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164 results for “food product”
NutriGreen Image Dataset: A Collection of Annotated Nutrition, Organic, and Vegan Food Products
<p>The generated dataset is an annotated collection, with each image carrying labels (NutriScore, V-label and Bio). The presence of annotated data is essential for developing a supervised machine-learning model capable of automatically identifying labels in new images. In our case, we utilize this data to train a model that can autonomously recognize labels on new images not present in the dataset, achieving a model accuracy of 94%. In the future, you have the option to train a new model using the dataset to achieve higher accuracy or employ the existing model to automatically identify bio and nutri labels in newly collected images, eliminating the need for manual review. We should emphasize that these resources should be utilized by a data science team. There is an opportunity for this model to be integrated with a mobile app, but this is a direction for future work, we included in the revised version.</p> <p>In this research, we introduce the NutriGreen dataset, which is a collection of images representing packaged food products. Each image in the dataset comes with three distinct labels: one indicating its nutritional value using the Nutri-Score, another denoting whether it's vegan or vegetarian with the V-label, and a third displaying the EU organic certification (BIO) logo. The dataset comprises a total of 10,472 images. Among these, the Nutri-Score label is distributed across five sub-labels: A with 1,250 images, B with 1,107 images, C with 867 images, D with 1,001 images, and E with 967 images. Additionally, there are 870 images featuring the V-Label, 2,328 images showcasing the BIO label, and 3201 images with no labels. Furthermore, we have fine-tuned the YOLOv5 model to demonstrate the practicality of using these annotated datasets, achieving an impressive accuracy of 94.0%. These promising results indicate that this dataset has significant potential for training innovative systems capable of detecting food labels. Moreover, it can serve as a valuable benchmark dataset for emerging computer vision systems.</p> <p> </p> <p> </p>
Data from: Changes in Invertebrate Food Web Structure Between High- and Low-productivity Environments are Driven by Intermediate but Not Top Predator Diet Shifts
Open the record for dataset details and reuse information.
Data from: Effect of yeast addition on the biogas production performance of a food waste anaerobic digestion system
<p>Food waste contains numerous easily degradable components, and anaerobic digestion is prone to acidification and instability. This work aimed to investigate the effect of adding yeast on biogas production performance, when substrate is added after biogas production is reduced. The results showed that the daily biogas production increased 520 ml and 550 ml by adding 2.0% (VS) of activated yeast on the 12th and 37th day of anaerobic digestion, respectively, and the gas production was relatively stable. In the control group without yeast, the increase of gas production was significantly reduced. After the second addition of substrate and yeast, biogas production only increased 60 ml compared with that before the addition. After fermentation, the biogas production of yeast group also increased by 33.2% compared with the control group. Results of the analysis of indicators, such as volatile organic acids, alkalinity, and propionic acid, showed that the stability of the anaerobic digestion system of the yeast group was higher. Thus, the yeast group is highly likely to recover normal gas production when the biogas production is reduced, and substrate is added. The results provide a reference for experiments on the industrialisation of continuous anaerobic digestion to take tolerable measures when the organic load of the feed fluctuates dramatically.</p>
Implementation of ATP and Microbial Indicator Testing for Hygiene Monitoring in a Tofu Production Facility Improves Product Quality and Hygienic Conditions of Food Contact Surfaces: A Case Study
<p>This is the code and associated data that was used to generate conclusions for the following manuscript published in Applied and Environmental Microbiology:</p> <p>DOI: 10.1128/AEM.02278-20</p> <p>Implementation of ATP and Microbial Indicator Testing for Hygiene Monitoring in a Tofu Production Facility Improves Product Quality and Hygienic Conditions of Food Contact Surfaces: A Case Study</p> <p>Authors: Jonathan H. Sogin(a), Gabriela Lopez Velasco(b), Burcu Yordem(b), Cari K. Lingle(b), John M. David(b), Mario Cobo(a), Randy W. Worobo(a)</p> <p>(a)Department of Food Science, Cornell University, Ithaca, NY, USA</p> <p>(b)3M Company, St. Paul, MN, USA</p> <p>Address correspondence to Jonathan H. Sogin, jhs397@cornell.edu</p>
Data from: Food webs obscure the strength of plant diversity effects on primary productivity
Plant diversity experiments generally find that increased diversity causes increased productivity; however, primary productivity is typically measured in the presence of a diverse food web, including pathogens, mutualists and herbivores. If food web impacts on productivity vary with plant diversity, as predicted by both theoretical and empirical studies, estimates of the effect of plant diversity on productivity may be biased. We experimentally removed arthropods, foliar fungi and soil fungi from the longest-running plant diversity experiment. We found that fungi and arthropods removed a constant, large proportion of biomass leading to a greater reduction of total biomass in high diversity plots. As a result, the effect of diversity on measured plant productivity was much higher in the absence of fungi and arthropods. Thus, diversity increases productivity more than reported in previous studies that did not control for the effects of heterotrophic consumption.
eDNA metabarcoding of avocado flowers: 'Hass' it got potential to survey arthropods in food production systems?
<p>In the face of global biodiversity declines, surveys of beneficial and antagonistic arthropod diversity as well as the ecological services that they provide are increasingly important in both natural and agro-ecosystems. Conventional survey methods used to monitor these communities often require extensive taxonomic expertise and are time-intensive, potentially limiting their application in industries such as agriculture, where arthropods often play a critical role in productivity (e.g. pollinators, pests and predators). Environmental DNA (eDNA) metabarcoding of a novel substrate, crop flowers, may offer an accurate and high throughput alternative to aid in the detection managed and unmanaged arthropod taxa (e.g. flower-visiting insects and potential pollinators). Here, we compared the arthropod communities detected with eDNA metabarcoding of flowers, from an agricultural species (<em>Persea americana </em>- 'Hass' avocado), with two conventional survey techniques; Digital Video Recording (DVR) devices and pan traps. In total, 80 eDNA flower samples, 96 hours of DVRs and 48 pan trap samples were collected. Across the three methods, 49 arthropod families were identified, of which 12 were unique to the eDNA dataset. Alpha diversity levels did not differ across the three survey methods although taxonomic composition varied significantly, with only 12% of arthropod families found to be common across all three methods. This study demonstrates that eDNA metabarcoding of flowers to detect visiting arthropods, although in a developmental stage, can complement traditional survey methods and increase the diversity of taxa detected with implications for both natural and agro-ecosystems.</p>
Questionnaire on COVID pandemic influence at attitude and prevalence of plant-based food products consumption in Serbia
<p>An anonymous online questionnaire that contained 16 open-ended and closed-ended questions was used to assess the influence of the COVID-19 pandemic on 1) eating behavior and dietary habits changes concerning various plant-based foods; 2) frequency of consumption of herbal teas and dietary supplements; 3) quantity of traditionally pickled plant-based food prepared for the winter period, and 4) the general attitude toward diet, plant-based food, natural products, and dietary supplements.</p> <p> </p>
Effects of enhanced productivity of resources shared by predators in a food-web module: Comparing results of a field experiment to predictions of mathematical models of intra-guild predation
<p>This dataset contains data from a field experiment described in the publication "Wise, D. H. & Farfan, M.A. (2021) Effects of enhanced productivity of resources shared by predators in a food-web module: Comparing results of a field experiment to predictions of mathematical models of intra-guild predation. Ecology and Evolution, 00: 1-11. <a href="https://doi.org/10.1002/ece3.8375">https://doi.org/10.1002/ece3.8375</a>".</p> <p>The field experiment compared the response to increased input of nutrients and energy (artificial detritus) to an empirical model of intra-guild predation (IGP) to the predictions of published, simple mathematical models of asymmetric IGP (a generalist IG Predator that feeds both on a specialist IG Prey and a Resource that it shares with the IG Prey). The empirical model was a food-web module created by pooling species abundances across many families in a community of soil micro-arthropods into three response variables: IG Predator (large predatory mites), IG Prey (small predatory mites) and a shared Resource (fungivorous mites and springtails). The pattern of change over time in densities of the three response variables (IG Predator, IG Prey and Resource) was compared to the predictions of mathematical models of IGP to determine if the feeding relationships in this community of soil micro-arthropods could be abstracted into a simple IGP module. Thus, we were testing the hypothesis that IGP is a dominant organizing principle in this community.</p> <p>Simple mathematical models predict that increased input of nutrients and energy to the shared Resource will increase the equilibrium density of Resource and IG Predator, but will decrease that of IG Prey. By the experiment's end, densities of fungivores (Resource) had increased ~1.5x (ratio of pooled fungivore densities in the High treatment to plots with no addition of detritus (None treatment); and IG Predator densities had increased ~4x. Contrary to the prediction of mathematical models, IG Prey had not decreased, but instead had increased ~1.5x. We discuss possible reasons for the failure of the empirical model to agree with IGP theory.</p>
Data from: Terrigenous subsidies in lakes support zooplankton production mainly via a green food chain and not the brown food chain
<p><span>Terrestrial organic matter (t-OM) has been recognized as an important cross-boundary subsidy to aquatic ecosystems. However, recent evidence has shown that t-OM contributes little to promote secondary production in lakes because it is low quality food for aquatic consumers. To resolve this conflict, we performed a field experiment using leaf litter as t-OM. In the experiment, we monitored zooplankton biomass in enclosures with and without addition of leaf litter under shaded and unshaded conditions and assessed food web changes with stable isotope analyses. We then examined whether or not leaf litter indeed stimulates lake secondary production and, if it does, which food chain, the detritus-originated food chain ("brown" food chain) or the algae-originated food chain ("green" food chain), contributes more to this increase. Analyses with stable isotopes showed a substantial importance of t-OM in supporting the secondary production under ambient lake conditions. However, addition of the leaf litter increased the zooplankton biomass under unshaded conditions but not under shaded conditions. We found that phosphorus was leached from leaf litter at much faster rate than organic carbon and nitrogen despite its low content in the leaf litter. These results showed that leaf litter stimulated the increase of zooplankton biomass mainly through the green food chain rather than through the brown food chain, because the leaf litter supplied limiting nutrients (i.e., phosphorus) for primary producers. Our results indicate that the functional stoichiometry of the subsidized organic matter plays a crucial role in determining the relative importance of brown and green food chains in promoting production at higher trophic levels in recipient ecosystems.</span></p>
Investigating food production-associated DNA methylation changes in paleogenomes: lack of consistent signals beyond technical noise
<p>The Neolithic transition introduced major diet and lifestyle changes to human populations across continents. Beyond well-documented bioarchaeological and genetic effects, whether these changes also had molecular-level epigenetic repercussions in past human populations has been an open question. In fact, methylation signatures can be inferred from UDG-treated ancient DNA through postmortem damage patterns, but with low signal-to-noise ratios; it is thus unclear whether published paleogenomes would provide the necessary resolution to discover systematic effects of lifestyle and diet shifts. To address this we compiled UDG-treated shotgun genomes of 13 pre-Neolithic hunter-gatherer (HGs) and 21 Neolithic farmer (NFs) individuals from West and North Eurasia, published by six different laboratories and with coverage c.1x-58x (median=9x). We used epiPALEOMIX and a Monte Carlo normalization scheme to estimate methylation levels per genome. Our paleomethylome dataset showed expected genome-wide methylation patterns such as CpG island hypomethylation. However, analysing the data using various approaches did not yield any systematic signals for subsistence type, genetic sex, or tissue effects. Comparing the HG-NF methylation differences in our dataset with methylation differences between hunter-gatherers vs. farmers in modern-day Central Africa also did not yield consistent results. Meanwhile, paleomethylome profiles did cluster strongly by their laboratories of origin. Using larger data volumes, minimizing technical noise and/or using alternative protocols may be necessary for capturing subtle environment-related biological signals from paleomethylomes.</p>
Historical Pollen Records from `The Productivity-Stability Trade-off in Global Food Systems'
<p>Historical pollen records from Europe used to detect evidence of agricultural development on plant pollen dynamics. </p>
Digital technologies for improving productivity in food manufacturing - graphical capture
<p>The Centre for SMART at Loughborough University collaborated with the Internet of Food Things Network Plus to host an event that targeted players in the food manufacturing industry, as well as policy makers, and aimed to provide attendees with the opportunity to learn from companies and technology providers on best practices to successfully implement current digital technologies in food manufacturing and to discuss policy and regulatory challenges to the uptake of such technologies within the UK Food Sector.</p> <p>A full report will be available later, but this drawing was produced by Becky James from Natalka Design who was commissioned to capture the complexity of the presentations and discussions that took place at the event.</p> <p>We therefore acknowledge the contribution that all attendees at the event made to this illustration.</p>
Supplementary data: Food product categories compared against National Act 26905 maximum sodium levels (n 864).
<p>Supplementary data: Food product categories compared against National Act 26905 maximum sodium levels (n 864). Article: Monitoring sodium content in processed foods in Argentina 2017-2018: compliance with national legislation and regional targets. (submitted for publication to Nutrients).</p>
Graphical capture from: Digital technologies for improving productivity in food manufacturing
<p>The Centre for SMART at Loughborough University collaborated with the Internet of Food Things Network Plus to host an event that targeted players in the food manufacturing industry, as well as policy makers, and aimed to provide attendees with the opportunity to learn from companies and technology providers on best practices to successfully implement current digital technologies in food manufacturing and to discuss policy and regulatory challenges to the uptake of such technologies within the UK Food Sector.</p> <p>A full report will be available later, but this drawing was produced by Becky James from Natalka Design who was commissioned to capture the complexity of the presentations and discussions that took place at the event.</p> <p>We therefore acknowledge the contribution that all attendees at the event made to this illustration.</p>
Bioprospecting for bioactive peptide production by lactic acid bacteria isolated from fermented dairy food
<p>Table S1 of the review article "Bioprospecting for bioactive peptide production by lactic acid bacteria isolated from fermented dairy food"</p> <p>by Davide Tagliazucchi, Serena Martini and Lisa Solieri</p>
Collecting data on Hungarian traditional/local pulse varieties, on legume production, consumption and trade of food-purpose pulses in Hungary
<p>Summary data on traditional and local Hungarian pulse varieties will be provided. This will include a systematic summary of all legume species and varieties used for food and feed that are stored in the seed bank data of the National Plant Diversity Centre, Hungary.</p> <p>Statistical data mined from the database of the Hungarian Central Statistical Office (CSO) on the production of the most significant food and feed legumes in Hungary, the household consumption of the some food-used pulses, as well as the food industry processing and the national trade of pulses.</p> <p>Mining and summarizing existing data from different resources will be performed during 2017 and will be provided by February 2018. Statistical data on production, consumption and traded will be supplemented during the project with the updates of CSO databases. Methodologies used will be desk research and primer analysis.</p>
Processing of Legume Products to new Foods
<p>The aim of the work is to develop and produce new foods from various legume processing products. Knowledge of the raw material properties (like water absorption, acidity and aggregation properties) of legume products is very important for product development. It was tried to find connections between raw material parameters and quality of the developed products.<br> Therefore, different technologies were used. The first orienting tests showed that extrusion is the most suitable technology for product development. Due to the dominance of the protein components, experiments were carried out during development in which the pH value was shifted to the alkaline range. Roasting was also tested. A flour was produced from roasted peas, but it did not have good processing properties.<br> These products should have good chances for marketing with regard to their properties. Therefore, properties should be achieved which represent unique selling points for these products. Essential characteristics are that these products are vegetarian or vegan, free of gluten, GMO and allergens. A further goal is a high protein content of the food, which offers the possibility to market these products as meat analogues. Since 2017, the work has been carried out in the pilot plants of IGV GmbH. The first products have been prototyped with pea products (green peas, yellow peas) and lentils. Flours of peeled peas, pea protein concentrates and pea protein isolates have been processed into directly expanded or gelatinised products by means of various types of extrusion, in particular by twin screw extrusion. Expanded products are produced by hot extrusion. They can be used as ready to eat snacks or form the basis for further developments. Gelatinated extrudates are extruded using a gentle process and are semi-finished products, that can be further processed by flocculation or deep-frying. <br> A product family based on pea protein is currently completed. These basic products can be used in various applications. The work will be continued with other legume products (Fava beans, Lentils).</p>
Dataset for the paper: Integrated spatial planning for biodiversity conservation and food production
<p>This dataset includes the input and output files associated with the article </p> <p>Fastré, C.<sup> </sup>, van Zeist, W-J., Watson, J.E.M.<span> </span>and Visconti, P. (2021) Integrated spatial planning for biodiversity conservation and food production", One-Earth.</p> <p>Instructions and code to reproduce the results are at https://github.com/pierovisconti/integratedSP</p>
Raw data of microbiological and physicochemical characteristics of artisanal food products
<p>Raw data of the microbiological and physicochemical characteristics of the artisanal food products under investigation, which were sampled from survey studies in anonymised regional producers. The data are part of the results produced in Work package 2; and have been used to construct the monitoring quality charts of deliverable D7.3.</p>
Aborption and Metabolism of Lyophilized Black Raspberry Food Products in Men With Prostate Cancer Undergoing Surgery
ClinicalTrials.gov study NCT01823562. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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DANDI Archive for NWB datasets
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.