Tracing the addition of black soldier fly larvae to barley flour using near infrared spectroscopy - Effects of batch and processing treatment
Year: 2025
Type: article
Abstract: This study evaluated the ability of two near infrared (NIR) instruments (e.g. bench top and portable) combined with chemometrics (e.g. PCA and PLS regression) to trace the addition of different levels (0.5% to 20% w/w) of black soldier fly larvae (BSFL) meal into barley flour samples. The effects of batch, BSFL processing treatment (drying and blanching) and the number of replicates on the prediction (SECV - standard error of cross validation) of the level of addition was evaluated. Mixture samples were prepared by combining three batches (B1 to B3), three processing methods (T1 to T3), and replicates (triplicates). The PCA score plot showed a separation between samples according to batch and mixtures (level of addition). The PLS regression models predicted the level of addition of BSFL meal to barley flour with a coefficient of determination in cross-validation (R 2 CV ) ranging from 0.76 to 0.90, depending on the instrument used to collect the spectra. The RPD values ranged from 2 to 6.1 depending on the combination of batch, treatment and instrument used during calibration. The standard error of prediction (SEP) obtained for the prediction of the level of BSFL meal addition was 2.63% using the benchtop or 4.10% using the portable NIR instrument. The study demonstrated that the prediction of the addition of BSFL to barley flour is possible, however, the accuracy of the method will depend on factors such as level of addition of BSFL meal to the barley flour, while batch or processing might have an effect. The development and implementation of rapid analytical methods such as those based on the utilization of NIR spectroscopy, will provide with no-destructive and green tools to the BSFL industry.
Institution: University of Veterinary Sciences Brno
Language: English
Subfield: Analytical Chemistry
Field: Chemistry
Domain: Physical Sciences
SDG: Zero hunger
Open Access status: hybrid
Estimated APC paid: $3,450
Award: G1660165325
OpenAlex ID: W4410351017