Vis/NIR hyperspectral imaging distinguishes sub-population, production environment, and physicochemical grain properties in rice.

Rice grain quality is a multifaceted quantitative trait that impacts crop value and is influenced by multiple genetic and environmental factors. Chemical, physical, and visual analyses are the standard methods for measuring grain quality. In this study, we evaluated high-throughput hyperspectral imaging for quantification of rice grain quality and classification of grain samples by genetic sub-population and production environment. Whole grain rice samples from the USDA mini-core collection grown in multiple locations were evaluated using hyperspectral imaging and compared with results from standard phenotyping. Loci associated with hyperspectral values were mapped in the mini-core with 3.2 million SNPs in a genome-wide association study (GWAS). Our results show that visible and near infra-red (Vis/NIR) spectroscopy can classify rice according to sub-population and production environment based on differences in physicochemical grain properties. The 702-900 nm range of the NIR spectrum was associated with the chalky grain trait. GWAS revealed that grain chalk and hyperspectral variation share genomic regions containing several plausible candidate genes for grain chalkiness. Hyperspectral quantification of grain chalk was validated using a segregating bi-parental mapping population. These results indicate that Vis/NIR can be used for non-destructive high throughput phenotyping of grain chalk and potentially other grain quality properties.

Red and Processed Meats and Health Risks: How Strong Is the Evidence?

Prevailing dietary guidelines have widely recommended diets relatively low in red and processed meats and high in minimally processed plant foods for the prevention of chronic diseases. However, an ad hoc research group called the Nutritional Recommendations (NutriRECS) consortium recently issued "new dietary guidelines" encouraging individuals to continue their current meat consumption habits due to "low certainty" of the evidence, difficulty of altering meat eaters' habits and preferences, and the lack of need to consider environmental impacts of red meat consumption. These recommendations are not justified, in large part because of the flawed methodologies used to review and grade nutritional evidence. The evidence evaluation was largely based on the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) criteria, which are primarily designed to grade the strength of evidence for clinical interventions especially pharmacotherapy. However, the infeasibility for conducting large, long-term randomized clinical trials on most dietary, lifestyle, and environmental exposures makes the criteria inappropriate in these areas. A separate research group proposed a modified and validated system for rating the meta-evidence on nutritional studies (NutriGRADE) to address several limitations of the GRADE criteria. Applying NutriGRADE, the evidence on the positive association between red and processed meats and type 2 diabetes was rated to be of "high quality," while the evidence on the association between red and processed meats and mortality was rated to be of "moderate quality." Another important limitation is that inadequate attention was paid to what might be replacing red meat, be it plant-based proteins, refined carbohydrates, or other foods. In summary, the red/processed meat recommendations by NutriRECS suffer from important methodological limitations and involve misinterpretations of nutritional evidence. To improve human and planetary health, dietary guidelines should continue to emphasize dietary patterns low in red and processed meats and high in minimally processed plant foods such as fruits and vegetables, whole grains, nuts, and legumes.

Circulating bile acids in healthy adults respond differently to a dietary pattern characterized by whole grains, legumes and fruits and vegetables compared to a diet high in refined grains and added sugars: A randomized, controlled, crossover feeding study.

OBJECTIVE: The effects of diets high in refined grains on biliary and colonic bile acids have been investigated extensively. However, the effects of diets high in whole versus refined grains on circulating bile acids, which can influence glucose homeostasis and inflammation through activation of farnesoid X receptor (FXR) and G protein-coupled bile acid receptor 1 (TGR5), have not been studied. MATERIALS AND METHODS: We conducted a secondary analysis from a randomized controlled crossover feeding trial (NCT00622661) in 80 healthy adults (40 women/40 men, age 18-45 years) from the greater Seattle Area, half of which were normal weight (BMI 18.5-25.0 kg/m2) and half overweight to obese (BMI 28.0-39.9 kg/m2). Participants consumed two four-week controlled diets in randomized order: 1) a whole grain diet (WG diet), designed to be low in glycemic load (GL), high in whole grains, legumes, and fruits and vegetables, and 2) a refined grain diet (RG diet), designed to be high GL, high in refined grains and added sugars, separated by a four-week washout period. Quantitative targeted analysis of 55 bile acid species in fasting plasma was performed using liquid chromatography tandem mass spectrometry. Concentrations of glucose, insulin, and CRP were measured in fasting serum. Linear mixed models were used to test the effects of diet on bile acid concentrations, and determine the association between plasma bile acid concentrations and HOMA-IR and CRP. Benjamini-Hochberg false discovery rate (FDR) < 0.05 was used to control for multiple testing. RESULTS: A total of 29 plasma bile acids were reliably detected and retained for analysis. Taurolithocholic acid (TLCA), taurocholic acid (TCA) and glycocholic acid (GCA) were statistically significantly higher after the WG compared to the RG diet (FDR < 0.05). There were no significant differences by BMI or sex. When evaluating the association of bile acids and HOMA-IR, GCA, taurochenodeoxycholic acid, ursodeoxycholic acid (UDCA), 5ß­cholanic acid­3ß,12α­diol, 5­cholanic acid­3ß­ol, and glycodeoxycholic acid (GDCA) were statistically significantly positively associated with HOMA-IR individually, and as a group, total, 12α­hydroxylated, primary and secondary bile acids were also significant (FDR < 0.05). When stratifying by BMI, chenodeoxycholic acid (CDCA), cholic acid (CA), UDCA, 5ß-cholanic acid-3ß, deoxycholic acid, and total, 12α-hydroxylated, primary and secondary bile acid groups were significantly positively associated with HOMA-IR among overweight to obese individuals (FDR < 0.05). When stratifying by sex, GCA, CDCA, TCA, CA, UDCA, GDCA, glycolithocholic acid (GLCA), total, primary, 12α­hydroxylated, and glycine-conjugated bile acids were significantly associated with HOMA-IR among women, and CDCA, GDCA, and GLCA were significantly associated among men (FDR < 0.05). There were no significant associations between bile acids and CRP. CONCLUSIONS: Diets with comparable macronutrient and energy composition, but differing in carbohydrate source, affected fasting plasma bile acids differently. Specifically, a diet characterized by whole grains, legumes, and fruits and vegetables compared to a diet high in refined grains and added sugars led to modest increases in concentrations of TLCA, TCA and GCA, ligands for FXR and TGR5, which may have beneficial effects on glucose homeostasis.

The influence of whole grain products and red meat on intestinal microbiota composition in normal weight adults: a randomized crossover intervention trial.

Intestinal microbiota is related to obesity and serum lipid levels, both risk factors for chronic diseases constituting a challenge for public health. We investigated how a diet rich in whole grain (WG) products and red meat (RM) influences microbiota. During a 10-week crossover intervention study, 20 healthy adults consumed two isocaloric diets, one rich in WG products and one high in RM. Repeatedly data on microbiota were assessed by 16S rRNA based denaturing gradient gel electrophoresis (DGGE). A blood sample and anthropometric data were collected. Mixed models and logistic regression were used to investigate effects. Microbiota showed interindividual variability. However, dietary interventions modified microbiota appearance: 8 bands changed in at least 4 participants during the interventions. One of the bands appearing after WG and one increasing after RM remained significant in regression models and were identified as Collinsella aerofaciens and Clostridium sp. The WG intervention lowered obesity parameters, while the RM diet increased serum levels of uric acid and creatinine. The study showed that diet is a component of major relevance regarding its influence on intestinal microbiota and that WG has an important role for health. The results could guide investigations of diet and microbiota in observational prospective cohort studies. Trial registration: ClinicalTrials.gov NCT01449383.