Biosystems Engineering

Biosystems Engineering publishes research in engineering and the physical sciences that represent advances in the understanding and management of the performance of biological systems for sustainable developments in land use and the environment, agriculture and amenity, bioproduction processes and the food chain. The subject matter of the journal reflects the wide range and interdisciplinary nature of research in engineering for biological systems.

Papers may report the results of experiments, modelling, theoretical analyses, data driven findings, design of, or innovations relating to, machines and mechanisation systems, processes or processing methods, equipment and buildings, experimental equipment, laboratory and analytical techniques and instrumentation.

Submissions should (1) involve new engineering science insights, including novel characteristics that can advance the specific scientific field; (2) present existing similar work in its field and discuss the advance over the state of the art offered, and (3) illustrate the knowledge gap that the work seeks to fill. The novelty aspect is of crucial importance for our Journal, and it is also linked with our focus on Science4Impact. Please see 3.3. for more information.

Biosystems Engineering does NOT wish to publish:

research that does not include sufficient novelty and engineering insights that could provide advances in the specific scientific field;

findings obtained under conditions which are not sufficiently representative of practice, making the usefulness of the results and conclusions not well demonstrated;

application of Artificial Intelligence (AI) and Machine Learning (ML) or Deep Learning (DL) techniques, without operational implementation and/or analysis of their impact on the specific biological application under investigation;

results from non-validated models, primarily based on assumptions;

work where the novelty is centred on property testing of products being processed using standard techniques;

calibration and verification results using well-known approaches for a specific application.