Ethylene Gas Measurement for Ripening of Fruits Using Image Processing

Srividhya, V.; Sujatha, K.; Ponmagal, R.S.

doi:10.17485/ijst/2016/v9i31/93838

Cited by 10 publications

(8 citation statements)

References 8 publications

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“…It also shows its toxic effects on human health. The work by Mustafa and Khairul [6] The highlight of the research work by Srividhya, Sujatha and Ponmagal [7] was that it could sense the presence of ethylene gas by using soft sensors that were built on the basis of Image Processing and Artificial Neural Networks (ANN) algorithms. The drawback of this technique is that it relied on the colour of the fruit at various stages in ripening.…”

Section: Literature Surveymentioning

confidence: 99%

A Consumer Friendly Machine Learning Based Mechanism to Recognize the Quality of Commercially Available Fruits

C.,

Jindal,

Reddy

et al. 2020

IJEAT

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Cultivators and sellers of many high-in-demand fruits traditionally preferred natural ripening after picking. Greed of hefty profits has motivated some of them to artificially hasten the ripening process at the cost of people’s health. Artificial ripening processes tend to degrade the entire quality of the fruit. The focus of this work is to describe a nondestructive method to detect artificial fruit ripening. To aid the detection, the proposed solution utilizes image processing and machine learning techniques to find the artificially ripened fruits. An input fruit image is selected as the test image. The next stage involves comparison of the features (histogram values) of the test image with the image of a naturally ripened one. A smartphone runs an android application to identify artificially ripened fruits. This work specifically concentrates on the commonly preferred Indian Mango and Indian Apple. The developed mechanism has an efficiency of 89-94% in correct detection.

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Section: Literature Surveymentioning

confidence: 99%

A Consumer Friendly Machine Learning Based Mechanism to Recognize the Quality of Commercially Available Fruits

C.,

Jindal,

Reddy

et al. 2020

IJEAT

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show abstract

“…To recognize levels of bananas they evolved statistical model and also contraption the system for processing of an image for bananas classification by extracting feature. In [9] Image processing technique is used to calculating the ethylene gas for ripening of fruits. In practice they also survey on existing methods for fruits ripening.…”

Section: An Overview On Thermal Image Processingmentioning

confidence: 99%

“…In [1] banana classification and quality analysis is done using image processing technique and quality relates to ripening stages of banana but not for the quality for contamination or decontamination with toxic chemicals. In [9] they conclude that ripening process by using exact concentration of ethylene gas is considered as a safe process. Image processing is used for ethylene gas measurement for fruit ripening.…”

Section: An Overview On Thermal Image Processingmentioning

confidence: 99%

An Overview on Thermal Image Processing

Ansari¹,

Salankar²

2017

Annals of Computer Science and Information Systems

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Abstract-Entire world is accentuated on inanition health certainty and food safety. Mostly, for fruit ripening the fruit seller uses calcium carbide and for human body the calcium carbide is exceptionally dangerous as it accommodates the phosphorous and arsenic traces. In many countries it is prohibited but in Pakistan, India, Nepal, and Bangladesh and in another country it is directly used. Quality assessment of banana fruit can be concluded by either human inspectors or instrumental tools. This paper presents a method of Thermal Imaging Technology for detection of banana fruit whether it is ripened by calcium carbide or naturally ripened. This paper also presents image preprocessing, image segmentation and feature extraction steps for processing of an image. For classifying these images the Neural Network is used.

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“…The binding of ethylene gas with receptor ETR1 in plants causes to increase the speed of the ripening process. Interaction between ethylene gas and ETR1 causes to translation of ripening genes and the senescence process is done . The ethylene gas is liberated from fruits in the respiratory activity in the ripening process.…”

Section: Introductionmentioning

confidence: 99%

“…The ethylene gas is liberated from fruits in the respiratory activity in the ripening process. The ripe fruits have some inappropriate features like flimsy and squashy, so the storage and transportation of ripe fruits are so difficult . The ethylene gas at low levels can stimulate the ripening of fruits like apple, apricot, banana, mango, and kiwi in a controlled environment of humidity and temperature.…”

Section: Introductionmentioning

confidence: 99%

Design of an optical sensor for ethylene based on nanofiber bacterial cellulose film and its application for determination of banana storage time

Pirsa

Chavoshizadeh

2018

Polymers for Advanced Techs

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In this work, new ethylene gas sensor was developed on the basis of portable bacterial cellulose (BC) nanofiber film doped with KMnO 4 (K-BC). The relationship between the concentration of KMnO 4 (8 × 10 −3 , 8 × 10 −4 , and 8 × 10 −5 mol L −1 ) and the optical and morphological properties of ethylene sensor was investigated. The Fourier-transform infrared results showed that some new interactions have occurred between BC membrane and KMnO 4 . The significant reduction in the relative intensity of the characteristic X-ray diffraction peak of BC in the doped films clearly indicates that the crystalline fraction decreases as a result of KMnO 4 addition. The fabricated K-BC was used for determination of ethylene concentration. The color, clarity, and absorbance of film at different concentrations of ethylene (10-2000 μg mL −1 ) were determined by spectrophotometer. Moisture absorption and water vapor permeability of BC were increased by the addition of KMnO 4 . Finally, the ethylene optical sensor was used for detection and determination of ethylene concentration in the bunch banana packages.

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Ethylene Gas Measurement for Ripening of Fruits Using Image Processing

Cited by 10 publications

References 8 publications

A Consumer Friendly Machine Learning Based Mechanism to Recognize the Quality of Commercially Available Fruits

A Consumer Friendly Machine Learning Based Mechanism to Recognize the Quality of Commercially Available Fruits

An Overview on Thermal Image Processing

Design of an optical sensor for ethylene based on nanofiber bacterial cellulose film and its application for determination of banana storage time

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