Periods of unfavorable storing conditions can lead to changes in the quality of fish feeds, as well as the development of relevant mycotoxins. In the present study, a commercial fish feed was stored under defined conditions for four weeks. The main findings indicate that even storing fish feeds under unsuitable conditions for a short duration leads to a deterioration in quality. Mycotoxin and fungal contamination were subsequently analyzed. These investigations confirmed that different storage conditions can influence the presence of fungi and mycotoxins on fish feed. Notably, ochratoxin A (OTA) was found in samples after warm (25 °C) and humid (>60% relative humidity) treatment. This confirms the importance of this compound as a typical contaminant of fish feed and reveals how fast this mycotoxin can be formed in fish feed during storage.
Planning and development decisions in both the government and business sectors often require small area population forecasts. Unfortunately, current methods often produce forecasts that are inaccurate, particularly for remote areas and those with smaller populations. Such inaccuracy necessitates the development and evaluation of methods to forecast and communicate forecast uncertainty, however, little research has been conducted in this domain for small area populations. In this paper, we evaluate a set of probabilistic forecasting methods which include Autoregressive integrated moving average, Exponential Smoothing, THETA, LightGBM and XGBOOST, to produce point forecasts and 80% prediction intervals for Australian SA2 small area populations. We also investigate methods to combine the intervals to produce ensemble forecasts. Our results show that individual probabilistic methods generally produce prediction intervals which underestimate forecast uncertainty. Combining forecasts improves the overall accuracy of point forecasts and the coverage of their intervals, however, coverage still tends to be less than the expected 80% for all but the most conservative combination method.
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