Vilma Kemešytė

Semi-natural grasslands support biodiversity, but their capacity to combine conservation with beef production remains insufficiently quantified. This case study compared a sown ley and a permanent semi-natural grassland in Lithuania during the 2019–2020 grazing seasons, using eight bulls annually (16 animal observations; four per field per year). Plant diversity, herbage yield and composition, liveweight change, and beef quality were evaluated. Soil phosphorus status differed, with lower extractable phosphorus in the permanent grassland. Species richness was higher in permanent grassland than in sown ley (84 vs. 12 species), whereas herbage dry matter yield was lower (1.45 vs. 2.92 t DM ha ⁻¹). Permanent grassland had half the livestock unit density and twice the land area per animal, resulting in similar dry matter yield per animal. Despite the greater land requirement, unadjusted growth differences varied in direction between years, and the adjusted difference in final liveweight was imprecisely estimated (permanent grassland minus ley: −10.1 kg; 95% CI: −39.7 to 19.5 kg). Beef from the studied permanent grassland had less saturated and more unsaturated fatty acids, lower atherogenicity and thrombogenicity indices, and a higher hypocholesterolaemic-to-hypercholesterolaemic fatty acid ratio. Multi-site studies are needed to assess the broader applicability of these differences.

Drought is a major constraint limiting maize productivity worldwide, highlighting the need for reliable methods to identify drought-tolerant genotypes. This study evaluated the effectiveness of drought tolerance indices and multivariate analyses for discriminating maize genotypes differing in drought adaptation. In total, 20 maize genotypes were assessed under optimal and water-limited conditions using grain yield under non-stress (Yp) and drought stress (Ys) together with 15 drought tolerance indices. Correlation analysis, principal component analysis (PCA), clustering, and overlay analysis were applied to identify informative indices and characterize genotype responses. Productivity-oriented indices (STI, GMP, HM, MSTI, REI, and YI) were strongly associated with grain yield and consistently identified superior genotypes, whereas SSI, TOL, and SSPI mainly reflected drought susceptibility. PCA separated productivity and stress susceptibility into two complementary components and showed that five variables (Yp, Ys, YI, ATI, and MSTI_K1) retained 99.49% of the variation explained by the complete dataset. Cluster and overlay analyses confirmed stable genotype classification and distinct adaptation strategies. These findings demonstrate that a reduced set of complementary variables provides an efficient framework for drought tolerance assessment and supports the identification of maize germplasm, combining high productivity with stable performance under variable water availability.

Drought tolerance assessment in maize requires the integration of yield performance and multiple stress-related indicators to identify genotypes combining productivity and environmental adaptation. In this study, twenty maize genotypes were evaluated under optimal and drought-stress conditions using grain yield parameters and fifteen drought tolerance indices. Significant variation was observed for yield potential (Yp), stress yield (Ys), and index-based drought responses. Productivity-related indices, including Stress Tolerance Index (STI), Geometric Mean Productivity (GMP), Harmonic Mean (HM), Modified Stress Tolerance Index (MSTI), and Relative Efficiency Index (REI), showed strong associations with yield performance and effectively identified stable, high-performing genotypes. Correlation analysis revealed a clear separation between productivity-oriented and susceptibility-related indices. Principal Component Analysis explained 97.5% of total variation in the first two components and separated indices into productive adaptation and stress susceptibility groups. Cluster analysis classified genotypes into four distinct groups, identifying genotypes with high yield potential, superior drought adaptation, intermediate performance, and stress sensitivity. Genotypes G11, G12, and G13 demonstrated the highest yield retention under drought, while G3, G15, and G18 combined high productivity with acceptable stress performance. The integration of multi-index analysis and multivariate approaches provides an effective framework for selecting drought-resilient maize genotypes.

Grass–legume mixtures can improve forage productivity and quality, but their performance may vary between years. This study evaluated grass–legume mixture types differing in composition and intended use (forage, universal, and grazing) across two growing seasons, focusing on the first cut. Mixtures were assessed for dry matter yield, botanical composition, chemical composition, and plant height, and principal component analysis (PCA) was used to describe multivariate trait patterns. The year strongly affected mixture performance. Mean dry matter yield decreased from 6949 ± 212 kg ha⁻¹ in 2023 to 1588 ± 94 kg ha⁻¹ in 2024, corresponding to an approximately 76% reduction. In 2023, forage mixtures produced the highest yield, followed by universal and grazing mixtures, whereas in 2024, differences among mixture types were not significant. Botanical composition shifted toward a higher legume proportion in 2024, while mixture type differences in chemical composition largely converged, except for DMD. PCA showed clearer separation among mixture types in 2023, with PC1 and PC2 explaining 64.9% and 17.6% of variance, respectively, whereas separation weakened in 2024. These results indicate that mixture composition and intended use influenced productivity and quality mainly under more favorable growing conditions, while year-to-year variation strongly constrained first-cut mixture performance.

Interest in using warm-season grasses, including switchgrass (SG) (Panicum virgatum L.), as a bioenergy crop has increased in Europe. This study evaluated the effects of harvesting regimes with two cuts per year on the productivity, chemical composition and biochemical methane potential of the SG cultivars ‘Dacotah’, ‘Foresburg’ and ‘Cave in Rock’ in environments with cool and moderate climates in Europe with minimal fertilizer application. The results of two harvest years suggest that the biomass yield, chemical composition and energy potential depend on the grass cultivars and harvesting time. Significant effects (p < 0.05) of the harvest date and cultivar were observed for most of the measured parameters for biomass and silage quality. All three SG cultivars harvested on August 8 produced the lowest (p < 0.05) volume of methane per kg of biomass (181–202 normal litres (NL) per kg⁻¹ volatile solids (VS)) compared to the biomass of the respective cultivar harvested on 14 July (287–308 NL kg⁻¹ VS) or on October 3, as regrowth after the first cut made in mid-July (274–307 NL kg⁻¹ VS). The stands of all three SG cultivars, when the first harvest was completed in mid-July, achieved a higher annual area-specific methane yield than those harvested first in August (1128–1900 Nm³ ha⁻¹ and 888–1332 Nm³ ha⁻¹, respectively). Depending on the harvest regime and cultivar, the annual gross energy presented as a lower heating value varied from 31.8 GJ ha⁻¹ to 68.0 GJ ha⁻¹. It is concluded that SG growing under the cool temperate climate of Northern Europe could be an interesting alternative crop for methane production. Our study proves that the cultivar choice also plays an important role.

Interest in using warm-season grasses, including switchgrass (SG) (Panicum virgatum L.), as a bioenergy crop has increased in Europe. This study evaluated the effects of harvesting regimes with two cuts per year on productivity, chemical composition and methane potential of SG cultivars ‘Dacotah’, ‘Foresburg’ and ‘Cave in Rock’in environments with cool and moderate climates in Europe with minimal fertilizer application. The results of two harvest years suggest that biomass yield, chemical composition and energy potential depend on grass cultivars and harvesting time. Significant effects (P-1 volatile solids (VS) compared to biomass of the respective cultivar harvested on July 14 (287–308 NL kg^-1 VS) or on October 3 as regrowth after the first cut made in mid-July (274–307 NL kg^-1 VS). Stands of all three SG cultivars, when the first harvest was done in mid-July, achieved a higher annual area-specific methane yield than those harvested first in August (1128–1900 Nm³ ha^-1 and 888–1332 Nm³ ha^-1, respectively). Depending on the harvest regime and cultivar, annual gross energy presented as lower heating value varied from 31.8 GJ ha^-1 to 68.0 GJ ha^-1. It is concluded that SG growing under the cool temperate climate of Northern Europe could be an interesting alternative crop for methane production. Our study proved that cultivar choice also plays an important role.

Background: In breeding the aim is to identify and accumulate beneficial variants. However, detection of these variants may be challenging in the presence of extensive genotype x environment interactions (GxE), as variant effects will be conditional on environment. Methods: The study assesses the performance of 264 diploid perennial ryegrass accessions in a multi-environment field trial. We investigate the extent of GxE, for yield (total dry matter) and persistence traits, i.e. winter kill and spring cover, under environmental conditions experienced in Nordic and Baltic regions at the limit of the species distribution. Two different approaches to modelling GxE were tested: reaction norm and envirotyping, and the models were validated under three different breeding scenarios. Results: Our analysis documented the presence of significant GxE interaction for all traits investigated in the study. Validation showed improvements in prediction accuracy when accounting for GxE: up to 4% for yield when predicting in unobserved environments, and up to 22% and 9% for spring cover and winter kill, respectively when predicting unobserved germplasm. Genome-wide-association-studies (GWAS) were utilized to detect genetic variants with marginal effects (environment-independent effect) and conditional effects (environment-dependent effects). Results showed the presence of large-effect genetic variants with marginal effects, in addition to few QTL whose effects were adaptive under specific environmental conditions while neutral or deleterious under different environmental conditions. Conclusion: This study demonstrates the usefulness and limitations of genomic prediction models for predicting GxE in highly diverse samples, and describes the extent of GxE interactions at the limit of species distribution for perennial ryegrass. Finally, our study points toward adaptive variation, which may enhance persistence of perennial ryegrass populations in Nordic and Baltic growing conditions.

Agricultural reforms, land consolidation, and the abandonment of livestock farming effects grassland ecosystems worldwide. Utilising data from four medium-sized livestock farms across different regions in Lithuania, we assess floristic composition, productivity, and grass quality in both permanent grasslands and leys. Our findings reveal significant differences in flora diversity, with 120 species identified in permanent grasslands compared to only 20 in leys. Additionally, dry matter yield was notably higher in leys (13.97 t ha⁻¹) than in permanent grasslands (5.66 t ha⁻¹), underscoring the productivity potential of leys. The crude protein levels remained stable across both types, but leys demonstrated significantly lower neutral detergent fibre content, indicating better forage quality. However, the high biodiversity of permanent grasslands supports ecosystem services.

Grasslands are important for sustainable milk and meat production as well as for providing other ecosystem services. One of the most productive components of short-term grasslands is Italian ryegrass (Lolium multiflorum subsp. italicum Lam.), offering high yield, excellent feed value, and high palatability to animals but low tolerance to abiotic stress. Global climate warming opens new opportunities and could be beneficial in increasing the potential of biomass production. In this study, we aimed to assess an Italian ryegrass cultivar of Lithuanian origin, ‘Ugnė’, for productivity and yield stability, with special emphasis on their relationship with climatic factors over a period of 14 years. The average winter temperatures and total spring precipitation explained 51% of the first-cut dry matter yield (DMY) variance. Second- and third-cut DMYs were associated with average temperature only. Italian ryegrass cv. ‘Ugnė’ demonstrated the potential to produce high dry matter yields after warm winters and withstand summer drought spells under Lithuanian conditions. However, mid-to-late-summer heat waves might reduce productivity and should be taken into consideration when breeding new Italian ryegrass cultivars.