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M A T I C A S R P S K A

P R O C E E D I N G S F O R

N A T U R A L S C I E N C E S

112

NOVI SAD2007ZB

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YU

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MATICA SRPSKA

ODEQEWE ZA PRIRODNE NAUKE

Z B O R N I K

MATICE SRPSKE ZA PRIRODNE NAUKE

MATICA SRPSKADEPARTMENT OF NATURAL SCIENCES

PROCEEDINGS FOR NATURAL SCIENCES

Pokrenut 1951 / First published in 1951.

Published as Nauåni zbornik, serija prirodnih nauka until the tenth issue (1955), as theSeries for Natural Science from the eleventh issue (1956) — Zbornik za prirodne nauke,

and under its present title since the sixty-sixth issue (1984)

Glavni urednici / Editors-in-Chief

Miloš Jovanoviã (1951), Branislav Bukurov (1952—1969),Lazar Stojkoviã (1970—1976), Slobodan Glumac (1977—1996), Rudolf Kastori (1996—)

112

Uredništvo / Editorial BoardS. GAJINL. DOVNIKOVIÃD. KAPORR. KASTORIL. LEPŠANOVIÃI. MAKSIMOVIÃV. MARIÃS. PETROVIÃS. ÃURÅIÃ

Consulting EditorsA. ATANASSOV, BulgariaP. HOCKING, AustraliaM. SIMMONDS, UKG. SCHILING, GermanyGY. VÁRALLYAY, Hungary

Glavni i odgovorni urednik / Editor-in-ChiefR U D O L F K A S T O R I

YU ISSN 0352-4906 UDK 5/6 (05)

M A T I C A S R P S K AP R O C E E D I N G S F O R

N A T U R A L S C I E N C E S

112

NOVI SAD2007

CONTENTSSADRŸAJ

ARTICLES AND TREATISESÅLANCI I RASPRAVE

Å e d o m i r N. R a d e n o v i ã, A l e k s a n d a r J. K a l a u z i, K o s a n aL j. K o n s t a n t i n o v, G o r a n M. D r i n i ã, Dynamics of generatingtransients of delayed fluorescence induction signal and photosynthetic an-tennas: a possible relationship. Mathematical modeling approach — Dina-mika nastajawa tranzijenata indukcionih procesa zakasnele fluore-

scencije hlorofila i fotosintetiåkih antena: moguãa zavisnost. Pri-

stup matematiåkog modelovawa . . . . . . . . . . . . . . . . 5B i l j a n a M. G o r j a n o v i ã, M a r i j a M. K r a l j e v i ã - B a l a l i ã, Inhe-

ritance of plant height, spike lenght and number of spikelets per spike indurum wheat — Nasleðivawe visine stabqike, duÿine klasa i brojaklasiãa po klasu kod durum pšenice . . . . . . . . . . . . . 27

Z o r i c a T. N i k o l i ã, M i r j a n a A. V a s i ã, M i r j a n a B. M i l o š e v i ã,M i l k a L j. V u j a k o v i ã, J e l i c a M. G v o z d a n o v i ã - V a r g a,Characterization of bean varieties on the basis of protein markers — Ka-rakterizacija sorti pasuqa na osnovu proteinskih markera . . . 35

Z o r a n I. J e r k o v i ã, M a r i n a P u t n i k - D e l i ã, Effect of cytoplasm onexpression of genes for resistance to Puccinia triticina — Uticaj cito-plazme na ispoqavawe gena za otpornost prema prouzrokovaåu lisne

rðe pšenice . . . . . . . . . . . . . . . . . . . . . . . 43L a n a N. K r s t i ã, G o r a n T. A n a å k o v, P a l P. B o ÿ a, R u ÿ i c a S.

I g i ã, J a d r a n k a Ÿ. L u k o v i ã, D r a g a n a M. V u k o v, Analysisof anatomical and micromorphological characteristics of Iva xanthifoliaN u t t. — Analiza anatomskih i mikromorfoloških karakteristikaIva xanthifolia N u t t. . . . . . . . . . . . . . . . . . . . . 49

A l e k s a n d r a V. D r o b a c - Å i k, T a m a r a I. D u l i ã, D e j a n B. S t o -j a n o v i ã, Z o r i c a B. S v i r å e v, The importance of extremophile cyano-bacteria in the production of biologically active compounds — Znaåaj eks-tremofilnih cijanobakterija u produkciji biološki aktivnih ma-

terija . . . . . . . . . . . . . . . . . . . . . . . . . . 57Z o r a n A. G a l i ã, S a š a S. O r l o v i ã, B o j a n a A. K l a š n j a, A n -

d r e j R. P i l i p o v i ã, M a r i n a B. K a t a n i ã, Improvement of pro-

duction of high-yield poplar varieties seedlings by mycorrhiza application— Efekti primene mikoriza na proizvodwu sadnog materijala vi-sokoproduktivnih sorti topola . . . . . . . . . . . . . . . 67

Z l a t a Ð. K l o k o å a r - Š m i t, D u š a n k a V. I n ð i ã, S l a v i c a M. V u -k o v i ã, M a j a M. F i l i p o v i ã, J a n k o F. Å e r v e n s k i, Prelimi-nary investigation on the effects of biological and synthetic insecticides onlarge white butterfly (Pieris brassicae L.) larvae — Preliminarna ispi-tivawa efekta bioloških i sintetiåkih insekticida na larve veli-

kog kupusara (Pieris brassicae L.) . . . . . . . . . . . . . . . 75I v a n a M. S t o j š i n, D u š k a D. B l a g o j e v i ã, Etiopathogenic considera-

tion and definishon of the clinical manifestation of erosive dental defects— Etiopatogenetsko razmatrawe i definisawe kliniåke manife-stacije zubnih defekata erozivne prirode . . . . . . . . . . . 83

Ÿ e l j k o A. M i h a l j e v, D u š a n B. O r l i ã, D u b r a v k a I. Š t a j n e r,M i l i c a M. Ÿ i v k o v - B a l o š, S a v a T. P a v k o v, The influence ofdifferent levels of dietary selenium on its distribution in the organs of broi-ler chickens — Uticaj razliåitih nivoa dijetarnog selena na wegovudistribuciju u organizmu brojlera . . . . . . . . . . . . . . 95

G o r a n S. M a r k o v i ã, V l a d i c a M. S i m i ã, A l e k s a n d a r M. O s t o -j i ã, S n e ÿ a n a B. S i m i ã, Seasonal variation in nutrition of chub (Leu-ciscus cephalus L., Cyprinidae, Osteichthyes) in one reservoir of West Ser-bia — Sezonska varirawa ishrane klena (Leuciscus cephalus L., Cypri-nidae, Osteichthyes) u jednoj akumulaciji Zapadne Srbije . . . . . 107

Zbornik Matice srpske za prirodne nauke izdaje Matica srpskaIzlazi dvaput godišwe

Uredništvo i administracija: Novi Sad, Ulica Matice srpske 1Telefon: 021/420-199

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Proceedings for Natural Sciences published by Matica SrpskaPublished twice a year

Editorial and publishing office: Novi Sad, Ul. Matice Srpske 121000 Novi Sad, SerbiaPhone: +381-21/420-199

The editors of the Matica srpska Proceedings for Natural SciencesCompleted the selection for Issue 112/2007 on December 14, 2007

Editorial Staff Secretary: Julkica BoarovManaging editor: Dr. Slavka Gajin

English text proof-reader: Stanka Matejašev and Vera VasiliãTechnical design: Vukica Tucakov

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Publikovawe ovog broja pomoglo jeMinistarstvo nauke i zaštite ÿivotne sredine Republike Srbije

The edition and printing of the Proceedings has been financially supported bythe Ministry of Science and Environmental Protection of Republic of Serbia

Zbornik Matice srpske za prirodne nauke / Proc. Nat. Sci, Matica Srpska Novi Sad,¥ 112, 5—26, 2007

UDC 581.132.1

Å e d o m i r N. R a d e n o v i ã1 , 2 , A l e k s a n d a r J. K a l a u z i3 ,K o s a n a L j. K o n s t a n t i n o v1 and G o r a n M. D r i n i ã1

1 Maize Research Institute “Zemun Polje", Zemun Polje,Slobodana Bajiãa br. 1, 11185 Belgrade—Zemun, Serbia

2 Faculty of Physical Chemistry, University of Belgrade,Studentski trg br. 12—16, 11000 Belgrade, Serbia

3 Center for Multidisciplinary Studies, University of Belgrade,Despota Stefana br. 142, 11000 Belgrade, Serbia

DYNAMICS OF GENERATING TRANSIENTSOF DELAYED FLUORESCENCE INDUCTION SIGNAL

AND PHOTOSYNTHETIC ANTENNAS:A POSSIBLE RELATIONSHIP. MATHEMATICAL

MODELING APPROACH*

ABSTRACT. A mathematical model was developed for resolved temporal transientsof experimentally recorded delayed fluorescence (DF) induction signal. During an intermit-tent light regime, antennas of the photosynthetic apparatus were treated as targets, repea-tedly hit by potentially absorbable photons within a series of consecutive light flashes. For-mulas were derived for the number of antennas, cumulatively hit by a specific number ofphotons, as function of the flash serial number (time). Model parameters included: numberof absorbable photons in one flash, antenna sizes and numbers. A series of induction curveswere analyzed, obtained from a Zea mays L. leaf segment and differing in the previous darkperiod (td). Each curve, consisting of the two most prominent DF transients (C and D), wasfitted with several model types, differing in the number of absorbed photons. For both tran-sients, the best fitting result was achieved when DF induction was linked to the second ab-sorbed photon. As expected, model parameters related to antenna sizes showed weaker de-pendence on td than those referring to antenna numbers. With restrictions applied in thismodel, the two DF induction transients may be related to two classes of photosynthetic an-tennas. Their different sizes may have a predominant influence on the efficiency of photonabsorption, and possibly time-dependent appearance of DF transients.

KEY WORDS: delayed fluorescence, photosynthetic antennas, induction transients,mathematical modeling, Zea mays L.

5

* Authors dedicate this paper to the memory of a countenance and deeds of DraganFidler's.

INTRODUCTION

Delayed fluorescence (DF) phenomenon can be described as lighting ofgreen plants, algae and photosynthetic bacteria in red range of the visible spec-trum, immediately upon their illumination. In the final step, DF is created bythe same S1 � S0 transition as prompt fluorescence (L a n g et al., 1991;K r a u s e et al.,1991). But very different lifetimes, 1.5 ns or less for promptfluorescence (G o v i n d j e e et al., 1990; S c h m u c k et al., 1992) compa-red to nanoseconds (S o n n e v e l d et al., 1981; M i m u r o et al., 1999),over microseconds (H a v e m a n et al., 1975; H o l z a p f e l et al., 1974) andmilliseconds (H i p k i n s et al., 1974; B a r b e r et al., 1974) to seconds' ran-ge (R u t h e r f o r d et al., 1984) for DF, clearly indicate two very distinctmechanisms by which photoactive S1 state of chlorophyll (Chl) is created. Incase of prompt fluorescence, the S1 state is created in a 10–12—10–14 s periodby internal conversion, following light absorption. In case of DF, the S1 stateis created through a recombination of products formed in the primary photo-chemical act (G o v i n d j e e et al., 1971; J u r s i n i c, 1986). Therefore, unli-ke prompt fluorescence, which does not need more than one single Chl mole-cule to be emitted, the entire entity of the photosynthetic apparatus is neces-sary for DF emission, i.e. DF has been used as a criterion for its integrity( Z a h a r i e v a et al., 1999).

Delayed fluorescence induction trace reflects processes and phenomenaoccurring when a photosynthetic object is being kept in darkness for a while,and then illuminated, i.e. in a transition period from dark to light regime. MostDF induction traces were recorded under the millisecond working regime of arotating disc, with intermittent illumination, consisting of a few millisecondsof light period, and consecutive few milliseconds of darkness in which DF isbeing recorded (V u å i n i ã, 1983; M a r k o v i ã et al., 1987). The overallshape of a DF induction trace is highly dependent on the length of the darkperiod preceding illumination (D z h i b l a d z e et al., 1988; B u k h o v et al.,1989). If the preceding dark period (td) is longer than 30 and shorter than 300s, DF induction trace is split into at least three transients (R a d e n o v i ã etal., 1985, 1994; R a d e n o v i ã, 1994, 1997; R a d e n o v i ã et al., 2003).Clearly distinct appearance time of their maxima (tmaxA = 31 � 6 ms; tmaxB == 5 � 0.5 s; tmaxC = 15 � 5 s and tmaxD = 300 � 60 s; tmaxE = 670 � 35 s) sug-gests that their origins are in various processes occurring during the dark/lighttransition period. V e s e l o v s k y and V e s e l o v a (1990) made a stepforward in explaining the DF induction trace transients, by putting a DF induc-tion trace on the same time scale with temporal variation of prompt fluore-scence during continuous illumination of the photosynthetic apparatus (Ka-utzky effect), and with oxygen evolution changes. The Kautzky effect hasbeen thoroughly investigated and it is reasonably well understood (G o v i n -d j e e et al., 1971; G o v i n d j e e 1975; L i c h t e n t h a l e r et al. 1988;1992). The comparison revealed correlation of the B and C transients withelectrochemical gradient (ECG), formed across thylakoid membranes upon il-lumination (V e s e l o v s k i i et al., 1990; R a d e n o v i ã et al., 1981, 1985,1994; R a d e n o v i ã 1994, 1997).

6

Another mathematical model of these transients, contained in our last re-port, was based on the chosen kinetic model for consecutive first order reacti-ons (M a r k o v i ã et al., 2001). In the present work we approach the problemof modeling DF induction signal transients from another angle. If a leaf seg-ment is subject to an intermittent light regime, consisting of a series of flashes,a mathematical procedure could be developed to track the most probable num-ber of targets (antennas), hit by a particular number of projectiles (photons), asa function of time (light flash number). Parameters of such a model includeantenna sizes and their relative numbers within the analyzed leaf segment, foreach of the recorded transient within the DF induction signal. Since it wasshown that DF induction transients depend on the previous leaf dark period td(R a d e n o v i ã et al., 1981, 1985, 1994; R a d e n o v i ã, 1994, 1997), a ba-sic test of the model would be to fit a number of induction curves, differing intd, with model equations. As a result, one should expect that fitted parametervalues concerning antenna sizes should not depend on td (at least not in atrend-like manner), while those related to relative antenna numbers (i.e. num-bers of PSII responsible for DF emission) may exhibit such a behavior, depen-ding on the complex processes during the leaf dark period.

MATERIALS AND METHODS

Objects of Studies

Inbred lines:— ZP R70ÿ — developed by the ear to row method from the Rumski

Golden Dent variety is the inbred of FAO maturity group 300, dent kerneltype, with white cob; the inbred is a good combiner, non-resistant to lodgingand it is a property of the Maize Research Institute, Zemun Polje.

— Oh43 — developed by the ear to row method from the F2 populationof a narrow genetic base that was derived by self-pollination of F1 hybridOh40B x W-8 is the inbred of FAO maturity group 500, dent kernel type, withwhite cob; the inbred is a good combiner, tolerant to drought, has lower yiel-ding per se, and it is of the USA origin.

The hybrid ZPSC 46A — derived by crosses of the inbred lined ZP R70ÿto the inbred line Oh43, is the hybrid of FAO maturity group 400, dent kerneltype, with white cob; the hybrid has a high yielding potential, is tolerant todrought and is very adaptive to the growth under different agroecological cul-tivation conditions.

Experimental Procedure

Maize (Zea mays L.) inbred lines ZP R70ÿ, Oh43 and hybrid ZPSC 46Aleaf segments (2 cm2) were cut under water and placed on a temperature con-trolled plate inside a phosphoroscope. They were adapted to plate temperature(23°C), and the delayed fluorescence emission was recorded. The DF intensity

7

was measured in the dark interval of intermittently illuminated leaves, using aBecquerel phosphoroscope and a 150 W quartz-halogen lamp. One cycle con-sisted of 2 ms of light and 10 ms of darkness. Delayed fluorescence was recor-ded from the 3rd to 7th ms of the dark interval, using a cooled photomultiplier.Signal from the multiplier was registered on a storage oscilloscope for the fa-stest processes, while slower variations of DF were recorded on a chart. Fewminutes of recording produced a DF induction trace, with faster transients inthe first two minutes, and slower changes afterwards. A schematic presentationof the experimental set up of the equipment for DF chlorophyll recording isgiven in Figure 1. Details of the experimental setup can be found elsewhere( V u å i n i ã et al., 1983; R a d e n o v i ã et al., 1994; R a d e n o v i ã 1994,1997).

A RETROSPECTIVE VIEW TO EXPERIMENTAL RESULTSWITH DISCUSSION

1. Conditions for generation of transients of delayed chlorophyllfluorescence induction process

Depending on the duration of the dark period (t) — the time of previouskeeping of intact leaf segments of maize inbred lines and the hybrid in thedark — two induction curves of DF chlorophyll can be registered (Figure 2a,p, q).

The registered curves of DF chlorophyll induction processes have a refe-rence connotation, hence they are used in preceding and initial measurements

8

Fig. 1 — Experimental setup of the method and measuring equipment for delayed chlorophyllfluorescence: C — dark chamber with a sample stand; s — sample (leaf segment), filters,ELS — excitation light source, PH — photo-multiplier; O — oscilloscope, R — printer,

ELB — excitation light beam, DF — luminescent light, IS — input chamber slot,OS — output chamber slot

of DF chlorophyll in the unknown objects of studies (R a d e n o v i ã et al.,1981, 1985, 2003; R a d e n o v i ã, 1994, 1997). The DF chlorophyll inductioncurve marked with p, Figure 2a, is always obtained when the maize intact leafsegment is kept in the dark for a longer period of time (t 15 minutes) prior toits intermittent illumination in the phosphoroscope.

The DF chlorophyll resolve induction curve, marked with q, Figure 2a, isobtained when the maize intact leaf segment is kept in the dark for signifi-cantly short period of time (500 s t 30 s) with a time rate of t = 30 or 60 se-conds prior to its intermittent illumination in the phosphoroscope. It is shownthat the DF chlorophyll induction processes resolved in 5 transients conditio-nally designated with A, B, C, D, E, Figure 2a (R a d e n o v i ã et. al., 1985;M a r k o v i ã et. al., 2001; R a d e n o v i ã, 1994, 1997).

2. Resolution of delayed chlorophyll fluorescence induction processesinto transients

In the experimental resolution of DF chlorophyll induction processes,transients B, C, D and E were initially revealed by the application of standardmeasurements of DF chlorophyll (R a d e n o v i ã et. al., 1985, 1994; R a d e -n o v i ã et. al., 1994, 1997). Much latter, the transient A was revealed (R a -d e n o v i ã, 1997).

The revealed transients of DF chlorophyll (Figure 2b and 2c) are charac-terised with the time of their generation (tA, tB, tC, tD, and tE) amounting to:

9

Fig. 2a — Schematic illustration of DF induction process. The curve p — DF inductionprocesses registered from an intact leaf segment previously kept in the dark longer than

15 minutes (t15 min). The curve q — DF induction processes registered from an intact leafsegment previously kept in the dark for a significantly shorter period (t varies from 30 to

500s, with a rate of 30s) and than it is resolved transients A, B, C, D and E

10

Fig. 2b — Three-dimensional plot of delayed fluorescence (DF) induction curve resolution intotransients B, C, D and E at the temperature of 22°C

Fig. 2c — Three-dimensional plot of delayed fluorescence (DF) induction curve resolution,recorded from an intact maize leaf segment, at 32°C, following various preceding darkness

periods (t). Peaks of the resolved transients are marked B, C, D and E

31.0 ± 6 ms (A), 5 ± 0.5 s (B), 15 ± 5 s (C), 300 ± 60 s (D) and 670 ± 35 s(E), continual change of transients intensity: IA, IB, IC, ID and IE, as well as,mechanisms of their generation (R a d e n o v i ã, 1994, 1997; M a r k o v i ã etal., 1999, 2001), which provide a possibility of their mathematical modelling( K a l a u z i, 2006; M a r k o v i ã et al., 2001; R a d e n o v i ã et al., 2003).

THE MATHEMATICAL MODEL

Suppose that a group of identical targets, uniformly distributed over aparticular surface, is being hit intermittently by flashes consisting of identicalprojectiles of infinitesimally small dimensions. Although relations resultingfrom this model may be applied on other objects, in this particular case targetsrepresent antennas of the photosynthetic apparatus, and projectiles — potenti-ally absorbing photons. Suppose, further, that each target may be associatedwith a number of discrete states, depending on the cumulative number of pho-tons absorbed from the beginning of the intermittent regime. The followingpresumptions will be respected: (a) each target is hit not more than once du-ring one flash; (b) “target history" can not be neglected, i.e. “target state" crea-ted by absorption of a particular number of photons is maintained throughoutthe process. This restriction may be overcome by deriving new equations, ta-king into account reversibility of target states.

Let us observe m uniformly dispersed targets, each with an area �, withina target field with surface area S. If only one projectile approaches the field,geometric probability of a hit is:

p m11 � �/S.

If two projectiles are being directed towards the field, the corresponding pro-babilities would be:

— for both projectiles to hit the targets

p22 � (m�/S)2;

— for one projectile to hit, the other to miss

p12 = (m�/S) (1 – m�/S) + (1 – m�/S) (m�/S) = 2 (m�/S) (1 – m�/S);

— for both projectiles to miss

p02 = (1 – m�/S)2.

Probability for a given number of successful hits obviously obeys the binomialdistribution. Therefore, for a flash containing n projectiles, probability ofexactly r successful hits would be:

11

pn

rrn �

�

��

� (m�/S)r (1 – m�/S)(n–r).

Most probable number of hits could then be calculated from the conditionp pr

nrn� �1, ich yields

rpmax = [(m�/S) (n + 1)] (m�/S) n = m (n�/S).

Let us observe a series of flashes, each flash consisting of n projectiles,and let us derive an expression for the most probable number of targets hit byj projectiles after k flashes. Schematically, the whole target field may be repre-sented by a rectangle. After the k-th flash, it could be split into a series of k +1 adjacent subfields (rectangles), each representing the group of targets cumu-latively hit by a given number (0, 1, …, k) of projectiles. Although each subfi-eld is drawn as a compact part of the whole field, it is presumed that subfieldtargets are uniformly dispersed within the field. In the centre of each rectangle,there is a numerical mark representing the cumulative number of hits receivedby each target in the subfield. After the k-th flash, there are two kinds of tar-gets, cumulatively hit j times:

1) Targets, cumulatively hit j –1 times by projectiles before the k-th flashand receiving the j-th hit during the k-th flash (“newly hit targets"). Theirnumber will be denoted with m j

k .2) Targets, cumulatively hit j times before the k-th flash, but missed by

projectiles of the k-th flash.Sum of the number of targets described by 1) and 2) will be denoted with

M jk . Bearing in mind the presumption (b), concerning the conservation of tar-

get states, M jk represents the total number of targets cumulatively hit j times

after k flashes. Schematically, it corresponds to the union of all subfields mar-ked with number j in their centers.

According to the above defined labels, number of targets before the firstflash is m0

0 . After the first flash, the following scheme appears:

M M11

01

1 0

m m11

01

Following the presumption (a), there are only two kinds of targets — missedones, and those hit by one projectile. Their numbers can be calculated fromthe following expressions:

m m11

00� (n�/S) M m1

111�

m m01

00� (1 – n�/S) M m0

101� .

12

After the second flash, the same fraction of the number of targets that had pre-viously been hit by one projectile (left subfield in the scheme above), is hit bythe second projectile. Similarly, the same fraction of the number of targets pre-viously missed (right subfield in the scheme above), is now hit by their firstprojectile. Therefore, each subfield from the previous scheme must be split in-to two new subfields, increasing the total number of subfields to four. In thenew scheme (below), first subfield from the left denotes targets cumulativelyhit by two projectiles, two subfields in the middle refer to targets hit by oneprojectile (one to targets hit during the first, the other during the second flash),while the last subfield stands for targets missed during both flashes:

M M M22

12

02

2 1 1 0

m m m22

12

02

The corresponding expressions are:

m M22

11� (n�/S) M m2

222�

m M12

01� (n�/S) M m M1

212

11� � (1 – n�/S)

m M02

01� (1 – n�/S) M m0

202� .

After the third flash, the following situation arises:

M M M M33

23

13

03

3 2 2 1 2 1 1 0

m m m m33

23

13

03

resulting in the following relations:

m M33

22� (n�/S) M m3

333�

m M23

12� (n�/S) M m M2

323

22� � (1 – n�/S)

m M13

02� (n�/S) M m M1

313

12� � (1 – n�/S)

m M03

02� (1 – n�/S) M m0

303� .

From these few steps, general recurrent formulas can be derived:

13

(1) m Mjk

jk� �

�11 (n�/S), j k�1, ,� ;

m Mk k0 01� � (1 – n�/S);

M mkk

kk� ;

(2) M m Mjk

jk

jk� � �1 (1 – n�/S), j k� �1 1, ,� ;

M mk k0 0� .

By sequential substitution of the corresponding quantities, one can deriveexplicit expressions for k = 1, 2 and 3:

m m11

00� (n�/S) M m1

100� (n�/S)

m m01

00� (1 – n�/S) M m0

100� (1 – n�/S)

m m22

00� (n�/S)2 M m2

200� (n�/S)2

m m12

00� (1 – n�/S) (n�/S) M m1

2002� (1 – n�/S) (n�/S)

m m02

00� (1 – n�/S)2 M m0

200� (1 – n�/S)2

m m33

00� (n�/S)3 M m3

300� (n�/S)3

m m23

002� (1 – n�/S) (n�/S)2 M m2

3003� (1 – n�/S) (n�/S)2

m m13

00� (1 – n�/S)2 (n�/S) M m1

3003� (1 – n�/S)2 (n�/S)

m m03

00� (1 – n�/S)3 M m0

300� (1 – n�/S)3

If one observes the right column relations, an induction hypothesis can beestablished:

(3) Mk

jmj

k ��

��

� 0

0 (n�/S) j (1 – n�/S)(k – j).

Using the induction method, it is easy to prove that formula (3) is valid forevery integer value of k.

Reversibility of Target States

Although the binomial distribution (3) could be derived more directly(starting from the fact that target states are independent and by calculating pro-babilities that a particular target received j hits from k flashes), the step-by--step tracking of target states, described above, turned out to be more suitablefor model modifications. Specifically, the relations derived in that manner maybe easily modified to account for reversibility of target states. The simplest

14

model modification would be by introducing only spontaneous transitions froma “more" to the “nearest less accumulated" state. Although these transitionsprobably occur during both light and dark intermittent intervals, for reasons ofsimplicity let us take into account only the dark transitions. Let us further de-note with ( )M j

k � number of targets hit by j photons during k flashes at the endof the k-th dark intermittent interval (after the reversible transitions had beencompleted). If the corresponding target state is denoted with (j, k), two opposi-te transitions occur during the dark interval:

1) From the first “higher" to the present state: (j + 1, k) � (j, k), increa-sing M j

k , and2) From the present to the first “lower" state (j, k) � (j – 1, k), decreasing

M jk .

However, two exceptions exist: the number of targets in the “highest" sta-te, Mk

k , may only decrease, while number of targets in the “lowest" state, M k0 ,may only increase. If the transition dynamics is exponential, so that at the endof the dark intermittent interval (Tid seconds long), from M j

k targets in state (j, k)only M j

k exp (– cj Tid) remain, two modified sets of recurrent equations couldbe written as:

m Mjk

jk� ��

�( )11 (n�/S), j k�1, ,� ;

m Mk k0 01� ��( ) (1 – n�/S);

M mkk

kk� ;

M m Mjk

jk

jk� � ��( )1 (1 – n�/S), j k� �1 1, ,� ;

M mk k0 0� .

valid for the light and

( ) exp ( );M M c Tkk

kk

k id� � �

( ) exp ( ) ( exp ( ), , ,M M c T M c T jjk

jk

j id jk

j id� � � � � � �� �1 11 1 � k �1;

( ) ( exp ( ));M M M c Tk k k id0 0 1 11� � � � �

describing the processes during the dark intermittent interval. However, unlikethe initial model, complexity of the corresponding explicit relations increa-ses considerably with k, even in case of equal transition rates: ck = ck – 1 = … == c1 = c. Therefore, in this work, we fitted the experimental data supposingthat c = 0, leaving the derivation of explicit set of equations for c � 0 for ourfuture work.

Model Summary

Observing formula (3), an expression relating the fraction of targets cu-mulatively hit by j photons during k flashes can be established:

15

(4) h kM

m

k

jjk

( ) � ��

��

�

00

(n�/S)j (1 – n�/S)(k – j).

Equation (4) defines a two-parameter (j, p), p = n�/S, family of curves,presented on Figs. 3 and 4.

16

Fig. 3. — Family of curves, calculated by formula (4), showing fraction of the numberof targets, h(k), cumulatively hit by j = 1, …, 7 projectiles, as a function of time

(i. e. number of flashes, k). Parameter p = n�/S (product of the number of projectilesin each flash, n, and relative target area, �/S) was set to 0.2

Fig. 4. — Family of curves, calculated by formula (4), showing fraction of the numberof targets, h(k), cumulatively hit by two projectiles (j = 2) as a function of time

(i. e. number of flashes, k). Parameter p = n�/S was varied (0.1—0.9)

Abscissa variable is k, proportional to t, the illumination time of the inter-mittent regime in experiments with rotating disc (described in ExperimentalProcedure). These two quantities are related by the following equation: t =(k – 1) / f = (k – 1) T [s], where f (83.3 Hz) denotes the frequency of disc ope-ning appearances, T (12 ms) the corresponding light-dark cycle period. Ordi-nate variable is the fraction of targets hit by j projectiles during k flashes,h k M mj

k( ) /� �00 1. The curves presented in Figs 3 and 4 are products of

polynomial and exponential functions. For the first few values of j, expression(4) reduces to the following functions:

jM

m

k

� �1 1

00

; k [(n�/S)/(1 – n�/S)] (1 – n�/S)k

jM

m

k kk� �

�2

1

22

00

;( )

[(n�/S)/(1 – n�/S)]2 (1 – n�/S)k

jM

m

k k kk� �

� �3

1 2

63

00

;( )( )

[(n�/S)/(1 – n�/S)]3 (1 – n�/S)k

Since in this paper DF induction transients (DFIT) are modeled with fun-ctions defined by (3), each recorded DF induction curve, containing DFIT ascomponents, should be related to (3) in the following manner:

I k Sc M Sc mk

jjk

itit

nt

itit

nt

it

( ) ( ) ( ) [(� ��

��

�

� �� �

100

1

n S n Sitj

itk jit it� �/ ) ] [ ( / ) ] ,( ) ( )1 � �

where: Sc is the scaling factor, relating the number of targets hit and the ordi-nate value (in [mm]) of the experimentally recorded DF induction curve (de-pends on the experimental setup); it — index assigned to each induction tran-sient; nt — number of induction transients. In addition, a steady state of DFinduction trace, achieved after sufficient intermittent illumination time, wasmodeled with an exponential function: Is(k) = Cs(1 – exp(– �s k)), where Cs re-presents the DF steady state level, �s — time constant defining the steady statedynamics. Final form of the fitting function is therefore:

(5) I k Sc M Sc mk

jpj

kit

it

nt

itit

nt

itit( ) ( ) [ ]

(� ��

��

�

� �� �

1 1

jit

k js s

it itp C k) ( )[ ] ( exp ( )).1 1� � � �� �

In (5), in case of it-th induction transient, mit stands for its initial number oftargets (m0

0 of expression (3)), and pit for n�/S of expression (3). These notati-ons will be used throughout the RESULTS section. Additionally, in the samesection, subscripts it = 1 and it = 2 will be substituted with conventional tran-sient notations: C and D. Therefore, mC, mD, pC, pD, jC and jD will be used, rat-her than m1, m2, p1, p2, j1 and j2, as in (5).

17

Fitting Procedure

Each DF induction curve, within one series, was recorded from the sameleaf segment after a previous dark period (td = 45, 60, 90, 120, 150, 180 and240 [s]). The fitting procedure was performed applying the Nelder-Meadsimplex algorithm, supplied with MATLAB for windows, Version 4.2c. A mo-re detailed description of the procedure can be found in our previous paper( M a r k o v i ã et al., 2001).

RESULTS

As an example, four of the seven analyzed DF induction curves are pre-sented on Fig. 5. After fitting the whole series of seven curves with three mo-del types (jC = jD = 1; jC = jD = 2; jC = jD = 3), the resulting values of mC andmD parameters are presented on Fig. 6. The main difference between parame-ters mC and mD, as functions of the previous dark period td, for all three modeltypes, was that mC showed a tendency to increase with td, while mD did not.The two parameters had similar values for short dark periods, while for td 200s, mC values were 2—3 times higher. Analogous analysis of pC and pD yielded

18

Fig. 5. — Four of the seven analyzed DF induction curves, obtained by intermittentillumination of a Zea mays L leaf segment (2 cm2), using a Becquerel phosphoroscope.

As indicated, previous leaf dark periods were td = 60, 90, 120 and 180 s

19

Fig. 6. — Dependence of the fitted model parameters, mC and mD, on the previousleaf dark period, td, obtained by fitting a series of DF induction curves with three modeltypes: jC = jD = 1 (solid); jC = jD = 2 (long-short dashed); jC = jD = 3 (short dashed);

point marks: (*) — mC; (?) — mD

Fig. 7. — Dependence of the fitted model parameters, pC and pD, on the previousleaf dark period, td. The results were obtained by fitting the same series of DF induction

curves, with the same model types, as in Fig. 4. Line style same as in Fig. 4;point marks: (*) — pC; (?) — pD

results shown on Fig. 7. These results show a dependence of pC and pD on td,different from mC and mD. Parameter pC had no obvious linear trend with td asmC had (Fig. 6), but rather an inverse “U" shape with a broad plateau, whilepD was close to a constant.

In order to obtain an answer to the question which model type is mostappropriate, we compared their mean square errors:

� �E NN

DFIC I ipipip

N2 2

1

1/ ( ) ( ) ,� �

��

where: N is the number of experimental points for a particular DF inductioncurve (DFIC); (DFIC)ip — value of the experimental curve in point ip; I(ip) —value of the fitted model line, according to (5), in the same point.

Six model types: jC, jD = 1,1; 1,2; 1,3; 2,2; 2,3; 3,3 were tested. Each ofthe seven experimental DF induction curves (td = 45, 60, 90, 120, 150, 180,240) was fitted with every one of the six models. For each model type, all se-ven mean square fitting errors were averaged, and the result presented on Fig.8. As shown, the smallest fitting error was obtained when both (C and D) DFtransients had been modeled as targets cumulatively hit by two photons after kintermittent light flashes.

20

Fig. 8. — Comparison of fitting efficiency for different model types, according to theirmean square errors. Each of the seven experimental DF induction curves was fitted with

six model types and the fitting errors were averaged for each model type.The most accurate model was jC = jD = 2.

DISCUSSION

Induction kinetics of delayed fluorescence is dependent on the used pho-tosynthetic object, as well as on the applied experimental method, and the sa-me stands for very rare attempts of the transients modeling. For example,G o l t s e v and Y o r d a n o v (1997) recorded simultaneously prompt anddelayed fluorescence emission from few photosynthetic objects, using a phos-phoroscope disc, but with much shorter registration and dark periods. Theirmodeling was related to particular electron-transport steps involved in themechanism of DF emission (primarily located in PSII), but antennas role wasnot considered. In a recently published paper, G o l t s e v et al. (2003) exten-ded their research by analyzing prompt/delayed fluorescence relationship frombarley-wild type and chlorophyll b-less mutant chlorina f2, but antennas rolewere interpreted in an indirect manner.

Although DF emission is a minor probability dissipation event, once thephotons are absorbed inside antennas (0.03% of total absorbed energy (J u r -s i n i c et al., 1982)), delayed fluorescence is the only registered emissionwith the described experimental setup. In our case, a typical DF inductioncurve may be split into at least three components (M a r k o v i ã et al., 2001).In this work, similarity of shapes between theoretical (Figs. 3 and 4) andexperimental DF induction curves (Fig. 5) was used as a starting point to rela-te two distinct DF transients (C and D) with subpopulations of targets, hit by aparticular number of photons. This was achieved by means of theoretically in-troduced model parameters mC, mD, pC and pD (equations (4) and (5)). Sincethe shape of the DF induction signal is dependent on the preceding dark periodtd (R a d e n o v i ã et al., 1985, 1994; R a d e n o v i ã, 1994, 1997), and bea-ring in mind that DF induction transients are ECG controlled (M a r k o v i ã etal., 1999), investigation of a possible relationship between ECG induced struc-tural changes and dependence of the model parameters mC, mD, pC and pD,shown on Figs. 6 and 7, appears as a challenge in future research. It wasshown already that variation of td induces ECG controlled structural changes,before any temperature induced ones (M a r k o v i ã et al., 1999). Beside, inour previous report we showed that the two transients originate from differentECG controlled states (M a r k o v i ã et al., 2001). On the other hand, fromFigs. 6 and 7 it is obvious that parameters mC and pC exhibit a clearly distinctbehavior from parameters mD and pD. As stated in the INTRODUCTION, bea-ring in mind the physical interpretation of the p parameters (p = n�/S; productof n, number of absorbable photons in one flash and the ratio of target area �,over leaf area S), one should expect a smaller dependence of pC and pD on td,than mC and mD, which represent the number of targets (antennas of the pho-tosynthetic apparatus). Really, pD was very weakly dependent on td (Fig. 7),while pC was characterized by a very broad plateau in the middle range of tdvalues (60—180 s). The important result was that no obvious quasilinear trendwas observed for pC or pD, as was for mC on Fig. 6. However, the detecteddecrease of pC for the smallest and biggest values of td, if confirmed, still re-mains to be explained. Since the leaf segment area S was an experimental con-stant, the only quantity responsible for any dependence of pC or pD on td, could

21

have been n� — product of the number of absorbable photons in a singleflash, n, and the target area, �. It is still an open question, though, whether ba-sed on these results solely, we are qualified to speak about two subpopulationsof targets. Obviously, additional analyses are required in order to acquire relia-ble answers to these questions. But if this hypothesis would be confirmed, tar-gets associated with transient C would have an order of magnitude greater va-lue of the product n�, than those associated with transient D (although itwould still remain unclear whether this could be transferred to their areas:pC/pD � �C/�D). As well, it would be interesting to check whether different de-pendences of their DF-emitting numbers on td (mC showed a quasilinear incre-ase while mD did not, Fig. 6.), would also be confirmed.

Two types of photosynthetic antennas, dealing with DF, have alreadybeen described. They were related to the intensity of the incident light (IL), de-pending on the light regime by which a photosynthetic object was illuminated.Two types of DF dependences on light intensity (IL) have been found: squaredependence (proportional to (IL)2), at lower IL values, and linear dependence, athigher light intensities (M c C a u l e y et al., 1981). The (IL)2 dependence wasobtained using a phosphoroscope (millisecond light/dark regime), while the li-near dependence has been observed with microsecond and submicrosecondexcitation flashes. Square dependence of DF intensity, for low IL values, couldalso be associated with our model. Namely, since light intensity is proportionalto n, number of absorbable photons contained in one light flash, let us tran-sform expression (4) into the following form:

h k nM

m

k

jjk

( ) ( )� � ��

��

��

00

[(n�/S)/(1 – n�/S)]j (1 – n�/S)k.

For j = 2, and for sufficiently small values of n, since n�/S

Accuracy of any model is limited, among other factors, on the choice ofits initial assumptions. In case of the presented model, whole procedure andconsequent conclusions are based on somewhat restrictive presumptions (a)and (b). It is of interest, therefore, to suggest corresponding potential generali-zations of this model. Namely, if one flash would consist of so many photonsthat the number of targets hit with two or more projectiles could not be ne-glected, then the flash itself should be treated as a series of successive, shortersub-flashes, each of them respecting the condition (a). On the other hand, ifthe number of targets, with reversible history between two flashes, could notbe neglected, present recurrent formulas should be modified to account for the-se “inter-flash state changes", by introducing expressions like m f Mj

kjk� �

�( )11

(one simple case of this modification was described in the subsection Reversi-bility of Target States). Future introduction of these more sophisticated modelswill hopefully contribute to a better understanding of already known experi-mental facts.

ACKNOWLEDGEMENTS

This study was supported by the Ministry of Science, Technologies andDevelopment of the Republic of Serbia (Projects: 143043, 142025, 03E22 andTR-6827B).

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25

DINAMIKA NASTAJAWA TRANZIJENATA INDUKCIONIHPROCESA ZAKASNELE FLOURESCENCIJE HLOROFILA I

FOTOSINTETIÅKIH ANTENA: MOGUÃA ZAVISNOST.PRISTUP MATEMATIÅKOG MODELOVAWA

Åedomir N. Radenoviã1,2, Aleksandar A. Kalauzi3,Kosana Q. Konstantinov1 i Goran M. Driniã1

1 Institut za kukuruz „Zemun Poqe", Slobodana Bajiãa br. 1,11185 Beograd, Srbija

2 Fakultet za fiziåku hemiju, Univerzitet u Beogradu,Studentski trg, br. 12—16, 11000 Beograd, Srbija

3 Centar za multidisciplinarne studije, Univerzitet u Beogradu,Despota Stefana br. 142, 11000 Beograd, Srbija

Rezime

Ovaj rad åine dva meðusobno povezana dela. U prvom delu izlaÿu se ekspe-rimentalni rezultati sloÿenih indukcionih procesa zakasnele fluorescencijehlorofila i fotosintetiåkih antena intaktnog segmenta lista inbred linijeZP R70ÿ i Oh43 i hibrida kukuruza ZPSC 46A. Prouåavano je i otkriveno raz-lagawe indukacionih procesa na pet tranzijenata (kinetiåki oblici promena)koji su oznaåeni kao A, B, C, D i E. Wih karakterišu vremena nastajawa: tA, tB,tC, tD i tE koja iznose: 31,0 ± 6 ms (A), 5 ± 0,5 s (B), 15 ± 5 s (C), 300 ± 60 s (D) i670 ± 35 s (E), kontinuelne promene intenziteta tranzijenata: IA, IB, IC, ID i IEkao i mehanizmi wihovog nastajawa. Navedeni rezultati o karakteristikamatranzijenata indukcionih procesa zakasnele flourescencije hlorofila i foto-sintetiåkih antena bila su dobra osnova za poseban pristup wihovog matema-tiåkog modelovawa.

U drugom delu razvijen je matematiåki model vremenskog razlagawa tranzi-jenata eksperimentalno registrovanih indukcionih signala zakasnele fluore-scencije (ZF). Za vreme intermitentnog svetlosnog reÿima antene fotosintet-skog aparata su tretirane kao meta i gaðane ponavqajuãim pogocima apsorbuju-ãih fotona unutar serija uzastopnih svetlosnih snopova. Formula je izvedenaza broj antena, kumulativno gaðanih odreðenim brojem fotona. Parametri mode-la ukquåuju: broj apsorbovanih fotona u svakom snopu, veliåinu i broj antena.Analizirane su serije indukcionih krivih, dobijenih iz lista kukuruza, koje suse prethodno razlikovale u tamnoj fazi (tD). Svaka kriva, koja sadrÿi dva iza-brana tranzijenta C i D indukcionih procesa zakasnele fluorescencije, je op-timizovana sa nekoliko tipova modela, koji se razlikuju po broju apsorbovanihfotona. Za oba tranzijenta najoptimalniji rezultati su postignuti kada su in-dukcioni procesi zakasnele flourescencije bili povezani sa drugim apsorbo-vanim fotonom. Kao što se oåekivalo, parametri modela ukazuju da veliåinaantena pokazuje slabiju zavisnost tD u odnosu na broj antena. Uz ograniåewaovog modela, dva tranzijenta indukcionih procesa zakasnele fluorescencijemogu se povezati sa dve klase fotosintetskih antena. Wihove razlike u veliåi-ni mogu da imaju preovlaðujuãi uticaj na efikasnost apsorpcije fotona i mo-guãu vremensku zavisnost pojave tranzijenata indukcionih procesa zakasnelefluorescencije.

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Zbornik Matice srpske za prirodne nauke / Proc. Nat. Sci, Matica Srpska Novi Sad,¥ 112, 27—33, 2007

UDC 633.11:631.527.5:581.46

B i l j a n a M. G o r j a n o v i ãM a r i j a M. K r a l j e v i ã - B a l a l i ã

Faculty of Agriculture, Trg D. Obradoviãa 8,21000 Novi Sad, Serbia

INHERITANCE OF PLANT HEIGHT,SPIKE LENGTH AND NUMBER OF SPIKELETS

PER SPIKE IN DURUM WHEAT

ABSTRACT: Using the line x tester analysis we studied the combining ability andgene effects of plant height, spike length and number of spikelets per spike in durum wheat.The results of the study show that non-additive genes play more important role than addi-tive genes in the inheritance of plant height, number of spikelets per spike in both years andin inheritance of spike length only in the first year of research. Variety Belfugito, the bestgeneral combiner for plant height and number of spikelets per spike, combined well in twobest hybrids: Belfugito x Alifen and Belfugito x Yavaros 79, and these hybrids may be usedin wheat breeding programs. In the majority of the cases, good specific combining ability(SCA) effects were associated with crosses of two genetically divergent parents having atleast one parent as a good general combiner.

KEY WORDS: combining ability, gene effects, durum wheat, yield components

INTRODUCTION

The choice of parents is a very important task in a breeding program.Combining ability studies are used by plant breeders to select parents withmaximum potential of transmitting desirable genes to the progenies. In autoga-mous crops like wheat, where the ultimate aim is to develop pure line varie-ties, the estimates of general combining ability (GCA) are very useful becausethe variance due to general combining ability is attributable to additive geneaction and A x A interaction which can be fixed in further generations, whilethe variance due to specific combining ability is attributable to non-additivegene action. The gene effects and combining ability of yield components werealready studied by a number of scientists using diallel analysis (K n e ÿ e v i ãand K r a l j e v i ã - B a l a l i ã, 1993; M e n o n and S h a r m a, 1994; M e -n o n and S h a r m a, 1995; P e r o v i ã, 1995; P e t r o v i ã et al., 1995; J o -s h i et al., 2002).

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This study was therefore, undertaken to obtain information regarding thecombining ability and gene effects of plant height, spike length and number ofspikelets per spike in durum wheat using line x tester analysis.

MATERIALS AND METHODS

Five durum wheat (Triticum turgidum durum) genotypes: Mexicali 75(MEX), Yantar odeskij (UKR), Belfugito (ITA), Monodur (FRA) and Kunduru(TUR) were crossed with each of the three testers: Durumko (SCG), Yavaros79 (MEX) and Alifen (CHL). The parent varieties and their F1 hybrids wereexamined in randomized block design, with three replications. All parentswere selected on the basis of different phenotypic expression and geographicorigin.

The experiment was conducted at the experiment field of the Institute ofField and Vegetable Crops, Novi Sad, during 2000—2002. Sowing was donein the beginning of the October, in 1.2 m2 plot, with a 10—12 cm space insidethe row, and a 20 cm space between rows. Three traits were studied at fullmaturity: plant height, spike length and number of spikelets per spike. All tra-its were determined in 5 plants per replication. The combining ability and geneeffects were studied using GEN software package (Program for quantitativegenetic analysis) — line x tester analysis, described by S i n g and C h o u d -h a r y (1979).

RESULTS

The analysis of variance for plant height, spike length and number of spi-kelets per spike showed highly significant differences amongst genotypes inboth years. The genotype x environment interaction was also highly significantin both years of investigation.

The analysis of variance for line x tester for spike length indicated thatsignificant differences existed between parents (both years), interaction parentsvs. crosses (both years), crosses (second year), lines (second year), testers (se-cond year) and interaction line x tester (first year). Analysis of variance forplant height showed that significant differences existed between parents (firstyear), parents vs. crosses (both years), crosses (first year), lines (both years),testers (first year) and interaction line x tester (both years). For number of spi-kelets per spike significant differences existed between parents (second year),parents vs. crosses (second year), crosses and lines (both years), testers (firstyear) and line x tester (both years) (Table 1).

The estimation of the genetic components of variation, as well as the ra-tio of GCA/SCA showed that the additive component was lower than the do-minance component which suggests that, in both years of the investigation,plant height and number of spikelets per spike were predominantly controlledby non-additive gene action. Spike length was predominantly controlled bynon-additive gene action in the first year, while in the second year spikelength was controlled mostly by additive genes (Table 1).

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Tab. 1. — ANOVA line x tester for yield components in durum wheat

Source ofvariation DF

Mean squares

Plant height Spike length Number of spikelets

2001 2002 2001 2002 2001 2002

Replication 2 17.62 3.39 0.13 0.03 0.07 1.20Treatments 22 877.94** 437.66** 0.81** 0.53** 8.63** 4.65**Parents 7 1144.26** 459.25 1.47** 0.43** 7.01 6.49**P vs. C 1 1360.21** 722.15** 2.23** 0.54** –0.01 2.43*Crosses 14 710.33** 406.55 0.38 0.57** 10.06** 3.88*Lines 4 889.44** 727.14* 0.66 0.50** 22.44** 9.73**Testers 2 2641.24** 440.23 0.05 0.67** 12.45* 0.15L x T 8 138.05** 237.83** 0.33** 0.08 3.27** 1.89**Error 44 7.86 4.77 0.10 0.07 0.38 0.58

Total 68

Components of genetic variance

Plant height Spike length Number of spikelets

2001 2002 2001 2002 2001 2002

GSA 20.23 5,97 0.002 0.017 0.24 0.07SCA 43.39 77.69 0.075 0.005 0.96 0.44GCA/SCA 0.47 0.08 0.027 3.40 0.25 0.16

* p < 0.05; ** p < 0.01

The estimates of general combining ability pointed out that the best gene-ral combiner for plant height in the first year was Mexicali 75, while in the se-cond year it was Belfugito (Figure 1). For spike length the best combiner inthe first year was Yantar odeskij, while in the second year it was Mexicali 75(Figure 2). For number of spikelets per spike the best combiners were Belfugi-to, in the first year, and Kunduru in the second year of research (Figure 3).

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Fig. 1. — GCA for plant height in durum wheat

The hybrid which showed significant positive SCA for spike length in thefirst year was Belfugito x Yavaros 79, while in the second year there was nosignificant SCA. For plant height, the best specific combiner in the first yearwas Kunduru x Alifen, while in the second year it was Belfugito x Alifen. Incase of number of spikelets per spike the best specific combiners were Mexi-cali 75 x Yavaros 79 in the first year, and Monodur x Alifen and Belfugito xYavaros 79 in the second year of research (Table 2).

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Fig. 2. — GCA for spike length in durum wheat

Fig. 3. — GCA for number of spikelets per spike in durum wheat

Tab. 2. — Specific combining ability for yield components in wheat

HybridPlant height Spike length Number ofspikelets

2001 2002 2001 2002 2001 2002

1. Mexicali 75 / Durumko –5.04* –8.59* –0.07 0.12 –0.19 –0.492. Mexicali 75 / Yavaros 79 3.26* 4.97* 0.26 0.03 1.10* 0.483. Mexicali 75 / Alifen 1.78 3.62* –0.19 –0.15 –0.91* 0.004. Yantar odeskij / Durumko –5.03* –2.94* 0.22 0.08 0.79* 0.755. Yantar odeskij / Yavaros 79 –0.33 –6.00* –0.08 –0.13 0.01 –0.556. Yantar odeskij / Alifen 5.37* 8.94* –0.13 0.05 –0.80* –0.207. Belfugito / Durumko –1.91 6.58* –0.34 –0.14 –0.60 0.248. Belfugito / Yavaros 79 –2.43 8.42* 0.40* 0.19 0.86* 0.869. Belfugito / Alifen 4.35* –15.00* –0.06 –0.05 –0.26 –1.10*

10. Monodur / Durumko 2.01 2.82* –0.12 0.12 –0.28 –0.1211. Monodur / Yavaros 79 –2.16 –5.85* –0.22 –0.18 –0.66 –0.7512. Monodur / Alifen 0.14 3.03* 0.34 0.06 0.94* 0.87*13. Kunduru / Durumko 9.97* 2.13 0.31 –0.18 0.28 –0.3814. Kunduru / Yavaros 79 1.67 –1.54 –0.36 0.09 –1.30* –0.0515. Kunduru / Alifen –11.63* –0.59 0.05 0.09 1.03* 0.42S.E. (PKS) 1.62 1.26 0.18 0.15 0.36 0.44

* p < 0.05

DISCUSSION

The estimation of genetic components of variation showed that non-addi-tive gene effects were predominant in inheritance of plant height and numberof spikelets per spike. Similar results were obtained by S i n g et al. (1984),M e n o n and S h a r m a (1994), P e t r o v i ã et al. (1995). However, someauthors (K r a l j e v i ã - B a l a l i ã and D i m i t r i j e v i ã, 1992; K n e ÿ e -v i ã et al., 1995; J o s h i et al., 2002; S h a r m a et al., 2002) reported thatthose traits were affected mainly by additive gene action. Spike length waspredominantly controlled by non-additive gene actions in the first year, whichis in agreement with studies of S r i v a s t a v a et al. (1981) and S h a r m a etal. (2003). In the second year of research the spike length was predominantlycontrolled by additive gene action. Similar results were obtained by M i h a -l j e v and K r a l j e v i ã - B a l a l i ã (1981) and J o s h i et al. (2002).

The best general combiners with maximum number of favorable allelesfor traits under study are: Mexicali 75 and Belfugito (for plant height), Yantarodeskij and Mexicali 75 (for spike length) and Belfugito and Kunduru (fornumber of spikelets per spike). These genotypes may be exploited in the cros-sing programs in obtaining superior segregants.

Variety Belfugito, the best general combiner for plant height and numberof spikelets per spike combined well in two best hybrids: Belfugito x Alifenand Belfugito x Yavaros. Therefore, suitable segregates may be expected fromthese cross combinations. In majority of the crosses positive SCA effect wereassociated with crosses of two genetically divergent parents having at least oneparent as a good general combiner, which is in agreement with studies of

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K r a l j e v i ã - B a l a l i ã and B o r o j e v i ã (1985), or two poor generalcombiners. The crosses involving high x low and low x low combiners geneticinteraction might be additive x dominance and dominance x dominance type innature, respectively. Therefore, the heterosis observed in these crosses will benot-fixable and possibility of good segregants will be rare (S i n g et al.,1980). The combinations of two good general combiners not showing positiveSCA may be due to the fact that parents were not diverse, while in those cros-ses with high SCA involving high x high general combiners, the genetic inter-action might be additive x additive, which is fixable in further generations andcan be used in wheat breeding.

REFERENCES

J o s h i, S. K., S h a r m a, S. N., S i n g h a n i a, D. L., S a i n, R. S. (2002): Geneticanalysis of quantitative and quality traits under varying environmental conditionsin bread wheat, Wheat Inf. Service, 95, 5—10.

K n e ÿ e v i ã, D., K r a l j e v i ã - B a l a l i ã, Marija (1993): Genetic analysis of grainweight per spike in wheat, Genetika, 25 (1), 71—75.

K n e ÿ e v i ã, D., K r a l j e v i ã - B a l a l i ã, Marija, U r o š e v i ã, D. (1993): A studyof gene effects for plant height by diallel crossing in wheat, Genetika, 25, 1,57—61.

K r a l j e v i ã - B a l a l i ã, Marija, B o r o j e v i ã, S. (1985): Nasleðivanje visine sta-bljike i ÿetvenog indeksa pšenice, Arhiv za poljoprivredne nauke, 46 (163), 253—266.

K r a l j e v i ã - B a l a l i ã, Marija, D i m i t r i j e v i ã, M. (1992): Genetiåka analizabroja klasiãa po klasu kod pšenice, Savremena poljoprivreda, 40, 6, 77—80.

M e n o n, U., S h a r m a, S. N. (1994): Combining ability analysis for yield and itscomponents in bread wheat over environments, Wheat Inf. Service, 79, 18—23.

M e n o n, U., S h a r m a, S. N. (1995): Inheritance studies for yield and yield compo-nent traits in bread wheat over the environments, Wheat Inf. Service, 80, 1—5.

M i h a l j e v, I., K r a l j e v i ã - B a l a l i ã, Marija (1981): Genetska analiza kvantita-tivnih svojstava pšenice, Genetika, 13, 3, 265—280.

P e r o v i ã, D. (1995): Inheritance of stem height and yield components in wheat hy-brids in F4 and F5 generations, M Sci. Thesis. Faculty of Agriculture, Zemun.

P e t r o v i ã, S., K r a l j e v i ã - B a l a l i ã, Marija, D i m i t r i j e v i ã, M. (1995): Themode of inheritance and gene effects for plant height and harvest index in diffe-rent wheat genotypes, Genetika, 27, 169—180.

S h a r m a, S. N., S a i n, R. S., S h a r m a, R. K. (2002): The genetic system control-ling number of spikelets per ear in macaroni wheat over environments, Wheat Inf.Service, 95, 36—40.

S h a r m a, S. N., S a i n, R. S., S h a r m a, R. K. (2003): Genetics of spike length indurum wheat, Euphytica, 130, 155—161.

S i n g, R. K., C h a u d h a r z, B. D. (1979): Biometrical methods in quantitative gene-tic analysis, Kalayani Publishers, New Delhi.

S r i v a s t a v a, R. B., L u t h r a, O. P., S i n g, D., G o y a l, K. C. (1981): Geneticarchitecture of yield, harvest index and related traits in wheat, Cereal Res. Com-mun., 9, 1, 31—37.

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NASLEÐIVAWE VISINE STABQIKE, DUŸINE KLASA I BROJAKLASIÃA PO KLASU KOD DURUM PŠENICE

Biqana M. Gorjanoviã, Marija M. Kraqeviã-BalaliãPoqoprivredni fakultet, Trg D. Obradoviãa 8, 21000 Novi Sad, Srbija

Rezime

U radu su pomoãu linija h tester analize ispitivane kombinacione spo-sobnosti i efekti gena za visinu stabqike, duÿinu klasa i broj klasiãa poklasu kod durum pšenice, koristeãi pet linija, tri testera i wihove hibride.

Rezultati ispitivawa pokazuju da su neaditivni geni imali veãi znaåaj unasleðivawu visine stabqike i broja klasiãa po klasu u obe godine istraÿi-vawa, dok su u nasleðivawu duÿine klasa imali veãi znaåaj samo u prvoj godiniistraÿivawa. Najboqi opšti kombinatori za visinu stabqike bili su genoti-povi Mexicali 75 i Belfugito. Za duÿinu klasa najboqe opšte kombinacione spo-sobnosti imali su Yantar odeskij i Mexicali 75, dok su za broj klasiãa po klasunajboqi opšti kombinatori bili Belfugito i Kunduru. Sorta Belfugito, najboqiopšti kombinator za visinu stabqike i broj klasiãa po klasu, dala je dva hi-brida sa najboqim posebnim kombinacionim sposobnostima (Belfugito x Alifeni Belfugito x Yavaros 79), koji se kao takvi preporuåuju za daqi rad na ople-mewivawu pšenice. U veãini sluåajeva hibridi sa dobrim posebnim kombina-cionim sposobnostima nastali su ukrštawem dva razliåita roditeqa od kojihje bar jedan bio dobar opšti kombinator.

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Zbornik Matice srpske za prirodne nauke / Proc. Nat. Sci, Matica Srpska Novi Sad,¥ 112, 35—42, 2007

UDC 635.652:577.112

Z o r i c a T. N i k o l i ã1 , M i r j a n a A. V a s i ã2 ,M i r j a n a B. M i l o š e v i ã1 , M i l k a L j. V u j a k o v i ã1 ,J e l i c a M. G v o z d a n o v i ã - V a r g a2

1 National laboratory for seed testing,Maksima Gorkog 30, 21000 Novi Sad, Serbia

2 Institute of field and vegetable crops,Maksima Gorkog 30, 21000 Novi Sad, Serbia

CHARACTERIZATION OF BEAN VARIETIESON THE BASIS OF PROTEIN MARKERS

ABSTRACT: The biochemical marker phaseolin and isozymes were used in thiswork to display the variation of common bean germ plasm. Fifteen bean genotypes of diffe-rent origin i. e. selections were studied. From 8 analyzed enzymic systems, enzymes MDH,SKDH, ME and IDH were polymorphic, while there were no differences in zymograms forenzymes PGM, PHI, PGD, and ADH. Analysis of phaseolin revealed two types: S and T.The S type of phaseolin was found in most of analyzed genotypes (9). Phaseolin type Twas found in varieties of Novi Sad selection: Zlatko, Sremac and Aster, domestic popula-tion Ÿuto-zeleni Stepanoviãevo and Jovandeka, Croatian variety Slavonski ÿuto-zeleni. Tho-se varieties were developed from domestic populations from north-west region of Balkan,Slavonia, and Vojvodina.

KEY WORDS: common bean, germ plasm, phaseolin, isozymes

INTRODUCTION

Bean is an unavoidable food component in diets of people living in manyBalkan countries, and elsewhere in the world. It is main source of protein andenergy, and is gaining importance in human diet.

Origin of bean (Phaseolus vulgaris) is America. It was brought to Europefrom Central America during second Columbus voyage. It was brought to Bal-kan from two directions: from Turkey — south, and From France and Italy —north. Crossing of main trade ways, soil and climatic conditions, and other dif-ferences led to great divergence of bean in our surroundings (V a s i ã, 2004).Domestic populations of tall, climbing beans, of short bean and introducedAmerican varieties with shrubby straight stem, and small, white with roundgrains prevailed earlier. Today, mostly domesticated populations and modern,bred bean varieties are grown (V a s i ã et al., 2001).

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It is thought that domestication of bean was done in two regions, one isCentral America, and second is the area of Andes in South America (G e p t set al., 1986). It is still unclear if there was small centre in Columbia aroundthat region, where transfer of genes from wild relatives to domestic varietieswas done (B e e b e et al., 1997).

Proofs supporting diversity of two centers of origin come from study ofvariability of grain size (E v a n s, 1973), phaseolin (G e p t s et al., 1986),morphology (S i n g h et al., 1991), isozyme (K o e n i g and G e p t s, 1989,S i n g h et al., 1991a), and DNK markers (H a l e y et al., 1993).

Storage protein phaseolin and isozymes

From total protein content in bean 50 and 75% are globulins (A l l i etal., 1994). There are two types of protein inside this group, the dominatingone — phaseolin, and lectin or phytohemagglutinin (S t a s w i k et al., 1986).Phaseolin the main reserve bean protein is soluble in high salt concentration. Itcontains from 35 to 50% of total nitrogen in seed (M a and B l i s s, 1978,L i o i, 1989). Phaseolin is coded with loci complex from 6 to 9 genes. Allelescoding polypeptides of each phaseolin type are co-dominant. Reserve proteinsare reliable markers in studies of domestication and dispersion of bean varieti-es, and in analysis of phytogene relationship between species inside Phaseolusgenus. In comparison with Phaseolus vulgaris L., bean and string bean, otherspecies of this genus have not been studied enough in the context of molecularcharacterization.

Bean as a self-pollinated plant species presents an excellent material forisoenzymic fingerprint. Low level of heterozygosity makes it possible for eachspecies to be characterized with one or two isozymic profiles (W e e d e n,1984).

The aim of this work was to evaluate 15 bean varieties, using phaseolinseed protein and isozymes analysis, the genetic variability as well as to relatetheir origin to the Mesoamerican and Andrean gene pools. The results maycontribute to improvement of germ plasm bank management and may improvethe efficiency of the breeding process.

MATERIAL AND METHODS

Fifteen bean genotypes of different origin i. e. selections were studied inthis paper. Eight varieties of Department of vegetables, Research institute offield and vegetable crops (IFVC), Novi Sad: Zlatko, Sremac, Balkan, Belko,Dvadesetica, Levaå, Maksa and Aster, domestic population: Greenish-yellowStepanoviãevo and Jovandeka, Bulgarian varieties Prelom and Ludogorje, vari-ety Medijana from Smederevska Palanka, American variety C-20, and Slavon-ski ÿuto zeleni from Croatia.

Stem tissues of 5 days old seedling homogenized in 50mMTrisHCl, pH6.8 in which 1% mercaptoethanol was added, was used for isozymic analysis.

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Isozyme systems: malate dehydrogenase (MDH), malic enzyme (ME), phos-phohexose isomerase (PHI), phosphogluconate dehydrogenase (PGD), phos-phoglucomutase (PGM), shikimate dehydrogenase (SKDH), isocitrate dehydro-genase (IDH), alcohol dehydrogenase (ADH) were analyzed according to S t u -b e r et al. (1988).

Preparation of samples and 1D-SDS PAGE electrophoresis of phaseolinwere done according to R o d i n o et al. (2001). Four individual seeds weretested from each samples.

RESULTS

From 8 analyzed enzymic systems, enzymes MDH, SKDH, ME and IDHwere polymorphic, while there were no differences in zymograms for enzymesPGM, PHI, PGD, and ADH (Fig 1). Genotypes Jovandeka and Aster had fa-ster traveling variant of malic enzyme and malate dehydrogenase, while rest ofthem had slow traveling allelic variants (Fig. 2a and b). Three different allelicvariants were found for enzyme shikimate dehydrogenase (Scheme 1) and twofor locus Idh1 isocitrate dehydrogenase.

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Fig. 1. — Zymogram pattern of PGM (a) and PHI (b) bean genotypes

Fig. 2. ME (a) and MDH (b.) zymograms of bean genotypes from the left to the right:C-20, Aster, Ludogorje, Jovandeka, Prelom, Medijana, Greenish-yellow Stepanoviãevo

Analysis of phaseolin revealed two types: S and T. S type of phaseolinwas found in most of analyzed genotypes (9 from 14) (Tab. 1). Phaseolin typeT is found in varieties of Novi Sad selection: Zlatko, Sremac and Aster, dome-stic population greenish-yellow Stepanoviãevo and Jovandeka, Croatian varietySlavonski ÿuto-zeleni (Fig. 3).

Tab. 1. — Bean varieties, origin, type of phaseolin and isozymic variants

Bean variety Origin Type ofphaseolin MDH ME SKDH IDH

1. Zlatko IFVC T S S B F2. Sremac IFVC T S S A F3. Balkan IFVC S S S C F4. Belko IFVC S S S C F5. Dvadesetica IFVC S S S B F6. Levaå IFVC S S S C F7. Maksa IFVC S S S C F8. Greenish-yellow

Stepanoviãevodomestic

population T S S A S

9. Medijana S. Palanka S S S C F10. Prelom Bulgaria S S S C F

11. Jovandeka domesticpopulation T F F B S

12. Ludogorje Bulgaria S S S C F13. Aster IFVC T F F B S14. C-20 USA S S S C F15. Slavonski ÿuto-zeleni Croatia T S S B F

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Scheme 1. — Presentation of SKDHzymogram pattern of bean genotypes

DISCCUSSION

The variability at the protein level has been well documented for P. vulga-ris (W e e d e n 1984, K o e n i n g and G e p t s, 1989). Isozyme analysis (K o e -n i n g and G e p t s, 1989) and the analysis of phaseolin seed storage proteinpointed out to two different groups of P. vulgaris. It was found out that therewas a relationship between geographic distribution and phaseolin type in wildand cultivated bean varieties. Samples from Central America had primarily Sphaseolin type, with a few exceptions having M type. Samples from Andeshad primarily T phaseolin type, and some had C, H, A, J, or I type. There arebean varieties with S and C/T phaseolin type, revealing that multiple events ofgene recombination happened during domestication process (B r o w n et al.,1982, G e p t s et al., 1986).

The origin of Serbian bean germ plasm is unclear. The biochemical mar-ker phaseolin and isozymes were used in this work to display the variation ofcommon bean germ plasm. The S type of phaseolin was found in most ofanalyzed genotypes (9 from 14) (Tab. 1), which revealed that in the process ofdevelopment of new varieties under climatic conditions of our country and theregion, germ plasm from Central America was used. According to G e n å e vet al. (2002) Bulgarian bean varieties with dominating S phaseolin were betteradapted, to climatic conditions of high temperature, and irregular rain falls, incomparison to others.

Phaseolin type T was found in varieties of Novi Sad selection: Zlatko,Sremac and Aster, domestic population greenish-yellow Stepanoviãevo and Jo-vandeka, Croatian variety Slavonski ÿuto-zeleni (Fig. 3). Those varieties were

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Fig. 3. — Different types of phaseolin obtained by SDS PAGE electrophoresis:1. protein marker (170-11 kDa), 2,3 control S type phaseolin, 4,5 control C type,6,7 control S, 8—11 C-20, 12—15 Aster, 16—19 Ludogorje, 20—23 Jovandeka

developed from domestic populations from north-west region of Balkan, Sla-vonia, and Vojvodina.

Z e v e n et al. (1999) showed that T phaseolin type predominated in Hol-land gene bank. It was found in 132 genotypes from analyzed 157, which re-vealed Andes origin.

By combination of data for phaseolin and seed size one can conclude thatat least three independent domestications took place. In Central America do-mestication led to varieties with small seed and S phaseolin type; in Columbiasmall seed and B phaseolin type, and in region of South Andes large seed andT phaseolin type. Low frequency of B phaseolin type pointed out that it was aminor center (G e p t s et al., 1986). Origin of C, H and T phaseolin type hasnot been cleared yet. They have not been found in Central America. B r o w net al. (1981) suggested that C phaseolin type could be created by translocationor uneven crossing over in hybrids between two lines having T and S type.This event could take place after introduction of varieties with S phaseolintype into Andes region. Results obtained in this work suggested that both genepools were used in process of introduction and breeding of common bean inSerbia.

Data on isozymic variability in combination with data on phaseolin typegive a fine picture on genetic diversity of bean varieties (S a n t a l l a et al.,2002). Analysis of specific region of genes for phaseolin, identification of va-riation in exon and intron, offers more precise data on genetic diversity (K a -m i et al., 1995).

CONCLUSION

It was confirmed by experiment that significant polymorphism of enzy-mic system was not expected since commercial bean varieties were studied.Different allelic variants were found for enzymes: MDH, ME, SKDH andIDH. Most of studied genotypes had S type of phaseolin, and T type was fo-und in just a few. Germ plasm from Central and South America was used inthe process of creation new varieties under climatic conditions of our countryand the region. Analysis and characterization of varieties of Department of ve-getables, Research institute of field and vegetable crops, Novi Sad at the levelof protein was done for the first time. Obtained results present a solid startingbase for further investigation of gene bank and application of molecular mar-kers.

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V a s i ã, Mirjana, G v o z d a n o v i ã - V a r g a, Jelica, A. T a k a å (2001): Selekcijapasulja (Phaseolus vulgaris L.), Savremena polj. 1—2, 237—245.

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KARAKTERIZACIJA SORTI PASUQA NA OSNOVUPROTEINSKIH MARKERA

Zorica T. Nikoliã1, Mirjana A. Vasiã2, Mirjana B. Miloševiã1,Milka Q. Vujakoviã1, Jelica M. Gvozdanoviã-Varga2

1 Nacionalna laboratorija za ispitivawe semena,Maksima Gorkog 30, 21000 Novi Sad, Srbija

2 Nauåni institut za ratarstvo i povrtarstvo,Maksima Gorkog 30, 21000 Novi Sad, Srbija

Rezime

U radu je prouåeno 15 sorti pasuqa razliåitog porekla i selekcija, izbanke gena Zavoda za povrtarstvo Nauånog instituta za ratarstvo i povrtarstvo,Novi Sad. Analizirano je 8 enzimskih sistema i rezervni protein fazeolin.Razliåite alelne varijante naðene su za enzime: MDH, ME, SKDH i IDH. Veãi-na analiziranih genotipova (9) ima S tip fazeolina. Sorte novosadske selek-cije: Zlatko, Sremac i Aster, domaãe populacije Ÿuto zeleni Stepanoviãevo iJovandeka, hrvatska sorta Slavonski ÿuto-zeleni imaju T tip fazeolina. Novo-sadske sorte su nastale izborom iz domaãih populacija iz severozapadnog pod-ruåja Balkana, Slavonije i Vojvodine.

Na osnovu dobijenih rezultata zakquåeno je da se u procesu stvarawa novihsorti u klimatskim uslovima naše zemqe i regiona koristila germplazme izSredwe i iz Juÿne Amerike. Po prvi put su izvršene analize i karakterizaci-je sorti Zavoda za povrtarstvo Nauånog instituta za ratarstvo i povrtarstvo,Novi Sad, na proteinskom nivou. Rezultati polimorfizma fazeolina i izoen-zima predstavqaju dobru polaznu osnovu za daqa istraÿivawa banke gena pasuqai primenu molekularnih markera.

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Zbornik Matice srpske za prirodne nauke / Proc. Nat. Sci, Matica Srpska Novi Sad,¥ 112, 43—48, 2007

UDC 633.11:632.4

Z o r a n I . J e r k o v i ãM a r i n a P u t n i k - D e l i ã

Institute of field and vegetable crops,Maksima Gorkog 30, 21000 Novi Sad, Serbia

EFFECT OF CYTOPLASM ON EXPRESSION OF GENESFOR RESISTANCE TO PUCCINIA TRITICINA

ABSTRACT: The F2 progenies from crosses of wheat varieties Pliska, Sreãa, Vila,Holly, three BM lines as Lr 26, Lr 34 and Lr 38 near isogenic lines (NIL), were tested si-multaneously in the greenhouse at seedling stage (20°C) and differentiate