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Automated Modelling of Physiological Processes During Postharvest Distribution of Agricultural Products

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Abstract

In this paper, we present an approach to automated modelling of physiological processes occurring during postharvest distribution of agricultural products. The approach involves reasoning about the reuse of both qualitative and mathematical models for physiological processes, and constructs quantitative simulation models for the postharvest behaviour of agricultural products. The qualitative models are used to bridge the gap between the modeller's knowledge about the physiological phenomenon and the mathematical models. The qualitative models are represented by knowledge graphs, that are conceptual graphs containing only causal relations, aggregation relations, and generalisation relations between domain quantities. The relationships between the mathematical models and the qualitative models are explicitly represented in application frames.

The automated modelling task consists of two subtasks. In the first subtask, Qualitative Process Analysis, a process structure graph is constructed using the qualitative models as building blocks. The process structure graph is a qualitative description of the phenomenon under study, that contains the processes that are responsible for the behaviour of the phenomenon. The process structure graph serves as a focus for the second subtask, Simulation Model Construction. This subtask uses a library of mathematical models to compose a quantitative simulation model that corresponds to the process structure graph constructed in the first subtask. The approach is illustrated with the construction of a model for the occurrence of chilling injury in bell peppers.

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  1. Artificial Intelligence Group, Vrije Universiteit, Amsterdam and Agrotechological Research Institute (ATO-DLO), Wageningen, The Netherlands

    M. Sloof

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  1. M. Sloof
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Sloof, M. Automated Modelling of Physiological Processes During Postharvest Distribution of Agricultural Products. Artificial Intelligence Review 12, 39–70 (1998). https://doi.org/10.1023/A:1006588305364

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