Exploring the use of FT-NIR Spectroscopy and chemometrics to accurately determine the geographical origins of Chahayang and Wuchang rice varieties.

After screening the characteristic wavebands of the rice samples in the experimental fields, Fourier transform diffuse reflection near-infrared spectroscopy combined with chemometrics was used to determine the origin of the geographical indication products Chahayang rice and Wuchang rice from 2014 and 2015. Traceability testing. The results show that rice samples from different regions have significant differences in the band 5?136~5?501?cm-1. The qualitative analysis model established using the factorization method has a correct prediction rate of 100% for Chahayang and Wuchang rice in 2014, and the correct prediction rates for samples from the two regions in 2015 are 100% and 91.67% respectively. The quantitative analysis model established using the partial least squares method has a correct prediction rate of 90.90% and 95.83% for samples from the two regions in 2014, and a correct prediction rate of 91.67% and 87.50% for the samples from the two regions in 2015.

Exploring FT-NIR Spectroscopy for Rice Origin Verification

In recent years, the verification of the geographical origin of agricultural products has become a significant field of study, particularly for geographical indication products that carry a premium due to their unique regional characteristics. This paper focuses on the application of Fourier Transform Diffuse Reflection Near-Infrared (FT-NIR) Spectroscopy in combination with chemometrics to ascertain the geographical origins of Chahayang and Wuchang rice, two premium rice varieties with geographical indication status, harvested in the years 2014 and 2015.

Identifying Characteristic Wavebands in Rice Analysis

The research commenced with the screening of characteristic wavebands specific to the rice samples collected from experimental fields. It was found that the waveband region of 5136 to 5501 cm^-1 exhibited significant differences among rice samples from various regions. This discovery laid the groundwork for further analysis using sophisticated chemometric techniques.

Applying FT-NIR and Chemometrics in Rice Traceability

The methodology employed involved the use of FT-NIR Spectroscopy, a technique renowned for its efficiency and non-destructive nature, making it ideally suited for the analysis of agricultural products. Coupled with chemometric methods, the study aimed to establish models capable of accurately predicting the geographical origins of the rice samples.

Two main chemometric methods were utilized in this study: the factorization method for qualitative analysis and the Partial Least Squares (PLS) method for quantitative analysis. The results were promising, showcasing the potential of these methods in the field of traceability testing for agricultural products.

Achieving High Prediction Accuracy in Rice Origin Analysis

The qualitative analysis model, established using the factorization method, demonstrated an impressive correct prediction rate of 100% for both Chahayang and Wuchang rice samples from 2014. For the 2015 samples, the model maintained a 100% prediction accuracy for Chahayang rice and achieved a 91.67% accuracy for Wuchang rice. These results underscore the effectiveness of the factorization method in qualitative analysis, providing a reliable means of distinguishing between rice samples from different geographical origins.

Quantitative Analysis Success in Predicting Rice Geographical Origin

On the quantitative front, the PLS method was employed to establish a prediction model. For the 2014 samples, the model achieved correct prediction rates of 90.90% and 95.83% for Chahayang and Wuchang rice, respectively. The 2015 samples saw slightly lower, yet still commendable, prediction accuracies of 91.67% for Chahayang rice and 87.50% for Wuchang rice. These findings highlight the utility of the PLS method in quantitative analysis, offering a substantial degree of accuracy in predicting the geographical origin of rice samples.

Significance and Future Applications in Agricultural Traceability

This study’s findings are significant, providing a robust framework for the application of FT-NIR Spectroscopy and chemometrics in the traceability testing of geographical indication products. The high prediction accuracies achieved in both qualitative and quantitative models affirm the potential of these techniques in ensuring the authenticity and integrity of premium agricultural products. Future research could further refine these methods and explore their applicability to other products, bolstering the global agricultural economy’s sustainability and reliability.

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Original research was done by Yu Guo, Yu Jinchi, Zhou Yi, Song Xuejian, Zhang Dongjie, Wang Xinhui, Qian Lili

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