Genetic advance and regression analysis in sunflower

The knowledge about the magnitude and nature of variability that is present in a breeding population is an important prerequisite for designing efficient breeding programme in order to improve the yield potential of genotypes. The objective of this research was to evaluate heritability and genetic advance of important quantitative traits in new crosses of sunflower as well as to evaluate ratio of dominant and recessive genes in parental genotypes. The plant material selected for this research consisted of 6 sunflower genotypes, which according to literary data possess important characteristics for the production of sunflower. According to presented results there is significant variability of evaluated quantitative traits. Phenotypic variance was higher than genotypic demonstrating strong environment effect in expression of traits. The broad sense heritability was found very high for plant height (83.25%), high for 1000 seed weight (69.33%), moderate for seed yield/plant (46.53%) and head diameter (56.89%), while low for oil content (29.35%). Genetic advance expressed as a percentage of the mean ranged between 2.23% and 19.96%. Placement of array points displayed that the highest frequency of dominant genes for seed yield/plant, 1000 seed weight and head diameter was found in parental genotype Rodnik. Position of expected line of regression pointed over dominance in inheritance for seed yield/plant, oil content and head diameter, while for 1000 seed weight and plant height additive gene action played role in inheritance suggesting that selection in early generations for these traits will be effective. By testing the coefficients of regression interallelic interaction was not determined

Primena perkolacione teorije u formulaciji farmaceutskih oblika - hidrofilne matriks tablete

Percolation theory is a mathematical tool that enables insight into characteristics of geometrically complex systems. Geometrical transition of solid dosage forms is followed by sudden changes in certain tablet characteristics (mechanical properties, drug release rate). The aim of the presented study is implementation of percolation theory concepts in hydrophilic matrix tablets characterization, by determination of the percolaction thresholds for key mechanical properties of matrix tablets as well as for drug release profiles. Hydrophilic matrix tablets have been formulated using polyethylene oxide polymers as matrix forming substances, diclofenac sodium as the model drug substance, as well as mycrocristaline cellulose as a tablet filler. Varying the excipient weight ratio and applied compression force, 18 formulations have been prepared using direct compression method. Compressibility and compactibility of the excipients hava been investigated, followed by characterization of matrix tablets tensile strenght. Dissolution test for diclofenac sodium matrix tablets has been conducted using rotating paddles method, and obtained drug release profiles have been analyzed using mathematical model. In order to estimate percolation thresholds changes in matrix tablets tensile strength and kinetic parameters of dissolution profiles were studied in aspect to changes in matrix tablets relative density i.e. volumetric ratio of matrix forming substance and initial porosity of matrix tablets. Obtained values for percolation thresholds, i.e. critical porosities for tensile strenghts are 22,57 % and 50,63 % for PEO WSR 1105 and PEO WSR Coagulant hydrophilic matrix tablets respectively. Percolation threshold for kinetic parameters of diclofenac sodium release profiles for PEO WSR 1105 matrix tablets is 20,86%. Obtained results indicate that percolation thresholds can be identified as critical formulations that are susceptible to sudden changes in mechanical properties and/or characteristics in drug release profiles following minor changes in formulation composition or process parameters.Perkolaciona teorija je matematička alatka koja omogućava uvid u karakteristike geometrijski složenih sistema. Geometrijska tranzicija u čvrstim farmaceutskim oblicima je povezana sa naglim promenama određenih karakteristika tableta (mehaničke karakteristike, brzina rastvaranja lekovite supstance). Cilj rada je implementacija koncepata perkolacione teorije u karakterizaciji hidrofilnih matriks tableta, određivanjem perkolacionih pragova za ključne mehaničke karakteristike matriks tableta kao i za profile brzine rastvaranja lekovite supstance. Hidrofilne matriks tablete su izrađene sa polietilen oksidnim polimerima kao matriks-formirajućim materijalima, diklofenak-natrijumom kao lekovitom supstancom i mikrokristalnom celulozom kao sredstvom za dopunjavanje. Izrađeno je 18 formulacija variranjem masenog udela ekscipijenasa i primenjene sile kompresije, pri čemu su matriks tablete izrađene metodom direktne kompresije. Ispitana je kompresibilnost i kompaktibilnost ekscipijenasa, kao i zatezna čvrstoća izrađenih matriks tableta. Brzina rastvaranja diklofenak-natrijuma iz matriks tableta je ispitana u aparaturi sa rotirajućom lopaticom, a dobijeni profili su analizirani primenom matematičkog modela. Perkolacioni pragovi su određeni praćenjem promena u zateznoj čvrstoći matriks tableta i kinetičkim parametrima profila brzine rastvaranja lekovite supstance, u funkciji relativne gustine matriks tableta odnosno zapreminskog udela matriks-formirajuće supstance i poroziteta matriks tableta. Dobijene vrednosti perkolacionih pragova, tj. kritičnih poroziteta za zateznu čvrstoću iznose 22,57% odnosno 50,63% za PEO WSR 1105 i PEO WSR Coagulant hidrofilne matriks tablete. Perkolacioni prag za kinetičke parametre profila brzine rastvaranja diklofenak-natrijuma za PEO WSR 1105 hidrofilne matriks tablete iznosi 20,86 %. Dobijeni rezultati ukazuju na mogućnost identifikacije perkolacionih pragova kao kritičnih formulacija koje podležu naglim promenama karakteristika matriks tableta sa manjim promenama u sastavu formulacija ili parametara procesa izrade

Variability of morphological characters among ornamental sunflower collection

The research describes the field comparison of 81 decorative sunflower genotypes. In order to assess genetic diversity of sunflower genotypes the studies were conducted in the field conditions during 2010-2015 at the Institute of Field and Crops, Novi Sad, Serbia. The genetic diversity of species Helianthus annuus L. has enabled the breeding work in the direction of the decorating and plant landscaping. Depending on the qualitative and quantitative characteristics, production of decorative sunflowers can be divided into three directions. The first line is for the production of cut flowers, the second one is for garden production and the third line is for the production of pot plants. The direction of production dictates the main breeding objectives, which may include: plant architecture, the color of ray and disc flowers and duration of flowering. Investigation of the genetic variability of ornamental sunflowers relies on quantitative traits of which the greatest variability was observed in branching and plant height, which are also the most important qualities for production. The quantitative characteristics of decorative sunflowers have been examined on the basis of 81 samples

Masa 1000 semena suncokreta u zavisnosti od godine i genotipa

For a successful seed production, it is necessary to know the size, i.e. 1000-seed weight, since it affects the sowing rate, plant density over the vegetative period as well as the seed yield per unit area. The study was conducted in field conditions, on plots where seed production of sunflower hybrids parental components was organized. Seed production was based at three different localities. Observation was conducted during the course of three years. The study was performed on 18 different genotypes. Considering the total number of the observed genotypes, 10 genotypes represented lines based on CMS, while the remaining 8 genotypes represented restorer lines. The study showed that 1000-seed weight was higher with CMS based lines than with restorer lines, which was expected considering the branching of the restorer lines. Sunflower 1000-seed weight depended on the year of observation and the observed genotype. Year had a significant effect on 1000-seed weight.Za uspešnu semensku proizvodnju neophodno je poznavati krupnoću, tj. masu 1000 semena jer ona utiče na setvenu normu, optimalan sklop biljka u toku vegetacije, a samim tim i na prinos semena po jedinici površine. Ispitivanje je vršeno u poljskim uslovima na parcelama gde je organizovana semenska proizvodnja roditeljskih komponenti hibrida suncokreta. Semenska proizvodnja organizovana je na tri različita lokaliteta. Posmatranje se odvijalo tokom tri godine. Ispitivanje je obavljeno na 18 različitih genotipova. Od ukupnog broja posmatranih genotipova, 10 genotipova predstavljale su linije na bazi CMS-a, dok su preostalih 8 genotipova predstavljale restorer linije. Ispitivanja su pokazala da je masa 1000 semena veća kod linija na bazi CMS-a u odnosu na restorer linije, što je bilo i za očekivati s obzirom na granatost linija restorera. Masa 1000 semena suncokreta zavisila je od godine posmatranja i posmatranog genotipa. Godine kao faktor posmatranja imale su značajnog uticaja na masu 1000 semena

Genetic improvement in sunflower breeding—integrated omics approach

Foresight in climate change and the challenges ahead requires a systematic approach to sunflower breeding that will encompass all available technologies. There is a great scarcity of desirable genetic variation, which is in fact undiscovered because it has not been sufficiently researched as detection and designing favorable genetic variation largely depends on thorough genome sequencing through broad and deep resequencing. Basic exploration of genomes is insufficient to find insight about important physiological and molecular mechanisms unique to crops. That is why integrating information from genomics, epigenomics, transcriptomics, proteomics, metabolomics and phenomics enables a comprehensive understanding of the molecular mechanisms in the background of architecture of many important quantitative traits. Omics technologies offer novel possibilities for deciphering the complex pathways and molecular profiling through the level of systems biology and can provide important answers that can be utilized for more efficient breeding of sunflower. In this review, we present omics profiling approaches in order to address their possibilities and usefulness as a potential breeding tools in sunflower genetic improvement

Uticaj biostimulatora na energiju klijanja i klijavost semena suncokreta

The aim of this paper was to examine the effect of biostmulators on seed quality parameters - germination energy and germination, depending on the genotype and age of sunflower seeds. Testing has been conducted at the Institute of Field and Vegetable Crops on four cytoplasmic male sterile lines: OCMS-98 (L1), HA-NS-26 (L2), PH-BC2-74 (L3) and VL-A-8 (L4). Seed was produced in the period from 2010 to 2012. Two seed variants were tested - treated with metalaxyl-m and non-treated. Prior to sowing, seed was treated with fertilizes Slavol S, Bioplant Flora, and their combination. Selecting the right biostimulator for a particular genotype may lead to increased germination energy and germination, which has the positive effect on the number of plants per unit area, and hence the yield.Cilj rada bio je da se ispita uticaj biostimulatora na parametre kvaliteta semena - energiju klijanja i klijavost, u zavisnosti od genotipa i starosti semena suncokreta. Testiranje je sprovedeno u novosadskom Institutu za ratarstvo i povrtarstvo na četiri citoplazmatski muško sterilne linije: OCMS- 98, HA-NS-26, PH-BC2-74 i VL-A-8. Seme je proizvedeno u periodu 2010-2012. Testirane su dve varijante semena: tretirano metalaksilom-m i netretirano. Seme je pre setve tretirano komercijalnim preparatima Slavol S, Bioplant Flora i njihovom kombinacijom. Ispitivanje je pokazalo da dejstvo biostimulatora zavisi od genotipa, ali i od starosti semena. Odabirom adekvatnog biostimulatora za određeni genotip može se postići povećanje energije klijanja i klijavosti, što povoljno utiče na broj biljaka po jedinici površine, a samim tim i na prinos. Međutim, izborom neadekvatnog biostimulatora ili njihove kombinacije može se postići suprotan efekat od željenog, odnosno da se parametri kvaliteta semena smanje u određenoj meri

Sadržaj proteina u semenu suncokreta u zavisnosti od vremena desikacije i vlažnosti semena

The objective of this study was to investigate the effect of desiccation date and seed moisture content on sunflower seed protein content. The experimental materials were three new parental sunflower lines of the Institute of Field and Vegetable Crops from Novi Sad, Serbia (L1, L2 and L3). Reglone forte (2 l ha-1) was used for desiccation and it was applied at 7-day intervals from the end of flowering to harvest maturity. The protein content was determined by the classical method of Kjeldahl. The stabilization of the protein content was determined in treatment that was performed 21 days after flowering (DAF) at seed moisture of about 45%. Regression analysis determined the highest and statistically significant effect of seed moisture at the moment of desiccation on seed protein content in the line L1, while the effects in lines L2 and L3 were not significant.Cilj ovog ogleda je bilo ispitivanje uticaja vremena desikacije i vlažnosti semena na sadržaj proteina u semenu suncokreta. Kao materijal su korišćene tri nove komercijalne linije novosadskog Instituta za ratarstvo i povrtarstvo (L1, L2 i L3). Desikacija je izvođena preparatom Reglone forte (2 l ha-1) svakih 7 dana od završetka cvetanja do žetvene zrelosti. Sadržaj proteina utvrđen je klasičnom metodom po Kjeldahl-u. Stabilizacija sadržaja proteina utvrđena je kod tretmana koji je izveden 21 dan posle cvetanja (DPC) pri vlažnosti semena od oko 45%. Regresionom analizom utvrđen je najviši i statistički značajan uticaj vlažnosti semena u momentu desikacije na sadržaj proteina kod linije L1, dok kod druge dve linije nije bilo značajnog uticaja

Effect of plant density on stem and flower quality of single-stem ornamental sunflower genotypes

The aim of this research was to determine the optimum planting density for the production of high-quality cut flowers with desirable characteristics. 25 single-stem ornamental sunflower genotypes were planted at different densities and evaluated for flowering time, flower diameter, and stem circumference and length over a two-year production cycle. Three spacing patterns were used: 25 x 25 cm, 30 x 30 cm, and 70 x 30 cm, which led to the planting densities of 160 000, 90 000, and 60 000 plants/ha, respectively. The plant density had the most important effect on the stem circumference, flower diameter, and stem length (total variation 52, 60, and 58%, AMMI analysis) and a small effect on the flowering time (total variation 1%, AMMI analysis). Based on environment-focused scaling, all high-density environments could be suitable for the production of single-stem sunflower genotypes. The results demonstrated the adaptation of several sunflower genotypes G9, G11, G12, G21, and G22 as the most suitable based on the optimum flower diameter, stem circumference, and stem length. These results may lead to progress in growing ornamental sunflowers as a cut flower

New approaches in phenotype prediction – machine learning techniques

Use of multivariate modelling in order to improve prediction accuracy has been widely applied in plant breeding programs. In these models phenotype prediction is based on large number of independent variables which is at the same time strength and weakness. Lately, intensive research in order to improve prediction accuracy resulted in extensive use of different machine learning techniques. The aim of this study is to present new approaches in phenotype prediction based on complex relationships between genotypes and phenotypes. Widely used, one of the main tools in machine learning is artificial neural network (ANN). Although it has a long history, this powerful class of algorithms has been recently used as a state-of-the-art solution for non-linear relationship between the genotype and the trait of interest. Another important advance, capable of identifying extremely complex patterns of prediction and classification of information is called deep learning (DL). Main difference between DL and ANN is in the numbers of layers of neurons. Being based on how humans learn and process information, machine learning is powerful tool for processing complex data in order to make accurate predictions

In silico methods in stability testing of hydrocortisone, powder for injections: Multiple regression analysis versus dynamic neural network

This article presents the possibility of using of multiple regression analysis (MRA) and dynamic neural network (DNN) for prediction of stability of Hydrocortisone 100 mg (in a form of hydrocortisone sodium succinate) freeze-dried powder for injection packed into a dual chamber container. Degradation products of hydrocortisone sodium succinate: free hydrocortisone and related substances (impurities A, B, C, D and E; unspecified impurities and total impurities) were followed during stress and formal stability studies. All data obtained during stability studies were used for in silico modeling; multiple regression models and dynamic neural networks as well, in order to compare predicted and observed results. High values of coefficient of determination (0.950.99) were gained using MRA and DNN, so both methods are powerful tools for in silico stability studies, but superiority of DNN over mathematical modeling of degradation was also confirmed