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Analysing growth dynamics: non-linear models of maize kernel dry matter accumulation
No full textThe present work aimed to model the kernel dry matter accumulation in maize (Zea mays L.) hybrids across two different environments. The Weibull, Logistic, and Gompertz sigmoidal growth models were fitted to actual growth data and their predictions were compared. The Weibull model showed the best fit for the first growing season, while the Logistic model outperformed others in the second. Estimated maximum dry matter accumulation (ASYM), time in GDD at which the maximum growth rate occurs (IP) and relative rate of dry matter accumulation (GR) were calculated and compared between hybrids and years. In 2022, the maximum ASYM was noted in hybrid NS3023 (0.291 g). In 2023, ASYM was the highest in hybrid NS6061 (0.339 g), which also required most GDD to reach the AGR (1220.978 GDD). Significant correlations were observed between ASYM and AGR and IP and AGRmax.This study presents new findings that enhance our understanding of the selection of appropriate mathematical and statistical models for accurately describing dry matter accumulation in maize. By employing advanced modelling techniques and integrating comprehensive data analyses, this research not only refines our predictive capabilities regarding maize growth but also lays the groundwork for more targeted breeding strategies. Such strategies can potentially lead to the development of maize hybrids that are more resilient, productive, and adaptable to fluctuating environmental conditions, thereby contributing to global food security and sustainable agricultural practices
The importance of domestic seed production for food security and national food sovereignty
No full textThe authors consider the current issue of strategic development of agriculture and agro-industry in the Republic of Serbia. The authors emphasize seed production as a branch of agro-industry that has comparative advantages and development prospects in the Republic of Serbia. Using the method of analysis and synthesis, the authors point out the multiple roles and importance of domestic seed production. They particularly emphasize the importance of seed production for food security and national food sovereignty. The effects of investing in the seed industry are manifold. The authors believe that investing in the seed industry is not only an economic issue but is primarily of strategic importance. Improving domestic seed production can be achieved through several key strategies: technical and technological development, innovation, research and development, support for producers, and biodiversity conservation. This implies investments in this important and promising branch of agro- industry. In this regard, it is important to have a balanced and combined approach to the market and market mechanisms, as well as the state and its agricultural policies. The example of the Institute of Field and Vegetable Crops from Novi Sad demonstrates the contribution to the development of seed production in the Republic of Serbia
NS Polar, hibrid suncokreta
No full textNS Polar, hibrid suncokreta, priznat od strane Ministarstva poljoprivrede, šumarstva i vodoprivrede, Uprava za zaštitu bilja, rešenje broj 320-04-5972/2023-11 od 09.04.2025, Beograd, Republika Srbij
Synergistic digital innovations for enhanced safety and quality in organic food production systems
No full textThis paper examines the synergistic integration of digital technologies in organic food production systems through a comprehensive literature review. We analyzed how IoT sensors, blockchain traceability, artificial intelligence, and integrated platforms collectively address organic agriculture’s unique safety and quality challenges. Our findings demonstrate significant benefits, including 72-hour early contamination detection, 92% reduced authentication time, and 18% improved nutritional retention. Our analysis identifies four key technological clusters (data acquisition technologies, verification systems, analytical platforms, and application interfaces) that collectively enable predictive contamination prevention, quality optimization, and transparent verification exceeding conventional systems. While implementation faces challenges, including digital literacy limitations and infrastructure constraints, our research indicates that strategic digital integration enhances organic food safety and quality while supporting sustainable rural development and preserving core organic principles.[https://doi.ub.kg.ac.rs/doi/7thmtagricult-18s/
Sustainable phytoremediation and biofuel production using Brassica napus on multi-contaminated sediments
No full textPhytoremediation represents an eco-friendly solution for restoring contaminated lands while enabling sustainable biofuel production. This study, conducted within the H2020 Phy2Climate project led by the Faculty of Technology, University of Novi Sad, explores the potential of Brassica napus for phytoextraction of multi-element contaminated dredged sediment. Field trials were conducted in 2022 and 2023 at a dredged sediment landfill along the Begej Canal, near the Serbian-Romanian border, covering a total area of approximately 2000 m². Given the heterogeneity of the deposited sediment, the landfill was divided into 10 subplots, each analyzed individually. The winter variety of Brassica napus 'Zlatna' was sown at a density of 50 seeds/m² in September 2022 and harvested at full maturity in July 2023. The estimated seed yield reached 380 kg (1.9 t/ha), with an additional 1600 kg of dry biomass collected. Analysis of metal concentrations in the harvested biomass, along with bioaccumulation and transfer factors, indicated that Brassica napus holds significant potential for the remediation of multi-contaminated sediments. Furthermore, the harvested biomass presents an opportunity for sustainable biofuel production, aligning with the goals of Environmental and Sustainable Research Solutions promoted by the TwiNSol-CECs project
Soybean yield prediction using multi-omics data integration
No full textSoyPredict focuses on the efficiency improvement of breeding new soybean varieties, suitable for Serbian and European agro-climatic conditions, by applying advanced breeding tools, multiomics data and advanced mathematical modeling for yield prediction. Project activities are focused on soybean, as crop of major economic and environmental importance, by developing long-term breeding strategies based on state-of-the-art technologies. The term ‘breeding strategy’ implies a plan to optimize the production of soybean varieties using the full suite of technologies and to release improved cultivars faster. Specific strategies will determine how to integrate traditional and multi-omics approaches for improving the efficiency of breeding process. Main concept of SoyPredict is predicting ability and accuracy of GP, HTPP and PP models in soybean yield prediction (within and between environments, in different stages of genotype evaluations), implementing model compilation and developing strategy for model/models application in cost effective manner. Degree and relations between yield predictors are complex (and probably non-linear), while SoyPredict have ambition to estimate efficiency of each particular model and describe mutual relationships. For prediction model compilations, SoyPredict will use several strategies. First one is treating equally all data sets (SNP, NIR, HTTP). Linear mix models and its variation is first choice in phenotype prediction for complex traits. At their core, those models rely at the assumption that genetically similar individuals are more likely to share similar phenotypes. Recently, high-order interaction linear mix models show promising results. Using all mentioned strategies for combining prediction models should provide answer is it possible to improve precision and accuracy of soybean phenotype prediction, within and between environments, as key indicator for increasing the genetic gain
A Preliminary Insight into Under Researched Plants from the Asteraceae Family in the Balkan Peninsula: Bioactive Compound Diversity and Antioxidant Potential
No full textNatural resources rich in polyphenols from plants belonging to the Asteraceae family remain largely unexplored. The main goal of this study was to characterize under-studied Asteraceae plants in terms of different bioactive compounds, antioxidant potential, and chemical profile. Twenty-three samples from 19 plant species were analyzed using conventional solid/liquid extraction, and the contents of total phenolics (TP), flavonoids (TF), flavonols (FL), hydroxycinnamic acids (HCA) and condensed tannins (CT), as well as extraction yield were determined. Antioxidant activity was assessed using DPPH, ABTS and FRAP assays, and five plant samples were subjected to LC-MS analysis. Extraction yields ranged from 0.57% to 1.74%. Solidago virgaurea had the highest TP and FL contents, while Tanacetum vulgare showed the highest TF and HCA levels. The highest CT content was found in the roots of Helianthus tuberosus. Asteraceae species such as S. virgaurea, Tussilago farfara, Cota tinctoria, T. vulgare, and Inula ensifolia demonstrated the greatest antioxidant potential, with about 130 different identified compounds. Given the promising chemical richness of these under-researched species, future studies should focus on enhancing extraction of bioactive compounds using novel techniques and incorporating extracts as natural, non-synthetic preservatives in various products to improve their nutritional and biological properties
Assessment of the biological influence of natural emulsifier on the growth and initial development of Sinapis alba L. and Lactuca sativa L. in laboratory conditions
No full textUnder controlled laboratory conditions, the biological influence of the emulsifiers Polysorbate 80, Glyceryl Monostearate SE, and Olivem 1000 on seed germination and initial development of Sinapis alba L. and Lactuca sativa L. was evaluated and compared. It was found that the emulsifiers included in the study and the applied concentrations had an indifferent to lethal effect on seed germination and initial development of the target plants. It was found that the emulsifier Polysorbate 80 can be used in concentrations ranging from 0.05 to 0.2% v/v, while Glyceryl Monostearate SE and Olivem 1000 in concentrations not higher than 0.025% v/v when performing screening laboratory studies to establish the biocidal effect of essential oils. Further studies are needed, including validation of the obtained experimental results in laboratory and vascular trials, to establish the influence of emulsifiers in combined application with essential oils or hydrolates of plant biomass from plants with proven allelopathic potential
Economical production of millet - Panicum miliaceum L. in the world and importance as functional food
No full textMany studies indicate the increasing functional value of millet - Panicum miliaceum L. in human nutrition. Consumers have increasingly high criteria for quality of life and an increasingly developed awareness of the role of food in maintaining health, while the prices of treatment are increasing. This has led to greater interest in consuming functional foods. The area under millet in the world is recording a growth trend. In 2023, the area under millet amounted to 31,332,668 ha, with a total production of 31,596,316 tons. Europe is a significant global producer of millet, with an area of 368,612 ha, or a total world share of 1.18%, and a total production of 661,707.8 tons. In 2023, average millet yields in Serbia were at the level of average world yields (956 t/ha) while production amounted to 107.43 tons. The Republic of Serbia and Montenegro have favorable conditions for growing millet. Proper growing technology and variety selection are prerequisites for economically profitable millet production. Millet is a source of carbohydrates, proteins, essential amino acids, polyphenols, minerals and dietary fiber, which indicates the possibility of using millet in the diet as a component that contributes to functionality and health improvement
Chromatin signature and gene target of drought
No full textHistone H3 trimethylation at lysine 4 (H3K4me3) is a marker of active promoters. We assessed its enrichment at the transcription start site (TSS) using ChIP followed by qPCR in a selection of drought-responsive genes. ChIP-qPCR (Chromatin Immunoprecipitation followed by quantitative PCR) allows to detect enrichment of H3K4me3 at the 5' end (promoter region) of a gene, by designing specific primers on this gene region. Genes were selected from DEGs in RNA-Seq experiments (Fig.1), primers were designed at gene 5’ (Fig.2) and amplification of chromatin was performed using +AB chromatin (chromatin immunoprecipitatated with H3K4me3 antibody) and -AB (chromatin immunoprecipitated without antibody, negative control) and input DNA from leaf. The results of the analysis of three genes are reported. Differential gene expression (DGE) analysis is a key approach for understanding how gene activity changes under different biological conditions, such environmental stress or developmental stages. RNA sequencing (RNA-Seq) enables comprehensive and quantitative profiling of transcriptomes, allowing researchers to identify differentially expressed genes (DEGs) by comparing expression levels between sample groups.After sequencing, raw reads are processed and aligned to a reference genome or transcriptome. Gene expression is quantified, often in terms of normalized counts or raw counts normalized with tools like DESeq. Statistical analyses are then applied to identify DEGs—genes showing significant changes in expression between conditions, typically based on adjusted p-values and fold-change thresholds. Among the DEGs, transcription factors (TFs) are of particular interest, as they play central roles in regulating gene expression networks. We identified TFs in sunflower by cross-referencing DEG lists (Fig.1 and 2) with known TF databases (PlantTFDB). Selected TFs (Fig.3) were prioritized for further functional studies to understand their regulatory roles and potential as biomarkers of drought stress