A New Method to Quantify Postharvest Quality Loss of Cucumber using the Taguchi Approach

Abstract

One-third of global food produced for human consumption, which amounts to about 1.3 billion tons is lost or wasted annually. A clear pathway to ensure the availability of food and alleviating poverty is to minimize the postharvest losses (PHL). Measuring these losses is an essential operational strategy to enhance postharvest management and to curtail quality loss of fresh horticultural commodities. At the present time, the literature does not offer any methodology for an effective and reliable measurement of postharvest losses of fresh produce. The aim of this study was to use the Taguchi approach to quantify postharvest quality loss of cucumber as affected by environmental factors (temperature, light, humidity) over time. The experimental design included the 4 three-level factors and an L-9 orthogonal array. The Taguchi loss function was used to quantify quality loss of fresh cucumber after each storage combination. The results revealed that fresh cucumber lost some of its quality attributes as early as immediately after harvesting. At firmness of 15.68 N, the loss was equivalent to 13.68 units. However, at 7.68 N firmness, the loss value was increased by almost 4 times (56.98 units). In terms of quality index, it was noticed that even when the score was high (QI = 9 points), the produce had lost 8.74 units of its quality. In theory, the only time when the loss is equal to zero is when the cucumber fruit is still attached to its mother plant. When the quality index dropped to 1.67 points, the loss was increased by almost 30 times more (loss = 254.91 units). The results showed how large the extent of loss could be when fresh cucumber is stored under undesirable conditions. The percent influence of studied factors on each quality attribute was also determined. For the overall quality, 46.5% of loss was due to time, followed by 18% due to temperature and 11.5% due equally to light and humidity. Finally, using a measure of goodness-of-fit of linear regression, Taguchi predictions fitted the observed data. This confirmed the ability of the Taguchi technique to predict postharvest quality loss of fresh produce in response to different combinations of factors and their levels.

Keywords: Cucumber, postharvest, quality management, loss function, Taguchi approach, quantification.