Software Application in Machine Vision Investigation of Agricultural Seeds Quality

Ola, D. C.; Manescu, Mihai; Cristea, Luciana; Budde, Jörn; Hoffmann, Thomas

doi:10.4028/www.scientific.net/amm.436.463

Cited by 4 publications

(3 citation statements)

References 8 publications

(10 reference statements)

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“…It is noteworthy that computer vision technology has been widely used in the detection and analysis of rice appearance quality traits. For example, computer vision technology could be used to quickly determine the chalky grain rate and chalkiness area in rice, and it could also be used to distinguish pure rice, whole rice, and even the different rice varieties (Ola et al, 2013;Zhou et al, 2010;Ren et al, 2014), which had greatly facilitated the improvement of rice appearance quality. Therefore, with the rapid development of detection technologies, various high-tech technologies are continuously applied to the detection and analysis of rice grain quality, which will certainly bring great convenience to the genetic improvement of rice grain quality.…”

Section: Application Of Other High-tech Technologies In Genetic Impromentioning

confidence: 99%

Genetic Improvement of Grain Quality Promoted by High and New Technology in Rice

Peng¹,

Li²,

Kong³

et al. 2018

JAS

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Rice (Oryza sativa L.) is considered as one of the most important food crops all over the world. Because of the improvement of the actual living standards, there is more and more demand for improved grain quality. Although, the grain quality is a very complex quantitative trait in rice, it has great scientific significance and practical application value for the improvement of the quality of rice grain using high and up to date techniques. Here, we focus on the new advances in the application of the genetic improvement of grain quality by high throughput sequencing, genomic editing, near infrared spectroscopy, scanning electron microscopy, and other new techniques. Simultaneously, the application prospects of these high and up to date techniques have also been expected in the genetic improvement of rice quality. Thus, this will provide important information for genetic improvement of grain quality in rice breeding.

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Section: Application Of Other High-tech Technologies In Genetic Impromentioning

confidence: 99%

Genetic Improvement of Grain Quality Promoted by High and New Technology in Rice

Peng¹,

Li²,

Kong³

et al. 2018

JAS

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“…The rotating type classifier has several sieves with different hole diameters. The vibrating-type classifier is mechanically driven from electrical energy to the frame, which then proceeds to the sieve section [30,31].…”

Section: Introductionmentioning

confidence: 99%

Design and Performance Test of the Coffee Bean Classifier

et al. 2021

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Currently, some coffee production centers still perform classification manually, which requires a very long time, a lot of labor, and expensive operational costs. Therefore, the purpose of this research was to design and test the performance of a coffee bean classifier that can accelerate the process of classifying beans. The classifier used consisted of three main parts, namely the frame, the driving force, and sieves. The research parameters included classifier work capacity, power, specific energy, classification distribution and effectiveness, and efficiency. The results showed that the best operating conditions of the coffee bean classifier was a rotational speed of 91.07 rpm and a 16° sieve angle with a classifier working capacity of 38.27 kg/h: the distribution of the seeds retained in the first sieve was 56.77%, the second sieve was 28.12%, and the third sieve was 15.11%. The efficiency of using a classifier was found at a rotating speed of 91.07 rpm and a sieve angle of 16°. This classifier was simple in design, easy to operate, and can sort coffee beans into three classifications, namely small, medium, and large.

show abstract

“…The rotating type classifier has several sieves with different hole diameters. The vibrating type-classifier is mechanically driven from electrical energy to the frame, then proceeds to the sieves section [30,31].…”

Section: Introductionmentioning

confidence: 99%

Design and Performance Test of the Coffee Bean Classifier

Ansar¹,

Sukmawaty²,

Murad³

et al. 2021

Preprint

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Nowadays, some coffee production centers are still classification manually, so it requires a very long time, a lot of labor, and expensive operational costs. Therefore, the purpose of this research was to design and performance of the coffee bean classifier that can accelerate the process of classification beans. The classifier used consists of three main parts, namely the frame, driving force, and sieves. Research parameters include classifier work capacity, power, specific energy, classification distribution and effectiveness, and efficiency. The results showed that the best operating conditions of the coffee bean classifier was found at a rotational speed of 91.07 rpm and a 16° sieves angle with a classifier working capacity of 38.27 kg/h, the distribution of the seeds retained in the first sieve was 56.77 %, the second sieves was 28.12%, and the third sieves was 15.11%. The efficiency of using a classifier was found at a rotating speed of 91.07 rpm and a sieves angle of 16°. This classifier was simple in design, easy to operate, and can sort coffee beans into three classification, namely small, medium, and large.

show abstract

Software Application in Machine Vision Investigation of Agricultural Seeds Quality

Cited by 4 publications

References 8 publications

Genetic Improvement of Grain Quality Promoted by High and New Technology in Rice

Genetic Improvement of Grain Quality Promoted by High and New Technology in Rice

Design and Performance Test of the Coffee Bean Classifier

Design and Performance Test of the Coffee Bean Classifier

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