Applications | Nutritional Content Analysis of Rice Seeds Based on NIR Spectroscopy

2025-11-04

The nutritional quality of rice seeds directly impacts crop yield and agricultural product value, with key components such as protein, fat, and starch serving as essential indicators for quality assessment. Traditional chemical detection methods are cumbersome, time-consuming, labor-intensive, and environmentally unfriendly.

Optosky's near-infrared (NIR) spectrometer, combined with advanced spectral analysis technology, provides a complete solution for the rapid, non-destructive, and accurate analysis of rice seed nutritional content.

01 NIR Spectroscopy and Rice Seed Nutritional Analysis

Near-infrared spectroscopy (NIR) is a rapid, non-destructive analytical technique based on molecular vibrations. By measuring a sample's absorption and scattering characteristics in the NIR range (~700–2500 nm), it captures chemical composition information. This technique is particularly suitable for analyzing organic compounds containing chemical bonds such as C–H, O–H, and N–H, which correspond to the characteristic absorption features of protein, fat, and starch in rice seeds.

In recent published research, NIR spectroscopy was used to collect spectral data from six different rice seed varieties. Combined with chemometric algorithms, it successfully achieved accurate prediction of protein, fat, and starch content, with the best model reaching a prediction accuracy of R² = 0.971.

02 Technical Advantages of Optosky NIR Spectrometers

Optosky NIR spectrometers are specially optimized for agricultural detection applications and offer the following core technical features:

Excellent Optical Performance

Broad spectral range: Covers 900–2500 nm, fully capturing nutritional component characteristic spectra
High signal-to-noise ratio: >1000:1 ensures accurate detection of weak signals
Superior resolution: High optical resolution clearly distinguishes adjacent characteristic peaks
Stable light source system: High-performance halogen tungsten lamp provides stable and uniform illumination

Professional System Design

Transmission detection mode: Penetrates the rice seed interior to obtain comprehensive component information
Dedicated sampling accessories: Optimized sample chamber ensures consistency and repeatability
Intelligent temperature control system: Maintains stable detector temperature, reducing environmental interference
Modular structure: Supports customized configurations to meet diverse application needs

03 NIR Spectral Analysis and Modeling Process for Rice Seeds

3.1 Spectral Collection and Preprocessing

The study used transmission mode for spectral collection, effectively avoiding interference from the seed coat surface reflection and obtaining true internal composition information. Preprocessing methods such as Gaussian denoising, first-derivative processing, and multiplicative scatter correction (MSC) significantly improved spectral quality by:

Eliminating baseline drift and background noise
Enhancing resolution of characteristic spectral peaks
Correcting effects of uneven particle size and distribution

3.2 Characteristic Wavelength Selection

The successive projections algorithm (SPA) was used to screen key characteristic wavelengths from the full spectrum, reducing variable dimensions by over 70% while maintaining prediction accuracy and significantly improving model efficiency.

3.3 Prediction Model Construction

Multiple modeling methods were compared, including partial least squares (PLS), orthogonal partial least squares (OPLS), and artificial neural networks (ANN). The OPLS model demonstrated the best performance.

Nutritional Components	Coefficient of determination R²	Cross-validation Q²	RMSE	RMSECV
Fat	0.971	0.926	0.175	0.186
Starch	0.956	0.907	0.159	0.146
Protein	0.967	0.936	0.164	0.156

04 Technical Advantages and Value

4.1 Revolutionary Improvement in Detection Efficiency

Rapid analysis: Each sample takes only seconds, dozens of times faster than traditional methods
Non-destructive testing: No sample preparation required, preserving seed viability and commercial value
Multi-component synchronization: Obtain protein, fat, starch, and other component contents in a single scan

4.2 Key Support for Precision Agriculture

Variety breeding: Rapid screening of rice varieties with high nutritional value
Quality grading: Scientific and accurate grading of rice seed quality
Process monitoring: Tracking changes in nutritional components during storage

4.3 Significant Economic Benefits

Cost reduction: Less chemical reagent usage and lower labor costs
Value enhancement: Achieving premium pricing through quality grading
Facilitating trade: Providing reliable quality benchmarks for rice seed transactions

05 Application Prospects

The successful application of Optosky NIR spectrometers in rice seed nutritional analysis opens new pathways for quality detection in grain crops. The technology can be further extended to:

Other grain testing: Quality analysis of wheat, corn, soybeans, and other crops
Seed vitality assessment: Predicting germination rates based on nutritional content
Agricultural product processing: Raw material inspection and product quality control
Research and education: Analytical studies in agricultural universities and research institutions

Optosky IR Series Products:

IR2300 NIR Grain Analyzer

//www.optosky.net/IR2300.html

IR2000 AT-Line NIR Analyzer

//www.optosky.net/IR2000.html

Reference

Kong, H.; Wang, J.; Lin, G.; Chen, J.; Xie, Z. Analysis of Nutritional Content in Rice Seeds Based on Near-Infrared Spectroscopy. Photonics 2025, 12, 481. //doi.org/10.3390/photonics12050481.