Articles
Evaluation of green asparagus (Asparagus officinalis L.) freshness treated by cassava starch-based coating using near-infrared spectroscopy
Article number
1382_14
Pages
109 – 116
Language
English
Abstract
The application of near-infrared (NIR) spectroscopy for predicting green asparagus quality was investigated.
In this study, green asparagus was treated with cassava starch-based coating (2, 3 and 4% of starch) and evaluated for the changes of quality in weight loss and firmness during 4 days of storage at room temperature (26±2°C, 65-70% RH). The coated samples significantly decreased weight loss and firmness reduction compared to uncoated samples (p<0.05). At the end of storage, samples coated with 4% of starch exhibited the highest quality retention efficiency compared to the remaining samples.
Furthermore, NIR spectra was acquired in the range of 900-1700 nm.
Partial least squares regression (PLSR) was performed on spectral data sets to build prediction models for quality changes at 3 parts of asparagus.
Besides, the preprocessing methods including standard normal variable (SNV), first derivative (lD) and second derivative (2D) were used for comparative analysis.
The PLSR-1D model outperformed other models in predicting weight loss rate with R2 value between 0.94 to 0.95 and RMSE value ranging from 3.05 to 3.24%. Moreover, the PLSR-1D model also exhibited the most accurate prediction for firmness, achieving the highest R2 value of 0.90 to 0.94 and an RMSE value within the range of 0.88 to 4.21 N. This study suggested the potential of NIR spectroscopy in examining the quality of asparagus treated with edible coating during storage.
In this study, green asparagus was treated with cassava starch-based coating (2, 3 and 4% of starch) and evaluated for the changes of quality in weight loss and firmness during 4 days of storage at room temperature (26±2°C, 65-70% RH). The coated samples significantly decreased weight loss and firmness reduction compared to uncoated samples (p<0.05). At the end of storage, samples coated with 4% of starch exhibited the highest quality retention efficiency compared to the remaining samples.
Furthermore, NIR spectra was acquired in the range of 900-1700 nm.
Partial least squares regression (PLSR) was performed on spectral data sets to build prediction models for quality changes at 3 parts of asparagus.
Besides, the preprocessing methods including standard normal variable (SNV), first derivative (lD) and second derivative (2D) were used for comparative analysis.
The PLSR-1D model outperformed other models in predicting weight loss rate with R2 value between 0.94 to 0.95 and RMSE value ranging from 3.05 to 3.24%. Moreover, the PLSR-1D model also exhibited the most accurate prediction for firmness, achieving the highest R2 value of 0.90 to 0.94 and an RMSE value within the range of 0.88 to 4.21 N. This study suggested the potential of NIR spectroscopy in examining the quality of asparagus treated with edible coating during storage.
Authors
T.T. Pham, H.X. Mac, N.T.T. Ha, Z.H. Siyum, L.P.L. Nguyen, N.H.N. Thi, T. Zsom, G. Hitka, L. Baranyai
Keywords
asparagus, edible coating, non-destructive, quality assessment, shelf-life
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