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Pregled bibliografske jedinice broj: 1100239

Digital image analysis method - a valuable tool for predicting the physical properties of wheat grain


Lukinac, Jasmina; Velikanović, Valentina; Koceva Komlenić, Daliborka; Mastanjević, Kristina; Mastanjević, Krešimir; Jukić, Marko
Digital image analysis method - a valuable tool for predicting the physical properties of wheat grain // “Agriculture for Life, Life for Agriculture” Conference Proceedings, 2020.
Bucharest: Sciendo, 2020. str. 730-730 (poster, međunarodna recenzija, sažetak, ostalo)


CROSBI ID: 1100239 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Digital image analysis method - a valuable tool for predicting the physical properties of wheat grain

Autori
Lukinac, Jasmina ; Velikanović, Valentina ; Koceva Komlenić, Daliborka ; Mastanjević, Kristina ; Mastanjević, Krešimir ; Jukić, Marko

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, ostalo

Izvornik
“Agriculture for Life, Life for Agriculture” Conference Proceedings, 2020. / - Bucharest : Sciendo, 2020, 730-730

Skup
International Conference "Agriculture for Life, Life for Agriculture"

Mjesto i datum
Bukurešt, Rumunjska, 04-06.06.2020

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
digital image analysis, geometric features ; physical properties ; quality ; wheat grain

Sažetak
Apart from other indicators such as grain freshness, chemical composition and physical properties, geometric characteristics of grains are very important quality parameter. The aim of this paper was to examine six different grain geometrical characteristics (grain surface area, grain perimeter, grain circularity, grain length and width and average grey value) of winter wheat varieties and to determine their correlation with physical properties of grain (flour milling yield, 1000 kernel weight, hectolitre mass, grain vitreousness). The study was conducted on 54 different winter wheat varieties. An image analysis technique was used to evaluate the geometric features of winter wheat grains. The physical properties of winter wheat grains were determined by standard methods. Based on the obtained results, performed correlation and regression analysis, it can be concluded that the physical properties of wheat grain can be successfully predicted by digital image analysis method. The grain surface area was shoved as a good predictor of 1000 kernel weight, circularity as a predictor of hectolitre mass, while average grey value were shoved as the best predictor of wheat grain vitreousness. Digital image analysis method is a valuable tool for determine the grain quality (geometric and colour characteristics) and in prediction of wheat grain physical properties.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Poljoprivreda (agronomija), Biotehnologija, Prehrambena tehnologija



POVEZANOST RADA


Ustanove:
Prehrambeno-tehnološki fakultet, Osijek


Citiraj ovu publikaciju

Lukinac, Jasmina; Velikanović, Valentina; Koceva Komlenić, Daliborka; Mastanjević, Kristina; Mastanjević, Krešimir; Jukić, Marko
Digital image analysis method - a valuable tool for predicting the physical properties of wheat grain // “Agriculture for Life, Life for Agriculture” Conference Proceedings, 2020.
Bucharest: Sciendo, 2020. str. 730-730 (poster, međunarodna recenzija, sažetak, ostalo)
Lukinac, J., Velikanović, V., Koceva Komlenić, D., Mastanjević, K., Mastanjević, K. & Jukić, M. (2020) Digital image analysis method - a valuable tool for predicting the physical properties of wheat grain. U: “Agriculture for Life, Life for Agriculture” Conference Proceedings, 2020..
@article{article, year = {2020}, pages = {730-730}, keywords = {digital image analysis, geometric features, physical properties, quality, wheat grain}, title = {Digital image analysis method - a valuable tool for predicting the physical properties of wheat grain}, keyword = {digital image analysis, geometric features, physical properties, quality, wheat grain}, publisher = {Sciendo}, publisherplace = {Bukure\v{s}t, Rumunjska} }
@article{article, year = {2020}, pages = {730-730}, keywords = {digital image analysis, geometric features, physical properties, quality, wheat grain}, title = {Digital image analysis method - a valuable tool for predicting the physical properties of wheat grain}, keyword = {digital image analysis, geometric features, physical properties, quality, wheat grain}, publisher = {Sciendo}, publisherplace = {Bukure\v{s}t, Rumunjska} }




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