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پایش غیرمخرب خواص کیفی سیبزمینی در انبار با تصویربرداری پس‌پراکنش نور لیزر | ||
| تحقیقات سامانه‌ها و مکانیزاسیون کشاورزی | ||
| دوره 25، شماره 92، اسفند 1403، صفحه 1-22 اصل مقاله (1.86 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/amsr.2026.372864.1536 | ||
| نویسندگان | ||
| منصوره مظفری گنبری* 1؛ بهاره جمشیدی2؛ جابر سلیمانی1؛ پریسا زرگری پور3 | ||
| 1استادیار پژوهش، بخش تحقیقات فنی و مهندسی کشاورزی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی آذربایجان‌شرقی، سازمان تحقیقات، آموزش و ترویج کشاورزی، تبریز، ایران | ||
| 2دانشیار پژوهش، بخش تحقیقات هوشمندسازی کشاورزی، موسسه تحقیقات فنی و مهندسی کشاورزی، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران | ||
| 3کارشناس بخش تحقیقات فنی و مهندسی کشاورزی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی آذربایجان‌شرقی، سازمان تحقیقات، آموزش و ترویج کشاورزی، تبریز، ایران | ||
| چکیده | ||
| پایش خواص سیبزمینی طی انبارداری نقش مهمی در تعیین زنجیرۀ مصرف، عرضۀ بهموقع محصول و کاهش ضایعات دارد. در این پژوهش، سامانۀ پایش غیرمخرب خواص سیبزمینی با استفاده از فناوری تصویربرداری پس‌پراکنش نور لیزر در محدوده نور مرئی و فروسرخ نزدیک نمونه‌سازی و ارزیابی شد. تصویربرداری طی نگهداری محصول در انبارهای سرد با دماهای 4 و 7 درجة سلسیوس و انبار سنتی صورت گرفت. در آزمایش‌ها از دو رقم سیبزمینی آگریا و جیلی استفاده شد. خواص محصول شامل درصد رطوبت، میزان نشاسته، مواد جامد حل‌شدنی و سفتی بافت طی انبارداری تعیین شد. ویژگی‌های مبتنی بر تحلیل‌های شدت نور و بافت تصاویر استخراج شد. از مدل شبکۀ عصبی مصنوعی برای به‌دست آوردن ارتباط بین هریک از خواص مذکور و ویژگی‌های تصاویر استفاده شد. نتایج حاصل نشان داد که طول موج 680 نانومتر در پیش‌بینی مقدار رطوبت، طول موج 880 نانومتر در پیش‌بینی سفتی و ترکیب دو طول موج در پیش‌بینی مواد جامد حل‌شدنی کل و درصد نشاسته موفق‌تر بودند. بیشترین مقدار ضریب همبستگی در پیش‌بینی مقدار رطوبت، مواد جامد حل‌شدنی، سفتی و درصد نشاسته به‌ترتیب 0/76، 0/82، 0/71و 0/73 به‌دست آمد. نتایج پژوهش بیانگر قابلیت استفاده از سامانه تصویربرداری پس‌پراکنش نور لیزر در سنجش خواص سیبزمینی انبارشده بود. | ||
| کلیدواژه‌ها | ||
| آزمون‌های غیرمخرب؛ انبارداری؛ پایش کیفی؛ پراکنش نور | ||
| عنوان مقاله [English] | ||
| Non-Destructive Monitoring of Potato Quality Properties in Storage by Laser Light Backscattering Imaging | ||
| نویسندگان [English] | ||
| Mansoureh Mozaffari Gonbari1؛ Bahareh Jamshidi2؛ Jaber Soleymani1؛ Parisa zargaripour3 | ||
| 1Assistant professor, Agricultural Engineering Research Department, East Azarbaijan Agricultural and Natural Resources Research and Education center, AREEO, Tabriz, Iran | ||
| 2Associate professor, Smart Agricultural Research Department, Agricultural Engineering Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran | ||
| 3Agricultural Engineering Research Department, East Azarbaijan Agricultural and Natural Resources Research and Education center, AREEO, Tabriz, Iran. | ||
| چکیده [English] | ||
| Monitoring potato quality attributes during storage is essential for optimizing supply chain management, ensuring timely product distribution, and minimizing postharvest losses. In this study, a non-destructive monitoring system for potato quality assessment was developed and evaluated using laser light backscattering imaging in the visible and near-infrared spectral regions. Backscattering images were acquired throughout the storage period under three storage conditions: cold storage at 4°C, cold storage at 7°C, and traditional storage. Two potato cultivars, Agria and Jelly, were included in the experiments. Key quality attributes, including moisture content, starch content, total soluble solids (TSS), and texture firmness, were measured periodically during storage. Features based on intensity and texture analyses of images were extracted. An artificial neural network model was employed to establish the relationship between the mentioned properties and image features. The results indicated that the 680 nm wavelength was the most effective for predicting moisture content, whereas the 880 nm wavelength provided superior performance for predicting firmness. The combination of both wavelengths performed well in predicting starch content and total soluble solid content. The highest correlation coefficients obtained for the prediction of moisture content, total soluble solids, firmness, and starch content were 0.76, 0.82, 0.71, and 0.73, respectively. These findings demonstrate the possibility of using laser backscattering imaging system for assessing the attributes of stored potatoes. | ||
| کلیدواژه‌ها [English] | ||
| Light scattering, Non-destructive tests, Quality monitoring, Storage | ||
| مراجع | ||
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