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Algorithms 2009, 2(2), 623-637; doi:10.3390/a2020623

Neural Network Modeling to Predict Shelf Life of Greenhouse Lettuce

*  and
Agriculture and Agri-Food Canada, Pacific Agri-Food Research Center, P.O. Box 1000, Agassiz, BC, V0M 1A0, Canada
* Author to whom correspondence should be addressed.
Received: 24 October 2008 / Revised: 7 March 2009 / Accepted: 25 March 2009 / Published: 3 April 2009
(This article belongs to the Special Issue Neural Networks and Sensors)
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Greenhouse-grown butter lettuce (Lactuca sativa L.) can potentially be stored for 21 days at constant 0°C. When storage temperature was increased to 5°C or 10°C, shelf life was shortened to 14 or 10 days, respectively, in our previous observations. Also, commercial shelf life of 7 to 10 days is common, due to postharvest temperature fluctuations. The objective of this study was to establish neural network (NN) models to predict the remaining shelf life (RSL) under fluctuating postharvest temperatures. A box of 12 - 24 lettuce heads constituted a sample unit. The end of the shelf life of each head was determined when it showed initial signs of decay or yellowing. Air temperatures inside a shipping box were recorded. Daily average temperatures in storage and averaged shelf life of each box were used as inputs, and the RSL was modeled as an output. An R2 of 0.57 could be observed when a simple NN structure was employed. Since the "future" (or remaining) storage temperatures were unavailable at the time of making a prediction, a second NN model was introduced to accommodate a range of future temperatures and associated shelf lives. Using such 2-stage NN models, an R2 of 0.61 could be achieved for predicting RSL. This study indicated that NN modeling has potential for cold chain quality control and shelf life prediction.
Keywords: Lactuca sativa; postharvest; storage temperature; neural network (NN); simple NN; 2-stage NN; regression analysis Lactuca sativa; postharvest; storage temperature; neural network (NN); simple NN; 2-stage NN; regression analysis
This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Lin, W.-C.; Block, G.S. Neural Network Modeling to Predict Shelf Life of Greenhouse Lettuce. Algorithms 2009, 2, 623-637.

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