• Soybean germplasm evaluation: Nutritive grain quality under climate change conditions
• Genotypic selection of peas under climate change
• Innovative strategies for early stress detection and increasing maize tolerance to cold stress
• Legumes as a source of biologically active phytochemicals
• Breeding development of alfalfa and red clover germplasm adapted to climate changes
• Predictive modelling of agronomic traits in maize using modern technologies
• Assessment of quantitative traits in small grain cereals germplasm considering climate change
• The role of genetic specificity, plant growth regulators, and biostimulants in increasing the resistance to abiotic and biotic stress, yield, and quality of sour cherry fruit
• The influence of climate changes on the expression of the most important agronomic, physiological and biochemical traits of sunflower under conditions of different plant density
• Influence of combined abiotic stresses and climatic oscillations on production and quality of seed
• Water, soil and cultivar – fundamental elements of sustainable agriculture in climate change

Full project title

Predictive modelling of agronomic traits in maize using modern technologies

Project acronym

MASK

Lead researcher

Andrija Brkić, PhD, Senior Scientific Associate

Project team members

1. Antun Jambrović, PhD, Senior Scientific Adviser, Agricultural Institute Osijek
2. Zvonimir Zdunić, PhD, EMBA, Senior Scientific Adviser, Full professor, Agricultural Institute Osijek
3. Tatjana Ledenčan, PhD, Senior Scientific Adviser, Agricultural Institute Osijek
4. Josip Brkić, PhD, Senior Scientific Associate, Agricultural Institute Osijek
5. Maja Mazur, PhD, Scientific Associate, Agricultural Institute Osijek
6. Vlatko Galić, PhD, Scientific Associate, Agricultural Institute Osijek
7. Miroslav Salaić, BSc, Technologist

Project financing source

National Recovery and Resilience Plan 2021-2026 within the framework of the Program Agreement with the Ministry of Science, Education and Youth

Project budget

52.500,00 EUR

Project summary

Maize is one of the most significant crops in the world. Utilizing the latest scientific knowledge in maize breeding is an important long-term strategy for successful maize production amid current climate changes. Improving nitrogen use efficiency in maize breeding germplasm represents a valuable option in maize production regions. The objectives of this project are to determine the combining abilities for yield and nitrogen use efficiency, develop statistical models for prediction, explore variability of hyperspectral readings and vegetative indices among genotypes and treatments, and create a comprehensive prediction model using SNP data, trial results, and selected phenotyping parameters. The anticipated contributions of this project would include the publication of at least three scientific papers in relevant journals, at least one popular science book, a project handbook, integration of results into breeding programs, i.e., development of new cultivars, and training of new staff at the institute.

Project aims

The aim of this project is to expand knowledge about phenotypic traits that could contribute to a better understanding of nitrogen use efficiency and to assess the high-value resource of the Agricultural Institute in Osijek (genotyped collection of breeding germplasm).

1) Determine the general and specific combining abilities of inbred lines for grain yield and nitrogen use efficiency by crossing with two testers and conducting experiments with three nitrogen levels.

2) Develop statistical models to predict yield and nitrogen use efficiency using experiment results and dense genotyping data.

3) Investigate the variability of phenotypic parameters among genotypes and treatments.

4) Develop a comprehensive model to predict yield and nitrogen use efficiency using SNP data, experiment results, hyperspectral parameters, and vegetative indices, and compare it with models from the literature.