Pregled bibliografske jedinice broj: 1246360
The usability of proximal sensing in modern maize breeding programs
The usability of proximal sensing in modern maize breeding programs // Book of Abstracts of International Conference on Biodiversity and Molecular Plant Breeding / Goreta Ban, Smiljana ; Šatović, Zlatko (ur.).
Novigrad, 2022. str. 17-17 (predavanje, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 1246360 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
The usability of proximal sensing in modern maize
breeding programs
(The usability of proximal sensing in modern maize
breeding
programs)
Autori
Galić, Vlatko ; Spišić, Josip ; Ledenčan, Tatjana ; Jambrović, Antun ; Zdunić, Zvonimir ; Šimić, Domagoj
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
Book of Abstracts of International Conference on Biodiversity and Molecular Plant Breeding
/ Goreta Ban, Smiljana ; Šatović, Zlatko - Novigrad, 2022, 17-17
Skup
International Conference on Biodiversity and Molecular Plant Breeding
Mjesto i datum
Novigrad, Hrvatska, 02.10.2022. - 06.10.2022
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
proximal sensing ; maize SNP
Sažetak
Besides breeder’s notes, modern maize breeding programs take only two types of objective information for selection of favorable progenies: genomic data and yield performance, overlooking the underlying biological complexity. Understanding the process of yield formation implies the need for increased information density during the vegetation period. We developed a novel low-cost proximal sensing node with reflectance reads at six adjusted wavelengths (610, 680, 730, 760, 810 and 860 nm). The nodes were set to multiple breeding trials in 2021 and 2022 growing seasons and the measurements were collected throughout the flowering and grain filling stages. It was shown that the reflectance reads and the derived vegetation indices can be used for monitoring of crop physiological state through modeling of plant photosynthetic efficiency. However, to utilize such proximal sensing nodes, the collected phenotypic data should be integrated with data on molecular level, such as SNP reads, thus increasing the information density on the whole system level. The possibilities for such integration and prospects of use for the developed proximal sensing node in a modern maize breeding program in the era of machine learning will be discussed.
Izvorni jezik
Engleski
Znanstvena područja
Poljoprivreda (agronomija)
POVEZANOST RADA
Ustanove:
Poljoprivredni institut Osijek,
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek
Profili:
Antun Jambrović
(autor)
Tatjana Ledenčan
(autor)
Domagoj Šimić
(autor)
Vlatko Galić
(autor)
Josip Spišić
(autor)
Zvonimir Zdunić
(autor)