Geographical Origin Research Articles

Can plants build their niche through modulation of soil microbial activities linked with nitrogen cycling? A test with Arabidopsis thaliana.

In natural systems, different plant species have been shown to modulate specific nitrogen (N) cycling processes so as to meet their N demand, thereby potentially influencing their own niche. This phenomenon might go beyond plant interactions with symbiotic microorganisms and affect the much less explored plant interactions with free-living microorganisms involved in soil N cycling, such as nitrifiers and denitrifiers. Here, we investigated variability in the modulation of soil nitrifying and denitrifying enzyme activities (NEA and DEA, respectively), and their ratio (NEA : DEA), across 193 Arabidopsis thaliana accessions. We studied the genetic and environmental determinants of such plant-soil interactions, and effects on plant biomass production in the next generation. We found that NEA, DEA, and NEA : DEA varied c. 30-, 15- and 60-fold, respectively, among A. thaliana genotypes and were related to genes linked with stress response, flowering, and nitrate nutrition, as well as to soil parameters at the geographic origin of the analysed genotypes. Moreover, plant-mediated N cycling activities correlated with the aboveground biomass of next-generation plants in home vs away nonautoclaved soil, suggesting a transgenerational impact of soil biotic conditioning on plant performance. Altogether, these findings suggest that nutrient-based plant niche construction may be much more widespread than previously thought.

Identification of Cortex Cercis chinensis Decoction Pieces from Different Growth Origins Using Raman Spectroscopy

The complexity of traditional Chinese medicine (TCM) components and the time-consuming of traditional detection methods make it necessary and meaningful to establish rapid and efficient identification techniques. This study explores the potential of Raman spectroscopy, a non-destructive technique offering details of molecular structure, for rapid and accurate identification. Cortex Cercis chinensis (CCC) decoction pieces from diverse geographical origins, Anhui, Sichuan, Zhejiang, and Hubei, were collected and analyzed using Raman spectroscopy at 785 nm, and the Raman characteristic peaks were analyzed. MATLAB software was employed to analyze the similarity between the spectra of CCC decoction pieces, and the original Raman spectral data were transformed into first and second derivative spectra. The results revealed distinct Raman spectral characteristics of carbohydrates and glycosidic bonds (characteristic peaks at 480, 531, 549, 873, 946 and 1086 cm−1). The correlation coefficients of the all the four samples from different origins ranged from 0.9625 to 0.9912, while the coincidence coefficients ranged from 0.9602 to 0.9934. The first and second derivative demonstrated significantly different peaks within specific ranges, 180–200, 280–380, and 680–740 cm−1 for first derivatives, 160–300, 340–400 and 420–480 cm−1 for second derivatives. These obvious differences in first and second derivative spectra of Raman spectra of CCC decoction pieces demonstrated the different growth origins. In conclusion, the study demonstrated the ability of Raman spectroscopy to accurately differentiate CCC decoction pieces from different geographical growth origin. These findings provided a basis for further application of Raman spectra characteristic fingerprints to be used in quality control for rapid identification of the quality and origin of TCM raw materials.

Genomic and epidemiological evidence for the emergence of a L. infantum/L. donovani hybrid with unusual epidemiology in northern Italy.

Leishmania (L.) infantum is one of the main causative agents of animal and human leishmaniasis across many endemic areas in South America, Europe, North Africa, and Asia. Despite its clinical significance, little is known about the genetic diversity of L. infantum circulating in a given endemic area. Here, we investigate this important open question by applying a comparative genomics approach to seven L. infantum isolates from different hosts and Italian regions, including the northern part of the country (Emilia-Romagna, RER), Sicily, and Sardinia, as an initial attempt to explore the breadth of parasite genetic heterogeneity in Italy. Additionally, microsatellite analysis was carried out to compare the isolates from RER with other 70 L. infantum strains from the same region as well as 65 strains belonging to the L. donovani complex from other countries. We revealed important karyotypic instability and identified strain-specific changes in gene dosage, which affected important virulence factors such as amastins and surface antigen-like proteins. Single nucleotide polymorphism-based clustering analysis of these genomes together with over 80 publicly available L. infantum and L. donovani genomes placed the Italian isolates into three geographically distinct clusters within the Mediterranean basin and uncovered three isolates clustering with putative L. infantum/L. donovani hybrids isolated in Cyprus. As judged by microsatellite profiling, these hybrid isolates are representative of a sub-population of parasites circulating in northern Italy that preferentially infect humans but not dogs. Our results place Italy at the crossroads of L. infantum infection in the Mediterranean and call attention to the public health risk represented by the introduction of non-European Leishmania species.IMPORTANCEThis study closes important knowledge gaps with respect to Leishmania (L.) infantum genetic heterogeneity in a given endemic country, as exemplified here for Italy, and reveals genetic hybridization as a main cause for re-emerging human leishmaniasis in northern Italy. The observed high diversity of Leishmania parasites on the Italian peninsula suggests different geographical origins, with genomic adaptation to various ecologies affecting both pathogenicity and transmission potential. This is documented by the discovery of a putative L. infantum/L. donovani hybrid strain, which has been shown to preferentially infect humans but not dogs. Our results provide important information to health authorities, which need to consider the public health risk represented by the introduction of new Leishmania species into EU countries due to population displacement or travel from countries where exotic/allochthonous parasite species are endemic.

Brief Notes on the European Geographical Indication Law: Among Sustainability Implications and Artificial Intelligence Applications

Purpose: Geographical indications (GIs) within the European Union are – as is known – legally protected designations highlighting unique qualities of products tied to their place of origin; accordingly, GIs can promote sustainable agricultural practices, preserve traditional knowledge and contribute to rural development, but, notwithstanding, issues in verifying and authenticating GI products persist. Within this framework, this paper investigates the intersection of EU geographical indication law with sustainability goals and potential applications of artificial intelligence (AI) in streamlining GI compliance and enhancing consumer trust. Study design/methodology/approach: The behind research employs a mixed-methods approach; in fact, it includes a systematic review of relevant EU legislation and policy documents alongside qualitative case studies exploring the use of AI-based technologies (e.g., precision agriculture, terroir monitoring, traceability systems…) in GI value chains. Findings: The analysis confirms the wanted complex interplay between GI law and sustainability; in this way, while GIs can be powerful tools for promoting environmentally responsible production, existing frameworks may not fully capture all dimensions of sustainability; in addition, case studies demonstrate the promise of AI in improving product traceability, combating fraud and supporting informed consumer choices regarding GI products. Originality/value: Therefore, the paper argues for a more holistic approach to GI law that integrates sustainability metrics beyond geographic origin, suggesting that responsible AI adoption presents the potential to significantly strengthen GI systems: policy recommendations should include incentivising the development of ethical AI solutions for GI verification, promoting data sharing along supply chains, and raising consumer awareness of the sustainability benefits associated with GI products.

German minority in urban space of a textile manufacturing centre: The case of 19th century city of Łódź

German settlement in Poland has been the subject of numerous studies. The causes and determinants of migratory movements have been discussed extensively, while little attention has been paid to the spatial aspects of the phenomenon. The aim of this study, which is part of geographical and historical research, is to determine the size of the influx of migrants of German nationality into the rapidly developing textile production centre of Łódź in the 19th century, as well as the geographical origins and distribution of this nationality group in the urban space. These considerations are complemented by the identification of key issues related to the social integration and assimilation processes of the German minority. In the first half of the 19th century, the influx of skilled labour, almost entirely recruited from the German population, conditioned the development of the textile industry in Łódź. It also had a key influence on the demographic development of Łódź, which soon became the largest centre of textile production in Poland. In subsequent decades, there was a tendency among German immigrants towards separation in the sphere of professional and social activities, but already by the end of the 19th century the German community settled in Łódź was diverse in terms of the sense of nationality. In addition to a certain proportion of the immigrants who were already Polonised, there were persons declaring German nationality, as well as those undecided about the issue.

Emphasizing the Potential of Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) Spectroscopy Combined with Chemometrics, for Classification of Greek Grape Marc Spirits

Grape marc spirits, such as the Greek tsipouro/tsikoudia, reflect the cultural heritage of winemaking traditions worldwide. This study explored the application of Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy combined with chemometrics for its potential as a fast classification methodology for spirit characterization. ATR-FTIR spectra from thirty-nine products revealed distinctive bands corresponding to various chemical constituents, such as alcohols, organic acids, water, carbohydrates, and phenols. Principal Component Analysis (PCA) was performed on all acquired ATR-FTIR data and 78.50% of the total variance in the data was explained. Also, partial least squares–discriminant analysis (PLS-DA), used for the classification of products based on their major geographic origin, gave a correct classification of 89.5% for the north and 83.3% for the south of Greece. Classification of the type of distillations used was with 74.36% accuracy. Significant markers were identified through analysis, such as those associated with the O-H bending vibrations of phenols or alcohols, contributing to the discrimination of grape marc spirits from Crete when compared with the other four main geographical origin designations. By combining ATR-FTIR spectroscopy with chemometrics, this research gave insights into the origins and compositional variations of the spirits, providing an opportunity for a quality control assessment tool.

Analysis of the genetic variation and geographic distribution patterns of Xanthomonas citri pv. citri strains in citrus production in Burkina Faso.

It is essential to have a thorough knowledge of the genetic variation among different strains of Xanthomonas citri pv. citri (Xcc), which is responsible for causing citrus bacterial canker. This understanding is important for studying disease characteristics, population structure, and evolution and ultimately for developing sustainable methods of control. A total of 48 strains obtained from citrus production areas in Burkina Faso in 2012, 2020, and 2021 were subjected to polymerase chain reaction (PCR) tests using specific primers. The aim was to examine the distribution of type 3 effectors (T3E) and determine the geographical origins of the strains. The examination of the distribution of type 3 non-transcription-activator-like effectors (TALEs) revealed a broader range of strains obtained in 2020 and 2021 than in 2012. However, all the strains possessed a shared set of three genes, specifically, XopE2, XopN, and AvrBs2. Furthermore, all examined effectors were observed in the Bobo-Dioulasso region. Regarding the characterization of TALEs, two profiles containing two to three TALEs were discovered. Profile 1, consisting of two TALEs, was found in 37 Xcc strains, whereas Profile 2, comprising three TALEs, was detected in 11 strains. Among the three TALEs (A, B, and C) that were identified, TALEs B and C were present in all the strains. The correlation matrix indicated a positive association between the T3E content of strains and the duration of their isolation. Principal component analysis revealed a limited organization of the strains under investigation.

Identifying the geographical origin and processing technology of Moyao () on the basis of near-infrared spectroscopy combined with chemometrics.

To evaluate the quality of Moyao (Myrrh) in the identification of the geographical origin and processing of the products. Raw Moyao (Myrrh) and two kinds of Moyao (Myrrh) processed with vinegar from three countries were identified using near-infrared (NIR) spectroscopy combined with chemometric techniques. Principal component analysis (PCA) was used to reduce the dimensionality of the data and visualize the clustering of samples from different categories. A classical chemometric algorithm (PLS-DA) and two machine learning algorithms [K-nearest neighbor (KNN) and support vector machine] were used to conduct a classification analysis of the near-infrared spectra of the Moyao (Myrrh) samples, and their discriminative performance was evaluated. Based on the accuracy, precision, recall rate, and F1 value in each model, the results showed that the classical chemometric algorithm and the machine learning algorithm obtained positive results. In all of the chemometric analyses, the NIR spectrum of Moyao (Myrrh) preprocessed by standard normal variation or Multivariate scattering correction combined with KNN achieved the highest accuracy in identifying the geographical origins, and the accuracy of identifying the processing technology established by the KNN method after first-order derivative pretreatment was the best. The best accuracy of geographical origin discrimination and processing technology discrimination were 0.9853 and 0.9706 respectively. NIR spectroscopy combined with chemometric technology can be an important tool for tracking the origin and processing technology of Moyao (Myrrh) and can also provide a reference for evaluations of its quality and the clinical use.

Study of green‐coloured gems of the Roman period from the collections of the Archaeological Museum of Thessaloniki (Greece) and their possible geographic origin

Study of green‐coloured gems of the Roman period from the collections of the Archaeological Museum of Thessaloniki (Greece) and their possible geographic origin

Injury Risk Estimation in Mandible-Related Surgical Procedures: A CBCT Study Based on Vital Interforaminal Anatomical Structures.

The mandibular interforaminal region has been considered safe for surgical procedures; nevertheless, the risk of injury to neurovascular structures, such as the mental foramen (MF) and its related structures (anterior loop [AL] and lingual foramina [LF]) should not be overlooked. The study aimed to evaluate the relative risk of injury to these structures during surgical procedures in the anterior region of the mandible based on cone-beam computed tomography (CBCT) scans. A retrospective cross-sectional and observational study was performed on 250 CBCTs from adults (18-69 years) with dentate jaws. Linear measurements of the MF, AL, and LF were evaluated to estimate the risk of injury to these structures during chin-related surgical procedures. The most frequent distance between the base of the mandible (BM) and MF was 8 mm (30.2%). In addition, 20.4% of the CTs had 6 mm from the vestibular cortical bone to the LF. The commonly found measurement from LF to the apex of the nearest tooth was 7 mm (24.0%); 64.2% of the CTs showed a 2-mm distance between the most distal point of the dental implant site to the most anterior point of the AL. Safety distances for genioplasty techniques (MF to mandible base > 6 mm, 96.6% [CI 95%, 95.0%-98.2%]) were observed. Considering the 5-mm cut-off point between the lower limit of a hypothetical bone graft and the chin, 65.4% (CI 95%, 58.9%-71.9%) of CTs were within this distance. Regarding the safety margin of 8 mm, 85.6% (CI 95%, 80.8%-90.4%) were up to this value. This study found safety margins for genioplasty and chin bone grafting surgical techniques that adopt a 5-mm cut-off point. Further similar studies assessing other surgical methods and employing larger samples from different geographical origins may contribute to this field of investigation.

Combined Effects of Cultivar, Extraction Technology, and Geographic Origin on Physicochemical Traits of Moroccan Olive Oil as Revealed by Multivariate Analysis

This study aimed at evaluating physicochemical traits of olive oil (‘Haouzia’ and ‘Moroccan Picholine’) according to extraction technologies (ETs: super-pressure SP, 2-phase 2P, and 3-phase 3P) across eight climatically contrasted Moroccan agroclimatic areas (AA). Our samples were classified as extra virgin olive oil (EVOO), whose traits varied (p < 0.05) among ETs, cultivars, and AA. EVOO from SP had high records of basic indices, most phytosterols, and trans fatty acids (TFA) due to partial oxidation during extraction, while continuous ETs (2P and 3P) displayed a better oil quality as demonstrated by routinely measured parameters. ‘Haouzia’ had the greatest saturated (SFA), monounsaturated (MUFA), polyunsaturated fatty acids (PUFA), and TFA. However, it had a lesser stability revealed by a low MUFA/PUFA and oleic/linoleic (O/L) as compared to ‘Moroccan Picholine’. Arid climatic areas had the highest palmitoleic, oleic acid, MUFA, MUFA/PUFA, and O/L and therefore the best oil stability as compared to the remaining agroclimatic areas. These variations were confirmed by principal component analysis, cluster analysis, and artificial neural networks. Important simple and multiple regression models with strong correlations were highlighted among the studied variables. In conclusion, environmental conditions have a key role to be considered when assessing olive oil quality and authenticity.

Assessing the effects of geographical origin and production practices on the levels of heavy metals in honey from three regions in Ghana

ABSTRACT To evaluate the impact of production methods and geographical origin on honey quality, honey from three regions in Ghana was analysed using INAA and FAAS for the presence of some selected metals. Five metals were found in all the ninety samples as Mg (321.1 mg/kg), Cu (56.2 mg/kg), V (8.18 mg/kg), Fe (3.28 mg/kg), and Pb (0.0400 mg/kg). Co and Cr were detected in 12% and 45% of the samples respectively but As, Cd, and Hg were not detected. The concentrations of Pb varied significantly based on production practices. Cu, Mg, and V showed differences based on geographical sources, according to the Kruskal Wallis test at p < 0.05. Co was below the WHO levels for drinking water and Cr, Cu, Fe, Mg and V were above the WHO levels. Ultimately, the honey source, as opposed to production practices, affected the metal content and potentially, honey consumption can have health risks.

Peritoneal Tumour DNA in Peritoneal Fluid: Emerging Tool for Peritoneal Metastasis Detection.

The prognostic significance of positive peritoneal cytology still varied between cancer types and geographical origin. However, because of the lack of sensitivity of this biomarker, conventional cytology is not routinely performed in every country. Here, we wanted to test a new biomarker, peritoneal tumour DNA, using NGS technique, in order to compare it with the historical one, in patients having peritoneal metastases of gastrointestinal or ovarian cancer.

The Faces and Forms of Pandemic Humor: Exploring Covid-19 Memes with Visual Machine Learning

The Covid-19 pandemic brought about an unprecedented cycle of digitally spread humor. This article analyzes a corpus of 12,337 humor items from 80+ countries, mainly in visual format, and mostly memes, collected during the first half of 2020, to understand the features and intended audiences of this “pandemic humor”. Employing visual machine-learning techniques and additional qualitative analysis, we ask which actors and which templates were most prominent in the pandemic humor, and how these actors and templates vary on the following dimensions: local vs. global, Covid-specific vs. general, and specifically for the actors, political vs. not political. Our analysis shows that most pandemic memes from the first wave are not political. The vast majority of the memes are global: They are based on well-recognized meme templates, and almost all identified actors are part of a cast of set “meme faces”, mostly from the US and the UK but recognized around the world. Most popular templates were found in several countries and languages, including non-European languages. Most memes were based on non-Covid specific templates, but we found new Covid-specific memes, which sheds new light on the process by which memes emerge, spread, and potentially become new meme templates. Our analysis supplements existing studies of (Covid) memes that mostly focus on small national samples, using qualitative methods. This cross-national analysis is enabled by a global dataset with unique data on geographical origin of humor. We show the usefulness of visual machine learning for identifying the emergence, spread and prevalence of transnational (humorous) cultural forms. By combining large-scale computational analysis with in-depth analysis, we bridge a gap in in meme studies between (mostly quantitative) data sciences and (mostly qualitative) communication and media studies.

Reform of the first year of medical studies and diversification of student profiles in France: an unmet need?

ObjectivesTo determine whether the reform of the first year of medical studies implemented in September 2020 in France met its objective of diversifying the profiles of students admitted to second year at the faculty of medicine at the University of Tours.MethodsSingle-centered, retrospective study, covering students who passed the first year of medical studies between 2018 and 2022. Student profiles originating from three different entry gateways (PACES, PASS and L.AS) to the second year of medical studies were compared.ResultsOne thousand four hundred and seventy-nine students over five promotions were included (806 in PACES, 329 in PASS, 198 in L.AS). The ratio of students who had obtained a baccalaureate with high or highest honors was significantly higher in PACES (85%) and PASS (96%) compared to L.AS (66%; p < 0.001). These differences were related to increased student intake via a standard pass in L.AS (21% compared to 3.2% in PACES and 0.9% in PASS) (p < 0.001). In terms of geographical origin, the proportion of students residing in regions outside the University City area increased significantly in L.AS (11%) compared to PACES (1.7%) and PASS (3.3%) (p < 0.001). The mean number of parents from the white-collar and knowledge professional category was significantly higher in PACES (0.91) and PASS (1.06) compared to L.AS (0.80; p < 0.001).ConclusionStudents with a scientific background and who obtained highest honors in their high school diploma, remain the standard in PACES and PASS. Diversification of student profiles was achieved only within the L.AS gateway, which represented 42% of total second year admissions during the post-reform year. Student profile diversification was therefore a partially achieved objective and follow up studies of future promotions is needed to assess the medium and long-term impact of the reform. Particular attention should be paid to the future of these students who have different profiles between L.AS and PASS to determine whether these changes will have any impact in the quality of healthcare for the French population.

Chemometric-based drug discovery approaches from natural origins using hyphenated chromatographic techniques.

Isolation and characterization of bioactive components from complex matrices of marine or terrestrial biological origins are the most challenging issues for natural product chemists. Biochemometric is a new potential scope in natural product analytical science, and it is a methodology to find the compound's correlation to their bioactivity with the help of hyphenated chromatographic techniques and chemometric tools. The present review aims to evaluate the application of chemometric tools coupled to chromatographic techniques for drug discovery from natural resources. The searching keywords "biochemometric," "chemometric," "chromatography," "natural products bioassay," and "bioassay" were selected to search the published articles between 2010-2023 using different search engines including "Pubmed", "Web of Science," "ScienceDirect," and "Google scholar." An initial stage in natural product analysis is applying the chromatographic hyphenated techniques in conjunction with biochemometric approaches. Among the applied chromatographic techniques, liquid chromatography (LC) techniques, have taken up more than half (53%) and also, mass spectroscopy (MS)-based chromatographic techniques such as LC-MS are the most widely used techniques applied in combination with chemometric methods for natural products bioassay. Considering the complexity of dataset achieved from chromatographic hyphenated techniques, chemometric tools have been increasingly employed for phytochemical studies in the context of determining botanicals geographical origin, quality control, and detection of bioactive compounds. Biochemometric application is expected to be further improved with advancing in data acquisition methods, new efficient preprocessing, model validation and variable selection methods which would guarantee that the applied model to have good prediction ability in compound relation to its bioactivity.

Geographical indication: a review

Geographical Indication (GI) is an industrial property instrument that seeks to distinguish the geographic origin of a certain product or service. The challenge is associated with identifying how the Geographical Indication seal could be a useful tool to leverage local and regional development. The objective of this study is to review the international literature on the topic of Geographical Indication, especially for wine production. The SCOPUS database was used as a search engine. The expression “geographical indication” was used as a search key in the title, keywords or summary fields, resulting in 2224 publications. Publications were analyzed without filter. It was noticed that “Protection” has a negative inclination, that is, it is being left aside as a research interest. The words associated with Wine, Food and Sustainability showed a positive slope in the linear regression, which suggests that they are causing increasing interest among researchers.

Changes in holopelagic Sargassum spp. biomass composition across an unusual year

The year 2021 marked a decade of holopelagic sargassum (morphotypes Sargassum natans I and VIII, and Sargassum fluitans III) stranding on the Caribbean and West African coasts. Beaching of millions of tons of sargassum negatively impacts coastal ecosystems, economies, and human health. Additionally, the La Soufrière volcano erupted in St. Vincent in April 2021, at the start of the sargassum season. We investigated potential monthly variations in morphotype abundance and biomass composition of sargassum harvested in Jamaica and assessed the influence of processing methods (shade-drying vs. frozen samples) and of volcanic ash exposure on biochemical and elemental components. S. fluitans III was the most abundant morphotype across the year. Limited monthly variations were observed for key brown algal components (phlorotannins, fucoxanthin, and alginate). Shade-drying did not significantly alter the contents of proteins but affected levels of phlorotannins, fucoxanthin, mannitol, and alginate. Simulation of sargassum and volcanic ash drift combined with age statistics suggested that sargassum potentially shared the surface layer with ash for ~50 d, approximately 100 d before stranding in Jamaica. Integrated elemental analysis of volcanic ash, ambient seawater, and sargassum biomass showed that algae harvested from August had accumulated P, Al, Fe, Mn, Zn, and Ni, probably from the ash, and contained less As. This ash fingerprint confirmed the geographical origin and drift timescale of sargassum. Since environmental conditions and processing methods influence biomass composition, efforts should continue to improve understanding, forecasting, monitoring, and valorizing sargassum, particularly as strandings of sargassum show no sign of abating.

Species classification and origin identification of Lonicerae japonicae flos and Lonicerae flos using hyperspectral imaging with support vector machine

Lonicerae japonicae flos (Jinyinhua, JYH) and Lonicerae flos (Shanyinhua, SYH) have high medical and economical value. Due to their similar appearance, the more expensive JYH is often adulterated with the cheaper SYH for economic gain. In this study, near-infrared hyperspectral imaging (HSI) was used to identify the geographical origins of JYH and SYH and differentiate JYH from SYH. Support vector classification (SVC) models using linear kernel function were established to achieve the research goals. For the identification of geographical origin, we explored the impact of different sample batches on classification performance. The overall testing sets classification accuracy of JYH and SYH was in the range of 60.10–85.59% and 63.35–91.67%, respectively. For species classification, the impact of sample geographical origins and sample batches on model performances was explored. The overall testing sets classification accuracy for distinguishing JYH and SYH was 98.46–100%. These results demonstrated the significant impact of sample sources on the performance of the models. Using SVC models, the important wavelengths contributing more to the classification were identified by recursive feature elimination (RFE). The results showed that HSI holds great potential for the identification of JYH and SYH, as well as their geographical origins. This technique can provide crucial technical support for the development and standardization of the Traditional Chinese Medicine industry.

Rapid quality assessment and traceability of ginger powder from Northeast India and Indian market based on near infrared spectroscopic fingerprinting.

Ginger (Zingiber officinale Rosc.) varies widely due to varying concentrations of phytochemicals and geographical origin. Rapid non-invasive quality and traceability assessment techniques ensure a sustainable value chain. The objective of this study is the development of suitable machine learning models to estimate the concentration of 6-gingerol and check traceability based on the spectral fingerprints of dried ginger samples collected from Northeast India and the Indian market using near-infrared spectrometry. Samples from the market and Northeast India underwent High Performance Liquid Chromatographic analysis for 6-gingerol content estimation. Near infrared (NIR) Spectrometer acquired spectral data. Quality prediction utilized partial least square regression (PLSR), while fingerprint-based traceability identification employed principal component analysis and t-distributed stochastic neighbor embedding (t-SNE). Model performance was assessed using RMSE and R2 values across selective wavelengths and spectral fingerprints. The standard normal variate pretreated spectral data over the wavelength region of 1,100-1,250 nm and 1,325-1,550 nm showed the optimal calibration model with root mean square error of calibration and R2 C (coefficient of determination for calibration) values of 0.87 and 0.897 respectively. A lower value (0.24) of root mean square error of prediction and a higher value (0.973) of R2 P (coefficient of determination for prediction) indicated the effectiveness of the developed model. t-SNE performed better clustering of samples based on geographical location, which was independent of gingerol content. The developed NIR spectroscopic model for Indian ginger samples predicts the 6-gingerol content and provides geographical traceability-based identification to ensure a sustainable value chain, which can promote efficiency, cost-effectiveness, consumer confidence, sustainable sourcing, traceability, and data-driven decision-making.