پديد آورندگان :
زندي، محسن دانشگاه زنجان - دانشكده كشاورزي - گروه علوم و مهندسي صنايع غذايي، زنجان، ايران , گنجلو، علي دانشگاه زنجان - دانشكده كشاورزي - گروه علوم و مهندسي صنايع غذايي، زنجان، ايران , بي مكر، ماندانا دانشگاه زنجان - دانشكده كشاورزي - گروه علوم و مهندسي صنايع غذايي، زنجان، ايران , قره باغي، ابوالفضل دانشگاه زنجان - دانشكده كشاورزي - گروه علوم و مهندسي صنايع غذايي، زنجان، ايران
كليدواژه :
پردازش تصوير , صدمات سطحي , انگور , پوشش دهي , درجه بندي
چكيده فارسي :
در پژوهش حاضر روش پردازش تصوير جديدي بر مبناي دو الگوريتم دودويي و RGB با هدف محاسبه ميزان صدمات سطحي به‌طور خودكار و انجام درجه‌بندي كيفي ايجاد گرديد. ابتدا انگورها با استفاده از فرمولاسيوني از سطوح مختلف صمغ فارسي (صفر، 1/5 و 3 درصد) و روغن شاهدانه (صفر، 0/075 و 0/15 درصد) و 0/3 درصد گليسرول پوشش‌دهي گرديد و در ادامه با اندازه‌گيري ميزان صدمات سطحي انگور در روزهاي 1 و 28 به‌صورت دستي (با كمك نرم‌افزار Image j)، ضمن بررسي اثر پوشش در قالب طرح فاكتوريل (طرح پايه كاملاً تصادفي)، عملكرد الگوريتم‌هاي پيشنهادي نيز ارزيابي گرديد. در الگوريتم دودويي پس از پيش‌پردازش تصاوير، تصاوير به تصاوير دودويي تبديل شدند. در الگوريتم RGB، فرآيند با كمك مقايسه آماري بين مولفه‌هاي رنگي صورت پذيرفت. پس از حذف دم انگور و محاسبه مناطق معيوب با كمك گشتاور تصوير (مرتبه صفر و اول)، در نهايت بر اساس درصد مناطق معيوب به 4 درجه كيفي عالي (كمتر از 5 درصد)، درجه 1 (بين 5 تا 20 درصد)، درجه 2 (بين 20 تا 35 درصد) و درجه 3 (بيشتر از 35 درصد) درجه‌بندي شد. مشخص شد كه از كانال‌هاي R، G و B با مقدار سطح آستانه 0/35، 0/45 و 0/3 مي‌توان براي فرآيند تشخيص صدمات سطحي استفاده نمود. نتايج نشان داد كه هر دو الگوريتم دودويي و RGB توانستند فرآيند محاسبه ميزان صدمات سطحي را با صحت بالايي (به‌ترتيب 97/33 و 98/08 درصد) انجام دهند و براساس نتايج ماتريكس درهم‌ريختگي فرآيند درجه‌بندي نيز با صحت بالاتر از 96/30 درصد انجام گرفت. همچنين مشخص شد كه پوشش‌دهي با صمغ فارسي و روغن شاهدانه خصوصاً در سطوح پايين سبب كاهش بروز صدمات سطحي طي دوره نگهداري مي‌گردد.
چكيده لاتين :
Introduction: Grape is a non-climacteric fruit with a low rate of physiological activity but is subject to serious physiological and parasitic disorders after harvest and during long term storage (Ciccarese et al., 2013). Currently, Edible
coatings have been studied as potential substitutes for conventional plastics in food packaging. Edible coating is a thin
layer of edible material formed as a coating on a food product. Edible coating can offer several advantages to the fresh
fruit and vegetable industry such as improvement in the retention of color, acids, sugar and flavor components, the
maintenance of quality during shipping and storage, the reduction of storage disorders and improved consumer appeal
(Antoniou et al., 2015; Cazon et al., 2017; Fakhouri et al., 2015; Galus & Kadzińska, 2015). Farsi gum as a novel source
of polysaccharides has drawn much attention in a wide range of various fields such as pharmaceutics, food and cosmetics
industries. Functional properties of Farsi gum are influenced by its structure and molecular weight (Hadian et al., 2016;
Joukar et al., 2017). By inclusion of bioactive compounds in the Farsi gum network the aforementioned impairments
could be overcome and moreover, new protective and functional valences could be added. The inclusion of lipid-based
component in Farsi gum gives it excellent light and moisture barrier properties. The benefic impact on human health of
hemp seed oil is worldwide recognized. A recent study demonstrated the antimicrobial properties of hemp seed oil. Due
to their abundance in biologically active compounds, hemp seed oil is promising natural alternatives that may extend the
shelf-life, microbiological safety and nutritional values of food (Cozmuta et al., 2015; Leizer et al., 2000; Salarnia et al.,
2018). Growing awareness of the quality of fruit has necessitated increasing effort to develop rapid and non-destructive
methods for evaluating fruit quality (Bhargava & Bansal, 2020; Rachmawati et al., 2017; Tao & Zhou, 2017; Wu & Sun,
2013). The aim of this study was the consideration of image processing application for grape sorting based on visual
surface characterize. Materials and Methods: Coating emulsion was prepared using (Farsi gum (0%, 1.5% and 3%), hemp seed oil (0%,
0.075% and 0.15%) and glyceride (0.3%)). grape fruit were coated by immersion in coating dispersion for 5 min. Samples
were then allowed to loss the excess coating dispersion. Coatings were developed at room temperature during an hour.
Samples were refrigerated at 4± 1°C for 28 days and analyses were performed at days 0 and 28. Defect identification and
maturity detection of grape fruits are challenging task for the computer vision to achieve near human levels of recognition.
The image acquisition was performed in a homogenously controlled lighting condition. Considering the camera lens’s
focal length, the samples were placed 25 cm under the camera’s lens to be under camera’s field of view. The images of
grape were segmented from the background using thresholding of the high contrast images via MATLAB software
(R2019a, image processing toolbox). The optimum threshold value was obtained to be 0.35, 0.45 and 0.30 for R, G and
B channel, respectively.
Results and Discussion: The proposed techniques can separate between the defected and the healthy grape fruits, and
then detect and classify the actual defected area. Classification is performed in two manners which in the first one, an input grape is classified with two different algorithms (RGB and binary). The Result showed that the accuracies for
detecting the surface defects on grape were 97.73% and 96.30% using RGB and binary algorithms, respectively. Proposed
method can be used to detect the visible defects of coated grape, and to grade the grape in high speed and precision.
Conclusions: The results of this research and similar ones can provide helpful recommendations in grading fruits for
fresh consumption. The simplicity and the efficiency of the proposed techniques make them appropriate for designing a low-cost hardware kit that can be used for real applications.
