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

  • (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.

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Document Type:Article
Author:Verena Overbeck, Michaela Schmitz, Michael Blanke
Parent Title (English):Sensors
Article Number:277
Place of publication:Basel
Publishing Institution:Hochschule Bonn-Rhein-Sieg
Date of first publication:2017/01/31
Copyright:© 2017 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Keyword:NAI; NDVI; Sweet cherry (Prunus avium L.); bio-innovation; harvest prediction; maturity index; modeling; nondestructive examination
Departments, institutes and facilities:Fachbereich Angewandte Naturwissenschaften
Dewey Decimal Classification (DDC):6 Technik, Medizin, angewandte Wissenschaften / 63 Landwirtschaft / 630 Landwirtschaft und verwandte Bereiche
Entry in this database:2017/02/06
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International