AOBPreview originally published online on August 11, 2004
Annals of Botany 2004 94(4):535-543; doi:10.1093/aob/mch170
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Annals of Botany 94/4, © Annals of Botany Company 2004; all rights reserved
Quantification of Photoperiodic Effects on Growth of Phleum pratense
Department of Plant and Environmental Sciences, Agricultural University of Norway, PO Box 5003, N-1432 Ås, Norway
* For correspondence. E-mail ole.baadshaug{at}ipm.nlh.no
Received: 16 March 2004 Returned for revision: 14 May 2004 Accepted: 16 June 2004 Published electronically: 11 August 2004
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSLITERATURE CITED |
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• Background and Aims Accurate quantifications of plant responses to photoperiod are useful for physiological studies, in growth modelling and in other studies of environmental effects. The objective of the current work was a mathematical description of photoperiodic influence on plant morphological traits, using functions with few and common parameters related to key plant characteristics and typical response patterns.
• Methods Two latitudinal cultivars of timothy (Phleum pratense) were studied in a climate chamber experiment at 9, 12, 15, 18, 21 and 24 h photoperiods. Seedling growth was recorded by measurements of main tiller leaf tip heights every other day from the 5–6 leaf stage onwards, and as plant size and dry weight at days 37, 46, 62 and 70, i.e. at the end of experiment. The plant responses to photoperiod were described by the term 
, where PP = photoperiod in h, PPc = photoperiod of maximum response, c = characteristic coefficient of main response interval, d = sensitivity coefficient characterizing course of function beyond the main response interval. PPR was tested on experimental data for different growth characteristics (i), e.g. size of individual leaves (Yi), identified by their sequential numbers on the main tiller (LN) using the function: 
. The growth course was described by the same function, replacing LN with day number of treatment exposure.
• Key Results and Conclusions The functions described with high precision (r2 > 0·97) the effect of photoperiod on growth as expressed by several plant characteristics, such as leaf area development, top and root DM production, as well as cultivar differences. Green leaf area was more sensitive to photoperiod than above-ground DM production. The southern cultivar ‘Grindstad’ was more sensitive than the northern one ‘Engmo’. The functional relationships suggest mechanisms for plants' daylength responses and latitudinal adaptation.
Key words: Daylength, dry matter, functional relationships, leaf area, leaf elongation, modelling, Phleum pratense, photoperiodic effects, quantification
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSLITERATURE CITED |
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Photoperiodism is one of the most significant and complex aspects of the interaction between plants and their environment. It is defined as plant responses to daylength, enabling living organisms to adapt to seasonal changes. For instance, at high latitudes autumnal short days signal the induction of bud dormancy and cold hardiness in perennial plant species. Similarly, in desert species dormancy may be induced by long-day conditions, which are accompanied by the unfavourable environment of water stress (Schwabe and Nachmony-Bascombe, 1963
).
The classification of plants according to their photoperiodic responses is usually based on flowering. The two main photoperiodic response categories are short-day plants (SDPs) and long-day plants (LDPs), in which flowering occurs in short or long days, respectively. Both types may respond qualitatively or quantitatively to daylength. Besides these types and day-neutral plants, a few plant species have more specialized daylength requirements; i.e. intermediate-day plants (IDPs), in which flowering occurs only between narrow daylength limits (e.g. 12–14 h for one cultivar of sugarcane) and ambiphotoperiodic species (APPSs) in which flowering occurs only in long or short days (e.g. Madia elegans) but not at intermediate daylengths (cf. Taiz and Zeiger, 1998). Most temperate grasses and sedges (Carex spp.) may have a dual daylength requirement for flowering (Heide, 1987, 1994, 1997), for example the plants must first be exposed to short days and thereafter to long days (SD–LD), or the dual requirement is reversed (LD–SD plants, e.g. Bryophyllum daigremontianum; Zeevaart, 1969).
Most plants are sensitive to photoperiod, not only for generative development but also in many other aspects, such as seed germination, leaf formation rate, leaf blade length and width expansion, dry matter production and its partitioning. Seed germination of rice, an SDP, was promoted by long days (Bhargava, 1975). Long days may result in an enhanced leaf appearance rate in, for example, wheat (Cao and Moss, 1989). However, in very many cases artificial photoperiod extension with low light intensity has been shown to have little or no significant effect on this rate: for example perennial ryegrass (e.g. Gautier et al., 1999), tall fescue (e.g. Skinner and Nelson, 1995), timothy, meadow fescue (e.g. Virkajärvi and Järvenranta, 2001), and cocksfoot (Østgård and Eagles, 1971). More-or-less the same results have been observed on leaf unfolding in many other crop plants (e.g. Mauchow and Carberry, 1990; Ritchie and NeSmith, 1991; Volk and Bugbee, 1991; Sadras and Villalobos, 1993; McMaster, 1997).
Photoperiod extension may influence final leaf size of grasses and cereals through significant increases in blade length (Cooper, 1964; Ryle, 1966a,b; Williams and Williams, 1968; Hofstra et al., 1969; Eagles, 1971; Eagles and Østgård, 1971; Heide, 1980, 1982) and sheath length (Williams and Williams, 1968; Hofstra et al., 1969; Hay and Pedersen, 1986), while the effect on leaf width seems to be small or insignificant (Østgård and Eagles, 1971; Heide, 1982; Heide et al., 1985b; Hay, 1990). Daylength extension has also been shown to significantly stimulate dry matter production in many grass species (Eagles and Østgård, 1971; Heide, 1982; Hay and Heide, 1983; Heide et al., 1985a, b; Solhaug, 1991), and biomass partitioning to above-ground plant parts (Eagles, 1971; Eagles and Østgård, 1971; Heide, 1982; Heide et al., 1985a, b).
Crop production models have usually not taken into account the types of true photoperiodic effects reported above, except the lucerne model of Holt et al. (1975) and the one for winter wheat of Porter (1984). Especially at high latitudes and in perennial crops that are harvested twice or more per season (e.g. perennial fodder grasses and legumes), such effects are main determinants of seasonal variation in potential production. For descriptive use in crop growth modelling information of daylength effects should be condensed in a mathematical quantification, ideally as a function or set of functions that also takes into account possible interactions with other environmental factors. The objective of this study was to generate a method for quantification of plant response characteristics to photoperiod that would be useful for: (1) overall analysis of plant sensitivity and response patterns to photoperiod; (2) interpretation of the responses in terms of individual processes and mechanisms; and (3) developing valid daylength modules for models simulating production and winter survival of perennial temperate forage crops.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSLITERATURE CITED |
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A versatile set of analytical functions
Booij and Meurs (1995)
used the logistic function (Lane et al., 1987) to describe the mean length of celery flower stalks as affected by photoperiod. However, the present results in timothy do not indicate a clear saturation photoperiod length but suggest rather an optimum photoperiod or a continual, slightly positive response up to continuous light. Thus, logistic functions do not seem to be convenient and sufficiently precise to describe the plant responses to photoperiod that are observed. Based on general knowledge of the response patterns of plants to photoperiod and on the present experimental data, the photoperiodic response (PPR) term was defined as:
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c 4 and –0·05 d c; and in SDPs by –4 c 0 and 0 d 0·05. For other traits such as growth and morphological development, the intervals of parameter values may be: 0 c 2 and –0·05 d 1. In any case, when c = 0 (i.e. no daylength response), the parameter d will also be equal to zero. PP is photoperiod, which is defined to the interval between the threshold photoperiod and continuous light (24 h).
In specific cases specific functions emerge from the term PPR:
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The response to photoperiod in any (i) growth characteristic (Yi) can be described by a regression function on PPR, denoted the plant response function to photoperiod, PRFPP:
 | (2) |
 | (3) |
0, the PPc is slightly displaced from the inflection point by a distance related to the values of c and d, and even reaching OPP when c = d. An IDP response pattern to photoperiod can be described by PPR when c 
d (Fig. 1), and an APPS response curve can be described indirectly as the reciprocal of an IDP's curve. Yi, may be the amount or percentage of flowers, or a plant growth characteristic (i). If daylength does not affect plant flowering or growth (DNPs), the parameters c and d will be zero (c = d = 0).
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Individual leaf response to photoperiod
In young grass plants, leaf growth and size depend on leaf position, i.e. leaf sequential number (LN) on the main stem of seedlings. Based on PPR (eqn 1) the individual leaf blade length, width, and area (Yi) can be described by:
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The parameters of c, d, PP and PPc are the same as in eqn (1), and 
accounts for the variation among individual leaves of the species or ecotype. The parameters a and will be equal to zero when there is no effect of leaf position. In this case, eqn (4) reduces to eqn (1). If there is no response to photoperiod, the parameters c and d will be equal to zero and eqn (4) becomes: 
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Time course of photoperiodic effects
Usually, a time course of plant growth follows a sigmoid curve, which can be described by a logistic function. However, at an early, vegetative stage plant growth follows an approximately exponential growth pattern. Thus, for forage grass plants which usually are harvested at a premature stage, early growth is of most interest, and the development over time of the plant size (Yi), expressed by a relevant measure (i), can be described by:
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, which relates growth to the time course (age) only. From eqn (5), three equations can be derived:
- Growth rate per day (DGR in g d–1) under different, constant daylength conditions.
(5.1)
- Photoperiod extension (per h) affects on growth increment (hourly growth increment, HGI in g h–1) at a given time (t).
(5.2)
- The composite change in growth rate (total growth rate, TGR in g d–1 h–1) per h extension of photoperiod and per day under varying time and photoperiod, which can be described by the total differential of eqn (5).
(5.3)
Examples with experimental results will be given by use of eqns (1 
–5) and (5.1–5.3).
Experimental conditions and materials
The experiment that was conducted from January to March 2001, in climate chambers (size 75 x 78 x 84 cm) at the Agricultural University of Norway, included two Norwegian latitudinal ecotypes of timothy (Phleum pratense L.), registered as cultivars ‘Engmo’ (69°N) and ‘Grindstad’ (59·5°N). The treatments consisted of six photoperiodic levels ranging from 9–24 h at 3-h intervals and a diurnal mean temperature of 11 °C (Fig. 2). Seeds were sown on 20 December 2000. The seedlings were transplanted to pots (diameter 12·5 cm, depth 15 cm) on 5 January 2001. The pots were transferred to the chambers on January 17 when seedlings had reached the five-leaf stage. The experiment comprised a total of 96 pots with 288 plants of two cultivars allotted to two replicates within each chamber, four harvest times, six photoperiodic treatments, and with three plants per pot. During the experimental period, pots were moved weekly within each chamber to randomize possible effects of uneven light distribution.
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hours of photosynthetic light of 155–170 µmol m–2 s–1 irradiance; 
hours of daylength extension with irradiance at 1·5–1·6 µmol m–2 s–1; 
hours of darkness. Ambient air temperature in the growth chambers is indicated at the bottom.The tip height above the soil surface of elongating leaves, number of leaves on the main tiller and number of tillers per plant were observed every other day. Harvests of two pots per cultivar and per treatment were conducted after 34, 49, 61 and 70 d (dates: 20 Febuary, 7, 19 and 28 March). Observations made at each harvest were as follows: blade length of each green leaf, maximum leaf blade width, individual leaf blade area and individual internode length on the main tiller, total leaf blade area plus corresponding dry weight, stem (including leaf sheaths) area plus corresponding dry weight, root dry weight, and number of senescent (dead or yellow) leaves. Areas were measured using a LI-3000 area meter (Li-Cor, Lincoln, NE, USA).
The responses of plant characteristics (Yi) to photoperiod, leaf position, time course and their interactions were analysed using eqns (1–5). The values of parameters were determined by using the non-linear regression method in the statistic software package SPSS v. 10·0.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSLITERATURE CITED |
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Leaf growth response to photoperiod
The photoperiodic effects on mean main tiller leaf growth, expressed as leaf blade length (LBL) or width (LBW) of fully expanded leaves, were described with high precision (r2 > 0·97) by eqn (2) (Table 1, Fig. 3).
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) and ‘Grindstad’ (—, •). Data for fully expanded leaves 7–12 on the main tiller.The Yb values of Table 1 indicate a higher leaf growth potential in ‘Grindstad’ than in ‘Engmo’, at least under daylengths
15 h (Fig. 3A). Leaf blade length and width of both cultivars increased with daylength extension. The sensitivity to daylength was also higher in ‘Grindstad’, as expressed by parameter c, which reflects a shorter daylength interval of maximum response and a steeper slope of the curve within this interval. In ‘Engmo’ a small and insignificant (d 0) decrease in LBL was observed for daylengths longer than the optimum (OPP) of 16·3 h, whereas ‘Grindstad’ showed a significant decrease for daylengths beyond its OPP of 14·2 h. The differences between the cultivars in PPc, which was not significant, and in OPP of some 2 h are small when considering the difference in growing-season daylength of the cultivars' latitudes of origin, which is at least 5–6 h. Leaf blade width increased continuously up to 24 h in both cultivars so that their response curves are almost parallel (Fig. 3).
Individual leaf growth on the main tiller
The effects of photoperiod, leaf position (expressed as leaf sequential number) and their interaction on mean main tiller leaf blade growth were described with high precision (r2 > 0·91) by eqn (4) (Table 2; Fig. 4). In both cultivars blade length from leaf no. 7 onwards decreased with increasing leaf sequential number (a < 0), most clearly in short daylengths. By daylength 
15 h, the blade lengths of ‘Engmo’ were almost equal for all leaves and daylengths (d 0), while ‘Grindstad’ showed a relatively strong decrease with daylength extension. The negative effect of daylength at values greater than the optimum of 14·2 h also increased with leaf number. Overall, this implies an increase in the total daylength effect with leaf number in both varieties, but most notably in ‘Grindstad’ (Fig. 4).
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In both cultivars blade width of consecutive leaves decreased under short daylengths while there was an increase under long days (Fig. 4). The maximum increment of leaf blade width that resulted from daylength extension was from approx. 1 mm for the seventh leaf to some 3 mm for the twelfth leaf.
Combined responses to photoperiod and time
The fitted parameters of eqn (5) produced r2 values higher than 0·98, except for root dry matter of ‘Engmo’ where r2 = 0·95 (Table 3). Most d values were >0 for this long-day species, indicating a reduced production towards continuous light and an optimum daylength (OPP) that was longer in ‘Engmo’ than in ‘Grindstad’. The exception was above-ground DM production for ‘Grindstad’ where d 0, indicating a levelling-off towards continuous light. The daylength effects on growth as described by eqn (5) and fitted coefficients (Table 3) are best visualized by the response surfaces shown in Figs 5 and 6, which also include the individual growth curves. Thus, the agreement between estimates and observed data (Table 3) is also evident from Fig. 5, which shows the course of the different growth measurements throughout the experiment. During this period some plants passed far into generative development, implying stem elongation, and a few plants reached heading of the main tiller. However, as judged from the time-course of the individual curves (Figs 5, 6), the consideration that growth was still in the exponential phase, also indicated by the -values (Table 3), seems fully justified. The concavity of the growth curves is most pronounced in cultivar ‘Grindstad’ (Figs 5 and 6), as indicated by the respective -values (Table 3) which are higher in this cultivar both for leaf area and DM production above-ground, as well as for roots. The superiority of ‘Grindstad’ in growth potential suggested by the individual leaf blade length and width data (Fig. 4) is also evident when considering total leaf area (Fig. 5, left) and even more striking in above-ground DM production (Fig. 5, middle).
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The sensitivity to daylength expressed as the instantaneous growth response per hour photoperiod and per day throughout the experiment is shown in Fig. 6. The difference between cultivars in the shape of the response surfaces is most remarkable for total leaf area (Fig. 6A). The contrast between the broad PP-interval with a relatively moderate response for ‘Engmo’, and the strong response within a narrow PP-interval for ‘Grindstad’ is also evident from the c-values (Table 3) of 0·6 and 1·3, respectively (see also Fig. 1). The shift of the response surface and its ridge towards longer days in ‘Engmo’ as compared with ‘Grindstad’ is reflected in PPc values of 14·7 and 12·6 h, respectively (Table 3). As in Fig. 5, the superiority of ‘Grindstad’ in growth potential is most pronounced in above-ground DM production (Fig. 6B).
In contrast with the above growth reactions, the daylength effect on root DM production was rather similar for the two cultivars. For both, estimated PPc was 9·0 h and the response occurred within a very narrow PP-interval (c = 2·0, Table 3).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSLITERATURE CITED |
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The chosen method of data analysis and presentation of results seems to be useful and effective in providing a precise description and visualization of plant responses over a range of photoperiods. The three parameters of the PPR function (eqn 1) are easily interpretable in terms of plant response pattern, as they indicate sensitivity, the daylength of the maximum sensitivity (PPc), the occurrence of a saturation daylength (d = 0), an optimum daylength (d > 0) or a ‘transition’ daylength (d < 0) beyond which the response decreases or increases, respectively. The function is versatile as an analytical tool since it is valid for qualitative reactions (high c-values) and types of daylength reaction found in SDPs, LDPs, IDPs and even APPSs. A continuous function allows analyses over any range of daylengths and the assessment of a base photoperiod requirement for growth traits, as well as a critical daylength for growth or phenological development. When studying ‘other factors’ (e.g. leaf position or time trends), the PPR term can be included in more comprehensive functions describing the total response (cf. Figs 4 and 6).
In this way it is easy to visualize differences between cultivars or the effects of other factors that may interact with photoperiod (consideration of such ‘other factors’, of which temperature is the one best known, was beyond the scope of the present investigation). Furthermore, the high resolution of the response pattern thus realized may contribute valuable clues to the understanding of individual processes and mechanisms involved. For instance, the effect of long days on leaf elongation has been mainly ascribed to increased cell elongation (Stuckey, 1942; Ryle, 1966a, b; Hay and Heide, 1983; Heide et al., 1985b, Hay, 1990), but stimulation of cell division has also been observed in some pasture grass species (Ryle, 1966a, b; Hay and Heide, 1983; Heide et al., 1985b). The small response of leaves that had already appeared at start of treatment and the stronger one of new leaves along the main tiller axis suggest cell division as an important mechanism of photoperiod response.
The overall positive effect of prolonged photoperiod on leaf growth is in accordance with previous findings (Eagles and Østgård, 1971; Heide, 1982; Hay and Heide, 1983; Heide et al., 1985a, b; Solhaug, 1991). The S-shape of the response curve was to be expected: an area of minimum reaction at short photoperiods followed by an interval with high sensitivity and then at least a more-or-less gradual levelling-off of the curve around the value required for maximal leaf growth. The occurrence of an optimum and a significant negative effect of further photoperiod prolongation on leaf elongation in ‘Grindstad’ (Table 2, Fig. 4) might be related to phenological effects of photoperiod and the difference between the cultivars in this respect. In ‘Grindstad’ in particular, photoperiods greater than 15 h stimulated initiation and advance to generative development involving stem elongation, and a shift in the partitioning of assimilates in favour of stems and at the expense of leaf elongation.
The striking difference in response pattern in above-ground DM as compared with root DM production (Fig. 6B,C) and the relatively small positive effect of daylength extension (Fig. 6A,B) and the short OPP (Table 3) of the latter, imply a strong long-day reaction in top/root ratio. Or, put conversely, short days enhance the root/top ratio by changing the partitioning of assimilates in favour of the roots. This is an advantageous reaction of perennial species in preparation for winter survival by giving preference to root growth and root strengthening in order to withstand physical stresses from soil frost and frost heaving.
The differences in daylength were rather small between the two timothy cultivars at the cardinal points of the photoperiodic response curves, that is at the point of inflection where PP PPc, and at the optimum point where PP = OPP. In PPc-values the difference was less than 0·5 h, and for size of individual main tiller leaves (Table 2) it was a little above 2 h for total leaf area and above-ground DM production (Table 3). This is appreciably less than the differences in maximum (mid-summer) daylengths between the two locations of cultivar origin, 5–6 h (24 h at 69°N, the origin latitude of ‘Engmo’ vs. 18·5 h at 60°N, the origin latitude of ‘Grindstad’). It is suggestive that PPc-values of 12–14 h are the daylengths when approaching the autumn equinox, irrespective of latitude. So, PPc is probably of minor importance when studying plant latitudinal adaptation. When considering OPP, there is a clearer difference between the cultivars, 1·5 h for individual leaf length (Table 2) >3 h for total leaf area (Table 3), but still less than might have been expected.
The overall superiority of the southern cultivar ‘Grindstad’ to the northern one, ‘Engmo’, in DM production (Fig. 6) is explainable at least partly from the differences between the cultivars in rate of phenological development. Compared to ‘Engmo’, ‘Grindstad’ had reached a more advanced generative stage, implying more stem elongation, increased light interception due to an improved leaf canopy structure, and a more efficient DM build-up.
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ACKNOWLEDGEMENTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSLITERATURE CITED |
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The authors wish to thank Professor John Einset, Department of Plant and Environmental Sciences, Agricultural University of Norway, for his contribution towards improving the language in this paper.
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LITERATURE CITED |
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