In marker assisted breeding programs, determination of genome polymorphism and development of suitable molecular markers is of the greatest importance. The aim of this research was development of RAPD markers, which will enable quick and cost efficient DNA polymorphism analysis among closely related sugar beet genotypes. The research was conducted on twelve sugar beet genotypes from population of closely related genotypes. Reactions with eight RAPD primers and five primer mixtures resulted in stable and reproducible bands in all samples, with 44 polymorphic and 14 monomorphic loci, and average of 6.13 bands per primer. In two-primer reactions nine new polymorphic bands were detected. Polymorphism information content (PIC) for each primer was calculated, while genetic variation was estimated by calculation of the number of polymorphic loci and their percentage, observed number of alleles, effective number of alleles, and Nei’s gene diversity. An unweighted pair group arithmetic mean method (UPGMA) cluster analysis showed that samples were divided in two groups with relatively high coefficient of similarity. The presented results showed that RAPD markers can be suitable for genetic diversity analysis in breeding material with high levels of homology and homozygosity

Summary:In different regions of Serbia people consume pepper fruits with various shapes, sizes and colors. In southern Serbia consumers prefer longer fruits, while in the northern part shorter fruits are more preferred. The aim of this paper was to evaluate four pepper genotypes (355, 356, 357, and 358) with shorter fruits originating from open pollination. These genotypes were compared with the parental line 354 with longer fruits. The fruits were harvested in technological maturity. Fruit (length, width, weight, and index), locule number, pericarp thickness, total soluble solids and fruit yield per plant were evaluated. The line 354 had the longest fruits (14.46 cm). Genotype 358 had the highest pericarp thickness (5.8 mm), while the genotype 357 had the highest fruit weight (105 g). Based on the evaluated traits, genotype 357 will be used for further selection because of higher fruit weight, and genotype 358 because of a thicker pericarp.

One of the main challenges in pepper production is to enhance seed germination energy and germination, and to grow healthy nursery plants with strong root system. Trichoderma species colonize roots as they grow and provide season-long benefits to plants, which is why Trichoderma species are widely used as plant growth promoter agents and promoters of plant defence mechanisms. This study evaluated the effectiveness of seed biopriming with Trichoderma isolates for growth promotion of pepper plants in early stage and their effects on seedling physiology. Nine out of ten Trichoderma isolates positively affected root weight of pepper seedlings, while three out of ten positively affected shoot weight. Root and shoot lengths were mainly unaffected. Germination energy was positively affected by five isolates with up to 40% increase compared to the control, while germination was significantly enhanced by two isolates with up to 22% increase. Considering seedling physiology, two different strain-dependent modes of actions were expressed. Promising Trichoderma isolates induced formation and accumulation of reactive oxygen species (ROS) which acted as signal molecules that increased germination energy and germination. Positive correlation was found between pyrogallol peroxidase, superoxide dismutase, catalase activity and germination in plants treated with these isolates.

The main goal of the present study is validation of different chemometric models in Raman spectroscopic monitoring of different maturity phases of the red pepper fruit. Successive ripening stages commonly corresponding with different fruit coloration (green, green‐brown, brown‐red, and deep red) were assessed. The fruit maturation process in red pepper is related to alteration in composition and content of different primary and secondary metabolites, including the most represented carotenoid, the capsanthin. Raman microspectroscopy with wavelength of 532 nm was used to obtain the spectra of the pericarp of different maturation phases. Several multivariate classification methods, such as Principal Component Analysis–Linear Discriminant Analysis (PCA–LDA), Partial Least Squares‐Discriminant Analysis (PLS‐DA), and Soft Independent Modeling of Class Analogy (SIMCA) were tested to determine the model which best fits the target ripening phases related to composition and the content of the most represented carotenoids. Concerning different fruit ripening phases, several characteristic bands were obtained, including those at 1514–1517, 1151, and 1003 cm−1, all assigned to carotenoids with nine conjugated double bonds in the main polyene chain (e.g., lutein, beta carotene, beta cryptoxanthin, zeaxanthin, capsorubin, and capsanthin). All tested classification chemometric models had a high rate of prediction accuracy (between 95% and 100%). The SIMCA showed the best result, probably because of using a different algorithm compared with the other tested models.

Multi-environment trials are performed every year with the aim of evaluating sugar beet varieties in different environmental conditions of Serbia. The objective of this research was to interpret the effects of genotype, environment and genotype × environment interaction on root yield, sugar content and white sugar yield. GGE biplot method was used to estimate stability of seven sugar beet hybrids developed at the Institute of Field and Vegetable Crops, Novi Sad, Serbia. Mixed model of analysis of variance (ANOVA) was used for the analysis of trial results. Factor genotype effect was assumed fixed while effects of year and environment were assumed random. ANOVA showed that the environment had the greatest effect on root and white sugar yield, while year had the strongest effect on sugar content. Variations of all traits were under significant impact of genotype, while the GEI influence was not a significant. Results of GGE biplot analysis suggested that hybrid Sara was the most stable variety for root yield, while Lara had the greatest stability for sugar content and white sugar yield among the tested genotypes. Also, optimal locations were identified for each genotype, which can be useful when recommending sugar beet varieties for certain growing areas of this field crop.