## 1 Introduction
Consequently, during the development of an NIR application, care should be taken to ensure that the sample presentation is repeatable between measurements as well as reproducible over time [18; 19; 20; 21; 22; 23]. Variations in sample presentation to the instrument can introduce unnecessary variability in the spectra collected [18; 19; 20; 21; 22; 23]. This variability can be one source of error during the development of either quantitative calibrations or classification models [23; 24; 25]. For example, it has been described that in the case of powder samples, presentation has an important effect. In this type of sample, both particle size and sample compaction are two of the main factors affecting NIR spectra. Due to these issues, different sources of variability can be introduced where scatter is considered one of the main factors affecting the quality of the NIR spectrum of a sample [18; 19; 20]. Therefore, evaluating sample presentation before the development of an NIR application or protocol is of importance as evidenced by different studies available in the scientific literature [18; 19; 20]. Recently, the effect of sample presentation (distance from the detector head, angle of scanning, etc.) has been evaluated when portable NIR instruments were used to analyze the composition of different types of samples [5; 23]. The authors of this study concluded that after generalized guidelines for the use of handheld instruments are defined, portable instruments can be utilized by both the food manufacturing industry and consumers [23]. Although sample presentation has been evaluated on the development of a quantitative model or calibrations based on NIR spectroscopy, few studies have evaluated or reported the effects of sample preparation or presentation on the NIR spectra and its ability to classify samples (e.g., geographical origin, variety). The different studies available have reported the effect of sample presentation on the accuracy of NIR spectra used to classify almond samples according to their geographical origin [25], the discrimination of Mediterranean pine nut samples from Chilean ones [26], or the effect of wheat kernel size on the spectra and color classification of kernels [27]. In particular, these authors reported that the wheat kernel size significantly affects the NIR spectra [27]. Black soldier fly larvae (BSFL) (_Hermetia illucens_) have been used commercially as a sustainable feed ingredient for livestock [1,3]. The BSFL is geographically distributed in warmer climates, especially in tropical and subtropical regions [1,3,28,29,30,31,32]. BSFL are saprophagous, feeding in a wide range of organic matter substrates including different food waste sources [1,3]. Previous studies by our group and other research teams have demonstrated the feasibility of NIR spectroscopy to trace the origin of the food waste used to feed the larvae [1,3] and to determine the proximate composition of the larvae [28]. More recently, the ability of hyperspectral NIR to classify and predict the proximate composition of BSFL according to the feed was also reported [29]. However, no studies have been published on the evaluation of the effect of sample presentation on either the NIR spectra or the classification of BSFL sources from different waste streams. 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 the classification models developed to trace the type of food or waste stream (e.g., supermarket and childcare center) used to feed the samples.