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Abstract Measuring the quality of life of an animal in a production system is difficult, time-consuming, and expensive. We tested the ability of both NIR and MIR spectroscopy, each combined with machine learning, to predict the prior exposure of pigs to long- and short-term life challenges when they are raised in an intensive system. Samples were obtained post-mortem from two locations in the prefrontal cortex. The analysis showed a clear separation between the gray and white matter from the prefrontal cortex with MIR spectroscopy. Exposure to long-term challenge was poorly predicted by the MIR or NIR spectra (

Abstract At a time when there is a growing public interest in animal welfare, it is critical to have objective means to assess the way that an animal experiences a situation. Objectivity is critical to ensure appropriate animal welfare outcomes. Existing behavioural, physiological, and neurobiological indicators that are used to assess animal welfare can verify the absence of extremely negative outcomes. But welfare is more than an absence of negative outcomes and an appropriate indicator should reflect the full spectrum of experience of an animal, from negative to positive. In this review, we draw from the knowledge of human biomedical science to propose a list of candidate biological markers (biomarkers) that should reflect the experiential state of non-human animals. The proposed biomarkers can be classified on their main function as endocrine, oxidative stress, non-coding molecular, and thermobiological markers. We also discuss practical challenges that must be addressed before any of these biomarkers can become useful to assess the experience of an animal in real-life.

This study assessed the metabolite content and bioactivities of Kakadu plum (KP) from Western Australia (WA). LC-MS/MS and UHPLC-PDA analyzed sugar, vitamin C, and ellagic acid (EA). Functional properties were evaluated by spectroscopic technique, agar well diffusion, and microplate dilution methods. WA KP exhibited higher total sugar (16.3 ± 1.0 g/100 g DW) and free ellagic acid (EA) (23.2 ± 1.7 mg/g DW), along with abundant vitamin C (25.20 ± 0.16 to 131.50 ± 0.20 mg/g DW) compared to Northern Territory KP fruits. The fruit showed strong antioxidant activities, α-glucosidase inhibition, and effectiveness against bacteria, with positive correlations to total phenolic content (TPC), vitamin C, and EA. These findings highlight WA KP’s potential for functional foods and pharmaceuticals, emphasizing the importance of TPC, vitamin C, and EA in selecting high-quality fruit.

The aim of this paper was to evaluate the effect of two different matrices (e.g., starch base flour vs. protein base flour) on the ability of near-infrared (NIR) spectroscopy to classify binary mixtures of chickpea (protein), corn and tapioca (starch) flours. Binary mixtures were made by mixing different proportions of chickpea plus corn, chickpea plus tapioca, and corn plus tapioca flour. Spectra were collected using NIR spectroscopy and the data analyzed using techniques such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The results showed an effect of the matrix on the PLS-DA classification results, in both classification rates and PLS loadings. The different combinations of flours/mixtures showed changes in absorbance values around 4752 cm−1 that are associated with starch and protein. Nevertheless, the use of NIR spectroscopic might provide a valuable initial screening and identification of the potential contamination of flours along the supply and value chains, enabling more costly methods to be used more productively on suspect samples.

Edible insects have been evaluated as an alternative and sustainable source of protein because of their nutritive and functional properties for humans and domestic animals. The objective of this study was to assess the use of chemometric [principal component analysis (PCA) and partial least squares (PLS)] combined with Rapid Visco Analyser (RVA) profiles to evaluate the addition of cricket powder (CKP) to chickpea (CPF) and flaxseed (FxF) flours. The results of this study showed that the addition of CKP powder to both CPF and FxF flours affects the pasting properties of the samples; in particular, a reduction in the peak (PV) and final viscosity (FV) was observed. The use of chemometric data techniques such as PCA and PLS regression allowed for a better interpretation of the RVA profiles. Both PCA and PLS regression allowed to qualitative and quantitatively identify the addition level of CKP powder to CPF and FxF flour samples. Differences in the PLS loadings associated with the RVA profile due to the addition of cricket powder were observed. The development of these methodologies will provide researchers and the food industry with better tools to both improve and monitor the quality of ingredients with functional properties as well as to further understand the use of insects as alternative sources of protein.

Edible insects are characterized by their low environmental footprint compared with traditional sources of animal and plant proteins. This is due to the high feed conversion efficiency of edible insects. The black soldier fly (Hermetia illucens) larvae (BSFL) are one of the preferred candidates to be used as alternative sources of protein, due to their ability to add value to a wide range of organic and food waste streams. The ability of BSFL to convert organic matter into protein has resulted in a viable and sustainable ingredient to be utilized in animal feed or human food. BSFL have also been considered as key components of the circular economy due to their intrinsic characteristics and properties. The evaluation of the chemical composition, nutritive value, and functional properties of BSFL have been achieved by the utilization of traditional methods of analysis, although most of these procedures do not agree with the requirements of a circular economy due to their intrinsic characteristics (e.g., destructive, energy use, highly reactive reagents, etc.). Therefore, green analytical technologies have been evaluated, of which infrared (IR) spectroscopy has several advantages. This article reviews current and potential applications of IR spectroscopy combined with chemometrics to analyze the proximate composition, functional characteristics, and traceability of BSFL and frass samples.

Growing location is known to affect the metabolite content and functionality of wild harvested fruits. Terminalia ferdinandiana, commonly known as Kakadu plum (KP), is among the most commercially important native Australian bush foods. Therefore, we evaluated the composition and in vitro bioactivity of aqueous acidified ethanol (AAE) and water extracts prepared from KP fruit wild harvested in the Northern Territory (NT) and Western Australia (WA). Compositional analysis included vitamin C, total ellagic acid (TEA), and total phenolic content (TPC), while in vitro bioactivity was assessed through anti-inflammatory (RAW 264.7 macrophages) activity and cell viability (Hep G2) assay. The IC50 of the extracts ranged from 33.3 to 166.3 µg/mL for NO inhibition and CC50 from 1676 to 7337 µg/mL for Hep G2 cell viability inhibition. The AAE KP fruit extracts from the NT exhibited potent anti-inflammatory activity and impacted Hep G2 cell viability more than other extracts, most likely due to TEA (3189 mg/100 g dry weight (DW)), vitamin C (180.5 mg/g DW) and TPC (196 mg GAE/g DW) being higher than in any other extract. Overall, the findings of the present study are promising for using KP fruit and derived products in functional foods, nutraceuticals, or dietary supplements.

Determining egg freshness is critical for ensuring food safety and security and as such, different methods have been evaluated and implemented to accurately measure and predict it. In this study, a portable near-infrared (NIR) instrument combined with chemometrics was used to monitor and predict the storage time of eggs under two storage conditions—room temperature (RT) and cold (CT) storage—from two production systems: cage and free-range. A total of 700 egg samples were analyzed, using principal component analysis (PCA) and partial least squares (PLS) regression to analyze the NIR spectra. The PCA score plot did not show any clear separation between egg samples from the two production systems; however, some egg samples were grouped according to storage conditions. The cross-validation statistics for predicting storage time were as follows: for cage and RT eggs, the coefficient of determination in cross validation (R2CV) was 0.67, with a standard error in cross-validation (SECV) of 7.64 days and residual predictive deviation (RPD) of 1.8; for CT cage eggs, R2CV of 0.84, SECV of 5.38 days and RPD of 3.2; for CT free-range eggs, R2CV of 0.83, SECV of 5.52 days and RPD of 3.2; and for RT free-range eggs, R2CV of 0.82, SECV of 5.61 days, and RPD of 3.0. This study demonstrated that NIR spectroscopy can predict storage time non-destructively in intact egg samples. Even though the results of the present study are promising, further research is still needed to further extend these results to other production systems, as well as to explore the potential of this technique to predict other egg quality parameters associated with freshness.

Edible insects have been recognised as an alternative food or feed ingredient due to their protein value for both humans and domestic animals. The objective of this study was to evaluate the ability of both near- (NIR) and mid-infrared (MIR) spectroscopy to identify and quantify the level of adulteration of cricket powder added into two plant proteins: chickpea and flaxseed meal flour. Cricket flour (CKF) was added to either commercial chickpea (CPF) or flaxseed meal flour (FxMF) at different ratios of 95:5% w/w, 90:10% w/w, 85:15% w/w, 80:20% w/w, 75:25% w/w, 70:30% w/w, 65:35% w/w, 60:40% w/w, or 50:50% w/w. The mixture samples were analysed using an attenuated total reflectance (ATR) MIR instrument and a Fourier transform (FT) NIR instrument. The partial least squares (PLS) cross-validation statistics based on the MIR spectra showed that the coefficient of determination (R2CV) and the standard error in cross-validation (SECV) were 0.94 and 6.68%, 0.91 and 8.04%, and 0.92 and 4.33% for the ALL, CPF vs. CKF, and FxMF vs. CKF mixtures, respectively. The results based on NIR showed that the cross-validation statistics R2CV and SECV were 0.95 and 3.16%, 0.98 and 1.74%, and 0.94 and 3.27% using all the samples analyzed together (ALL), the CPF vs. CKF mixture, and the FxMF vs. CKF mixture, respectively. The results of this study showed the effect of the matrix (type of flour) on the PLS-DA data in both the classification results and the PLS loadings used by the models. The different combination of flours (mixtures) showed differences in the absorbance values at specific wavenumbers in the NIR range that can be used to classify the presence of CKF. Research in this field is valuable in advancing the application of vibrational spectroscopy as routine tools in food analysis and quality control.

The aim of this study was to evaluate the ability of a droplet collar accessory attached to a portable near-infrared (NIR) instrument to characterize the artificial contamination of methanol in commercial whisky samples. Unadulterated samples (n = 12) were purchased from local bottle shops where adulterated samples were created by adding methanol (99% pure methanol) at six levels (0.5%, 1%, 2%, 3%, 4% and 5% v/v) to the commercial whisky samples (controls). Samples were analyzed using a drop collar accessory attached to a MicroNIR Onsite instrument (900–1650 nm). Partial least squares (PLS) cross-validation statistics obtained for the prediction of all levels of methanol (from 0 to 5%) addition were considered adequate when the whole adulteration range was used, coefficient of determination in cross-validation (R2cv: 0.95) and standard error in cross of validation (SECV: 0.35% v/v). The cross-validation statistics were R2cv: 0.97, SECV: 0.28% v/v after the 0.5% and 1% v/v methanol addition was removed. These results showed the ability of using a new sample presentation attachment to a portable NIR instrument to analyze the adulteration of whisky with methanol. However, the low levels of methanol adulteration (0.5 and 1%) were not well predicted using the NIR method evaluated.

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.

The effect of two drying methods (oven and freeze drying) and the addition of maltodextrin to Kakadu plum puree samples (KP) (Terminalia ferdianandiana) were evaluated using mid (MIR) and near-infrared (NIR) spectroscopy. Dry powder samples were obtained using the oven and freeze-drying methods and seven levels of maltodextrin. Training (n = 32) and validation (n = 28) sets were developed for the prediction of moisture (M %), water activity (aw %), hydroxymethylfurfural (HMF) and vitamin C (VITC mg/100 g DM) based on NIR and MIR spectroscopy. Results from this study demonstrated the ability of spectroscopy combined with partial least squares (PLS) regression to monitor these parameters during drying. The standard error in cross validation (SECV) and the residual predictive deviation (RPD) values obtained were of 0.71% (RPD = 4.1) and 0.47% (RPD = 6.1) for M, 0.06% (RPD = 4.4) and 0.02% (RPD = 8.2) for aw, 0.73 (RPD = 3.3) and 0.72 (RPD = 3.3) for HMF, 465.7 mg 100 g DM (RPD = 3.0) and 289.3 mg 100 g DM (RPD = 4.8) for VITC, using MIR and NIR, respectively. The results from this study showed that MIR and NIR spectroscopies are capable of both measuring and monitoring the effect of drying and the addition of maltodextrin as a carrier to KP puree samples.

Satiety can influence food intake, and as a consequence has the potential to affect weight and obesity. Human factors such as physiology and psychology are likely to be important in determining satiety. However, it is not well-understood how these factors (individual variations) alone or combined contribute to satiety feelings. In addition, there have been limited or no attempts to use a holistic approach to evaluate satiety. In this study, three plant-based foods were used as mid-morning snack for 52 participants to evaluate satiety response (during three consecutive days, one-day-one-food type). The foods were served ad libitum until participants felt comfortably full prior to satiety monitoring. The study explored diverse human factors (n = 30) that might contribute to satiety including those related to oral physiology, metabolic factors, body composition and psychology. It identified important variables for satiety as well as the interactions among them and the influences of age, gender, and low satiety phenotype (consistently lower reported fullness scores) on satiety. Overall, combinations of factors rather than individual ones contributed to self-reported satiety. Food factors (e.g., type, composition) had limited effects, but there were only three types used in the study. The combination of metabolic factors [respiratory quotient, age, and body energy usage type (e.g., carbohydrate or fat)], oral sensitivity & processing, personality traits (agreeableness, conscientiousness, and neuroticism), and eating behavior (e.g., emotional and external eating) were the most important for explaining individual satiety responses. Older participants had significantly higher reported satiety than younger participants, associated with significant differences in oral physiology, increased body fat, and mature psychological characters. Moreover, different satiety phenotypes had significant differences in relationships with body fat, oral physiology, personalities, food neophobia, and eating behaviors. The results of this study indicate that much greater insights into the factors determining satiety responses can be obtained by combining multiple food and human physiological and psychological characteristics. This study used more diverse measures of individual variation than previous studies of satiety and points the way toward a more holistic approach to understanding the (control of) perceptions of fullness at both individual and group levels.

Humans are exposed to an ever-increasing number of environmental toxicants, some of which have gradually been elucidated to be important risk factors for metabolic diseases, such as diabetes and obesity. These metabolism-sensitive diseases typically occur when key metabolic and signaling pathways were disrupted, which can be influenced by the exposure to contaminants such as endocrine disrupting chemicals (EDCs), along with genetic and lifestyle factors. This promotes the concept and research on environmental metabolism disrupting chemicals (MDCs). In addition, identifying endogenous biochemical markers of effect linked to disease states is becoming an important tool to screen the biological targets following environmental contaminant exposure, as well as to provide an overview of toxicity risk assessment. As such, the current review aims to contribute to the further understanding of exposome and human health and disease by characterizing environmental exposure and effect metabolic biomarkers. We summarized MDC-associated metabolic biomarkers in laboratory animal and human cohort studies using high throughput targeted and nontargeted metabolomics techniques. Contaminants including heavy metals and organohalogen compounds, especially EDCs, have been repetitively associated with metabolic disorders, whereas emerging contaminants such as perfluoroalkyl substances and microplastics have also been found to disrupt metabolism. In addition, we found major limitations in the effective identification of metabolic biomarkers especially in human studies, toxicological research on the mixed effect of environmental exposure has also been insufficient compared to the research on single chemicals. Thus, it is timely to call for research efforts dedicated to the study of combined effect and metabolic alterations for the better assessment of exposomic toxicology and health risks. Moreover, advanced computational and prediction tools, further validation of metabolic biomarkers, as well as systematic and integrative investigations are also needed in order to reliably identify novel biomarkers and elucidate toxicity mechanisms, and to further utilize exposome and metabolome profiling in public health and safety management.

A hand-held near infrared (NIR) spectrophotometer combined with a similarity index (SI) method was evaluated to identify meat samples sourced from exotic and traditional meat species. Fresh meat cuts of lamb (Ovis aries), emu (Dromaius novaehollandiae), camel (Camelus dromedarius), and beef (Bos taurus) sourced from a commercial abattoir were used and analyzed using a hand-held NIR spectrophotometer. The NIR spectra of the commercial and exotic meat samples were analyzed using principal component analysis (PCA), linear discriminant analysis (LDA), and a similarity index (SI). The overall accuracy of the LDA models was 87.8%. Generally, the results of this study indicated that SI combined with NIR spectroscopy can distinguish meat samples sourced from different animal species. In future, we can expect that methods such as SI will improve the implementation of NIR spectroscopy in the meat and food industries as this method can be rapid, handy, affordable, and easy to understand for users and customers.

The demand from the food industry and consumers for analytical tools that can assure the quality (e [...]

Black soldier fly (Hermetia illucens, L.) larvae are characterized by their ability to convert a variety of organic matter from food waste into a sustainable source of food (e.g., protein). This study aimed to evaluate the use of attenuated total reflectance (ATR) mid-infrared (MIR) spectroscopy to monitor changes in the composition as well as to classify black soldier fly larvae (BSFL) samples collected from two growth stages (fifth and sixth instar) and two waste stream diets (bread and vegetables, soy waste). The BSFL samples were fed on either a soy or bread-vegetable mix waste in a control environment (temperature 25 °C, and humidity 70%). The frass and BSFL samples harvested as fifth and sixth instar samples were analyzed using an ATR-MIR instrument where frequencies at specific wavenumbers were compared and evaluated using different chemometric techniques. The PLS regression models yield a coefficient of determination in cross-validation (R2) > 0.80 for the prediction of the type of waste used as diet. The results of this study also indicated that the ratio between the absorbances corresponding to the amide group (1635 cm−1) and lipids (2921 + 2849 cm−1) region was higher in diets containing a high proportion of carbohydrates (e.g., bread-vegetable mix) compared with the soy waste diet. This study demonstrated the ability of MIR spectroscopy to classify BSFL instar samples according to the type of waste stream used as a diet. Overall, ATR-MIR spectroscopy has shown potential to be used as tool to evaluate and monitor the development and growth of BSFL. The utilization of MIR spectroscopy will allow for the development of traceability systems for BSFL. These tools will aid in risk evaluation and the identification of hazards associated with the process, thereby assisting in improving the safety and quality of BSFL intended to be used by the animal feed industry.

Adulterated, poor-quality, and unsafe foods, including meat, are still major issues for both the food industry and consumers, which have driven efforts to find alternative technologies to detect these challenges. This study evaluated the use of a portable near-infrared (NIR) instrument, combined with chemometrics, to identify and classify individual-intact fresh goat muscle samples. Fresh goat carcasses (n = 35; 19 to 21.7 Kg LW) from different animals (age, breeds, sex) were used and separated into different commercial cuts. Thus, the longissimus thoracis et lumborum, biceps femoris, semimembranosus, semitendinosus, supraspinatus, and infraspinatus muscles were removed and scanned (900–1600 nm) using a portable NIR instrument. Differences in the NIR spectra of the muscles were observed at wavelengths of around 976 nm, 1180 nm, and 1430 nm, associated with water and fat content (e.g., intramuscular fat). The classification of individual muscle samples was achieved by linear discriminant analysis (LDA) with acceptable accuracies (68–94%) using the second-derivative NIR spectra. The results indicated that NIR spectroscopy could be used to identify individual goat muscles.

Edible green ants (Oecophylla smaragdina) are distributed in Asia, Australia, and the Pacific Islands, and are known for their pharmacological and nutritional applications, yet various properties are to be explored. Nutritional value, volatile compounds, antimicrobial and antioxidant potential were determined in four body regions [ant nest, whole ant, anterior part of the body, and gaster]. Proximate analysis revealed the anterior part have higher protein and fibre content, whilst fat content was higher in the gaster. GC–MS analysis revealed the complexity of ant nest with most compounds being organic acids, alcohols and alkanes. Antimicrobial activity was observed for whole ants (ZOI: 13.3 ± 0.8 mm) and anterior part (ZOI: 11.9 ± 0.5 mm) methanol extracted against Staphylococcus aureus (~104 CFU/ml). Whole ants methanol (813 ± 22.6 µg TROLOX eq/g of DW) and water (617.6 ± 59.2 µg TROLOX eq/g of DW) extracted exhibited higher free radical scavenging capacity amongst the four ant body regions. Whole ants water extracted (7 ± 0.4 mg GAE/g of DW) had the highest total phenolic content. In the methanol extracts, the gaster (6.2 ± 0.2 mg GAE/g of DW) exhibited the highest phenolic content. Whole ants exhibit good antioxidant and antimicrobial activity and considerable folate content.

The demand for animal proteins, especially from pork and poultry, is projected to increase significantly due to rapid growth in population and underlying socio-economic conditions. Livestock rearing using conventional feed ingredients is becoming challenging due to climate change and several other factors, thereby suggesting the need for alternative, viable and sustainable animal feed sources. The use of black soldier fly larvae (BSFL) (Hermetia illucens) as a component in animal feed is a promising candidate due to their ability to valorise different organic waste streams. The nutrient composition of BSFL reared on organic waste streams is also comparable to that of several conventional animal feed ingredients and varies depending upon the feed, rearing conditions, and the morphological stage of the larvae. The identification of organic waste is of importance as it can determine not only the composition but also the safety issues of BSFL as an animal feed ingredient. The objective of this study was to determine the ability of near-infrared (NIR) spectroscopy to trace the food waste used to grow BSFL. Samples of BSFL (5th and 6th instar BSFL; n = 50) obtained from a commercial production facility were analysed using NIR spectroscopy. Partial least squares discriminant analysis (PLS-DA) was employed to develop the models. The outcomes of this study revealed that NIR spectroscopy could distinguish different larval instars and suggested the importance of larval instars in developing calibration models for traceability applications. The developed PLS-DA model could predict the feed source used for rearing the 5th instar larvae (R2 value: 0.89) and 6th instar pre-pupae (R2 value: 0.91). This suggests that NIR spectroscopy could be used as a non-invasive traceability tool for BSFL and to assist in selecting the suitable time frame for larvae harvesting in commercial facilities.

An increase in interest in the use of sensing technologies (e.g., electrochemistry, fluorescence, thermal, surface plasmon resonance, piezo, reflectometry, chemo or bioluminescence, and optics) as analytical methods to be implemented in a wide range of fields, including agriculture and food has been witnessed in recent years. Most of these applications have been evaluated and developed targeting a wide range of samples (e.g., raw materials, commodities, soils, water, food ingredients, natural products). Sensing technologies must be integrated with different data analytical techniques (e.g., pattern recognition, modelling techniques, calibration development) to develop a target application. The increasing availability of modern and inexpensive sensors, together with access to easy-to-use software is determining a steady growth in the number of applications and uses of these technologies. This short review underlined and briefly discussed practical considerations that support the robust development and implementation of applications that combine the use of sensing technologies with chemometrics.

Issues related to food authenticity, traceability, and fraud have increased in recent decades as a consequence of the deliberate and intentional substitution, addition, tampering, or misrepresentation of food ingredients, where false or misleading statements are made about a product for economic gains. This study aimed to evaluate the ability of a portable NIR instrument to classify egg samples sourced from different provenances or production systems (e.g., cage and free-range) in Australia. Whole egg samples (n: 100) were purchased from local supermarkets where the label in each of the packages was used as identification of the layers’ feeding system as per the Australian legislation and standards. The spectra of the albumin and yolk were collected using a portable NIR spectrophotometer (950–1600 nm). Principal component analysis (PCA) and linear discriminant analysis (LDA) were used to analyze the NIR data. The results obtained in this study showed how the combination of chemometrics and NIR spectroscopy allowed for the classification of egg albumin and yolk samples according to the system of production (cage and free range). The proposed method is simple, fast, environmentally friendly and avoids laborious sample pre-treatment, and is expected to become an alternative to commonly used techniques for egg quality assessment.

Abstract The development of antimicrobial drug resistance among pathogenic bacteria and fungi is one of the most significant health issues of the 21st century. Recently, advances in nanotechnology have led to the development of nanomaterials, particularly metals that exhibit antimicrobial properties. These metal nanomaterials have emerged as promising alternatives to traditional antimicrobial therapies. In this review, a broad overview of metal nanomaterials, their synthesis, properties, and interactions with pathogenic micro‐organisms is first provided. Secondly, the range of nanomaterials that demonstrate passive antimicrobial properties are outlined and in‐depth analysis and comparison of stimuli‐responsive antimicrobial nanomaterials are provided, which represent the next generation of microbiocidal nanomaterials. The stimulus applied to activate such nanomaterials includes light (including photocatalytic and photothermal) and magnetic fields, which can induce magnetic hyperthermia and kinetically driven magnetic activation. Broadly, this review aims to summarize the currently available research and provide future scope for the development of metal nanomaterial‐based antimicrobial technologies, particularly those that can be activated through externally applied stimuli.

The number of food frauds in coconut-based products is increasing due to higher consumer demands for these products. Rising health consciousness, public awareness and increased concerns about food safety and quality have made authorities and various other certifying agencies focus more on the authentication of coconut products. As the conventional techniques for determining the quality attributes of coconut are destructive and time-consuming, non-destructive testing methods which are accurate, rapid, and easy to perform with no detrimental sampling methods are currently gaining importance. Spectroscopic methods such as nuclear magnetic resonance (NMR), infrared (IR)spectroscopy, mid-infrared (MIR)spectroscopy, near-infrared (NIR) spectroscopy, ultraviolet-visible (UV-VIS) spectroscopy, fluorescence spectroscopy, Fourier-transform infrared spectroscopy (FTIR), and Raman spectroscopy (RS) are gaining in importance for determining the oxidative stability of coconut oil, the adulteration of oils, and the detection of harmful additives, pathogens, and toxins in coconut products and are also employed in deducing the interactions in food constituents, and microbial contaminations. The objective of this review is to provide a comprehensive analysis on the various spectroscopic techniques along with different chemometric approaches for the successful authentication and quality determination of coconut products. The manuscript was prepared by analyzing and compiling the articles that were collected from various databases such as PubMed, Google Scholar, Scopus and ScienceDirect. The spectroscopic techniques in combination with chemometrics were shown to be successful in the authentication of coconut products. RS and NMR spectroscopy techniques proved their utility and accuracy in assessing the changes in coconut oil’s chemical and viscosity profile. FTIR spectroscopy was successfully utilized to analyze the oxidation levels and determine the authenticity of coconut oils. An FT-NIR-based analysis of various coconut samples confirmed the acceptable levels of accuracy in prediction. These non-destructive methods of spectroscopy offer a broad spectrum of applications in food processing industries to detect adulterants. Moreover, the combined chemometrics and spectroscopy detection method is a versatile and accurate measurement for adulterant identification.

The aim of this study was to evaluate the ability of mid-infrared (MIR) spectroscopy combined with chemometrics to analyze unstimulated saliva as a method to predict satiety in healthy participants. This study also evaluated features in saliva that were related to individual perceptions of human–food interactions. The coefficient of determination (R2) and standard error in cross validation (SECV) for the prediction of satiety in all saliva samples were 0.62 and 225.7 satiety area under the curve (AUC), respectively. A correlation between saliva and satiety was found, however, the quantitative prediction of satiety using unstimulated saliva was not robust. Differences in the MIR spectra of saliva between low and high satiety groups, were observed in the following frequency ratios: 1542/2060 cm−1 (total protein), 1637/3097 cm−1 (α-amino acids), and 1637/616 (chlorides) cm−1. In addition, good to excellent models were obtained for the prediction of satiety groups defined as low or high satiety participants (R2 0.92 and SECV 0.10), demonstrating that this method could be used to identify low or high satiety perception types and to select participants for appetite studies. Although quantitative PLS calibration models were not achieved, a qualitative model for the prediction of low and high satiety perception types was obtained using PLS-DA. Furthermore, this study showed that it might be possible to evaluate human/food interactions using MIR spectroscopy as a rapid and cost-effective tool.

Vibrational spectroscopy techniques are the most used techniques in the routine analysis of foods. This technique is widely utilised to measure and monitor the proximate chemical composition (e.g., protein, dry matter, fat and fibre) in an array of agricultural commodities, food ingredients and products. Developments in optics, instrumentation and hardware concomitantly with data analytics, have allowed for the progress in novel applications of these technologies in the field of nutraceutical and bio compound analysis. In recent years, several studies have demonstrated the capability of vibrational spectroscopy to evaluate and/or measure these nutraceuticals in a broad selection of fruit and plants as alternative to classical analytical approaches. This article highlights, as well as discusses, the challenges and opportunities that define the successful application of vibrational spectroscopy techniques, and the advantages that these techniques have to offer to evaluate and quantify nutraceuticals in fruits and plants.

Meat spoilage is a metabolic process where the change in sensory characteristics deems it to be unacceptable for human consumption. Meat spoilage typically occurs under conditions of optimal water availability, low oxygen, and low temperature conditions, where growth conditions are ideal for microbial growth. Technological advances in the food industry have been at high demand for the past decade, to ensure food safety and health regulations are met using earlier detection methods. Detection technologies such as polymerase chain reactions, spectroscopy, odor sensors devices such as the electric nose are just a few methods used to identify meat spoilage.

Near infrared (NIR) spectroscopy is considered one of the main routine analytical methods used by the food industry. This technique is utilised to determine proximate chemical compositions (e.g., protein, dry matter, fat and fibre) of a wide range of food ingredients and products. Novel algorithms and new instrumentation are allowing the development of new applications of NIR spectroscopy in the field of food science and technology. Specifically, several studies have reported the use of NIR spectroscopy to evaluate or measure functional properties in both food ingredients and products in addition to their chemical composition. This mini-review highlights and discussed the applications, challenges and opportunities that NIR spectroscopy offers to target the quantification and measurement of food functionality in dairy and cereals.

In a global context where trading of wines involves considerable economic value, the requirement to guarantee wine authenticity can never be underestimated. With the ever-increasing advancements in analytical platforms, research into spectroscopic methods is thriving as they offer a powerful tool for rapid wine authentication. In particular, spectroscopic techniques have been identified as a user-friendly and economical alternative to traditional analyses involving more complex instrumentation that may not readily be deployable in an industry setting. Chemometrics plays an indispensable role in the interpretation and modelling of spectral data and is frequently used in conjunction with spectroscopy for sample classification. Considering the variety of available techniques under the banner of spectroscopy, this review aims to provide an update on the most popular spectroscopic approaches and chemometric data analysis procedures that are applicable to wine authentication.

Biofilms are assemblages of microbial cells, extracellular polymeric substances (EPS), and other components extracted from the environment in which they develop. Within biofilms, the spatial distribution of these components can vary. Here we present a fundamental characterization study to show differences between biofilms formed by Gram-positive methicillin-resistant Staphylococcus aureus (MRSA), Gram-negative Pseudomonas aeruginosa, and the yeast-type Candida albicans using synchrotron macro attenuated total reflectance-Fourier transform infrared (ATR-FTIR) microspectroscopy. We were able to characterise the pathogenic biofilms’ heterogeneous distribution, which is challenging to do using traditional techniques. Multivariate analyses revealed that the polysaccharides area (1200–950 cm−1) accounted for the most significant variance between biofilm samples, and other spectral regions corresponding to amides, lipids, and polysaccharides all contributed to sample variation. In general, this study will advance our understanding of microbial biofilms and serve as a model for future research on how to use synchrotron source ATR-FTIR microspectroscopy to analyse their variations and spatial arrangements.

In recent times, the popularity of adding value to under-utilized legumes have increased to enhance their use for human consumption. Acacia seed (AS) is an underutilized legume with over 40 edible species found in Australia. The study aimed to qualitatively characterize the chemical composition of 14 common edible AS species from 27 regions in Australia using mid-infrared (MIR) spectroscopy as a rapid tool. Raw and roasted (180 °C, 5, 7, and 9 min) AS flour were analysed using MIR spectroscopy. The wavenumbers (1045 cm−1, 1641 cm−1, and 2852–2926 cm−1) in the MIR spectra show the main components in the AS samples. Principal component analysis (PCA) of the MIR data displayed the clustering of samples according to species and roasting treatment. However, regional differences within the same AS species have less of an effect on the components, as shown in the PCA plot. Statistical analysis of absorbance at specific wavenumbers showed that roasting significantly (p < 0.05) reduced the compositions of some of the AS species. The results provided a foundation for hypothesizing the compositional similarity and/or differences among AS species before and after roasting.

Kakadu plum (KP; Terminalia ferdinandiana Exell, Combretaceae) is an emergent indigenous fruit originating from Northern Australia, with valuable health and nutritional characteristics and properties (e.g., high levels of vitamin C and ellagic acid). In recent years, the utilization of handheld NIR instruments has allowed for the in situ quantification of a wide range of bioactive compounds in fruit and vegetables. The objective of this study was to evaluate the ability of a handheld NIR spectrophotometer to measure vitamin C and ellagic acid in wild harvested KP fruit samples. Whole and pureed fruit samples were collected from two locations in the Kimberley region (Western Australia, Australia) and were analysed using both reference and NIR methods. The standard error in cross validation (SECV) and the residual predictive deviation (RPD) values were 1.81% dry matter (DM) with an RPD of 2.1, and 3.8 mg g−1 DM with an RPD of 1.9 for the prediction of vitamin C and ellagic acid, respectively, in whole KP fruit. The SECV and RPD values were 1.73% DM with an RPD of 2.2, and 5.6 mg g−1 DM with an RPD of 1.3 for the prediction of vitamin C and ellagic acid, respectively, in powdered KP samples. The results of this study demonstrated the ability of a handheld NIR instrument to predict vitamin C and ellagic acid in whole and pureed KP fruit samples. Although the RPD values obtained were not considered adequate to quantify these bioactive compounds (e.g., analytical quantification), this technique can be used as a rapid tool to screen vitamin C in KP fruit samples for high and low quality vitamin C.

Terminalia ferdinandiana (Kakadu plum), belonging to the family Combretaceae, is endemic to Australia and has a long history of traditional medicinal applications and food cuisine by the Australian Indigenous people. This study investigated the effects of maturity stages on the morphology, physicochemical parameters (total soluble solids (TSS), total acid content (TAC), and pH), soluble sugar profile and antioxidant capacity of Kakadu plum (KP) fruits that were wild harvested from different trees and classified into four different maturity stages (immature to mature). TSS and TAC were determined by standard assays/procedures, main sugars by UHPLC–MS/MS and antioxidant capacity (total phenolic content (TPC) and DPPH free radical scavenging capacity) by spectrophotometry. The results showed that soluble sugars (glucose, sucrose and fructose) ranging from 1.3 to 17.7% dry weight (DW), TSS (17.0–52.7% DW) and TAC (1.3–6.7% DW) increased with maturity. However, antioxidant capacity (TPC in the range of 7.4–21.9% DW and DPPH free radical scavenging capacity from 22 to 76% inhibition at the extract concentration of 20 g·L−1) did not follow the same trend as the one observed for soluble sugars, TSS and TAC. These differences were associated with the tree-to-tree variability as a consequence of the wild harvest condition. This study provides important information to both the KP industry and Indigenous enterprises regarding the selection of the appropriate maturity stage to harvest KP fruit to target for different markets (e.g., low-sugar vs. high-sugar fruit).

Muscle food products play a vital role in human nutrition due to their sensory quality and high nutritional value. One well-known challenge of such products is the high perishability and limited shelf life unless suitable preservation or processing techniques are applied. Thermal processing is one of the well-established treatments that has been most commonly used in order to prepare food and ensure its safety. However, the application of inappropriate or severe thermal treatments may lead to undesirable changes in the sensory and nutritional quality of heat-processed products, and especially so for foods that are sensitive to thermal treatments, such as fish and meat and their products. In recent years, novel thermal treatments (e.g., ohmic heating, microwave) and non-thermal processing (e.g., high pressure, cold plasma) have emerged and proved to cause less damage to the quality of treated products than do conventional techniques. Several traditional assessment approaches have been extensively applied in order to evaluate and monitor changes in quality resulting from the use of thermal and non-thermal processing methods. Recent advances, nonetheless, have shown tremendous potential of various emerging analytical methods. Among these, spectroscopic techniques have received considerable attention due to many favorable features compared to conventional analysis methods. This review paper will provide an updated overview of both processing (thermal and non-thermal) and analytical techniques (traditional methods and spectroscopic ones). The opportunities and limitations will be discussed and possible directions for future research studies and applications will be suggested.

Food fraud and adulteration is a major concern in terms of economic and public health. Multivariate methods combined with spectroscopic techniques have shown promise as a novel analytical strategy for addressing issues related to food fraud that cannot be solved by the analysis of one variable, particularly in complex matrices such distilled beverages. This review describes and discusses different aspects of whisky production, and recent developments of laboratory, in field and high throughput analysis. In particular, recent applications detailing the use of vibrational spectroscopy techniques combined with data analytical methods used to not only distinguish between brand and origin of whisky but to also detect adulteration are presented.

Animal origin food products, including fish and seafood, meat and poultry, milk and dairy foods, and other related products play significant roles in human nutrition. However, fraud in this food sector frequently occurs, leading to negative economic impacts on consumers and potential risks to public health and the environment. Therefore, the development of analytical techniques that can rapidly detect fraud and verify the authenticity of such products is of paramount importance. Traditionally, a wide variety of targeted approaches, such as chemical, chromatographic, molecular, and protein-based techniques, among others, have been frequently used to identify animal species, production methods, provenance, and processing of food products. Although these conventional methods are accurate and reliable, they are destructive, time-consuming, and can only be employed at the laboratory scale. On the contrary, alternative methods based mainly on spectroscopy have emerged in recent years as invaluable tools to overcome most of the limitations associated with traditional measurements. The number of scientific studies reporting on various authenticity issues investigated by vibrational spectroscopy, nuclear magnetic resonance, and fluorescence spectroscopy has increased substantially over the past few years, indicating the tremendous potential of these techniques in the fight against food fraud. It is the aim of the present manuscript to review the state-of-the-art research advances since 2015 regarding the use of analytical methods applied to detect fraud in food products of animal origin, with particular attention paid to spectroscopic measurements coupled with chemometric analysis. The opportunities and challenges surrounding the use of spectroscopic techniques and possible future directions will also be discussed.

The last two decades have witnessed an increasing interest in the use of the so-called rapid analytical methods or high throughput techniques. Most of these applications reported the use of vibrational spectroscopy methods (near infrared (NIR), mid infrared (MIR), and Raman) in a wide range of samples (e.g., food ingredients and natural products). In these applications, the analytical method is integrated with a wide range of multivariate data analysis (MVA) techniques (e.g., pattern recognition, modelling techniques, calibration, etc.) to develop the target application. The availability of modern and inexpensive instrumentation together with the access to easy to use software is determining a steady growth in the number of uses of these technologies. This paper underlines and briefly discusses the three critical pillars—the sample (e.g., sampling, variability, etc.), the spectra and the mathematics (e.g., algorithms, pre-processing, data interpretation, etc.)—that support the development and implementation of vibrational spectroscopy applications.

Food authenticity, traceability and provenance are emerging issues of major concern for consumers, industries and regulatory bodies worldwide. In addition, both food safety and security are an intrinsic component of food quality where the above issues are key in modern traceability and management systems. It has been reported that substitution of a high-quality species by less expensive ones might be a frequent practice in seafood products such as fish and shellfish. In this type of products, the source (e.g., origin) and identification of the species are complex. Although different countries have implemented strict regulations and labelling protocols, these issues still are of concern. This article briefly reviews some of the most recent applications of vibrational spectroscopy (near and mid infrared, Raman) combined with chemometrics to target some of these issues in the seafood and fish industries.

Farmers are increasingly demanding rapid, cost-effective, easy-to-use and non-destructive methods for monitoring changes in the physical and chemical characteristics of crops and plants from the early stages of crop development until harvest. Remote and proximal sensor tools have been used recently to monitor different aspects of cereal production (e.g., fertilization, crop diseases). Most of these tools are characterized as non-destructive, non-invasive and easy-to-use, and most of them are based in near-infrared (NIR) spectroscopy. This article reviews recent and potential applications for the use of proximal sensors based on NIR spectroscopy to monitor dry matter (DM), yield, nitrogen and diseases in different cereal crops.

Spectroscopic methods provide with very useful qualitative and quantitative information about the biochemistry and chemistry of antioxidants. Near infrared (NIR) and mid infrared (MIR) spectroscopy are considered as powerful, fast, accurate and non-destructive analytical tools that can be considered as a replacement of traditional chemical analysis. In recent years, several reports can be found in the literature demonstrating the usefulness of these methods in the analysis of antioxidants in different organic matrices. This article reviews recent applications of infrared (NIR and MIR) spectroscopy in the analysis of antioxidant compounds in a wide range of samples such as agricultural products, foods and plants.

In this study, the suitability of attenuated total reflection (ATR) mid-infrared (MIR) spectroscopy, combined with principal component analysis (PCA) and partial least squares (PLS) regression, was evaluated as a rapid analytical technique for the classification of sparkling wine style and quality. Australian sparkling wines (n = 139) comprising a range of styles (i.e., white, rosé, red, Prosecco and Moscato) were analyzed by ATR-MIR spectroscopy combined with multivariate data analysis. The MIR spectra of 50 sparkling white wines, produced according to four different production methods (i.e., Carbonation, Charmat, Transfer and Methodé Traditionelle) were also evaluated against: (i) quality ratings determined by an expert panel; and (ii) sensory attributes rated by a trained sensory panel. Wine pH, titratable acidity (TA), residual sugar (RS), alcohol and total phenolic content were also determined. The sparkling wine styles were separated on the PCA score plot based on their MIR spectral data; while the sparkling white wines showed separation based on production method, which strongly influenced the style and sensory properties of wine (i.e., the intensity of fruit versus yeast-derived characters). PLS calibrations of 0.73, 0.77, 0.82 and 0.86 were obtained for sweetness, tropical fruit, confectionary and toasty characters (on the palate), respectively.

The content of phenolic compounds determines the state of phenolic ripening of red grapes, which is a key criterion in setting the harvest date to produce quality red wines. Wine phenolics are also important quality components that contribute to the color, taste, and mouth feel of wines. Spectroscopic techniques (e.g., near and mid infrared) offer the potential to simplify and reduce the analytical time for a range of grape and wine analytes. It is this characteristic, together with the ability to simultaneously measure several analytes in the same sample at the same time, which makes these techniques very attractive for use in both industry and research. The objective of this mini review is to present examples and to discuss different applications of visible (VIS), near infrared (NIR) and mid infrared (MIR) to assess and measure phenolic compounds in grape and wines.

Raman spectroscopy, being able to provide rich information about the chemical composition of the sample, is gaining an increasing interest in the applications of food. Raman spectroscopy was used to analyze a set of wine samples (red and white) sourced from rarely studied traditional Bulgarian wines. One of the objectives of this study was to attempt the fast classification of Bulgarian wines according to variety and geographic origin. In addition, calibration models between phenolic compounds and Raman spectroscopy were developed using partial least squares (PLS) regression using cross-validation. Good calibration statistics were obtained for total phenolic compounds (by the Folin−Ciocalteu method) and total phenolic compounds and phenolic acids (spectrophotometrically at 280 nm) where the coefficient of determination (R2) and the standard error in the cross-validation (SECV) were 0.81 (474.2 mg/dm3 gallic acid), 0.87 (526.6 mg/dm3 catechin equivalents), and 0.81 (44.8 mg/dm3 caffeic equivalents), respectively. This study has demonstrated that Raman spectroscopy can be suitable for measuring phenolic compounds in both red and white wines.

The definition of the optimal temperature and its effects (either increasing or variations) during analysis of alcoholic beverages are of importance to develop protocols based in spectroscopy. Although several reports have been published on the use of spectroscopy combined with chemometrics to classify and authenticate alcoholic beverages (e.g., wine, tequila, whisky), few reports deal with issues related with the spectra collection (e.g., temperature, path length) and its effect on the classification performances. The objective of this study was to evaluate the effect of increasing temperature on both the UV-VIS spectra of whisky and on the classification results of the samples according to country of origin. Whisky samples from different commercial labels were analysed at different temperatures (25, 35, 45, 55 °C) using a UV-VIS instrument (Agilent, Cary 3500). Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) models based in cross validation were used to classify whisky samples according to scanning temperature and origin. The results of this study indicated that temperature did not affect the classification of whisky samples according to country of origin. Overall, well defined protocols need to be defined for routine use of these methods in research and by the industry.

There is no doubt that the current knowledge in chemistry, biochemistry, biology, and mathematics have led to advances in our understanding about food and food systems. However, the so-called reductionist approach has dominated food research, hindering new developments and innovation in the field. In the last three decades, food science has moved into the digital and technological era, inducing several challenges resulting from the use of modern instrumental techniques, computing and algorithms incorporated to the exploration, mining, and description of data derived from this complexity. In this environment, food scientists need to be mindful of the issues (advantages and disadvantages) involved in the routine applications of chemometrics. The objective of this opinion paper is to give an overview of the key issues associated with the implementation of chemometrics in food research and development. Please note that specifics about the different methodologies and techniques are beyond the scope of this review.

The presence of lipids in wort and beer are important due to their influence on yeast metabolism and beer quality. Barley lipids have long been considered to have adverse effects on beer quality where some long-chain fatty acids are associated with high flavour potential. In addition, beer foam stability can be influenced by the concentration of lipids as well as other factors such as hop acids (e.g., iso-α-acids), proteins, polysaccharides and the presence of metal ions (e.g., nickel). Lipids can also influence yeast protease activity as well as the production of ethanol. This review provides an overview of the effect of climate change on the chemical composition of barley in relation to lipids and the influence of lipids in the process of this raw material in order to produce beer.

Around the world, the food industry needs to maintain high quality and safety standards in order to satisfy consumers demand for healthy foods and to trace the origin of raw materials and products that are used during food manufacture. These objectives can be achieved by applying analytical methods and techniques that are able to provide information about composition, structure, physicochemical properties, and sensory characteristics of foods. Modern techniques and methods based on spectroscopy (near infrared (NIR), mid infrared (MIR), Raman) are highly desirable due to their low cost and easy to implement, and often requiring minimal sample preparation. This paper reviews some of the advantages and recent applications of hyperspectral and chemical imaging to discriminate and authenticate foods.