, India, and Mexico emerged as prominent countries with notable collaboration efforts for imparting research under the given scenarios. Three thematic clusters delineating keywords from three distinct sections—key drivers, objectives, and methodology—were identified through co-word analysis using word clouds, tree maps, and thematic networking of the keywords from the abstract and titles of screened publications. These thematic clusters highlighted the growing emphasis on region-specific studies under CA, particularly in sub-Saharan Africa and the Indo-Gangetic plain, to enhance the resilience of the agri-food system. Therefore, mapping maize’s potentialities within the CA framework has revealed the field’s dynamic nature and offers insightful information to researchers and policymakers that could help them plan future studies and cooperative initiatives aimed at boosting the productivity and sustainability of maize-based systems under the CA framework. Full article

Olive cultivation, an icon of Mediterranean agriculture, economy, and cultural heritage, faces significant challenges due to climate change and soil degradation. Climate projections indicate that altered precipitation patterns, rising temperatures, and increased frequency of extreme weather events will adversely affect olive tree growth, fruit quality, and yield. This review provides a novel perspective on addressing these challenges through both long-term and short-term adaptation strategies, emphasizing innovative products, advanced technologies, and practical solutions that must work synergistically and be tailored to regional conditions. Long-term practices refer to proactive strategies for enduring climate resilience, including cover cropping, mulching, soil amendments, and breeding programs which enhance soil health, improve water retention, and increase the trees’ resilience. Short-term strategies focus on immediate impacts, offering immediate stress relief and enhanced plant physiological responses, including optimized irrigation systems, pruning management, particle coating films, biostimulants, and plant growth regulators. The review underscores the importance of aligning agricultural practices with sustainability goals and evolving environmental policies and the education of farmers and policymakers. By integrating adaptive practices and technological advancements, the olive sector can better address climate challenges, contribute to global food security, and advance environmental sustainability. Full article