Nondestructive evaluation of soluble solids content in tomato with different stage by using Vis/NIR technology and...

Area of Science:

• Agricultural Science
• Spectroscopy
• Food Science

Background:

• Soluble solids content (SSC) is a key quality indicator for tomatoes.
• Accurate and rapid SSC measurement is crucial for tomato quality control and breeding.
• Traditional methods for SSC measurement are often time-consuming and destructive.

Purpose of the Study:

• To develop and validate a non-destructive method for predicting tomato SSC using Vis/NIR spectroscopy.
• To compare different spectral ranges and chemometric methods for optimal SSC prediction.
• To evaluate the effectiveness of wavelength selection techniques in enhancing prediction accuracy.

Main Methods:

• Vis/NIR spectroscopy (500-930 nm and 900-1400 nm) was used on 168 tomato samples.
• Spectral data preprocessing included first derivative and Standard Normal Variate (SNV) normalization.
• Competitive Adaptive Reweighted Sampling (CARS) and Random Frog (RF) were used for wavelength selection.
• Partial Least Squares (PLS) and Least Square-Support Vector Machines (LS-SVM) models were built for SSC prediction.

Main Results:

• The Partial Least Squares (PLS) model combined with Competitive Adaptive Reweighted Sampling (CARS) in the 900-1400 nm range showed the best performance (Rp = 0.820, RMSEP = 0.207 °Brix).
• This optimal model achieved desirable results on an independent set (Rp = 0.830, RMSEP = 0.316 °Brix).
• The study demonstrated the effectiveness of selected wavelengths for accurate SSC prediction.

Conclusions:

• Vis/NIR spectroscopy, coupled with appropriate chemometric methods and wavelength selection, provides an effective and rapid non-destructive technique for predicting tomato SSC.
• The developed method can be valuable for real-time quality assessment and breeding programs.
• This approach offers a significant improvement over traditional destructive methods for SSC determination.