The Nutrient Data Laboratory is responsible for developing authoritative nutrient databases that contain a wide range of food composition values of the nation's food supply. This requires updating and revising the USDA Nutrient Database for Standard Reference (SR) and developing various special interest databases. However, with over 7,000 food items in SR and a complete nutrient profile costing approximately $2,000 for one sample, analyzing every food item for every nutrient and meeting all user requirements is impossible. Consequently, priorities must be determined. Procedures using food consumption data and nutrient values for developing the Key Foods list are explained. Key Foods have been identified as those food items that contribute up to 75% of any one nutrient to the dietary intake of the US population. These Key Foods will be used to set priorities for nutrient analyses under the National Food and Nutrient Analysis Program. The tables describe key foods based on Continuing Survey Of Food Intakes By Individuals (CSFII, 1989-) and WWEIA-NHANES (What We Eat In America - National Health and Nutrition Examination Survey 2001-) survey data. Resources in this dataset:Resource Title: List of Key Foods based on CSFII 1989-91. File Name: KeyFoods_key_ls91.txtResource Description: Key Foods based on CSFII 1989-91 https://www.ars.usda.gov/ARSUserFiles/80400525/Data/KeyFoods/key_ls91.txtResource Title: List of Key Foods based on CSFII 1994-96 . File Name: KeyFoods_key_ls9496.txtResource Description: List of Key Foods based on CSFII 1994-96 https://www.ars.usda.gov/ARSUserFiles/80400525/Data/KeyFoods/key_ls9496.txtResource Title: List of Key Foods based on WWEIA-NHANES 2001-02. File Name: KeyFoods_key_ls0102.txtResource Description: List of Key Foods based on WWEIA-NHANES 2001-02 https://www.ars.usda.gov/ARSUserFiles/80400525/Data/KeyFoods/key_ls0102.txtResource Title: List of Key Foods based on WWEIA-NHANES 2003-04 . File Name: KeyFoods_key_ls0304.txtResource Description: https://www.ars.usda.gov/ARSUserFiles/80400525/Data/KeyFoods/key_ls0304.txtResource Title: List of Key Foods based on WWEIA-NHANES 2007-08. File Name: Keyfoods_0708.xlsxResource Description: List of Key Foods based on WWEIA-NHANES 2007-08 https://www.ars.usda.gov/ARSUserFiles/80400525/Data/KeyFoods/Keyfoods_0708.xlsxResource Title: List of Key Foods based on WWEIA-NHANES 2009-10. File Name: Keyfoods_0910.xlsxResource Description: List of Key Foods based on WWEIA-NHANES 2009-10 https://www.ars.usda.gov/ARSUserFiles/80400525/Data/KeyFoods/Keyfoods_0910.xlsxResource Title: List of Key Foodsbased on WWEIA-NHANES 2011-12. File Name: Keyfoods_1112.xlsxResource Description: List of Key Foodsbased on WWEIA-NHANES 2011-12 https://www.ars.usda.gov/ARSUserFiles/80400525/Data/KeyFoods/Keyfoods_1112.xlsx

Several USDA food composition databases, including the Food and Nutrient Database for Dietary Studies (FNDDS), Standard Reference (SR) Legacy, and the USDA Branded Food Products Database, have transitioned to FoodData Central, a new and harmonized USDA food and nutrient data system. FoodData Central also includes expanded nutrient content information as well as links to diverse data sources that offer related agricultural, environmental, food, health, dietary supplement, and other information. The new system is designed to strengthen the capacity for rigorous research and policy applications through its search capabilities, downloadable datasets, and detailed documentation. Application developers can incorporate the information into their applications and web sites through the application programming interface (API) REST access. The constantly changing and expanding food supply is a challenge to those who are interested in using food and nutrient data. Including diverse types of data in one data system gives researchers, policymakers, and other audiences a key resource for addressing vital nutrition and health issues. FoodData Central: Includes five distinct types of data containing information on food and nutrient profiles, each with a unique purpose: Foundation Foods; Experimental Foods; Standard Reference; Food and Nutrient Database for Dietary Studies; USDA Global Branded Food Products Database. Provides a broad snapshot in time of the nutrients and other components found in a wide variety of foods and food products. Presents data that come from a variety of sources and are updated as new information becomes available. Includes values that are derived through a variety of analytic and computational approaches, using state-of-the-art methodologies and transparent presentation. FoodData Central is managed by the Agricultural Research Service and hosted by the National Agricultural Library. Resources in this dataset:Resource Title: Website Pointer for FoodData Central. File Name: Web Page, url: https://fdc.nal.usda.gov/index.html Includes Search, Download data, API Guide, Data Type Documentation, and Help pages.

[Note: Integrated as part of FoodData Central, April 2019.] The database consists of several sets of data: food descriptions, nutrients, weights and measures, footnotes, and sources of data. The Nutrient Data file contains mean nutrient values per 100 g of the edible portion of food, along with fields to further describe the mean value. Information is provided on household measures for food items. Weights are given for edible material without refuse. Footnotes are provided for a few items where information about food description, weights and measures, or nutrient values could not be accommodated in existing fields. Data have been compiled from published and unpublished sources. Published data sources include the scientific literature. Unpublished data include those obtained from the food industry, other government agencies, and research conducted under contracts initiated by USDA’s Agricultural Research Service (ARS). Updated data have been published electronically on the USDA Nutrient Data Laboratory (NDL) web site since 1992. Standard Reference (SR) 28 includes composition data for all the food groups and nutrients published in the 21 volumes of "Agriculture Handbook 8" (US Department of Agriculture 1976-92), and its four supplements (US Department of Agriculture 1990-93), which superseded the 1963 edition (Watt and Merrill, 1963). SR28 supersedes all previous releases, including the printed versions, in the event of any differences. Attribution for photos: Photo 1: k7246-9 Copyright free, public _domain photo by Scott Bauer Photo 2: k8234-2 Copyright free, public _domain photo by Scott Bauer Resources in this dataset:Resource Title: READ ME - Documentation and User Guide - Composition of Foods Raw, Processed, Prepared - USDA National Nutrient Database for Standard Reference, Release 28. File Name: sr28_doc.pdfResource Software Recommended: Adobe Acrobat Reader,url: http://www.adobe.com/prodindex/acrobat/readstep.html Resource Title: ASCII (6.0Mb; ISO/IEC 8859-1). File Name: sr28asc.zipResource Description: Delimited file suitable for importing into many programs. The tables are organized in a relational format, and can be used with a relational database management system (RDBMS), which will allow you to form your own queries and generate custom reports.Resource Title: ACCESS (25.2Mb). File Name: sr28db.zipResource Description: This file contains the SR28 data imported into a Microsoft Access (2007 or later) database. It includes relationships between files and a few sample queries and reports.Resource Title: ASCII (Abbreviated; 1.1Mb; ISO/IEC 8859-1). File Name: sr28abbr.zipResource Description: Delimited file suitable for importing into many programs. This file contains data for all food items in SR28, but not all nutrient values--starch, fluoride, betaine, vitamin D2 and D3, added vitamin E, added vitamin B12, alcohol, caffeine, theobromine, phytosterols, individual amino acids, individual fatty acids, or individual sugars are not included. These data are presented per 100 grams, edible portion. Up to two household measures are also provided, allowing the user to calculate the values per household measure, if desired.Resource Title: Excel (Abbreviated; 2.9Mb). File Name: sr28abxl.zipResource Description: For use with Microsoft Excel (2007 or later), but can also be used by many other spreadsheet programs. This file contains data for all food items in SR28, but not all nutrient values--starch, fluoride, betaine, vitamin D2 and D3, added vitamin E, added vitamin B12, alcohol, caffeine, theobromine, phytosterols, individual amino acids, individual fatty acids, or individual sugars are not included. These data are presented per 100 grams, edible portion. Up to two household measures are also provided, allowing the user to calculate the values per household measure, if desired.Resource Software Recommended: Microsoft Excel,url: https://www.microsoft.com/ Resource Title: ASCII (Update Files; 1.1Mb; ISO/IEC 8859-1). File Name: sr28upd.zipResource Description: Update Files - Contains updates for those users who have loaded Release 27 into their own programs and wish to do their own updates. These files contain the updates between SR27 and SR28. Delimited file suitable for import into many programs.

[Note: Integrated as part of FoodData Central, April 2019.] The USDA National Nutrient Database for Standard Reference (SR) is the major source of food composition data in the United States and provides the foundation for most food composition databases in the public and private sectors. This is the last release of the database in its current format. SR-Legacy will continue its preeminent role as a stand-alone food composition resource and will be available in the new modernized system currently under development. SR-Legacy contains data on 7,793 food items and up to 150 food components that were reported in SR28 (2015), with selected corrections and updates. This release supersedes all previous releases. Resources in this dataset:Resource Title: USDA National Nutrient Database for Standard Reference, Legacy Release. File Name: SR-Leg_DB.zipResource Description: Locally stored copy - The USDA National Nutrient Database for Standard Reference as a relational database using AcessResource Title: USDA National Nutrient Database for Standard Reference, Legacy Release. File Name: SR-Leg_ASC.zipResource Description: ASCII files containing the data of the USDA National Nutrient Database for Standard Reference, Legacy Release.Resource Title: USDA National Nutrient Database for Standard Reference, Legacy Release. File Name: SR-Leg_ASC.zipResource Description: Locally stored copy - ASCII files containing the data of the USDA National Nutrient Database for Standard Reference, Legacy Release.

The database contains values for 283 food items for the following proanthocyanidins groups: Dimers Trimers 4-6 mers (tetramers, pentamers and hexamers) 7-10 mers (heptamers, octamers, nonamers and decamers Polymers (DP>10) Resources in this dataset:Resource Title: READ ME - USDA Database for the Proanthocyanidin Content of Selected Foods. File Name: PA02.pdfResource Description: Information regarding the documentation, data sources, data management, data quality evaluation, aggregation and format, sources of data, and references cited.Resource Software Recommended: Adobe Acrobat Reader,url: http://www.adobe.com/prodindex/acrobat/readstep.html Resource Title: Data Dictionary. File Name: PA02_DD.pdfResource Title: PA02.accdb. File Name: PA02.zipResource Description: This file contains the Proanthocyanidin Database imported into a MS Access database version 2007 or later. The file structure is the same as that of the USDA National Nutrient Database for Standard Reference.

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Food Flavors Market Size 2024-2028

The food flavors market size is forecast to increase by USD 6.62 billion at a CAGR of 6.86% between 2023 and 2028.

The market is experiencing significant growth, driven by the premiumization trend in the food and beverage industry. Consumers' increasing preference for high-quality, gourmet, and authentic flavors is propelling market expansion. Technological advances in the food flavor industry, such as the use of natural and artificial flavors, are enabling manufacturers to create innovative and complex taste profiles. Furthermore, the demand for functional food ingredients, particularly in dairy foods, bakery products, and ice cream, is fueling market growth. The integration of fresh herbs and other natural ingredients into food products, driven by the health and wellness trend, is also contributing to market expansion. However, stringent food safety regulations and guidelines pose challenges for market players, necessitating continuous investment in research and development to ensure compliance.

What will be the Size of the Food Flavors Market During the Forecast Period?

Request Free SampleIn the dynamic and evolving world of food and beverage manufacturing, several key areas have emerged as crucial factors shaping market trends. Among these are flavor descriptors, spectroscopy, and profiles, which provide a standardized language for characterizing and understanding the complexities of food flavors. Flavor trademarks, release, and branding play essential roles in differentiating products and creating consumer loyalty. Taste receptors, extraction, and synthesis are at the heart of flavor development, while sensory evaluation, formulation, blending, and analysis ensure product consistency and quality. Flavor patents, modifiers, and enhancers protect intellectual property and extend the shelf life and sensory appeal of food products. Chromatography, synergists, masking, stabilization, notes, perception, communication, interaction, retention, and aroma compounds are all integral components of the flavor value chain. Flavor databases facilitate research and innovation, enabling companies to stay competitive and meet the evolving demands of consumers.

How is this Food Flavors Industry segmented and which is the largest segment?

The food flavors industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments. ProductNatural flavorsSynthetic flavorsOrganic flavorsApplicationBeveragesDairyConfectioneryEnd-useFood ProcessingFoodserviceHouseholdGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKMiddle East and AfricaEgyptKSAOmanUAEAPACChinaIndiaJapanSouth AmericaArgentinaBrazilRest of World (ROW)Rest of World (ROW)

By Product Insights

The natural flavors segment is estimated to witness significant growth during the forecast period.Natural flavors, derived from various sources including herbs, spices, fruits, vegetables, dairy products, edible yeast, meat, and eggs, have gained significant traction in the global food industry. With increasing health consciousness among consumers and growing awareness about the potential health risks associated with artificial flavors, the demand for natural and organic flavors has surged. Europe, North America, and South America are leading regions driving this trend, with countries like Germany, France, the US, Canada, and Brazil witnessing notable growth. Natural flavors not only retain the original flavor and aroma of natural ingredients but also offer an appealing scent to various food products. The confectionery, bakery, dairy, and beverage industries are major consumers of natural flavors. Flavor innovation, customization, and sustainability are key focus areas for companies in this sector. Flavor development and delivery systems, flavor profiles, and flavor safety are critical aspects of flavor technology. Organic, non-GMO, clean label, vegan, and kosher flavors are popular choices for consumers seeking healthier and ethically sourced options. Flavor regulations and research play a crucial role in ensuring the authenticity and stability of natural flavors. The meat industry and savory food sector also utilize natural flavors to enhance the taste and aroma of their products. Flavor extracts, concentrates, and compounds are essential components of flavor systems, while flavor masking and authentication techniques are used to maintain consistency and quality. Fruit, sweet, vanilla, chocolate, and herbal flavors are among the most commonly used in food processing. Flavor trends indicate a shift towards plant-based and sustainable flavors, with a growing interest in exotic and ethnic flavors.

Get a glance at the market report of share of various segments Request Free Sample

The Natural flavors seg

While art is omnipresent in human history, the neural mechanisms of how we perceive, value and differentiate art has only begun to be explored. Functional magnetic resonance imaging (fMRI) studies suggested that art acts as secondary reward, involving brain activity in the ventral striatum and prefrontal cortices similar to primary rewards such as food. However, potential similarities or unique characteristics of art-related neuroscience (or neuroesthetics) remain elusive, also because of a lack of adequate experimental tools: the available collections of art stimuli often lack standard image definitions and normative ratings. Therefore, we here provide a large set of well-characterized, novel art images for use as visual stimuli in psychological and neuroimaging research. The stimuli were created using a deep learning algorithm that applied different styles of popular paintings (based on artists such as Klimt or Hundertwasser) on ordinary animal, plant and object images which were drawn from established visual stimuli databases. The novel stimuli represent mundane items with artistic properties with proposed reduced dimensionality and complexity compared to paintings. In total, 2,332 novel stimuli are available open access as “art.pics” database at https://osf.io/BTWNQ/ with standard image characteristics that are comparable to other common visual stimuli material in terms of size, variable color distribution, complexity, intensity and valence, measured by image software analysis and by ratings derived from a human experimental validation study [n = 1,296 (684f), age 30.2 ± 8.8 y.o.]. The experimental validation study further showed that the art.pics elicit a broad and significantly different variation in subjective value ratings (i.e., liking and wanting) as well as in recognizability, arousal and valence across different art styles and categories. Researchers are encouraged to study the perception, processing and valuation of art images based on the art.pics database which also enables real reward remuneration of the rated stimuli (as art prints) and a direct comparison to other rewards from e.g., food or money.Key Messages: We provide an open access, validated and large set of novel stimuli (n = 2,332) of standardized art images including normative rating data to be used for experimental research. Reward remuneration in experimental settings can be easily implemented for the art.pics by e.g., handing out the stimuli to the participants (as print on premium paper or in a digital format), as done in the presented validation task. Experimental validation showed that the art.pics’ images elicit a broad and significantly different variation in subjective value ratings (i.e., liking, wanting) across different art styles and categories, while size, color and complexity characteristics remained comparable to other visual stimuli databases.

The global food and beverage filler market is a dynamic sector experiencing robust growth, driven by increasing demand for packaged food and beverages, particularly in developing economies. The market size in 2025 is estimated at $3165.4 million. While the exact CAGR isn't provided, considering the growth drivers (automation in filling lines, rising consumer preference for convenience food, and expansion of the food and beverage industry globally), a conservative estimate of the CAGR for the forecast period (2025-2033) would be between 5% and 7%. This growth is fueled by several factors. The increasing adoption of automated filling systems improves efficiency and reduces operational costs for food and beverage manufacturers. Furthermore, a shift towards convenient, ready-to-consume products boosts demand for efficient and high-speed filling solutions. The expanding global population, coupled with rising disposable incomes in emerging markets, contributes significantly to market expansion. Segmentation analysis reveals that plastic bottles currently dominate the market due to their cost-effectiveness and versatility, followed by glass bottles, which maintain strong appeal for premium products. The food application segment likely holds the largest share currently, given the higher volume of packaged food compared to beverages. Key players in the market, including GEA Group, Tetra Laval, and Krones, are continuously innovating and expanding their product portfolios to meet the evolving needs of the industry. Despite the positive outlook, the market faces certain challenges. Fluctuations in raw material prices, particularly for plastics, can impact production costs and profitability. Furthermore, stringent regulations concerning food safety and packaging waste management necessitate continuous investments in compliance and sustainable solutions. Nevertheless, the long-term outlook for the food and beverage filler market remains optimistic, with continued innovation in filling technology and packaging materials expected to drive sustained growth over the next decade. The market is poised to benefit from the rising focus on sustainability, with the emergence of eco-friendly packaging options and enhanced recycling infrastructure potentially reshaping the market landscape. Regional growth is expected to vary, with Asia-Pacific anticipated to witness substantial growth due to rapid industrialization and economic expansion. This in-depth report provides a comprehensive analysis of the global food and beverage filler market, projecting a market value exceeding $15 billion by 2030. It delves into key market segments, competitive dynamics, and future growth trajectories, offering valuable insights for industry stakeholders, investors, and strategic decision-makers. The report leverages extensive primary and secondary research, incorporating data from industry leaders, market research databases, and expert interviews. Key search terms covered include: food filler machines, beverage filling equipment, packaging machinery, automatic filling systems, liquid filling machines, bottle fillers, food processing equipment, and packaging automation.

This database contains values for six choline metabolites: Betaine, Glycerophosphocholine, Phosphocholine, Phosphatidylcholine, Sphingomyelin, and Total choline This database was created through a collaborative effort between the USDA and the Department of Nutrition, University of North Carolina. Resources in this dataset:Resource Title: READ ME - Documentation: USDA Database for the Choline Content of Common Foods . File Name: Choln02.pdfResource Description: Contains information about documentation, methods and procedures, data evaluation, format, and dissemination information. Also contains references and general information about choline compounds. Resource Title: Choline Content Release 2. File Name: Choln02.zipResource Description: .zip file with Food and Nutrient database tables for Choline from phosphocholine, Choline from phosphatidylcholine, Choline from glycerophoshocholine, Betaine, and Choline from sphingomyelin.

The United States Department of Agriculture (USDA) Nutrient Data Laboratory (NDL), in collaboration with the National Cattlemen's Beef Association, National Pork Board, American Lamb Board, and meat scientists at selected universities, has conducted several research studies designed to update and expand nutrient data on retail meat cuts in the USDA National Nutrient Database for Standard Reference (SR). These studies have provided current and accurate estimates of data to update SR, and the study results have been incorporated into data sets that can be used for nutrient labeling. NDL has developed these data sets, presented in an easy-to-use table format.
Each data set provides retailers with easier access to the most accurate nutrient data for the purpose of on-pack nutrition labeling and for nutrition claims. These data sets focus on the cuts identified by USDA Food Safety and Inspection Service (FSIS) proposed labeling regulations for fresh, single-ingredient meats. The FSIS, an agency of the USDA, is the public health agency responsible for ensuring that the nation's commercial supply of meat, poultry and egg products is safe, wholesome, and correctly labeled and packaged. Resources in this dataset:Resource Title: The USDA Nutrient Data Set for Retail Beef Cuts, Release 3.0. File Name: Retail_Beef_Cuts03.pdfResource Description: Each data set provides retailers with easier access to the most accurate nutrient data for the purpose of on-pack nutrition labeling and for nutrition claims. These data sets focus on the cuts identified by USDA Food Safety and Inspection Service (FSIS) proposed labeling regulations for fresh, single-ingredient meats. The online version of this document can be found at https://www.ars.usda.gov/ARSUserFiles/80400525/Data/Meat/Retail_Beef_Cuts03.pdfResource Title: The USDA Nutrient Data Set for Retail Beef Cuts, Release 3.0 (MS Excel download). File Name: Beef_Labelling_Table03.xlsxResource Description: The tables in "The USDA Nutrient Data Set for Retail Beef Cuts" imported into a Microsoft Excel spreadsheet. The online version of this spreadsheet can be found at https://www.ars.usda.gov/ARSUserFiles/80400525/Data/Meat/Beef_Labelling_Table03.xlsxResource Title: USDA Nutrient Data Set for Retail Pork Cuts, Release 2. File Name: Pork09.pdfResource Description: Each data set provides retailers with easier access to the most accurate nutrient data for the purpose of on-pack nutrition labeling and for nutrition claims. These data sets focus on the cuts identified by USDA Food Safety and Inspection Service (FSIS) proposed labeling regulations for fresh, single-ingredient meats. Find the online version of this document at https://www.ars.usda.gov/ARSUserFiles/80400525/Data/Meat/Pork09.pdfResource Title: USDA Nutrient Data Set for Retail Pork Cuts, Release 2 (MS Excel download). File Name: Pork09_Tbl.xlsResource Description: The tables in "The Revised USDA Nutrient Data Set for Fresh Pork" imported into a Microsoft Excel spreadsheet. Find the online version of this spreadsheet at https://www.ars.usda.gov/ARSUserFiles/80400525/Data/Meat/Pork09_Tbl.xlsResource Title: Raw Ground Pork (MS Excel download). File Name: EstNutrRawGrndPork4_28.xlsResource Description: These tables provide nutrient profiles for raw ground pork from 4-28% fat, in increments of 1% fat, as determined by regression equations. Find the online version of this spreadsheet at https://www.ars.usda.gov/ARSUserFiles/80400525/Data/Meat/EstNutrRawGrndPork4_28.xlsResource Title: USDA Nutrient Data Set for Retail Veal Cuts. File Name: Retail_Veal_Cuts.pdfResource Description: Each data set provides retailers with easier access to the most accurate nutrient data for the purpose of on-pack nutrition labeling and for nutrition claims. These data sets focus on the cuts identified by USDA Food Safety and Inspection Service (FSIS) proposed labeling regulations for fresh, single-ingredient meats. Find the online version of this document at https://www.ars.usda.gov/ARSUserFiles/80400525/Data/Meat/Retail_Veal_Cuts.pdfResource Title: Veal Labeling Table (MS Excel download). File Name: Veal_Labeling_Table.xlsxResource Description: The tables in "The USDA Nutrient Data Set for Retail Veal Cuts" imported into a Microsoft Excel spreadsheet. Find the online version of this spreadsheet at https://www.ars.usda.gov/ARSUserFiles/80400525/Data/Meat/Veal_Labeling_Table.xlsxResource Title: USDA Nutrient Data Set for Retail Lamb Cuts. File Name: Lamb_Labeling_Doc.pdfResource Description: Each data set provides retailers with easier access to the most accurate nutrient data for the purpose of on-pack nutrition labeling and for nutrition claims. These data sets focus on the cuts identified by USDA Food Safety and Inspection Service (FSIS) proposed labeling regulations for fresh, single-ingredient meats. Find the online version of this document at https://www.ars.usda.gov/ARSUserFiles/80400525/Data/Meat/Lamb_Labeling_Doc.pdfResource Title: Lamb Labeling Table (MS Excel download). File Name: Lamb_Labeling_Table.xlsxResource Description: The tables in "The USDA Nutrient Data Set for Retail Lamb Cuts" imported into a Microsoft Excel spreadsheet. Find the online version of this spreadsheet at https://www.ars.usda.gov/ARSUserFiles/80400525/Data/Meat/Lamb_Labeling_Table.xlsx

Search string for bibliographic databases (four components will be combined with the Boolean operator AND before combination with the Boolean operator ‘NOT’ for the fifth component).

NUOnet Vision: Efficient use of nutrients to optimize production and product quality of food for animals and humans, fuel and fiber in a sustainable manner that contributes to ecosystem services. This record contains the DET and Data Dictionary for NUOnet - the data files may be found at https://usdaars.maps.arcgis.com/apps/MapSeries/index.html?appid=e90392a99d5c427487c6c37cf6d47844 Best nutrient management practices are critical for maintaining profitable economic returns, sustaining higher yields, lowering environmental impacts, optimizing nutritional quality, and providing ecosystem services. Best management practices that improve nutrient use efficiencies can reduce nutrient losses from agricultural systems. However, we need to improve our understanding of biological, physical and chemical influences on nutrient processes. For instance, crop use efficiency of nitrogen (N), the primary macronutrient regulating yield and protein content, can be reduced by processes such as denitrification (N2O and N2 emission), leaching (NH4-N, NO3-N, and organic-N), ammonia (NH3-N,) volatilization, surface runoff and erosion, disease, and non-crop competition. Similarly, we need to obtain more information about biological and physical cycles of nutrients, especially phosphorus (P), including factors that influence nutrient availability from fertilizers, crop residues, cover crops, manures, and other byproducts. We need a better understanding of relationships between soil biological communities and ecosystems, including plant roots and root exudates, and availability and uptake of macro- and micro-nutrients. In addition, we need information regarding how these practices impact yields, organoleptic qualities, and the macro- and micro-nutritional composition of plants. This information will improve our ability to develop best nutrient management practices. Optimal soil nutrient levels are critical for maximizing economic returns, increasing sustainable yields, lowering environmental impacts, sustaining ecosystem services and optimizing nutritional and organoleptic qualities of human and animal foods. Efficient management practices are crucial for increasing economic returns for land managers in a sustainable manner while producing high quality of food for animals and humans with reduced off-site transfer of nutrients from agricultural areas in watersheds. Optimizing N and P inputs requires more information about nutrient inputs from fertilizers, manures, composts, agricultural byproducts, cover crops, and other nutrient sources in addition to nutrient cycling within soils. This requires data from long-term nutrient management studies across a wide range of soils, crops, and environmental conditions. Land management needs are to connect nutrient management practices for crops with nutrient use efficiency; crop quality; crop chemical composition and nutritional value, quality and acceptability for animal and human health. Development of databases that enable the scientific exploration of connections among data generated from diverse research efforts such as nutrient management, fate and ecosystem service outcomes, nutritional composition of crops, and animal and human health, is needed. Nitrogen is a key nutrient that enhances agricultural yield and protein content, but multiple N loss pathways, as previously mentioned, reduce crop N use efficiency (NUE). Implementing proper management practices is needed to reduce N losses from agricultural systems. ARS has multidisciplinary scientific teams with expertise in soils, ecological engineering, hydrology, livestock management and nutrition, horticulture, crop breeding, human and animal nutrition, post-harvest management and processing, and other areas, and intentional collaboration among these teams offers opportunities to rapidly improve NUE and crop quality and reduce off-site N losses. Similarly, increased P use efficiencies are needed to enhance and ensure sustainable agricultural production and to reduce environmental degradation of water sources. Manure is a valuable source of P and it can be used as a soil amendment to reduce crop production costs. However, there is a need to improve our understanding of the biological and physical cycles of soil P, as well as to obtain more information about P supplies from fertilizer, crop residues, cover crops, manure, and byproducts, and livestock nutrition impacts on manure properties. There is also a need for a better understanding of soil biological communities and ecosystems, including plant roots and root exudates and how their interactions with crops and community ecology affect yield and the uptake of macro- and micro-nutrients and the ultimate nutritional composition and organoleptic qualities of the crop. Studies documenting the responses of crop-associated biological communities to management practices and genetic technologies implemented across multiple environments (e.g., soil types and chemistries, hydrologic regimes, climates) will improve our understanding of gaps in macro- and micro-nutrient management strategies. A goal of the USDA-ARS is to increase agricultural production and quality while reducing environmental impacts. The Nutrient Uptake and Outcomes (NUOnet) database will be able to help establish baselines on nutrient use efficiencies; processes contributing to nutrient losses; and processes contributing to optimal crop yield, nutritional and organoleptic quality. This national database could be used to calculate many different environmental indicators from a comprehensive understanding of nutrient stocks and flows. Increasing our understanding of stocks and flows could help in the identification of knowledge gaps as well as areas where increased efficiencies can be achieved at a national level. NUOnet could also be used to develop tools to derive cost-benefit curves associated with nutrient management improvement scenarios and assess local, regional and national impacts of off-site nutrient loss. Understanding how agricultural production impacts human health is a challenge, and the database could be used to link crop management strategies to crop chemical composition to human consumption patterns and ultimately to human health outcomes. A national database will also be very important for development and evaluation of new technologies such as real-time sensing or other proximal and remote sensing technologies that enable assessment of nutrient use efficiencies, particularly at the grower level. The database could also be used to develop analyses that will contribute to the recommendation of policies for resource allocations that will most effectively fulfill the goals of the Grand Challenge. Such a national database with contributions from peers across different national programs could also enhance collaborations between ARS, universities, and extension specialists, as well as with producers, industry, and other partners. See the NUOnet Home Page for more information about this database and strategic goals. Resources in this dataset:Resource Title: GRACEnet-NUOnet Data Dictionary. File Name: GRACEnet-NUOnet_DD.csvResource Title: NUOnet Data Entry Template. File Name: DET_NATRES_NUO.zipResource Description: A multi-tab worksheet for data entry. Users can customize fields to be mandatory, set minimum and maximum values, and run a validation on fields as specified by the user. https://gpsr.ars.usda.gov/html/NUOnet_DET/DET_NATRES_NUO.xlsm

In support of nutrition research, concentrations of compounds from different parts of the watermelon plant are provided. The parts of the plant for which data are tabulated include (red) flesh, heart tissue, juice, seed, rind, peel, yellow flesh, seedling, leaf, root, other parts of the plant, and detected but plant part undeclared. The collected data include the low value in the range, the high value in the range, deviation from those values, and units (assumed to be fresh or wet weight unless noted). This table also provides for all compounds the citations to the literature and database sources. The “AFC” identifier represents the Agricultural Research Service (ARS) Food Compound; PubChem refers to the identifier from this resource of chemical compounds. Resources in this dataset:Resource Title: Catalog of natural products occurring in watermelon. File Name: Watermelon_NP_catalog_20210623.tsvResource Description: This is a table of chemical compounds found in watermelonResource Title: Data dictionary. File Name: Data_dictionary_Watermelon_compounds_NAL_20210623.xlsxResource Description: This is the data dictionaryResource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/access