Insects represent a sustainable alternative protein source but also provide an appreciable amount of fat, which has usually a high PUFA content [8]. Consequently, the research on the nutritional requirements, metabolism, and transport of nutrients, and especially the utilization and storage of dietary lipids in insects, has become a very important topic [10]. Insects have tremendous plasticity in lipid accumulation and fatty acid profile which is mainly dependent on diet, developmental and larval stage, species, and environmental conditions (e.g., temperature, humidity, etc.) [34,35,36]. In this study, the fat content and FA composition of Tenebrio molitor larvae were analyzed to determine a suitable feeding substrate and to modify the FA content for achieving a healthier larva with a valuable FA composition. FAs perform several important functions in insects by acting as precursors for the synthesis of pheromones, an energy reserve, and an important component for the performance of metamorphosis [37,38]. The main FAs detected in mealworm larvae were, in particular, oleic, linoleic, and palmitic acid and are similar to those reported in previous studies [9,39]. Normally, commercially produced insects consist of a high amount of oleic and linoleic acid due to feeding with grains and grain by-products that are generally high in oleic and linoleic acid [40,41]. This is consistent with the results of this publication, as feeding with wheat bran led to high levels of these FAs. Diet can also change the FA composition of mealworm larvae, especially the content of α-linolenic and oleic acid. However, the FA composition of Tenebrio molitor larvae did not always reflect the diet, indicating that some physiological regulation of lipids in insects may appear [42]. Several insects show an extension pathway similar to that described for vertebrates, but unlike vertebrates, the larvae of Tenebrio molitor can synthesize linoleic and α-linolenic acid de novo, too [43,44]. Insects can also biosynthesize long-chain polyunsaturated FAs, such as eicosapentaenoic acid (EPA, C20:5) and docosahexaenoic acid (DHA, C22:6), from the C18 polyunsaturated FAs in their diet [43,45,46,47]. These two primary n-3 long-chain PUFA were not found in the larvae of T. molitor examined in this study. According to van Broekhoven et al., (2015) [24] and Siemianowska et al., (2013) [48], mealworm larvae that were raised on a substrate with a high protein and low carbohydrate content contained EPA, which was most likely acquired from their diet. However, since an enrichment of EPA and DHA could be achieved in the black soldier fly (Hermetia illucens) by the feeding of fish waste [49], it may also be feasible to accumulate EPA and DHA in Tenebrio molitor by feeding them an appropriate diet. A majority of insects acquire fatty acids through the absorption of dietary lipids in their midgut epithelium or from sugars produced by their enterocytes [50]. A higher inclusion level of flaxseed flour resulted in an increase in the concentrations of stearic and oleic acids, as well as a numerically high increase in the concentration of α-linolenic acid in mealworm larvae. Where the flaxseed flour inclusion amount is higher, these 18-carbon fatty acids might be more abundant as a result of microbial biohydrogenation, as occurs in sheep and cattle [51]. It has also been suggested that the consumption of carrots could influence the FA composition and ω6/ω3 ratio [24]. In the present work, carrots were added to all diets, so it was not possible to determine if carrot consumption would affect the larval composition. The shortest FA analyzed in this paper is lauric acid (C12:0) (see Table 3). However, the shorter FA capric acid (C10:0) was detected by Cito et al. (2017) [39] when mealworm larvae were raised on layer feed; the SFA content ranged between 26.3 and 41.4%. Similar SFA values were reported by Lawal et al. (2021) [52] when the diet was supplemented with flaxseed flour (26.9–28.4%), and Cito et al. (2017) [39] were able to achieve an SFA value of 28.8% when larvae were fed with wheat flour, oat flour, and yeast. Furthermore, a comparable SFA composition (29.6%) [39] was found in the larvae as in the present research from feeding pure wheat bran (29.3%). However, lower SFA values in Tenebrio molitor larvae fed only with wheat bran were also described by Ravzanaadii et al. (2012) [42] (22.3%). Studies by Giannetto et al. (2020) [53] and Meneguz et al. (2018) [54] have shown that a rearing substrate rich in polysaturated FAs can affect the FA profile, meaning that the insect larvae can become rich in saturated FAs. The fat content of mealworm larvae ranged between 5.7 and 16.1% and was similar to those reported in the literature [40,55,56]. The differences in the fat content of insects are normally due to the diet, rearing conditions, extraction method, and type of species [57]. All groups attained a higher lipid content compared to the initial larvae at an age of 8 weeks, regardless of the substrate. This is due to the progressive development having an influence on the nutritional composition, especially the fat content, of T. molitor larvae [58]. All diets in this study had a high survival rate (≥99%), making them suitable for Tenebrio molitor development. Our research clearly demonstrates that the fat content and fatty acid composition are hugely affected by diet, which was also observed in similar investigations [8,9,52,59]. Consequently, the differences in the fat content of T. molitor larvae observed in this research can be linked to the nutrient content of the larval diets on which they were reared. Van Broekhoven et al. (2015) showed that the fat content of Tenebrio molitor larvae was greatly influenced by the various starch and protein contents of their feeding substrates, suggesting that mealworm larvae fed with a low nutritional quality substrate possibly use their fat reserves for energy, thereby reducing their fat content [23].

In insects raised on diets with a high protein content or a variable protein/starch ratio, differences in the larval growth rate were noted. The growth rates and weight gain of T. molitor larvae were different based on diet treatments, depending on their contrasting differences in nutritional composition. Some previous studies demonstrated that the nutrient content and composition differ between and within insect species as a result of different diets and feeding patterns [8,52,59]; generally, low protein levels reduce growth rates [60,61]. The growth of insects is affected by the ratio of nutrients absorbed, and insects may use behavioral and post-ingestive mechanisms to compensate for nutrient deficiency [62,63]. A similar ratio between proteins and carbohydrates appears to be the best diet for beetles, but they may have eaten low-protein substrates at higher rates to ensure that they consumed sufficient nutrients [64]. However, a disproportional amount of protein content can also have a detrimental effect on larval growth. The protein content of the diets HPF8 (40.0%) and PPF6 (40.0%) is very high, but the larvae showed a reduced growth rate and weight gain. This may be due to the low carbohydrate contents of 18.4% (HPF8) and 29.5% (PPF6). According to other studies, the optimal macronutrient content varied depending on different factors (larval age, instar, diet, etc.) and should be between 61.3 and 79.2% for carbohydrates, between 14.4 and 25.4% for protein, and around 4.3 to 13.4% for fat [65,66,67]. As stated by Alves et al. (2016) [68], Tenebrio molitor larvae reared on diets (acrocomia aculeata pulp flour) with a high protein and low-fat content also exhibited the highest protein and fat levels. On the other hand, the fat content of mealworm larvae did not appear to be strongly influenced by the fat amount of the diet, as reported by Silva et al. (2021) [58]. Harsányi et al. (2020) [69] detected a minor variation in the protein and fat content of mealworm larvae, despite existing differences in dietary composition. The protein content of the diet should not influence the larval protein content when they are reared on a nutritionally balanced diet, as excessive protein is catabolized, which could be observed by the increase in the uric acid in the larval excreta [24]. As a result, mealworm larvae with a higher protein content may accumulate less fat due to diets with lower energy sources. This effect was also observed in locusts (Locusta migratoria) [70], which could explain the differences reported in other studies. However, there is no information on whether the ingestion rates differed between treatments. Furthermore, the diets used in this research were not isocaloric, so the larvae could have responded to changes in energy intake and different elements such as nitrogen contained in the substrate, as appears in several arthropods [71,72]. Consequently, the quality (including the total nitrogen content) of the larvae diet could influence the growth rate and body mass of T. molitor larvae. The last instars normally have the highest lipid reserves [73] and increase as larval development progresses [65] but decrease significantly in the adult since fat is needed as an energy source during pupation [74]. This might be the reason why the fat content of the larvae at the beginning of the experiment is much lower (5.7 ± 1.1 g/100 g) than the fat content of the larvae at the end (7.6–16.1 g/100 g) of the feeding trial. Additionally, other factors can also have a significant effect on the larvae’s nutritional composition. A number of environmental factors (temperature, humidity, light, etc.) have been shown to affect the development, growth, and nutritional composition of insects [22,34,36].

This paper is the first study to predict the fat content in living Tenebrio molitor larvae using near-infrared reflectance spectroscopy, with prediction models (R²_C = 0.975, R²_P = 0.986, RPD = 8.33) that are comparable with the analysis of fat content in pork (R²_C = 0.84–0.99, R²_P = 0.84–0.98) [19] or cheese (R²_C = 0.972–0.995, R²_P = 0.914–0.933) [75], and better than the prediction of fat content in rice (R²_C = 0.73–0.89, R²_P = 0.62–0.87) [20], beef (R²_C = 0.879, R²_P = 0.901, RPD = 2.84) [76], and nuts (R²_C = 0.96, R² = 0.97, RPD = 5.61) [77]. As a complex matrix, measuring living mealworm larvae using NIRS is challenging, since the nutrient content of homogenized samples, such as insect flour [78], can be predicted more accurately than in intact samples [79]. A significant number of spectra peaks were detected at 1454 nm (combination of C-H stretching and first overtone stretching) and at 1930 nm (combination of N-H stretching and O-H stretching), mostly associated with protein, water, sugar, and starch concentrations [80,81]. The second overtone of C-H stretching at 1205 nm, and the first overtone of C-H stretching between 1727 and 1797 nm are usually associated with fat and fatty acid content [82,83]. The predictability of fat content in living mealworm larvae is very good, but it could probably be improved by creating a larger variety of data for fat content within the calibration, as other studies have shown if more data points are available, a higher model performance is reached [84,85]. Since the fat content of living Tenebrio molitor larvae can be predicted highly accurately, it may be possible to monitor the amount of fat in real-time online for the large-scale production of mealworm larvae, resulting in a significant advantage in terms of influencing the nutritional content of the larvae and achieving the desired nutrient profile at harvest time through specific feeding. Published studies also demonstrate the applicability of NIRS for FA profiling in different food and feed such as oilseeds [84], chicken breast [86], pork sausages [87], and fish oil [88]. The purpose of this study was to compare the performances of the calibration methods in order to investigate the possibility of using NIRS for measuring the FA composition of living mealworm larvae. This study is the first that demonstrated a very high degree of accuracy in predicting the fatty acid content of living mealworm larvae. The prediction results of validation demonstrated that the equation for oleic acid had the highest predictive ability (R²_P = 0.949, RPD = 5.55), followed by α-linolenic acid (R²_P = 0.945, RPD = 4.90), myristic acid (R²_P = 0.930, RPD = 4.11), linoleic acid (R²_P = 0.931, RPD = 3.98), and lauric acid (R²_P = 0.917, RPD = 3.73), and are valid for quality analysis. The palmitic acid model (R²_P = 0.877, RPD = 2.66) was usable for several research applications such as sample screening. A high predictive capability was performed for analyzing the SFA (R²_P = 0.942, RPD = 4.26), MUFA (R²_P = 0.903, RPD = 4.00), and PUFA (R²_P = 0.878, RPD = 3.03) content in Tenebrio molitor larvae. However, no suitable predictive model for palmitoleic (R²_P = 0.345, RPD = 1.57) and stearic (R²_P = 0.509, RPD = 1.96) acids could be established. A similar model with low prediction accuracy for stearic acid (R²_P = 0.49, RPD = 1.4) in soybeans was developed by Kovalenko et al. (2006) [84]. However, the author was also able to establish good prediction models for palmitic acid (R²_P = 0.80, RPD = 2.2) and SFA (R²_P = 0.91, RPD = 3.3) in soybeans [84]. There is a large variance in the prediction ability of NIR models attributed to the standard deviation of reference data obtained from calibration sets. As a result, introducing samples with extremely high and low palmitoleic and stearic acid values into calibration sets may increase the accuracy of the prediction [84]. The coefficient for determining the correlation of relative FA concentration with the fat content (R²_F) of mealworm larvae had a wide range (0.019–0.568), which suggests that not all fatty acids have the same dependence on the total fat content. Prediction values (R²_P) of the NIR calibration models for α-linolenic acid were high (0.945), whereas the correlation coefficients between the fat content and α-linolenic acid in Tenebrio molitor larvae were very low (R²_F = 0.019). This indicates that the calibration methods of NIRS used in this research might have gained information from individual FA absorption bands rather than from broader total fat absorption bands. This has also been observed in a study by Kovalenko et al. (2006) [84].