Multiangle discrimination of geographical origin of rice based on analysis of mineral elements and characteristic volatile components

Geographical origin identification of Khao Dawk Mali 105 rice using combination of FT-NIR spectroscopy and machine learning algorithms

The mislabelled Khao Dawk Mali 105 rice coming from other geographical region outside the Thung Kula Rong Hai region is extremely profitable and difficult to detect; to prevent retail fraud (that adversely affects both the food industry and consumers), it is vital to identify geographical origin. Near infrared spectroscopy can be used to detect the specific content of organic moieties in agricultural and food products. The present study implemented the combinatorial method of FT-NIR spectroscopy with chemometrics to identify geographical origin of Khao Dawk Mali 105 rice. Rice samples were collected from 2 different region including the north and northeast of Thailand. NIR spectra data were collected in range of 12,500 - 4,000 cm-1 (800-2,500 nm). Five machine learning algorithms including linear discriminant analysis (LDA), partial least squares discriminant analysis (PLS-DA), C-support vector classification (C-SVC), backpropagation neural networks (BPNN), hybrid principal component analysis-neural network (PC-NN) and K-nearest neighbors (KNN) were employed to classify NIR data of rice samples with full wavelength and selected wavelength by Extremely Randomized Trees (Extra trees) algorithm. Based on the findings, geographical origin of rice could be specified quickly, cheaply, and reliably using combination of NIRS and machine learning. All models creating by full wavelength and selected wavelength exhibited accuracy between 65 and 100 % for identifying geographical region of rice. It was proven that NIR spectroscopy may be used for the quick and non-destructive identification of geographical origin of Khao Dawk Mali 105 rice.

Simultaneous determination of subspecies and geographic origins of 110 rice cultivars by microsatellite markers

Rice varieties of different subspecies types (indica rice and japonica rice) across various geographical origins (Hunan, Jiangsu, and Northeast China) were monitored using microsatellite markers (simple sequence repeats, SSR). 110 representative rice cultivars were collected from the main crop areas. Multiple methods including clustering analysis (neighbor-joining (NJ) method, unweighted pair-group method with arithmetic mean (UPGMA) method), principal component analysis (PCA) and model-based grouping were applied. The study revealed that 25 pairs of SSR markers exhibited a broad range of polymorphism information content (PIC) values, ranging from 0.240 to 0.830. Furthermore, our study successfully achieved a higher overall mean correct rate of 99.09% in determining the geographical origin of rice. Simultaneously, it accurately classified indica rice and japonica rice. These findings are significant as they provide an SSR fingerprint of 110 high-quality rice cultivars, serving as a valuable scientific resource for the detection of rice adulteration and traceability of its origin.

Antioxidant activities, phenolic compounds, and mineral composition of seed from Acacia retinodes, A. Provincialis and A. Tenuissima

Seeds of the species Acacia retinodes, A. provincialis, and A. tenuissima) from different growing locations were analysed for their mineral composition, free and bound polyphenols, and flavonoids. Previous research has studied these compounds in only a limited number of Acacia species, and only one study reports significant differences between three species. All species were rich in potassium (353 - 427 mg/100 g), sodium (14 - 240 mg/100 g) and iron (7 - 8 mg/100 g). The free polyphenol extracts of all species had higher total phenolic content, total flavonoid content and antioxidant activities than their bound counterparts, indicating the possibility of higher bioavailability than the bound polyphenol extracts. The predominant phenolic compounds found in the Acacia polyphenol seed extracts were 6-Hydroxy-2-methylindole and 2,2'-Methylenebis(6-tert-butyl-methylphenol), though no phenolic compounds were identified in the bound extracts of A. retinodes Grampians and A. provincialis Tarrington. Other compounds identified in the seed extracts include sucrose, d-fructofuranose and d-pinitol.

Role of conformation transition of high acyl gellan in the design of double network hydrogels

Double network hydrogels (DNs) with excellent strength and toughness have been preliminarily applied in the preparation of artificial foods. To evaluate the effect of conformation transition of ductile polymers on the physicochemical properties of DNs, we firstly prepared agarose (AR)/high acyl gellan (HAG) DNs and investigated their mechanical properties, and then calcium ion (Ca²⁺) was introduced into optimized AR/HAG DNs to regulate the conformation of ductile chains (HAG) for further increasing their mechanical properties. The mechanical strength of the optimized AR/HAG gel is 5 times and 2 times that of AR and HAG gel, respectively. Compared with adding Ca²⁺ method, immersing Ca²⁺ solution endowed optimized DNs with 5-fold increase in mechanical strength, outstanding textural properties and lower swelling ratio, which was attributed to the extended conformation of ductile chains. Furthermore, the obtained DNs were reminiscent of beef omasum based on their physicochemical properties. Optimized AR/HAG DNs after immersing in 2 wt% CaCl₂ solution exhibited comparable texture properties with beef omasum by three correlation analysis methods and sensory evaluation, providing a new strategy to fabricate biomimetic food with high chewiness by regulating the conformation of ductile polymers in DNs.

Combination of light stable isotopic and elemental signatures in Thai Hom Mali rice with chemometric analysis

This study aims to discriminate the geographical origin of Thai Hom Mali rice in order to protect consumers from mislabeling. Stable isotopic and elemental compositions (δ¹³C, δ¹⁵N, δ¹⁸O, As, Br, K, Mn, Rb, and Zn) of Thai Hom Mali rice cultivated inside and outside the Thung Kula Rong-Hai Plain were combined with chemometric analysis, linear discriminant analysis (LDA) and partial least squares-discriminant analysis (PLS-DA). The 9 variables combined with LDA can distinguish Thai Hom Mali rice cultivated inside and outside the Thung Kula Rong-Hai Plain with 98.2 % correct classification and 94.6 % cross-validation. The efficiency in using stable isotopic and elemental compositions combined with soft PLS-DA was achieved 100 % in discrimination of Thai Hom Mali rice cultivated inside and outside the Thung Kula Rong-Hai Plain. The variables δ¹⁵N, Br, K, and Rb were key parameters to discriminate the geographical origin of Thai Hom Mali rice.

Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), a Useful Tool in Authenticity of Agricultural Products' and Foods' Origin

Fraudulent practices are the first and foremost concern of food industry, with significant consequences in economy and human's health. The increasing demand for food has led to food fraud by replacing, mixing, blending, and mislabeling products attempting to increase the profits of producers and companies. Consequently, there was the rise of a multidisciplinary field which encompasses a large number of analytical techniques aiming to trace and authenticate the origins of agricultural products, food and beverages. Among the analytical strategies have been developed for the authentication of geographical origin of foodstuff, Inductively Coupled Plasma Mass Spectrometry (ICP-MS) increasingly dominates the field as a robust, accurate, and highly sensitive technique for determining the inorganic elements in food substances. Inorganic elements are well known for evaluating the nutritional composition of food products while it has been shown that they are considered as possible tracers for authenticating the geographical origin. This is based on the fact that the inorganic component of identical food type originating from different territories varies due to the diversity of matrix composition. The present systematic literature review focusing on gathering the research has been done up-to-date on authenticating the geographical origin of agricultural products and foods by utilizing the ICP-MS technique. The first part of the article is a tutorial about food safety/control and the fundaments of ICP-MS technique, while in the second part the total research review is discussed.

Multi-Element Analysis and Origin Discrimination of Panax notoginseng Based on Inductively Coupled Plasma Tandem Mass Spectrometry (ICP-MS/MS)

Panax notoginseng is an important functional health product, and has been used worldwide because of a wide range of pharmacological activities, of which the taproot is the main edible or medicinal part. However, the technologies for origin discrimination still need to be further studied. In this study, an ICP-MS/MS method for the accurate determination of 49 elements was established, whereby the instrumental detection limits (LODs) were between 0.0003 and 7.716 mg/kg, whereas the quantification limits (LOQs) were between 0.0011 and 25.7202 mg/kg, recovery of the method was in the range of 85.82% to 104.98%, and the relative standard deviations (RSDs) were lower than 10%. Based on the content of multi-element in P. notoginseng (total of 89 mixed samples), the discriminant models of origins and cultivation models were accurately determined by the neural networks (prediction accuracy was 0.9259 and area under ROC curve was 0.9750) and the support vector machine algorithm (both 1.0000), respectively. The discriminant models established in this study could be used to support transparency and traceability of supply chains of P. notoginseng and thus avoid the fraud of geographic identification.

Tracing the Origins of Blueberries by Their Mineral Element Contents and 87Sr/86Sr Ratios

This study investigated the feasibility of using the mineral element contents and ⁸⁷Sr/⁸⁶Sr ratios of blueberries to trace their origins. The contents of 28 mineral elements, including K, Al, and Mg, were determined in 104 blueberry samples from three blueberry-producing areas in Guizhou Province, China. Also determined were both the ⁸⁷Sr/⁸⁶Sr ratios in 48 blueberry samples as well as the type of soil in which the blueberries were grown. Cluster analysis of ⁸⁷Sr/⁸⁶Sr ratios, stepwise discriminant analysis of mineral element contents, and combined discriminant analyses of ⁸⁷Sr/⁸⁶Sr ratios and mineral element contents were done. The results show that ten elements (Ca, Cr, Cs, Mg, Mn, P, Rb, Sb, Th, and Y) were selected by linear discriminant analysis, which could be used to establish the provenance traceability model of blueberries in Guizhou. The original accuracy of linear discriminant analysis was 89.4%, and the accuracy of cross-validation was 83.6%. When ⁸⁷Sr/⁸⁶Sr ratios were used for tracing, the accuracies of both the original discrimination and the cross-validation were 81.3% as determined by linear discriminant analysis, and the accuracy rate of origin discrimination was 81.25% by cluster analysis. The results of combined discrimination were the best: the accuracy of the original discrimination was 95.8%, and the accuracy of cross-validation was 93.8%. Mineral element contents and ⁸⁷Sr/⁸⁶Sr ratios can be used to trace the origins of blueberries, and combining them can significantly improve the discrimination accuracy. Fisher linear discriminant analysis had the greatest accuracy followed by cluster analysis, while principal component analysis was relatively poor in the research of Guizhou blueberry origin traceability.

Tracing the Geographical Origin of Thai Hom Mali Rice in Three Contiguous Provinces of Thailand Using Stable Isotopic and Elemental Markers Combined with Multivariate Analysis

Rice is a staple food for more than half of the world’s population. The discrimination of geographical origin of rice has emerged as an important issue to prevent mislabeling and adulteration problems and ensure food quality. Here, the discrimination of Thai Hom Mali rice (THMR), registered as a European Protected Geographical Indication (PGI), was demonstrated. Elemental compositions (Mn, Rb, Co, and Mo) and stable isotope (δ¹⁸O) in the rice were analyzed using inductively coupled plasma mass spectrometry (ICP-MS) and elemental analyzer isotope ratio mass spectrometry (EA-IRMS), respectively. The recoveries and precisions of all elements were greater than 98% and lower than 9%, respectively. The analytical precision (±standard deviation) was below ±0.2‰ for δ¹⁸O measurement. Mean of Mn, Rb, Co, Mo, and δ¹⁸O levels was 14.0 mg kg⁻¹, 5.39 mg kg⁻¹, 0.049 mg kg⁻¹, 0.47 mg kg⁻¹, and 25.22‰, respectively. Only five valuable markers combined with radar plots and multivariate analysis, linear discriminant analysis (LDA) could distinguish THMR cultivated from three contiguous provinces with correct classification and cross-validation of 96.4% and 92.9%, respectively. These results offer valuable insight for the sustainable management and regulation of improper labeling regarding geographical origin of rice in Thailand and other countries.

Multielement Principal Component Analysis and Origin Traceability of Rice Based on ICP-MS/MS

In this experiment, inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) was used to determine the content of 30 elements in rice from six places of production and to explore the relationship between the multielement content in rice and the producing area. The contents of Ca, P, S, Zn, Cu, Fe, Mn, K, Mg, Na, Ge, Sb, Ba, Ti, V, Se, As, Sr, Mo, Ni, Co, Cr, Al, Li, Cs, Pb, Cd, B, In, and Sn in rice were determined by ICP-MS/MS in the SQ and MS/MS mode. By passing H2, O2, He, and NH3/He reaction gas into the ICP-MS/MS, respectively, the interference was eliminated by means of in situ mass spectrometry and mass transfer. The detection limit of each element was 0.0000662–0.144 mg/kg, and the limit of quantification was in the range of 0.000221–0.479 mg/kg, the linear correlation coefficient was greater or equal to 0.9987 (R2 ≥ 0.9987), and the detection results had low detection limit and great linear regression. Recovery of the method was in the range of 80.6% to 110.5% with spike levels of 0.10–100.00 mg/kg, and relative standard deviations were lower than 10%. For the multielement content of rice from different producing areas, the principal component factor analysis can get six principal component factors, 87.878% cumulative contribution rate, and the distribution of the principal component scores of each element and different producing areas. Based on the multielement content and cluster analysis, the samples were accurately divided into two major categories and six subcategories according to the places of production, which proved that there was a significant correlation between the multielement content in rice and the place of production, so that the place of rice origin can be traced.

E-sensing and nanoscale-sensing devices associated with data processing algorithms applied to food quality control: a systematic review

Devices of human-based senses such as e-noses, e-tongues and e-eyes can be used to analyze different compounds in several food matrices. These sensors allow the detection of one or more compounds present in complex food samples, and the responses obtained can be used for several goals when different chemometric tools are applied. In this systematic review, we used Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, to address issues such as e-sensing with chemometric methods for food quality control (FQC). A total of 109 eligible articles were selected from PubMed, Scopus and Web of Science. Thus, we predicted that the association between e-sensing and chemometric tools is essential for FQC. Most studies have applied preliminary approaches like exploratory analysis, while the classification/regression methods have been less investigated. It is worth mentioning that non-linear methods based on artificial intelligence/machine learning, in most cases, had classification/regression performances superior to non-liner, although their applications were seen less often. Another approach that has generated promising results is the data fusion between e-sensing devices or in conjunction with other analytical techniques. Furthermore, some future trends in the application of miniaturized devices and nanoscale sensors are also discussed.

Study on the origin traceability of Tibet highland barley (Hordeum vulgare L.) based on its nutrients and mineral elements

The potential of traceability by nutrients and mineral elements in highland barley (Hordeum vulgare L.) from five cities in Tibet were investigated. The results showed that there were significant differences in nutrients and mineral elements in highland barley from different regions (P < 0.05). The original classification accuracy of linear discriminant analysis (LDA) was 78.3%, and the discrimination accuracy of training set samples based on partial least-squares discriminant analysis (PLS-DA) model was over 65%. The results of correlation analysis show that five elements (Fe, Zn, K, Mn and P) in highland barley are related to the concentration of elements in soil, while three elements (Ca, Cu and Mg) in highland barley have no obvious correlation with soil, because the special natural environment in Tibet affecting the growth of highland barley. This indicates that the origin traceability of highland barley can be achieved by measuring its nutrients and mineral elements.

Determination of Geographical Origin of Wuchang Rice with the Geographical Indicator by Multielement Analysis

The study aims to investigate whether the multielement analysis result can be used as a fingerprint to identify the geographical origin of Wuchang rice. The element contents of rice and soil samples from three regions in China (Wuchang, Qiqihar, and Jiamusi) were analyzed. The concentrations of 16 elements (Na, Mg, Al, K, Ca, V, Mn, Fe, Co, Cu, Zn, As, Rb, Sr, Cd, and Pb) in 194 rice samples and 112 soil samples from the harvest season in 2013 and 2014 were determined. The analysis of variance and linear discriminant analysis were performed to analyze the variation among regions and rice genotypes and classify the geographical origins of rice. Only the element of Cu showed significant differences among different genotypes. In the discriminant analysis, the overall correct identification rates of the rice samples obtained in 2013 and 2014 were, respectively, 96.6% and 89.6% and the overall correct identification rate for Wuchang rice reached 100%.