Cereal Chem. 78(5):572-577Three problems need to be addressed in networks of Infratec Grain Analysers: 1) the networks are not interconnected, 2) the partial least squares (PLS) calibrations used so far have to be individually adjusted for bias when transferred to the slave instruments, and 3) the calibrations are not entirely stable over time. Nonlinear artificial neural network (ANN) calibrations based on a large common European data set (≈4,000 samples in the training sets and ≈1,000 samples in the stop sets) were introduced to overcome these constraints. The performance of these ANN calibrations was compared with Danish PLS models for protein and moisture in cereals during the 1998 harvest in Denmark, and subsequently with PLS models based on the same European data set. ANN models were more accurate than PLS and, unlike PLS, were linear and transferable up to 25% moisture. It is suggested that the improved performance of the ANN models is attributable to the modeling technique rather than the size and nature of the European data set. In most cases, ANN models could be applied directly and without bias adjustment to slave instruments. The ANN models were also more stable, they required fewer bias adjustments or remodeling over time compared with Danish PLS models. ANN calibrations using shared data have been adopted for commercial use in several European countries and work is in progress to develop global ANN models for determination of protein in wheat and barley.
The Danish NIR transmission network is used for the determination of protein, moisture and starch in barley and wheat; moisture in rye; oil in rapeseed; and Zeleny in wheat. The network is described briefly. To achieve optimal performance of the field instruments, a standardisation using grain and rapeseed samples has to be conducted at least once a year. The systematic instrument-to-instrument variation is thus virtually eliminated just after standardisation. The random variation between the field instruments and the sub-master is small and not influenced by the standardisation.
In Denmark, porcine kidneys displaying macroscopic lesions of mycotoxic nephropathy are analysed for Ochratoxin A and the carcass condemned if the concentration exceeds 25 micrograms/kg. Since late 1982 these analyses have been conducted centrally. The reliability of the one-dimensional thin layer chromatographic method is discussed and results from an interlaboratory comparison are presented. From 1980 to 1984 there has been an overall decline in the rate of ochratoxicosis, interrupted in 1983 by a major increase geographically located in the northern half of Jutland. During that year 7639 kidneys were examined; 3% contained more than 150 micrograms/kg and 29% more than 25 micrograms/kg Ochratoxin A, corresponding to a condemnation rate of 15 per 100 000 slaughterings. The early stage of the increased incidence was characterized by kidneys with extremely high levels of the toxin; later most of the samples were negative or near-negative, as affected pigs were presumably fed a toxin-free diet before slaughtering. The efficacy of the control program is discussed in view of the 1983 data.
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