ArticleSensors (Basel, Switzerland)2020
High-Throughput Phenotyping Approach for Screening Major Carotenoids of Tomato by Handheld Raman Spectroscopy Using Chemometric Methods.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 45 citations in OpenAlex.
- Recent advancements on innovative technologies and applications for non-destructive monitoring of tomato quality.Frontiers in plant science · 2026Review
- The SlymiR394-ZDS Module Enhances the Antioxidant Capacity of Tomato by Promoting Lycopene Synthesis.Biomolecules · 2025Article
- Raman Spectroscopy in the Characterization of Food Carotenoids: Challenges and Prospects.Foods (Basel, Switzerland) · 2025Review
- Carotenoids in Paprika Fruits and Ajvar: Chemical Characterization and Biological Activity.Foods (Basel, Switzerland) · 2025Article
- RamanSPy: An Open-Source Python Package for Integrative Raman Spectroscopy Data Analysis.Analytical chemistry · 2024Article
- An Integrated Approach for Biofortification of Carotenoids in Cowpea for Human Nutrition and Health.Plants (Basel, Switzerland) · 2024Review
- Nondestructive and Rapid Screening of Aflatoxin-Contaminated Single Peanut Kernels Using Field-Portable Spectroscopy Instruments (FT-IR and Raman).Foods (Basel, Switzerland) · 2024Article
- Development of a Quick-Install Rapid Phenotyping System.Sensors (Basel, Switzerland) · 2023Article
- Navigating with chemometrics and machine learning in chemistry.Artificial intelligence review · 2023Article
- Raman Spectroscopy Detects Changes in Carotenoids on the Surface of Watermelon Fruits During Maturation.Frontiers in plant science · 2022Article
- Comparative Transcriptome Profiling Analysis Reveals the Adaptive Molecular Mechanism of Yellow-Green Leaf inFrontiers in plant science · 2022Article
- Trends in artificial intelligence, machine learning, and chemometrics applied to chemical data.Analytical science advances · 2021Review
- Rapid Authentication of Potato Chip Oil by Vibrational Spectroscopy Combined with Pattern Recognition Analysis.Foods (Basel, Switzerland) · 2020Article
- Near-Infrared Spectroscopy Coupled Chemometric Algorithms for Rapid Origin Identification and Lipid Content Detection ofSensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Our objective was to develop a rapid technique for the non-invasive profiling and quantification of major tomato carotenoids using handheld Raman spectroscopy combined with pattern recognition techniques. A total of 106 samples with varying carotenoid profiles were provided by the Ohio State University Tomato Breeding and Genetics program and Lipman Family Farms (Naples, FL, USA). Non-destructive measurement from the surface of tomatoes was performed by a handheld Raman spectrometer equipped with a 1064 nm excitation laser, and data analysis was performed using soft independent modelling of class analogy (SIMCA)), artificial neural network (ANN), and partial least squares regression (PLSR) for classification and quantification purposes. High-performance liquid chromatography (HPLC) and UV/visible spectrophotometry were used for profiling and quantification of major carotenoids. Seven groups were identified based on their carotenoid profile, and supervised classification by SIMCA and ANN clustered samples with 93% and 100% accuracy based on a validation test data, respectively. All-
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.