Focal commodity scenario analysis

There are different methods for modifying the (background) concentration data for specific (prospective) focal commodity scenario analyses. In the front end, these focal commodity scenario analysis method are accessible through the option Include focal commodity concentrations, (see Figure 58). Checking this option will open the focal commodity scenario analysis form (see Figure 56) where the method and the focal commodity food/substance can be selected, and associated other settings can be configured, see also focal food concentrations.

Replace samples with focal commodity samples

This method will replace all samples for the selected focal commodity food by samples from the focal commodity concentration data. Food sample replacement is substance independent, therefore all substance concentrations of the focal commodity food in the background concentration data are replaced.

Append focal commodity samples

This method adds the focal commodity samples of the selected focal commodity food to the background concentration data. This method is independent of the substance and may be a useful approach when the substances measured in the field trial do not overlap with the substances of the (background) concentration data. In this case, the focal commodity substance concentrations will be missing for the background concentration data and (also the other way around) the substance concentrations of all other substances will be considered missing for the focal commodity samples. These missing values may be imputed at a later stage according to the standard procedures.

Replace measurements of focal food/substance combinations with measurements from focal commodity samples

Replace for the selected (focal) combination of food and substance, all substance concentrations with focal concentration samples.

Replace by focal commodity samples: The focal food/substance measurements are obtained from focal commodity samples. Here, substance measurements of the focal commodity food in the background concentration data are replaced by randomly assigned substance measurements of the focal commodity samples.

Replace measurements of focal food/substance combinations with proposed concentration limit value from data

Replace for the selected (focal) combination of food and substance, all substance concentrations with proposed focal concentration limits from data.

Replace by concentration limits from data: The focal food/substance measurements are obtained from focal commodity samples. Here, substance measurements of the focal commodity food in the background concentration data are replaced by the concentration limit value (e.g., MRL s) obtained from the provided concentration limits data.

Replace measurements of focal food/substance combinations with proposed concentration limit value

Replace for the selected (focal) combination of food and substance, all substance concentrations with proposed focal concentration limits.

Replace by proposed concentration limits:. Here, substance measurements of the focal commodity food in the background concentration data set are replaced by the proposed concentration limit values (e.g., MRLs in mg/kg) specified in the interface.

For all three approaches above:

Use the focal commodity substance occurrence percentage to specify an occurrence percentage for the combination of focal food and substance. For percentages less than 100%, a part of concentrations of the focal commodity food and substance is replaced with the focal concentrations, the remaining part of the concentrations is replaced with zero concentrations. E.g., when background concentrations of the substance Abamectine on oranges are replaced with an MRL value, then a specified occurrence percentage of 40% will replace 40% of the measurements with the MRL, and 60% of the measurements with a zero concentration. Note that the replacement is random, i.e., each substance measurement has a probability of being assigned to a focal concentration (> 0) or a zero. So, the actual replacement percentage may differ from the specified percentage. This option is, for example, used to simulate a percentage of agricultural use.

Use the adjustment factor for the focal food/substance concentration to adjust the (positive) concentrations of the focal food and substance measurements. This factor is used when the focal commodity concentrations (e.g., from field trials) are assumed to be higher than what is expected in practice. In this case, this factor could be set for instance, to the expected ratio of mean monitoring concentration and mean field trial concentration. Note that for replacement by focal commodity measurements, this factor will only adjust the positive concentrations and not the LORs.

By default, the focal commodity substance measurements are replaced before the optional step of converting the concentrations from measured to active substance concentrations. This means that for replaced measurements, the conversion rules apply, and the these measurements may be converted to active substance measurements. Alternatively, substance measurements are replaced after allocation of the active substance. Then deterministic substance conversions factors are used for the focal commodity food and substance to convert measurements to the level of active substances.

When the occurrence data includes samples for processed derivatives of the selected focal food(s) (e.g., orange juice samples for focal food oranges), the substance measurements of the focal substance for the samples of the processed food can also be replaced. Checking the option include processed derivatives of the focal food replaces focal substance measurements of the processed derivatives of the focal food. If there is a specific processing factor available for the focal food, focal substance, and processing type of the derivative, then this processing factor is used to first correct the focal concentrations for processing.

Note that when also using using substance authorisations, the focal food and substance combination will be treated as authorised, even if there is no authorisation supplied for the combination. The approved authorisation status is considered to be part of this scenario analysis.

Remove measurements of focal food/substance combinations

Simply remove all background concentrations for the selected focal commodity food and substance combination, values are not replaced. This method is useful when a separate analysis is desired for the background and foreground concentrations.

Option Use deterministic substance conversions for focal commodity

TODO. See module Deterministic substance conversion factors

Option Filter processed focal food commodity samples

This option is used to exclude concentration data at the level of raw primary commodity (RPC) derivatives (processed RPC) for the focal food. In this case for focal food P0110020A (oranges) all samples for the processed RPC P0110020A#F28.A07LN (Oranges - PROCESS-Juicing) are filtered out. Note that the regular food conversion scheme is followed. Because concentrations for orange juice are excluded, concentrations found on P0110020A will be used in the exposure assessment. When processing factors for juicing are missing, then exposure can be substantial using this option.