Author
Listed:
- Binbin Zhang
- Bin Peng
- Chunhua Zhang
- Zhizhong Song
- Ruijuan Ma
Abstract
Harvest maturity is closely related to peach fruit quality and has a very important effect on the fresh fruit market. Unfortunately, at present, it is difficult to determine the maturity level of peach fruits by artificial methods. The objectives of this study were to develop quadratic polynomial regression models using near-infrared spectroscopy that could determine the peel color difference, fruit firmness, soluble solids content (SSC), soluble sugar, organic acid components, and their relationships with the absorbance of chlorophyll (index of absorbance difference, IAD) in late maturing ‘Xiahui 8’ peach and ‘Xiaguang’ nectarine fruits. The analysis was based on data for fruits at veraison, fruits at harvesting maturity, and all fruits. The results showed that firmness has the highest correlation coefficient with IAD. Prediction models for fruit maturity were established between firmness and the IAD of the two cultivars using the quadratic polynomial regression method. Further variance analysis on the one degree term and quadratic term of each equation showed that every partial regression coefficient reached a significant or extremely significant level. No significant difference was observed between estimated and observed values after regression prediction. The regression equations seem to fit well. Other peach and nectarine varieties were used to test the feasibility of maturity prediction by this method, and it was found that maturity was successfully predicted in all the samples. The result indicated that the IAD can be used as an index to predict peach fruit maturity.
Suggested Citation
Binbin Zhang & Bin Peng & Chunhua Zhang & Zhizhong Song & Ruijuan Ma, 2017.
"Determination of fruit maturity and its prediction model based on the pericarp index of absorbance difference (IAD) for peaches,"
PLOS ONE, Public Library of Science, vol. 12(5), pages 1-11, May.
Handle:
RePEc:plo:pone00:0177511
DOI: 10.1371/journal.pone.0177511
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