A Multi-Methodological Approach to Characterize the Grain “Senatore Cappelli” Food Chain: Composition and Safety

Ancient grains, so long-forgotten due to the dominance of modern grains with high yield and improved technological quality as result of breeding programs, are currently experiencing a comeback. A plethora of reasons involving the global loss of biodiversity, caused by a streamlined and uniform agriculture that relies on few species and leaves ecosystems vulnerable to pests and climate change, as well as global food challenges have been encouraging the use of ancient and traditional crops. “Senatore Cappelli” (SC) durum wheat is an important versatile resource for reintroducing genetic heterogeneity and providing special traits with health benefits and favorable nutritional compositions for food applications. Although many aspects of ancient grains have been discovered, it is still critical to investigate the safety and biological effects of SC food chain products. In this work, a multidisciplinary approach has been performed to characterize the chemical composition, biological effects and safety of SC seeds, flour, pasta and chaff for assessing the changes occurring during the industrial process. he NMR-based analysis pointed out significant qualitative differences among the examined matrices, specifically chaff, involving phenylpropanoids bioactive metabolites; a content of toxic biogenic amines commonly accepted by EU regulation, and a pesticide and mycotoxin content under European Limits were revealed by HPLC-MS/MS analysis. No potentially pathogenic microorganisms were detected in all raw matrices and ethanolic extracts. Moreover, in vitro and in vivo experiments showed no negative effects of hydroalcoholic extracts on the proliferation capacity of BV2 cells and an interesting ability to extend the lifespan of the animal model Caenorhabditis elegans. The used methodologies for quality and food safety control may be included in flow-chart to apply for the development of food sustainable and quality assurance models.