کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
8881884 1624951 2018 10 صفحه PDF سفارش دهید دانلود رایگان
عنوان انگلیسی مقاله ISI
Non-destructive recognition and classification of citrus fruit blemishes based on ant colony optimized spectral information
ترجمه فارسی عنوان
تشخیص غیر مخرب و طبقه بندی پوسیدگی میوه های مرکبات بر اساس اطلاعات طیفی بهینه سازی شده در مورچه
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موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم زراعت و اصلاح نباتات
چکیده انگلیسی
Fast and accurate assessment of citrus fruit blemishes is critical to improve fruit quality and company profitability of citrus packinghouses and juice processing plants. This study aimed to identify spectral signatures of healthy fruit, and fruit exhibiting symptoms or damage from Huanglongbing (HLB), melanose, oleocellosis (oil spot), wind scar, leafminer and rust mites. Fruit samples were classified using identified spectral information. The current work proposes a characteristic waveband selection method based on the combination of the ant colony optimization (ACO) algorithm and variable selection principles. Six characteristic wavebands for each type of citrus blemishes were determined. Two different classification methods were established by the acquired characteristic wavebands, including simple layer support vector machine (SVM) classification models and tree-type SVM models. After using the tree-type SVM models, classification accuracies of healthy, HLB, melanose, oil spot, wind scar, leafminer and rust mite categories were 98.4%, 90.8%, 95.2%, 92.0%, 90.8%, 95.2% and 96.8%, respectively. The proposed characteristic wavebands selection methods were therefore very effective in extracting features of citrus fruit with these blemishes and the tree-type SVM classification models made it possible to correctly classify the fruit with high detection accuracies and universality.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Postharvest Biology and Technology - Volume 143, September 2018, Pages 119-128
نویسندگان
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