Variation of Specific Leaf Area for Sugar Beet Depending on Sowing Dateand Irrigation

M. RINALDI

Istituto Sperimentale Agronomico, Via C. Ulpiani 5, 70125 Bari, Italy. Tel.: +39 080 5475016; Fax: +39 0805475023; E-mail: michele_rinaldi@libero.it

Received: 9 September 2002. Accepted: 21 February 2003.

Ital. J. Agron., 7, 1, 23-32

ABSTRACT

BACKGROUND. Specific Leaf Area (SLA) is a growthparameter that relates leaf area to dry matter accu-mulation. The aim of this work was to analyse theSLA variation during the crop cycle of sugar beet(Beta vulgaris var. saccharifera L.) depending onsowing time and irrigation treatment.METHOD. In a 4-year experiment in a southern Ital-ian environment (Capitanata plain, Foggia), sugarbeet was planted in spring (2 out of 4 years) or au-tumn and given different irrigation regimes: Optimal(100% real evapotranspiration, ETc) and Reduced(60% ETc). Growth analysis (green leaf area, weight,number and size, dry matter of roots, leaves andstems) was performed with a destructive method.RESULTS. The beet SLA variations are expressed main-ly in dry matter accumulation, lower in the spring (short-er crop cycle) than in the autumnal crop, with a highernumber of green leaves in spring. Seasonal average val-ues of SLA were 16.7 and 15.1 m2 kg-1 for spring andautumn sowing, respectively. There was a significant dif-ference between irrigation regimes (16.2 vs. 15.6 m2 kg-1

for optimal and reduced irrigation treatments). No dif-ference was observed for “Sample” effect.CONCLUSIONS. These SLA values can be used in thesimulation of sugar beet growth, in autumn andspring sowing and in optimal and sub-optimal irriga-tion conditions.

Key-words: specific leaf area, Beta vulgaris var. sac-charifera L., leaf area, model.

INTRODUCTION

Specific leaf area (SLA) represents the meanleaf area per unit of leaf weight, or in otherwords it measures leaf density or relative thick-ness (Hunt, 1982). Being influenced by envi-ronment and growth stages, it is a useful toolfor characterising the development of photo-synthetic apparatus of crop plants. Several stud-

ies on different plant types have shown thatcanopy SLA is also closely related to canopyleaf nitrogen content and photosynthetic capac-ity (Pierce et al., 1994). Hughes and Evans(1962) observed that deep shade caused in-creases in SLA. Evans (1989) observed thatSLA was negatively correlated with irradianceand CO2 concentration and positively with tem-perature. Evans and Porter (2001), from theirexperiments on a range of species, observed thatplants acclimate to low-light environment by in-creasing SLA: the importance of SLA in max-imising carbon gain per unit leaf mass wasgreater than the effect of reallocating nitrogenbetween leaf pools, especially under low light.In free-air CO2 experiments (Kimball et al.,2002), any storage of extra carbohydrate in theleaves or any reallocation of biomass to thick-er leaves increased leaf mass more than leafarea. SLA decreased from 7 to 14% in ryegrass,17% in potato, 5% in grape and, in general,more in C3 than C4 crops. Chernyad’ev II(2001) found that at an early stage of ontogeny(up to 50-60% of the maximum LAI) of sever-al crops, sugar beet included, changes in SLAare related to photosynthetic CO2, Rubisco en-zyme activity, concentration of chlorophyll aand b, carotenoids and soluble leaf protein.Several assumptions have been used for model-ling SLA. It can be considered as constantthroughout the growth cycle and within thecanopy (e.g. van Keulen et al., 1982), or chang-ing with the development stage of the crop (e.g.Wilkerson et al., 1983). In both cases, leaf areaexpansion is calculated by multiplying the in-crease in leaf dry weight by SLA. Thus, dailychanges in leaf area and dry weight are consid-ered as strictly proportional. In the SUCROS(Simple and Universal CROp growth Simula-tor) model (van Keulen et al., 1982; Spitters et

al., 1989) SLA is important either to set initialgrowth conditions or to drive leaf area index de-velopment. From the initial SLA (the authorssuggest a value of 22 m2 kg-1 for sugar beet) theinitial amounts of dry matter in leaves are cal-culated. SLA drives leaf area development inthe maturation stage, when leaf area expansionrate is restricted only by exponential and linearassimilate supply. During this stage (leaf area in-dex > 0.75 and development stage > 0.3), themodel calculates the growth of leaf area by mul-tiplying the simulated increase in leaf weight bythe SLA of new leaves. In the WOFOST model(van Diepen et al., 1989), similar to the SUCROSmodel, the authors modified the calculation ofgreen area in the maturation stage. In fact, theSLA of a crop can differ depending on the de-velopment stage and this model allows a curve tobe introduced describing the SLA in up to 15points as a function of development stage. In theCropSyst (Cropping Systems, Stöckle et al., 2003)model, SLA is used to determine the amount ofgreen area index produced in a day, together withthe leaf area expansion-related biomass producedin a given day and the accumulated quantity un-til that day. Values of SLA usually range between15 and 25 m2 kg-1, but the authors suggest de-termining it empirically.The aim of this paper was to analyse the evo-lution of leaf traits (leaf area, leaf biomass andSLA) in sugar beet. Variations in sowing timeand irrigation were used to widen the environ-mental range. Appropriate values of SLA wereobtained for modelling purposes.

MATERIALS AND METHODS

The field experiments were carried out at Fog-gia (41 °N, 3 °E, 90 m a.s.l.), in Southern Italyduring the 1999-2002 seasons. The soil is a ver-

tisol of alluvial origin (Typic Chromoxerert, fine,thermic, according to Soil Taxonomy-USDA),silty-clay with the following characteristics: or-ganic matter 2.1%; total N 0.122%; NaHCO3-extractable P 41 ppm; NH4O Ac-extractableK2O 1598 ppm; pH (water) 8.3; field capacity0.396 m3 m-3; permanent wilting point 0.195 m3 m-3.The climate is “accentuated thermomediter-ranean” (Unesco-FAO classification), with tem-peratures which may fall below 0 °C in winterand rise above 40 °C in summer. Annual rain-fall (avg. 550 mm year-1) is unevenly distributedthroughout the year, being mostly concentratedduring the winter months and “class A” evapo-ration can also exceed 10 mm d-1 in summer.The experiments were carried out with spring-sown (1999 and 2000, labelled as SP99 andSP00) and autumn-sown (2001 and 2002, AU01and AU02) sugar beet. Two irrigation treat-ments, Optimal (OPT) and Reduced (RED),distributed, except for the first two irrigations,different amounts of water: more regular andabundant (100% of real evapotranspiration,ETc) in the OPT, with a partial (60%) recoveryof ETc in the RED treatment (Table 1). Plantswere thinned to 8 plants per m2; further detailsof the experiments are reported in Table 2. Theexperimental design was a randomised completeblock with 3 replicates and main plots of 240 m2

(12 m x 20 m). Cumulated total dry matter, sep-arated in roots, stems, green and dead leaves,was periodically measured (every 2-4 weeks) byrandomly taking four 1 m2 samples from eachmain plot. Green leaf area index (GLAI) wasmeasured using a Delta-T Device area meterand the number of green leaves with a laminalength greater than 6 cm was also recorded.Specific Leaf Area (SLA) was calculated, foreach sample, according to the ratio:

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Table 1. Water balance components in the four sugar beet experiments. The irrigation treatments are optimal (OPT, 100%of ETc) and reduced (RED, 60% of ETc).

1999 Spring 2000 Spring 2001 Autumn 2002 Autumn

OPT RED OPT RED OPT RED OPT RED

Irrigation number (n) 227 225 211 211 227 227 228 228Irrigation amount (mm) 434 298 560 364 360 248 346 232Rainfall (mm) 204 204 119 119 342 342 442 442Soil moisture variation (mm, in 0-60 cm depth) 247 239 288 286 236 235 -115 -103ETc (mm) 685 541 765 571 738 625 673 571ETo (Penman-Monteith) (mm) 828 828 866 866 825 825 787 787Average ETc/ETo 0.83 0.65 0.88 0.66 0.89 0.76 0.85 0.72

Leaf area (m2 of green leaves m-2 of soil)

SLA = ___________________________________Leaf dry weight (kg of green leaves

dry matter m-2 of soil)

and the unit is m2 kg-1.This incremental method assumes that the SLAof existing leaves remains unchanged, assessingthe plant’s canopy at each sampling as old, in-termediate and new leaves.Soil moisture was determined periodically at 0-60 cm depth with the gravimetric method andexpressed in m3 m-3. Daily evapotranspirationwas estimated for irrigation scheduling using thePenman-Monteith model and correcting the val-ue using sugar beet crop coefficients (Dooren-bos and Pruitt, 1977). Irrigation started when ac-cumulated values of soil moisture deficitreached 60 mm. A seasonal value of ETc wasestimated by the mass balance method, whichignores runoff, drainage and capillary arise.Growing degree-days (GDD) were calculateddaily and cumulated from sowing date using abase temperature of +2 °C.Daily weather data – temperature, humidity,rainfall, wind speed and solar radiation – werecollected at the weather station of the experi-mental farm.Analysis of variance was done, using a fixedmodel, with replication within samples as nest-ed effect (Steel and Torrie, 1980). A statisticalanalysis by experiment and by sample was thenperformed to identify the differences betweenthe two irrigation regimes for each sampling.

RESULTS AND DISCUSSION

Seasonal trends of daily average temperature vs.long-term (LT) values are reported in Figure 1.

Specific Leaf Area in Sugar Beet 25

Table 2. Sugar beet cropping data.

1999 Spring 2000 Spring 2001 Autumn 2002 Autumn

Cultivar Puma Azzurro Suprema SupremaPlanting date (DOY) 62 82 292 304Emergence date 102 103 308 323Full cover date 163 175 98 120Harvest date 243 241 204 213Nitrogen fertilisationDate 133 161 341 + 25 66Fertiliser Ammonium nitrate Ammonium nitrate Urea + Ammonium nitrate Ammonium nitrateAmount (kg ha-1 of N) 100 75 46 + 50 50

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Figure 1. Average air temperature (thin line) during the th-ree experiments, starting, respectively, on 3rd March 1999,22nd March 2000, 18th October 2000 and 29th October 2001,compared with long-term (1953-1997) average values (thickline).

With the exception of AU02 experiment (a pe-riod of low temperatures with minimums above0 °C during the 40-80 days after sowing), theother three years were warmer than the LT and,in particular, a period of 3 weeks with temper-atures about 8 °C above LT in SP99 and a warmperiod at the end of winter in AU01. During thiswarm period (January-March) in AU01, a severeaphid (Aphis fabae) attack occurred; this wasnot easily controlled, even after a double spray-ing with Azinphos methyl.A comparison between water supply (rainfall+ irrigation) in both irrigation treatments vs.potential evapotranspiration (ETo) and LT cu-mulated rainfall is shown in Figure 2. TheAU02 experiment resulted as the best wateredone, either for OPT or RED treatment, withETo completely covered by water supply, alsobecause the weather conditions (cool) reducedthe ETo values. Apart from the last irrigation,in the two autumnal sowing times, both irri-gation regimes proved to be equally effectivein sustaining crop water requirements. Con-versely, irrigation was inadequate to coverplant water needs in SP00 and particularly inSP99.

Green leaf weight (GLW)Table 3 shows the results of analysis of variance.For GLW a significant effect of “Sample”emerged, with lower values in the samples at thebeginning and end of the crop cycle and high-er in the samples at maximum leaf expansionand canopy growth. The other significant effectwas “Irrigation”, with an average GLW of 166vs. 131 g m-2 in the OPT and RED treatments,respectively.GLW resulted as about the same in AU01 andSP00, with maximum values of 300 and 250 g m-2,respectively, for OPT and RED treatments (Fig-ure 3). In SP99 the maximum GLW was slight-ly lower than in the other experiments, whilethe highest GLW value was obtained in AU02.The maximum GLW was reached after 1500-2000 GDD on average, with a delay of REDtreatment only in SP99.The results of ANOVA carried out by experi-ment and by sample, showed a significant supe-riority of OPT in the 1st, 5th and 7th samples inSP99 and the 4th in SP00. These results are ex-plained by the drier conditions of SP99 than theother 3 experiments.

Green leaf area index (GLAI) GLAI in sugar beet resulted as significantlyhigher in OPT than RED irrigation treatmentsin agreement with GLW (Table 3). In the 4 ex-periments the OPT treatment, resulted as supe-rior in 5 out of 8 samples in SP99, 2 out of 7 inSP00 and 2 out of 8 in AU01 (Figure 4) The

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Figure 2. Cumulated values of daily potential evapotranspi-ration estimated with the Penman-Monteith model (a), ir-rigation supplies (rainfall + irrigation) in the two irrigationtreatments (b = OPT, c = RED) and long-term (1953-1997)cumulated rainfall (d) in the four experiments.

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Specific Leaf Area in Sugar Beet 27

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Figure 3. Sugar beet dry matter weight of green leaves (GLW) in the four experiments (� = OPT and � = RED irriga-tion treatments). Vertical bars represent standard deviations of each average value (n = 4). In this and in the following fi-gures the symbols �, �, and �, represent, on the sampling date, a significant effect of irrigation regime at 0.05, 0.01 and0.001 P level, respectively.

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Figure 4. Green Leaf Area Index (GLAI) of sugar beet in the four experiments; symbols as in Figure 3.

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well watered conditions in AU02 is the reasonfor this response, For this variable the “Year”effect resulted as significant, showing some fieldexperiment variability mainly for the two yearsof autumnal sugar beet: this was extremely lowin AU01 and high in AU02 (4.0 vs. 7.0, respec-tively).

Green leaf number The number of green leaves per plant reachedthe maximum value (40) in the OPT treatmentof SP99 (Figure 5). A curvilinear behaviour isusually expected, with an increasing number un-til maximum GLAI. The two sowing times re-sulted as different, with a higher average num-ber of green leaves per plant in SP (22.5) thanin AU (18.5).In the SP99 experiment, the OPT irrigated cropmaintained a large number of green leaves inthe second part of the growing season, while inthe RED irrigated crop, green leaves droppedabout 30 days before harvest. In AU01 a sig-nificant superiority of OPT emerged constantly

throughout the crop cycle, while in the othertwo experiments the number of leaves was morevariable and did not diverge between the twotreatments. The aphid outbreak in AU01 nega-tively influenced the emission and expansion ofnew leaves in the first five samples, with an av-erage green leaf number less than in AU02 (16.7vs. 19.7).A not significant effect of “Sample” means thatthe green leaf number was more or less con-stant in the sampling period (from 10 to 35leaves per plant).

Green leaf size A difference in leaf size was noticed for “Sam-ple”, “Year” and “Irrigation” effects. No signif-icant difference resulted between spring and au-tumn sowing times. A similar behaviour in SP99and AU01 with respect to SP00 and AU02 wasobserved, in relation to different sowing timeand season (Figure 6). In general, leaf size in-creased until time of maximum GLAI and de-creased with the end of the crop cycle, by the

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Figure 5. Number of green leaves per plant, with a lamina length greater than 6 cm, in the four experiments; symbols asin Figure 3.

senescence of the largest leaves and emission ofnew leaves. In SP99 there was a significant dif-ference between OPT and RED in the 1st, 6th

and 8th samples, in accordance with the GLAIresults. Also in SP00 the samples when irriga-tion treatments were significant were the sameas the GLAI variable (3rd and 4th). The effect ofwater supply in this environment is more im-portant in spring than autumn sowing and it in-

fluences crop canopy mainly in leaf size, leafnumber per plant and, consequently, leaf areaindex.

Specific leaf areaThe “Sample” effect did not result as significantwith analysis of variance: this means that an av-erage seasonal value of SLA can be used in cropmodels, without a great source of error in thesimulation (Table 3).

Specific Leaf Area in Sugar Beet 29

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Figure 6. Sugar beet individual green leaf size, in the four experiments; symbols as in Figure 3.

Table 3. ANOVA table. *, ** and ***: significant, respectively at 0.05, 0.01 and 0.001 probability level. n.s. = not signifi-cant.

Sources of variation DF Green Leaf Green Leaf Number of Leaf size Specific Leaf Weight Area Index green leaves Area

Sample (S) 227 ** ** n.s. ** n.s.Year (Y) 221 n.s. * n.s. *** n.s.E1 226Sowing Time (ST) 221 n.s. n.s. * n.s. *Y × ST 221 n.s. n.s. n.s. n.s. **E2 213Irrigation (I) 221 *** *** * *** *Y × I 221 n.s. n.s. n.s. n.s. n.s.E3 213ST × I 221 n.s. n.s. n.s. n.s. n.s.Y × ST × I 221 n.s. n.s. n.s. n.s. n.s.E4 213Total 211

There is also a difference between sowing times,with SLA values in the autumn being lowerthan in spring sugar beet (seasonal average 15.1vs. 16.7 m2 kg-1, Table 4).A significant “Year × Sowing time” interactionresulted and a variable response of this para-meter can be observed. In particular, the AU01experiment showed the lowest seasonal SLAvalue, significantly different in SP99 and AU02.This is explained mainly by a low GLAI in theAU01 experiment (Table 4), due to the low leafemission and expansion rate in the sugar beetplants attacked by aphids. Furthermore, a larg-er fraction of entirely expanded and old leaves(heavy and thick) was noticed than in AU02.An important difference between autumnal andspring sown sugar beet is in crop cycle length(on average 277 vs. 170 days) even if this dif-

ference is less if crop cycle is expressed in termsof GDD (3440 vs. 3280 °C d, with Tb = + 2 °C).This influenced leaf area duration, which con-sequently affected intercepted radiation andleaf dry matter accumulation. In fact, only thenumber of the leaves resulted as different inspring and autumn sown crops (Figure 5). Thehigher values of SLA in the spring crop cantherefore be explained by different dynamics inthe formation of new green leaves (faster) anda shorter photosynthetic activity period. The lowtemperatures during winter slowed the emissionof new leaves. In addition, spring sown leaveswere photosynthetically more active than theautumnal ones because of the higher radiationregime.Throughout the crop cycle (Figure 7) a light de-crease of SLA in the spring sowing can be ob-

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Table 4. Seasonal averages of Specific Leaf Area (m2 kg-1) in sugar beet. The letters indicate a significant difference betweenthe two treatments (column) and the four experiments (row) at P > 0.05 level (SNK test).

Irrigation treatment 1999 Spring 2000 Spring 2001 Autumn 2002 Autumn Average

Optimal 18.43 A 15.85 13.30 17.32 16.23 AReduced 17.01 B 15.60 12.97 16.72 15.58 BAverage 17.72 A 15.72 AB 13.13 B 17.02 A 15.91

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Figure 7. Specific Leaf Area (SLA) of sugar beet in the four experiments; symbols as in Figure 3.

served. This decline can be attributed to an ef-fect of leaf shading (normally, a sugar beet planthas 10 to 30 active green leaves) during the sum-mer and, at the same time, a loss of cell turgordue to leaf senescence and water stress.No important difference in SLA has been ob-served between the two irrigation treatments.

CONCLUSIONS

The aim of this research was to analyse leafgrowth dynamics and SLA variations in sugarbeet, cropped in Southern Italy with two dif-ferent sowing times and two irrigation regimes.All the examined variables resulted as beingvery sensitive to irrigation treatment, in bothspring and autumnal sowing.The results indicated a higher SLA seasonal av-erage value in spring than in autumnal sowing(16.7 vs. 15.1 m2 kg-1). The higher SLA in thespring sowing was due mainly to a larger num-ber of green leaves, leaves with a higher per-centage of dry matter content than the autumnone.Significant differences were found between irri-gation treatments, showing a strong dependenceof leaf development dynamics on water avail-ability.The use of a fixed value of SLA throughout thecrop cycle, taking into account the lack of dif-ference between samples, can guarantee a goodaccuracy in crop modelling.

REFERENCES

Chernyad’ev II, 2001. The specific density of a leaf as acharacteristic of the photosyntetic apparatus. Appl.Biochem. Microbiol., 37, 400-405.

Doorenbos J., Pruitt W.O., 1977. Guidelines for predict-ing crop water requirements. FAO, Rome, Irr. and Drain.Paper no. 24 (rev), 144 pp.

Evans J.R., 1989. Photosynthesis and nitrogen relation-ships in leaves of C-3 plants. Oecologia, 1, 9-19.

Evans J.R., Porter H., 2001. Photosynthetic acclimationof plants to growth irradiance: the relative importanceof specific leaf area and nitrogen partitioning in maxi-mizing carbon gain. Plant Cell Environ., 24, 755-767.

Hughes A.P., Evans G.C., 1962. Plant growth and the aer-ial environment. II. Effects of light intensity on Impa-tiens parviflora. New Phytol., 61, 367-388.

Hunt R., 1982. Plant growth curves. Edward Arnold,London, 248 pp.

Kimball B.A., Kobayashi K., Bindi M., 2002. Responsesof agricultural crops to free-air CO2 enrichment. Adv.Agron., 77, 293-368.

Pierce L.L., Running S.W., Walker J., 1994. Regional-scale relationships of leaf-area index to specific leaf-areaand leaf nitrogen-content. Ecol. Applic., 4, 313-321.

Spitters C.J.T., van Keulen H., van Kraalingen D.W.G.,1989. A simple and universal crop growth simulator: SU-CROS87. In: Rabbinge R., Ward S.A., van Laar H.H.(eds.): Simulation and Systems Management in CropProtection. Simulation Monographs 32, PUDOC, Wa-geningen, The Netherlands, 434 pp.

Steel R.G.D., Torrie J.H., 1980. Principles and proceduresof statistics. McGraw Hill, 2nd ed., 633 pp.

Stöckle C., Donatelli M., Nelson R., 2003. CropSyst: acropping system simulation model. Eur. J. Agron., 18,289-307.

van Diepen C.A., Wolf J., van Keulen H., Rappoldt C.,1989. WOFOST – A simulation-model of crop produc-tion. Soil Use Manag., 5, 16-24.

van Keulen H., Penning de Vries F.W.T., Drees E.M.,1982. A summary model for crop growth. In: Penning deVries F.W.T., van Laar H.H. (eds.): Simulation of plantgrowth and crop production. Simulation MonographsPUDOC, Wageningen, The Netherlands, 308 pp.

Wilkerson G.G., Jones J.W., Boote K.J., Ingram K.T.,Mishoe J.W., 1983. Modeling soybean growth for cropmanagement. Trans. ASAE, 26, 63-73.

Specific Leaf Area in Sugar Beet 31

VARIAZIONI DELLO “SPECIFIC LEAF AREA” IN BARBABIETOLA DA ZUCCHERO INFUNZIONE DELL’EPOCA DI SEMINA E DEL REGIME IRRIGUO

SCOPO. Lo “Specific Leaf Area” (SLA) è un parametro di crescita che lega area fogliare e sostanza secca accumu-lata nelle foglie. Scopo del lavoro è analizzare le variazioni dello SLA nel corso del ciclo colturale di barbabietolada zucchero (Beta vulgaris var. saccharifera L.) in funzione dell’epoca di semina e del trattamento irriguo.METODO. Un esperimento durato 4 anni, in due dei quali la barbabietola è stata seminata a fine inverno e negli al-tri due in autunno, è stato condotto a Foggia (Capitanata). La coltura è stata sottoposta a due diversi regimi irrigui:Ottimale (100% dell’ETc) e Ridotto (60%). L’analisi di accrescimento è stata condotta con il metodo distruttivo.RISULTATI. Dall’analisi del peso secco delle foglie verdi, del numero, della dimensione e dall’andamento temporaledel LAI, lo SLA è risultato dipendente principalmente dalla minore sostanza secca accumulata, nella primaverile econ un ciclo più breve rispetto alla autunnale e da un maggiore numero di foglie verdi. I valori medi stagionali so-no risultati di 16,7 e 15,1 m2 kg-1, rispettivamente per la primaverile e l’autunnale. Nessuna differenza significativaè emersa tra i campionamenti nel corso dei cicli colturali. Differenze significative sono emerse tra i due trattamentiirrigui (16,2 e 15,6 m2 kg-1, per i regimi irrigui ottimale e ridotto).CONCLUSIONI. Questi valori di SLA possono essere utilizzati per la simulazione della coltura di barbabietola da zuc-chero, sia coltivata in semina primaverile che autunnale e sia in condizioni di rifornimento irriguo ottimale che sub-ottimale.

Parole chiave: specific leaf area, Beta vulgaris var. saccharifera L., area fogliare, modello.

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