Search Results (44)

The market of plant-based food, including plant-based beverages, is one of the fastest-growing food sectors within the food industry and a subject of major research in the area of new product development. Plant-based beverages are a diverse group of non-dairy beverages with varying nutritional value, depending on the raw material sources and additional substances used in their production. A wide range of plant beverages makes it possible to choose products tailored to individual consumer preferences and needs as a part of sustainable dietary patterns. Increased consumer awareness of the environmental and health implications of proper nutrition, interest in plant-based diets, climate, and natural resource protection, as well as ethical concerns about animal welfare and the negative environmental impact of animal production, have led some consumers to seek a more balanced diet based on varied plant-based products, including beverages. Considering the highly diversified nutritional value of plant-based beverages, their availability, convenience, accessibility to consumers, ethical and environmental concerns, increasing health concerns as well as growing popularity of plant-based beverages as potential cow-milk alternatives, the Group of Experts in medicine and nutritional sciences presents the opinion on the nutritional value, health benefits and concerns of the available plant-based beverages. The opinion was based on a critical review of the current scientific literature, as well as on the experts’ experience. This knowledge can be used to make the right choices to improve the nutritional status and health of the consumers from different groups. Since the nutritional profiles of plant-based beverages vary across different plant-based drink varieties and they do not have standards of identity, in our opinion, there is a need for action to standardize nutrient fortification regarding the type and amount of added ingredients to ensure the safety of consumers and avoid potential over- or under-fortification of plant-based beverages. Full article

Seafloor topography data are fundamental for marine resource development, oceanographic research, and maritime rights protection. However, approximately 75% of the ocean remains unsurveyed for bathymetry. Sole reliance on shipborne measurements is insufficient for constructing a global bathymetric model within a short timeframe; consequently, satellite altimetry-based inversion techniques are essential for filling data gaps. Recent advancements have improved the variety and quality of satellite altimetry gravity data. To leverage the complementary advantages of multiparameter gravity data, we propose a 1D convolutional neural network based on a convolutional attention module, termed the Attention Channel 1D Convolutional Network (AC1D). Results of a case study of the Mariana Trench indicated that the AC1D grid predictions exhibited improved agreement with single-beam depth checkpoints, with standard deviation reductions of 6.32%, 20.79%, and 36.77% and root mean square error reductions of 7.11%, 22.82%, and 50.99% compared with those of parallel linked backpropagation, the gravity–geological method, and a convolutional neural network, respectively. The AC1D grid demonstrated enhanced stability in multibeam bathymetric validation metrics and exhibited better consistency with multibeam bathymetry data and the GEBCO2023 grid. Power spectral density analysis revealed that AC1D effectively captured rich topographic signals when predicting terrain features with wavelengths below 6.33 km. Full article

In recent years, the internet has developed rapidly. With the popularity of social media, uploading and backing up digital images has become the norm. A huge number of digital images are circulating on the internet daily, and issues related to information security follow. To protect intellectual property rights, digital watermarking is an indispensable technology. However, the common lossy compression technology in the network transmission process is a big problem for watermarking. This paper describes an innovative semi-blind watermarking method with the use of deep convolutional generative adversarial networks (DCGANs) for hiding and extracting watermarks from JPEG-compressed images. The proposed method achieves an average peak signal-to-noise ratio (PSNR) of 49.99 dB, a structural similarity index (SSIM) of 0.95, and a bit error rate (BER) of 0.008 across varying JPEG quality factors. The process is based on an embedder, decoder, generator, and discriminator. It allows watermarking, decoding, or reconstruction to be symmetric such that there is less distortion and durability is improved. It constructs a specific generator for each image and watermark that is supposed to be protected. Experimental results show that, with the variety of JPEG quality factors, the restored watermark achieves a remarkably low corrupted rate, outstripping recent deep learning-based watermarking methods. Full article

Variety characterization is crucial in the seed trade, particularly for protecting variety rights. However, the identification of roselle (Hibiscus sabdariffa L.) varieties, known for their beneficial effects on human health and high processing potential, has traditionally relied on morphological traits due to limited genetic information. To investigate genetic polymorphisms of roselle germplasms and to develop breeder-accessible genotyping tools, this study first phenotyped a roselle collection from diverse geographical origins for the selection of core varieties, and then utilized double-digest restriction-associated DNA sequencing (ddRAD-seq) to identify 53,746 single nucleotide polymorphisms (SNPs) across 17 core varieties. Cluster analysis of the SNP data effectively grouped varieties with similar genetic backgrounds. From this genetic information, we selected nine SNPs as a toolkit to simplify core variety discrimination. These SNPs were then converted into breeder-friendly kompetitive allele-specific PCR (KASP) markers, facilitating the classification of an additional 54 roselle accessions. In conclusion, this research contributes novel insights into the genetic relationships among roselle varieties, and establishes a robust framework utilizing ddRAD-seq and KASP markers for improved genetic resource identification and application in breeding programs. Full article

Climate change poses significant threats to coffee supply chains, highlighting the crucial role of coffee genetic resources in enhancing resilience and improving the livelihoods of coffee farmers. Increasing climate change effects are intensifying pressure to develop new high-performance resilient varieties. Current cultivated coffee species include Coffea arabica and C. canephora, while uncultivated genetic resources include C. stenophylla, C. racemosa, and many others among the 130 known coffee species. To protect and recognize the property rights of countries and people hosting and conserving genetic resources, the international community has developed regulations embodied in the Plant Treaty and the Nagoya Protocol, among others. The majority of coffee genetic resources originate in Africa and are maintained in large field collections, particularly in Côte d’Ivoire, Ethiopia, and Madagascar. The 2023 International Coffee Convention (ICC) highlighted the need for community awareness in applying these international regulations. To foster a common understanding and establish precise rules for exchanging coffee genetic resources, the Crop Trust and the International Coffee Organization organized an invitation-only satellite workshop in Mannheim, Germany, on 16 October 2024, in connection with ICC 2024. International experts on the Nagoya Protocol and Plant Treaty and genebank experts were invited to participate. This presentation summarizes key outcomes from the workshop, covering topics such as (i) key requirements of the Convention on Biological Diversity (CBD), its Nagoya Protocol, and the Plant Treaty specifically applicable to the coffee sector; (ii) assessment of the coffee sector’s readiness to implement these international regulations for the transparent use and exchange of coffee genetic resources; (iii) suggestions for mechanisms enabling transparent use and exchange of coffee genetic resources in compliance with international regulations; (iv) evaluation of strategies for generating benefits for communities hosting coffee genetic resources; (v) a practical, user-friendly checklist to ensure the correct handling of coffee genetic resources in line with international regulations; and (vi) a practical decision-making tree with examples to differentiate genetic resources falling under Nagoya/CBD and the Plant Treaty from others. The workshop’s discussions and outcomes expanded on these topics, yielding several concrete initiatives and recommendations. Most importantly, the workshop identified critical gaps in existing coffee genetic resource collections and proposed a global safety duplication strategy. Participants conceptualized a global platform to facilitate the exchange and use of coffee genetic resources, including a centralized database and a system for tracking benefit-sharing obligations. A comprehensive list categorizing coffee varieties based on their status under the Nagoya Protocol may be initiated to clarify access and benefit-sharing requirements. The workshop concluded with a clear roadmap for advancing coffee genetic resource conservation and exchange. Full article

Health care is currently showing a fall in heart failure (HF) incidence and prevalence, particularly in developed countries, but with only a subset receiving appropriate therapy to protect the heart against maladaptive processes such as fibrosis and hypertrophy. Appropriate markers of advanced HF remain unidentified, which would help in choosing the most suitable therapy and avoid major compliance problems. Speckle tracking echocardiography (STE) is a good choice, being a non-invasive imaging technique which is able to assess cardiac deformation in a variety of conditions. Several multicenter studies and meta-analyses have demonstrated the clinical application and accuracy of STE in early and late stages of HF, as well as its association with both left ventricular (LV) filling pressures and myocardial oxygen consumption. Furthermore, STE assists in assessing right ventricular free-wall longitudinal strain (RVFWLS), which is a solid predictor of right ventricle failure (RVF) following LV assist device (LVAD) implantation. However, STE is known for its limitations; despite these, it has been shown to explain symptoms and signs and also to be an accurate prognosticator. The aim of this review is to examine the advantages of STE in the early evaluation of myocardial dysfunction and its correlation with right heart catheterization (RHC) parameters, which should have significant clinical relevance in the management of HF patients. Full article

The interplay between intellectual property rights for new plant varieties and public interests, particularly farmers’ rights, is critically examined within the context of global agricultural practices and Sustainable Development Goals (SDGs). According to the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS), World Trade Organization (WTO) members shall establish a mechanism to grant effective protection to new plant varieties. There are two typical compliance mechanisms with TRIPS: the model developed by the International Convention for the Protection of New Varieties of Plants (UPOV Convention) and India’s sui generis system. A comparison from the sustainable development perspective is conducted through the textual analysis of the regulations of each model. The results show that the UPOV Convention cannot advance the achievement of Sustainable Development Goals and might have adverse effects. Conversely, India’s sui generis system represents a more balanced approach, addressing the needs of the farmers, the community, and environmental protection alongside those of breeders and benefitting sustainable development. The conclusion advocates for revising the UPOV Convention to incorporate broader concerns, including farmers’ rights and environmental sustainability, to ensure a more equitable approach to the protection of plant varieties. Full article

It has long been stated that children have the rights to protection from, e.g., abuse and to the provision of age-appropriate leisure, play, and recreational activities along with participation in all matters that concerns them. Yet, the full range of children’s rights to and in sport has not yet been explored in detail. To do so, it is relevant to turn to the Scandinavian countries, which are praised for promoting children’s rights and well-being, with organized sport forming part of the daily lives of many children and youths. In this paper, we examine the organizational policies in Scandinavian sport in order to develop foundational knowledge about how the range of children’s rights to and in sport may be supported. Comparing key policy documents of the major sports confederations in Denmark, Norway, and Sweden, these analyses identify great variety in the following: 1. when and how children’s rights to and in sport have been made explicit in the three countries; 2. whether the emphasis is on protection and/or provision of sport to children and youths or their participation in shaping sporting activities; 3. the degree to and ways in which such rights are regulated. In sum, our findings reflect a disparity between organizational policies in the three countries, with a more liberal and individualistic approach to public policy in the Danish context, providing some explanation of the only recent development in and scattered enaction of regulations to support children’s rights to and in sports. Furthermore, we identify that political attention has mainly been drawn to the protection and provision of sports to children and youths, while their participation in shaping sport is a shared challenge for sport confederations in the Scandinavian countries and beyond. Full article

Gamma-ray irradiation is one of the most widely used mutagens worldwide. We previously conducted mutation breeding using gamma irradiation to develop new Citrus unshiu varieties. Among these mutants, Gwonje-early had an ovate shape, a protrusion of the upper part of the fruit, and a large fruit size compared with wild-type (WT) fruits. We investigated the external/internal morphological characteristics and fruit sugar/acid content of Gwonje-early. Additionally, we investigated genome-wide single-nucleotide polymorphisms (SNPs) and insertion/deletion (InDel) variants in Gwonje-early using whole-genome re-sequencing. Functional annotation by Gene Ontology analysis confirmed that InDels were more commonly annotated than SNPs. To identify specific molecular markers for Gwonje-early, allele-specific PCR was performed using homozygous SNPs detected via Gwonje-early genome re-sequencing. The GJ-SNP1 and GJ-SNP4 primer sets were effectively able to distinguish Gwonje-early from the WT and other commercial citrus varieties, demonstrating their use as specific molecular markers for Gwonje-early. These findings also have important implications in terms of intellectual property rights and the variety protection of Gwonje-early. Our results may provide insights into the understanding of morphological traits and the molecular breeding mechanisms of citrus species. Full article

Every citizen has the right to be appropriately informed about the foods they consume. Whilst the provision of food information is regulated in the EU, to ensure a high level of health protection for consumers and to guarantee the right to such information, little is known about the accessibility of food information for consumers with a visual impairment. We, therefore, aimed to explore how consumers with such an impairment experience their access to food information by conducting a phenomenological qualitative study. The phenomenon of access to food information was studied via qualitative, semi-structured interviews with 10 Dutch consumers (above 18 years old) who are partially sighted or blind. Through reflexive thematic analysis, themes were constructed from these interviews. Participants highlighted that they did try to derive food information from labels. Often, they used websites, apps, or other assistive technologies in retrieving such information. Respondents highly differed in their information needs. Whilst the accessibility was mostly not considered to be very good, in line with the variation in needs and wants, interviewees also differed in how important they deemed this food information and its accessibility. The interviews highlighted the need to consider personal interests, health status, and the full buying and cooking procedure in analysing food information needs. Our exploratory study shows that consumers with a visual impairment often face difficulties when attempting to derive food information. Having a visual impairment does not only affect buying and cooking behaviour but has also been previously linked to decreased dietary variety. Limited access to food information may play a role in this. Our study highlights that for people with a visual impairment, deriving information from food labels is hard or even impossible, whilst citizens have the right to information to make well-informed decisions regarding their diet. Consumers with a visual impairment are inclined to stick to familiar products and recipes. Considering the global push towards adopting a healthy and more sustainable diet, which includes new products such as alternative protein, it is important to consider the accessibility of food information to the population. Full article

A common consequence of diabetes mellitus called diabetic retinopathy (DR) results in lesions on the retina that impair vision. It can cause blindness if not detected in time. Unfortunately, DR cannot be reversed, and treatment simply keeps eyesight intact. The risk of vision loss can be considerably decreased with early detection and treatment of DR. Ophtalmologists must manually diagnose DR retinal fundus images, which takes time, effort, and is cost-consuming. It is also more prone to error than computer-aided diagnosis methods. Deep learning has recently become one of the methods used most frequently to improve performance in a variety of fields, including medical image analysis and classification. In this paper, we develop a federated learning approach to detect diabetic retinopathy using four distributed institutions in order to build a robust model. Our federated learning approach is based on Vision Transformer architecture to classify DR and Normal cases. Several performance measures were used such as accuracy, area under the curve (AUC), sensitivity and specificity. The results show an improvement of up to 3% in terms of accuracy with the proposed federated learning technique. The technique also resolving crucial issues like data security, data access rights, and data protection. Full article

Wheat is a significant cereal for humans, with diverse varieties. The growth of the wheat industry and the protection of breeding rights can be promoted through the accurate identification of wheat varieties. To recognize wheat seeds quickly and accurately, this paper proposes a convolutional neural network-based image-recognition method for wheat seeds, namely GC_DRNet. The model is based on the ResNet18 network and incorporates the dense network idea by changing its residual module to a dense residual module and introducing a global contextual module, reducing the network model’s parameters and improving the network’s recognition accuracy. Experiments were conducted on the self-constructed wheat-seed dataset and the publicly available dataset CIFAR-100 by combining GC_DRNet with network models such as ResNet18, ResNet34, ResNet50, and DenseNet121. The GC_DRNet model achieved a recognition accuracy of 96.98% on the wheat-seed dataset, which was improved by 2.34%, 1.43%, 2.05%, and 1.77% compared to ResNet18, ResNet34, ResNet50, and DenseNet121, respectively. On the CIFAR-100 dataset, the recognition accuracy of the GC_DRNet model was 80.77%, which improved the accuracy of ResNet18, ResNet34, ResNet50, and DenseNet121 by 8.19%, 1.6%, 9.59%, and 16.29%, respectively. Analyzing the confusion-matrix results of the wheat-seed dataset, the average recognition precision of the test set was 97.02%, the recall rate was 96.99%, and the F1 value was 96.98%. The parameter size of the GC_DRNet model was smaller than that of the other three models, only 11.65MB. The experimental results show that the GC_DRNet has a high level of recognition accuracy and detection capability for images of wheat seeds and provides technical support for wheat-seed identification. Full article

Sesame is a highly valuable crop with significant global importance due to its nutritional and economic value. To better understand the genetic diversity of sesame genotypes at both molecular and morphological levels, a comprehensive study was conducted using 25 pairs of simple sequence repeat (SSR) primers and 56 biological traits in a collection of 183 sesame accessions, which comprised 101 Chinese cultivars, 62 landraces, and 20 exotic accessions. The analysis revealed a total of 166 SSR polymorphic bands, with an average of 6.64 bands per marker. The values of Shannon’s information index ranged from 0.2732 to 0.6497, indicating a moderate level of genetic diversity. The polymorphic information index ranged from 0.0859 to 0.6357, further supporting the presence of genetic variation. The average frequency of heterozygous genotypes was calculated as 0.34, suggesting a relatively narrow genetic diversity. The application of the unweighted pair group method with arithmetic averaging (UPGMA) clustering and principal component analysis allowed for the categorization of the 183 sesame accessions into three distinct groups. Furthermore, the genetic diversity coefficient of sesame germplasm is generally constrained, with no significant difference observed between the genetic diversity coefficient of Chinese cultivars and that of foreign resources. The results provide valuable data for various applications, including the breeding and promotion of new sesame cultivars in China, the protection of new variety rights, the inquiry and identification of DNA genetic information of cultivars, as well as the development and utilization of sesame germplasm resources both domestically and internationally. Full article

The autotetraploid potato (Solanum tuberosum L.) is an important crop in China, and it is widely cultivated from Northeast China to South China. Thousands of varieties are bred by breeding institutions or companies, and distinguishing the different varieties based on morphological characteristics is difficult. Using DNA fingerprints is an efficient method to identify varieties that plays an increasingly important role in germplasm identification and property rights protection. In this study, the genetic diversity and population structure of 135 autotetraploid potatoes were evaluated using specific-locus amplified fragment sequencing (SLAF-seq) methods. A total of 3,397,137 high-quality single-nucleotide polymorphisms (SNPs), which were distributed across 12 chromosomes, were obtained. Principal component analysis (PCA), neighbour-joining genetic trees, and model-based structure analysis showed that these autotetraploid potato subpopulations, classified by their SNPs, were not consistent with their geographical origins. On the basis of the obtained 3,397,137 SNPs, 160 perfect SNPs were selected, and 71 SNPs were successfully converted to penta-primer amplification refractory mutation (PARMS-SNP) markers. Additionally, 190 autotetraploid potato varieties were analysed using these 71 PARMS-SNP markers. The PCA results show that the accessions were not completely classified on the basis of their geographical origins. The SNP DNA fingerprints of the 190 autotetraploid potato varieties were also constructed. The SNP fingerprint results show that both synonyms and homonyms were present amongst the 190 autotetraploid potatoes. Above all, these novel SNP markers can lay a good foundation for the analysis of potato genetic diversity, DUS (distinctness, uniformity, and stability) testing, and plant variety protection. Full article

Coronavirus Disease 2019 (COVID-19) is still a threat to global health and safety, and it is anticipated that deep learning (DL) will be the most effective way of detecting COVID-19 and other chest diseases such as lung cancer (LC), tuberculosis (TB), pneumothorax (PneuTh), and pneumonia (Pneu). However, data sharing across hospitals is hampered by patients’ right to privacy, leading to unexpected results from deep neural network (DNN) models. Federated learning (FL) is a game-changing concept since it allows clients to train models together without sharing their source data with anybody else. Few studies, however, focus on improving the model’s accuracy and stability, whereas most existing FL-based COVID-19 detection techniques aim to maximize secondary objectives such as latency, energy usage, and privacy. In this work, we design a novel model named decision-making-based federated learning network (DMFL_Net) for medical diagnostic image analysis to distinguish COVID-19 from four distinct chest disorders including LC, TB, PneuTh, and Pneu. The DMFL_Net model that has been suggested gathers data from a variety of hospitals, constructs the model using the DenseNet-169, and produces accurate predictions from information that is kept secure and only released to authorized individuals. Extensive experiments were carried out with chest X-rays (CXR), and the performance of the proposed model was compared with two transfer learning (TL) models, i.e., VGG-19 and VGG-16 in terms of accuracy (ACC), precision (PRE), recall (REC), specificity (SPF), and F1-measure. Additionally, the DMFL_Net model is also compared with the default FL configurations. The proposed DMFL_Net + DenseNet-169 model achieves an accuracy of 98.45% and outperforms other approaches in classifying COVID-19 from four chest diseases and successfully protects the privacy of the data among diverse clients. Full article