{"title":"利用可见光/近红外光谱形态特征提高虫害蟹爪兰的鉴别精度","authors":"Yuanhao Zheng, Ying Zhou, Penghui Liu, Yingjie Zheng, Zichao Wei, Zetong Li, Lijuan Xie","doi":"10.1007/s11694-024-02841-y","DOIUrl":null,"url":null,"abstract":"<div><p>The visible/near-infrared (Vis/NIR) spectroscopy technique is effective for fruit quality detection. The distinct spectral features can reflect the internal composition of fruits, while variations in external orientation may induce interference. Considering both external and internal factors, we improved the discrimination accuracy of pest-infested crabapples by compensating for variations in orientation and amplifying differences in spectral morphological features (SMFs). Firstly, spectral intensity variations caused by orientations and morphological differences caused by pest infestation were analyzed. Based on these differences, the global model was established to mitigate the external orientation influence. Subsequently, SMFs, derived from spectral peaks and troughs, were employed to amplify spectral features. Finally, with the supplementation using 1<sup>st</sup> deviation, SMFs improved the discrimination performance of the partial least square–linear discriminant analysis (PLS-LDA) model for pest infestation, yielding results of sensitivity, specificity, and accuracy as 95.14%, 96.32%, and 95.94%, respectively. Overall, compensating for external orientation variations and exploiting internal spectral features enhanced the detection accuracy of pest infestation, providing valuable insights for internal defect discrimination based on Vis/NIR spectroscopy.</p></div>","PeriodicalId":631,"journal":{"name":"Journal of Food Measurement and Characterization","volume":"18 10","pages":"8755 - 8766"},"PeriodicalIF":2.9000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improving discrimination accuracy of pest-infested crabapples using Vis/NIR spectral morphological features\",\"authors\":\"Yuanhao Zheng, Ying Zhou, Penghui Liu, Yingjie Zheng, Zichao Wei, Zetong Li, Lijuan Xie\",\"doi\":\"10.1007/s11694-024-02841-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The visible/near-infrared (Vis/NIR) spectroscopy technique is effective for fruit quality detection. The distinct spectral features can reflect the internal composition of fruits, while variations in external orientation may induce interference. Considering both external and internal factors, we improved the discrimination accuracy of pest-infested crabapples by compensating for variations in orientation and amplifying differences in spectral morphological features (SMFs). Firstly, spectral intensity variations caused by orientations and morphological differences caused by pest infestation were analyzed. Based on these differences, the global model was established to mitigate the external orientation influence. Subsequently, SMFs, derived from spectral peaks and troughs, were employed to amplify spectral features. Finally, with the supplementation using 1<sup>st</sup> deviation, SMFs improved the discrimination performance of the partial least square–linear discriminant analysis (PLS-LDA) model for pest infestation, yielding results of sensitivity, specificity, and accuracy as 95.14%, 96.32%, and 95.94%, respectively. Overall, compensating for external orientation variations and exploiting internal spectral features enhanced the detection accuracy of pest infestation, providing valuable insights for internal defect discrimination based on Vis/NIR spectroscopy.</p></div>\",\"PeriodicalId\":631,\"journal\":{\"name\":\"Journal of Food Measurement and Characterization\",\"volume\":\"18 10\",\"pages\":\"8755 - 8766\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Food Measurement and Characterization\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s11694-024-02841-y\",\"RegionNum\":3,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"FOOD SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Food Measurement and Characterization","FirstCategoryId":"97","ListUrlMain":"https://link.springer.com/article/10.1007/s11694-024-02841-y","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Improving discrimination accuracy of pest-infested crabapples using Vis/NIR spectral morphological features
The visible/near-infrared (Vis/NIR) spectroscopy technique is effective for fruit quality detection. The distinct spectral features can reflect the internal composition of fruits, while variations in external orientation may induce interference. Considering both external and internal factors, we improved the discrimination accuracy of pest-infested crabapples by compensating for variations in orientation and amplifying differences in spectral morphological features (SMFs). Firstly, spectral intensity variations caused by orientations and morphological differences caused by pest infestation were analyzed. Based on these differences, the global model was established to mitigate the external orientation influence. Subsequently, SMFs, derived from spectral peaks and troughs, were employed to amplify spectral features. Finally, with the supplementation using 1st deviation, SMFs improved the discrimination performance of the partial least square–linear discriminant analysis (PLS-LDA) model for pest infestation, yielding results of sensitivity, specificity, and accuracy as 95.14%, 96.32%, and 95.94%, respectively. Overall, compensating for external orientation variations and exploiting internal spectral features enhanced the detection accuracy of pest infestation, providing valuable insights for internal defect discrimination based on Vis/NIR spectroscopy.
期刊介绍:
This interdisciplinary journal publishes new measurement results, characteristic properties, differentiating patterns, measurement methods and procedures for such purposes as food process innovation, product development, quality control, and safety assurance.
The journal encompasses all topics related to food property measurement and characterization, including all types of measured properties of food and food materials, features and patterns, measurement principles and techniques, development and evaluation of technologies, novel uses and applications, and industrial implementation of systems and procedures.