拉曼和FT-IR光谱与机器学习相结合,用于区分不同蔬菜作物种子品种
Stefan M Kolašinac1, Marko Mladenović2, Ilinka Pećinar1
1Department of Agrobotany, Faculty of Agriculture, University of Belgrade, Nemanjina 6, 11180 Belgrade, Serbia.
Plants (Basel, Switzerland)
|May 14, 2025
概括
拉曼和FT-IR光谱学与机器学习相结合,可以准确地识别种子品种. 这种方法为管理种子收集中的遗传资源提供了一个强大的工具.
科学领域:
- 频谱学是一种光谱学.
- 化学测量 化学测量 化学测量
- 生物信息学是一种生物信息学.
背景情况:
- 准确的种子品种识别对于作物管理和遗传资源保护至关重要.
- 传统的方法可能是耗时和劳动密集的.
研究的目的:
- 评估拉曼和FT-IR光谱法,以区分红,西红和生菜的种子品种.
- 评估各种化学测量模型和机器学习算法用于光谱数据分析的有效性.
主要方法:
- 用拉曼和FT-IR光谱分析了种子.
- 光谱数据经过预处理,包括平滑,基线校正和正常化.
- 分类是使用主要组件分析 (PCA),支向量机 (SVM),部分最小方位差异分析 (PLS-DA) 和PCA-二次差异分析 (PCA-QDA) 进行的.
主要成果:
- 支持矢量机 (SVM) 使用拉曼光谱技术实现了高分类准确率:百分之百的菜,百分之99.37的胡卜和92.71的西红.
- 使用SVM进行FT-IR光谱检测,对生菜的准确率为99.37%,对西红的准确率为92.50%,对西红的准确率为97.50%.
- 合并拉曼和FT-IR光谱提高了分类准确性, lettuce和西红的分类准确性达到100%, paprika的分类准确性达到95%.
结论:
- 拉曼和FT-IR光谱学与机器学习相结合,为种子品种歧视提供了快速有效的方法.
- 这种技术在种子银行中对遗传资源的评估和管理具有重大潜力.
更多相关视频
06:50O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
Published on: November 8, 2019
6.5K
07:37An Integrated Raman Spectroscopy and Mass Spectrometry Platform to Study Single-Cell Drug Uptake, Metabolism, and Effects
Published on: January 9, 2020
9.3K
相关概念视频
01:26Raman Spectroscopy Instrumentation: Overview
247
A conventional Raman spectrophotometer includes a laser source, a sample holding system, a wavelength selector, and a detector.
The monochromatic laser source, typically using visible or near-infrared radiation, generates a highly focused beam of light. This light interacts with the molecules of the sample, scattering some of the light. Liquid and gaseous samples are usually tested in ordinary glass capillaries, while solids can be analyzed as powders packed in capillaries or as potassium...
The monochromatic laser source, typically using visible or near-infrared radiation, generates a highly focused beam of light. This light interacts with the molecules of the sample, scattering some of the light. Liquid and gaseous samples are usually tested in ordinary glass capillaries, while solids can be analyzed as powders packed in capillaries or as potassium...
247
01:20Raman Spectroscopy: Overview
267
The underlying principle of Raman spectroscopy is based on the interaction between light and matter, specifically molecules' inelastic scattering of photons. When a monochromatic beam of light, typically from a laser source, interacts with a sample, most scattered light has the same frequency as the incident light. This is known as Rayleigh scattering.
However, a small fraction of the scattered light exhibits a frequency shift due to the exchange of energy between the incident photons and...
However, a small fraction of the scattered light exhibits a frequency shift due to the exchange of energy between the incident photons and...
267
02:16Light Acquisition
8.4K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
8.4K
01:03IR Frequency Region: Fingerprint Region
657
IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
657