Next Article in Journal
A Paper-Based Electrochromic Array for Visualized Electrochemical Sensing
Previous Article in Journal
Classification of Multiple Chinese Liquors by Means of a QCM-based E-Nose and MDS-SVM Classifier
Open AccessArticle

Non-Destructive Sensor-Based Prediction of Maturity and Optimum Harvest Date of Sweet Cherry Fruit

1
INRES-Horticultural Science, Faculty of Agriculture, University of Bonn, D-53121 Bonn, Germany
2
Department of Applied Science, Bonn-Rhein-Sieg University, D-53359 Rheinbach, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Sensors 2017, 17(2), 277; https://doi.org/10.3390/s17020277
Received: 18 November 2016 / Revised: 20 January 2017 / Accepted: 23 January 2017 / Published: 31 January 2017
(This article belongs to the Section Physical Sensors)
(1) Background: The aim of the study was to use innovative sensor technology for non-destructive determination and prediction of optimum harvest date (OHD), using sweet cherry as a model fruit, based on different ripening parameters. (2) Methods: Two cherry varieties in two growing systems viz. field and polytunnel in two years were employed. The fruit quality parameters such as fruit weight and size proved unsuitable to detect OHD alone due to their dependence on crop load, climatic conditions, cultural practices, and season. Coloration during cherry ripening was characterized by a complete decline of green chlorophyll and saturation of the red anthocyanins, and was measured with a portable sensor viz. spectrometer 3–4 weeks before expected harvest until 2 weeks after harvest. (3) Results: Expressed as green NDVI (normalized differential vegetation index) and red NAI (normalized anthocyanin index) values, NAI increased from −0.5 (unripe) to +0.7 to +0.8 in mature fruit and remained at this saturation level with overripe fruits, irrespective of variety, treatment, and year. A model was developed to predict the OHD, which coincided with when NDVI reached and exceeded zero and the first derivative of NAI asymptotically approached zero. (4) Conclusion: The use of this sensor technology appears suitable for several cherry varieties and growing systems to predict the optimum harvest date. View Full-Text
Keywords: Sweet cherry (Prunus avium L.); bio-innovation; harvest prediction; maturity index; modeling; NAI; NDVI; nondestructive examination Sweet cherry (Prunus avium L.); bio-innovation; harvest prediction; maturity index; modeling; NAI; NDVI; nondestructive examination
Show Figures

Figure 1

MDPI and ACS Style

Overbeck, V.; Schmitz, M.; Blanke, M. Non-Destructive Sensor-Based Prediction of Maturity and Optimum Harvest Date of Sweet Cherry Fruit. Sensors 2017, 17, 277.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop