Modelling Processes and Products in the Cereal Chain

[EN] In recent years, modelling techniques have become more frequently adopted in the field of food processing, especially for cereal-based products, which are among the most consumed foods in the world. Predictive models and simulations make it possible to explore new approaches and optimize proceedings, potentially helping companies reduce costs and limit carbon emissions. Nevertheless, as the different phases of the food processing chain are highly specialized, advances in modelling are often unknown outside of a single domain, and models rarely take into account more than one step. This paper introduces the first high-level overview of modelling techniques employed in different parts of the cereal supply chain, from farming to storage, from drying to milling, from processing to consumption. This review, issued from a networking project including researchers from over 30 different countries, aims at presenting the current state of the art in each domain, showing common trends and synergies, to finally suggest promising future venues for research.The authors would like to acknowledge networking and article processing charge support by COST Action CA15118 (Mathematical and Computer Science Methods for Food Science and Industry).Carvalho, O.; Charalambides, MN.; Djekic, I.; Athanassiou, C.; Bakalis, S.; Benedito Fort, JJ.; Briffaz, A.... (2021). Modelling Processes and Products in the Cereal Chain. Foods. 10(1):1-18. https://doi.org/10.3390/foods10010082S11810

Development of a multiprimer metabarcoding approach to understanding trophic interactions in agroecosystems

To understand trophic interactions and the precise ecological role of each predatory species, it is important to know which arthropod and plant resources are used by generalist predators in agroecosystems. Molecular approaches, such as the use of high-throughput sequencing (HTS), play a key role in identifying these resources. This study develops a multiprimer metabarcoding approach for screening the most common trophic interactions of two predatory arthropods with contrasting morphologies, Rhagonycha fulva (Coleoptera: Cantharidae) and Anthocoris nemoralis (Hemiptera: Anthocoridae) collected from a peach crop. To reduce the time and cost of this metabarcoding approach, we first evaluated the effect of using two different predator-pools of different size (10 and 23 individuals of the same species). We also used our system to analyze the performance of one and two primer pairs in the same library. Our results show that the analysis of 23 individuals together with the use of two primer pairs in the same library optimize the HTS analysis. Using these best-performing conditions, we then analyzed the entire bodies of field-collected predators as well as the washing solutions used to clean the insect bodies. We were able to identify both gut content (i.e., diet) and external pollen load (i.e., on the insects’ bodies). This study also demonstrates the importance of washing predatory insects’ bodies prior to HTS analysis when the target species have a considerable size (>10 mm) and hairy structures. This metabarcoding approach has significant potential for the study of trophic links in agriculture, revealing expected and unexpected trophic relationships.info:eu-repo/semantics/acceptedVersio