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.
INRES-Horticultural Science, Faculty of Agriculture, University of Bonn, D-53121 Bonn, Germany. v.overbeck@gmx.de.
Verena
V
Overbeck
Department of Applied Science, Bonn-Rhein-Sieg University, D-53359 Rheinbach, Germany. Michaela.Schmitz@h-brs.de.
Michaela
M
Schmitz
INRES-Horticultural Science, Faculty of Agriculture, University of Bonn, D-53121 Bonn, Germany. mmblanke@uni-bonn.de.
Michael
M
Blanke
D000872:Anthocyanins; D003116:Color; D005638:Fruit; D000068220:Prunus avium
D000872:Anthocyanins
NAI; NDVI; Sweet cherry (Prunus avium L.); bio-innovation; harvest prediction; maturity index; modeling; nondestructive examination