Ripening Control via Plant Physiological Model
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for ripening climacteric fruits, such as those described in EP 3 705 888 A2, are complex, require substantial investment in sensors and high-resolution cameras, and have unstable outputs due to self-learning, making it difficult to consistently achieve optimal ripening conditions.
Innovation Solution
A computer-implemented method using a plant physiological model based on ethylene biosynthesis and diffusion to automatically monitor and predict the ripening process of climacteric fruits, allowing for precise control of atmospheric conditions without the need for image analysis or artificial neural networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If artificial neural network models are used to predict optimal ripening conditions, then prediction capability is improved, but system complexity and investment cost increase substantially
Solution Approach 1:
The patent extracts the essential predictive function from complex neural network models and implements it through a simplified physiological model based on ethylene biosynthesis pathways. This extraction maintains the core prediction capability while removing unnecessary complexity, achieving accurate ripening prediction through fundamental biological principles rather than data-intensive machine learning approaches.
Solution Approach 2:
The patent replaces expensive, complex sensor systems and high-resolution cameras with simpler, more affordable sensing approaches. By using basic gas composition sensors to monitor ethylene and other atmospheric parameters, the system achieves effective ripening prediction without substantial investment in sophisticated equipment, making the solution economically viable for widespread adoption.
2Adaptability or versatility
If artificial neural network self-learning is used to adapt to new conditions, then adaptability is improved, but output stability deteriorates
Solution Approach 1:
The patent implements self-adaptation through the natural physiological response of fruits to atmospheric conditions. The physiological model automatically adjusts predictions based on measured gas composition changes, eliminating the need for external retraining or adaptation mechanisms. This self-service approach maintains both adaptability to new conditions and stability of outputs, as the model relies on consistent biological principles rather than fluctuating learned patterns.
3Measurement precision
If high-resolution cameras and image analysis are used to monitor ripening stages, then monitoring precision is improved, but device complexity and investment cost increase
Solution Approach 1:
The patent replaces optical monitoring systems (cameras and image analysis) with gas composition-based sensing. By substituting mechanical/optical measurement methods with chemical sensing approaches, the system achieves accurate ripening stage detection through atmospheric parameter measurement, simplifying the device while maintaining or improving monitoring precision through direct physiological indicators.
4Ease of operation
If conventional operator-based monitoring is used, then operational flexibility is maintained, but productivity and consistency deteriorate
Solution Approach 1:
The patent implements automated feedback control by continuously measuring atmospheric gas composition and using the physiological model to predict ripening progression. This feedback system automatically adjusts monitoring and prediction without operator intervention, significantly improving productivity and consistency while maintaining operational flexibility through programmable parameters and adaptable model configurations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables objective and experience-independent monitoring and control of the ripening process, ensuring fruits reach the desired degree of ripeness at the right time, reducing the risk of over-ripening and improving efficiency with minimal investment in equipment.
Implementation Method 1
The plant physiological model is based on a biosynthetic pathway of ethylene in the fruit and on dilution and diffusion of ethylene through skins of the fruits
Implementation Method 2
The rate at which the fruits ripen depends i.a. on temperature during transport and storage and on the composition of the atmosphere in which the fruits are transported and stored
Data Source
Figure 1
Figure 2~3
Figure 4~6
AI summary
The invention relates to a computer implemented method for ripening climacteric fruits in an enclosure comprising the steps of: a. setting a target for a degree of ripening of the fruits in the enclosure; b. at least periodically analyzing a composition of the atmosphere in the enclosure; c. deriving, by a processor, based on a plant physiological model describing the ripening process in the fruits, an instantaneous degree of ripening of the fruits from the analyzed composition; d. predicting, by the processor, based on the model and the derived degree of ripening, a moment in time when the target will be met; and e. signaling, by the processor, the predicted moment. The invention also relates to a device for ripening climacteric fruits in an enclosure comprising: A. a first setting module for setting a target for a degree of ripening of the fruits in the enclosure; B. a control module connected to the first setting module and including a plant physiological model describing the ripening process and a processor; C. an analyzer module connected to the control module for at least periodically analyzing a composition of the atmosphere in the enclosure; wherein the processor is arranged for: deriving, based on the model, an instantaneous degree of ripening of the fruits from the analyzed composition of the atmosphere; predicting, based on the model and the derived degree of ripening, a moment in time when the target will be met; and signaling the predicted moment.