MY164318A - A system for fruit grading and quality determination - Google Patents

A system for fruit grading and quality determination

Info

Publication number
MY164318A
MY164318A MYPI2010700086A MYPI2010700086A MY164318A MY 164318 A MY164318 A MY 164318A MY PI2010700086 A MYPI2010700086 A MY PI2010700086A MY PI2010700086 A MYPI2010700086 A MY PI2010700086A MY 164318 A MY164318 A MY 164318A
Authority
MY
Malaysia
Prior art keywords
fruit
classification
ripeness
processing unit
ripe
Prior art date
Application number
MYPI2010700086A
Inventor
Rashid Bin Mohamed Shariff Abdul
Rodzi Mahmud Ahmad
Zulhaidi Mohd Helmi
Mohamed Ben Saeed Osama
Din Bin Amiruddin Mohd
Original Assignee
Univ Putra Malaysia
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Univ Putra Malaysia filed Critical Univ Putra Malaysia
Priority to MYPI2010700086A priority Critical patent/MY164318A/en
Priority to BR112013013330A priority patent/BR112013013330A2/en
Priority to PCT/MY2011/000237 priority patent/WO2012074372A2/en
Publication of MY164318A publication Critical patent/MY164318A/en

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/02—Food
    • G01N33/025—Fruits or vegetables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/47—Scattering, i.e. diffuse reflection
    • G01N21/4738—Diffuse reflection, e.g. also for testing fluids, fibrous materials
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/85—Investigating moving fluids or granular solids

Abstract

A SYSTEM FOR FRUIT GRADING AND QUALITY DETERMINATION, THE SYSTEM (10) INCLUDES: A) HOUSING (12) WITH AN ENCLOSURE (12A) FOR SCANNING PROCESS; B) AN ILLUMINATION MEANS (14) TO PROVIDE SHADOW FREE ILLUMINATION; C) A SPECTRAL CAMERA (16) EQUIPPED WITH HYPERSPECTRAL SCANNER TOGETHER WITH A SUITABLE CHARGE-COUPLED DEVICE (CCD) ARRAY FOR CAPTURING FRUIT SAMPLE’S IMAGE; D) A CONVEYING MEANS (18) TO PROVIDE SCANNING PLATFORM TO THE SYSTEM; E) A PROCESSING UNIT (20) TO PROCESS AND ANALYZE THE FRUIT SAMPLE IMAGE; AND F) A DATA ACQUISITION INTERFACE (22) PROVIDED IN BETWEEN THE SPECTRAL CAMERA (16) AND THE PROCESSING UNIT (20); CHARACTERIZED IN THAT, THE SYSTEM (10) UTILIZES HYPERSPECTRAL IMAGING TECHNOLOGY FOR AGRICULTURAL PRODUCT AND QUALITY INSPECTIONS, SAID SYSTEM (10) IS SUBJECTED TO AN ARTIFICIAL NEURAL NETWORK (ANN) TECHNIQUE FOR PURPOSES OF OIL PALM FRESH FRUIT BUNCH (FFB) RIPENESS CLASSIFICATION, SUCH THAT THE TECHNIQUE OF RIPENESS CLASSIFICATION OF OIL PALM FFB IMAGE IS DONE BY ANALYSIS OF THE FRUIT SAMPLE OF THREE DIFFERENT RIPENESS CATEGORIES: UNDER RIPE, RIPE AND OVER RIPE; WHEREIN THE ENCLOSURE (12A) OF THE HOUSING (12) IS FORMED BY DARKEN FINISHING MATERIAL; AND THE CONVEYING MEANS (18) IS FURNISHED WITH NON-REFLECTIVE FINISHING FOR CARRYING THE FRUIT SAMPLES INTO THE ILLUMINATION FIELD OF THE SYSTEM; AND WHEREIN THE PROCESSING UNIT (20) USED DATA PROCESSING SOFTWARE SUCH AS MATLAB® TO PERFORM THE ANALYSIS OF THE FRUIT SAMPLE CLASSIFICATION AND TO OBTAIN THE RESULTANT QUALITY DATA. FIGS. 1A AND 1B
MYPI2010700086A 2010-11-30 2010-11-30 A system for fruit grading and quality determination MY164318A (en)

Priority Applications (3)

Application Number Priority Date Filing Date Title
MYPI2010700086A MY164318A (en) 2010-11-30 2010-11-30 A system for fruit grading and quality determination
BR112013013330A BR112013013330A2 (en) 2010-11-30 2011-11-25 fruit grading and quality determination system
PCT/MY2011/000237 WO2012074372A2 (en) 2010-11-30 2011-11-25 A system for fruit grading and quality determination

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
MYPI2010700086A MY164318A (en) 2010-11-30 2010-11-30 A system for fruit grading and quality determination

Publications (1)

Publication Number Publication Date
MY164318A true MY164318A (en) 2017-12-15

Family

ID=46172442

Family Applications (1)

Application Number Title Priority Date Filing Date
MYPI2010700086A MY164318A (en) 2010-11-30 2010-11-30 A system for fruit grading and quality determination

Country Status (3)

Country Link
BR (1) BR112013013330A2 (en)
MY (1) MY164318A (en)
WO (1) WO2012074372A2 (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021010817A1 (en) 2019-07-12 2021-01-21 Sime Darby Plantation Intellectual Property Sdn. Bhd. Apparatus to measure ripeness of oil palm fruitlets via real-time chlorophyll content measurement

Families Citing this family (16)

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ES2445245B1 (en) * 2012-08-28 2014-12-11 Universidad De Extremadura Cell for fruit quality control through an intelligent multispectral vision system and robotic system
JP2018004646A (en) 2016-07-05 2018-01-11 シャープ株式会社 Determination device of degree of ripeness, and method for determining degree of ripeness
US10304179B2 (en) 2016-07-05 2019-05-28 Sharp Kabushiki Kaisha Maturity determination device and maturity determination method
JP2018025548A (en) 2016-08-10 2018-02-15 シャープ株式会社 Fruit harvester and fruit harvesting method
CN106525732B (en) * 2016-10-25 2021-08-17 沈阳农业大学 Rapid nondestructive detection method for internal and external quality of apple based on hyperspectral imaging technology
CN107247957A (en) * 2016-12-16 2017-10-13 广州中国科学院先进技术研究所 A kind of intelligent agricultural product sorting technique and system based on deep learning and cloud computing
US10902581B2 (en) 2017-06-19 2021-01-26 Apeel Technology, Inc. System and method for hyperspectral image processing to identify foreign object
US10902577B2 (en) 2017-06-19 2021-01-26 Apeel Technology, Inc. System and method for hyperspectral image processing to identify object
CN107505325B (en) * 2017-08-18 2023-04-25 西北农林科技大学 Omnibearing quality detection method for winter jujube fruits
CN108372133A (en) * 2018-05-16 2018-08-07 江西农业大学 A kind of EO-1 hyperion automatic fruit non-destructive testing sorting equipment
CN109406414A (en) * 2018-10-31 2019-03-01 中国中医科学院中药研究所 Method based on vanilla acid content in high light spectrum image-forming technology prediction fructus lycii
CN111076670B (en) * 2019-12-03 2021-06-08 北京京仪仪器仪表研究总院有限公司 Online nondestructive testing method for internal and external quality of apples
CN112858192A (en) * 2021-01-11 2021-05-28 中科谱光(郑州)应用科学技术研究院有限公司 Quality grading algorithm based on wormwood hyperspectral data
EP4137813A1 (en) * 2021-08-20 2023-02-22 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. System and method for the automatic quality testing of fruit and vegetables and other foodstuffs
CN114112932A (en) * 2021-11-08 2022-03-01 南京林业大学 Hyperspectral detection method and sorting equipment for maturity of oil-tea camellia fruits based on deep learning
CN114419311B (en) * 2022-03-29 2022-07-01 武汉轻工大学 Multi-source information-based passion fruit maturity nondestructive testing method and device

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2008041124A1 (en) * 2006-10-06 2008-04-10 Sacmi Cooperativa Meccanici Imola Societa' Cooperativa A method and device for quality inspection of vegetable produce
CA2685158C (en) * 2007-04-25 2017-09-26 The United States Of America, As Represented By The Secretary Of Agricture Simultaneous acquisition of fluorescence and reflectance imaging techniques with a single imaging device

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021010817A1 (en) 2019-07-12 2021-01-21 Sime Darby Plantation Intellectual Property Sdn. Bhd. Apparatus to measure ripeness of oil palm fruitlets via real-time chlorophyll content measurement

Also Published As

Publication number Publication date
WO2012074372A3 (en) 2012-10-11
BR112013013330A2 (en) 2016-09-13
WO2012074372A2 (en) 2012-06-07

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