Detection of soluble solids content in tomatoes using full transmission Vis-NIR spectroscopy and combinatorial...

Area of Science:

• Agricultural Science
• Spectroscopy
• Chemometrics

Background:

• Soluble solids content (SSC) is crucial for tomato flavor but traditional measurement methods are destructive and time-consuming.
• Developing rapid, non-destructive methods for SSC assessment is essential for the tomato industry.

Purpose of the Study:

• To investigate the effectiveness of full transmittance visible and near-infrared (Vis-NIR) spectroscopy for predicting tomato SSC.
• To evaluate the impact of data acquisition orientation, spectral preprocessing, and wavelength selection on SSC regression models.

Main Methods:

• Utilized full transmittance Vis-NIR spectroscopy with multi-posed data acquisition (Z1 and Z2 directions).
• Applied four spectral preprocessing techniques and three wavelength selection methods.
• Developed Partial Least Squares Regression (PLSR) models for SSC prediction.

Main Results:

• The PLSR model using spectra from the Z2 direction and preprocessed data achieved good prediction (R = 0.877, RMSEP = 0.417%).
• A combination of wavelength selection methods (backward variable selection-partial least squares and simulated annealing) reduced wavelengths to 20 and improved prediction accuracy (R = 0.912, RMSEP = 0.354%).

Conclusions:

• Full-transmission Vis-NIR spectroscopy is effective for non-destructively predicting tomato SSC.
• Integrating advanced wavelength selection with intelligent algorithms offers a promising approach for rapid and accurate SSC assessment in tomatoes.