dataesr/scientific-paragraphs-categorization huggingface dataset:
Nowadays, these processes can be easily automated by using a b A basic food product, in this case an apple, can be a simple anatomical part, in this case a pome fruit, deriving from a particular plant species (Malus domestica) of a specific variety (Fuji). Reprinted with permission from ref. [26, 27]. 2017. Roger A Smith (cc-by-sa/2. 0). Whole food databases are described below and summarised in Table  1. The inclusion criteria were 'freely accessible online', in 'English', and 'providing extensive datasets as well as corresponding metadata on food composition', while exclusion criteria were 'not in English' and/or 'absence of online access and/or information not easily accessible' and/or 'pay-per-use/subscription service' and/or 'not updated regularly'.
Main Whole Food Composition Databases As referred above, the main food composition databases have been enriched with more and more information about food constituents and linkages to different databases. For example, FDBs discriminating nutrients and components of a given food, from fresh product to packed branded foodstuffs (e. g. , EuroFIR), are linked to a second type of FDB, which is based on inspecting a wide range of foods for a given nutrient or a certain molecular family of compounds (as is the case of Phenol Explorer). A third type of specific FDB is the object of growing interest-that is, the case of HMDB (see below) exploring the interaction of food components, at the level of gut microbiota, and of metabolites, toxins, and specific compounds (biomarkers) at the cellular, organelle, or pathway level  [31] [32] [33] [34].
Food Data Central The United States Department of Agriculture (USDA) manages and maintains Food-Data Central [15], a platform providing access to distinct types of data on nutrients and other food components, including Foundation Foods, National Nutrient Database for Standard Reference (SR Legacy), Food and Nutrient Database for Dietary Studies (FNDDS 2017-2018), and Experimental Foods. The DB platform is noteworthy for providing different types of searches (by component or by food), which may encompass a combination of databases. Metadata are provided, including the number of samples, sampling location, date of collection, analytical approaches used, and if appropriate, agricultural information (e. g. , genotype and production practices-intensive, organic, etc. ). In respect to Experimental Foods, it is noteworthy that they are meant for research purposes and described foods may not be available in the market.
The corresponding database includes data from multiple sources to allow users to examine a range of factors that may affect the nutritional profiles of foods and resulting dietary intakes, as well as the sustainability of agricultural and dietary food systems. This FDB is available at https://agcros-usdaars. opendata. arcgis. com accessed on 17 August 2021, and the user is able to explore data (referring to US) by topic or by location, for example [15].
CIQUAL-French Food Composition Table CIQUAL is an open access French FDB [16], covering a wide range of the most consumed foodstuffs in France. This reference database on the nutritional composition of foods is maintained by the Agency for Food, Environmental and Occupational Health and Safety (known by the acronym ANSES). This FDB was updated in 2020 and provides the levels of macro (lipids, fatty acids, carbohydrates) and micronutrients (vitamins, minerals, etc. ) of more than 3185 foods and 67 components. The main axes targeted by CIQUAL are the input and management of a reference database relating to the composition of foods, the contribution to the assessment of nutritional risks, and the communication and dissemination of validated data to the greatest number of users (encompassing researchers, nutritionists, food manufacturers, and consumers).
EuroFIR, European Food Information Resource EuroFIR, European Food Information Resource [14], is an independent food composition resource in Europe bringing together food composition datasets from 26 European Countries, Canada, the US, New Zealand, and Japan. It is currently a non-profit international organization that resulted from a network project, Network of Excellence (NoE) comprising of 48 partners from academia, research organizations, and small-and mediumsized enterprises (SMEs). EuroFIR is a food composition table or database providing detailed information on the nutritional composition of foods, typically energy, macronutrients (e. g. , protein, carbohydrate, fat) and their components (e. g. , sugars, starch, fatty acids), minerals (e. g. , calcium, iron, sodium), and vitamins  [14].
One of its tools, Food Explorer, is an interface that allows to simultaneously search information about food composition data from most of the available databases from the EU, Canada, USA, New Zealand, and Japan. Food Explorer allows searches by food names or by nutritional groups with the unique ability to allow comparisons of attributes' values of foods from different countries. Another relevant tool in this FDB is Bioactive Substances in Food Information Systems (eBASIS), which is a compilation of food composition and their biological effects. Such data are extracted from peer-reviewed literature as raw data and critically evaluated, thus relying on the curation work of experts.
FoodDB The Canadian database, FoodDB Version 1. 0, 2021, is licensed under a Creative Commons Attribution-Non-Commercial 4. 0 International License, and it is supported by the Canadian Institutes of Health Research, Canada Foundation for Innovation, and by The Metabolomics Innovation Centre (TMIC)  [35]. This FDB supplies extensive data on food constituents, chemistry, and biology, providing information on both macronutrients and micronutrients, including many of the constituents that give foods their flavour, colour, taste, texture, and aroma with detailed compositional, biochemical, and physiological information (obtained from the literature). Searches can be made by food source, name, function, or concentrations, and the FDB content can be accessed from the Food Browse (listing foods by their chemical composition) or from the Compound Browse (listing chemicals by their food sources), according to the user's preferences.
Frida Food Data The database Frida Food Data (frida. fooddata. dk), also known as DTU foods  [17] , is managed by the National Food Institute with the Technical University of Denmark (DTU) allowing public access to information about foods available in Denmark. The FDB also relies on the cooperation of stakeholders as food industries and retailers, as well as scholars and the Danish Veterinary and Food Administration. Metadata (as the number of samples and their source) are included in registries encompassing more than 1000 food items. The information above is summarised in Table  1  presenting some features of the most utilized food composition databases, for whole foods, easily and freely accessible online, in English. The FDBs listed in Table  1  follow international standards and are interconnected thus providing access to reliable, comprehensive information on foods serving most common purposes.
National Whole Food Composition Databases National FDBs, where they exist, vary widely in the extent of provided information, standardisation at various levels (see Figure  1 ; Figure  2 ), and the ease of access (including the language). Thus, starting by the British food composition table, obviously in English, in the United Kingdom, Public Health England (PHE) is responsible for maintaining food composition data relating to nutrients (macronutrients, e. g. , fats, protein, carbohydrates as well as their micronutrient content, which includes vitamins and minerals) mostly from analysing foods commonly consumed in the country. The results are published as McCance and Widdowson's 'The Composition of Foods'-the UK food composition tables. The Composition of Foods Integrated Dataset (CoFIDS) is a nutrient dataset for 2898 foods and 303 others in the 'old foods' file, comprising 185 individual nutrients.
CoFIDS is searchable online and can be downloaded free of charge in MS Excel or Ascii format, and it was first published in 2008 (https://fdnc. quadram. ac. uk/ accessed on 17 August 2021), available online at the date of this publication. PortFIR is the Portuguese national food composition database for the most consumed foods in Portugal. The data cover about 42 nutrients ex. energy, macronutrients, fatty acids, vitamins, and minerals (http://portfir. insa. pt/ accessed on 17 August 2021), available online at the date of this publication. The information is classified into groups and subgroups according to the FoodEx2 classification and description system (http://www. efsa. europa. eu/en/datex/datexfoodclass accessed on 17 August 2021), available online at the date of this publication from the EFSA.
The PortFIR FDB is free online, displayed in English, and allows searches as well as downloading in Excel format  [36]. Similarly, the Turkish food composition database, an open access digital platform, 'Türkomp' (http://www. turkomp. gov. tr/main accessed on 17 August 2021), available online at the date of this publication provides a considerable dataset and information related to the nutrients, composition, and energy values of processed or unprocessed agricultural products that are produced and consumed in Turkey. Türkomp exhibits 63,000 data entries on the nutritional and energy value of 100 food components belonging to 580 foods from 14 food groups  [37]. As referred above, it is rare to find suitable food composition tables of reliable and updated contents from developing countries, and to illustrate such situations, a few examples are herein presented.
The updated version provides information on foods and dishes commonly consumed in Morocco and can be used as a tool to promote nutritional research and to design public health strategies. Another common situation with national databases of developing countries can be illustrated by the Tunisian food composition table, which displays the 240 foods and dishes usually consumed by Tunisians. The table corresponds to 95% of the food needs of the entire Tunisian population. It includes, for each food, the energy value as well as the content in 34 nutrients, expressed per 100 g of the raw edible part. This table is presented in the form of a book produced by a group of nutritionists from the National Institute of Nutrition and Food Technology (INNTA) who were supported by French and Belgian experts within the framework of the European project 'Impact of transitions epidemiological studies on health in North African countries'  [41].
Another common situation corresponds to the composition table of foods from the Republic of Bahrain, which is a printed book not so regularly updated and hardly available. This database brings together 150 raw and readyto-eat foods and composite dishes according to standardized methods. This list includes cereals and grain products, bread and bread products, fruits, vegetables, legumes, nuts and seeds, meat, poultry and eggs, fish, milk and dairy products, fats and oils, herbs and spices, beverages, local and western fast foods, etc. The table provides data for proximate composition, three minerals (calcium, phosphorus, and iron), and five vitamins (retinol, thiamine, riboflavin, niacin and vitamin C) expressed per 100 g of edible portion  [42]. Similarly, the Chinese food composition database is given by a printed book, not necessarily in English  [43].
As the reader can easily deduce, the randomness of updates, the limited access, and the absence of English versions can be strong limitations to the use of national FDBs in disclosing specific food habits and/or the composition of particular food items. In addition to free access institutional databases, a growing number of commercial customized applications have been appearing in the market. Such apps or so-called food databases mainly encompass different types of software to assist food formulation and labelling, dietary features, and recipe analysis, as well as fitness apps. The access is reserved and includes consultancy support services. An example of a privately owned FDB, with an associated API, is offered by Edamam, a company that provides access to a food and grocery database with close to 900,000 basic foods, restaurant items, and consumer packaged foods available on the website, at the date of this publication, https://developer.
edamam. com/food-database-api (accessed on 17 August 2021). The Food API provides a filter to sort data by diet and health, determining dietary, allergy, and nutrition labelling, based on the food's ingredients. Over 70+ claims are automatically generated such as peanut free, shellfish free, gluten free, vegan, and vegetarian. Edamam also provide data for basic foods (as flour and eggs) for calories, fats, carbohydrates, protein, cholesterol, sodium, etc. , for a total of 28 nutrients. The food we ingest is expected to interact at the level of the gut microbiota, and thus, considering the scenario of metabolic pathways and the benefits of bioactive compounds in humans, Durazzo et al. [44]  noted the database Human Metabolome Database (HMDB) version 4. 0, also originating from Canada, and supported by the same organizations as FoodDB vs.
1. This database, HMDB, contains detailed information about small molecule metabolites found in the human body aiming to be an input for studies in metabolomics, clinical chemistry, biomarker discovery, etc. This database encompasses data of different kinds: chemical, clinical, and molecular biology/biochemistry data, notably more than 100,000 metabolite entries (water-soluble and non-polar metabolites) either abundant (>1 µM) or rare (<1 nM), which are linked to almost 6000 protein sequences. Even if this database does not directly reflect food composition, it is of undoubted interest in nutritional studies to assess how a food or a diet might influence metabolism, either in a positive or unhealthy way. The HMDB supports text, sequence, chemical structure, and relational query searches, and it is linked to other databases whether on drugs, toxins, pollutants, or on nutrients and food additives  [31] [32] [33] [34].
At https://hmdb. ca accessed on 17 August 2021, available online at the date of this publication it is possible to browse metabolites, pathways, etc. , as well as performing advanced searches based on molecular mass, chemical structure, or text queries. Another freely accessible data resource of the same kind is MGnify, an EMBL-EBI online resource containing Human Gastrointestinal Protein catalogue and a dataset on the Human Gastrointestinal Genome, allowing researchers to compare their findings on microbial genomics and proteomics with existing datasets. MGnify has been growing, and promoters would like to close knowledge gaps, such as the variation in bacterial diversity across different human populations  [45]. The Sydney University Glycaemic Index Research Service (SUGiRS) produced a free database that gives the glycaemic index of any food inserted on their search engine available on their website https://www.
FDBs Concerning Food Processing In order to process safe food, several hours of research are needed when searching for the precise thermal processing parameters; D-value and z-value parameters that describe the characteristics of thermal death of food target microorganisms, for the ingredients or final food products, are not always easily found. The Lemgo D-and z-value Database for food, a project of the Institute for Food Technology NRW (ILT. NRW) at the OWL University of Applied Sciences and Arts, supplies information on these parameters, to design pasteurization or sterilization processes with a main focus on beverage spoiling microorganisms. Additional information is given on parameters known to have an effect on the D-and z-values like pH, Brix and a w value. The data are sorted by the species of microorganism and their medium, and on the experiments from which these data originated or a cluster of relevant data  [47].
Another very important database for food engineers is the Database of Physical Properties of Food is available online, at the date of the current publication http://www. nelfood. com, (accessed on 17 August 2021); nelfood. com grew out of the Physical Properties of Food Data Base project that started to collect and publish on the internet reliable and useful data on Physical Properties of Foods. This project was managed by Dr Paul Nesvadba with internet work done by NEL, and it was partly funded by the EU and partly sponsored by companies such as Nestle, RHM, and Unilever. It is only available to subscribed members that may search 11,094 bibliographic references, 1519 materials, and 1694 experiment datasets. These datasets range over 24 food categories encompassing 249 food subcategories and 260 physical properties.
FDBs Concerning Environmental Impact of Foods Generally speaking, current food systems are operating out of planetary boundaries, with agriculture being a top driver for biodiversity loss, using water above the natural capacity of replenishment, causing soil degradation, pollution, and more  [49, 50]. The urge of the food systems' transformation is such that, among many initiatives, the UN organised a food system summit in 2021 (https://www. un. org/en/food-systems-summit accessed on 17 August 2021), available online at the data of this publication and the European Union issued a climate law that binds the EU Institutions and the Member States to take the necessary measures to reach carbon neutrality by 2050. On the other hand, a growing awareness from consumers about the impact of their individual food choices in their health and the environment has been registered  [51].
Shifts in food habits may fuel the desired changes, but the commitment of food producers is key. Business pledges need to be underpinned in well-established targets and robust metrics fed with comprehensive information on the food-environment nexus. Despite the still existing gaps, efforts in compiling information are many, and advancements of FDBs in integrating data on the environmental footprint of foods are to be expected. In respect to the 2030 agenda, the Sustainable Development Report, by Sachs et al. , [52] provides interactive dashboards with visual representation of performances by SDGs to identify priorities for action. One of such priorities is tackling food loss and waste for which the FAO maintains a database in connection to tools to track progress, available online at the date of this publication, http://www.
fao. org/platform-food-loss-waste/ flw-data/en/ (accessed on 17 August 2021). The food loss and waste database contains data and information from various sources, measuring food loss and waste across food products, stages of the value chain, and geographical areas, also presenting underlying causes, according to the literature  [53]. Only a few FDBs present datasets on the environmental footprint of foods or are useful for its assessment. One of them is 'Experimental Foods' from USDA (see Section 4. 1) that contains information on environmental inputs and outputs on the supply chains, etc. ; however, it is not necessarily publicly available  [15]. A dataset on food environmental impacts through producers and consumers was published by Poore and Nemecek in 2018  [54]. The ADEME (the French Agency for Ecological Transition) recently launched Agribalyse, a food database providing an environmental score (Ecoscore) for 2500 food products based on their life cycle analysis (LCA).
Main Limitations of Food Databases: Missing Dimensions for Human Health? First, beyond only nutrients, foods are interlinked with cultural identity while playing a key role in many local economies, as highlighted by Dembska et al. [18]  in their double pyramids models connecting food culture, health, and climate. These authors and others  [18, [57] [58] [59] [60] [61]  call attention to the need of leveraging the various dimensions of foods, which are closely related, under the so-called one-health approach  [18, 57]. If FDBs are specifically useful for balancing a diet for nutrient composition and fully addressing nutritional needs in human studies, they, however, reflect a reductionist view of foods, viewed as only the sum of nutrients  [61] , not considering the food matrix effect, and hence, the degree of processing  [22].
Therefore, to be a relevant tool regarding human health in the long term, their data should not be used alone, but other parameters should be also considered, such as food form and degree of processing, together with other important food properties. For example, the newly developed Siga score  [59]  is hierarchically combined with the first degree of processing, then the food matrix effect, added salt, fat, and/or sugar, and the number of markers of ultra-processing (including some cosmetic additives and non-additive markers)  [60]. To be elaborated, this score typically needs not only the food composition data, but also the list of ingredients and the presence or not of added sugar, salt, and/or fat. Such a hierarchical and holistic score should be more considered, because, in the end, it is related to global (environmental and human) health  [18, 57, 60, 61] ; whereas, food composition only is insufficient to address diets from the global or one-health perspective as needed (e.
Some Important Bioactive Compounds and Food Properties Are Still Missing Another limitation is often observed worldwide and consists of missing values for some important key nutrients, e. g. , lipotropic compounds (such as choline, betaine, and myo-inositol) and phytic acid, but also for other characteristics of nutrients or foods, such as soluble and insoluble fibre (with different physiological effects), resistant starch, and glycaemic index  [65]. It is true that some FDBs report choline content such as the USDA Database for the Choline Content of Common Foods, Release 2 (2008)  [66] , or the phytic acid content such as the FAO/INFOODS/IZiNCG, Global Food Composition Database for Phytate (2018)  [67] , or the glycaemic index  [68] , but this should be completed and extrapolated to other FDBs more broadly in the future, e.
Considering industrially processed foods that are becoming dominant in our diets, in the future, FDBs should also distinguish between 'natural' and 'added' nutrients whatever they are and indicate the list of additives, as with the Open Food Facts database available online for industrial foods  [77]  or private pay-per-use food databases that also gives the list of ingredients, e. g. , Alkemics and Num-Alim. More specifically, the Open Food Facts database is a collaborative database of food products and is licenced under the Open Database Licence (ODBL). For such foods, the list of ingredients tells us more about their whole nutritional quality (including environmental aspects) than the only composition. Indeed, it should be underlined that no food is nutritionally balanced (except maternal milk for the growth of the infant), hence the recommendation to 'eat varied' at the level of the diet.
Emerging Applications and Trends of Food Databases In view of the ongoing changes in food systems, needs for curated and organized information on the composition of food secondary raw-materials, novel foods, and/or sources for nutrients (as insects and microalgae) are expected to be met by FDBs. These challenges may exacerbate existing issues with food data composition. Thus, in addition to the intrinsic features of foods, parameters related to the extraction and analytical procedures should be considered, according to Durazzo et al. ,  [44] , as different extraction procedures and analytical techniques and methodologies may lead to different datasets. Moreover, still according to these authors, only a few compounds within a class are investigated, and there are knowledge gaps on appropriate analytical methods for food analysis.