Non-Destructive Detection of Pomegranate Blackheart Disease via Near-Infrared Spectroscopy and Soft X-ray Imaging Systems
Pomegranate blackheart disease, as an internal disease affecting the global pomegranate industry, is difficult to identify externally and urgently requires non-destructive detection methods for rapid diagnosis. This study established discriminative models for blackheart disease severity in pomegrana...
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MDPI AG
2025-07-01
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| Series: | Foods |
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| Online Access: | https://www.mdpi.com/2304-8158/14/14/2454 |
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| author | Rongke Nie Xingyi Huang Xiaoyu Tian Shanshan Yu Chunxia Dai Xiaorui Zhang Qin Fang |
| author_facet | Rongke Nie Xingyi Huang Xiaoyu Tian Shanshan Yu Chunxia Dai Xiaorui Zhang Qin Fang |
| author_sort | Rongke Nie |
| collection | DOAJ |
| description | Pomegranate blackheart disease, as an internal disease affecting the global pomegranate industry, is difficult to identify externally and urgently requires non-destructive detection methods for rapid diagnosis. This study established discriminative models for blackheart disease severity in pomegranates by using near-infrared (NIR) spectroscopy and soft X-ray imaging techniques. The results showed that the optimal NIR-based discriminative model, constructed with a Random Forest (RF) algorithm based on spectra preprocessed by the second-derivative (D2) denoising and a Competitive Adaptive Reweighted Sampling (CARS) algorithm, achieved a prediction set accuracy of 86.00%; the optimal soft X-ray imaging-based discriminative model, built with an RF algorithm using textural features extracted from images preprocessed by median filtering and a Contrast-Limited Adaptive Histogram Equalization (CLAHE) algorithm combined with gray-level co-occurrence matrix (GLCM) and gray-gradient co-occurrence matrix (GGCM) algorithms, reached a prediction set accuracy of 93.10%. In terms of model performance, the model based on soft X-ray imaging exhibited superior performance. Both techniques possess distinct advantages and limitations yet enable non-destructive detection of pomegranate blackheart disease. Further technical optimizations in the future could provide enhanced support for the healthy development of the pomegranate industry. |
| format | Article |
| id | doaj-art-2dc688d44da148558764fade19323b71 |
| institution | DOAJ |
| issn | 2304-8158 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Foods |
| spelling | doaj-art-2dc688d44da148558764fade19323b712025-08-20T03:08:09ZengMDPI AGFoods2304-81582025-07-011414245410.3390/foods14142454Non-Destructive Detection of Pomegranate Blackheart Disease via Near-Infrared Spectroscopy and Soft X-ray Imaging SystemsRongke Nie0Xingyi Huang1Xiaoyu Tian2Shanshan Yu3Chunxia Dai4Xiaorui Zhang5Qin Fang6School of Food and Biological Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, ChinaSchool of Food and Biological Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, ChinaSchool of Food and Biological Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, ChinaSchool of Food and Biological Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, ChinaSchool of Electrical and Information Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, ChinaSchool of Food and Biological Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, ChinaSchool of Food and Biological Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, ChinaPomegranate blackheart disease, as an internal disease affecting the global pomegranate industry, is difficult to identify externally and urgently requires non-destructive detection methods for rapid diagnosis. This study established discriminative models for blackheart disease severity in pomegranates by using near-infrared (NIR) spectroscopy and soft X-ray imaging techniques. The results showed that the optimal NIR-based discriminative model, constructed with a Random Forest (RF) algorithm based on spectra preprocessed by the second-derivative (D2) denoising and a Competitive Adaptive Reweighted Sampling (CARS) algorithm, achieved a prediction set accuracy of 86.00%; the optimal soft X-ray imaging-based discriminative model, built with an RF algorithm using textural features extracted from images preprocessed by median filtering and a Contrast-Limited Adaptive Histogram Equalization (CLAHE) algorithm combined with gray-level co-occurrence matrix (GLCM) and gray-gradient co-occurrence matrix (GGCM) algorithms, reached a prediction set accuracy of 93.10%. In terms of model performance, the model based on soft X-ray imaging exhibited superior performance. Both techniques possess distinct advantages and limitations yet enable non-destructive detection of pomegranate blackheart disease. Further technical optimizations in the future could provide enhanced support for the healthy development of the pomegranate industry.https://www.mdpi.com/2304-8158/14/14/2454pomegranatefood non-destructive detectionblackheart diseasenear-infrared spectroscopysoft X-ray |
| spellingShingle | Rongke Nie Xingyi Huang Xiaoyu Tian Shanshan Yu Chunxia Dai Xiaorui Zhang Qin Fang Non-Destructive Detection of Pomegranate Blackheart Disease via Near-Infrared Spectroscopy and Soft X-ray Imaging Systems Foods pomegranate food non-destructive detection blackheart disease near-infrared spectroscopy soft X-ray |
| title | Non-Destructive Detection of Pomegranate Blackheart Disease via Near-Infrared Spectroscopy and Soft X-ray Imaging Systems |
| title_full | Non-Destructive Detection of Pomegranate Blackheart Disease via Near-Infrared Spectroscopy and Soft X-ray Imaging Systems |
| title_fullStr | Non-Destructive Detection of Pomegranate Blackheart Disease via Near-Infrared Spectroscopy and Soft X-ray Imaging Systems |
| title_full_unstemmed | Non-Destructive Detection of Pomegranate Blackheart Disease via Near-Infrared Spectroscopy and Soft X-ray Imaging Systems |
| title_short | Non-Destructive Detection of Pomegranate Blackheart Disease via Near-Infrared Spectroscopy and Soft X-ray Imaging Systems |
| title_sort | non destructive detection of pomegranate blackheart disease via near infrared spectroscopy and soft x ray imaging systems |
| topic | pomegranate food non-destructive detection blackheart disease near-infrared spectroscopy soft X-ray |
| url | https://www.mdpi.com/2304-8158/14/14/2454 |
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