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تشخیص آلودگی قارچی در غده سیب‌زمینی با استفاده از تصویربرداری حرارتی | ||
| مهندسی بیوسیستم ایران | ||
| مقاله 1، دوره 48، شماره 3، مهر 1396، صفحه 243-253 اصل مقاله (913.16 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijbse.2017.212753.664821 | ||
| نویسندگان | ||
| سعید فرخزاد1؛ اسعد مدرس مطلق2؛ پرویز احمدی مقدم* 3؛ سعید جلالی هنرمند4؛ کامران خیر علی پور5 | ||
| 1دانشجوی دکتری، گروه مهندسی مکانیک بیوسیستم، دانشکده کشاورزی، دانشگاه ارومیه | ||
| 2دانشیار، گروه مهندسی مکانیک بیوسیستم، دانشکده کشاورزی، دانشگاه ارومیه | ||
| 3استادیار ،گروه مهندسی مکانیک بیوسیستم، دانشکده کشاورزی، دانشگاه ارومیه | ||
| 4استادیار، گروه زراعت و اصلاح نباتات پردیس کشاورزی و منابع طبیعی،دانشگاه رازی کرمانشاه | ||
| 5استادیار، گروه مهندسی مکانیک بیوسیستم، دانشکده کشاورزی، دانشگاه ایلام | ||
| چکیده | ||
| پوسیدگی خشک سیب‌زمینی یکی از خسارت‌زاترین بیماری‌های غده‌های سیب‌زمینی است که عامل اصلی آن قارچ فوزاریوم سولانی است. برای جلوگیری از توسعه بیماری پوسیدگی خشک سیب‌زمینی و کاهش تلفات آن، باید قارچ عامل شناسایی و از بین برده شود. روش‌های معمول در تشخیص آلودگی قارچی زمان‌بر، پرهزینه و مشکل هستند. در این تحقیق یک روش سریع و قابل اطمینان مبنی بر فناوری گرمانگاری فعال برای تشخیص غده‌های سالم و آلوده و هم‌چنین برای طبقه‌بندی مرحله آلودگی (آلوده یک روزه تا نه روزه) ارائه شده است. در گرمانگاری فعال دو سطح دمای گرم‌کن و چهار سطح زمان خنک شدن نمونه لحاظ شد. نتایج تجزیه واریانس و مقایسه میانگین اختلاف دمای سطح غده‌های سالم و آلوده نشان داد که دمای 90 درجه سانتی‌گراد گرم‌کن و خنک شدن 40 ثانیه نمونه‌ها بهترین تیمار برای داشتن بیشترین اختلاف بین غده‌های سالم و آلوده است. برای ارزیابی طبقه بند شاخص‌های آماری نظیر دقت، صحت، حساسیت و اختصاصی بودن محاسبه شد. دقت کلی طبقه بند 67/96 % بود. نتایج تحقیق حاضر نشان داد که روش ارائه شده در این تحقیق یکی از روش‌های توانمند بینایی ماشین در تشخیص کیفیت و سلامت مواد غذایی و محصولات کشاورزی است. | ||
| کلیدواژه‌ها | ||
| آلودگی قارچی؛ فوزاریوم سولانی؛ گرمانگاری؛ ماشین بردار پشتیبان | ||
| عنوان مقاله [English] | ||
| Fungal Infection in Potato Tuber Using Thermal Imaging | ||
| نویسندگان [English] | ||
| Saeid Farokhzad Farokhzad1؛ asad Modarese Motlagh2؛ parviz ahmadi moghadam3؛ Saeid Jalali Honarmand4؛ Kamran Khaieralipour5 | ||
| 1PhD . Candidate, Mechanical Engineering of Biosystems Department, Faculty of Agriculture, Urmia University, Iran | ||
| 2Associate Professor, Mechanical Engineering of Biosystems Department, Faculty of Agriculture, Urmia University, Iran | ||
| 3Assistant Professor, Mechanical Engineering of Biosystems Department, Faculty of Agriculture, Urmia University, Iran | ||
| 4Assistant Professor, Department of Agronomy and Plant Breeding, Campus of Agriculture and Natural Resources, Razi University, Iran | ||
| 5Assistant Professor, Mechanical Engineering of Biosystems Department, Faculty of Agriculture, Ilam University, Iran | ||
| چکیده [English] | ||
| Potato dry rot is one of the most detrimental diseases affecting on potato tubers caused by Fusarium Solani fungus. In order to prevent the expansion of potato dry rot and the losses caused by this disease, the fungi must be detected and destroyed. The common methods for detecting contaminations are time-consuming, expensive and painstaking. In this study, a fast and reliable method has been presented based on active thermography technology. This method was used to detect the healthy tubers from contaminated ones and to classify the different stages of contamination (1 to 9 day after infection). In the active thermography, two heating temperature levels and four cooling time levels were applied on the samples. The results of variance analysis and compare mean of the average temperature differences between the surfaces of the healthy and contaminated tubers indicated that 90 oC heating temperature and 40 s cooling time of the samples was the best treatment for detecting healthy and contaminated tubers. For evaluating the classifier performance, statistical indicators such as accuracy, precision, sensitivity and specificity were calculated. The total accuracy of the classifier was 96.67%. | ||
| کلیدواژه‌ها [English] | ||
| Fungal Infection, Fusarium Solani, thermography, Support vector Machine | ||
| مراجع | ||
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آمار تعداد مشاهده مقاله: 848 تعداد دریافت فایل اصل مقاله: 597 |
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