Near infrared spectroscopy for high-throughput characterization of Shea tree (Vitellaria paradoxa) nut fat profiles

Effect of Refining and Fractionation Processes on Minor Components, Fatty Acids, Antioxidant and Antimicrobial Activities of Shea Butter

Shea butter is becoming increasingly popular in foods, cosmetics and pharmaceutical products. This work aims to study the effect of the refining process on the quality and stability of fractionated and mixed shea butters. Crude shea butter, refined shea stearin, olein and their mixture (1:1 w/w) were analyzed for fatty acids, triacylglycerol composition, peroxide value (PV), free fatty acids (FFA), phenolic (TPC), flavonoid (TFC), unsaponifiable matter (USM), tocopherol and phytosterol content. Additionally, the oxidative stability, radical scavenging activity (RSA), antibacterial and antifungal activities were evaluated. The two main fatty acids in the shea butter samples were stearic and oleic. The refined shea stearin showed lower PV, FFA, USM, TPC, TFC, RSA, tocopherol and sterol content than crude shea butter. A higher EC50 was observed, but antibacterial activity was much lower. The refined olein fraction was characterized by lower PV, FFA and TFC in comparison with crude shea butter, but USM, TPC, RSA, EC50, tocopherol and sterol content was unchanged. The antibacterial activity was higher, but the antifungal activity was lower than those of crude shea butter. When both fractions were mixed, their fatty acid and triacylglycerol composition were similar to those of crude shea butter, but other parameters were different.

Near-Infrared Reflectance Spectroscopy for Quantitative Analysis of Fat and Fatty Acid Content in Living Tenebrio molitor Larvae to Detect the Influence of Substrate on Larval Composition

Several studies have shown that mealworms (Tenebrio molitor L.) could provide animals and humans with valuable nutrients. Tenebrio molitor larvae were studied to determine whether their rearing diets affected their fat and fatty acid content and to ascertain if it is possible to detect the changes in the larval fat composition using near-infrared reflectance spectroscopy (NIRS). For this reason, a standard control diet (100% wheat bran) and an experimental diet, consisting of wheat bran and the supplementation of a different substrate (coconut flour, flaxseed flour, pea protein flour, rose hip hulls, grape pomace, or hemp protein flour) were used. The results showed lesser weight gain and slower growth rates for larvae raised on diets with a high fat content. A total of eight fatty acids were identified and quantified, where palmitic, oleic, and linoleic acids were the most prevalent and showed a correlation between larval content and their content in the rearing diets. There was a high content of lauric acid (3.2-4.6%), myristic acid (11.4-12.9%), and α-linolenic acid 8.4-13.0%) in mealworm larvae as a result of the high dietary content of these fatty acids. NIR spectra were also influenced by the fat and fatty acid composition, as larval absorbance values differed greatly. The coefficient of the determination of prediction (R²_P) was over 0.97, with an RPD value of 8.3 for the fat content, which indicates the high predictive accuracy of the NIR model. Furthermore, it was possible to develop calibration models with great predictive efficiency (R²_P = 0.81-0.95, RPD = 2.6-5.6) for all fatty acids, except palmitoleic and stearic acids which had a low predictive power (R²_P < 0.5, RPD < 2.0). The detection of fat and fatty acids using NIRS can help insect producers to quickly and easily analyze the nutritional composition of mealworm larvae during the rearing process.

Lipids in a Nutshell: Quick Determination of Lipid Content in Hazelnuts with NIR Spectroscopy

Hazelnuts (Corylus avellana L.) are among the most consumed dry fruits all over the world. Their commercial quality is defined, above all, by origin and dimension, as well as by lipid content. Evaluation of this parameter is currently performed with chemical methods, which are expensive, time consuming, and complex. In the present work, the near-infrared (NIR) spectroscopy, using both a benchtop research spectrometer and a retail handheld instrument, was evaluated in comparison with the traditional chemical approach. The lipid content of hazelnuts from different growing regions of origin (Italy, Chile, Turkey, Georgia, and Azerbaijan) was determined with two NIR instruments: a benchtop FT-NIR spectrometer (Multi Purpose Analyser-MPA, by Bruker), equipped with an integrating sphere and an optic fibre probe, and the pocket-sized, battery-powered SCiO molecular sensor (by Consumer Physics). The Randall/Soxtec method was used as the reference measurement of total lipid content. The collected NIR spectra were inspected through multivariate data analysis. First, a Principal Component Analysis (PCA) model was built to explore the information contained in the spectral datasets. Then, a Partial Least Square (PLS) regression model was developed to predict the percentage of lipid content. PCA showed samples distributions that could be linked to their total crude fat content determined with the Randall/Soxtec method, confirming that a trend related to the lipid content could be detected in the spectral data, based on their chemical profiles. PLS models performed better with the MPA instrument than SCiO, with the highest R² of prediction (R²_PRED = 0.897) achieved by MPA probe, while this parameter for SCiO was much lower (R²_PRED = 0.550). Further analyses are necessary to evaluate if more acquisitions may lead to better performances when using the SCiO portable spectrometer.

Shelf-Life Prediction and Thermodynamic Properties of No Added Sugar Chocolate Spread Fortified with Multiple Micronutrients

The development of fortified healthy pleasant foods, in which saturated fats are replaced with unsaturated ones, poses a challenge for the food industry due to their susceptibility to oxidative rancidity, which decreases product shelf-life, causes the destruction of health-promoting molecules, and forms potentially toxic compounds. A comparative study applying the Arrhenius model was carried out to investigate the oxidative stability and predict the shelf-life of a newly developed no added sugar chocolate spread formulated with sunflower oil, and fortified with vitamin D, Mg, and Ca checked against two commercially available spreads: No Palm and a well-known commercially available product (RB). The results obtained from the accelerated shelf-life testing for peroxide value (PV) showed relatively higher activation energy (Ea, 14.48 kJ/mol K) for RB, whereas lower Ea (11.31–12.78 kJ/mol K) was obtained for No Palm and all the experimental spread chocolates. Q10 values were comparable (1.202–1.154), indicating a similar catalytic effect of the temperature upon the oxidation rate across all the investigated samples. The positive Gibbs free energies ranged from 75.014 to 83.550 kJ/mol and pointed out that the lipid oxidation reaction in the chocolate spread was an endergonic process. The predicted shelf-life at 293.15 K was 8.57 months (RB), 7 months (No Palm), and 6.8 months for all the experimental spreadable chocolate. However, the higher production of hydroperoxides was observed in chocolate fortified with magnesium-calcium carbonate nanoparticles and stored at 313.15 and 323.15 K, suggesting these particles may enhance lipid oxidation.

Using Spraying as an Alternative Method for Transferring Capsules Containing Shea Butter to Denim and Non-Denim Fabrics : Preparation of microcapsules for delivery of active ingredients

The aim of this study was to prepare microcapsules and transfer them to denim and non-denim trousers using different application methods. For this purpose, shea butter as active agent was encapsulated in an ethyl cellulose shell using the spray dryer method, and capsule optimisation was studied. A morphological assessment showed that the capsules had a smooth surface and were spherical in shape. The homogenous size distribution of the capsules was supported by laser diffraction analysis. The capsules showed a narrow size distribution, and the mean particle size of optimum formulations of shea butter was 390 nm. Denim fabrics were treated with shea butter capsules using the methods of exhaustion and spraying in order to compare these application methods. The presence of capsules on the fabrics was tested after five wash cycles. The comparison of application methods found similar preferred characteristics for both the exhaustion and spraying methods. However, the spraying method was found to be more sustainable, because it allows working with low liquor ratios in less water, with lower chemical consumption and less waste than the exhaustion method, which requires working with a high liquor ratio. This study showed that the spraying method can be used as an alternative to other application methods in the market for reducing energy consumption, and shea butter capsules can provide moisturising properties to the fabrics.

Online Application of a Hyperspectral Imaging System for the Sorting of Adulterated Almonds

Almonds are nutrient-rich nuts. Due to their high level of consumption and relatively high price, their production is targeted for illegal practices, with the intention of earning more profit. The most common adulterants are based on superficial matching, and as an adulterant, the apricot kernel is comparatively inexpensive and almost identical in color, texture, odor, and other physicochemical characteristics to almonds. In this study, a near-infrared hyperspectral imaging (NIR-HSI) system in the wavelength range of 900–1700 nm synchronized with a conveyor belt was used for the online detection of added apricot kernels in almonds. A total of 448 samples from different varieties of almonds and apricot kernels (112 × 4) were scanned while the samples moved on the conveyor belt. The spectral data were extracted from each imaged nut and used to develop a partial least square discrimination analysis (PLS-DA) model coupled with different preprocessing techniques. The PLS-DA model displayed over a 97% accuracy for the validation set. Additionally, the beta coefficient obtained from the developed model was used for pixel-based classification. An image processing algorithm was developed for the chemical mapping of almonds and apricot kernels. Consequently, the obtained model was transferred for the online sorting of seeds. The online classification system feedback had an overall accuracy of 85% for the classification of nuts. However, the model presented a relatively low accuracy when evaluated in real-time for online application, which might be due to the rough distribution of samples on the conveyor belt, high speed, delaying time in suction, and lighting variations. Nevertheless, the developed online prototype (NIR-HSI) system combined with multivariate analysis exhibits strong potential for the classification of adulterated almonds, and the results indicate that the system can be effectively used for the high-throughput screening of adulterated almond nuts in an industrial environment.

A new scattering correction method of different spectroscopic analysis for assessing complex mixtures

Physical properties such as particle size distribution and compactness have significant confounding effects on the spectral signals of complex mixtures, which multivariate linear calibration methods such as partial least-squares (PLS) cannot effectively model or correct. Therefore, these effects significantly deteriorate calibration models' predictive abilities for spectral quantitative analysis of complex mixtures. Here, new scattering correction methods were proposed to estimate the additive and multiplicative parameters considering light scattering effects in each spectrum and hence mitigate the detrimental influence of additive and multiplicative effects on quantitative spectroscopic analysis of complex mixtures. Three different correction methods were proposed to estimate the addition coefficient based on two different underlying assumptions, namely, whether this coefficient is related to the wavelength. After addition coefficient elimination, the multiplicative parameter can be eliminated by a simple but very efficient spectral ratio method. Furthermore, linear models are built with key variables, and the predictive performance of these models is verified using the root-mean-square error of prediction datasets. The proposed methods were tested on one apple data set and two publicly available benchmark datasets (i.e., near-infrared spectral data of meat and powder mixture samples) and compared with some existing correction methods. The results showed that (1) additive effects of different types of samples can be eliminated by different methods and (2) these methods can appreciable improve quantitative spectroscopic analysis of complex mixture samples. This study indicates that accurate quantitative spectroscopic analysis of complex mixtures can be achieved through the combination of additive effect elimination and the spectral ratio method.

Novel phase change materials for thermal energy storage: Evaluation of tropical tree fruit oils

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Tree fruit oils of Allanblackia spp., shea butter and palm kernel were evaluated for their physical and chemical properties using DSC, TGA and FTIR.

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All oils were thermally cycled to investigate their stability and reliability for potential use as phase change materials (PCMs) for thermal energy storage.

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Allanblackia spp. oil demonstrated greatest potential for use as PCM in thermal energy storage systems.

We report for the first time the evaluation of oils from the tropical forest tree, Allanblackia, shea butter and palm kernel oil as a potential phase change material for thermal energy storage based upon its thermo-physical and chemical properties. Differential Scanning Calorimetry showed that all the oils were polymorphic and hence exhibited multiple melting/freezing profile over a wide range. For both melting and freezing cycles, Allanblackia oil showed high latent heat of energy (80.53 J/g) with the highest melting point profile (34.74 °C) of all the oils. Thermo-gravimetric analysis showed that all the oil samples were thermally stable and did not degrade within the temperature of interest even though Allanblackia oil showed an increase in weight around 37 °C indicating oxidative instability. Chemical stability was confirmed by FTIR spectra. Of all the oils studied, Allanblackia exhibited a potential for use as a PCM for thermal energy storage if purified to improve oxidative stability.

Cooking with shea butter is associated with lower blood pressure in the Ghanaian population

The cardiovascular health benefits of shea butter, an edible off-white or ivory-colored fat native to West Africans has never been investigated. This is in spite of anecdotal evidence, which suggests that shea butter may have medicinal properties and its bioactive constituents lower certain cardiovascular risk markers. We hypothesized that cooking with shea butter would be associated with lower blood pressure (BP) in the Ghanaian population. Data from the 2014 Ghana Demographic and Health Survey, a nationally representative population-based survey was analyzed. A total of 9396 women aged 15-49 years and 4388 men aged 15-59 years selected from 12,831 sampled households were included in the study. Respondents with average systolic BP of ≥140 mmHg or average diastolic BP of ≥90 mmHg were classified as hypertensive. Multivariable linear and logistic regression adjusting for gender, age, area of residence, religion, ethnic group, marital status, education and wealth index was used to establish the association between shea butter consumption and BP. Overall prevalence of hypertension in the population was 15.1%. Shea butter consumption was associated with 2.43 mmHg (95% CI: -3.54, -1.31) and 1.78 mmHg (95% CI: -2.71, -0.86) decrease in systolic BP and diastolic BP, respectively, and 25% (AOR = 0.75, 95% CI: 0.55, 1.04) reduced odds of hypertension, compared to use of vegetable oils. Region of residence appeared to modify the relationship. We found an association of shea butter consumption with lower BP, which provides the rationale for investigation through rigorous study designs to evaluate the benefits of shea butter consumption for prevention of hypertension and improved cardiovascular health.

Identification of genes involved in shea butter biosynthesis from Vitellaria paradoxa fruits through transcriptomics and functional heterologous expression

Shea tree (Vitellaria paradoxa) is one economically important plant species that mainly distributes in West Africa. Shea butter extracted from shea fruit kernels can be used as valuable products in the food and cosmetic industries. The most valuable composition in shea butter was one kind of triacylglycerol (TAG), 1,3-distearoyl-2-oleoyl-glycerol (SOS, C18:0–C18:1–C18:0). However, shea butter production is limited and little is known about the genetic information of shea tree. In this study, we tried to reveal genetic information of shea tree and identified shea TAG biosynthetic genes for future shea butter production in yeast cell factories. First, we measured lipid content, lipid composition, and TAG composition of seven shea fruits at different ripe stages. Then, we performed transcriptome analysis on two shea fruits containing obviously different levels of SOS and revealed a list of TAG biosynthetic genes potentially involved in TAG biosynthesis. In total, 4 glycerol-3-phosphate acyltransferase (GPAT) genes, 8 lysophospholipid acyltransferase (LPAT) genes, and 11 diacylglycerol acyltransferase (DGAT) genes in TAG biosynthetic pathway were predicted from the assembled transcriptome and 14 of them were cloned from shea fruit cDNA. Furthermore, the heterologous expression of these 14 potential GPAT, LPAT, and DGAT genes in Saccharomyces cerevisiae changed yeast fatty acid and lipid profiles, suggesting that they functioned in S. cerevisiae. Moreover, two shea DGAT genes, VpDGAT1 and VpDGAT7, were identified as functional DGATs in shea tree, showing they might be useful for shea butter (SOS) production in yeast cell factories.

Safety Assessment of Plant-Derived Fatty Acid Oils

The Cosmetic Ingredient Review Expert Panel (Panel) assessed the safety of 244 plant-derived fatty acid oils as used in cosmetics. Oils are used in a wide variety of cosmetic products for their skin conditioning, occlusive, emollient, and moisturizing properties. Since many of these oils are edible, and their systemic toxicity potential is low, the review focused on potential dermal effects. The Panel concluded that the 244 plant-derived fatty acid oils are safe as used in cosmetics.

Preservation of Quality of Table Eggs Using Vegetable Oil and Shea Butter

The poultry industry in Nigeria keeps expanding on a daily basis and it is faced with the problem of egg glut almost yearly. Most of the poultry are raised in rural environments where there is no available and avoidable power supply for egg preservation. The study was aimed at using locally available and cheap materials for preservation of eggs quality under the hot ambient temperature. The eggs were divided into three groups of 80 eggs each. The first and second groups were treated with vegetable oil (soybean oil) and shea butter, respectively, while the third group served as control. The eggs were stored under the ambient conditions and assessed for their physical and nutritional qualities on days 1, 8, 15, 22, 29, 36, 43 and 50. The physical quality was assessed by determining the albumen height and the Haugh’s unit, while the nutritional quality was appraised through the protein concentration of the albumen. Based on the values of Haugh’s unit, eggs treated with vegetable oil produced excellent results; good quality eggs were obtained up to 50th day of storage. Treatment with shea butter maintained quality eggs up to the 29th day, while with untreated eggs good physical quality was maintained up to 22nd day of storage. Protein concentrations of eggs in the three groups studied decline with duration of storage, however the protein concentrations of eggs treated with vegetable oil were significantly higher than the other groups (p<0.001). The eggs treated with shea butter recorded a comparative higher protein concentrations than the untreated eggs (p=0.002).

Preservation of Quality of Table Eggs Using Vegetable Oil and Shea Butter

The poultry industry in Nigeria keeps expanding on a daily basis and it is faced with the problem of egg glut almost yearly. Most of the poultry are raised in rural environments where there is no available and avoidable power supply for egg preservation. The study was aimed at using locally available and cheap materials for preservation of eggs quality under the hot ambient temperature. The eggs were divided into three groups of 80 eggs each. The first and second groups were treated with vegetable oil (soybean oil) and shea butter, respectively, while the third group served as control. The eggs were stored under the ambient conditions and assessed for their physical and nutritional qualities on days 1, 8, 15, 22, 29, 36, 43 and 50. The physical quality was assessed by determining the albumen height and the Haugh’s unit, while the nutritional quality was appraised through the protein concentration of the albumen. Based on the values of Haugh’s unit, eggs treated with vegetable oil produced excellent results; good quality eggs were obtained up to 50thday of storage. Treatment with shea butter maintained quality eggs up to the 29thday, while with untreated eggs good physical quality was maintained up to 22ndday of storage. Protein concentrations of eggs in the three groups studied decline with duration of storage, however the protein concentrations of eggs treated with vegetable oil were significantly higher than the other groups (p<0.001). The eggs treated with shea butter recorded a comparative higher protein concentrations than the untreated eggs (p=0.002).

Oil extraction from sheanut (Vitellaria paradoxa Gaertn C.F.) kernels assisted by microwaves

Shea butter, is highly solicited in cosmetics, pharmaceuticals, chocolates and biodiesel formulations. Microwave assisted extraction (MAE) of butter from sheanut kernels was carried using the Doehlert's experimental design. Factors studied were microwave heating time, temperature and solvent/solute ratio while the responses were the quantity of oil extracted and the acid number. Second order models were established to describe the influence of experimental parameters on the responses studied. Under optimum MAE conditions of heating time 23 min, temperature 75 °C and solvent/solute ratio 4:1 more than 88 % of the oil with a free fatty acid (FFA) value less than 2, was extracted compared to the 10 h and solvent/solute ratio of 10:1 required for soxhlet extraction. Scanning electron microscopy was used to elucidate the effect of microwave heating on the kernels' microstructure. Substantial reduction in extraction time and volumes of solvent used and oil of suitable quality are the main benefits derived from the MAE process.

Use of Near-Infrared Spectroscopy and Chemometrics for the Nondestructive Identification of Concealed Damage in Raw Almonds (Prunus dulcis)

Concealed damage (CD) is defined as a brown discoloration of the kernel interior (nutmeat) that appears only after moderate to high heat treatment (e.g., blanching, drying, roasting, etc.). Raw almonds with CD have no visible defects before heat treatment. Currently, there are no screening methods available for detecting CD in raw almonds. Herein, the feasibility of using near-infrared (NIR) spectroscopy between 1125 and 2153 nm for the detection of CD in almonds is demonstrated. Almond kernels with CD have less NIR absorbance in the region related with oil, protein, and carbohydrates. With the use of partial least squares discriminant analysis (PLS-DA) and selection of specific wavelengths, three classification models were developed. The calibration models have false-positive and false-negative error rates ranging between 12.4 and 16.1% and between 10.6 and 17.2%, respectively. The percent error rates ranged between 8.2 and 9.2%. Second-derivative preprocessing of the selected wavelength resulted in the most robust predictive model.

Near infra-red characterization of changes in flavan-3-ol derivatives in cocoa (Theobroma cacao L.) as a function of fermentation temperature

Flavan-3-ols were successfully extracted from cocoa by the Fast-Prep device and analyzed by HPLC-DAD, and their identifications were confirmed by injection of authentic standards. (-)-Epicatechin was the most abundant component with an average of 9.4 mg/g dried cocoa powder. More than 700 cocoa samples were used to calibrate the NIRS. An efficient calibration model was developed to accurately determine any flavan-3-ol compound of ground dried cocoa beans (SEP = 2.33 mg/g in the case of total flavan-3-ols). This performance enabled NIRS to be used as an efficient and easy-to-use tool for estimating the level of targeted compounds. The analysis of the PLS loadings of the model and pure epicatechin spectra gave proof that NIRS was calibrated on an indirect strong correlation resulting in the changes in flavan-3-ols during fermentation and their interaction with some major components, such as proteins. Total flavan-3-ol concentration fell from an average of 33.3 mg/g for unfermented samples to an average of 6.2 mg/g at the end of fermentation. Changes in flavan-3-ol content were dependent upon the origin and highly correlated to the fermentation level expressed as the sum of temperatures (average R(2) = 0.74), a good marker of the fermentation process and of the heterogeneity of the batch.

A Review of Optical Nondestructive Visual and Near-Infrared Methods for Food Quality and Safety

This paper is a review of optical methods for online nondestructive food quality monitoring. The key spectral areas are the visual and near-infrared wavelengths. We have collected the information of over 260 papers published mainly during the last 20 years. Many of them use an analysis method called chemometrics which is shortly described in the paper. The main goal of this paper is to provide a general view of work done according to different FAO food classes. Hopefully using optical VIS/NIR spectroscopy gives an idea of how to better meet market and consumer needs for high-quality food stuff.

Past climate changes explain the phylogeography of Vitellaria paradoxa over Africa

The evolution of the savanna biome has been deeply marked by repeated contraction/expansion phases due to climate perturbations during the Quaternary period. In this study, we investigated the impact of the last glacial maximum (LGM) on the present genetic pattern of Vitellaria paradoxa (shea tree), a major African savanna tree. A range-wide sampling of the species enabled us to sample 374 individuals from 71 populations distributed throughout sub-Sahelian Africa. Trees were genotyped using 3 chloroplasts and 12 nuclear microsatellites, and were sequenced for 2 polymorphic chloroplast intergenic spacers. Analyses of genetic diversity and structure were based on frequency-based and Bayesian methods. Potential distributions of V. paradoxa at present, during the LGM and the last interglacial period, were examined using DIVA-GIS ecological niche modelling (ENM). Haplotypic and allelic richness varied significantly across the range according to chloroplast and nuclear microsatellites, which pointed to higher diversity in West Africa. A high but contrasted level of differentiation was revealed among populations with a clear phylogeographic signal, with both nuclear (F(ST) = 0.21; R(ST) = 0.28; R(ST) > R(ST) (permuted)) and chloroplast simple sequence repeats (SSRs) (G(ST) = 0.81; N(ST) = 0.90; N(ST) > N(ST) (permuted)). We identified a strong geographically related structure separating western and eastern populations, and a substructure in the eastern part of the area consistent with subspecies distinction. Using ENM, we deduced that perturbations during the LGM fragmented the potential eastern distribution of shea tree, but not its distribution in West Africa. Our main results suggest that climate variations are the major factor explaining the genetic pattern of V. paradoxa.