Applying AI and machine learning algorithms to improve various aspects of the food industry. There are many ideas, but not much experience of how efficient AI really is and what really works. Many applications are not yet AI even though called AI. But the potential of machine learning is very high. (Strong) artificial intelligence generally refers to the

computer-aided reproduction of human intelligence. The goal is an autonomous computer system that can work independently on abstract, non-trivial problems under changing boundary conditions. Artificial intelligence has (self-) learning abilities. However, the term is not clearly defined, so the imitation of intelligent behaviour by programmed algorithms is also referred to as (weak) artificial intelligence. With this weak AI, however, the function of machine learning is clearly limited. Artificial intelligence has an impact on products, production environments and socio-economic systems.

Sources: "https://www.hindawi.com/journals/jfq/2022/8521236/; Van de Velde et al. (2023)/ EISMEA Report: Monitoring the twin transition of industrial ecosystems. AGRI-FOOD. Analytical Report (doi not yet available); Project DAKIS: https://www.bundesregierung.de/breg-de/aktuelles/agrarsysteme-der-zukunft-2194584; https://www.isi.fraunhofer.de/de/competence-center/foresight/projekte/dakis.html#9; 50-trends-influencing-Europes-food-sector.pdf (fraunhofer.de); https://www.sciencedirect.com/science/article/pi/

Utilising blockchain technology for secure, transparent, and decentralised management of the food supply chain is an expectation. There are critical views, questioning if blockchain is well-suited to solve these problems.

Sources: https://thecorrespondent.com/655/blockchain-the-amazing-solution-for-almost-nothing/86649455475-f933fe63; https://www.scnsoft.com/blockchain/food-supply-chain; Van de Velde et al. (2023)/ EISMEA Report: Monitoring the twin transition of industrial ecosystems. AGRI-FOOD. Analytical Report (doi not yet available); https://thecorrespondent.com/655/blockchain-the-amazing-solution-for-almost-nothing/86649455475-f933fe63; https://www.mdpi.com/2305-6290/4/4/27

Incorporating robots and automation to streamline and enhance food production and processing. This is a large field of applied sciences and many countries meanwhile have action plans and strategies for robotics in agriculture and industrial food production.

Sources:

https://www.dlg.org/fileadmin/downloads/lebensmittel/themen/publikationen/expertenwissen/lebensmitteltechnologie/e_2015_1_Expertenwissen_Robots.pdf;

https://doi.org/10.1038/s44222-023-00126-5; https://www.extrica.com/article/23209

Using advanced sensory technology to analyse and enhance flavour profiles in food products.

https://www.frontiersin.org/articles/10.3389/fpsyg.2018.00026/full

Leveraging data analytics and predictive modelling for informed decision making in the food industry.

Source: https://www.dataversity.net/the-impact-of-predictive-analytics-on-the-global-food-system

There is already a wide range of meat substitutes and synthetically produced foods. In the future, alternatively produced foods may be used to feed humans, like cultured meat and fish, vertical farming, insects, micro-algae, etc. But there are many pro's and cons. If it is possible to produce meat without killing animals, this is often seen as a huge advantage. It still needs a lot of experiments and research to do this on a large scale. Lab-grown meat in masses will have a huge impact on animal production and agriculture in general - if successful. But it does not only have advantages, there are many different points to consider.

Sources: FOSTER topic modelling: many sources from the automatic scanning with details in new foods; https://www.efsa.europa.eu/en/events/efsas-scientific-colloquium-27-cell-culture-derived-foods-and-food-ingredients; https://doi.org/10.1038/s44222-023-00137-2; https://doi.org/10.1038/s44222-023-00075-z; https://jk-lund.medium.com/the-promise-and-peril-of-artificial-meat-f07096686c64; https://www.ox.ac.uk/news/2011-06-21-lab-grown-meat-would-cut-emissions-and-save-energy; https://doi.org/10.1038/s44222-023-00076-y; https://doi.org/10.1038/s44222-023-00115-8;https://doi.org/10.1038/s44222-023-00112-x; https://doi.org/10.1038/s44222-023-00077-x

Intensive agriculture, which makes extensive use of agrochemicals, has undoubtedly increased farm commodity output, but the negative impact of these chemicals on soil structure, soil microbiology, water quality, food, fodder and food materials is abundantly obvious. Pesticides and fertiliser nitrates have been identified in ground water in numerous agricultural areas due to chemical leaching. [This type of agriculture also usually increases topsoil erosion]

Sources: http://large.stanford.edu/courses/2015/ph240/verso2/; https://www.degruyter.com/document/doi/10.1515/psr-2022-0174/html; http://large.stanford.edu/courses/2015/ph240/verso2

Vertical farming is an agricultural concept in which production takes place in high-rise buildings (vertically) in order to use urban space for sustainable agriculture. The cultivation of plant and animal products can thus take place directly in cities and saves transport time and costs due to the proximity to the consumer. Critical: beware high energy needs

Sources: https://www.greenforges.com/blog/energy-and-underground-farming; https://www.pflanzenforschung.de/de/pflanzenwissen/lexikon-a-z/vertical-farming-10036#:~:text=Unter%20Vertical%20Farming%20versteht%20man,Raum%20nachhaltig%20landwirtschaftlich%20zu%2 0nutzten.

Smart farming makes it possible to make agriculture more sustainable, efficient and resilient at the same time - so the expectations. Lower costs for sensor technology make investments in smart farming technologies attractive. Using technology to optimise crop production and reduce resource waste increases productivity and reduces manual work. AI enables precision farming techniques that utilise real-time data, satellite imagery, and sensors to optimise crop

management. Machine learning algorithms analyse data from weather patterns, soil conditions, and crop health to provide insights on optimal planting times, fertiliser application, irrigation schedules, and pest control. Precision farming minimises resource waste, enhances crop productivity, and reduces environmental impact.

Sources: https://www.iks.fraunhofer.de/de/themen/smart-farming.html; https://www.mdpi.com/2077-0472/13/8/1593; https://link.springer.com/article/10.1007/s10462-022-10266-6https://books.google.de/books?hl=de&lr=&id=hEv9DwAAQBAJ&oi=fnd&pg=PA157&dq=Vertical+farming+and+urban+ agriculture&ots=9LnmKsr29d&sig=osBz1SLxuwaCze03Hey8EcLqIho#v=onepage&q=Vertical%20farming%20and%20urb an%20agriculture&f=false; https://www.tandfonline.com/doi/full/10.1080/14620316.2022.2141666; https://www.researchgate.net/publication/349623902

In precision farming, the combination of the Internet of Things and the blockchain can move us from smart farms only to the internet of smart farms and add more control in supply-chains networks. The result of this combination can lead to more autonomy and intelligence in managing precision agriculture in more efficient and optimised ways.

Sources: https://www.sciencedirect.com/science/article/abs/pii/S0168169919324329; https://www.sciencedirect.com/science/article/pii/S0959652621009823

Agri-food systems consume about 30% of the world’s energy, and a third of agri-food systems' emissions of greenhouse gases stem from energy use. The energy transition to renewable generation will directly affect the food system, and vice versa. The structure of energy consumption in food systems varies significantly between developing and developed countries. Worldwide, energy consumption in agri-food systems increased by more than 20% between 2000 and 2018.

Sources: International Renewable Energy Agency and the Food and Agriculture Organization of the United Nations:

https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2021/Nov/IRENA_FAO_Renewables_Agrifood_2021.pdf;

https://link.springer.com/article/10.1007/s43154-022-00080-x

In the present and future times, when climate extremes are increasing, site-adapted varieties and a wide variety of seeds would be important. Many of the varieties that were common in the past were well suited to the local soil and climate because that is exactly where they developed. To meet the challenge of finding suitable plants for new climatic conditions, mankind needs a rich gene pool of varieties. One danger and constraint for breeders is the increasing patenting of seeds and plants. This has created monopolies for seeds in the past. Although since 2017 the European Patent Office is no longer allowed to grant patents on plants and animals of conventional breeding, this does not apply to breeding based on genetic engineering methods, e.g. CRISPR/CAS. In some cases, attempts are also made to create the impression of a technical and thus patentable invention. The boundaries are fluid.

Sources: Schumacher, Birgit: Saatgut ist Kulturgut, in: Slow Food 03-04-2023, S. 90-93; www.no-atents-on-seeds.org; www.opensourceseeds.org

Related to previous: Genebanks and seed vaults like the Svalbard Global Seed Vault and the Indian Seed Vault provide a safe, cheap access to diversified seed varieties. This offers the possibility to find seeds that adapt to the changing local climates or to develop new improved varieties that do.

Sources:

https://www.croptrust.org/fileadmin/uploads/croptrust/Documents/Technical_reports/Genebank_Platform/Impact-Paper_16Dec2015_ks.pdf

Even though "the widespread use of veterinary antimicrobials drives antimicrobial resistance, with important consequences for animal health, and potentially human health", antimicrobial use (AMU) in food-producing animals is projected to increase at least until 2030. Although the number of countries reporting national AMU data is increasing (particularly within the exporting countries), the majority still do not do it. Such data would enable effective antibiotic stewardship policies.

Source: https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0001305#sec014

Advanced manufacturing and industrial robotics for food processing and preparation may help tackle challenges within the natural or socio-economic environment, as they enable the flexibilisation and automation of food production processes. These are industrial tools which are used for food processing activities, like sorting, handling and packing. They may either work without immediate human presence or alongside human workers with varying degrees of human-robot cooperation. The convergence of technologies is visible here (SFA 2023).

Sources: SFA 2023: https://www.act.nato.int/wp-content/uploads/2024/01/SFA2023_Final.pdf; Van de Velde et al. (2023)/ EISMEA Report: Monitoring the twin transition of industrial ecosystems. AGRI-FOOD. Analytical Report (doi not yet available)

Organizations that are unable to afford high upfront investment and maintenance on physical servers can access enormous amounts of data processing and storage space through cloud computing. The cloud infrastructure serves as the foundation for data collection and analysis for the food supply chain from collections of crops from farms to warehouses where it is stored to the shipping containers to final delivery to the consumer.

Sources: https://ieeexplore.ieee.org/abstract/document/9103523; Van de Velde et al. (2023)/ EISMEA Report:

Monitoring the twin transition of industrial ecosystems. AGRI-FOOD. Analytical Report (doi not yet available)

Increased use of technology in the food industry and its supply chains puts this sector more at risk of cyberattacks and breaches than ever. Cyber attacks are starting to impact the operations and distribution of foodstuff, which is a concerning trend for society.

Sources: https://doi.org/10.1016/j.compind.2022.103702; Van de Velde et al. (2023)/ EISMEA Report: Monitoring the twin transition of industrial ecosystems. AGRI-FOOD. Analytical Report (doi not yet available

Transporting food from farm to fork is a critical element of any supply chain distributed across global markets connected via internet using e-business solutions. The technologies implemented impact the food transportation and the transportation needs (from short distances from retailers to end consumers to long distances between farmers in one country to processors or distributors in another country) impact the technologies needed.

Sources: Van de Velde et al. (2023)/ EISMEA Report: Monitoring the twin transition of industrial ecosystems. AGRI-FOOD. Analytical Report (doi not yet available); https://doi.org/10.1016/j.rtbm.2017.10.002

The Internet of Things (IoT) enables the visualisation of supply chain operational processes, information gathering, and control of business development in real time. In particular, in the food industry it enables to maintain safety standards, limit food waste, manage unpredictable variations, track and monitor the quality of foodstuffs, reduce energy consumption and smart control of refrigerators and ovens.

https://doi.org/10.1016/j.tifs.2023.07.006; Van de Velde et al. (2023)/ EISMEA Report: Monitoring the twin transition of industrial ecosystems. AGRI-FOOD. Analytical Report (doi not yet available)"