{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T14:46:04Z","timestamp":1785422764064,"version":"3.56.0"},"reference-count":40,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T00:00:00Z","timestamp":1782518400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"SECIHTI","award":["1047606"],"award-info":[{"award-number":["1047606"]}]},{"award":["1047606"],"award-info":[{"award-number":["1047606"]}],"id":[{"id":"https:\/\/ror.org\/059ex5q34","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Chlorophyll-a (Chl-a) is commonly used as an indicator of phytoplankton biomass and water quality, but its determination usually depends on laboratory-based methods and specialized equipment. In this work, a portable multispectral fluorometer was developed and evaluated for Chl-a estimation in 90% acetone extracts prepared from water samples. The system integrates a nominal 420\u2013425 nm fluorescence excitation source, 90\u00b0 detection geometry, two multispectral sensors (AS7341 and AS7343), an ESP32-S3 microcontroller, and an Android application for device control and result visualization. A dataset of 76 samples was used for model development, including regression-model benchmarking, model selection, and internal testing. A Random Forest model selected for embedded implementation was exported to C++ for on-device inference. Validation using 15 independent samples yielded R2 = 0.979, root mean square error (RMSE) = 35.41 \u00b5g\/L, mean absolute error (MAE) = 28.91 \u00b5g\/L, and mean absolute percentage error (MAPE) = 6.14%. Agreement analysis showed a positive bias of 22.00 \u00b5g\/L, while repeatability tests showed a maximum coefficient of variation (CV) of 3.29%. Embedded inference was highly consistent with Python predictions (R2 = 0.997). These results suggest that the system is a promising portable alternative for Chl-a estimation in prepared acetone extracts under the evaluated conditions.<\/jats:p>","DOI":"10.3390\/s26134086","type":"journal-article","created":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T05:49:33Z","timestamp":1782712173000},"page":"4086","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Portable Multispectral Fluorometer with Embedded Machine Learning for Chlorophyll-a Estimation in Acetone-Extracted Samples"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-1848-0855","authenticated-orcid":false,"given":"Armando Daniel","family":"Blanco-J\u00e1quez","sequence":"first","affiliation":[{"name":"Departamento de Ingenier\u00eda Sustentable, SECIHTI\u2014Centro de Investigaci\u00f3n en Materiales Avanzados, Calle CIMAV 110, Ejido Arroyo Seco, Durango 34147, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1168-8544","authenticated-orcid":false,"given":"Mar\u00eda Teresa","family":"Alarc\u00f3n-Herrera","sequence":"additional","affiliation":[{"name":"Departamento de Ingenier\u00eda Sustentable, SECIHTI\u2014Centro de Investigaci\u00f3n en Materiales Avanzados, Calle CIMAV 110, Ejido Arroyo Seco, Durango 34147, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5825-9766","authenticated-orcid":false,"given":"Luz I.","family":"Valenzuela-Garc\u00eda","sequence":"additional","affiliation":[{"name":"Departamento de Ingenier\u00eda Sustentable, SECIHTI\u2014Centro de Investigaci\u00f3n en Materiales Avanzados, Calle CIMAV 110, Ejido Arroyo Seco, Durango 34147, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2459-0397","authenticated-orcid":false,"given":"Ana Elizabeth","family":"Mar\u00edn-Celestino","sequence":"additional","affiliation":[{"name":"Divisi\u00f3n de Geociencias Aplicadas, SECIHTI\u2014Instituto Potosino de Investigaci\u00f3n Cient\u00edfica y Tecnol\u00f3gica, A.C., Camino a la Presa San Jos\u00e9 2055, Col. Lomas 4ta Secci\u00f3n, San Luis Potosi 78216, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8635-1132","authenticated-orcid":false,"given":"Samuel","family":"Villarreal-Rodr\u00edguez","sequence":"additional","affiliation":[{"name":"Departamento de Ingenier\u00eda Sustentable, SECIHTI\u2014Centro de Investigaci\u00f3n en Materiales Avanzados, Calle CIMAV 110, Ejido Arroyo Seco, Durango 34147, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4629-9645","authenticated-orcid":false,"given":"V\u00edctor M.","family":"Ayala-Garc\u00eda","sequence":"additional","affiliation":[{"name":"Faculty of Chemical Sciences, Juarez University of Durango State, Durango 34120, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Finlandia","family":"Barbosa-Moreno","sequence":"additional","affiliation":[{"name":"Departamento de Ingenier\u00eda y Gesti\u00f3n Forestal y Ambiental, ETSI Montes, Universidad Polit\u00e9cnica de Madrid, 28040 Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7304-2928","authenticated-orcid":false,"given":"Diego Armando","family":"Mart\u00ednez-Cruz","sequence":"additional","affiliation":[{"name":"Departamento de Ingenier\u00eda Sustentable, SECIHTI\u2014Centro de Investigaci\u00f3n en Materiales Avanzados, Calle CIMAV 110, Ejido Arroyo Seco, Durango 34147, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1016\/j.watres.2003.10.033","article-title":"Freshwater phytoplankton quantification by chlorophyll a: A comparative study of in vitro, in vivo and in situ methods","volume":"38","author":"Gregor","year":"2004","journal-title":"Water Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"S56","DOI":"10.1016\/j.ecolind.2008.11.013","article-title":"Phytoplankton bloom status: Chlorophyll a biomass as an indicator of water quality condition in the southern estuaries of Florida, USA","volume":"9","author":"Boyer","year":"2009","journal-title":"Ecol. Indic."},{"key":"ref_3","first-page":"51","article-title":"Chlorophyll a and Its Use as an Indicator of Eutrophication in the Caloosahatchee Estuary, Florida","volume":"69","author":"Doering","year":"2006","journal-title":"Fla. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1002\/iroh.19900750207","article-title":"Comparison of Spectrophotometric, Fluorometric and High Performance Liquid Chromatography Methods for Determination of Chlorophyll a in Aquatic Samples: Effects of Solvent and Extraction Procedures","volume":"75","author":"Jacobsen","year":"1990","journal-title":"Int. Rev. Gesamten Hydrobiol. Hydrogr."},{"key":"ref_5","unstructured":"Arar, E.J. (1997). Method 445.0: In Vitro Determination of Chlorophyll a and Pheophytin a in Marine and Freshwater Algae by Fluorescence, Environmental Protection Agency."},{"key":"ref_6","unstructured":"Arar, E.J. (1997). Method 446.0: In Vitro Determination of Chlorophylls a, b, c1 + c2 and Pheopigments in Marine and Freshwater Algae by Visible Spectrophotometry, Environmental Protection Agency."},{"key":"ref_7","unstructured":"Arar, E.J. (1997). Method 447.0: Determination of Chlorophylls a and b and Identification of Other Pigments of Interest in Marine and Freshwater Algae Using High Performance Liquid Chromatography with Visible Wavelength Detection, Environmental Protection Agency."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Hamdhani, H., Eppehimer, D.E., Walker, D., and Bogan, M.T. (2021). Performance of a Handheld Chlorophyll-a Fluorometer: Potential Use for Rapid Algae Monitoring. Water, 13.","DOI":"10.3390\/w13101409"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1080\/10402381.2019.1607958","article-title":"To measure chlorophyll or phytoplankton biovolume: An aquatic conundrum with implications for the management of lakes","volume":"35","author":"Canfield","year":"2019","journal-title":"Lake Reserv. Manag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"125447","DOI":"10.1016\/j.talanta.2023.125447","article-title":"A low-cost and portable fluorometer based on an optical pick-up unit for chlorophyll-a detection","volume":"269","author":"Chen","year":"2024","journal-title":"Talanta"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"5474","DOI":"10.1039\/D3AY00991B","article-title":"A novel low-cost plug-and-play multi-spectral LED based fluorometer, with application to chlorophyll detection","volume":"15","author":"Power","year":"2023","journal-title":"Anal. Methods"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"13529","DOI":"10.1038\/s41598-022-17299-5","article-title":"Chlorophyll soft-sensor based on machine learning models for algal bloom predictions","volume":"12","author":"Mozo","year":"2022","journal-title":"Sci. Rep."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Zhao, X., Li, Y., Chen, Y., Qiao, X., and Qian, W. (2022). Water Chlorophyll a Estimation Using UAV-Based Multispectral Data and Machine Learning. Drones, 7.","DOI":"10.3390\/drones7010002"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Zhang, T., Sim, Y.L., Luo, J., and Ye, S. (2025). A High-Performance and Versatile Fluorometer for Chlorophyll a Monitoring. Biosensors, 15.","DOI":"10.3390\/bios15120787"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Lopin, P., Nawsang, P., Laywisadkul, S., and Lopin, K.V. (2025). Evaluation of Low-Cost Multi-Spectral Sensors for Measuring Chlorophyll Levels Across Diverse Leaf Types. Sensors, 25.","DOI":"10.20944\/preprints202503.1183.v1"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Kumar, M., Khamis, K., Stevens, R., Hannah, D.M., and Bradley, C. (2024). In-situ optical water quality monitoring sensors\u2014Applications, challenges, and future opportunities. Front. Water, 6.","DOI":"10.3389\/frwa.2024.1380133"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1145\/3608473","article-title":"Is TinyML Sustainable?","volume":"66","author":"Prakash","year":"2023","journal-title":"Commun. ACM"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1595","DOI":"10.1016\/j.jksuci.2021.11.019","article-title":"A review on TinyML: State-of-the-art and prospects","volume":"34","author":"Ray","year":"2022","journal-title":"J. King Saud. Univ.-Comput. Inf. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.psep.2023.09.072","article-title":"Applications of artificial intelligence technologies in water environments: From basic techniques to novel tiny machine learning systems","volume":"180","author":"Bagheri","year":"2023","journal-title":"Process Saf. Environ. Prot."},{"key":"ref_20","unstructured":"American Public Health Association (2017). 10200 Plankton. Standard Methods For the Examination of Water and Wastewater, American Public Health Association. [23rd ed.]. Available online: https:\/\/www.standardmethods.org\/doi\/10.2105\/SMWW.2882.207."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3977","DOI":"10.1016\/S0043-1354(01)00102-6","article-title":"Chlorophyll-a determination via continuous measurement of plankton fluorescence: Methodology development","volume":"35","author":"Pinto","year":"2001","journal-title":"Water Res."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Lakowicz, J.R. (2006). Principles of Fluorescence Spectroscopy, Springer.","DOI":"10.1007\/978-0-387-46312-4"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Stahl Kavai, M., and Da Silva, J.A.F. (2026). Application of a Low-Cost Fluorescence Detector for 3D-Printed Lab-on-a-Chip Microdevices. Hardware, 4.","DOI":"10.3390\/hardware4020008"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"7","DOI":"10.2150\/jstl.IEIJ240000668","article-title":"Enhancing Spectral Resolution by Fusing Data from Multiple Commercial Sensors","volume":"49","author":"Wichler","year":"2026","journal-title":"J. Sci. Technol. Light."},{"key":"ref_25","unstructured":"Hastie, T., Tibshirani, R., and Friedman, J. (2017). The Elements of Statistical Learning, Springer. [2nd ed.]."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","article-title":"Regression Shrinkage and Selection Via the Lasso","volume":"58","author":"Tibshirani","year":"1996","journal-title":"J. R. Stat. Soc. Ser. B Methodol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1023\/A:1022627411411","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1214\/aos\/1013203451","article-title":"Greedy Function Approximation: A Gradient Boosting Machine","volume":"29","author":"Friedman","year":"2001","journal-title":"Ann. Stat."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"e1557","DOI":"10.1002\/ecm.1557","article-title":"Cross validation for model selection: A review with examples from ecology","volume":"93","author":"Yates","year":"2023","journal-title":"Ecol. Monogr."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Hutter, F., Kotthoff, L., and Vanschoren, J. (2019). Automated Machine Learning: Methods, Systems, Challenges. The Springer Series on Challenges in Machine Learning, Springer International Publishing.","DOI":"10.1007\/978-3-030-05318-5"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Olson, R.S., Bartley, N., Urbanowicz, R.J., and Moore, J.H. (2016, January 20\u201324). Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science. Proceedings of the Genetic and Evolutionary Computation Conference 2016, Denver, CO, USA.","DOI":"10.1145\/2908812.2908918"},{"key":"ref_33","unstructured":"Salerno, S. (2026, June 23). Micromlgen: Port Machine Learning Models to Arduino and Microcontrollers. Available online: https:\/\/github.com\/eloquentarduino\/micromlgen."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"79","DOI":"10.3354\/cr030079","article-title":"Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance","volume":"30","author":"Willmott","year":"2005","journal-title":"Clim. Res."},{"key":"ref_35","unstructured":"(2025). Accuracy (Trueness and Precision) of Measurement Methods and Results\u2014Part 2: Basic Method for the Determination of Repeatability and Reproducibility of a Standard Measurement Method (Standard No. ISO 5725-2:2025). Available online: https:\/\/www.iso.org\/standard\/90054.html."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/S0140-6736(86)90837-8","article-title":"Statistical methods for assessing agreement between two methods of clinical measurement","volume":"327","author":"Bland","year":"1986","journal-title":"Lancet"},{"key":"ref_37","first-page":"162","article-title":"Selective Inner-Filter on the Fluorescence Response of Chlorophyll and Pheophytin Molecules Extracted from Caesalpinia echinata Leaves","volume":"31","author":"Lopes","year":"2020","journal-title":"J. Braz. Chem. Soc."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1016\/j.biosystemseng.2005.05.001","article-title":"Potential for Onsite and Online Analysis of Pig Manure using Visible and Near Infrared Reflectance Spectroscopy","volume":"91","author":"Saeys","year":"2005","journal-title":"Biosyst. Eng."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"11853","DOI":"10.3390\/s120911853","article-title":"Instrumentation in Developing Chlorophyll Fluorescence Biosensing: A Review","volume":"12","year":"2012","journal-title":"Sensors"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"134361","DOI":"10.1016\/j.scitotenv.2019.134361","article-title":"In situ fluorescence measurements of dissolved organic matter: A review","volume":"699","author":"Carstea","year":"2020","journal-title":"Sci. Total Environ."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/13\/4086\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T05:58:01Z","timestamp":1782712681000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/13\/4086"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,27]]},"references-count":40,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2026,7]]}},"alternative-id":["s26134086"],"URL":"https:\/\/doi.org\/10.3390\/s26134086","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,27]]}}}