In most African countries, there is need for revitalizing HEIs to deliver agricultural science curricula that will produce graduates with requisite skills for employment, job creation and agricultural development. AgriENGAGE aims at strengthening HEIs to provide excellent training programmes in agricultural sciences responsive to evolving labour market demands of stimulating agricultural transformation and enhanced agricultural sector competitiveness. The specific objectives of the project are: availability of updated agripreneurial and Community Engagement Training programmes at HEIs; enhanced teaching compentences in business development services and community engagement in HEIs’ academic staff; students skilled in demand driven agripreneurship, agribusiness development services and community engagement and enhanced collaboration between HEIs and industry. The project is envisioned to upscale the hands on approach to agricultural science teaching by skilling staff and students through reviewing existing curricula and developing modules in agripreneurship and community engagement, training staff and students in community engagement and agribusiness development services and working with farmers and industry. Moreover the project will conduct agribusiness clinics, farm attachment, entrepreneurship and community engagement challenges to build the skills of students in entreprenurship and community engagement. This will enhance academic staff pedagogical skills to deliver curricula for agripreneurship and Community engagement, strengthen students’ skills in agripreneurship, business development services and community engagement as well as enhance collaboration between HEIs institutions, farming community and industry. The target groups in AgriENGAGE are students, academic staff and the higher education institutions. Indirect target groups like farmers and employers will benefit through ability of graduates to work with farmers and industry to transform smallholder en

Although they have the potential to improve the economic and environmental sustainability of biorefineries, oxidative enzymes have not experienced a complete breakthrough yet in the biobased industries. This is mainly caused by the high cost and long time associated with traditional enzyme engineering methods such as directed evolution. SMARTBOX will develop an advanced computational engineering platform specifically for oxidative enzymes, which can automatically screen for improved enzyme variants with minimal human intervention. This is achieved by implementing several innovations into current computational screening methods, most importantly machine learning, which allows to train the algorithms with experimental results. As this significantly improves computational predictability, the time and costs associated with oxidative enzyme engineering will be reduced 10-fold compared to state-of-the-art (SOTA) directed evolution methods. Relying on the advanced engineering platform, SMARTBOX will develop the one-enzyme conversion of HMF into FDCA and intermediates, and the one-enzyme conversion of lignin monomers into a potential biobased building block for polycarbonates and vanillin. By adopting a 1-enzyme FDCA production process, the associated production costs and carbon footprint are expected to decrease significantly compared to SOTA chemical oxidation methods. The unique feature of SMARTBOX is that reductive catalytic fractionation (RCF) will be used to selectively produce specific lignin monomers from biomass in near theoretical yields. The structural similarity of the resulting monomers with the SMARTBOX building blocks allows the development of high-yielding processes with only one enzyme. Due to the smart combination between oxidative biocatalysis and RCF, the production of bio-aromatics will proceed with higher yields than the state of the art.