A low-cost multispectral device for in-field fruit ripening assessment

Abstract

When assessing fruit ripeness, multispectral sensors offer a cheaper alternative to high-resolution spectroscopy. Additionally, they provide a more robust solution to environmental factors, in contrast to multispectral cameras. However, the low spectral resolution of multispectral devices proposed in the literature may not be sufficient to discriminate with acceptable accuracy a high number of different ripeness classes with machine learning techniques. Moreover, meaningful features to be given as input to the classification models are generally hand-crafted on the basis of the fruit to be evaluated, making the devices not versatile across other fruit categories. This paper aims at overcoming these limitations, by introducing a multispectral device for in-situ fruitripening evaluation that is i) affordable for a wide range of end-users, ii) robust to environmental factors, iii) capable of automatically finding the most meaningful features depending on the fruit categories to evaluate and iv) capable of discriminating a high number of fruit ripeness classes with high accuracy. The device integrates a broadband LED and a VIS-NIR multispectral sensor to gather information about the fruit' ripeness levels through predictive machine learning algorithms. The proposed device was trained on a dataset of 450 spectral measurements acquired from tomatoes at six different ripeness stages. The results demonstrated the high capability of the proposed approach to recognize the tomatoes' ripeness levels (average accuracy of 93.72%).

Design and Implementation of a Low-Cost, Linear Robotic Camera System, Targeting Greenhouse Plant Growth Monitoring

“…In a similar fashion, in [38], a small farming CNC machine for irrigation, planting, and fertilizer application in predefined locations is implemented. Moreover, the utilization of hyperspectral imaging sensors, along with the potential adaptation of other low-cost, yet promising multispectral compact designs [39,40] suitable for integration into robotic platforms, can be effectively utilized in agricultural applications to perform repetitive activities such as the plant photography that the present work focus on, but also facilitate other interesting agricultural procedures and applications such as fruit harvesting or even fruit ripening assessments.…”