4. Discussion
Performing a study such as this requires a number of assumptions to be made, creating a number of uncertainties that could have major impacts on the results. The results presented here should therefore be interpreted with caution and more investigations, including practical studies, are needed to fully determine the consequences of reduced storage temperature. However, in comparison with previous studies, the present study advanced knowledge by using actual long-term waste data, instead of interview data, as the basis for calculations. The assumptions made in the analysis were tested in a sensitivity analysis. The first group of assumptions concerned the model used for predicting food waste at different shelf life durations, with a specific minimum order size and turnover. The design of the model included assumptions, e.g. that a product will react in the same way as other products with longer shelf life as the shelf life increases. This is a reasonable assumption, even though other causes might interfere with this prediction in reality. The model was also based on a sub-set of the products investigated, since data on all parameters were not available for all products, which potentially introduced a bias. The adjusted R2value was only 0.666, which means that the model is far from a perfect description of reality, but it is still significantly better than that presented by Eriksson et al.(2014). Finding a model that exactly describes this complex reality was not possible within this study and might not be possible at all. Calculation of prolonged shelf life was based on the assumption that producers will actually use the full potential to prolong the shelf life if given the opportunity. They may not do so, since they could be afraid of longer shelf life being interpreted as less fresh by customers (Jensen et al., 2013). Moreover, even if the shelf life were extended, the extra time might not be available tosupermarkets, since the logistics chain has a tendency to use more time when time is available (Lindbom et al., 2014). However, we assumed that the logistics chain always uses the full third of the shelf life that is available to it. The calculations on shelf life were also based mainly on a few studies performed in laboratory environments, which might not reflect the wide range of products with the many possible combinations of preserving techniques, packing, raw materials and preparation conditions that potentially make all products unique and not corresponding to the simplifications used in this study. However, a study on shelf life in the Nordic countries by Møller et al. (2014) allowed some
4. สนทนาPerforming a study such as this requires a number of assumptions to be made, creating a number of uncertainties that could have major impacts on the results. The results presented here should therefore be interpreted with caution and more investigations, including practical studies, are needed to fully determine the consequences of reduced storage temperature. However, in comparison with previous studies, the present study advanced knowledge by using actual long-term waste data, instead of interview data, as the basis for calculations. The assumptions made in the analysis were tested in a sensitivity analysis. The first group of assumptions concerned the model used for predicting food waste at different shelf life durations, with a specific minimum order size and turnover. The design of the model included assumptions, e.g. that a product will react in the same way as other products with longer shelf life as the shelf life increases. This is a reasonable assumption, even though other causes might interfere with this prediction in reality. The model was also based on a sub-set of the products investigated, since data on all parameters were not available for all products, which potentially introduced a bias. The adjusted R2value was only 0.666, which means that the model is far from a perfect description of reality, but it is still significantly better than that presented by Eriksson et al.(2014). Finding a model that exactly describes this complex reality was not possible within this study and might not be possible at all. Calculation of prolonged shelf life was based on the assumption that producers will actually use the full potential to prolong the shelf life if given the opportunity. They may not do so, since they could be afraid of longer shelf life being interpreted as less fresh by customers (Jensen et al., 2013). Moreover, even if the shelf life were extended, the extra time might not be available tosupermarkets, since the logistics chain has a tendency to use more time when time is available (Lindbom et al., 2014). However, we assumed that the logistics chain always uses the full third of the shelf life that is available to it. The calculations on shelf life were also based mainly on a few studies performed in laboratory environments, which might not reflect the wide range of products with the many possible combinations of preserving techniques, packing, raw materials and preparation conditions that potentially make all products unique and not corresponding to the simplifications used in this study. However, a study on shelf life in the Nordic countries by Møller et al. (2014) allowed some
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