دورية أكاديمية
Detection of Oil Chestnuts Infected by Blue Mold Using Near-Infrared Hyperspectral Imaging Combined with Artificial Neural Networks
| العنوان: | Detection of Oil Chestnuts Infected by Blue Mold Using Near-Infrared Hyperspectral Imaging Combined with Artificial Neural Networks |
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| المؤلفون: | Lei Feng, Susu Zhu, Fucheng Lin, Zhenzhu Su, Kangpei Yuan, Yiying Zhao, Yong He, Chu Zhang |
| المصدر: | Sensors, Vol 18, Iss 6, p 1944 (2018) |
| بيانات النشر: | MDPI AG, 2018. |
| سنة النشر: | 2018 |
| المجموعة: | LCC:Chemical technology |
| مصطلحات موضوعية: | chestnuts, hyperspectral imaging technology, blue mold, artificial neural networks, Chemical technology, TP1-1185 |
| الوصف: | Mildew damage is a major reason for chestnut poor quality and yield loss. In this study, a near-infrared hyperspectral imaging system in the 874–1734 nm spectral range was applied to detect the mildew damage to chestnuts caused by blue mold. Principal component analysis (PCA) scored images were firstly employed to qualitatively and intuitively distinguish moldy chestnuts from healthy chestnuts. Spectral data were extracted from the hyperspectral images. A successive projections algorithm (SPA) was used to select 12 optimal wavelengths. Artificial neural networks, including back propagation neural network (BPNN), evolutionary neural network (ENN), extreme learning machine (ELM), general regression neural network (GRNN) and radial basis neural network (RBNN) were used to build models using the full spectra and optimal wavelengths to distinguish moldy chestnuts. BPNN and ENN models using full spectra and optimal wavelengths obtained satisfactory performances, with classification accuracies all surpassing 99%. The results indicate the potential for the rapid and non-destructive detection of moldy chestnuts by hyperspectral imaging, which would help to develop online detection system for healthy and blue mold infected chestnuts. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1424-8220 37235230 |
| Relation: | http://www.mdpi.com/1424-8220/18/6/1944; https://doaj.org/toc/1424-8220 |
| DOI: | 10.3390/s18061944 |
| URL الوصول: | https://doaj.org/article/3103f67e2b1b4e92ae881ce37235230f |
| رقم الأكسشن: | edsdoj.3103f67e2b1b4e92ae881ce37235230f |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 14248220 37235230 |
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| DOI: | 10.3390/s18061944 |