Bovine milk can harbor microbes that cause mastitis, milk spoilage, and foodborne illness. Fatty acids found in milk can be antimicrobial and milk oligosaccharides can have antiadhesive, prebiotic, and immune-modulatory effects.

This study examined the physiological effects of replacing some of the casein with either a plant based, animal or combination of protein sources in a high-fat diet fed to golden Syrian hamsters. Cooked kidney beans (BN) and beef (Bf) patties drained of fat were fed at 25 and 50% of diet. A combination of BN and Bf (BNBf) was also fed at 25 and 50%. Saturated fat content of the 25% Bf (Bf25) and 50% Bf (Bf50) increased 57 and 215% compared to Control. The Bf diets also increased caloric density compared to the Control. Likewise, the 50% Bn (Bn50) diet had 60% less saturated fat and lower caloric density than the Control. Despite these differences there were no differences in body weight gain or adipose weight between BN of Bf diets and Control. The BN50 diet reduced liver weight and increased caloric intake. The BN diets reduced total plasma cholesterol (TC). The BF diets also reduced TC but the results were not significant. The BN25, BN50 and BNBF50 diets also reduced low density lipoprotein (LDL) cholesterol. The BN and BF50 diets reduced liver fat. The BN diets decreased fecal fat excretion while the BF diets increased excretion. This suggests that increased fat excretion might offset the higher total fat and saturated fat of the BF diets to reduce adverse effects on body weight, adipose weight, and cholesterol. The high-fat content of the base (Control) diet may have muted the effects of the diet treatments. Graphical Abstract

BackgroundBranched-chain fatty acids (BCFAs) are rumen-derived fatty acids comprising ∼2% of bovine-milk fatty acids. BCFAs possess anti-inflammatory properties and enriching the BCFA content of bovine milk may provide human health benefits.ObjectiveWe determined whether forage content impacts the BCFA content of milk from Holstein cows and identified fatty acid phenotypes in high vs. low BCFA-containing milks.MethodsHolstein cows (n = 62), fed for 67 d in a crossover design, consumed a diet with high forage and low concentrate (HF:C) and a diet with low forage and high concentrate (LF:C). Milk samples were collected at the end of each treatment period and fatty acid content determined. Paired t-tests, 1-factor ANOVA, sparse partial least-squares discriminant analysis (sPLSDA), and Pearson's correlation analysis were used to analyze the data.ResultsThe total milk fatty acid concentration for cows fed the HF:C diet was greater than that of cows fed the LF:C diet (4.2 ± 0.7 g/100 mL vs. 3.9 ± 0.9 g/100 mL). sPLSDA demonstrated separation of the dietary treatments, with BCFAs and odd-chain fatty acids as primary determinants. Total BCFA content in milk fat was elevated by HF:C intake compared with LF:C intake (1.80 vs. 1.68%). Quintile separation of high vs. low BCFA milks resulted in 4 groups: HF:C /low BCFAs, HF:C /high BCFAs; LF:C /low BCFAs, and LF:C /high BCFAs. Milks from the high BCFA quintiles had lower palmitic acid content (29.6% vs. 34.4%) but higher oleic acid content than milks from the low BCFA quintiles (19.7% vs. 17.0%). Some cows were identified as high BCFA producers or low BCFA producers regardless of diet.ConclusionsBCFA content of milk is diet-sensitive but variation in responses exists. The potential to produce milk with high BCFA content and lower SFA content needs further study.

Berry fruits are rich in polyphenolic compounds (PCs) and may promote health benefits. Anthocyanin (ACN) concentrations of red raspberry (RR) (Rubus idaeus) extracts were 887.6 ± 262.8 μg g-1, consisting mainly of cyanidin-3-sophoroside (C3S) equivalents. To test the efficacy of RR in diabetes treatment, seven patients with type 2 diabetes mellitus (T2DM) were given one oral RR serving (123 g per day) for two weeks. Blood samples were drawn at the baseline (BSL) and post-feeding (PF) periods for phenolic metabolite, inflammation and insulin resistance (IR) biomarker analysis. Two urolithin conjugates, urolithin A glucuronide (Uro-A glur) and urolithin A sulphate (Uro-A sulf) were identified in the PF period in 5 of the 7 patients in nanomolar concentrations (1.6 ± 0.7-63.2 ± 31.2 nM). ACN-derived metabolites such as protocatechuic acid (PCA) and 3,4-dihydroxyphenylacetic acid (DOPAC) were at micromolar levels and were higher during the PF period for diabetics and the levels were as follows: BSL: PCA = 0.6 ± 0.4, DOPAC = 1.2 ± 0.5; PF: PCA = 0.6 ± 0.4, DOPAC = 1.1 ± 0.6. The results revealed significant reductions in high sensitivity C-reactive protein, hsCRP (p = 0.01) and there was a downward trend in IR measured by the homeostatic model assessment of insulin resistance (HOMA-IR, p = 0.0584) in T2DM patients. DOPAC (1-100 μM) failed to stimulate insulin secretion in pancreatic β-cells. The multiplex assay showed variations in the cytokine levels between patients, but differences were not significant. This study demonstrates a potential use of RR in the treatment of inflammation and possibly IR as well in patients with type 2 diabetes.

Machine learning and classical statistics were used to unravel the complex data set generated by the analysis of 77 fatty acids in milk from 76 cows fed 3 forages. Multivariate analysis of variance - principal components analysis (mANOVA-PCA) was used to deconvolute the data and determine the variance contributed by the main experimental factors: forage, the arbitrary cow groups, cow-to-cow variability, and milking day. All four factors contributed significantly to the data variance at the 99 % confidence level as did the cross-factor variances. Cow-to-cow variance constituted 51 % of the total variance of the data set and had to be removed before the significance of the other factors could be determined. The 3 forages were then found to generate milk fatty acid profiles that were significantly different. The PCA loadings showed that the major contributors to separate clustering of the forages were the less concentrated branched chain fatty acids. Fatty acids with even numbers of carbons were more concentrated, contributed high signal levels, and high noise, but were not significant in discriminating between forages. Classical paired analysis also removed the cow-to-cow variance and allowed discrimination between forages. The results showed that forages can significantly impact the fatty acid composition of milk.

Background: A more sustainable dairy cow diet was designed that minimizes use of feed components digestible by monogastric animals by increasing the quantity of forages. Objectives: This study determined if feeding lactating cows the more sustainable, low-starch and high-fiber (LSHF) diet was associated with changes in raw milk microbiota composition and somatic cell count (SCC). Methods: In a crossover design, 76 lactating Holstein cows were assigned to an LSHF diet or a high-starch and low-fiber (HSLF) diet, similar to common dairy cow diets in the United States, for 10 wk then placed on the opposite diet for 10 wk. The LSHF diet contained greater quantities of forages, beet pulp, and corn distillers' grain, but contained less canola meal and no high-moisture corn compared with the HSLF diet. Raw milk samples were collected from each cow 4-5 d before intervention and 5 wk into each diet treatment. Within 4 d, additional milk samples were collected for measurement of SCC using Fossmatic 7. The microbial community was determined by sequencing the 16S rRNA gene V4-V5 region and analyzing sequences with QIIME2. After quality filtering, 53 cows remained. Results: Raw milk microbial communities differed by diet and time. Taxa associated with fiber consumption, such as Lachnospiraceae, Lactobacillus, Bacteroides, and Methanobrevibacter, were enriched with the LSHF diet. Meanwhile, taxa associated with mastitis, such as Pseudomonas, Stenotrophomonas, and Enterobacteriaceae, were enriched with the HSLF diet. Relatedly, an interaction of diet and time was found to impact SCC. Conclusions: In raw milk, consumption of an LSHF diet compared with an HSLF diet was associated with changes in abundance of microbes previously associated with fiber consumption, udder health, and milk spoilage. Further research is needed to determine if an LSHF diet indeed leads to lower rates of mastitis and milk spoilage, which could benefit the dairy industry.

FoodData Central (FDC) is the center of the USDA-based food-composition information web. It is an integrated data system that presently provides—in 1 place—5 distinct types of data containing information on food and nutrient profiles. Each data type has a unique purpose. Two of the data types—Foundation Foods (FF) and Experimental Foods (EF)—represent "a bridge to the future" in food and nutrient composition. They provide data and metadata that have never previously been available from a database. The other 3 data types are well established and familiar to many users: Standard Reference (SR) Legacy, Food and Nutrient Database for Dietary Studies (FNDDS), and Global Branded Foods Products Database (GBFPD). After >100 y of maintaining food-composition data within the USDA, it was clear that change was needed to respond to the rapid increase in the number and variety of foods in the food supply, evolution of analytical approaches, and new agricultural practices and products. FDC is USDA's answer to the challenge of providing reliable, web-based, transparent, and easily accessible information about the nutrients and other components of foods to meet the increasingly diverse needs of many audiences, including public health professionals, agricultural and environmental researchers, policy makers, nutrition professionals, health care providers, product developers, and the public at large.

Background:Bovine milk oligosaccharides (BMOs) have several demonstrated and hypothesized benefits including roles in cognitive development and antipathogenic activities, making them promising ingredients for infant formulas and nutraceutical applications. BMO extraction from bovine milk is challenged by low concentrations relative to nonbioactive simple sugars like lactose. BMO abundances are known to vary with a cow's lactation stage, breed, and parity, but these characteristics are difficult to modify in existing dairy herds. In contrast, diet modification is an accessible target, and is already known to influence milk yield, lipid content, protein levels, and monosaccharide compositions. Objectives:To determine the impact of a low starch high fiber versus a high starch low fiber diet on overall BMO profiles and individual BMO abundances in Holstein dairy cattle. Methods:Milk samples were collected from 59 midlactation Holsteins in a crossover study featuring dietary modification with either a low starch high fiber or high starch low fiber feed. BMO profiles were evaluated by nano-LC quadrupole time-of-flight tandem MS, and differences in BMO abundances between diets were evaluated using linear mixed effects modeling. Results:A total of 19 BMOs were identified across the sample set, including 4 large fucosylated compounds. Seven BMOs were found to have significantly more positive percent changes in yield-adjusted abundance from the pre-experiment baseline period for milk samples collected during feeding with the low starch high fiber diet compared with the high starch low fiber diet. Conclusions:Consuming the low starch high fiber diet promoted greater overall BMO production than the high starch low fiber diet in a population of midlactation Holsteins. Additionally, this study afforded the opportunity to investigate the impact of other factors potentially influencing BMO abundances, furthering understanding of how dairy herd management practices can positively impact milk composition and support the potential use of BMOs as functional ingredients.

ObjectivesA dynamic US food supply and need for assessment of diet on health demands transparent, easily accessible information on foods and food components and related data on production and variability for researchers, health and nutrition policymakers and professionals, and food manufacturers. USDA is to develop an integrated food data system to address these needs and provide capacity for higher resolution compositional data analysis and an increase in available food metadata.

Since the outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the coronavirus disease-19 (COVID-19), in December 2019, the infection has spread around the globe. Some of the risk factors include social distancing, mask wearing, hand washing with soap, obesity, diabetes, hypertension, asthma, cardiovascular disease, and dysbiosis. Evidence has shown the incidence of total infection and death rates to be lower in sub-Saharan Africa when compared with North Africa, Europe and North America and many other parts of the world. The higher the metabolic syndrome rate, the higher the risk of SARS-CoV-2 infection. Africa has a lower rate of metabolic syndrome risk than many other continents. This paradox has puzzled several in the biomedical and scientific communities. Published results of research have demonstrated the exciting correlation that the combination of young age of the population coupled with their native plant-based diet has lowered their risk factors. The plant-based diet include whole grains (millet, sorghum), legumes (black-eye peas, dry beans, soybean), vegetables, potato, sweet potato, yams, squash, banana, pumpkin seeds, and moringa leaves, and lower consumption of meat. The plant-based diet results in a different gut microbiota than of most of the rest of the world. This has a significant impact on the survival rate of other populations. The "plant-based diet" results in lower rates of obesity, diabetes and dysbiosis, which could contribute to lower and less severe infections. However, these hypotheses need to be supported by more clinical and biostatistics data.

Recent analyses indicate that global fruit and vegetable (F&V) production will need to increase by 50%–150% by 2050 in order to achieve sustainable and healthy diets for 10 billion people. Although global production of F&V has grown by 50% during the last two decades alone, simply scaling up current systems of F&V production, supply chains, and consumption will inevitably worsen environmental and socioeconomic tradeoffs. This article examines three examples of important F&V—avocados, leafy greens, and tomatoes—to assess the global challenge of meeting dietary recommendations at affordable prices to consumers while sustaining producer livelihoods and minimizing environmental damage. These three cases highlight key characteristics of F&V systems that make the challenge of sustainable expansion especially difficult: knowledge-, input-, and labor-intensive production, high rates of food loss and waste, and low affordability to consumers relative to less nutrient-dense food groups. Our analysis shows that only by investing in innovations that increase diversity, integrate technology, and improve equity will truly sustainable expansion of F&V systems be possible.

With a growing global population, the demand for high-quality food to meet nutritional needs continues to increase. Our ability to meet those needs is challenged by a changing environment that includes constraints on land and water resources and growing concerns about the impact of human activity including agricultural practices on the changing climate. Adaptations that meet food/nutritional demands while avoiding unintended consequences including negatively affecting the environment are needed. This article covers a specific case study, the role of animal source foods (ASFs) in meeting micronutrient needs in a changing environment. The article covers our understanding of the role of ASFs in meeting micronutrient needs, evidence-based approaches to the development of nutrition guidance, the current issues associated with the relation between animal production practices and greenhouse gas emissions, and examples of how we might model the myriad sources of relevant data to better understand these complex interrelations.

The agriculture system is tasked with the responsibility to deliver adequate quantities of food, which meet national needs, provide health benefits, and deliver these in an environmentally sustainable system. Efforts by the food industry to deliver safe and nutritious foods, which also improve health and wellness, are complicated by a constantly changing landscape. As early as the 1950s, fat in diets was a concern, and in the 1980s and early 1990s, fat was an evil component in foods. In response, the industry developed zero/low fats and foods and low-fat foods. The evolution in dietary guidelines in the 2000s has evolved to greater concern over simple sugars and starches as negative sources of calories in an environment of increasing obesity. With the world population approaching 9 billion individuals by 2050, food production, which relies on large amounts of water and energy, must become more efficient. Food production and delivery also must find innovative ways to reduce food waste, environmental pollutants, and greenhouse gas production. The nexus of food, energy, and water is and will continue to be a major research and political and communication emphasis for the scientific community. We must find clear and consumer friendly communications to explain the utilization of modern technology in food production. Solutions to these issues must also include sustainably produced, safe, nutritious, satisfying, and wholesome foods.

Manganese is an essential trace element because of its role in a number of enzyme systems and perhaps, because of its role as an intracellular metabolic regulator. The involvement of manganese in enzyme systems can be differentiated between manganese-containing enzymes and manganese-activated enzymes. Absorption of manganese is influenced most notably by iron; these two elements may utilize a common absorptive pathway. Manganese enters the portal system bound to a ligand, and recent findings indicate that the ligand may be albumin,6 although other findings suggest transferrin. Primary problems encountered in manganese-deficient animals include skeletal abnormalities. The primary causative factor apparently is decreased glycosyltransferase activity that leads to a subsequent decrease in proteoglycan formation. An initial indication of this relationship came from the report of an insulin-resistant man whose blood glucose was lowered by administration of oral manganese supplements. The interaction between iron and manganese has been noted in numerous studies and reviewed extensively.

Beans provide a rich source of plant-based proteins and carbohydrates. It is well documented in the literature that the raffinose family of oligosaccharides (RFOs: raffinose, stachyose, and verbascose) is linked with flatulence issues. In this study, the soluble sugar content of 23 dry beans was investigated using a newly developed and validated analytical method with high-performance anion-exchange chromatography coupled to an amperometric pulse detection. All seven sugars (galactose, glucose, fructose, sucrose, raffinose, stachyose, and verbascose) showed good linearity (r(2) >= 0.99) between 0.156 and 20 mu g/mL. The limit of detection and quantification were determined as 0.01-0.11 mu g/mL and 0.04-0.32 mu g/mL, respectively. Significant variations in the profiles and concentrations of individual and total sugars were observed in 23 dry beans. Sucrose and stachyose were the two prominent soluble sugars combinedly representing an average of 86% of the total soluble sugars. Yellow split beans, large lima, and black eyed peas contained higher amounts of total soluble sugars (79.8-83.6 mg/g), whereas lower amounts were observed in speckled butter peas and lentils (53.6-56.6 mg/g). Garbanzo beans contained maximum levels of mono and disaccharides (MD), and yellow split beans showed the highest levels of RFOs. Based on the hierarchical cluster analysis of the total soluble sugars (TS), MD, RFOs, and MD/RFOs ratio, 23 beans can be classified into five groups. The average TS content and the MD/RFOs ratios of the five groups were determined as group 1 (TS = 55.1 mg/g and MD/RFOs = 0.30), group 2 (TS = 77.6 mg/g and MD/RFOs = 0.31), group 3 (TS = 78.3 mg/g and MD/RFOs = 0.51), group 4 (TS = 59.1 mg/g and MD/RFOs = 1.06), and group 5 (TS = 68.5 mg/g and MD/RFOs = 0.62). This information is useful for researchers, food industries, and consumers that are looking for plant-based protein source as an alternative to animal proteins with reduced flatulence problems.

Glyphosate is the most used herbicide on the planet because of its excellent efficacy on almost all weed species and due to the large-scale adoption of transgenic, glyphosate-resistant (GR) crops. Agnes Rimando became an expert in glyphosate analysis almost 20 years ago to support research on GR crop safety and on mechanisms of evolved glyphosate resistance by weeds. Her work was the first to show that the amount of glyphosate and its primary metabolite aminomethylphosphonic acid (AMPA) that accumulates in GR soybean seed from plants treated with approved glyphosate doses can approach their legal limits. However, she later found that only trace amounts of these compounds accumulate in the seed of GR maize treated with recommended glyphosate doses. She showed that GR canola, the only transgenic crop with a transgene encoding an enzyme for degradation of glyphosate, metabolizes glyphosate to AMPA very rapidly. Her work was instrumental in providing support for the view that "yellow flash" symptoms sometimes observed in field-grown GR soybeans are due to accumulation of enough AMPA to cause mild phytotoxicity. She did the chemical analyses in the only paper to survey the capacity of an array of plant species to metabolize glyphosate to AMPA. She found a wide range in this capacity, with grasses with little or no metabolism of glyphosate to AMPA and with legumes readily metabolizing glyphosate. Lastly, she found no evidence of enhanced degradation of glyphosate to be a mechanism of evolved resistance to glyphosate by two weed species but that it might be involved in natural tolerance to glyphosate of some weeds.

Efforts to promote health through improved diet and nutrition demand an appreciation of the nutritional ecology that accounts for the intersection of agriculture, food systems, health, disease and a changing environment. The complexity and implications of this ecology is exemplified by current trends and efforts to address nutrition-related non-communicable diseases (NCDs), most prominently type 2 diabetes. The global prevalence of type 2 diabetes continues to rise unabated. Of particular concern is how to address the unhealthy dietary patterns that are contributing to this pandemic in a changing environment. A multi- disciplinary approach is required that will engage those communities that comprise the continuum of effort from research to translation and implementation of evidence-informed interventions, programs and policies. Using the prevention of type 2 diabetes by increasing fruit and vegetable consumption as an exemplar, we argue that the ability to effect positive change in this and other persistent nutrition-related problems can be achieved by moving away from siloed approaches that limit the integration of key components of the diet-health continuum. Ultimately the impact of preventing type 2 diabetes via increased fruit and vegetable consumption will depend on how the entire diet changes, not just fruits and vegetables. In addition, the rapidly changing physical environment that will confront our food production system going forward will also shape the interventions that are possible. Nonetheless, the proposed "team science" approach that accounts for all the elements of the nutrition ecology will better position us to achieve public health goals through safe and sustainable food systems.

The USDA Agricultural Research Service (ARS) conducts research of value to US agriculture and the food supply. Most research conducted in the past has been reductionist in nature and primarily one- or two-dimensional. However, the colliding challenges of feeding a burgeoning world population, maintaining a food supply that both provides sufficient nutrition without contributing to obesity and other chronic diseases and addresses the impact of agriculture on, as well as by, the environment, have changed the complexity of the task. Today's challenges have become multidimensional, requiring systems-type approaches across multiple and diverse disciplines. These projects cut across traditional boundaries and seek to optimize agricultural productivity within the context of reducing environmental impact and maintaining or increasing nutritional value that ultimately impacts public health. In short, new projects must take a systems approach, and the synergy gained from this approach is only made possible by simultaneous modeling of disparate data sets, demanding a new approach to data.