Pub Date : 2025-02-19DOI: 10.1016/j.saa.2025.125933
L. Castellino , E. Alladio , M. Vincenti , M. Moreau , C. Ruckebusch , R. Vitale
Forensic analysis of biological traces based on advanced approaches like DNA fingerprinting, serology and toxicology plays a crucial role in suspect identification and event reconstruction. In the last decades, non-destructive spectroscopic and imaging techniques have often permitted to gather preliminary information on the presence of biological fluids in specific locations of a crime scene. This study combines Raman hyperspectral imaging with chemometrics to characterize biological stains on cotton supports. Our results (obtained through the application of Soft Independent Modelling of Class Analogy – SIMCA – Principal Component Analysis – PCA – and Partial Least Squares Discriminant Analysis – PLS-DA) show that such a combination allows stains of 4 distinct biological fluids (i.e., blood, urine, sperm and saliva) to be successfully differentiated, paving the way to the development of a robust and accurate tool for on-site recognition and identification of liquid traces of forensic interest.
{"title":"Application of Raman hyperspectral imaging for bio-fluid spots segmentation and characterization on cotton supports","authors":"L. Castellino , E. Alladio , M. Vincenti , M. Moreau , C. Ruckebusch , R. Vitale","doi":"10.1016/j.saa.2025.125933","DOIUrl":"10.1016/j.saa.2025.125933","url":null,"abstract":"<div><div>Forensic analysis of biological traces based on advanced approaches like DNA fingerprinting, serology and toxicology plays a crucial role in suspect identification and event reconstruction. In the last decades, non-destructive spectroscopic and imaging techniques have often permitted to gather preliminary information on the presence of biological fluids in specific locations of a crime scene. This study combines Raman hyperspectral imaging with chemometrics to characterize biological stains on cotton supports. Our results (obtained through the application of Soft Independent Modelling of Class Analogy – SIMCA – Principal Component Analysis – PCA – and Partial Least Squares Discriminant Analysis – PLS-DA) show that such a combination allows stains of 4 distinct biological fluids (<em>i</em>.<em>e</em>., blood, urine, sperm and saliva) to be successfully differentiated, paving the way to the development of a robust and accurate tool for on-site recognition and identification of liquid traces of forensic interest.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125933"},"PeriodicalIF":4.3,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Phosphorescent tricarbonylrhenium(I) complexes that are more emissive in the aggregate state than in solution could be very valuable probes for biological analyses, but their development is delicate. The present work focuses on the synthesis and spectroscopic study of three new complexes that differ by the nature of their positively charged substituent. The dissolved complexes were very weakly emissive. Due to electrostatic interaction and aggregation, they showed a strong aggregation-induced phosphorescence enhancement (AIPE) effect in the presence of heparin, a polyanionic macromolecule of biological interest, and a weaker effect in the presence of chondroitin sulfate, which contains fewer negative charges. The magnitude of the AIPE effect depended on the nature and number of the cationic groups borne by the complex. However, it was weaker than expected from the behavior of the parent neutral complex studied in a conventional acetonitrile/water system, which highlights the challenge of accurately predicting solid-state emission properties for this class of molecules. This work introduces rhenium(I) complexes in the field of AIPE-active probes for the detection of polyanionic biomolecules.
{"title":"Tricarbonylrhenium(I) complexes with aggregation-induced phosphorescence emission (AIPE) properties: Application to the selective detection of heparin and its main contaminant","authors":"Corinne Vanucci-Bacqué , Valentine Guilbaud , Maëlle Deleuzière , Charles-Louis Serpentini , Florence Bedos-Belval , Eric Benoist , Suzanne Fery-Forgues","doi":"10.1016/j.saa.2025.125932","DOIUrl":"10.1016/j.saa.2025.125932","url":null,"abstract":"<div><div>Phosphorescent tricarbonylrhenium(I) complexes that are more emissive in the aggregate state than in solution could be very valuable probes for biological analyses, but their development is delicate. The present work focuses on the synthesis and spectroscopic study of three new complexes that differ by the nature of their positively charged substituent. The dissolved complexes were very weakly emissive. Due to electrostatic interaction and aggregation, they showed a strong aggregation-induced phosphorescence enhancement (AIPE) effect in the presence of heparin, a polyanionic macromolecule of biological interest, and a weaker effect in the presence of chondroitin sulfate, which contains fewer negative charges. The magnitude of the AIPE effect depended on the nature and number of the cationic groups borne by the complex. However, it was weaker than expected from the behavior of the parent neutral complex studied in a conventional acetonitrile/water system, which highlights the challenge of accurately predicting solid-state emission properties for this class of molecules. This work introduces rhenium(I) complexes in the field of AIPE-active probes for the detection of polyanionic biomolecules.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125932"},"PeriodicalIF":4.3,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143528738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-19DOI: 10.1016/j.saa.2025.125907
Xiang Deng , Huan Yang , An-Jie Gong , Xiao-Mei Huang , Lu Li
The excessive accumulation of heavy metal ions can pose significant hazards to human health and the environment, hence the detection and removal of heavy metal ions from water bodies are essential. Generally, carbon dots (CDs) are used as a good fluorescence sensor to sense heavy metal ions. In this study, using one-step microwave method, CDs were synthesized with the traditional Chinese medicine Radix Vladimiriae as a carbon source for the first time. These CDs display excellent fluorescence properties with an average particle size of approximately 5.9 nm and a fluorescence quantum yield (QY) about 0.15. The fluorescence emission spectra were recorded at different excitation peaks with the highest intensity emission peak observed at 465 nm with an excitation wavelength of 360 nm. Interestingly, fluorescence intensities of CDs greatly decreased in the existence of Fe3+. Under optimum conditions, a good linear relationship was observed between (I0-I)/I and the Fe3+ concentration in the range of 0.2–200 μM with the correlation coefficient (R2) of 0.9992 and the limit of detection (LOD) of 62 nM. Finally, after adding Fe3+ at concentrations of 5 μM, 20 μM, and 50 μM to real water samples, the relative standard deviation and spiked recovery rates were 1.2 %–2.7 % and 99.2 %–101.6 %, respectively. Thus, a novel method for rapid detection of Fe3+ were successfully discovered.
{"title":"Sensitive and selective chemosensor for Fe3+ detection using carbon dots synthesized by microwave method","authors":"Xiang Deng , Huan Yang , An-Jie Gong , Xiao-Mei Huang , Lu Li","doi":"10.1016/j.saa.2025.125907","DOIUrl":"10.1016/j.saa.2025.125907","url":null,"abstract":"<div><div>The excessive accumulation of heavy metal ions can pose significant hazards to human health and the environment, hence the detection and removal of heavy metal ions from water bodies are essential. Generally, carbon dots (CDs) are used as a good fluorescence sensor to sense heavy metal ions. In this study, using one-step microwave method, CDs were synthesized with the traditional Chinese medicine Radix Vladimiriae as a carbon source for the first time. These CDs display excellent fluorescence properties with an average particle size of approximately 5.9 nm and a fluorescence quantum yield (QY) about 0.15. The fluorescence emission spectra were recorded at different excitation peaks with the highest intensity emission peak observed at 465 nm with an excitation wavelength of 360 nm. Interestingly, fluorescence intensities of CDs greatly decreased in the existence of Fe<sup>3+</sup>. Under optimum conditions, a good linear relationship was observed between (<em>I</em><sub>0</sub>-<em>I</em>)/<em>I</em> and the Fe<sup>3+</sup> concentration in the range of 0.2–200 μM with the correlation coefficient (<em>R<sup>2</sup></em>) of 0.9992 and the limit of detection (LOD) of 62 nM. Finally, after adding Fe<sup>3+</sup> at concentrations of 5 μM, 20 μM, and 50 μM to real water samples, the relative standard deviation and spiked recovery rates were 1.2 %–2.7 % and 99.2 %–101.6 %, respectively. Thus, a novel method for rapid detection of Fe<sup>3+</sup> were successfully discovered.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125907"},"PeriodicalIF":4.3,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143511791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-18DOI: 10.1016/j.saa.2025.125918
Nafees Ahmad , Ghada Eid , Mohamed M. El-Toony , Asif Mahmood
The design of fluorescent dyes with optimized performance is crucial for advancements in various fields, including bioimaging, diagnostics, and optoelectronics. Traditional approaches to dye design often rely on trial-and-error experimentation, which can be time-consuming and resource-intensive. 42 ML models are tried for each property. One best model is selected for each property. Gradient boosting regressor is best model for the prediction of excitation values while extra trees regressor is best model for the prediction of emission values. A database of 5000 new dyes is generated and analyzed. 30 dyes with higher excitation and emission values are selected. Synthetic accessibility analysis is done for 30 dyes and majority of dyes are easy to synthesized. Our results demonstrate that ML-assisted design can significantly accelerate the discovery process, reduce the need for costly experimental iterations, and lead to the development of dyes with tailored properties for specific applications.
{"title":"Harnessing machine learning for the rational design of high-performance fluorescent dyes","authors":"Nafees Ahmad , Ghada Eid , Mohamed M. El-Toony , Asif Mahmood","doi":"10.1016/j.saa.2025.125918","DOIUrl":"10.1016/j.saa.2025.125918","url":null,"abstract":"<div><div>The design of fluorescent dyes with optimized performance is crucial for advancements in various fields, including bioimaging, diagnostics, and optoelectronics. Traditional approaches to dye design often rely on trial-and-error experimentation, which can be time-consuming and resource-intensive. 42 ML models are tried for each property. One best model is selected for each property. Gradient boosting regressor is best model for the prediction of excitation values while extra trees regressor is best model for the prediction of emission values. A database of 5000 new dyes is generated and analyzed. 30 dyes with higher excitation and emission values are selected. Synthetic accessibility analysis is done for 30 dyes and majority of dyes are easy to synthesized. Our results demonstrate that ML-assisted design can significantly accelerate the discovery process, reduce the need for costly experimental iterations, and lead to the development of dyes with tailored properties for specific applications.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125918"},"PeriodicalIF":4.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Understanding the complexity of membrane biochemical changes in in-vitro-induced elliptocytosis can be interesting as it may mimic those in hereditary elliptocytosis. Studying the membrane biochemical changes in metabolically active elliptocytes can be crucial, but most modern methods, such as ektacytometry and EMA binding tests, fail to do so. This study employs single-cell Raman spectroscopy, a proven technique to study biochemical changes in individual functional cells to investigate biochemical modifications in the membrane and cytoskeleton of elliptocytes. This was possible by applying a vortex beam, which can probe the RBC membrane with a reduced contribution from hemoglobin, which otherwise dominates the cell spectrum. Raman spectral variations in elliptocytes indicated changes in proteins, lipids, and lipid-protein interactions. The study also presented an incidental observation of diversity in membrane components and membrane-hemoglobin interaction among tested individuals.
{"title":"Unraveling biochemical differences in the membrane of functional RBCs and elliptocytes using vortex beam-based micro-Raman spectroscopy","authors":"Panchanil Sarmah , Cheviri Ghanashyam , Ruchee Khanna , Aseefhali Bankapur","doi":"10.1016/j.saa.2025.125911","DOIUrl":"10.1016/j.saa.2025.125911","url":null,"abstract":"<div><div>Understanding the complexity of membrane biochemical changes in <em>in-vitro</em>-induced elliptocytosis can be interesting as it may mimic those in hereditary elliptocytosis. Studying the membrane biochemical changes in metabolically active elliptocytes can be crucial, but most modern methods, such as ektacytometry and EMA binding tests, fail to do so. This study employs single-cell Raman spectroscopy, a proven technique to study biochemical changes in individual functional cells to investigate biochemical modifications in the membrane and cytoskeleton of elliptocytes. This was possible by applying a vortex beam, which can probe the RBC membrane with a reduced contribution from hemoglobin, which otherwise dominates the cell spectrum. Raman spectral variations in elliptocytes indicated changes in proteins, lipids, and lipid-protein interactions. The study also presented an incidental observation of diversity in membrane components and membrane-hemoglobin interaction among tested individuals.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125911"},"PeriodicalIF":4.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-18DOI: 10.1016/j.saa.2025.125920
Lu Bai , Xue Pan , Zhicheng Liu
The development of electrospun nanomaterials as highly efficient and portable substrates for surface-enhanced Raman scattering (SERS) is of great significance for rapid detection of pollutant molecules. In this work, we prepared sustainable polylactic acid (PLA) electrospun nanofibers decorated with silver nanoparticles (Ag NPs) as a flexible SERS substrate through a combined process of facile electrospinning and green plasma treatment. Using rhodamine 6G (R6G) as probe molecule, the PLA/Ag NPs composite nanofibers show excellent SERS performance and allow the detection of R6G at a low concentration of 10−10 M. In addition, the SERS substrate could be used for trace detection of pesticide thiram, and exhibits high sensitivity with a detection limit of 10−8 M. By taking advantage of the flexibility of the nanofibers, the nanofibrous membrane was pasted on the surface of an apple to sample and detect residual thiram, and the pesticide could be distinctly identified even at a low concentration of 10−7 M. The presence of dense Ag NPs with numerous hot-spots played a crucial role in the substrate’s high sensitivity for SERS detection. This environmentally friendly, self-supporting SERS substrate holds great promise for diverse applications, including environmental monitoring and medical diagnostics.
{"title":"Fabrication of a flexible nanofiber membrane for SERS detection of pollutants: An efficient and eco-friendly approach","authors":"Lu Bai , Xue Pan , Zhicheng Liu","doi":"10.1016/j.saa.2025.125920","DOIUrl":"10.1016/j.saa.2025.125920","url":null,"abstract":"<div><div>The development of electrospun nanomaterials as highly efficient and portable substrates for surface-enhanced Raman scattering (SERS) is of great significance for rapid detection of pollutant molecules. In this work, we prepared sustainable polylactic acid (PLA) electrospun nanofibers decorated with silver nanoparticles (Ag NPs) as a flexible SERS substrate through a combined process of facile electrospinning and green plasma treatment. Using rhodamine 6G (R6G) as probe molecule, the PLA/Ag NPs composite nanofibers show excellent SERS performance and allow the detection of R6G at a low concentration of 10<sup>−10</sup> M. In addition, the SERS substrate could be used for trace detection of pesticide thiram, and exhibits high sensitivity with a detection limit of 10<sup>−8</sup> M. By taking advantage of the flexibility of the nanofibers, the nanofibrous membrane was pasted on the surface of an apple to sample and detect residual thiram, and the pesticide could be distinctly identified even at a low concentration of 10<sup>−7</sup> M. The presence of dense Ag NPs with numerous hot-spots played a crucial role in the substrate’s high sensitivity for SERS detection. This environmentally friendly, self-supporting SERS substrate holds great promise for diverse applications, including environmental monitoring and medical diagnostics.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125920"},"PeriodicalIF":4.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-18DOI: 10.1016/j.saa.2025.125927
Yewei Pi , Ruirui Cui , Xinyong Gong , Chaoyong Deng
A novel Bi3+ doped Ba3Ga2O6 phosphor was successfully synthesized by high-temperature solid-state method in this work. The results of X-ray diffraction (XRD) characterization, scanning electron microscope (SEM) characterization and energy dispersive spectrometer (EDS) characterization indicate that Bi3+ ions were doped successfully into the lattice. The phosphor has a broad emission band covering the 350–580 nm spectral region peaked at 416 nm under the excitation at 340 nm, due to the 3P1 → 1S0 transition of Bi3+ ions. Furthermore, when Na+ ions and K+ ions were co-doped, the emission intensity increased by 1.53 times and 1.55 times, respectively. By combining Ba3Ga2O6: Bi3+, K+, the commercial green phosphor (Ba, Sr)2SiO4: Eu2+ and the commercial red phosphor CaAlSiN3: Eu2+ with a 340 nm UV chip, a pc-white LED was fabricated successfully. And the chromaticity coordinates of the WLED is (0.3647, 0.3329), the value of Correlated Color Temperature (CCT) is 4136 K and the Color Rendering Index (CRI) = 88.4. All results indicate that Ba3Ga2O6: Bi3+ phosphor can make a great contribution to the field of NUV-based WLEDs.
{"title":"Enhanced blue emission of Ba3Ga2O6: Bi3+ phosphor co-doped with alkali metal ions","authors":"Yewei Pi , Ruirui Cui , Xinyong Gong , Chaoyong Deng","doi":"10.1016/j.saa.2025.125927","DOIUrl":"10.1016/j.saa.2025.125927","url":null,"abstract":"<div><div>A novel Bi<sup>3+</sup> doped Ba<sub>3</sub>Ga<sub>2</sub>O<sub>6</sub> phosphor was successfully synthesized by high-temperature solid-state method in this work. The results of X-ray diffraction (XRD) characterization, scanning electron microscope (SEM) characterization and energy dispersive spectrometer (EDS) characterization indicate that Bi<sup>3+</sup> ions were doped successfully into the lattice<sub>.</sub> The phosphor has a broad emission band covering the 350–580 nm spectral region peaked at 416 nm under the excitation at 340 nm, due to the <sup>3</sup>P<sub>1</sub> → <sup>1</sup>S<sub>0</sub> transition of Bi<sup>3+</sup> ions. Furthermore, when Na<sup>+</sup> ions and K<sup>+</sup> ions were co-doped, the emission intensity increased by 1.53 times and 1.55 times, respectively. By combining Ba<sub>3</sub>Ga<sub>2</sub>O<sub>6</sub>: Bi<sup>3+</sup>, K<sup>+</sup>, the commercial green phosphor (Ba, Sr)<sub>2</sub>SiO<sub>4</sub>: Eu<sup>2+</sup> and the commercial red phosphor CaAlSiN<sub>3</sub>: Eu<sup>2+</sup> with a 340 nm UV chip, a pc-white LED was fabricated successfully. And the chromaticity coordinates of the WLED is (0.3647, 0.3329), the value of Correlated Color Temperature (CCT) is 4136 K and the Color Rendering Index (CRI) = 88.4. All results indicate that Ba<sub>3</sub>Ga<sub>2</sub>O<sub>6</sub>: Bi<sup>3+</sup> phosphor can make a great contribution to the field of NUV-based WLEDs.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125927"},"PeriodicalIF":4.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-18DOI: 10.1016/j.saa.2025.125930
Marlon Rodrigues , Everson Cezar , Glaucio Leboso Alemparte Abrantes dos Santos , Amanda Silveira Reis , Roney Berti de Oliveira , Leticia de Melo Teixeira , Marcos Rafael Nanni
This study investigated the development and validation of predictive models for estimating foliar nitrogen (N), phosphorus (P), and potassium (K) contents, along with shoot dry mass (SDM) of Brachiaria ruziziensis L. The approach utilized Vis-NIR-SWIR spectroscopy coupled with multivariate statistical techniques (PLS, PCR) and machine learning algorithms (SVM, RF). A triple-factorial, completely randomized design with ten replications per treatment was employed in a greenhouse setting. Treatments included type of input (limestone-mining coproducts), input particle size (filler and powder), and soil class (Arenosol and Ferralsol). Following input incubation, B. ruziziensis was sown. Forty days later, foliar spectra and leaves were collected. Chemical analysis determined NPK content, along with SDM. The study developed predictive models utilizing Vis-NIR-SWIR spectroscopy, Partial Least Squares (PLS), and machine learning algorithms like Support Vector Machine (SVM) and Random Forest (RF) to estimate foliar N, P, K, and biomass. Model adjustments achieved R2p > 0.70 and RPDp > 1.80 for PLS, SVM, and RF models across all variables (SDM, N, P, and K). These results highlight the effectiveness of specific spectral bands for nutrient and biomass discrimination and emphasize the potential of these techniques for rapid, non-destructive nutrient content estimation. The findings support the integration of advanced spectroscopic methods with machine learning algorithms for improved precision agriculture practices, providing a more sustainable alternative for nutrient and biomass analysis in forage crops. This approach optimizes forage production and minimizes atmospheric CO2 emissions.
{"title":"Unveiling the potential of Brachiaria ruziziensis: Comparative analysis of multivariate and machine learning models for biomass and NPK prediction using Vis-NIR-SWIR spectroscopy","authors":"Marlon Rodrigues , Everson Cezar , Glaucio Leboso Alemparte Abrantes dos Santos , Amanda Silveira Reis , Roney Berti de Oliveira , Leticia de Melo Teixeira , Marcos Rafael Nanni","doi":"10.1016/j.saa.2025.125930","DOIUrl":"10.1016/j.saa.2025.125930","url":null,"abstract":"<div><div>This study investigated the development and validation of predictive models for estimating foliar nitrogen (N), phosphorus (P), and potassium (K) contents, along with shoot dry mass (SDM) of <em>Brachiaria ruziziensis</em> L. The approach utilized Vis-NIR-SWIR spectroscopy coupled with multivariate statistical techniques (PLS, PCR) and machine learning algorithms (SVM, RF). A triple-factorial, completely randomized design with ten replications per treatment was employed in a greenhouse setting. Treatments included type of input (limestone-mining coproducts), input particle size (filler and powder), and soil class (Arenosol and Ferralsol). Following input incubation, <em>B. ruziziensis</em> was sown. Forty days later, foliar spectra and leaves were collected. Chemical analysis determined NPK content, along with SDM. The study developed predictive models utilizing Vis-NIR-SWIR spectroscopy, Partial Least Squares (PLS), and machine learning algorithms like Support Vector Machine (SVM) and Random Forest (RF) to estimate foliar N, P, K, and biomass. Model adjustments achieved R<sup>2</sup><sub>p</sub> > 0.70 and RPD<sub>p</sub> > 1.80 for PLS, SVM, and RF models across all variables (SDM, N, P, and K). These results highlight the effectiveness of specific spectral bands for nutrient and biomass discrimination and emphasize the potential of these techniques for rapid, non-destructive nutrient content estimation. The findings support the integration of advanced spectroscopic methods with machine learning algorithms for improved precision agriculture practices, providing a more sustainable alternative for nutrient and biomass analysis in forage crops. This approach optimizes forage production and minimizes atmospheric CO<sub>2</sub> emissions.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125930"},"PeriodicalIF":4.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Accurate assessment of soluble solid content (SSC) in blueberries is crucial for quality evaluation. However, in real production lines, blueberries are usually in random placement and the biological heterogeneity of blueberry parts can lead to spectral distortion, which affects the accuracy of SSC prediction models in various placement situations. Therefore, it is crucial to investigate an appropriate modeling method to minimize these negative effects. In this paper, we propose an approach that combines hyperspectral imaging (HSI) technique, residual multilayer perceptron, and transfer learning to build a universal model capable of detecting blueberry SSC in various placement situations. The study acquired SSC values of 1150 blueberry samples and hyperspectral data at different surfaces (stem end, calyx end, and two parts of the equatorial plane), used a residual multilayer perceptron to build a local model, and fine-tuned the model by transfer learning to improve its generalization ability. The results show that the optimized model has significantly improved prediction accuracy on different surfaces, especially the model based on equatorial surface data (enhanced-equator-1) performs well. In the external validation set, the model achieved correlation coefficients of prediction (rp) of 0.941, 0.924, 0.933, and 0.943; root mean square errors of prediction (RMSEP) of 0.539 %, 0.612 %, 0.571 %, and 0.542 %; and residual predictive deviations (RPD) of 2.91, 2.57, 2.75, and 2.90 on the four surfaces, respectively. This suggests that building a local model by residual multilayer perceptron and fine-tuning the model using the transfer learning method can eliminate the effect of the heterogeneity of blueberry parts on the model to a certain extent, enhance the robustness of the model to biological heterogeneity, and improve the accuracy of the detection of blueberry SSC under different placement situations.
{"title":"Exploring a universal model for predicting blueberry soluble solids content based on hyperspectral imaging and transfer learning to address spatial heterogeneity challenge","authors":"Guoliang Chen, Mianqing Yang, Guozheng Wang, Jingyuan Dai, Saiwei Yu, Baichao Chen, Dayang Liu","doi":"10.1016/j.saa.2025.125921","DOIUrl":"10.1016/j.saa.2025.125921","url":null,"abstract":"<div><div>Accurate assessment of soluble solid content (SSC) in blueberries is crucial for quality evaluation. However, in real production lines, blueberries are usually in random placement and the biological heterogeneity of blueberry parts can lead to spectral distortion, which affects the accuracy of SSC prediction models in various placement situations. Therefore, it is crucial to investigate an appropriate modeling method to minimize these negative effects. In this paper, we propose an approach that combines hyperspectral imaging (HSI) technique, residual multilayer perceptron, and transfer learning to build a universal model capable of detecting blueberry SSC in various placement situations. The study acquired SSC values of 1150 blueberry samples and hyperspectral data at different surfaces (stem end, calyx end, and two parts of the equatorial plane), used a residual multilayer perceptron to build a local model, and fine-tuned the model by transfer learning to improve its generalization ability. The results show that the optimized model has significantly improved prediction accuracy on different surfaces, especially the model based on equatorial surface data (enhanced-equator-1) performs well. In the external validation set, the model achieved correlation coefficients of prediction (<em>r<sub>p</sub></em>) of 0.941, 0.924, 0.933, and 0.943; root mean square errors of prediction (RMSEP) of 0.539 %, 0.612 %, 0.571 %, and 0.542 %; and residual predictive deviations (RPD) of 2.91, 2.57, 2.75, and 2.90 on the four surfaces, respectively. This suggests that building a local model by residual multilayer perceptron and fine-tuning the model using the transfer learning method can eliminate the effect of the heterogeneity of blueberry parts on the model to a certain extent, enhance the robustness of the model to biological heterogeneity, and improve the accuracy of the detection of blueberry SSC under different placement situations.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125921"},"PeriodicalIF":4.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-18DOI: 10.1016/j.saa.2025.125923
Xiaoli Zhang , Zhaoguang Wang , Jing Yang , Yingying Li , Cheng Lu , Yanqiang Hao , Guanbo He , Yongjian Zhang , Qifang Song , Jun Long , Jiajie Liang , Yong Tang
Currently, producing NPSH after HPV infection of cells has been confirmed. These NPSH-containing substances accumulate around the urethral opening and are subsequently washed out with urine. Therefore, indirect detection of HPV infection by assessing NPSH levels in urine is feasible, but it has not been reported in detail so far. Here, an assay using phosphotungstic acid to oxidise and produce colour changes by NPSH in urine was developed. This assay enabled the rapid, non-invasive identification of HPV infection by detecting the metabolic byproduct NPSH produced by HPV-infected cells. Employing a smartphone-based device, developed using an ambient light sensor, reduces the cost and simplifies the operation associated with the colourimetric assay. The colourimetric assay was used to detect L-cysteine and L-ascorbic acid standard substance (as NPSH mimics), the limited of detection were 0.12 mM and 31.25 μM, respectively, with high reproducibility and stability. When this colourimetric assay was used to evaluate urine samples from individuals suspected of HPV infection, along with other at-home self-screening methods for HPV nucleic acid detection in urine, showed comparable sensitivity and specificity. Compared with nucleic acid detection in urine, this colourimetric assay is cost-effective, user-friendly, amenable to self-sampling, and enables testing at one’s convenience and location of choice, which is more suitable for home self-testing or population self-screening.
{"title":"Smartphone-based urine colourimetric assay for home self-screening of HPV infection","authors":"Xiaoli Zhang , Zhaoguang Wang , Jing Yang , Yingying Li , Cheng Lu , Yanqiang Hao , Guanbo He , Yongjian Zhang , Qifang Song , Jun Long , Jiajie Liang , Yong Tang","doi":"10.1016/j.saa.2025.125923","DOIUrl":"10.1016/j.saa.2025.125923","url":null,"abstract":"<div><div>Currently, producing NPSH after HPV infection of cells has been confirmed. These NPSH-containing substances accumulate around the urethral opening and are subsequently washed out with urine. Therefore, indirect detection of HPV infection by assessing NPSH levels in urine is feasible, but it has not been reported in detail so far. Here, an assay using phosphotungstic acid to oxidise and produce colour changes by NPSH in urine was developed. This assay enabled the rapid, non-invasive identification of HPV infection by detecting the metabolic byproduct NPSH produced by HPV-infected cells. Employing a smartphone-based device, developed using an ambient light sensor, reduces the cost and simplifies the operation associated with the colourimetric assay. The colourimetric assay was used to detect L-cysteine and L-ascorbic acid standard substance (as NPSH mimics), the limited of detection were 0.12 mM and 31.25 μM, respectively, with high reproducibility and stability. When this colourimetric assay was used to evaluate urine samples from individuals suspected of HPV infection, along with other at-home self-screening methods for HPV nucleic acid detection in urine, showed comparable sensitivity and specificity. Compared with nucleic acid detection in urine, this colourimetric assay is cost-effective, user-friendly, amenable to self-sampling, and enables testing at one’s convenience and location of choice, which is more suitable for home self-testing or population self-screening.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125923"},"PeriodicalIF":4.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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