<p><strong>Eurachem and CITAC welcome analysts interested in the evaluation of chemical analysis uncertainty and in how to use this information in results interpretation. The Eurachem Week 2026 will begin with a training course on “Evaluation of the measurement uncertainty from in-house precision and recovery data” scheduled for Sunday, 10 May 2026. A two-days workshop on “Quality in Analytical Measurements: Uncertainty Evaluation and Results Interpretation” open to all interested participants will take place from 11 to 12 May 2026. On 13 May 2026, the Eurachem Working Groups will convene, followed by the Eurachem General Assembly, which will bring together the Executive and national delegates on 14 and 15 May. Both Working Group Meetings and the General Assembly are restricted to their members.</strong></p><p>The results of qualitative and quantitative chemical analyses should have an acceptable uncertainty, which should ideally be reported and considered in results interpretation.</p><p>For many analytical applications, simplified uncertainty evaluations can determine uncertainty values that meet the defined requirements for this parameter. The workshop will focus on the key technical challenges involved in practical evaluations of measurement uncertainty based on precision and recovery data gathered during in-house method validation and quality control. There will be a discussion of how to model the variation of the measurement uncertainty within the analytical range and how to handle divergent recovery values from the analysis of various reference materials. A session on the use of measurement uncertainty in conformity assessment will explore how the risk of false conformity decisions can be managed.</p><blockquote><h5><strong>New Eurachem guidance on using in-house precision and recovery data will be discussed at the workshop.</strong></h5></blockquote><p>Topics will also include the validation and uncertainty evaluation for qualitative analyses with particular attention to current accreditation requirements for these types of analysis. The last session of the workshop will be dedicated to the evaluation of measurement uncertainty arising from sampling and using it to judge the fitness for purpose, and hence validation, of measurement procedures that include sampling. Four sessions of the workshop will include engaging breakout sessions where participants will have the chance to share their views about challenging aspects of the analytical work. Participants are invited to propose posters and oral communications on session topics or any other relevant topic for analytical chemists or stakeholders of the analytical work.</p><h3><strong>Registration</strong></h3><blockquote><p class="cke-user_style-important"><strong>👉</strong><a target="_blank" rel="noopener noreferrer" href="https://conferences.chemistry.pt/register/eurachem2026"><strong>Register here for the workshop</strong></a></p></blockquote><h4><strong>Registration Fees</strong></h4><h5><strong>Early bird (EUR) - Until April 15th</strong></h5><ul><li><strong>Workshop: Regular participant (11 &amp; 12 May 2026): </strong>400 EUR</li><li><strong>Workshop: Student (11 &amp; 12 May 2026): </strong>250 EUR</li><li><strong>Eurachem Working Group<sup>1</sup> (13 May 2026):</strong> 75</li><li><strong>General Assembly<sup>2</sup> (14 &amp; 15 May 2026): </strong>250</li><li><strong>Training On Uncertainty Evaluation<sup>3</sup> (10 May 2026):</strong> 150</li></ul><h5><strong>After April 15th</strong></h5><ul><li><strong>Workshop: Regular participant (11 &amp; 12 May 2026): </strong>450 EUR</li><li><strong>Workshop: Student (11 &amp; 12 May 2026):</strong> 300 EUR</li><li><strong>Eurachem Working Group<sup>1</sup> (13 May 2026): </strong>100</li><li><strong>General Assembly<sup>2</sup> (14 &amp; 15 May 2026):</strong> 300</li><li><strong>Training On Uncertainty Evaluation<sup>3</sup> (10 May 2026): </strong>200</li></ul><blockquote><p>§ - <strong>50 EUR reduction for members of Eurachem</strong>, CITAC, SPQ, RELACRE, ForMEQ and SPMet at the workshop.</p><p>10% reduction for organisations that registered more than one participant.</p><p><sup>1 </sup>- Working group members</p><p><sup>2</sup> - Eurachem members</p><p><sup>3</sup> - 50% reduction for workshop participants</p></blockquote><h3><strong>Workshop</strong></h3><h4><strong>Eurachem/CITAC Workshop on Quality in Analytical Measurements:</strong></h4><h5><strong>Uncertainty Evaluation and Results Interpretation</strong></h5><p>The results of qualitative and quantitative chemical analyses should have an acceptable uncertainty, which should ideally be reported and considered in results interpretation. For many analytical applications, simplified uncertainty evaluations can determine uncertainty values meeting defined requirements for this parameter. The workshop will focus on the key technical challenges involved in practical evaluations of measurement uncertainty based on precision and recovery data gathered during in-house method validation. It will be discussed how to model the variation of the measurement uncertainty within the analytical range and how to handle divergent recovery values from the analysis of various reference materials. A session on the use of measurement uncertainty in conformity assessment will explore how the risk of false conformity decisions can be managed.</p><p>Topics will also include the validation and uncertainty evaluation of qualitative analyses with particular attention to current accreditation requirements for these types of analysis. The last session of the workshop will be dedicated to the evaluation of measurement uncertainty arising from sampling and using it to judge the fitness for purpose, and hence validation, of measurement procedures that include sampling.</p><p>Four sessions of the workshop will include engaging breakout sessions where participants will have the chance to share their views about challenging aspects of the analytical work. Participants are invited to propose posters and oral communications on session topics or any other relevant topic for analytical chemists or stakeholders of the analytical work.</p><h3><strong>Training Course</strong></h3><h4><strong>Evaluation of the measurement uncertainty from in-house precision and recovery data</strong></h4><ul><li>10 May 2026</li></ul><p>A course on the fundamentals of the evaluation of the measurement uncertainty from in-house precision and recovery data will be held on Sunday, 10 May 2026. This training is targeted for analysts with a basic understanding of the measurement uncertainty concept, how uncertainty components propagate, and how the combined uncertainty is expanded. Following the morning presentation of the theory of uncertainty evaluation, the afternoon will be dedicated to applying the theory to real-world cases. Trainees should have basic skills in using Microsoft Excel spreadsheets and bring a laptop with Microsoft Excel to complete the exercises. The interaction between trainers and trainees will be promoted to guarantee learning efficiency.</p><h5><strong>Trainers:</strong></h5><ul><li>Ricardo Bettencourt da Silva, Faculdade de Ciências da Universidade de Lisboa, Portugal (rjsilva@ciencias.ulisboa.pt)</li><li>Stephen L. R. Ellison - UK National Measurement Laboratory (NML) hosted at LGC, United Kingdom</li><li>Vicki Barwick - UK National Measurement Laboratory (NML) hosted at LGC, United Kingdom</li></ul><h4><strong>Agenda</strong></h4><h5><strong>8:00 Registration</strong></h5><h5><strong>9:00 Opening</strong></h5><h5><strong>9:05 Identifying, combining, and expanding uncertainty components: Theory and examples</strong></h5><h5><strong>9:45 Precision uncertainty: Theory and examples</strong></h5><h5><strong>10:30 </strong>Coffee break</h5><h5><strong>10:50 Trueness-related uncertainty: Theory and examples</strong></h5><h5><strong>12:00 Additional questions and discussion</strong></h5><h5><strong>12:30 </strong>Lunch</h5><h5><strong>13:30 Application example 1</strong></h5><h5><strong>15:30 </strong>Coffee break</h5><h5><strong>15:50 Application example 2</strong></h5><h5><strong>17:00 Additional questions and discussion</strong></h5><h5><strong>17:30 Closing</strong></h5><h3><strong>Venue</strong></h3><p>The series of Eurachem events will be held in:</p><ul><li>Meliã Lisboa Aeroporto ****</li><li>Rua C,2 1749-125 Lisboa, Portugal&nbsp;</li></ul>

Eurachem/CITAC Workshop on Quality in Analytical Measurements 2026

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezICPMS Library in the week of 9th February 2026? Check out new documents from the field of spectroscopy/spectrometry and related techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT SPECTROSCOPY/SPECTROMETRY RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><strong>LabRulezGCMS</strong></a> libraries.</p></blockquote><p>This week we bring you application notes by <strong>Agilent Technologies</strong>, <strong>Metrohm,</strong> <strong>Shimadzu </strong>and<strong> Thermo Fisher Scientific!</strong></p><h3><strong>1. Agilent Technologies: Black Pepper Origin Differentiation Using Large ICP-MS Datasets and Chemometric Tools</strong></h3><p><strong>Elemental profiling using an </strong><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=1&amp;search=7850+ICP-MS"><strong>Agilent 7850 ICP-MS</strong></a><strong> and Agilent </strong><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=1&amp;search=Mass+Profiler+Professional+software"><strong>Mass Profiler Professional (MPP) software</strong></a></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_black_pepper_origin_7850_icp_ms_5994_8741en_agilent_7c190968ef.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Black pepper’s high value and global demand are drivers for economically motivated adulteration, a fraudulent practice that can pose public health risks. Because black pepper is most often sold in ground, crushed, or mixed forms, its supply chain is difficult to monitor and manage. Also, consumer campaigns against deforestation and the European Union Regulation on Deforestation-free (EUDR) products have increased calls for greater sourcing transparency. Products with a known geographical indication can demand a higher price. Companies do not want to become implicated in false claims about the sourcing of products, and many are keen to have full visibility of their products’ origin. To address this need, the European Commission has established the Protected Geographical Indication (PGI) system to protect regional specific products, thereby promoting their unique characteristics based on geographical origin and traditional competence of production. The PGI scheme has increased the demand for detailed information regarding the geographical source of food products, a trend that is likely to continue as EUDR is implemented across the EU and associated markets. Verifying the geographical origin of black pepper using elemental fingerprints is highly relevant to protecting value chain stakeholders, ensuring both quality and traceability while upholding the principles of food integrity.&nbsp;</p><p>Several analytical methods can be used for profiling certain elements in foods. However, inductively coupled plasma mass spectrometry (ICP-MS) is unique because of its rapid throughput, multi-element capability, ultratrace sensitivity, isotopic analysis, versatility across sample types, low sample volume requirements, compliance with regulatory requirements, and low cost.<sup>3</sup>&nbsp;</p><p>The Agilent 7850 ICP-MS is equipped with an Octopole Reaction System (ORS4 ), a collision/reaction cell (CRC) that uses helium (He) gas and Kinetic Energy Discrimination (KED) to remove polyatomic interferences on key analytes.<sup>4</sup> If left unchecked, these interferences can affect data accuracy in complex food products. The integration of the 7850 with Agilent ICP-MS MassHunter software streamlines data analysis. When integrated with chemometric analysis, ICP-MS demonstrates high precision in multi-elemental profiling of diverse food matrices, effectively distinguishing their geographical origin.<sup>5</sup>&nbsp;</p><p>In this study, 150 black pepper samples from five countries (Brazil, Cambodia, India, Indonesia, Vietnam) were analyzed using the 7850 ICP-MS to obtain elemental fingerprints of the samples. Agilent Mass Profiler Professional (MPP) software was used to process the ICP-MS elemental data and to construct chemometric models for distinguishing the geographical origin of the samples, as adapted from Chilaka et al.<sup>5</sup></p><h4><strong>Experimental&nbsp;</strong></h4><h5><strong>Instrumentation&nbsp;</strong></h5><p>An <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=1&amp;search=7850+ICP-MS"><strong>Agilent 7850 single-quadrupole ICP-MS</strong></a> was used for the analysis of 38 elements in the black pepper samples. Sample introduction was performed via a peristaltic pump connected to an Agilent MicroMist nebulizer and an Agilent SPS 4 autosampler. All elements were measured using helium collision (He KED) mode, except for boron (B), which was analyzed in no gas mode. Instrument control was performed using <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=1&amp;search=MassHunter"><strong>Agilent ICP-MS MassHunter 5.1 software</strong></a>, and data processing was conducted using <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=1&amp;search=Mass+Profiler+Professional+software"><strong>Agilent MPP software</strong></a>, version 15.1. Instrument operating conditions as shown in Table 1.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>This study investigated the potential of ICP-MS elemental profiling coupled with chemometric analysis for geographical origin discrimination of black pepper samples from five countries, including Brazil, Cambodia, India, Indonesia, and Vietnam. A total of 38 elements was measured in 150 black pepper samples using the Agilent 7850 ICP-MS. Chemometric analysis was performed on the ICP-MS elemental data using Agilent Mass Profiler Professional (MPP) software. The PCA analysis exhibited satisfactory reliability and classification rates and demonstrated potential for the authentication of the geographical origin of black pepper. However, the separation of the Cambodian and Vietnamese samples was less distinct than the other groups, revealing potential similarities in elemental profiling between the bordering countries, which share similar climatic, geological, and agricultural conditions. Using LDA and RF classification models on the black pepper test set, we achieved a high overall accuracy in determining the geographical origin of the samples. These findings provide empirical support for the combined use of elementomics and chemometric techniques in black pepper authentication, contributing to fraud prevention. The study also demonstrates the potential of the method for application to other food types.</p><h3><strong>2. Metrohm: Milk powder analysis by near-infrared spectroscopy</strong></h3><p><strong>Determination of moisture, fat, lactose, and protein content</strong></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_nir_128_download_867321cfb0.pdf"><strong>Full PDF for download</strong></a></li></ul><p>For milk powder producers, final product control is essential to meet strict regulatory standards, guarantee comprehensive quality assurance, ensure consistent nutritional quality, and extend shelf life. These are all especially important for infant formula and dairy ingredients used in sensitive applications. Near-infrared spectroscopy (NIRS) is a fast, reagentfree method for measuring key quality parameters such as moisture, protein, lactose, and fat content directly in milk powder. The NIRS solution requires no sample preparation, enabling real-time monitoring either in the lab or directly on the production line. This allows producers to react quickly to process variations, minimize waste, and maintain product integrity batch after batch.</p><h4><strong>EXPERIMENTAL EQUIPMENT&nbsp;</strong></h4><p>More than 600 samples of powdered milk from different suppliers were analyzed on an <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=56&amp;search=OMNIS+NIR"><strong>OMNIS NIR Analyzer</strong></a> (Figure 1). The different milk powders were placed into an OMNIS sample cup and analyzed in diffuse reflection mode. To include sample variety, the sample rotated during measurement to collect spectra from different locations. The automatically averaged spectra were used for model development. Reference values were obtained by official methods, e.g., AOAC 927.05 (moisture), AOAC 939.02 (protein), and AOAC 932.06 (fat). For the lactose content determination, a phenol-sulfuric acid method was used.</p><h4><strong>CONCLUSION</strong></h4><p>This Application Note presented the analysis of milk powder using NIR spectroscopy. Models for several quality parameters (fat, protein, lactose, and moisture content) were created. Independent validation samples confirmed the robustness and reliability of the models, with high correlation coefficients and low prediction errors achieved across all parameters. Notably, the dataset included samples from diverse global origins, capturing a broad range of product variability. This study shows that NIRS can be successfully integrated into the quality control workflow for dairy powder analysis.</p><h3><strong>3. Shimadzu: Analysis of Electrolyte and Electrode in LIB Degraded by Overcharge and High Temperature</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_01064_en_b4f9f4330a.pdf"><strong>Full PDF for download</strong></a></li></ul><h4><strong>User Benefits</strong></h4><ul><li>ICP-AES enables accurate quantification of cathode material dissolved in electrolytes.</li><li>GC-MS assesses degradation from components in electrolytes with unknown usage.</li><li>EDXRF easily evaluates transition metals, phosphorus, fluorine, and other elements deposited on electrodes</li></ul><p>When lithium-ion batteries are used in EVs or ESS applications, numerous cells are connected in series and parallel to form modules, and multiple modules are further connected to construct a pack. In such configurations—where many cells are connected in series—the state of charge of individual cells varies, as shown in Figure 1. Moreover, because the cells are densely packed to reduce volume, the ambient temperature experienced by each cell also varies. In this application, we conducted cycle tests under overcharged or high-temperature conditions, disassembled the degraded pouch cells, and analyzed both the electrolytes and the electrodes.</p><h4><strong>Analysis of electrolyte and electrode</strong></h4><p>Electrolytes and electrodes were extracted from the batteries degraded through the cycle tests (hereafter referred to as “degraded cells”) and analyzed using the instruments shown in Figures 3–5. It is known that electrolytesin degraded cells contain transition metals (Ni, Co, Mn) dissolved from the cathode active material1). In addition, electrolyte solvents are known to generate characteristic degradation products as deterioration progresses2). By analyzing these degradation-related elements and compounds, the degradation state of the battery can be assessed. In this article, we propose a multifaceted evaluation of electrolytes using <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=3&amp;search=ICPE-9820"><strong>ICP-AES</strong></a> and GC-MS. On both the cathode and anode, insulating layers known as CEI/SEI form on the electrode surfaces. Under improper charging conditions, excessive formation of these layers can lead to capacity loss. Furthermore, the dissolved metals from the cathode deposit and precipitate on the anode. These deposits can cause internal short circuits, posing risks such as fire hazards. While such electrode conditions are typically evaluated by ICP-AES or XPS to examine elemental content or surface chemical states, this article introduces a simpler evaluation method using <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=3&amp;search=EDX-8100"><strong>EDXRF</strong></a>.</p><h4><strong>Summary</strong></h4><p>Analysis of the electrolytesfrom degraded batteries using ICP-AES and GC-MS revealed dissolution of transition metals as well as the formation of degradation products. Furthermore, EDXRF analysis of the electrodes enabled straightforward detection of changesin elemental composition, including transition metals, fluorine, and phosphorus. These analytical techniques allow for a multifaceted evaluation of battery degradation. In real-world battery operation, fluctuations in charging conditions and ambient temperature introduce variability in degradation states. By assessing degradation mechanisms individually, as demonstrated in thisreport, it is possible to obtain insights that contribute not only to improving intrinsic battery performance but also to optimizing implementation methods and control conditions.</p><h3><strong>4. Thermo Fisher Scientific: Analyzing Spinel refractory MgO-Al2O3 premix using </strong><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=2&amp;search=ARL%E2%84%A2+X%E2%80%99TRA+Companion"><strong>ARL X’TRA Companion XRD</strong></a></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/spinel_refractory_xrd_an41525_en_75f2527e78.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Spinel refractories—primarily magnesia–alumina (MgAl₂O₄)— are the workhorses of high-temperature linings in steel ladles, cement rotary kilns, glass tanks, and non-ferrous smelters. Their appeal lies in a combination of shock resistance, chemical stability against basic slags, and an expansion behavior that mitigates cracking. Depending on the duty, they are used as bricks, castables, or gunned repairs, sometimes with engineered microstructures that blend spinel with periclase, corundum, or zirconia to tune creep, corrosion, and spalling performance.&nbsp;</p><p>X-ray diffraction (XRD) underpins manufacturing control from raw mix to fired product. During synthesis, XRD tracks the solid-state reaction of MgO and Al₂O₃ into spinel, verifying the disappearance of periclase and alumina and quantifying the spinel fraction by Rietveld analysis. Lattice parameters reveal cation stoichiometry and solid-solution effects; peak breadth trends indicate crystallite growth and microstrain, proxies for sintering progress. In finished components, XRD detects secondary phases such as calcium aluminates introduced by binders, slags, impurities, and it provides fingerprinting for batch-to-batch consistency after thermal exposure. Embedded into routine QA/QC, XRD shortens feedback loops, stabilizes recipes, and links processing conditions to the microstructure that governs refractory life.</p><h4><strong>Instrument &amp; software&nbsp;</strong></h4><p>The <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=2&amp;search=ARL%E2%84%A2+X%E2%80%99TRA+Companion"><strong>Thermo Scientific™ ARL™ X’TRA Companion</strong></a> X-Ray Diffractometer (c.f. Figure 1) is a simple, easy-to-use benchtop instrument for routine phase analysis as well as more advanced applications. The ARL X’TRA Companion uses a θ/θ goniometer (160 mm radius) in Bragg-Brentano geometry coupled with a 600 W X-ray source (Cu or Co). The radial and axial collimation of the beam is controlled by divergence and Soller slits, while air scattering is reduced by a variable beam knife. An integrated water chiller is available as an option. Thanks to the state-of-the art solid state pixel detector (55x55 μm pitch), the ARL X’TRA Companion provides very fast data collection and comes with single-click Rietveld quantification capabilities and automated result transmission to a LIMS (Laboratory Information Management System) seamless integrated into Thermo Scientific™ SolstiX™ Pronto instrument control software.</p><h4><strong>Your benefits&nbsp;</strong></h4><p>The ARL X’TRA Companion XRD workflow delivers answers in minutes, quantifying MgO, α-Al₂O₃, and MgAl₂O₄ while resolving Ca–Si silicates and trace Fe-spinels. Subtle differences between corundum and spinel are cleanly separated, and LOI drivers—carbonates, brucite, and Mg-sulfates—are identified and trended. These insights let you compute spinel potential, anticipate pore-closing expansion, and set the right pre-dry / prefire schedule to avoid spalling. You can clearly distinguish mid-grade, ore-derived feeds from premium low-silica materials, tighten incoming QA, and optimize formulations for cement/lime kilns, tundish linings, and other carbon-free basic applications.</p>

News from LabRulezICPMS Library - Week 07, 2026

<p><strong>Although modern agriculture needs to be based on accurate real-time data on soil, plant, and environmental conditions, affordable, sufficiently sensitive, and robust monitoring devices for this purpose are currently missing. According to scientists, low-cost sensors based on new smart materials and printing technologies offer a suitable solution. The results of multidisciplinary research thus far and proposals for the development of these devices have been presented by researchers from Czechia, Great Britain, Spain, and the USA in a review article in the prestigious journal </strong><a target="_blank" rel="noopener noreferrer" href="https://www.nature.com/articles/s41467-026-68778-6#Abs1"><i><strong>Nature Communications</strong></i></a><strong>.</strong></p><p>“<i>Sensor technologies for monitoring plant health are still in their infancy. Only simple sensors capable of monitoring basic parameters such as pH, soil moisture, or temperature are commonly available on the market. However, if farmers are to face current challenges, including climate change, and ensure sufficient food for humanity, they need much more effective tools that will enable them to monitor, for example, various pathogens, including bacteria and fungi. In our opinion, a suitable solution is a combination of new smart materials and printing for the production of inexpensive, durable, and scalable materials</i>,” said the article’s first author, <strong>David Panáček</strong> from CATRIN, who worked on the study during his internship at Imperial College London.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/CATRIN_Soucasne_senzory_nestaci_Vedci_navrhuji_novou_cestu_ke_sledovani_zdravi_rostlin_b4014952a3.jpg" alt="CATRIN: David Panáček" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_CATRIN_Soucasne_senzory_nestaci_Vedci_navrhuji_novou_cestu_ke_sledovani_zdravi_rostlin_b4014952a3.jpg 208w," sizes="100vw" width="1536" height="1152"></p><p>Sensors for monitoring plant health, for example, lag behind similar devices used in human medicine. According to the authors, advances in materials science, which will enable the development of scalable sensor technologies, play a key role in this potential shift. “<i>Printing techniques, including inkjet printing, screen printing, aerosol printing, 3D printing, and direct laser writing, offer flexible ways to produce flexible sensors, large-area sensors, and sensors integrated directly into plants. The review article summarizes recent advances in printable low-dimensional materials for agricultural sensors, analyzes their physico-chemical properties in relation to sensor performance, and discusses key challenges and future opportunities requiring interdisciplinary integration</i>,” said one of the corresponding authors, <strong>Michal Otyepka</strong>.</p><p>The research brought together materials scientists, chemists, biologists, sensing experts, and printing technology specialists. Materials research and the use of graphene-based smart materials were led by scientists from CATRIN at Palacký University and VŠB-Technical University of Ostrava. Plant biologists from CATRIN contributed their knowledge of plant development, their responses to stress conditions, and the monitoring of their properties. Researchers from Imperial College London took care of the electronics, while representatives from<a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/companies/36"><strong> CEITEC – VUT</strong></a> focused on printing technologies. The team also included leading experts in sensing from the Catalan Institute of Nanoscience and Nanotechnology in Barcelona, and Joseph Wang of the University of California San Diego, the “father of sensing and electrochemistry,” also contributed his extensive knowledge.</p><p>“<i>This is a groundbreaking study on this topic, which has managed to attract some truly big names in their respective fields. Last but not least, the study demonstrates that interdisciplinarity at CATRIN gives rise to completely new and promising research topics, such as plant sensing and its use for studying plant-environment interactions and smart agriculture,</i>” added another corresponding author, <strong>Nuria De Diego</strong>.</p>

Current sensors are not good enough. Scientists propose a new way to monitor plant health

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Eurachem is a European network promoting international traceability of chemical measurements and good analytical practice. It provides expert guidance, supports method validation, uncertainty evaluation, proficiency testing, and facilitates discussion on technical and policy issues in analytical quality.

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The Czech Advanced Technology and Research Institute (CATRIN) at Palacký University is a cutting-edge scientific hub dedicated to advancing research in the fields of nanotechnology, biotechnology, and biomedicine. At its core, CATRIN boasts outstanding scientific teams, featuring international researchers. We emphasize interdisciplinarity, foster global collaborations, and work to translate our research findings into practical applications.

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Mestrelab Mnova Advanced Chemometrics software

Leverage sophisticated multivariate analysis tools such as PCA, PLS, and SIMCA for in-depth data exploration, regression, and classification.

<h4><strong>Advanced Chemometrics for Enhanced Data Analysis</strong></h4><p>Leverage sophisticated multivariate analysis tools such as <strong>PCA, PLS, and SIMCA</strong> for in-depth data exploration, regression, and classification. The user-friendly interface ensures seamless integration of spectral data with analysis results, making it ideal for advanced users seeking powerful chemometric techniques for comprehensive data analysis.</p><h4><strong data-start="641" data-end="654">Benefits:</strong></h4><ul><li><strong>All-in-One Solution</strong>: Offers seamless spectral processing, binning, and analysis with just a few clicks, simplifying workflows and managing complex data efficiently in a single platform.</li><li><strong>Incorporates Recognized Methods:</strong> Includes PCA, PLS, and SIMCA for advanced data analysis and unsupervised chemometrics.</li><li><strong>Powerful and Intuitive Interface:</strong> Provides a user-friendly design for a streamlined analysis experience.</li><li><strong>Improved Classification and Prediction</strong>: Classifies samples with SIMCA and builds predictive models using PLS.</li><li><strong>Noise and Outlier Reduction</strong>: Effectively reduces noise and detects outliers, ensuring accurate and reliable results.</li><li><strong>Expandable Plugin:</strong> Features Higher Order Structure (HOS) capabilities, powered by Mnova BioHOS.&nbsp;</li></ul><h4><strong>Features:</strong></h4><h5><strong>New MCR Tool for Peak Purity Assessment in LCMS Data</strong></h5><p>Introduces an MCR tool based on the MCR-ALS algorithm for peak purity assessment, providing comprehensive tables and plots to streamline LCMS data analysis and enhance decision-making. This tool is available with the Advanced Chemometrics or BioHOS plugins and requires an MSChrom plugin license.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_Advanced_Chemometrics_New_MCR_Tool_for_Peak_Purity_Assessment_in_LCMS_Data_94993e71c3.webp" alt="Mestrelab Research: Mnova Advanced Chemometrics - New MCR Tool for Peak Purity Assessment in LCMS Data" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Mnova_Advanced_Chemometrics_New_MCR_Tool_for_Peak_Purity_Assessment_in_LCMS_Data_94993e71c3.webp 245w," sizes="100vw" width="1920" height="1200"></p><h5><strong>Enhanced Data Analysis with Partial Least Squares (PLS) Regression</strong></h5><p>Facilitates comprehensive analysis and accurate prediction of dependent variables from independent variables (such as binned spectra), while also providing intuitive graphical evaluation tools for deeper insights.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_Advanced_Chemometrics_Enhanced_Data_Analysis_with_Partial_Least_Squares_PLS_Regression_7363eca35a.webp" alt="Mestrelab Research: Mnova Advanced Chemometrics - Enhanced Data Analysis with Partial Least Squares (PLS) Regression" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Mnova_Advanced_Chemometrics_Enhanced_Data_Analysis_with_Partial_Least_Squares_PLS_Regression_7363eca35a.webp 211w," sizes="100vw" width="1175" height="870"></p><h5><strong>Advanced Data Classification with SIMCA Modeling</strong></h5><p>Offers a powerful statistical method for supervised classification of data, allowing researchers to categorize and analyze complex datasets with precision.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_Advanced_Chemometrics_Advanced_Data_Classification_with_SIMCA_Modeling_830f63d8a0.webp" alt="Mestrelab Research: Mnova Advanced Chemometrics - Advanced Data Classification with SIMCA Modeling" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Mnova_Advanced_Chemometrics_Advanced_Data_Classification_with_SIMCA_Modeling_830f63d8a0.webp 195w," sizes="100vw" width="1026" height="820"></p><h5><strong>Advanced PCA Analysis for In-Depth Data Insights</strong></h5><p>Provides features for comprehensive data exploration and visualization, including quantile plots (1D NMR), comparison tools, plot labels display, enhanced selection and interactivity in scores and loadings plots, and additional distance. calculation options in scores plots. These enhancements enable precise, interactive analysis for deeper data insights.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_Advanced_Chemometrics_Advanced_PCA_Analysis_for_In_Depth_Data_Insights_32b2644333.webp" alt="Mestrelab Research: Mnova Advanced Chemometrics - Advanced PCA Analysis for In-Depth Data Insights" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Mnova_Advanced_Chemometrics_Advanced_PCA_Analysis_for_In_Depth_Data_Insights_32b2644333.webp 245w," sizes="100vw" width="1026" height="647"></p>

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