Development of an Optical Smart Portable Instrument for Fruit Quality Detection

2021 ◽  
Vol 70 ◽  
pp. 1-9
Author(s):  
Sadjad Abasi ◽  
Saeid Minaei ◽  
Bahareh Jamshidi ◽  
Davood Fathi
Keyword(s):  
Fruit Quality ◽  
Portable Instrument ◽  
Quality Detection

scholarly journals Detection of Ridge Gourd (Luffa acutangula) Fruit Quality During Storage Using Near-Infrared Spectrometer

2018 ◽  
Author(s):  
Yuda Hadiwijaya
Keyword(s):  
Fruit Quality ◽  
Near Infrared ◽  
Plant Production ◽  
Maturity Stage ◽  
Quality Detection ◽  
Infrared Spectrometer ◽  
Total Dissolved Solid ◽  
Near Infrared Spectrometer ◽  
Luffa Acutangula ◽  
Absorbance Spectra

Fruit quality detection using near-infraread spectrometer is fast and it does not damage the fruit, hence the fruit is still marketable. The aim of this research focused on analyzing quality component of ridge gourd during storage using near-infrared spectrometer. The research was conducted on March to July 2017 at the Laboratory Plant Production Technology of Horticulture Division of Agriculture Faculty of Padjadjaran University, Jatinangor. Ridge gourds were harvested at the same maturity stage from the orchad, then stored at 5 and 10 days. The method used in this research was multivariate data analysis using Unscrambler software (version 7.51, CAMO, Oslo, Norway). The data acquisition was taken using portable near-infrared (NIR) spectrometer (NirVana AG410, Integrated Spectronics Pty, Ltd, Australia) with wavelength range of 600-1100 nm and stored as absorbance spectra and pretreated by secondderivatives spectra using ISIS software (Integrated Spectronics Pty, Ltd, Australia). The results showed that non-destrucive method using near-infrared spectrometer was able to measure ridge gourd fruit quality component such as, total dissolved solid, moisture content, firmness and color values.

Application and Imaging Processing Algorithm of Biospeckle Technology in Fruit Quality Detection

2019 ◽  
Vol 56 (9) ◽  
pp. 090003
Author(s):  
邓博涵 Deng Bohan ◽  
陈嘉豪 Chen Jiahao ◽  
胡孟晗 Hu Menghan ◽  
许文平 Xu Wenping ◽  
张才喜 Zhang Caixi
Keyword(s):  
Fruit Quality ◽  
Processing Algorithm ◽  
Imaging Processing ◽  
Quality Detection

A HTS dc SQUID-NMR: fabrication of the SQUID and application to low-field NMR for fruit quality detection

2014 ◽  
Author(s):  
J. Frédéric Isingizwe Nturambirwe ◽  
Willem J. Perold ◽  
Linus U. Opara
Keyword(s):  
Fruit Quality ◽  
Low Field ◽  
Quality Detection ◽  
Squid Nmr ◽  
Low Field Nmr

scholarly journals An Approach for Detecting Fruit Quality with RBF-SVM Classification Model

2021 ◽  
Vol 9 (VII) ◽  
pp. 1052-1058
Author(s):  
Sonia Chaudhary
Keyword(s):  
Fruit Quality ◽  
Detection System ◽  
Region Of Interest ◽  
Classification Model ◽  
Quality Analysis ◽  
Classification Rate ◽  
Svm Classification ◽  
Performance Factors ◽  
Quality Detection ◽  
Analysis System

For the regular development of rural area especially for the agriculture domain, automation is very important. Currently fruit's quality plays an important factor in their sales and production. Detecting the quality of fruits by using manual methods are not recommended because of the reasons that it cause delay and the results are also not upto the mark. Therefore, machine learning and computer vision is gaining much interest from current researchers to develop fruit quality detection systems. This paper contributes to provide an effective and advanced Orange fruit quality detection system. the proposed scheme is focused on giving an Fuzzy C-Mean based region of interest extracting scheme along with RBF-SVM classification model to improve the classification rate in comparison to existing approaches. The proposed scheme is simulated in MATLAB software and results are evaluated in terms of various performance factors such as Accuracy, Sensitivity, Specificity, Precision, Recall and F-Score. Finally a comparison of the proposed scheme is given that show an improvement of approximately 18% with respect to various state of art techniques. this strengthen the recommendation of proposed scheme for future fruit quality analysis system.

High performance ethylene sensor based on palladium-loaded tin oxide: Application in fruit quality detection

2020 ◽  
Vol 31 (8) ◽  
pp. 2045-2049 ◽  
Author(s):  
Qiuni Zhao ◽  
Zaihua Duan ◽  
Zhen Yuan ◽  
Xian Li ◽  
Wang Si ◽  
...  
Keyword(s):  
Fruit Quality ◽  
Tin Oxide ◽  
High Performance ◽  
Quality Detection
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