sugars | Ag Data Commons

Data from: Honeydew associated with four common crop aphid species increases longevity of the parasitoid wasp, Bracon cephi (Hymenoptera: Braconidae)

Abstract from published manuscript: The absence of sugar resources can be an important factor in limiting the success of parasitoids as biological control agents. Restoring vegetation complexity within agricultural landscapes has thus become a major focus of conservation biological control efforts, with a traditional emphasis on nectar resources. Aphid honeydew is also an important source of sugars that is infrequently considered. We carried out a laboratory experiment to examine the potential effects of honeydew from six different aphid species by crop species combinations on the longevity of Bracon cephi Gahan (Hymenoptera: Braconidae), the most important biological control of the wheat stem sawfly, Cephus cinctus Norton (Hymenoptera: Cephidae), a major pest of wheat in the northern Great Plains of North America. The benefits of honeydew for parasitoid longevity varied significantly among different aphid and crop species, illustrating the complexity of these interactions. However, honeydew produced by four aphid species commonly found in wheat, pea, and canola crops significantly increased the longevity (by two- to threefold) of the parasitoid. The study suggests that honeydew provisioning could be an important mechanism underlying the benefits of crop diversification to support biological control that merits further research.

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Data from: Characterization of Levilactobacillus brevis genotypes and phenotypes from industrial cucumber fermentation identifies the presence of 1,2-propanediol metabolosomes in the species

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Data from: Pre-inoculation water deficit effects on grapevine physiology, Xylella fastidiosa titers and Pierce's disease progression

Data are from three experimental trials examining pre-existing water stress on Xylella fastidiosa infections and possible associated shifts in host chemistry, including free sugar, amino acid, and phenolic compound measurements.

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Data from: Amino acid, sugar, phenolic, and terpenoid profiles are capable of distinguishing Citrus tristeza virus infection status in grapefruit, lemon, mandarin, and sweet orange leaves

Amino acid, sugar, phenolic, and terpenoid compound level data collected from different citrus species that were healthy or infected with different CTV strains, with CTV titer and symptoms provided.

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Feedstock Readiness Level (FSRL) evaluation: Saccharum officinarum (sugarcane), SIP and Alcohol-to-Jet, Hawaii, June 2018

Feedstock readiness level evaluations are performed for a specific feedstock-conversion process combination and for a particular region. FSRL evaluations complement evaluations of Fuel Readiness Level (FRL) and environmental progress. The data from this evaluation, compiled in June 2018, assesses the maturity of *Saccharum officinarum* (sugarcane), as a feedstock for the the Hydroprocessed Fermented Sugars to Synthetic Isoparaffins (HFS-SIP) and/or Alcohol-to-Jet conversion process in the United States Hawaii region.

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Sodium Monitoring Dataset

The Agricultural Research Service of the US Department of Agriculture (USDA) in collaboration with other government agencies has a program to track changes in the sodium content of commercially processed and restaurant foods. Results of these monitoring activities are shared once a year in the [Sodium Monitoring Dataset](https://www.ars.usda.gov/ARSUserFiles/80400525/Sodium/Copy%20of%20SodiumMonitoringDatasetUpdatedJuly2616.xlsx) and [USDA National Nutrient Database for Standard Reference](https://www.ars.usda.gov/Services/docs.htm?docid=8964) and once every two years in the [Food and Nutrient Database for Dietary Studies](https://www.ars.usda.gov/Services/docs.htm?docid=12068).

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Data from: Secretome data from Trichoderma reesei and Aspergillus niger cultivated in submerged and sequential fermentation methods

The cultivation procedure and the fungal strain applied for enzyme production may influence levels and profile of the proteins produced. The proteomic analysis data presented here provide critical information to compare proteins secreted by Trichoderma reesei and Aspergillus niger when cultivated through submerged and sequential fermentation processes, using steam-explosion sugarcane bagasse as inducer for enzyme production.

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Food Intakes Converted to Retail Commodities Databases (FICRCD)

Food Intakes Converted to Retail Commodities Databases (FICRCD) provide data for foods consumed in the United States national dietary intake surveys at the retail commodity level. The survey foods are converted into 65 retail-level commodities. The commodities are grouped into eight major categories: Dairy Products; Fats and Oils; Fruits; Grains; Meat, Poultry, Fish and Eggs; Nuts; Caloric Sweeteners; and Vegetables, Dry Beans and Legumes.

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Food Patterns Equivalents Database (FPED)

USDA’s Food Patterns Equivalents Database (FPED) converts the foods and beverages in the Food and Nutrient Database for Dietary Studies to the 37 USDA Food Patterns components. The FPED serves as a unique research tool to evaluate food and beverage intakes of Americans with respect to the 2015-2020 Dietary Guidelines for Americans recommendations.

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USDA National Nutrient Database for Standard Reference Dataset for What We Eat In America, NHANES (Survey-SR)

The dataset, Survey-SR, provides the nutrient data for assessing dietary intakes from the national survey What We Eat In America, National Health and Nutrition Examination Survey (WWEIA, NHANES). Historically, USDA databases have been used for national nutrition monitoring (1). Currently, the Food and Nutrient Database for Dietary Studies (FNDDS) (2), is used by Food Surveys Research Group, ARS, to process dietary intake data from WWEIA, NHANES. Nutrient values for FNDDS are based on Survey-SR. Survey-SR was referred to as the "Primary Data Set" in older publications. Early versions of the dataset were composed mainly of commodity-type items such as wheat flour, sugar, milk, etc. However, with increased consumption of commercial processed and restaurant foods and changes in how national nutrition monitoring data are used (1), many commercial processed and restaurant items have been added to Survey-SR.