AI summary

70% confidence

The MEC model was evaluated for its ability to predict daily changes in cultivation variables for green and red-leaved lettuce in precision indoor cultivation, and its predictions were found to be reliable compared to experimental measurements.

Generated by MESSAI extraction pipeline · review against source PDF

Generic MECRepresentative model
Click to animate flow
loading 3D model…

Representative MEC — matched on the paper’s system type only, not its reactor or geometry.

Extraction

Reported parameters

No values extracted from this paper yet.

Open in lab for full controls, parameter editing, and template overlays.

Open in lab →

What they did

System
MEC

What worked

No outcome metrics extracted yet.

Abstract

A fundamental objective in precision horticulture is the development of mathematical explanatory models to be implemented in decision support systems for optimal crop management. Such models, designed to predict daily changes in cultivation variables for given boundary conditions, can be exploited to predict the direction and the magnitude of possible changes in crop variables, under both nominal and off-nominal conditions. In this way, control strategies, capable of counteract the negative effects of environmental disturbances on crops, can be promptly applied. In the present study, we evaluated the Modified Energy Cascade (MEC) model with data collected during experiments conducted in growth chambers with green and red-leaved lettuce, under controlled environmental conditions (lighting, temperature, irrigation) and two different vapor pressure deficits. Results showed that the model predictions were reliable compared with experimental measurements, especially for biomass production and photosynthesis. Thus, the MEC model can be a useful tool in decision support systems for crop management in controlled environment.

Keywords

Agricultural engineeringIrrigationCropBiomass (ecology)Precision agriculture

Identifiers

Journal
2019 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)
Year
2019