Effect of Interacting Abiotic Storage Conditions on Respiration,Dry Matter Losses and Aflatoxin B_(1) Contamination of Stored Turkey’s Shelled Hazelnuts

Hazelnuts are an economically important nut which is consumed world-wide.It is prone to infection by Aspergillus flavus and contamination with aflatoxins.Taking Tukey’s hazelnuts as a research object,the objective of this study were to(a)quantify respiration rates and(b)dry matter losses(DMLs)and(c)aflatoxin B_(1)(AFB_(1))contamination of naturally stored shelled hazelnuts at different temperatures and water availabilities.Subsequently,shelled hazelnuts were inoculated with additional A.flavus inoculum prior to storage to examine effects on dry matter losses and on AFB_(1) contamination.Maximum respiration of hazelnuts and associated mycoflora was under wetter conditions of 0.90~0.95 water activity(aw=12.5%~18%moisture content).This resulted in between approx.10%DML at 25 and 30℃after 5 days storage.Inoculation and storage of shelled hazelnuts+A.flavus inoculum resulted in similar patterns of respiration with optimal levels at 25~30℃and>0.90 aw.Indeed,AFB_(1) contamination was highest at the maximum water levels tested of 0.90 aw.Indeed the contamination level exceeded the legislative limits set by the EU for AFB_(1) contamination of these nuts.Correlation between DMLs and all the AFB_(1) data in both sets of studies showed that very small changes in DML due to poor drying or storage of≥0.6%resulted in AFB_(1) contamination levels exceeding the EU legislative limits.Thus,efficient drying and safe monitored storage is necessary to minimise the risk of AFB_(1) contamination in this economically important commodity and to avoid exposure of consumers to such toxins.

Improved method for prediction of milled rice moisture content based on Weibull distribution

The loss on drying method,which is regarded as the standard method of rice moisture content analysis,provides the most reliable results but is both labor intensive and time consuming.In order to improve the detection efficiency of the loss on drying method,this study investigated the drying characteristics of milled rice and developed an information fusion algorithm with which to predict milled rice moisture content based on the Weibull distribution and Levenberg-Marquardt(LM)algorithm.Application of the Weibull distribution model was investigated regarding its description of the drying kinetics of milled rice during infrared drying.An adaptive mechanism was applied to algorithm design,with the starting point of the estimation algorithm determined by calculating the drying rate at each measuring point,and the end-point distinguished using a two-level threshold algorithm.The calculated results were then compared with the measured data regarding the infrared drying of milled rice.For milled rice samples varying in moisture content from 14.44%-17.67%(dry basis),the relative error between predicted and observed values ranged 0.0037-0.0589,with a reduction in test time of 50.71%-67.87%.