Dear Colleagues,

Here we are!

I would like to invite you in the 13^th International Conference of Predictive Modelling in Food!

The motivation. 

Over the last decades, Predictive Modelling society has contributed significantly to the better understanding of Food Science. As “everything flows” ("τα πάντα ρεί…”, acc. to Heraclitus), the preparedness and resilience of Food Supply Chain is probably the ultimate prerequisite for the agri-food industry in response to

(i)                  the current state of tremendous technological progress, where consumers’ lifestyles and preferences are in a constant state of flux

(ii)                 the emerging issue of climate change and 

(iii)                OneHealth needs.

Food chain transparency and trust are drivers for food integrity control and for improvements in interventions’ efficiency and economic growth. Similarly, the circular economy has great potential to reduce wastage and improve the efficiency of operations in multi-stakeholder ecosystems.

Throughout the supply chain, food commodities are exposed to multiple hazards, resulting in a variable likelihood of contamination.  Such biological or chemical hazards may be naturally present at any stage of food production, whether accidentally introduced or fraudulently imposed, threatening consumers’ health and compromising the trust of society to the food industry.  

Expressing food safety and quality in quantitative terms via Predictive Modeling tools enabled assessment of compliance with standards, making of timely, risk-based decisions, cost-effective targeted recalls, and implementation of safety/quality-by-design, standardized processes. Predictive Modeling has also been the cornerstone of the transition from hazard to risk-based thinking.

Nowadays, a massive amount of data is generated across the food supply chain, not only from the next generation of food safety monitoring systems but also from Internet-of-things, advances in omics era, media, non-destructive sensors and hyper-automated analytical equipment. These data should be used for the benefit of society, and data science should be a vital player in helping to make come true. To convert laboratory data and multi-channel data (from various streams) into new insights, knowledge and ultimately, wisdom!

These new approaches must meet market demands and business operators’ (producers, retailers, resellers) and regulators’, needs i.e., develop, and apply structured quality and safety assurance systems based on thorough risk analysis and prevention, through monitoring, recording, and controlling of critical parameters covering the entire product’s life cycle. However, the production, supply, and processing sectors of the food chain are fragmented and this lack of cohesion results in a failure to adopt new and innovative technologies, products, and processes.

The potential of using information technologies (e.g., data storage, communication, and cloud platforms) in tandem with data science (e.g., data mining, pattern recognition, uncertainty modelling, artificial intelligence, deep learning etc), throughout the food supply chain, including processing, retailers and consumers, will provide stakeholders with novel tools regarding the implementation of a more efficient food safety management.

The shift from Middle Age to Enlightment was triggered by philosophy and vision, forecasting that certain changes in people’s mindset would bring a desirable cultural change. Six hundred years later, AI enables pattern recognition and mining of underlying trends out of theoretically unrelated data, or unexplained trends, with a capacity/speed at multitudes higher than human brain. As such, scientists need to harness the power they granted to the machines, for the benefit of humanity and for reducing the burden from climate changes and other contemporary global threats.

Bearing in mind the above, we believe that since the transformation of the unstructured body of modellers to a solid, strong, sustainable and life-learning scientific society has been achieved, it is time to meet another challenge quoted by Darvin “neither the smartest nor the strongest, but the most adaptable is the one who survives” and indirectly, it should be adopted in our case.

Thus, the vision of this international conference is to allow our scientific society to refresh, re-establish (or re-assess) the drivers of Predictive modelling in Food for the next 30 years, deploying “stochastic approaches”, not with the sensu stricto mathematician terminology (random) but with its authentic Greek interpretation (i.e., I am pondering—try to guess).

To achieve this, emerging cutting-edge disciplines should be encouraged to contribute and join forces, with us, to empower our efforts for food safety and quality, which all of us are willing to serve.

The President of the Organizing Committee, 

George - John NYCHAS BSc, PhD & DSc 

Distinguished Professor at Shandong Agricultural University, Tai’an,China 

Emeritus Professor at Agricultural University of Athens, Greece