Peaches are a fruit that originated in China and have been extensively farmed in various nations and areas for more than three thousand years. It is widely adored by customers and has grown to be the third-largest fruit in the world due to its delectable and sweet flavor. With the rise in living standards in recent years, there has been an increase in demand for peaches of superior quality.
Types of Peaches
China's four classic and well-known varieties of peach are the Yangshan, Feicheng, Shenzhou, and Fenghua.
The Fenghua peach, which has been grown for over 800 years and is regarded as the first peach in China by domestic and international peach specialists, is produced in Ningbo, Zhejiang. Produced in Shenzhou, Hebei, the Shenzhou peach has a long history of planting dating back to the Western Han Dynasty and was long considered a tribute of the imperial court. Produced in Feicheng, Shandong, the Feicheng peach is hailed as "the champion of peach groups" and has been grown there for 1700 years. In 2009, the Wall Street Journal referred to the Wuxi, Jiangsu-produced Yangshan peach as "the most delectable peach in the world."
Why the Geographic Origin Identification of Peaches is Important
These four classic and well-known peaches offer clear benefits over other peaches in terms of acidity, hardness, and soluble solids content (SSC), which are also significant indicators of peach quality. They cost a lot more than ordinary peaches as a consequence. The necessity to identify the geographic origin of peaches extends beyond the demands of peach suppliers because of the greater economic worth of peaches produced in certain places and the fact that peaches from various regions have distinctive flavors that influence customer choice. Consequently, it is imperative to pinpoint the region of origin for peaches.
Current Methods for Geographic Origin Identification of Peaches
Various techniques, including DNA analysis, high-performance liquid chromatography (HPLC), gas chromatography (GC), have been successfully used to pinpoint peaches' origin. However, these procedures' drawbacks include likely damaged samples, expensive to operate, and time-consuming and laborious process. Therefore, providing a practical, straightforward, and non-destructive way to determine geographic origin is essential.
Methods Used in this Study for Geographic Origin Identification of Peaches
The viability of using image processing technology, fluorescence spectroscopy and VIS-NIR spectroscopy to determine the geographic origin of peaches was investigated in this study. First, principal component analysis (PCA) was used to analyze the spectral data, and color attributes were retrieved from the pictures; then, the classification models for extreme learning machine (ELM), random forest (RF), k-nearest neighbor (KNN), and support vector machine (SVM) were developed. To streamline the models, the decision tree analysis was subsequently used to investigate the variables most closely associated with peaches' geographical origin. Peach quality characteristics such as SSC, firmness, diameter and mass were also measured.
Significant Findings of the Study
This research investigated the viability of using VIS-NIR, fluorescence, and image processing technologies to pinpoint peaches' origin. The findings demonstrated substantial variations between the four peach types employed in this study in hardness, SSC, mass, longitudinal diameter and transverse diameter (5% probability level).
Accuracy Achieved by Different Models
All models' accuracy was maximum when full spectral data and color features were utilized as the input data for ELM, RF, KNN, and SVM identification models. The best accuracy among all the models was of SVM (100%), whereas the least accuracy was of the ELM method (95%).
The SVM model created using HSV and RGB data achieved the maximum accuracy of 100% when HSV, RGB, fluorescence spectra and VIS-NIR spectra values were separately input into the models.
The fluorescence spectra and VIS-NIR's primary components, together with the color features, were taken and added to the models to make them simpler. The accuracy of the other three models, except for the ELM model, was found to be above 95%, with the KNN model having 100% accuracy.
According to decision tree analysis, the H-value, PC1 of the fluorescence spectrum, and R-value were crucial in determining the peaches' origin. With the exception of the ELM model, the accuracy of the classification models did not vary substantially when these three parameters were used as input data; the accuracy of the RF and KNN models became 98.75%.
Hence, utilizing image processing, fluorescence spectroscopy, and VIS-NIR spectroscopy technologies, the researchers could detect peaches from various geographic origins through an easy, effective and non-destructive method compared to conventional analytical methods.
Reference
Qinyi Yang, Shijie Tian, Huirong Xu (2022) Identification of the geographic origin of peaches by VIS-NIR spectroscopy, fluorescence spectroscopy and image processing technology. Journal of Food Composition and Analysis. https://www.sciencedirect.com/science/article/pii/S0889157522004616
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