Exploring the Analytical Complexities in Insect Powder Analysis Using Miniaturized NIR Spectroscopy

Riu, Jordi; Vega, Alba Edith; Boqué, Ricard; Giussani, Barbara

doi:10.3390/foods11213524

Cited by 11 publications

(4 citation statements)

References 39 publications

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“…Riu and coworkers studied the possibility to classify insect powder by handheld NIR spectrometer. Experimental evidences confirmed this instrumental approach to be a trusted tool of analysis, able to predict macronutrients ( Riu et al, 2022 ).…”

Section: Applications To Food Quality Characterization and Adulterationsmentioning

confidence: 61%

Portable NIR spectroscopy: the route to green analytical chemistry

Gullifa,

Barone,

Papa

et al. 2023

Front. Chem.

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There is a growing interest for cost-effective and nondestructive analytical techniques in both research and application fields. The growing approach by near-infrared spectroscopy (NIRs) pushes to develop handheld devices devoted to be easily applied for in situ determinations. Consequently, portable NIR spectrometers actually result definitively recognized as powerful instruments, able to perform nondestructive, online, or in situ analyses, and useful tools characterized by increasingly smaller size, lower cost, higher robustness, easy-to-use by operator, portable and with ergonomic profile. Chemometrics play a fundamental role to obtain useful and meaningful results from NIR spectra. In this review, portable NIRs applications, published in the period 2019–2022, have been selected to indicate starting references. These publications have been chosen among the many examples of the most recent applications to demonstrate the potential of this analytical approach which, not having the need for extraction processes or any other pre-treatment of the sample under examination, can be considered the “true green analytical chemistry” which allows the analysis where the sample to be characterized is located. In the case of industrial processes or plant or animal samples, it is even possible to follow the variation or evolution of fundamental parameters over time. Publications of specific applications in this field continuously appear in the literature, often in unfamiliar journal or in dedicated special issues. This review aims to give starting references, sometimes not easy to be found.

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Section: Applications To Food Quality Characterization and Adulterationsmentioning

confidence: 61%

Portable NIR spectroscopy: the route to green analytical chemistry

Gullifa,

Barone,

Papa

et al. 2023

Front. Chem.

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“…The effect of the waste stream used to feed the larvae is shown along PC2 (12%), where samples were separated according to the waste stream used to feed the larvae (childcare or supermarket waste). Riu and collaborators (2022) [40] analyzed insect powders with a miniature NIR instrument and highlighted that the spectroscopic signal obtained depends on the physical and chemical characteristics of the powder samples analyzed. These authors stated that using a portable NIR instrument, the classification of insect powders might be possible by including the granulometric characteristics of the samples analyzed [40].…”

Section: Resultsmentioning

confidence: 99%

Effect of Sample Presentation on the Classification of Black Soldier Fly Larvae Using Near-Infrared Spectroscopy

Sanchez,

Alagappan,

Hoffman

et al. 2024

Applied Sciences

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Black soldier fly larvae (BSFL) (Hermetia illucens) reared on food waste streams are considered a sustainable source of protein in feed livestock diets. Recently, portable near-infrared spectroscopy (NIR) instruments have been assessed to monitor the consistency and quality of food waste streams used to feed black soldier fly larvae. During the application of NIR spectroscopy, sample presentation (e.g., drying, processing, particle size) plays an important role in the accuracy of the models developed (quantitative or qualitative analysis). The objective of this study was to evaluate the effect of sample presentation (number of larvae used during the scanning of BSFL) on the accuracy of classification models developed to trace the food waste stream (e.g., supermarket of childcare) used to feed the larvae. BSFL samples were sourced from two waste streams and scanned as half, 1, 2, or 3 larvae using an NIR portable instrument (MicroNIR, Viavi, Milpitas, California, USA). Principal component analysis (PCA) and linear discriminant analysis (LDA) were used to analyze the NIR data and to classify the samples according to the waste stream. The main differences in the NIR spectra of the BSFL samples associated with the number of larvae scanned were observed around 1200 nm, mainly associated with the C-H overtones (lipids). The classification results showed that high classification rates (>93%) were obtained regardless of the number of larvae scanned, ranging from 93% (using 0.5 larvae) to 100% (using 1, 2, or 3 larvae samples). Overall, the number of larvae scanned had minimal to no effect on the accuracy of the LDA classification models. The present study demonstrated that a portable NIR instrument can be suitable for an initial rapid classification or determination of the origin of the waste stream used to feed the BSFL.

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“…The bands around 5968 cm −1 and 6928 cm −1 are also associated with C-H (2υ) vibrations in aromatic groups [ 58 , 60 ]. The highest loadings for the prediction of YMC using the frass samples were observed around 4352 cm −1 and 4784 cm −1 , associated with C-H bending (aromatic groups) and O-H, respectively [ 58 , 59 , 61 ] whilst the band around 6032 cm −1 corresponds with C-H vibrations in the 1st overtone region attributed to lipids [ 59 , 60 ]. The highest loadings used to predict YMC using the larvae samples were observed around the regions 4848 cm −1 , 5088 cm −1 , 5952 cm −1 , and 6800 cm −1 .…”

Section: Resultsmentioning

confidence: 99%

Near Infrared Spectroscopy for Prediction of Yeast and Mould Counts in Black Soldier Fly Larvae, Feed and Frass: A Proof of Concept

Alagappan

Dong

Mikkelsen

et al. 2023

Sensors

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The use of black soldier fly larvae (BSFL) grown on different organic waste streams as a source of feed ingredient is becoming very popular in several regions across the globe. However, information about the easy-to-use methods to monitor the safety of BSFL is a major step limiting the commercialization of this source of protein. This study investigated the ability of near infrared (NIR) spectroscopy combined with chemometrics to predict yeast and mould counts (YMC) in the feed, larvae, and the residual frass. Partial least squares (PLS) regression was employed to predict the YMC in the feed, frass, and BSFL samples analyzed using NIR spectroscopy. The coefficient of determination in cross validation (R2CV) and the standard error in cross validation (SECV) obtained for the prediction of YMC for feed were (R2cv: 0.98 and SECV: 0.20), frass (R2cv: 0.81 and SECV: 0.90), larvae (R2cv: 0.91 and SECV: 0.27), and the combined set (R2cv: 0.74 and SECV: 0.82). However, the standard error of prediction (SEP) was considered moderate (range from 0.45 to 1.03). This study suggested that NIR spectroscopy could be utilized in commercial BSFL production facilities to monitor YMC in the feed and assist in the selection of suitable processing methods and control systems for either feed or larvae quality control.

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Exploring the Analytical Complexities in Insect Powder Analysis Using Miniaturized NIR Spectroscopy

Cited by 11 publications

References 39 publications

Portable NIR spectroscopy: the route to green analytical chemistry

Portable NIR spectroscopy: the route to green analytical chemistry

Effect of Sample Presentation on the Classification of Black Soldier Fly Larvae Using Near-Infrared Spectroscopy

Near Infrared Spectroscopy for Prediction of Yeast and Mould Counts in Black Soldier Fly Larvae, Feed and Frass: A Proof of Concept

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