Application of Electronic Nose and Eye Systems for Detection of Adulteration in Olive Oil based on Chemometrics and Optimization Approaches

In this study, a combined system of electronic nose (e-nose) and computer vision was developed for the detection of adulteration in extra virgin olive oil (EVOO). The canola oil was blended with the pure EVOO to provide adulterations at four levels of 5, 10, 15, and 20%. Data collection was carried out using an e-nose system containing 13 metal oxide gas sensors, and a computer vision system. Applying principal component analysis (PCA) on the e-nose-extracted features showed that 93% and 92% of total data variance was covered by the three first PCs generated from Maximum Sensor Response (MSR), Area Under Curve (AUC) features, respectively. Cluster analysis verified that the pure and impure EVOO samples can be categorized by e-nose properties. PCA-Quadratic Discriminant Analysis (PCA-QDA) classified the EVOOs with an accuracy of 100%. Multiple Linear Regression (MLR) was able to estimate the adulteration percentage with the R2 of 0.8565 and RMSE of 2.7125 on the validation dataset. Moreover, factor analysis using Partial Least Square (PLS) introduced the MQ3 and TGS2620 sensors as the most important e-nose sensors for EVOO adulteration monitoring. Application of Response Surface Methodology (RSM) on RGB, HSV, L*,a*, and b* as color parameters of the EVOO images revealed that the color parameters are at their optimal state in the case up to 0.1% of canola impurity, where the obtained desirability index was 97%. Results of this study demonstrated the high capability of e-nose and computer vision systems for accurate, fast and non-destructive detection of adulteration in EVOO and detection of food adulteration may be more reliable using these artificial senses.&nbsp

Deep Learning to Detect and Classify the Purity Level of Luwak Coffee Green Beans

Luwak coffee (palm civet coffee) is known as one of the most expensive coffee in the world. In order to lower production costs, Indonesian producers and retailers often mix high-priced Luwak coffee with regular coffee green beans. However, the absence of tools and methods to classify Luwak coffee counterfeiting makes the sensing method’s development urgent. The research aimed to detect and classify Luwak coffee green beans purity into the following purity categories, very low (0-25%), low (25-50%), medium (50-75%), and high (75-100%). The classifying method relied on a low-cost commercial visible light camera and the deep learning model method. Then, the research also compared the performance of four pre-trained convolutional neural network (CNN) models consisting of SqueezeNet, GoogLeNet, ResNet-50, and AlexNet. At the same time, the sensitivity analysis was performed by setting the CNN parameters such as optimization technique (SGDm, Adam, RMSProp) and the initial learning rate (0.00005 and 0.0001). The training and validation result obtained the GoogLeNet as the best CNN model with optimizer type Adam and learning rate 0.0001, which resulted in 89.65% accuracy. Furthermore, the testing process using confusion matrix from different sample data obtained the best CNN model using ResNet-50 with optimizer type RMSProp and learning rate 0.0001, providing an accuracy average of up to 85.00%. Later, the CNN model can be used to establish a real-time, non-destructive, rapid, and precise purity detection system

Smart Gas Sensors: Materials, Technologies, Practical ‎Applications, and Use of Machine Learning – A Review

The electronic nose, popularly known as the E-nose, that combines gas sensor arrays (GSAs) with machine learning has gained a strong foothold in gas sensing technology. The E-nose designed to mimic the human olfactory system, is used for the detection and identification of various volatile compounds. The GSAs develop a unique signal fingerprint for each volatile compound to enable pattern recognition using machine learning algorithms. The inexpensive, portable and non-invasive characteristics of the E-nose system have rendered it indispensable within the gas-sensing arena. As a result, E-noses have been widely employed in several applications in the areas of the food industry, health management, disease diagnosis, water and air quality control, and toxic gas leakage detection. This paper reviews the various sensor fabrication technologies of GSAs and highlights the main operational framework of the E-nose system. The paper details vital signal pre-processing techniques of feature extraction, feature selection, in addition to machine learning algorithms such as SVM, kNN, ANN, and Random Forests for determining the type of gas and estimating its concentration in a competitive environment. The paper further explores the potential applications of E-noses for diagnosing diseases, monitoring air quality, assessing the quality of food samples and estimating concentrations of volatile organic compounds (VOCs) in air and in food samples. The review concludes with some challenges faced by E-nose, alternative ways to tackle them and proposes some recommendations as potential future work for further development and design enhancement of E-noses

Deteksi Campuran Kopi Reguler Dalam Kopi Luwak Menggunakan Metode Dielektrik dan Pengolahan Citra Digital

Kopi adalah bahan baku minuman yang banyak dikonsumsi dan penting bagi perekonomian negara produsen kopi. Salah satu jenis kopi yang dikenal mahal dan langka adalah kopi luwak (palm civet coffee) sehingga rawan dicampur dengan kopi reguler. Deteksi campuran kopi reguler dalam kopi luwak secara konvensional menggunakan analisis kimia bersifat destruktif, mahal, membutuhkan preparasi sampel dan waktu lama. Saat ini, konsumsi ekstrak green beans menjadi trend baru karena dianggap rendah kalori. Pengukuran total fenol green beans membantu mengukur aktivitas antioksidan. Selain itu, kopi memiliki rasa asam yang identik dengan pH. Trend mengonsumsi ekstrak green beans kopi membuat pengukuran pH dilakukan karena banyak konsumen kopi sensitif terhadap keasaman kopi terutama kopi arabika. Hal ini memberi peluang perancangan peralatan sederhana, cepat, akurat, dan non destruktif untuk menduga persentase campuran kopi reguler dalam kopi luwak, total fenol, dan pH. Perancangan alat penduga persentase campuran kopi reguler dalam kopi luwak, total fenol, dan pH dapat menggunakan metode dielektrik dan metode pengolahan citra digital. Metode dielektrik untuk mengakuisisi data biolistrik biji kopi dan metode pengolahan citra untuk mengakuisisi data citra. Pendugaan persentase campuran kopi reguler dalam kopi luwak, total fenol, dan pH perlu integrasi dengan metode untuk mempelajari pola data seperti Jaringan Saraf Tiruan (JST). Penelitian ini dilakukan dengan mencampur green beans kopi luwak dan kopi reguler pada presentase 0% kopi luwak, 10% kopi luwak, 30% kopi luwak, 40% kopi luwak, 50% kopi luwak, 70% kopi luwak, 90% kopi luwak, dan 100% kopi luwak. Hasil penelitian menunjukkan 5 fitur terpilih sebagai input JST data biolistrik yaitu impedansi (Z), induktansi seri (Ls), induktansi paralel (Lp), resistansi seri (Rs), dan resistansi paralel (Rp) menggunakan metode correlation attribute evaluator. Topologi JST terpilih untuk data biolistrik yaitu 5 – 40 – 40 – 3 (5 input, 40 node hidden layer 1, 40 node hidden layer 2, 3 output) dengan learning rate 0,1 dan momentum 0,9 fungsi pembelajaran trainlm, fungsi aktivasi tansig pada hidden layer dan output layer. Topologi terpilih menghasilkan R pelatihan 0,98902; R validasi 0,98204 dan MSE pelatihan 0,0099; MSE validasi 0,0479. Hasil penelitian deteksi pemalsuan kopi luwak menunjukkan 5 fitur terpilih sebagai input JST data citra yaitu lain red sum mean, value sum mean, S_HSL sum mean, blue variance, dan hue variance menggunakan metode ReliefF. Data citra menggunakan JST menghasilkan topologi terpilih yaitu 5 – 30 – 40 – 3 (5 input, 30 node hidden layer 1, 40 node hidden layer 2, 3 output) dengan learning rate 0,1 dan momentum 0,5 fungsi pembelajaran trainlm, fungsi aktivasi tansig pada hidden layer dan purelin pada output layer. Topologi terpilih menghasilkan R pelatihan 0,99502; R validasi 0,97933 dan MSE pelatihan 00085; MSE validasi 0,0442. Hasil penelitian menunjukkan MSE validasi metode dielektrik sedikit lebih rendah dibandingkan metode pengolahan citra digital. Hal ini membuat kedua metode non destruktif ini berpotensi sebagai sensor dalam menduga persentase campuran kopi reguler dalam kopi luwak, total fenol, dan pH

Emergent quality issues in the supply of Chinese medicinal plants: A mixed methods investigation of their contemporary occurrence and historical persistence

Quality issues that emerged centuries ago in Chinese medicinal plants (CMP) were investigated to explore why they still persist in an era of advanced analytical testing and extensive legislation so that a solution to improve CMP quality could be proposed. This is important for 85% of the world’s population who rely on medicinal plants (MP) for primary healthcare considering the adverse events, including fatalities that arise from such quality issues. CMP are the most prevalent medicinal plants globally. This investigation used mixed-methods, including 15 interviews with CMP expert key informants (KI), together with thematic analysis that identified the main CMP quality issues, why they persisted, and informed solutions. An unexplained case example, Eleutherococcus nodiflorus (EN), was analysed by collection of 106 samples of EN, its known toxic adulterant Periploca sepium (PS), and a related substitute, Eleutherococcus senticosus (ES), across mainland China, Taiwan and the UK. Authenticity of the samples was determined using High-performance thinlayer chromatography. Misidentification, adulteration, substitution and toxicity were the main CMP quality issues identified. Adulteration was found widespread globally with 57.4% EN found authentic, and 24.6% adulterated with cardiotoxic PS, mostly at markets and traditional pharmacies. The EN study further highlighted that the reason CMP quality issues persisted was due to the laboratory-bound nature of analytical methods and testing currently used that leave gaps in detection throughout much of the supply chain. CMP quality could be more effectively tested with patented analytical technology (PAT) and simpler field-based testing including indicator strip tests. Education highlighting the long-term economic value and communal benefit of delivering better quality CMP to consumers was recommended in favour of the financial motivation for actions that lead to the persistence of well-known and recurrent CMP quality issues

Target and Non-Target Approaches for Food Authenticity and Traceability

Over the last few years, the subject of food authenticity and food fraud has received increasing attention from consumers and other stakeholders, such as government agencies and policymakers, control labs, producers, industry, and the research community. Among the different approaches aiming to identify, tackle, and/or deter fraudulent practices in the agri-food sector, the development of new, fast, and accurate methodologies to evaluate food authenticity is of major importance. This book, entitled “Target and Non-Target Approaches for Food Authenticity and Traceability”, gathers original research and review papers focusing on the development and application of both targeted and non-targeted methodologies applied to verify food authenticity and traceability. The contributions regard different foods, among which some are frequently considered as the most prone to adulteration, such as olive oil, honey, meat, and fish. This book is intended for readers aiming to enrich their knowledge through reading contemporary and multidisciplinary papers on the topic of food authentication

Following cocoa beans to chocolate : The search for intrinsic characteristics

The assessment of cocoa’s natural characteristics can be used to link cocoa beans and chocolate. Establishing a link between the raw material and the finished product is complicated not only because of complex characteristics of the supply chain but also because of the technology involved in the production and the composition of the ingredients. One may wonder why a link between raw material and the finished product is relevant. Nowadays, more and more attention is given to sustainability, pushing the cocoa manufacturers to take into account social, economic and environmental issues while producing. As a consequence, the demand in cocoa-importing countries for certified sustainable cocoa has increased considerably and is expected to show continuous growth over the next years. Moreover, more consumers have become increasingly aware of the existence of different cocoa varieties and their origins, and the market of specialty chocolates such as chocolates with single-origin bean, organic and fair-trade chocolate has largely grown in the last decades. The aforementioned trends in the chocolate sector and the growing concerns regarding food quality and safety led to a growing effort in the implementation of traceability systems. This trend has facilitated the need to verify and guarantee the origin of the cocoa beans along with the cocoa-chocolate supply chain and to establish a link between raw material and the finished product. For these reasons, the main objective of this thesis is to discover cocoa beans’ traits in terms of the botanical and geographical origin carried along the cocoa–chocolate supply chain. Compositional characteristics of botanical and geographical origin of cocoa beans after fermentation and drying, after manufacturing chocolate and during chocolate consumption were analysed. This information can be used to derive a link between raw material and the finished product, which in turn can be used to support traceability systems. To investigate the cocoa-chocolate botanical and geographical origin information, markers related to intrinsic properties were used: volatile and non-volatile characteristics. The latter include small non-volatile compounds, elemental composition, isotope ratios and hyperspectral profiles. The reflectance of the cocoa beans origin along the supply chain is investigated starting from the consumer perspective with the analysis of the nosespace (NS) profile of consumers eating chocolates manufactured from beans of different origins. Moving back along the supply chain, the possibility to extract botanical and geographical traits from both volatile and non-volatile profiles is further tested in chocolates available in the supermarket. To extract more information cocoa beans and corresponding chocolates to extract raw material markers in a finished product analysing their volatile, elemental and isotopic compositional traits. Finally, the raw material analysis completes the assessment of cocoa beans origin traits along the supply chain. Regarding the botanical traits carried along the supply chain, the volatile intrinsic characteristic showed the potential to track and trace raw material origin along the entire supply chain. It was possible to identify typical volatile compounds of the raw material in chocolate bar and chocolate during chocolate consumption. VOCs were found to be the most robust markers that were carried from cocoa beans to consumer products, revealing a constant shift/change between the raw materials and the finished products. Potential markers (i.e. acetic acid) were detected to reveal botanical traits from raw material to chocolate to chocolate consumption. However, in general, it was difficult to identify specific individual markers carried along the supply chain highlighting the fact that the botanical traits are more related to a general volatile pattern. The same is valid for the small non-volatile compounds analysed in chocolate. Interestingly, when analysing the non-volatile compositional traits, the botanical trend explained the samples overlapping according to the geographical origin. This occurred despite the impact of the processing step or the ingredient added on the origin expression. The brand influence was confirmed also when the elemental and stable isotope fingerprints of cocoa beans and chocolates were compared. Stable isotope signatures appear less sufficient for tracing the characteristics of cocoa in chocolate products without previously estimating the isotope signature of all the ingredients reducing the possibility to use them as origin markers. Our results support the botanical traits’ influence as highlighted for the volatile and non-volatile profiles of chocolate and the volatile NS profile of chocolate during consumption and it indicates that intrinsic features of the beans are retained after processing and even during consumption. Regarding the geographical origin traits carried along the supply chain, volatile compounds reflected the geographical trait from cocoa beans to consumers. Within the non-volatile compositional traits Cr, Fe and Cd appeared to be distinct geographical markers although they are susceptible to environmental contamination. However, along the supply chain, the geographical traits were hidden by other factors. During chocolate consumption, geographical discrimination was possible only within each botanical group. In chocolate, the geographical information was evidently contained by the volatile compounds. However, we highlighted an interference with botanical and brand traits. This was particularly clear when analysing the small non-volatile compounds. Only when reducing the influence of the brands, it becomes clear that the samples are spread according to the three origins. Regarding the raw material, the impact of the geographical origin on the volatile and hyperspectral profile of cocoa beans is influenced by the variability related to differences in fermentation and drying within a country and between countries. Despite these interferences, a similar trend both in cocoa beans and in chocolates is visible for certain compounds, making them usable as cocoa-chocolate linking markers. The evidence from this study suggests that volatile and non-volatile compositional traits of cocoa and cocoa products can be used to verify and/or follow origin traits along the supply chain and link raw material and the finished product. However, more research is needed on how to reduce botanical and geographical interaction and improve the product characterisation along the supply chain. Within the compositional traits that were measured, the volatile profile is the most suitable for gathering information at the beginning of the production and at different stages in the supply chain

Establishment of authenticity and typicality of sugarcane from Madeira Island, and its derivative sugarcane honey, based on molecular, chemical and chemometric analysis

Food authenticity has become a worldwide concern, foresting the importance of the development of strategies to guarantee the quality and safety of food products. The purpose of this doctoral thesis was the establishment of the typicality and authenticity of sugarcane cultivars from Madeira Island, and its main derivative, sugarcane honey. The followed strategy was based on the identification of typical volatile, sugars and furan derivatives profiles in sugarcane honey processed by the certified producer Fábrica Mel-de-Cana Ribeiro Sêco, and compare it with sugarcane-based syrups from non-certified regional producers and from producers from different geographical regions. Also, the typical volatile profile throughout all stages of sugarcane honey processing were identified during four years, allowing the evaluation of influence of each stage in the formation of its typicality. In addition, the typical volatile profile of all sugarcane cultivars currently cultivated in Madeira Island were identified, namely amarela, canica, roxa, radiada, verde and violeta. Different analytical methodologies based on effective extractive techniques and high-resolution chromatographic methods were successfully developed, optimized and validated, namely solid-phase microextraction combined with gas chromatography-mass spectrometry for the volatile profile, microextraction by packed sorbent combined with ultra-high performance liquid chromatography with diode-array detector for the furan derivatives profile, and ultrasound-assisted liquid-liquid extraction combined with liquid chromatography with a refractive index detector for sugars profile. Furthermore, an innovative and powerful Quality-by-Design approach was selected for development of the methodologies used for quantitation of furan derivatives and SGs. An exhaustive chemometric analysis based on one-way ANOVA, principal component analysis, partial least squares, linear discriminant analysis and hierarchical clustering analysis was successfully applied to recognize the typical profiles of sugarcane honey. This doctoral thesis represents the first attempt to define the typicality, authenticity and traceability of sugarcane honey from Madeira Island, providing a highly valuable information to support its European Union certification.A autenticidade alimentar tornou-se uma preocupação mundial, evidenciando a importância do desenvolvimento de estratégias para garantir a qualidade e segurança dos produtos alimentares. O objetivo do presente doutoramento foi estabelecer a tipicidade e autenticidade das cultivares de cana de-açúcar da Ilha da Madeira, e do seu principal derivado, o mel-de-cana. A estratégia seguida baseou-se na identificação de perfis típicos de voláteis, açúcares e derivados do furano no mel-de-cana processado pela empresa certificada Fábrica Mel-de-Cana Ribeiro Sêco, e compará-lo com xaropes de cana-de-açúcar de produtores regionais não certificados e produtores de diferentes regiões geográficas. Também foram identificados os perfis voláteis típicos ao longo de todas as etapas de processamento do mel-de-cana, permitindo avaliar a influência de cada etapa na formação de sua tipicidade. Além disso, foram identificados os perfis voláteis típicos de todas as cultivares de cana-de-açúcar atualmente cultivadas na Ilha da Madeira, nomeadamente amarela, canica, roxa, radiada, verde e violeta. Diferentes metodologias analíticas baseadas em técnicas extrativas e métodos cromatográficos foram desenvolvidos, otimizados e validados com sucesso, nomeadamente a microextração em fase sólida combinada com cromatografia gasosa e espectrometria de massa para perfil volátil, microextração por sorvente empacotado combinado com cromatografia líquida de ultra-alto desempenho com detetor díodos para perfil de derivados de furano, e extração líquido-líquido assistida por ultrassom combinada com cromatografia líquida com detetor de índice de refração para perfil de açúcares. Além disso, uma abordagem inovadora e poderosa de Quality-by-Design foi selecionada para o desenvolvimento das metodologias usadas para quantificação de derivados de furano e açúcares. A análise quimiométrica exaustiva baseada em ANOVA unilateral, análise de componentes principais, mínimos quadrados parciais, análise discriminante linear e análise de agrupamento hierárquico foi aplicada com sucesso para o reconhecimento de perfis típicos de mel-de-cana. O presente doutoramento representa a primeira tentativa de definir a tipicidade, autenticidade e rastreabilidade do mel-de-cana, fornecendo uma informação altamente valiosa para apoiar a sua certificação na União Europeia