| Autor: |
Galić, Vlatko, Spišić, Josip, Ledenčan, Tatjana, Jambrović, Antun, Zdunić, Zvonimir, Šimić, Domagoj |
| Přispěvatelé: |
Goreta Ban, Smiljana, Šatović, Zlatko |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Popis: |
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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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