Modelling and Control strategies using Reliable data for Optimising food Production in greenhouses (CROP)

One of the main problems of current society is food production due to the prospects of global population increase. This implies pressure on natural environments, requiring an increase in the use of water and energy, in addition to hidden environmental effects, such as greenhouse gas emissions. These cumulative problems evidence the need for the use of holistic strategies to address the complex interactions among population growth, climate change, and resource scarcity, which leads to the recognition of the Water-Energy-Carbon-Food (WECF) nexus, identified as a critical challenge that humanity must face for its sustainable development.

Within this framework, greenhouse agriculture presents a series of advantages, allowing the provision of optimal climatic conditions for crop growth, and increasing production yield compared to open-field systems. For an optimal management of greenhouse food production, it is essential to use modeling and control techniques for the variables that affect crop growth, such as climate, irrigation, and nutrient supply. The proper management of these highly increases production and it is possible to increase farmer profitability, maximizing the difference between sales revenue from production and associated costs, evaluating potential risks throughout the crop cycle, and guaranteeing environmental sustainability.

The main objective of this project is the development of modeling, control, and profit optimization strategies for greenhouse food production, seeking a trade-off between production and associated costs, as well as the optimal planning of heterogeneous resources in this type of nexus, in a sustainable and efficient manner in the use of energy and water. The project proposes two lines of work: (1) design and validation of control strategies for the variables that influence crop growth in a more efficient way than those used commercially and, (2) development of an economic profit optimizer, crop harvesting dates, and planner of the resource sources that are necessary to consume in the nexus, considering renewable sources.

In this context, there is an additional essential problem to address related to data quality, as the fundamental support for decision-making in these systems. A large number of anomalous behavior events of sensors and measurement systems occur that severely affect the soundness of the optimization, modeling, and control processes, and formal models must be developed to guarantee reliable data.

The results of this project will represent significant scientific-technical, economic, and social contributions in these systems. This statement is corroborated by the interest awakened in institutions (COEXPHAL and Fundación Cajamar), in addition to other companies interested in the results, expecting these to be applicable in the short term. The proposal is a natural continuation of previous projects, where considerable experience was acquired in the hierarchical control of greenhouse crop growth, with numerous articles published in prestigious journals and relationships with relevant national and international research groups.