Knowledge of population structure and genetic relationship among inbred lines is essential for exploiting heterosis in maize breeding programs. This study evaluated the concordance between 25k Illumina^® Infinum Maize SNP (Single Nucleotide Polymorphism) Array (25k SNP array)-derived and ribonucleic acid (RNA)-sequencing (seq)-derived markers in estimating genetic relatedness and population structure within the Maize Research Institute “Zemun Polje” (MRIZP) breeding program. A panel of 28 elite MRIZP maize inbred lines, along with two public lines, was analyzed. For the RNA-seq data, three alternative SNP datasets were generated based on heterozygous-site handling (ALL, HOM, and FINAL) to assess their impact on downstream genetic inference. These approaches had distinct effects on clustering resolution and genetic relationship structure. The FINAL dataset, in which heterozygous positions were recoded as missing values and re-filtered, was selected as the most balanced dataset for comparative analyses with 25k SNP array data. Only a limited number of overlapping SNP positions were identified between RNA-seq and 25k SNP array datasets (six in ALL, two in FINAL, and none in HOM), all located within coding regions. Despite this minimal overlap, distance-based analyses revealed partial concordance in genetic relationship patterns and population structure between platforms. Genetic distances estimated from 25k SNP array markers were consistent with pedigree records and provided more informative insights than pedigree data alone. Population structure inferred from 25k SNP array data showed high concordance with previously defined heterotic groups, correctly assigning 29 out of 30 lines (96.67%) to their expected clusters. In contrast, RNA-seq-derived SNPs showed moderate concordance with expected heterotic groupings (56.67%), indicating that transcriptome-derived markers capture part of the underlying breeding structure, but do not fully resolve heterotic group separation. Overall, these results support the 25k SNP array as a robust tool for assessing genetic relatedness and population structure in maize breeding programs, while RNA-seq-derived SNPs provide complementary but less reliable information for routine heterotic assignment.

Coppice is�the oldest form of�systematic and sustainable use of�forests, and is�currently applied on�about 29 million ha (about 14% of�total forest land area) in�Europe. It�had its maximum spread in�the 16th century, when an�estimated 36% of�a...

The production and processing of commercial seeds place significant emphasis on seed quality, with germination rates being a critical determinant of market performance. A major challenge in corn seed production and processing is maintaining optimal storage conditions to preserve germination and vigor over time. In the Republic of Serbia, certified corn seeds must adhere to specific germination standards as outlined by regulatory guidelines. Given that germination rates decline during storage, routine germination testing at accredited laboratories is imperative. The aim of this study is to evaluate the changes in total germination and vigor of certified hybrid corn seed over a five-year period. Annual germination tests were conducted from 2018 to 2022 for three commercial maize hybrids (ZP 704, ZP 873, and ZP 600). The standard "between the paper" germination test was utilized, and results for each hybrid were reported as averages from the tested lots. Initial testing conducted in 2018 revealed the highest average values for total germination and vigor across three hybrids: ZP 704 (98.8%/98.8%), ZP 873 (100%/100%), and ZP 600 (98.3%/98.3%). By 2020, a slight decrease in both germination and vigor was observed for all hybrids, with equal values for germination energy and total germination. By the end of the study in 2022, the average total germination for all hybrids remained above 90%, specifically ZP 704 (93.7%), ZP 873 (94%), and ZP 600 (96%). Notably, while the vigor of hybrids ZP 704 (92.7%) and ZP 873 (88%) was lower than their total germination rates, hybrid ZP 600 demonstrated consistent results, with both total germination and vigor at 96%. The findings indicate that seed storage conditions were in accordance with regulations, as evidenced by acceptable overall germination rates for all hybrids at the end of the test period.

High-throughput field phenotyping (HTFP) has become an important approach for improving the efficiency and objectivity of phenotypic evaluation in modern plant breeding. Within the PHENO_MaizE project the practical application of UAV-based RGB phenotyping in temperate maize breeding under field conditions is investigated. The project integrates repeated drone imaging, extraction of image-derived traits, and predictive modeling in order to evaluate the potential of digital phenotyping for the selection of superior maize genotypes. Experimental material includes maize inbred lines and their corresponding testcrosses evaluated across multiple environments in Serbia. UAV surveys conducted during the growing season will enable monitoring of temporal crop development and extraction of traits such as plant height, canopy cover, vegetation indices, and growth dynamics. The research within the project will also assess the potential of phenomic prediction models for estimating important agronomic traits, including grain yield, flowering time, and grain moisture at harvest. Special emphasis is placed on developing a practical, cost-effective, and scalable HTFP framework adapted to medium-sized breeding programs. The expected outcomes may support wider implementation of digital phenotyping and data-driven selection strategies in maize breeding.