Inferring ethylene temporal and spatial distribution in an apple orchard (Malus domestica Borkh): a pilot study for optimal sampling with a gas sensor

Abstract

AbstractApples emit a volatile organic compounds during the ripening process named ethylene, which can be used to infer the optimal harvest time. Currently, the fruit ethylene emission is assessed in controlled facilities, thus laborious and expensive. This article pioneers the study of assessing ethylene emissions in uncontrolled environments. However, understanding how the ethylene spatial temporal dynamics in an open field, its still elusive. Therefore, this paper provides a model from an (Malus domestica Borkh) apple orchard for simulation and analysis of ethylene behaviour. We demonstrate that the model is able to explain the ethylene emissions behaviour in an orchard field when subject to different wind speeds, directions and ripeness stages. Based on that we have investigated different sampling schemes—regular and random—for capturing the variability of ethylene in an orchard using an electrochemical gas sensor. These results show that a random sampling scheme performs 25% better than an equivalent regular-defined grid. Moreover, the measurements acquired locally in the rows tend to be 10% more reliable than in other locations from the orchard. Finally, the ethylene variability can be assessed with a confidence of 75% using 4 and 16 sampling points.