Location: Methods and Application of Food Composition Laboratory
2024 Annual Report
Objectives
Objective 1. Utilize comprehensive, non-targeted methods for classifying foods and for identifying candidate compounds that can then be quantified by specific targeted methods to determine the variance of nutritionally important food components in the western diet. (NP 107, Problem Statement 2A).
Objective 2. Apply comprehensive non-targeted methods to identify, and apply specific targeted methods to quantify, nutritionally important compounds in food crops that may be impacted by genetics, environment, management, and processing (GxExMxP). (NP 107, Problem Statement 1A and NP 216, Component 5)
Objective 3. In collaboration with other laboratories, utilize metabolite fingerprinting, metabolomics, and lipidomics to: A) characterize the impact of genetics, environment (including geographical location) and management on the nutritional characteristics of dry beans and soybeans; and B) evaluate the impact of bovine diet and environment on the nutritional composition (with emphasis on lipids) of milk and dairy products. (NP 107, Problem Statement 1A and 2A and NP 216, Component 5)
Objective 4. Demonstrate that comprehensive non-targeted analysis of individual samples from selected national studies prior to compositing is a critical compliment to targeted data in the new USDA Food Composition Database. (NP 107, Problem Statement 2A)
Approach
New analytical technology will be adapted to the analysis of foods to help nutritionist, health practitioners, and the public to understand the link between agricultural systems, nutrition, and health. The food supply is changing rapidly with new genotypes from the farm and new processed foods in the marketplace. Every food consists of thousands of compounds, each with the potential to impact human health. Each must be identified, quantified, and added to a database. For a database to keep pace with the new foods, high throughput must be combined with even more detailed, comprehensive analyses. Rapid screening methods, based on metabolite fingerprinting, will allow classification of foods and determination of the relative variance associated with food production factors. Selected samples from each class will be subjected to metabolomic and lipidomic analysis. These methods will produce libraries of compounds that will allow metabolite fingerprinting methods to be used for rapid identification and quantification and will fill out nutrient databases. The combination of fingerprinting, metabolomic, and lipidomic methods will be used to analyze commodities and processed foods and to evaluate the nutritional qualities of crops and food products as a function of genetics, environment, management, and processing. This data is critical to establishing relationships between agricultural systems, nutrition, and Health. Ultimately, this data will be combined into a single database available to researchers and the public.
Progress Report
Objective 1:
The Methods and Application of Food Composition Laboratory (MAFCL) developed and refined non-targeted methods for classification of foods based on their secondary metabolite composition, those numerous non-essential compounds that have potential health significance, and applied these methods to numerous nutritional problems. MAFCL perfected methods using ultra-high performance liquid chromatography-high-resolution mass spectrometry (UHPLC- HRMS) for the characterization of complex plant components. MAFCL was invited to publish a review on the use of mass spectrometry for non-targeted and targeted analysis in the fields of food and agriculture for the Journal of Agricultural and Food Chemistry.
MAFCL developed a method for the identification and classification of steroidal saponins, one class of the tens of thousands of secondary metabolites found in plant foods that constitute the black matter of nutrition. They are large, complex molecules consisting of more than 30 carbons and are ubiquitous in the plant kingdom, but are difficult to detect.
MAFCL developed a metabolite-ratio rule-based method for accurate identification of four major cinnamon species that allows for evaluation of individual health impacts. A method was developed for rapid authentication of curcuminoids. This method allows the detection of adulterated products, a common problem due to the increased commercial demand for turmeric because of its purported health-promoting activities.
MAFCL collaborated with numerous other labs in ARS, applying non-targeted mass spectrometry (MS) methods to agricultural problems. In collaboration with Diet, Genomics and Immunology Laboratory (DGIL), a method was developed to detect phenolics and glucosinolates in the urine of human volunteers fed kale and Daikon radishes. The combination of non-targeted and targeted analyses can provide insight into human metabolism and urine is an excellent non-invasive indicator of food consumption for human dietary intervention studies.
Objective 2:
MAFCL collaborated with numerous outside labs, identified below, to examine the impact of genetics, environment, management, and processing (GxExMxP) on the secondary metabolite composition of foods and foods. MAFCL furnished the analytical and chemometric expertise of non-targeted and targeted methods to analyze samples furnished by outside labs that were grown under a wide variety of experimental conditions.
MAFCL collaborated with the Adaptive Cropping Systems laboratory, USDA-ARS to examine the impact of elevated CO2 levels on the nutritional composition of wheat. This study examined the metabolite profiles for nutrients and other small molecules of two genetic lines of wheat grown under ambient and free-air CO2 enrichment (FACE) conditions. Fifty compounds (amino acids, sugars, phenolic acids, flavonoids, and lipids) were found to vary with the CO2 level, with variation in the sugars, lipids, and amino acids having the greatest impact. These data demonstrated that genetics and environment (elevated CO2) impacted the whole wheat biochemistry, not just proteins and minerals.
In collaboration with the Agricultural Water Efficiency and Salinity ResearchLaboratory USDA-ARS, non-targeted methods were used to examine the impact of salinity on two genotypes of spinach grown in a greenhouse. Significant differences in the concentration of polyphenols, phenolic acids, and soluble sugars were identified increasing our understanding of the differences in metabolism for crops grown using recycled and saline waters as sustainable alternatives to freshwater.
In collaboration with the Food Quality laboratory, USDA-ARS, non-targeted methods were used to examine the compoisitonal differences between kale and broccoli microgreens grown in growth chambers and windowsills. The study revealed clear variations in the secondary metabolites between plants and growing conditions demonstrating that environmental factors have a significant impact on the plant secondary metabolites composition affecting their health-enhancing potential.
USDA-ARS in collaboration with the University of District of Columbia, examined the impact of urban farming modes (field, green roof, and high tunnel grown) on secondary phytochemicals in leaves of seven accessions of Hibiscus. Phenolic compounds were higher in green roof samples and total amino acids and sugars were higher in field samples.
In collaboration with the Food Quality laboratory, USDA-ARS investgated the effect of light emitting diode LED light wavelengths on the secondary metabolites (phenolics, anthocyanins, and glucosinolates) of mustard “Ruby Streak” microgreens. The results suggested a significant and complex impact of lighting on phytochemical accumulation in microgreens and the potential of modulating plant nutritional profiles by varying wavelengths of the light source.
MAFCL collaborated with ARS and academic labs to obtain funding from USDA under the Pulse Crop Health Initiative. Dry bean samples from North Dakota and Washington State were analyzed by near infrared and mass spectrometry. Results showed that beans could e differentiated based on genotype and growing location. Gluten-free pastas from individual beans and bean composite flours were distinguishable from pastas from Durum wheat.
MAFCL collaborated with ARS and academic labs to develop a model that showed that as temperatures during the growing season increase, the production of the essential fatty acid, alpha-linoleic acid, decreases in soybean and canola oil. This reduction will result in dietary insufficiency for a wide-ranging population of Americans.
MAFCL collaborated with an academic lab to demonstrate that using non-targeted MS analysis the secondary metabolites of wild American ginseng were different from its cultivated counterpart and profiles for both ginsengs changed systematically with age. This strategy is beneficial for the quality evaluation of America ginseng and quality control by manufacturers.
Objective 3:
MAFCL developed a multi-dimensional liquid chromatography-mass spectrometry (LC-MS) method for the analysis of Infant formula and milk containing fat-soluble vitamins and highly complex and difficult to analyze fats (triacylglycerols) with short-chain and medium/long-chain fatty acids. This approach provides a new tool and opens new avenues for investigation using multi-dimensional chromatography
MAFCL improved the analysis of fatty acid methyl esters (FAMEs) by combining gas chromatography-flame ionization detection (GC-FID) with MS confirmation. Statistical treatment of the GC-FID FAME data showed the same grouping pattern by principal component analysis of the triacylglycerol composition by LC-MS but using a simpler analysis. The modified method will simplify and speed up fatty acid analysis.
MAFCL successfully applied an analytical method developed for lipids and lipid-soluble vitamins in milk products to the analysis of lipids in pulses thus filling a knowledge gap for pulses. A long, detailed method for analysis and a fast, high-throughput method for analysis were developed. Both methods allow quantification of triacylglycerol regioisomers and fat-soluble vitamins.
Objective 4:
MAFCL examined the the similarities of plant foods using principal component analysis (PCA) and the macro- and micro-nutrients listed for the raw commodities in USDA’s Database for Standard Reference. PCA provided a tool for categorizing raw plant foods with similar nutrients to guide the acquisition of balanced nutrients from diverse plant sources. This is the first report of a nutrient-based food categorization system. Importantly, this process can be used to guide the development of other food categorization systems for nutrient diversification.
Accomplishments
1. Influence of growing temperature on lipid content of soybean oil. Increasing high temperatures may be impacting the nutritional quality of food. Based on plant physiology, USDA-ARS scientists at the Beltsville Human Nutrition Research Center in Beltsville, Maryland, hypothesized that increasing temperatures would reduce the essential fatty acid content in soybean oil. Through extensive literature review, a model was developed that predicts the magnitude of changes expected in the food supply and verifies the negative impact of increasing temperatures on fatty acid content.
2. Influence of growing temperature on lipid content of canola oil. Influence of growing temperature on lipid content of canola oil. USDA-ARS scientists at the Beltsville Human Nutrition Research Center in Beltsville, Maryland, previously developed a model showing the loss of essential fatty acid content in the oils we eat but data to validate this model were lacking in the United States. USDA-ARS scientists initiated an international collaboration with the Canadian Grains Commission to obtain fatty acid composition data for Canadian canola oil across the major producing regions in Canada, which represents a major contribution to the global supply of this staple ingredient. It was demonstrated that the essential fatty acid content of canola oil has decreased over the last decade to a level where people may not be consuming enough essential fatty acids in their diet. When this change is mapped against local, contemporaneous weather data, the major contributor to this change is increasing daytime high temperatures during growth.
3. Development of a one-class method for authentication of foods. Development of a one-class method for authentication of foods. Identifying authentic foods for reasons of nutrition or to establish provenance is an important process. This is usually done by comparing the composition of a test sample to a series of authentic reference samples. USDA-ARS scientists at the Beltsville Human Nutrition Research Center in Beltsville, Maryland, has developed a simple mathematical approach to build a model based only the characteristics of the reference samples (one class of samples) and avoids the necessity of identifying adulterated samples. The one-class method can be used with any analytical method and provides a statistical yes/no answer to the question of authenticity. This model will replace the more complex models currently being used for authentication.
4. Differences between authentic botanical samples. identification of a plant or herbal material is usually accomplished by comparing a test material to a series of reference material. Unfortunately, the reference materials, even of the same species, do not always agree. USDA-ARS scientists at the Beltsville Human Nutrition Research Center in Beltsville, Maryland, demonstrated that processing of the analytical data can influence the agreement of the reference materials and assist in discriminating from other species. These results provide insight into physical and mathematical approaches for improved identification of plant materials.
5. Impact of genetics and environment on cranberry fruit metabolites. Climate change is dramatically influencing the yield and nutritional composition of crops. A systematic method is needed to evaluate the influence of cultivars and growing location on the composition of fruits and vegetables. USDA-ARS scientists at the Beltsville Human Nutrition Research Center in Beltsville, Maryland, collected 15 cultivars of cranberries from 16 growing locations in 4 states and a Canadian province. The combination of analysis by mass spectrometry and sophisticated chemometric analysis allowed each chemical component (sugars, acids, flavonoids) to be quantified with respect to cultivar and location. This method can serve as a model for evaluating the impact of genetics and environment on the composition of foods.
6. An improved analytical method for the analysis of glucosinolates. Glucosinolates, sulfur containing compounds found in brassica vegetables (broccoli, cauliflower, and kale plants found in the mustard family), have purported value in mitigating cancer but are extremely difficult to analyze due to their chemical variation. USDA-ARS scientists at the Beltsville Human Nutrition Research Center in Beltsville, Maryland, developed an improved extraction and purification procedure as an alternative to the traditional ISO 9167-1 method for quantitation of glucosinolates. This efficient procedure involved a weak anion exchange solid-phase extraction (SPE) cartridge which resulted in comparable quantification of total and individual glucosinolates on certified rapeseeds and other brassica vegetables compared to the ISO method. The SPE method is simpler and more efficient, allowing application to a large sample size with reduced analysis time, improved repeatability and accuracy, and possible automation. This work is being used collaboratively with scientists at the Food Quality Laboratory of USDA-ARS.
7. A simple method for optimizing controlled environment agricultural (CEA). A rapid and simple investigation method for optimizing the CEA growing conditions was developed. USDA-ARS scientists at the Beltsville Human Nutrition Research Center in Beltsville, Maryland, developed a non-targeted metabolomic method for investigation of phytochemical profiles of vegetables grown under different CEA conditions using brassica microgreens as model plants. With this method, a minimum sample size of two cotyledons and liquid chromatography-high resolution mass spectrometry were used for sample analysis. Image-based data normalization coupled with chemometric analysis were applied for post-acquisition data analysis. This method successfully distinguished between brassica microgreens grown under different CEA settings in a shortened cycle. This work is being used collaboratively with scientists at the Food Quality Laboratory of USDA-ARS.
8. Pig fecal diet biomarkers for fruit and vegetable intake. Exploring the link between diet and health has obtained significant attention. USDA-ARS scientists at the Beltsville Human Nutrition Research Center in Beltsville, Maryland, identified potential dietary biomarkers from pig fecal samples with fruit and vegetable interventions using liquid chromatography-high resolution mass spectrometry, multivariate statistical analysis, and metabolic pathway prediction and network exploration. The integration of data-driven and knowledge-based analytical methods enables the exploration of interconnected metabolic pathways and potential interactions between identified biomarkers. Based on this strategy, a significant number of potential biomarkers related to the intake of a diet enriched in flavanols, flavones, flavan-3-ols, and anthocyanins were identified. This work is being used collaboratively with scientists at the Diet, Genomics, and Immunology Lab of USDA-ARS.
9. Identify variability in wild and cultivated soybean seeds. USDA-ARS scientists at the Beltsville Human Nutrition Research Center and Beltsville Agricultural Research Center in Beltsville, Maryland, investigated the differential metabolite profiles of four wild and ten cultivated soybean genotypes. This was achieved by applying a non-targeted metabolomics approach using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry. The results showed putative identification of 98 metabolites belonging to several classes of phytochemicals, including isoflavones, organic acids, lipids, sugars, amino acids, saponins, and other compounds. Multivariate analysis showed a clear difference between wild and cultivated soybean cultivars. This metabolic information will benefit breeders and biotechnology professionals in developing value-added soybean seeds.
10. Phytochemical content of tomato cultivars grown under different salinity conditions. USDA-ARS scientists at the Beltsville Human Nutrition Research Center in Beltsville, Maryland in collaboration with USDA-ARS scientists in Riverside, California, evaluated the effect of increasing concentration of sulfate and chloride salts in irrigation water on the secondary metabolites profile in two tomato cultivars (‘Jaune Flamme’ and ‘Red Pear’). This was achieved by applying targeted and non-targeted approaches using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry. The results showed no significant impact of salinity in both cultivars based on secondary metabolites semi-quantification. Principal component analysis showed a distinct differentiation between the two cultivars. The total free amino acid concentrations increased with salinity as compared to the control. This research is important for identification of tomato cultivars that can be grown in drought-affected high saline areas with similar nutrient profiles with recycled water.
Review Publications
Tareq, F.S., Singh, J., Ferreira, J.F., Sandhu, D., Suarez, D.L., Luthria, D.L. 2024. A targeted and an untargeted metabolomics approach to study the phytochemicals of tomato cultivars grown under different salinity conditions. Journal of Agricultural and Food Chemistry. 72(14):7694-7706. https://doi.org/10.1021/acs.jafc.3c08498.
Dong, W., Yang, X., Chen, P., Sun, J., Harnly, J.M., Zhang, M., Zhang, N. 2024. Study of uv-vis molar absorptivity variation and quantitation of anthocyanins using molar relative response factor. Food Chemistry. 444:138653. https://doi.org/10.1016/j.foodchem.2024.138653.
Geng, P., Harnly, J.M., Sun, J., Chen, P. 2024. Variability and determinants of secondary metabolite profiles in cranberries (Vaccinium macrocarpon) from key cultivation states. Journal of Agriculture and Food Research. 15:100983. https://doi.org/10.1016/j.jafr.2024.100983.
Li, Y., Zhang, M., Pehrsson, P.R., Harnly, J.M., Chen, P., Sun, J. 2024. Fast and simple solid phase extraction-based method for glucosinolate determination: an alternative to ISO-9167 method. Foods. 13(5):650. https://doi.org/10.3390/foods13050650.
Teng, Z., Luo, Y., Sun, J., Pearlstein, D.J., Oehler, M., Fitzwater, J.D., Zhou, B., Hussan, M.A., Chang, C.Y., Chen, P., Wang, Q., Fonseca, J.M. 2024. Effect of far-red light on biomass accumulation, plant morphology, and phytonutrient composition of ruby streaks mustard at microgreen, baby leaf, and flowering stages. Journal of Agricultural and Food Chemistry. 72(17):9587–9598. https://doi.org/10.1021/acs.jafc.3c06834.
Choe, U., Liu, Z., Li, Y., Sun, J., Wu, X., Pehrsson, P.R., Xie, Z., Zhang, Y., Wang, T.T., Yu, L., Gao, B. 2023. Chemical compositions of dill (Anethum graveolens L.) water and ethanol extracts and their potential in reducing the COVID-19 risk and free radical scavenging capacities. Food Chemistry. 3(10):1654–1662. https://doi.org/10.1021/acsfoodscitech.3c00206?urlappend=%3Fref%3DPDF&jav=VoR&rel=cite-as.
