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Chemometrics for near infrared spectral analysis

A chemometric and near-infrared technology, applied in the field of chemometrics for near-infrared spectroscopy, can solve the problems of reduced efficiency and no complex calibration model memory

Inactive Publication Date: 2014-07-30
DOW AGROSCIENCES LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

however, these instruments do not contain enough memory to store the complex calibration models required and to perform data analysis
As such, these platforms experience severe inefficiencies when implementing data analysis of complex plant-based samples

Method used

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  • Chemometrics for near infrared spectral analysis
  • Chemometrics for near infrared spectral analysis
  • Chemometrics for near infrared spectral analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0198] Example 1: Using an Automated Machine Learning and Statistics Platform to Analyze Brassica Seed Characteristics

[0199] Materials and methods

[0200] Canola seed samples were prepared from Natreon canola, or canola with the yellow seed coat (YSC) trait. The training data is scanned in SpectraStar TM Whole canola seeds were collected in large spout cups on a 250Ox NIR spectrometer (Unity Scientific, Inc.) at wavelengths from 650-2500nm. 24 scans of 4 counterclockwise steps were averaged to obtain absorbance measurements. These scans were used to form training NIR spectra. To ensure consistent instrument performance throughout, internal standards were scanned before, during, and after scanning the training set.

[0201] calibration model

[0202] Development of PCR, PLS, ANN and SVM stoichiometric correction models for NIR spectroscopy using technical programming language. Cross-validation paths were developed and each calibration model was validated to be robus...

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Abstract

This disclosure concerns systems and methods for identifying and selecting a more accurate chemometric model for the analysis of specific plant samples via near infrared spectrometry. This disclosure further concerns the use of such systems and methods to identify characteristics and traits of interest in plants and plant samples, for example, to facilitate selective breeding, quality control, and / or inventory control.

Description

[0001] priority statement [0002] This application claims the benefit of US Provisional Patent Application Serial No. 61 / 538,662, filed September 23, 2011. field of invention [0003] The present disclosure relates to systems and methods for analyzing near-infrared spectroscopy data corresponding to plant traits and characteristics. Aspects of the present disclosure relate to methods for developing and identifying stoichiometric assays that are particularly useful for identifying plant traits of interest from near-infrared spectral data. Some aspects of the present disclosure relate to the use of global, automated systems and methods, such as, but not limited to, selecting plants comprising a trait or characteristic of interest from near-infrared spectroscopy data obtained from a variety of plants. Background of the invention [0004] Near Infrared Spectroscopy (NIRS) uses photon energy to collect information from chemical or biological samples in the energy range of about...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00G01N21/35G01N33/46
CPCG01N21/359G01N2201/129G01N21/3563G16C20/20G16C20/70
Inventor R.派D.Z.卡拉维洛C.卡尔D.加西亚
Owner DOW AGROSCIENCES LLC
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