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Background Human selection has a long history of transforming crop genomes. Peach ( Prunus persica ) has undergone more than 5000 years of domestication that led to remarkable changes in a series of agronomically important traits, but genetic bases underlying these changes and the effects of artificial selection on genomic diversity are not well understood. Results Here, we report a comprehensive analysis of peach evolution based on genome sequences of 480 wild and cultivated accessions. By focusing on a set of quantitative trait loci (QTLs), we provide evidence supporting that distinct phases of domestication and improvement have led to an increase in fruit size and taste and extended its geographic distribution. Fruit size was predominantly selected during domestication, and selection for large fruits has led to the loss of genetic diversity in several fruit weight QTLs. In contrast, fruit taste-related QTLs were successively selected for by domestication and improvement, with more QTLs selected for during improvement. Genome-wide association studies of 11 agronomic traits suggest a set of candidate genes controlling these traits and potential markers for molecular breeding. Candidate loci for genes that contributed to the adaption to low-chill regions were identified. Furthermore, the genomic bases of divergent selection for fruit texture and local breeding for different flavors between Asian and European/North American cultivars were also determined. Conclusions Our results elucidate the genetic basis of peach evolution and provide new resources for future genomics-guided peach breeding.

Background The 2019 EAT-Lancet Commission report recommends healthy diets that can feed 10 billion people by 2050 from environmentally sustainable food systems. This study compares food consumption patterns in India, from different income groups, regions and sectors (rural/urban), with the EAT-Lancet reference diet and highlights the deviations. Methods The analysis was done using data from the Consumption Expenditure Survey (CES) of a nationally representative sample of 0.102 million households from 7469 villages and 5268 urban blocks of India conducted by the National Sample Survey Organization (NSSO) in 2011–12. This is the most recent nationally representative data on household consumption in India. Calorie consumption (kcal/capita/day) of each food group was calculated using the quantity of consumption from the data and nutritional values of food items provided by NSSO. Diets for rural and urban, poor and rich households across different regions were compared with EAT-Lancet reference diet. Results The average daily calorie consumption in India is below the recommended 2503 kcal/capita/day across all groups compared, except for the richest 5% of the population. Calorie share of whole grains is significantly higher than the EAT-Lancet recommendations while those of fruits, vegetables, legumes, meat, fish and eggs are significantly lower. The share of calories from protein sources is only 6–8% in India compared to 29% in the reference diet. The imbalance is highest for the households in the lowest decile of consumption expenditure, but even the richest households in India do not consume adequate amounts of fruits, vegetables and non-cereal proteins in their diets. An average Indian household consumes more calories from processed foods than fruits. Conclusions Indian diets, across states and income groups, are unhealthy. Indians also consume excess amounts of cereals and not enough proteins, fruits, and vegetables. Importantly, unlike many countries, excess consumption of animal protein is not a problem in India. Indian policymakers need to accelerate food-system-wide efforts to make healthier and sustainable diets more affordable, accessible and acceptable.

Background Mango is one of the world’s most important tropical fruits. It belongs to the family Anacardiaceae, which includes several other economically important species, notably cashew, sumac and pistachio from other genera. Many species in this family produce family-specific urushiols and related phenols, which can induce contact dermatitis. Results We generate a chromosome-scale genome assembly of mango, providing a reference genome for the Anacardiaceae family. Our results indicate the occurrence of a recent whole-genome duplication (WGD) event in mango. Duplicated genes preferentially retained include photosynthetic, photorespiration, and lipid metabolic genes that may have provided adaptive advantages to sharp historical decreases in atmospheric carbon dioxide and global temperatures. A notable example of an extended gene family is the chalcone synthase (CHS) family of genes, and particular genes in this family show universally higher expression in peels than in flesh, likely for the biosynthesis of urushiols and related phenols. Genome resequencing reveals two distinct groups of mango varieties, with commercial varieties clustered with India germplasms and demonstrating allelic admixture, and indigenous varieties from Southeast Asia in the second group. Landraces indigenous in China formed distinct clades, and some showed admixture in genomes. Conclusions Analysis of chromosome-scale mango genome sequences reveals photosynthesis and lipid metabolism are preferentially retained after a recent WGD event, and expansion of CHS genes is likely associated with urushiol biosynthesis in mango. Genome resequencing clarifies two groups of mango varieties, discovers allelic admixture in commercial varieties, and shows distinct genetic background of landraces.

Background Banana ( Musa spp.) is the most popular marketable fruit crop grown all over the world, and a dominant staple food in many developing countries. Worldwide, banana production is affected by numerous diseases and pests. Novel and rapid methods for the timely detection of pests and diseases will allow to surveil and develop control measures with greater efficiency. As deep convolutional neural networks (DCNN) and transfer learning has been successfully applied in various fields, it has freshly moved in the domain of just-in-time crop disease detection. The aim of this research is to develop an AI-based banana disease and pest detection system using a DCNN to support banana farmers. Results Large datasets of expert pre-screened banana disease and pest symptom/damage images were collected from various hotspots in Africa and Southern India. To build a detection model, we retrained three different convolutional neural network (CNN) architectures using a transfer learning approach. A total of six different models were developed from 18 different classes (disease by plant parts) using images collected from different parts of the banana plant. Our studies revealed ResNet50 and InceptionV2 based models performed better compared to MobileNetV1. These architectures represent the state-of-the-art results of banana diseases and pest detection with an accuracy of more than 90% in most of the models tested. These experimental results were comparable with other state-of-the-art models found in the literature. With a future view to run these detection capabilities on a mobile device, we evaluated the performance of SSD (single shot detector) MobileNetV1. Performance and validation metrics were also computed to measure the accuracy of different models in automated disease detection methods. Conclusion Our results showed that the DCNN was a robust and easily deployable strategy for digital banana disease and pest detection. Using a pre-trained disease recognition model, we were able to perform deep transfer learning (DTL) to produce a network that can make accurate predictions. This significant high success rate makes the model a useful early disease and pest detection tool, and this research could be further extended to develop a fully automated mobile app to help millions of banana farmers in developing countries.

Fruit peels have a diverse range of phytochemicals including carotenoids, vitamins, dietary fibres, and phenolic compounds, some with remarkable antioxidant properties. Nevertheless, the comprehensive screening and characterization of the complex array of phenolic compounds in different fruit peels is limited. This study aimed to determine the polyphenol content and their antioxidant potential in twenty different fruit peel samples in an ethanolic extraction, including their comprehensive characterization and quantification using the LC-MS/MS and HPLC. The obtained results showed that the mango peel exhibited the highest phenolic content for TPC (27.51 ± 0.63 mg GAE/g) and TFC (1.75 ± 0.08 mg QE/g), while the TTC (9.01 ± 0.20 mg CE/g) was slightly higher in the avocado peel than mango peel (8.99 ± 0.13 mg CE/g). In terms of antioxidant potential, the grapefruit peel had the highest radical scavenging capacities for the DPPH (9.17 ± 0.19 mg AAE/g), ABTS (10.79 ± 0.56 mg AAE/g), ferric reducing capacity in FRAP (9.22 ± 0.25 mg AA/g), and total antioxidant capacity, TAC (8.77 ± 0.34 mg AAE/g) compared to other fruit peel samples. The application of LC-ESI-QTOF-MS/MS tentatively identified and characterized a total of 176 phenolics, including phenolic acids (49), flavonoids (86), lignans (11), stilbene (5) and other polyphenols (25) in all twenty peel samples. From HPLC-PDA quantification, the mango peel sample showed significantly higher phenolic content, particularly for phenolic acids (gallic acid, 14.5 ± 0.4 mg/g) and flavonoids (quercetin, 11.9 ± 0.4 mg/g), as compared to other fruit peel samples. These results highlight the importance of fruit peels as a potential source of polyphenols. This study provides supportive information for the utilization of different phenolic rich fruit peels as ingredients in food, feed, and nutraceutical products.

Objective: Mediterranean diet is associated with decreased levels of inflammatory markers and metabolic risk factors in epidemiologic studies and recent trials on patients with metabolic syndrome. Given the recent improvements in medical treatments, it is unclear if such beneficial effects are also present in patients with coronary artery disease (CAD). We therefore investigated the effect of Mediterranean diet on markers of inflammation and metabolic risk factors in patients with treated CAD. Design: Randomized, controlled trial. Subjects: A total of 101 patients (59.4+/-8.6 years, 23% female) with established and treated CAD (80% statins). Interventions: Participants were assigned to a Mediterranean diet group (MG; n=48) with a 1-year program of 100 h of education, or to a written advice-only group (AG; n=53). Before and after intervention, we measured serum high-sensitivity C-reactive protein (hs-CRP), fibrinogen, fasting insulin, homocysteine, serum lipids and plasma fatty acids. Results: The Mediterranean diet program increased the intakes of fish, fruits/vegetables and moderately of canola/olive oil and increased plasma concentrations of long-chain n-3 polyunsaturated fatty acids in the MG. Median hs-CRP and mean fibrinogen, homocysteine, fasting insulin, triglycerides and serum cholesterols remained unchanged in both groups. Conclusions: Adoption of a Mediterranean diet by patients with medically treated CAD has no effect on markers of inflammation and metabolic risk factors. Sponsorship: Alfried Krupp Foundation, Essen, Germany.

Intensively bred fruit crops, including tomatoes and strawberries, are widely viewed as lacking flavour. The lack of breeder focus on the consumer is largely due to the genetic complexity of the flavour phenotype as well as a lack of a simple assay that can define consumer preferences. Rapid advances in genomics have opened up new opportunities to understand the chemistry and genetics of flavour. Here, we describe the underlying causes for the loss of flavour in fruits over time and delineate a blueprint for defining the chemistry of consumer liking, reducing that knowledge into a molecular roadmap for flavour improvement.

Human and animal diet reconstruction studies that rely on tissue chemical signatures aim at providing estimates on the relative intake of potential food groups. However, several sources of uncertainty need to be considered when handling data. Bayesian mixing models provide a natural platform to handle diverse sources of uncertainty while allowing the user to contribute with prior expert information. The Bayesian mixing model FRUITS (Food Reconstruction Using Isotopic Transferred Signals) was developed for use in diet reconstruction studies. FRUITS incorporates the capability to account for dietary routing, that is, the contribution of different food fractions (e.g. macronutrients) towards a dietary proxy signal measured in the consumer. FRUITS also provides relatively straightforward means for the introduction of prior information on the relative dietary contributions of food groups or food fractions. This type of prior may originate, for instance, from physiological or metabolic studies. FRUITS performance was tested using simulated data and data from a published controlled animal feeding experiment. The feeding experiment data was selected to exemplify the application of the novel capabilities incorporated into FRUITS but also to illustrate some of the aspects that need to be considered when handling data within diet reconstruction studies. FRUITS accurately predicted dietary intakes, and more precise estimates were obtained for dietary scenarios in which expert prior information was included. FRUITS represents a useful tool to achieve accurate and precise food intake estimates in diet reconstruction studies within different scientific fields (e.g. ecology, forensics, archaeology, and dietary physiology).

States that many children globally do not meet government guidelines for daily fruit and vegetable intake, and in New Zealand, adherence to the vegetable intake recommendation is declining. Aims to identify systemic barriers to children (from a low-income, ethnically-diverse community in West Auckland) meeting fruit and vegetable (FV) guidelines and generate sustainable actions within a local community to improve children’s FV intake. Highlights the effectiveness of group model building for engaging a local community in systems change to improve child nutrition. Discusses home environment, fast food, community nutrition and health outcomes. Source: National Library of New Zealand Te Puna Matauranga o Aotearoa, licensed by the Department of Internal Affairs for re-use under the Creative Commons Attribution 3.0 New Zealand Licence.

Pregnant women and children are especially vulnerable to exposures to food contaminants, and a balanced diet during these periods is critical for optimal nutritional status. Our objective was to study the association between diet and measured blood and urinary levels of environmental contaminants in mother-child pairs from six European birth cohorts ( mothers and 1,288 children). We assessed the consumption of seven food groups and the blood levels of organochlorine pesticides, polybrominated diphenyl ethers, polychlorinated biphenyls (PCBs), per- and polyfluoroalkyl substances (PFAS), and heavy metals and urinary levels of phthalate metabolites, phenolic compounds, and organophosphate pesticide (OP) metabolites. Organic food consumption during childhood was also studied. We applied multivariable linear regressions and targeted maximum likelihood based estimation (TMLE). Maternal high ( ) versus low ( ) fish consumption was associated with 15% higher PCBs [geometric mean (GM) ; 95% confidence interval (CI): 1.02, 1.29], 42% higher perfluoroundecanoate (PFUnDA) ( ; 95% CI: 1.20, 1.68), 89% higher mercury (Hg) ( ; 95% CI: 1.47, 2.41) and a 487% increase in arsenic (As) ( ; 95% CI: 2.57, 9.23) levels. In children, high ( ) versus low ( ) fish consumption was associated with 23% higher perfluorononanoate (PFNA) ( ; 95% CI: 1.08, 1.40), 36% higher PFUnDA ( ; 95% CI: 1.12, 1.64), 37% higher perfluorooctane sulfonate (PFOS) ( ; 95% CI: 1.22, 1.54), and higher Hg and As [ (95% CI: 1.91, 4.31) and (95% CI: 2.23, 3.21)] concentrations. Using TMLE analysis, we estimated that fish consumption within the recommended 2-3 times/week resulted in lower PFAS, Hg, and As compared with higher consumption. Fruit consumption was positively associated with OP metabolites. Organic food consumption was negatively associated with OP metabolites. Fish consumption is related to higher PFAS, Hg, and As exposures. In addition, fruit consumption is a source of exposure to OPs. https://doi.org/10.1289/EHP5324.