As efforts are made to increase food security, millets are gaining increasing importance due to their excellent nutritional credentials. Among the millets, pearl millet is the predominant species possessing several health benefiting nutritional traits in its grain that are helpful in mitigating chronic illnesses such as type−2 diabetes and obesity. In this paper, we conducted metabolomic fingerprinting of 197 pearl millet inbred lines drawn randomly from within the world collection of pearl millet germplasm and report the extent of genetic variation for health benefitting metabolites in these genotypes. Metabolites were extracted from seeds and assessed using flow infusion high-resolution mass spectrometry (FIE-HRMS). Metabolite features (m/z), whose levels significantly differed among the germplasm inbred lines, were identified by ANOVA corrected for FDR and subjected to functional pathway analysis. A number of health-benefiting metabolites linked to dietary starch, antioxidants, vitamins, and lipid metabolism-related compounds were identified. Metabolic genome-wide association analysis (mGWAS) performed using the 396 m/z as phenotypic traits and the 76 K SNP as genotypic variants identified a total of 897 SNPs associated with health benefiting nutritional metabolite at the -log p-value ≤ 4.0. From these associations, 738 probable candidate genes were predicted to have an important role in starch, antioxidants, vitamins, and lipid metabolism. The mGWAS analysis focused on genes involved in starch branching (α-amylase, β-amylase), vitamin-K reductase, UDP-glucuronosyl, and UDP-glucosyl transferase (UGTs), L-ascorbate oxidase, and isoflavone 2′-monooxygenase genes, which are known to be linked to increases in human health benefiting metabolites. We demonstrate how metabolomic, genomic, and statistical approaches can be utilized to pinpoint genetic variations and their functions linked to key nutritional properties in pearl millet, which in turn can be bred into millets and other cereals crops using plant breeding methods.

Genotype × environment interactions (GEIs) should play an important role in the selection of suitable germplasm in breeding programmes. We here assessed GEI effects on pearl millet (Pennisetum glaucum L.) genotypes, selected to possess a high concentration of slowly digestible starch (SDS) and resistant starch (RS) in their grains. Entries were grown in a randomized complete block design with three replications at locations in Bawku-Ghana, Sadore-Niger, Bamako-Mali, Konni-Nigeria, and Gampella-Burkina Faso across West Africa. Harvested grains from these locations were metabolomically profiled using flow injection ionization-high-resolution mass spectrometry (FIE-HRMS). A total of 3144 mass features (m/z) (1560 negative ion mode and 1584 positive ion mode) were detected, of which, 475 m/z were linked to metabolites be involved in starch, antioxidant and lipid biosynthesis, and vitamin metabolism. Combined ANOVA revealed that the GEI was significantly evident for 54 health-benefiting metabolites, many associated with sugar, especially galactose, metabolism. Additive main effects and multiplicative interaction (AMMI) analysis examined genotype variation and GEI effects, which, when combined with principal component analysis (PCA), found that m/z 171.14864 (positive ionisation, propenyl heptanoate) accounted for 89% of the GEI variation along PC1. The AMMI-based stability parameter (ASTAB), modified AMMI stability value (MASV), and modified AMMI stability index (MASI) were then applied to identify stable and high-performing genotypes for all the health-benefiting metabolites. Similarly, the best-linear-unbiased-prediction (BLUP)-based stability estimation was also performed using the harmonic mean of genotypic values (HMGV), relative performance of genotypic values (RPGV), and harmonic mean of relative performance of genotypic values (HMRPGV), to identify genotype rankings across multiple environments. The multi-trait stability index (MTSI) was calculated and found that the genotypes G1 (ICMH-177111) and G24 (ICMX-207137) were the most stable and were the best mean performers across 52 health-benefiting metabolic traits. These findings demonstrate the potential of G × E assessments on the delivery of health-benefiting metabolite-rich grains in future varieties and hybrids of pearl millet.

Cultivated raspberries (Rubus idaeus L.) most commonly bear small, red, highly aromatic fruits. Their colour is derived predominantly from anthocyanins, water soluble polyphenolic pigments, but as well as red forms, there exist cultivars that display yellow- and apricot-coloured fruits. In this investigation, we used a multi-omics approach to elucidate the genetic basis of the apricot fruit colour in raspberry. Using metabolomics, we quantified anthocyanins in red and apricot raspberry fruits and demonstrated that, in contrast to red-fruited raspberries, fruits of the apricot cultivar ‘Varnes’ contain low concentrations of only a small number of anthocyanin compounds. By performing RNASeq, we revealed differential expression patterns in the apricot-fruited ‘Varnes’ for genes in the anthocyanin biosynthesis pathway and following whole genome sequencing using long-read Oxford Nanopore Technologies sequencing, we identified a CACTA-like transposable element (TE) in the second exon of the Anthocyanidin synthase (Ans) gene that caused a truncated predicted ANS protein. PCR confirmed the presence in heterozygous form of the transposon in an unrelated, red-fruited cultivar ‘Veten’, indicating apricot fruit colour is recessive to red and that it may be widespread in raspberry germplasm, potentially explaining why apricot forms appear at regular intervals in modern raspberry breeding populations.

This study was conducted to quantify the variation in environmental impacts of strawberry production across Europe to inform breeders and fruit producers on practical ways to improve the sustainability of their products. We assessed the environmental impact of different strawberry genotypes and cultivation systems, including open field and protected systems, conducted by seven different partners in Europe. The Life Cycle Assessment (LCA) methodology was applied. Fifty‐seven strawberry genotypes were included in the analysis, covering 19 different field trials. The functional unit (FU) was 1 kg of freshly harvested ripe strawberry fruit at the farm gate, produced between 2017 and 2024. The results for the climate change impact category showed an average of 0.58 kg CO ₂ eq./FU among all the genotypes analyzed. The highest value was 3.8 kg CO ₂ eq./FU for a greenhouse system, and the lowest was 0.21 kg CO ₂ eq./FU for a polyethylene‐covered tunnel system. The results highlighted the crucial roles of cultivation systems, genotype selection, produced yield, and various input and management practices in the environmental performance of strawberry production. The work was based on trials connected to the breeding and testing of strawberry genotypes. The results thus help breeders to develop high‐quality strawberry cultivars designed to meet sustainable production under different climatic environments by showing the critical environmental impacts associated with their products. The comparison of the environmental performance of different strawberry cultivation systems across Europe even provides a benchmark to support fruit producers and policymakers in decision‐making for shaping sustainable strawberry production in Europe.