Faculty of Agriculture

Kovačević B., S.Orlović., M.Ivanović, K. Čobanović, E. Nikolić-Đorić, M. Katanić and V.Galović (2011): Relationship among eastern cottonwood genotypes according to early rooting traits-Genetika, Vol 43, No. 2,[307][308][309][310][311][312][313][314][315][316][317][318][319][320] The relationship between twelve genotypes of eastern cottonwood (Populus deltoides Bartr.) was analyzed according to sixteen early rooting traits and cutting survival. Principal component analysis (PCA) and cluster analysis were used on data that were standardized by common and by one alternative way of standardization. Alternative way of standardization (standardization with within-genotype standard deviation instead of standard deviation of genotypes' means) was used in order to emphasize the contribution of genotype to the effect of differences among genotypes on 308 GENETIKA, Vol. 43, No. 2, 307 -320, 2011 total variation. After bought ways the first principal component had high correlation with the most of rooting traits and cutting survival, while the second was mainly related to the traits of root formation on the basal cut of cutting (wound roots). Three difficult-to-root genotypes (S6-7, S1-3, 129/81) were distinctly grouped against other examined genotypes, by bought principal component and cluster analysis. There was a slight difference in grouping of easy-to-root genotypes (B-229 and PE19/66) among examined ways of standardization.

Mineralna ðubriva predstavljaju jedan od najvaÿnijih èinilaca koji utièu na poveaeanje prinosa. Dosadašnja istraÿivanja izvedena na bazi eksperimentalnih i empirijskih podataka pokazala su da se porast prinosa pšenice u našim proizvodnim uslovima moÿe ostvariti racionalnijom upotrebom mineralnih ðubriva. Racionalna primena mineralnih ðubriva treba da doprinese stalnom poveaeanju prinosa i smanjenju troškova po jedinici gotovog proizvoda.

Background Numerous studies with conflicting results have tried to prove the influence of seasonal variations or different meteorological factors on the occurrence of aneurysmal subarachnoidal hemorrhage (SAH). The aim of this study was to establish a mathematical model of a series of aneurysmal rupture dates in different patients and verify a temporal pattern in the occurrence of SAH. Methods We analyzed a group of 563 patients with the exact aneurysm rupture dates, hospitalized at the Clinic of Neurosurgery, Clinical Center of Vojvodina, Novi Sad, Serbia, between January 1, 1998 and December 31, 2009. After the monthly distributions, we evaluated the period between two subsequent rupture dates.

Razvoj racunarske tehnologije u poslednje dve decenije je uticao na inienzivniju primenu metoda nelinearne regresije u mnogim oblastima istraiivanja kao: tehnologiji, biologiji, hemiji itd. U radu se ukazuje na brojne prednosti, ali i na ogranicenja metoda nelinearne regresije. Razmatrana su pitanja koja sepostavljaju u vezi sa njenom primenom: kada je nelineama regresija superioma u poredenju sa linearnomregresijom oeenjenomna osnovu transformisanin promenljivih, utvrdivanje validnosti modela, preciznost oeena parametara modela, poredenje modela ocenjenih na osnovu istog skupa podataka,poredenjemodela ocenjenih na osnovu razlicuih skupova nezavisno pnkuplienih podataka. Ukazanoje i na probleme u izracunavanjuoeenaparametara koji sejavljaju u prakticnim primenama. Za ilustraciju, nelinearnaregresija je primenjena u modeliranju zavisnostiprinosa secernerepe (tlha) u zavisnosti od utrosenili kolicina mineralnin dubriva. KUUCNE RECI: nelinearna regresija, fitovanje krive, preciznost oeena parametara, robusna regresija

The aim of this paper is to find distributions that adequately describe returns of the Belgrade Stock Exchange index BELEX15. The sample period covers 1067 trading days from 4 October 2005 to 25 December 2009. The obtained models were considered in estimating Value at Risk ( VaR ) at various confidence levels. Evaluation of VaR model accuracy was based on Kupiec likelihood ratio test.

One of the most difficult issues of farm management is giving the answer to the question what to produce, i.e. making a decision about the sowing structure. Economic factors and principles play an important role in farmers' decisions about what to grow and on which areas. The purchase price of each crop, including soybeans, is an important but not the only factor of competitiveness. The authors of this paper started from the assumption that the level and trend of soybean purchase prices, among others, affect producers' decision on the growing area for this crop. Therefore, in order to scientifically confirm the initial assumption, an attempt has been made to examine (using appropriate statistical methods) the effect of average soybean purchase prices on the spread of this crop in Serbia.

The paper is dealing with the application of knowledge of mathematics that students of agriculture and agricultural economics get in the calculus course that precede statistics, in teaching of growth curves with an asymptote, known as S-shaped curves. The most known growth curves are Gompertz curve and logistic curve. These curves are characterized by period of an increasing growth rate followed by a period with a decreasing one. The point of inflection of the growth curve is that point where the curve turns from concave to convex. The important property of asymptotic growth curves is approaching an upper limit called asymptote and to lower asymptote of zero. Many time series in different fields like in demography, biology, and marketing are characterized by this pattern. The authors present two methods that can help in discriminate Gomperz and logistic curve that are based on mathematical characteristics of curves that students can easily prove.

We have proposed novel measures based on the Kolmogorov complexity for use in complex system behavior studies and time series analysis. We have considered background of the Kolmogorov complexity and also we have discussed meaning of the physical as well as other complexities. To get better insights into the complexity of complex systems and time series analysis we have introduced the three novel measures based on the Kolmogorov complexity: (i) the Kolmogorov complexity spectrum, (ii) the Kolmogorov complexity spectrum highest value and (iii) the overall Kolmogorov complexity. The characteristics of these measures have been tested using a generalized logistic equation. Finally, the proposed measures have been applied on different time series originating from: the model output (the biochemical substance exchange in a multi-cell system), four different geophysical phenomena (dynamics of: river flow, long term precipitation, indoor 222 Rn concentration and UV radiation dose) and economy (stock prices dynamics). Results which are obtained offer deeper insights into complexity of the system dynamics behavior and time series analysis when the proposed complexity measures are applied. distributed manner; there are many connections between the system's parts [2,3], (3) it is difficult to model complex systems and to predict their behavior even if one knows to a large extent the parts of such systems and the connections between the parts . The complexity of a system depends on the number of its elements and connections between the elements (the system´s structure). In the review paper Crutchfield [5] has underlined: " Spontaneous organization, as a common phenomenon, reminds us of a more basic, nagging puzzle. If, as Poincaré found, chaos is endemic to dynamics, why is the world not a mass of randomness? The world is, in fact, quite structured, and we now know several of the mechanisms that shape microscopic fluctuations as they are amplified to macroscopic patterns. Critical phenomena in statistical mechanics and pattern formation in dynamics are two arenas that explain in predictive detail how spontaneous organization works. Moreover, everyday experience shows us that nature inherently organizes; it generates pattern. Pattern is as much the fabric of life as life's unpredictability". These sentences are also related to the phenomenon of the complexity of systems in many disciplines, ranging from philosophy and cognitive science to evolutionary and developmental biology and particle astrophysics [5,9 and refrences herein].