تجزیه و تحلیل صدای حاصل از اعمال ضربه به میوه انار به منظور تعیین رسیدگی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشکده مهندسی‌ زراعی و عمران روستایی، گروه مکانیک بیوسیستم، دانشگاه کشاورزی و منابع طبیعی رامین خوزستان

2 استادیار دانشگاه کشاورزی و منایع طبیعی رامین

3 گروه باغبانی، دانشگاه کشاورزی و منابع طبیعی رامین خوزستان

چکیده

یکی از آزمون‌های غیر مخرب توسعه یافته در تعیین رسیدگی میوه‌ها، تجزیه و تحلیل صدا و همچنین پردازش سیگنال حاصل از اعمال ضربه می‌باشد . لذا در این تحقیق به منظور ارزیابی کیفیت‌ و رسیدگی میوه انار یک سامانه ثبت پاسخ صوتی حاصل از ضربه توسعه یافت. بدین منظور صدای حاصل از ضربه150 عدد انار در سه مرحله رسیدگی (نارس، رسیده و بیش‌رس) ثبت گردید. برای ارزیابی کیفیت انار از میان ویژگی‌های مخرب میزان مواد جامد محلول، میزان اسیدیته، ویتامین ث، آنتوسیانین، فنل کل وpH اندازه‌گیری شدند؛ همچنین به منظور ثبت و استخراج ویژگی‌های صوتی (آزمون غیر مخرب)، جهت قرارگیری میکروفن نسبت به محل اعمال ضربه (پشت، کنار و زیر میوه) و درجه ضربه‌زن (5، 10 و 15 درجه) به عنوان متغیر مورد بررسی قرار گرفتند. به منظور طبقه‌بندی داده‌ها از الگوریتم درخت تصمیم‌گیری ترکیب شده با الگوریتم ژنتیک استفاده گردید. بر اساس آنالیز آماری که در سطح احتمال خطای %5 صورت گرفت مشخص گردید که؛ بهترین جهت قرارگیری میکروفن و زاویه ضربه‌زن به ترتیب قرارگیری میکروفن در کنار میوه و درجه ضربه زن 15 درجه می‌باشد. بر اساس نتایج طبقه‌بند، بیشترین و کمترین دقت به ترتیب %7/96 (در گروه رسیده)، 73% (در گروه بیش‌رس) و در نهایت دقت کلی %2/89 بدست آمد.

چکیده تصویری

تجزیه و تحلیل صدای حاصل از اعمال ضربه به میوه انار به منظور تعیین رسیدگی

تازه های تحقیق

  • از روش پردازش سیگنال و آنالیز صدا به منظور ارزیابی کیفیت­ و رسیدگی میوه انار استفاده شد.
  • جهت قرارگیری میکروفن نسبت به محل اعمال ضربه و درجه ضربه­زن به‌عنوان متغیر مورد بررسی قرار گرفتند.
  • به‌منظور طبقه­بندی داده­ها از الگوریتم درخت تصمیم­گیری  ترکیب شده با الگوریتم ژنتیک استفاده گردید.
  • بهترین جهت قرارگیری میکروفن در کنار میوه و زاویه ضربه­زن 15 درجه بود.
  • بیش‌ترین و کم‌ترین دقت طبقه­بندی به‌ترتیب %7/96 و 73%، و دقت کلی %2/89 به‌دست آمد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Analysis of the the impact response of pomegranate fruit to determine its maturity stage

نویسندگان [English]

  • Sulmaz Janati 1
  • Saman Abdanan Mehdizadeh 2
  • Mokhtar Heidari 3
1 Mechanics of Biosystems Engineering Department, Faculty of Agricultural Engineering and Rural Development, Ramin University of Agriculture and Natural Resources of Khuzestan.
2 Assistant Professor of Biosystems Engineering Department, Faculty of Agricultural Engineering and Rural Development, Agricultural Sciences and Natural Resources University of Khuzestan.
3 Associate Professor of Department of Horticulture, Faculty of Agriculture, Agricultural Sciences and Natural Resources University of Khuzestan.
چکیده [English]

One of the non-destructive tests developed for determining fruit maturity stage is the analysis of imapact fruit response of fruit . Therefore, in this study, in order to evaluate the quality and maturity stages of pomegranate fruit, a system for recording acoustic responses was developted. For this purpose, the acoustic response of 150 pomegranates in three maturity stages (immature, ripe, and over-ripe) was recorded. To evaluate the destructive properties, the total soluble solids, acidity, ascoric acid , anthocyanin, total phenol and pH were measured; Also, in order to record and extract the acoustic features (non-destructive test), positions of microphone (behind, next to and under the fruit), as well as the hitting angle (5, 10 and 15 degrees) were evaluated as variables. In order to classify the data, a decision tree classifier combined with the genetic algorithm was utilized. Based on the statistical analysis, it was determined that the best orientation of the microphone and the hitting angle were the placement of the microphone next to hitting ball and 15 degrees, respectivily. Based on the results of the classification, the highest, lowest and overall classification accuricy were 96.7% (in the ripe group), 73% (in the over-ripe group) and 89.2%, respectively.

کلیدواژه‌ها [English]

  • Pomegranate
  • Quality Parameters
  • Sound Analysis
  • Genetic algorithm
  • Classification
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