The potent hepatotoxin and carcinogen aflatoxin B1 (AFB1) is a common mycotoxin contaminant of grains used in animal feeds. Aflatoxin M1 (AFM1) is the major metabolite of AFB1 in mammals, being partially excreted into milk, and is a possible human carcinogen. The maximum permitted concentration of AFM1 in cows’ milk is 0.05 μg/kg in Israel and the European Union. Since milk yield and the carry-over of AFB1 in the feed to AFM1 in the milk are highly correlated, it was considered important to determine the AFM1 carry-over in Israeli-Holstein dairy cows, distinguished by world record high milk production. Twelve such cows were used to determine AFM1 carry-over following daily oral administration of feed containing ~86 μg AFB1 for 7 days. The mean carry-over rate at steady-state (Days 3–7) was 5.8% and 2.5% in mid-lactation and late-lactation groups, respectively. The carry-over appears to increase exponentially with milk yield and could be described by the equation: carry-over% = 0.5154 e^{0.0521 × milk yield}, with r² = 0.6224. If these data truly reflect the carry-over in the national Israeli dairy herd, the maximum level of AFB1 in feed should not exceed 1.4 μg/kg, a value 3.6 times lower than the maximum residue level currently applied in Israel.

Beehive products such as honey, beeswax and recently pollen have been regarded for many years as appropriate sentinels for environmental pesticide pollutions. However, despite yearly application of hundreds of approved pesticides in agricultural fields, only a minor fraction of these organic compounds were actually detected in honey and beeswax samples. This observation has led us to question the general suitability of beehive products as a sentinel for synthetic organic pesticides applied in the field. The aim of the present study was to experimentally determine the distribution (logarithmic ratio of beeswax to honey pesticide concentration, LogD) and depletion kinetics (half-life) of selected pesticides in honey and beeswax as a measure of the latter matrixes to serve as a pesticide sentinel. The obtained parameters were used to extrapolate to pesticide burden in honey and beeswax samples collected from German and Israeli apiaries. In addition, we aimed to establish a mathematical model, enabling us to predict distribution of selected pesticides between honey to beeswax, by utilizing simple substance descriptors, namely, octanol/water partitioning coefficient, molar weight and Henry coefficient. Based on the present results, it appears that pesticides with LogD values > 1 and half-life in beeswax > 1 day, were likely to accumulate and detected in beeswax samples, and less likely to be found in honey. On the other hand, pesticides with negative LogD values were highly likely to be found in honey and less so in beeswax samples. Finally, pesticides with LogD values between 0–1 were expected to be found in both matrixes. The developed model was successfully applied to predict LogD values, thereby identifying octanol/water partitioning and molar weight as the most prominent substance descriptors, which affect pesticide distribution between honey and beeswax.