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طبقه‌بندی محصول مرزه (Satureja hortensis L.) براساس سطح کود اوره مصرفی به کمک ماشین بویایی | ||
| تحقیقات گیاهان دارویی و معطر ایران | ||
| مقاله 8، دوره 35، شماره 5 - شماره پیاپی 97، آذر و دی 1398، صفحه 789-801 اصل مقاله (1.01 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijmapr.2019.125506.2525 | ||
| نویسندگان | ||
| فرانه خدامرادی1؛ اسماعیل میرزایی قلعه* 2؛ محمد جعفر دالوند3؛ روح الله شریفی4 | ||
| 1دانشجوی کارشناسی ارشد، گروه مهندسی مکانیک بیوسیستم، دانشگاه رازی، کرمانشاه، ایران | ||
| 2استادیار، گروه مهندسی مکانیک بیوسیستم، دانشگاه رازی، کرمانشاه، ایران | ||
| 3دانش‌آموخته مقطع دکتری، رشته مهندسی مکانیک بیوسیستم، دانشگاه تهران، تهران، ایران | ||
| 4استادیار، گروه گیاه‌پزشکی، دانشگاه رازی، کرمانشاه، ایران | ||
| چکیده | ||
| شناسه دیجیتال (DOR): 98.1000/1735-0905.1398.35.789.97.5.1591.1610 مرزه (Satureja hortensisL.) گیاهی معطر و از خانواده نعناعیان است که دارای خواص دارویی بسیار زیادی می‌باشد. امروزه در پرورش این گیاه از کود اوره استفاده می‌شود که تأثیر زیادی بر عملکرد آن دارد. اما استفاده بی‌رویه از کود اوره سلامت مصرف‌کننده را به شدت تهدید می‌کند. ازاین‌رو در این تحقیق، طبقه‌بندی محصول مرزه برداشت شده براساس میزان اوره مصرفی به کمک سامانه ماشین بویایی بررسی شد. اوره در چهار سطح (صفر، 50، 100 و 150 کیلوگرم در هکتار) به خاک اضافه شد. مرزه در کرت‌های آزمایشی و در شرایط گلخانه‌ای پرورش داده شد. رایحه نمونه‌ها به کمک سامانه بینی الکترونیک ارزیابی شد. به‌منظور بهبود سیگنال‌های خروجی بینی الکترونیک، داده‌ها به روش کسری نرمال شدند. برای ترکیب ویژگی‌ها از روش تحلیل مؤلفه‌های اصلی (PCA) و برای طبقه‌بندی آنها از شبکه عصبی مصنوعی (ANN) استفاده شد. براساس نتایج، حسگر TGS822 بهترین پاسخ را در محدوده تغییرات کود اوره مورد آزمایش از خود نشان داد. براساس نتایج تحلیل مؤلفه‌های اصلی، PC1 و PC2 93% واریانس داده‌ها را مورد پوشش قرار دادند. همچنین ماتریس اغتشاش بهترین ساختار ANN، تفکیک 100% را نشان داد. | ||
| کلیدواژه‌ها | ||
| تحلیل مؤلفه‌های اصلی؛ شبکه عصبی مصنوعی؛ کود اوره؛ ماشین بویایی؛ مرزه (Satureja hortensis L.) | ||
| عنوان مقاله [English] | ||
| Classification of savory (Satureja hortensis L.) based on the level of used urea fertilizer consumed using an olfactory machine | ||
| نویسندگان [English] | ||
| F. Khodamoradi1؛ E. Mirzaee- Ghaleh2؛ M.J. Dalvand3؛ R. Sharifi4 | ||
| 1M.Sc. student, Mechanical Engineering of Biosystem Department, Razi University, Kermanshah, Iran | ||
| 2Mechanical Engineering of Biosystem Department, Razi University, Kermanshah, Iran | ||
| 3Ph.D. graduate of Mechanical Engineering of Biosystems, University of Tehran, Tehran, Iran | ||
| 4Plant Protection Department, Razi University, Kermanshah, Iran | ||
| چکیده [English] | ||
| Summer savory (Satureja hortensisL.) is a fragrant herb in the Lamiaceae family with many medicinal properties. Today, urea fertilizer is used for growing this plant which has a great impact on its performance. However, the unnecessary use of urea fertilizer threatens consumer health. Therefore, in this research, the harvested savory plants were classified based on the amount of urea consumed by an olfactory machine. The urea was added to soil at four levels (0, 50, 100 and 150 kg ha-1). Plants were grown in experimental plots under greenhouse conditions. The fragrance of the samples was evaluated using the electronic nose system. In order to optimize the output signals of the electronic nose, the data were normalized by the fractional method. Principal component analysis (PCA) and artificial neural network (ANN) were used respectively to combine the features and classifying them. Based on the results, TGS822 sensorshowed the best response in the range of urea fertilizer tested. Based on the results of PCA, PC1 and PC2 accounted for 93% of the variance. Also, the confusion matrix showed a 100% correct classification rate by the best ANN structure. | ||
| کلیدواژه‌ها [English] | ||
| Principal component analysis, artificial neural network, urea fertilizer, olfactory machine, summer savory (Satureja hortensis L.) | ||
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