Effects of dietary exposure to plant toxins on bioaccumulation, survival, and growth of black soldier fly (Hermetia illucens) larvae and lesser mealworm (Alphitobius diaperinus).

In their natural habitat, insects may bioaccumulate toxins from plants for defence against predators. When insects are accidently raised on feed that is contaminated with toxins from co-harvested herbs, this may pose a health risk when used for human or animal consumption. Plant toxins of particular relevance are the pyrrolizidine alkaloids (PAs), which are genotoxic carcinogens produced by a wide variety of plant species and the tropane alkaloids (TAs) which are produced by a number of Solanaceae species. This study aimed to investigate the transfer of these plant toxins from substrates to black soldier fly larvae (BSFL) and lesser mealworm (LMW). PAs and the TAs atropine and scopolamine were added to insect substrate simulating the presence of different PA- or TA-containing herbs, and BSFL and LMW were grown on these substrates. Bioaccumulation from substrate to insects varied widely among the different plant toxins. Highest bioaccumulation was observed for the PAs europine, rinderine and echinatine. For most PAs and for atropine and scopolamine, bioaccumulation was very low. In the substrate, PA N-oxides were quickly converted to the corresponding tertiary amines. More research is needed to verify the findings of this study at larger scale, and to determine the potential role of the insect and/or substrate microbiome in metabolizing these toxins.

Predicting the performance of handheld near-infrared photonic sensors from a master benchtop device.

Many industries see a shifting focus towards performing on-site analysis using handheld spectroscopic devices. A determining factor for decision-making on the commissioning of these devices is available information on the potential performance of the device for specific applications. By now, myriad handheld solutions with very different specifications and pricing are available on the market. Although specifications are generally available for new devices, this does not directly quantify or predict how available devices will perform for targeted cases. We present a novel chemometric method to estimate the prediction performance of handheld NIR hardware and apply it to estimate the performance of two commercially available handheld NIR technologies in predicting protein content (ranging 120-180 g kg-1) in pig feed from existing data of a benchtop device. Adjusting benchtop data to the wavelength range and resolution of the handheld device lead to over-optimistic estimates of the handheld performances. Our method additionally utilizes information on the error structure of the handheld devices for the estimation. It yielded performance estimates differing less than 1 g kg-1 from the experimentally determined handheld performances and similar model parameters. Our method was effective for linear and nonlinear calibration algorithms, also when estimating performance after averaging multiple scans. Replicate spectra of twenty samples recorded using the handheld were required for replication error estimation to obtain an accurate performance estimation. The error structure could be reported by manufacturers in the future for this approach to be universally employed for predictive quantitative technology assessment. Overall, our method provides estimates of the performance of a handheld device for a specific task with minimal testing required and can thus be used as a device or application screening tool before committing to develop calibrations.