sugarcane: physiology, biochemistry, and functional biology (moore/sugarcane) || sugarcane yields...

Chapter 21

Sugarcane Yields and Yield-LimitingProcesses

Geoff Inman-Bamber

SUMMARY

A synopsis of yield-building and yield-limitingprocesses of sugarcane is timely given the diffi-culty facing many sugarcane industries in improv-ing cane yields and sucrose % cane. Average caneyields in some countries appear to be approachinga ceiling of about 90 t ha−1 and sucrose content(SC) has been static in many countries for 20 yearsor more.

Biomass and sucrose yields accumulate with thedevelopment of the leaf canopy, which progres-sively intercepts increasing amounts of radiationthat is used in photosynthesis to produce sucrose,which, in turn, is then translocated to varioussinks in the plant. The sugarcane canopy devel-ops slowly compared to annual crops such as maizeand sorghum. Delayed sugarcane canopy develop-ment is due to a slow rate of leaf production and aslow rate of tillering. The daily mean temperaturebelow which leaves stop elongating and emergingis about 10◦C, whereas tillering ceases at a highertemperature of about 16◦C. Both tillering and leafextension respond proportionally to temperaturesabove these lower limits.

Cell enlargement and leaf and culm expan-sion are highly dependent on plant water rela-tions. Culm elongation is more sensitive to waterstress than is leaf elongation. Combined leaf andculm extension can slow when leaf water poten-tial (�L) declines below –0.2 MPa and can ceasewhen �L declines below –1.0 MPa. The leaf and

culm extension rate of clones with a high SC aremore restricted by the imposition of water stressand reduced temperatures than are clones withlow SC. Differences among clones in sensitivityto abiotic environmental stresses may account tosome extent for the differences in the concentra-tion of sucrose among clones, because decreasedcell expansion would require less of the photoas-similate for cell wall synthesis and thus allow ahigher fraction of the photoassimilate to accumu-late as sucrose in the culm.

Despite its slow rate of canopy development,the long crop cycle of sugarcane makes it highlyefficient in intercepting annual radiation com-pared to other crops. Rates of photosynthesis perunit leaf area for individual leaves are greater forsugarcane than for Zea and Sorghum spp. Maxi-mum photosynthesis of single leaves is reportedlyin the 30–50 �mol m−2 s−1 range, whereas pho-tosynthesis of whole plants is considerably lowerthan this rate.

Radiation-use efficiency can be as high as 2 gMJ−1 but the average in experimental plots is onlyabout 1.44 g MJ−1 because of a developmentalslowdown, now called the reduced growth phe-nomenon (RGP), which appears to start after 30to 50 t biomass ha−1 has accumulated. Factorsincluding lodging, feedback on photosynthesis bysucrose accumulating in the culm, and respirationof sucrose could be responsible for the RGP.

The high efficiencies of radiation captureand use in sugarcane are not matched by high

Sugarcane: Physiology, Biochemistry, and Functional Biology, First Edition. Edited by Paul H. Moore and Frederik C. Botha.

C© 2014 John Wiley & Sons, Inc. Published 2014 by John Wiley & Sons, Inc.

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580 Sugarcane: Physiology, Biochemistry, and Functional Biology

efficiencies in the allocation of biomass to sucrose(only 30 to 40%). In commercial cultivars, thefraction of aboveground biomass in the culm is0.66 to 0.80 and up to 50% of that can be sucrose.

Although breeders and physiologist may be ableto make incremental gains in the large number ofsteps required to build biomass and sucrose yield,the growing community has a better opportunityto increase yields by crop management changestoward achieving the yield potential already builtinto the plant through many years of breedingand selection. Significant yield gains with existingcultivars should be possible since in at least onestudy only 53 to 69% of the potential was achieved.One way to direct crop management changes is touse growth models to estimate target yields thatcould be achieved with given radiation, tempera-ture, rainfall, and irrigation regimes and then towork with growers to identify fields that are under-performing to correct possible limiting factors.

INTRODUCTION

Records of average cane and sugar yields (Anony-mous 2009) indicate that cane yields generallyincreased over the last 23 years, but that sucrosecontent (SC) has been rather static (Fig. 21.1).Year-to-year variations in yields make it difficultto assess whether increases in yields are due to

plant improvement (breeding), improvements inmanagement, or simply generally more favorableclimatic conditions. Trends in cane yield over timewere significant (P<0.05) for Brazil, India, Mex-ico, and Thailand, but not for Australia and SouthAfrica. Trends in sugar extracted from cane, i.e.,sugar as a percent of the fresh weight of cane (sugar% cane), were significant only for Thailand andMexico, but these were from a low base comparedto other countries, indicating greater potential forimprovement. Genetic improvement in SC couldbe responsible for the increases in Thailand andMexico, but there are many other factors suchas improved transport and factory extraction pro-cesses that could also contribute to the increasesin sugar % cane.

These data are consistent with the observationby Jackson (2005) that sugarcane improvement forSC (commercial cane sugar [CCS] in Australia)has now stagnated. Garside et al. (1997) suggestedthat the sugar yield plateau in Australia (1970 to1990) may be because of the expansion of theindustry into more marginal land, the introductionof heavy chopper harvesters that can lead to soilcompaction, and the poorly defined crop malaisecommonly called yield decline. Subsequent workby these authors strongly implicated soil com-paction and monocropping in constraining caneyields in the Australian sugar industry (Garsideet al. 2009).

1985 1990 1995 2000 2005 201030

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Fig. 21.1. Average cane yield and raw sugar % cane for Australia (O, —··—), Brazil (X, —·—), India (+,— —), Mexico (� ,–·–),South Africa (�,– –), and Thailand (�,· · · ·). From Anonymous (2009).

Sugarcane Yields and Yield-Limiting Processes 581

The lack of sugar and cane yield increasesobserved in the recent records of many coun-tries does not necessarily indicate that geneticgains are not being made. Cox and Stringer (2007)attempted to measure genetic gains in cane andsucrose yield against an environment believed tobe contributing to yield decline in terms of theabove-mentioned factors, notably monoculture,machine harvesting, and expansion into marginalareas. They used statistical methods to estimatethat these factors reduced sucrose yield by about118 kg sugar ha−1 yr−1 since 1980. This decreasewas offset by productivity gains of about 166 kgha−1 yr−1, due to improved varieties and improvedagronomic practices. Genetic gains were estimatedto be 1470 kg cane and 245 kg sucrose per hectareand 0.033 units of CCS (SC) per annum from 1980to 2004.

The outline for this chapter is based on theconcepts of yield building used in most mod-els of sugarcane and other crop production sys-tems (see Chapter 20). This concept involvesthe development of the leaf canopy that progres-sively intercepts increasing amounts of photo-synthetically active radiation (PAR). This radia-tion is used in photosynthesis to produce sucrose,which is translocated to various sinks in the plant.Aboveground biomass produced in relation tothe amount of radiation intercepted is termedradiation-use efficiency (RUE in g MJ−1), andthe ratio of commercial product in the biomassis termed the harvest index (HI). The develop-ment of yield in these terms is summarized in thefollowing three equations:

Fi = 1 − (exp(−k.LAI)) (21.1)

B = PAR.Fi.RUE (21.2)

Y = B.HI (21.3)

where Fi is the fraction of incident PAR inter-cepted by leaves; LAI is leaf area index definedas the area of one side of all green leaves attachedto all plants rooted in one square meter of groundand is a measure of the size or area of the greenleaf canopy; k is the extinction coefficient as inthe Beer-Lambert law, governing the transmis-sion of light through a suspension of solids; B is

aboveground biomass (g m−2); HI is the fractionof commercial product in the biomass and Y is theyield of the commercial product, sucrose in thiscase.

Sucrose stored in the cane culm continues to bethe most important commercial product from sug-arcane, but fiber and reducing sugars are becomingmore important as interest in bioenergy increases.Total aboveground biomass, including dead andgreen leaves, is being valued more for this reason,and crop residue (trash) also has many benefits forsoil and water conservation, for weed control, andfor improving the organic and nutrient content ofthe soil. While the above-mentioned model will beuseful for analyzing the interaction of the canopy(Fi), RUE, and partitioning (HI) components ofyield, it assumes that photosynthesis is the mainlimiting factor, rather than the capacity of the plantto use photoassimilate. Put another way, the modelassumes that source, rather than sink, is limiting.This assumption is prevalent in most crop modelsin use today because the role of sink limitationsis not well understood. However, sink limitationswill be considered where there is some evidencefor them, even if the exact mechanism for limitingyield is not known.

CANOPY DEVELOPMENT (LAI)

Sugarcane grows slowly during the early part of itsgrowth period when compared with major graincrops such as maize and sorghum (Allison et al.2007). Canopy closure, defined as the stage ofdevelopment when 70% of PAR is interceptedby leaves, took as long as 214 days for cultivarN12 ratooned in April (autumn) in South Africa(Inman-Bamber 1994). N12 is known as a particu-larly slow developer suited to long cropping cycles(Inman-Bamber 1985). However, even NCo376,which develops more rapidly, required 165 daysfor canopy closure when ratooned in April, butdevelopment was much more rapid (65 days) whenratooned in February (summer)(Inman-Bamber1994).

Irrigation requirement depends to a large extenton the rate of canopy development, and a compre-hensive comparison of these rates can be found


in Allen et al. (1998) commonly referred to as TheFAO56 Irrigation Manual. According to this man-ual, full canopy development takes 55 to 80 daysfor maize grown for grain, 95 to 180 days for plantcane, and 80 to 140 days for ratoon cane (Allenet al. 1998).

Canopy development in Pennisetum pupureum(Napier grass) and sugarcane was compared byAllison et al. (2007). The two main differencesbetween these crops were in the rate of leaf pro-duction and the rate of tillering. The time andtemperature conditions occurring between theappearance of two successive leaves is termed thephyllochron and is measured in heat units or ther-mal time (◦Cd) defined as the sum of daily effec-tive temperatures (Tmean–Tbase, where Tmeanis the daily mean air temperature and Tbase is thedaily mean temperature below which the processunder consideration ceases). Sugarcane required120◦Cd (Tbase = 12◦C) for the emergence of eachleaf, whereas Napier grass required only 44◦Cd.Tillering began sooner in Napier grass and tillernumber reached a maximum 800◦Cd after plant-ing; it took 1100◦Cd for this to occur in sugarcane(Allison et al. 2007).

Leaf appearance rate

The daily mean temperature below which leaveswould stop elongating (Tbase) and therefore ceaseto emerge was 10◦C for the two varieties NCo376and N12 (Inman-Bamber 1994). Tbase was sim-ilar for Canal Point (Florida) cultivars: 11◦C forCP80-1743, 10.5◦C for CP88-1762, and 10◦C forCP72-2086 and CP89-2143 (Sinclair et al. 2004).Because Tbase is a mean of temperatures that nor-mally varies through the day, leaf extension willoccur at temperatures lower than the daily meanTbase unless normal diurnal variation is elimi-nated. When Q117 and Q138 were grown at fourconstant temperature regimes in a controlled envi-ronment facility, Tbase was 7.8◦C for Q117 and7.6◦C for Q138 (Campbell et al. 1998). Bonnett(1998) used Tbase = 8◦C from the constant tem-perature work of Campbell et al. (1998), and Sin-gels et al. (2005) used Tbase = 10◦C from thework of Inman-Bamber (1994). Tbase may varybetween genotypes, as seems to be the case in

the work of Liu et al. (1998). However, the mini-mum temperatures they reported were well above10◦C and possibly leading to Tbase ∼17◦C and∼20◦C for Q138 and Q141, respectively. If Tbaseis expressed as the daily mean for a typical range ofdiurnal temperatures, then a value of about 10◦Cis probably appropriate for many cultivars, as wasconcluded by Sinclair et al. (2004).

With Tbase = 10◦C, the phyllochrons forNCo376 and N12 increased after leaf 14 appearedso that subsequent leaves emerged less fre-quently in terms of thermal time. Up to leaf14, the phyllochrons were 109◦Cd and 118◦Cdfor NCo376 and N12, respectively, and 169◦Cdand 200◦Cd thereafter. A change in physiologi-cal phases implied by the biphasic model used byInman-Bamber (1994) was challenged by Bonnett(1998), who found that a power function explainedhis leaf appearance data best. The initial rapidappearance of leaves was due to the short distancethat leaves needed to travel through the sheathsof older leaves. Sheath length increased for thefirst 10 leaves and was then similar for subsequentleaves, so that the frequency of leaf appearancerelative to thermal time decreased rapidly for thefirst 10 leaves and less rapidly thereafter (Bon-nett 1998). Significant varietal differences wereevident with phyllochrons longer for Q141 andQ138 than the other varieties in the experiment(Fig. 21.2). The progressively longer phyllochronsderived from the power function used by Bonnett(1998) would result in progressively larger leaves,and as we will see later, this does occur up to a

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Fig. 21.2. Phyllochron with Tbase = 8◦C for successiveleaves on plants of nine sugarcane varieties. From Bonnett(1998).


point, but not beyond leaf 30. A linear function(constant phyllochron, Fig. 21.2) would best beused after leaf 30 and this seems to be consistentwith Bonnett’s data.

The phyllochrons determined by Inman-Bamber (1994), Bonnett (1998), and Allison et al.(2007) were of similar magnitude (while using dif-ferent base temperatures) and were much greaterthan for Napier grass (44◦Cd) and maize (27◦Cdto 35◦Cd, Tbase = 8◦C) (Birch et al. 1989).

Leaf area and culm expansion

In terms of Equations 21.1 to 21.3, culm elongationis relevant only through its influence on k, theradiation extinction coefficient, although in thecrop model APSIM, this is not acknowledged. Inthe crop model Canegro, k increases from 0.58 to0.85 between leaves 1 and 20 to acknowledge therole of culm length in reducing mutual shading ofleaves. This is because the horizontal distributionof sugarcane leaves becomes more uniform whenculms begin to elongate (Inman-Bamber 1991).

Culm elongation is obviously an importantcomponent of yield development in terms of caneyield expressed on a fresh mass basis. Fresh massof cane is the primary measure of yield in mostsugar industries worldwide, even though only thedry components are of commercial interest. More-over, cane yield is an important factor in the eco-nomics and efficiency of transport and milling pro-cesses, so culm expansion will be considered alongwith leaf expansion at this point. Culm volumemay also be important when high concentrationsof sucrose develop later in the growth process. Inthis case the storage capacity may become a limita-tion for photosynthesis, which is then sink limitedas inferred by the work of McCormick et al. (2008).

Leaf expansion depends on both continued celldivision and cell enlargement. In grasses like sug-arcane, cell division is restricted to the base of theleaf, and cell division and enlargement are essen-tially complete in the tissue that has emerged fromthe whorl (Dale & Milthorpe 1983). Leaves extendupwards as a result of cell division and enlarge-ment in both leaf and culm tissue (van Dillewijn1952), but culm growth contributes only about20% to the overall extension of leaves and intern-

odes (Batchelor et al. 1992). Leaf extension rate(LER) and culm extension rate (SER) combinedcan be called plant extension rate (PER), thusSER/PER ∼ 0.2. This is similar to SER/PER =0.18 found for 32 genotypes of Miscanthus, a genusclosely related to sugarcane (Clifton-Brown &Jones 1997).

Water stress

Cell enlargement and leaf expansion dependlargely on plant water relations through bothhydraulic and biochemical processes (Barlow1986; Cosgrove 2000). Diurnal maximum PERin five South African cultivars was observed atabout 18:00 due to a short burst of growth (Inman-Bamber & Smith 2005), probably stored growth,which is thought to arise when turgor increasesin cells with relaxed walls (Dale 1988). Diurnalpatterns in PER after rainfall and subsequent soildrying showed first that PER declined sharply forthese cultivars at midday followed by the eveninggrowth spurt (Fig. 21.3)

Later in the onset of stress, daytime PER wasreduced for 6 h or more, followed by a some-what subdued growth spurt, and then when water

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Fig. 21.3. Hourly plant extension rate (PER) for a rain-fedcrop in South Africa during sequential 3-d periods followingrainfall and subsequent soil drying. Minimal ( ), slight (- - -),moderate (·····), and severe (—) water stress as a result ofsoil drying, 1993. Shaded areas indicate nighttime (18:00–06:00 h).


stress was severe, growth was zero or negative dur-ing the day and slightly positive at night withoutthe growth spurt (Inman-Bamber 1995a; Inman-Bamber & Smith 2005). Shrinking and swelling oftissue such as this was observed in stems and fruitsof several plants as a result of dehydration duringthe day and rehydration at night (Kozlowski 1968).

For the climatic conditions in Childers, Aus-tralia, and the cultivar (Q170), two distinct peaksin PER were observed, one at about 08:00 andthe other at about 19:00. Minimum PER occurredbetween 13:00 and 15:00, and the diurnal rangein PER increased from 2.5 mm h−1 to 4 mm h−1

as the soil dried out (Inman-Bamber & Spillman2002).

Daily PER decreased early in the onset ofwater stress imposed on South African cultivarsNCo376 and N11 growing in pots. PER was about40 mm d−1 when midday leaf water potential(�L) was −0.5 MPa and reduced practically tozero when midday �L was −1.3 MPa during thefirst of four cycles of soil drying and rewetting(Inman-Bamber & de Jager 1986a). Some accli-mation (hardening) to stress was evident, in thatPER was 15 mm d−1 when �L was −1.3 MPaduring the fourth stress cycle. In field experi-ments with cultivars NCo376, N12, and N14, PERdeclined when midday �L decreased below −0.2MPa, and PER approached zero when midday �L

decreased below −1.0 MPa (Inman-Bamber & deJager 1986b). In this case, there was no evidenceof acclimation during a second stress period.

PER was included in a simple source–sinkmodel developed to explain differences betweenclones in regard to SC and sucrose accumula-tion. PER was reduced by water stress more sofor clones with high-sucrose content than cloneswith low-sucrose content. The model assumedthat high-sucrose clones diverted more photoas-similate to sucrose storage than did low-sucroseclones when under water stress (Inman-Bamberet al. 2009).

Culm elongation is more sensitive to waterstress than leaf elongation (Inman-Bamber 2004).Water stress reduced SER by 80% and LER byonly 50% in an irrigation experiment in Mau-ritius (Batchelor et al. 1992), and SER recov-ered less rapidly upon relief from water stress.

In the Hawaiian cultivar H62-4671, relative SER(RSER, the ratio of SER of stressed to unstressedplants) reduced rapidly as �L decreased below−0.6 MPa and was only 0.1 when �L decreasedbelow −1.3 MPa (Koehler et al. 1982). As �L candecrease to −1.0 MPa or less even in well-irrigatedplants (Roberts et al. 1990), it can be expected thatwater stress-induced reduction in SER will be dif-ficult to avoid even with frequent irrigation.

Temperature

PER responds strongly to temperature whenplants are under minimal water stress. HourlyPER (Y) of well-watered plants of NCo376 wascorrelated with air temperature (X) measured ina screen 1 m above the plants (Y = 1.77 +0.176X, R2 = 0.65, n=115) (Inman-Bamber1994). Although this equation is used in the Cane-gro model, the relatively low R2 indicates a morecomplex relationship between PER and tempera-ture. Inman-Bamber and Spillman (2002) noticedthat morning PER (between 02:01 and 09:00) washighly correlated with mean morning tempera-ture, but there was no correlation between day-time PER (between 09:01 and 17:00) and daytimetemperature. Soil water deficits (SWDs) up to 140mm had a small but significant effect on morningPER (-0.003 mm h−1 per mm SWD).

Low-sucrose clones were less responsive thanhigh-sucrose clones to variations in diurnal tem-perature in a way analogous to water stress(Inman-Bamber et al. 2010). Upper and lower95% confidence limits for the slope of thehourly PER/temperature regression were 0.165and 0.186 mm h−1◦C−1 for the low-sucrose clonesand 0.188 and 0.239 mm h−1◦C−1 for the high-sucrose clones. PER was therefore helpful inaccounting for differences in the SC in the simplesource–sink model developed earlier by Inman-Bamber et al. (2009).

Data from the temperature experiment byInman-Bamber et al. (2010) showed an interest-ing diurnal effect: temperature probably work-ing through water stress resulting from increasedvapor pressure deficit. Potted plants were wateredfrequently both day and night in a temperature-controlled and humid glasshouse. In the cool


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Fig. 21.4. Hourly PER (�,◦) and air temperature (- - -,·····) in hot (�,- - -) and cool (◦,·····) glasshouse chambers (datafrom Inman-Bamber et al. 2010). Each point is a mean ofthree PER and 60 temperature readings for each hour over aperiod of at least 100 days.

chamber (14◦C–25◦C), PER followed temperaturevery closely, but in the hot chamber (22◦C–29◦C),PER decreased during the hottest part of the dayand then increased to reach a second diurnal peakat 19:00, as was the case in field-grown plants(Inman-Bamber & Spillman 2002) (Fig. 21.4.).

Area of individual leaves

Several cultivars have been characterized on thebasis of the area of successive leaves on individualculms. The area of successive leaves is asymptotic,approaching maximum values at some positionafter leaf 15. Area per leaf of cultivars from Aus-tralia, Mauritius, and Florida, USA, was definedin terms of variations of the Gompertz function(Robertson et al. 1998; Cheeroo-Nayamuth et al.2000; Sinclair et al. 2004). Cultivars from SouthAfrica (Inman-Bamber 1994) presented in a simi-lar manner, and coefficients from Robertson et al.(1998) and Sinclair et al. (2004), were used in astandard form of the Gompertz equation to allowa graphical comparison of the cultivars from dif-ferent countries (Fig. 21.5).

Y = A.exp(−exp(B − C.X)) (21.4)

where Y represents the area of a leaf, A is theasymptote (maximum area), B and C define therate of leaf area increase, and X is the leaf positionfrom the base.

The range in maximum area per leaf is large(400 to 650 cm2) even between cultivars from onecountry (Fig. 21.5). For CP72-2086, area of leavestended to increase well after other cultivars hadreached a stable leaf size. Area increased rapidlyfor successive leaves of two cultivars grown inMauritius (M555/60 and R570) and then the areachanged little after leaf 15 (Fig. 21.5). In a con-trolled environment facility, leaves of Q117 weremuch larger than they were in the field (as in Fig.21.5), reaching 600 cm2 (Robertson et al. 1998).This and a marked difference in leaf size distri-bution between sites for one cultivar in Fig. 21.5indicate that the simple equations for area per leafthat are used in the Canegro and APSIM models(Inman-Bamber 1991; Keating et al. 1999) need tobe revised.

The maximum area per leaf of well-wateredpotted plants of Q117 was 380 cm2 when grownoutside, but when these plants were transferredto a glasshouse, leaves eventually reached 700 cm2

(Inman-Bamber et al. 2008). Singels et al. (2005)proposed a conceptual model for leaf development

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Fig. 21.5. Area of successive leaves up the culm of differentcultivars. Canal Point cultivars (CP) were determined at twosites (Sinclair et al. 2004). Curves for cultivars/sites were omit-ted where these were similar to the cultivar/site named first inthe legend.


in which each leaf has a genetically determinedthermal time during which to develop, as dis-cussed earlier. The final area of the expanding leafdepends on the availability of photoassimilate pro-duced by older leaves. The longer the phyllochron,the larger the leaf and the more assimilate thatis available to subsequent leaves. Varying waterand light conditions during leaf development willcause variations in the final areas of developingleaves. This model helps to explain some of thevariation in leaf size discussed earlier, as well asthe observation of reduced area per leaf in dryconditions (Inman-Bamber 2004).

Leaf senescence and green leaf numbers

Individual culms in a sugarcane crop producean indefinite number of leaves. In crops grownunder irrigated, high-input conditions in the field,Robertson et al. (1998) recorded up to 57 fullyexpanded (mature) leaves in a 24-month-old cropin Australia. In eight such experiments, the num-ber of green leaves per culm was remarkably sim-ilar for the cultivar Q117. Leaf senescence startedafter seven mature leaves had appeared. The rateof leaf senescence was about 10% lower than therate of leaf production so that the number ofmature green leaves per culm increased from 7 to11 over a 2-year period. The maximum green leafnumber per culm was about 14 when the aver-age number of expanding (immature) leaves perculm of Q117 (3.7) were added (Robertson et al.1998). This is more than the mean maximum num-ber of green leaves, both mature and immature,found on culms of NCo376 (11.5) and N12 (10.0)growing in rain-fed conditions in South Africa(Inman-Bamber 1994). The final culm populationwas lower for NCo376 (14.6 culms m−2) than forN12 (16.5 culms m−2), and thus green leaf num-ber probably varies between cultivars in relationto inherent differences in culm population becauseof competition for light within and between canerows.

Competition for light

Leaf senescence of maize plants grown at a highpopulation density (10 plants m−2) was acceler-

ated by assimilate starvation (Tollenaar & Daynard1982). This phenomenon was confirmed by Bor-ras et al. (2003), who reduced demand for pho-toassimilate by limiting kernel set, thus makingmore assimilate available to older leaves, whichthen senesced at a lower rate. The ratio of red tofar-red light perceived by the leaves did not affectsenescence, but the quantity of light perceived did(Borras et al. 2003).

Interesting data for the number of green leavesper culm was obtained by Singels & Smit (2009) ina row spacing experiment (Fig. 21.6). Interrow andintrarow competition for light apparently affectedthe maximum green leaf number, the timing ofthe peak in leaf number, as well as the declinein leaf numbers after this peak, which occurredwhen intrarow PAR interception was about 90%.The rate of decline in green leaves was consistentwith the extent to which shade from neighbor-ing rows negatively affected light perceived byleaves lower in the canopy (Singels & Smit 2009).The number of green leaves per culm of Q183 (19leaves) in a glasshouse experiment was consider-ably greater than can be obtained in the field, prob-ably because of the lack of shading of lower leavesin the glasshouse (Inman-Bamber et al. 2008).

Water stress

The number of green leaves per culm was highlycorrelated with midday �L in a dry down experi-ment with potted plants of NCo376 and N11 (Fig.21.7). The senescence rate depended on how manygreen leaves were present when the drying cyclestarted so that green leaf numbers converged as�L decreased, tending to two leaves when �L

was about -2.8 MPa (Inman-Bamber & de Jager1986a). Survival is doubtful after only two or threegreen leaves remain on plants subjected to waterstress. The limit of stress in terms of �L that canbe tolerated by sugarcane was suggested to be -2.8MPa (Inman-Bamber & de Jager 1986a).

For NCo376 growing in rain-fed conditions inSouth Africa, 70% of the variation in green leafnumber was associated with SWD (Y = 11.2 –0.053X) when SWD<90 mm. Water stress affectsgreen leaf number through a decrease in rate ofappearance of new leaves as well as an increase


RowSpacing

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Fig. 21.6. Green leaf number on primary shoots of sugarcane as a function of thermal time for different row spacings. Redrawnfrom Singels & Smit (2009).

in the rate of leaf senescence. Both these stresseffects occurred more or less simultaneously in twodry-down experiments with Q96 (Inman-Bamber2004), but leaf elongation and appearance slowedmore rapidly than senescence when SWD was lessthan 100 mm. The opposite was true when SWDwas greater than 100 mm. The number of greenleaves per culm (7.8) was remarkably large after 6

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1. N11 cycle 12. NCo376 cycle 13. N11 cycle 24. NC0376 cycle 2

−0.5 −1.0 −1.5 −2.0 −2.5 −3.0Midday ψL (MPa)

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Fig. 21.7. Number of green leaves per culm in relation tomidday leaf water potential (�L) for two cultivars undergoingtwo successive drying cycles (redrawn from Inman-Bamber &de Jager 1986a).

months without irrigation, and we could concludethat these plants were a long way from the degreeof stress from which there could be no recovery(Inman-Bamber 2004).

The number of green leaves per culm is a conve-nient indicator of the degree of water stress beingperceived. Later we will discuss the usefulnessof green leaf numbers for assessing the effect ofSWDs on biomass accumulation and partitioning,which were also determined in these experiments(Inman-Bamber 2004).

Plant population and row spacing

The tillering trait in grasses is highly heritable(Langer 1963). In sugarcane newly released cul-tivars are usually characterized in terms of theirculm population at the time of harvest relativeto other cultivars. Germination and tillering areinfluenced greatly by temperature with little ofeither occurring below 18◦C (van Dillewijn 1952).Plant population (including tillers and primaries)normally increases rapidly until intrarow compe-tition shades out smaller culms, eventually leav-ing a relatively stable population of primaries andolder tillers (Singels & Smit 2009). This patternfollows cumulative heat (thermal time) to a largeextent, particularly if 16◦C is used as the base tem-perature (Inman-Bamber 1994). In ratoon crops,there is a delay of about 350◦Cd (base 16◦C)between the emergence of a primary shoot and its


0 5 10 15 200

20

40

60

80

100

Primary plant population per m2

Max

imum

or

final

pop

ulat

ion

per

m2

Fig. 21.8. Maximum (solid symbols) and final (open sym-bols) culm population versus primary culm population forexperiments in the Burdekin (��) and Bundaberg (•◦) regionsof Australia (Bell & Garside 2005) and at Mt. Edgecombe,South Africa (��) (Singels & Smit 2009).

first tiller (Singels et al. 2005). Culm populationpeaked when overall PAR interception reached70% (Inman-Bamber 2004), but Singels and Smit(2009) showed that this was due to shading withinthe row, rather than between rows, because thetiming (thermal) of the peak was independent ofrow spacing. Culm senescence started when theground directly under the crop row was 90% inthe shade.

Many attempts have been made to overcome theslow canopy development of sugarcane by reduc-ing the row spacing or by planting in beds (Bull &Bull 2000). Populations of primary shoots var-ied with row spacing and seed density as well aswith cultivation history prior to planting (Bell &Garside 2005). Maximum and final culm popula-tion was closely related to the population of pri-maries (Fig. 21.8). Singels and Smit (2009) var-ied the initial population of primaries throughrow spacing and essentially extended the resultsof Bell and Garside (2005) despite the differentcultivars and climates across datasets (Fig. 21.8).Taken together, these results indicate tillering maybe greatly enhanced by a variety of managementoptions and that tillers contribute little to the cropthat is finally harvested (Fig. 21.8). Bell and Gar-side (2005) suggested that achieving a high pop-ulation of primary shoots through improved soil

health may be a less risky strategy of achieving ade-quate final culm numbers than through increasedseeding rates or reduced row spacing.

RADIATION INTERCEPTION

Although the relatively slow canopy developmentin sugarcane is responsible for wasting radiationduring the first three months of development, thelong duration of the crop (usually 10 to 24 months)makes it highly efficient in intercepting annualradiation. The relative rate of canopy developmentand subsequent senescence is evident for a range ofcrops in terms of crop coefficients listed by Allenet al. (1998). These coefficients are estimates of theratio of crop water use to reference evapotranspi-ration and are governed mostly by green leaf area.Fig. 21.9 combines the duration of different cropstages and the crop coefficient for each stage fromAllen et al. (1998) to produce an average coeffi-cient for each day of the development of a rangeof crops. The duration of a full green leaf groundcover is far longer for sugarcane, allowing it tocapture more annual radiation than any other cropunless two short-duration crops can be grown in 1year. Even then it would be hard to match the effi-ciency with which sugarcane intercepts radiation.The longer the duration of the sugarcane crop, themore efficient radiation interception becomes. Forexample, increasing age at harvest from 12 to 22months would increase efficiency from 54 to 69%in a rain-fed crop at Powers Court, South Africa(Inman-Bamber 1995b).

Temperature

As indicated in the discussion on leaf expansion,the proportion of radiation intercepted during thegrowth of sugarcane depends on prevailing tem-peratures during canopy development. Sugarcanecrops starting as plant or ratoons in winter inter-cept less radiation than those starting in summer(Fig. 21.10). Summer ratoons can be very efficient,intercepting more than 80% of annual radiation,and one would expect their yields to be greaterthan for crops starting at other times of the year.

Differences between cultivars in the proportionof radiation intercepted can be large in the earlier


0 100 200 300 400

Days of growth

0.0

0.5

1.0

1.5

Cro

p co

effic

ient

Winter wheat

Sugarcane PWheatSunflowerSorghumOatsMilletMaize sweetMaize grainCottonCastorBarley

Sugarcane R

Fig. 21.9. Mean crop coefficient for various crops derived from estimates of the duration of growth stages From Allen et al.(1998).

stages of crop development. For example, Robert-son, Muchow, et al. (1996) found large differencesbetween Q117 and Q138 during the first 111 daysafter planting, but these differences diminishedduring later development. The higher culm pop-ulation of Q138 was responsible for the initial dif-ference in interception.

Row spacing

Bull and Bull (2000) reduced spacing from 1.5 to0.5 m and found a 50% increase in yield, whichthey attributed to greatly improved radiation cap-

ture by the crop with the narrow rows. However,from Figure 21.9 it is apparent that even if onecould speed up canopy closure to match that ofcereal crops (Fig. 21.9), one could perhaps onlyhalve the waste of solar radiation by sugarcane.Interception efficiency increased 33% by decreas-ing row spacing from 1.5 to 0.9 m in a 10-month-old plant crop of N25 (Olivier & Singels 2003) and25% by decreasing row spacing from 1.5 to 0.5 min a 15-month-old plant crop of Q124 and Q155combined (Garside & Bell 2009). Singels and Smit(2002) found that total radiation intercepted by aplant crop at an age of 274 days increased by 26%

1 2 3 4 5 6 7 8 9 10 11 1250

60

70

80

90

Q138

Q117

NCo376

N12

CP66/1043

Inte

rcep

tion

of a

nnua

l rad

iatio

n (%

)

Month of planting or ratooning

Fig. 21.10. Interception of annual radiation for crops starting at different times in the southern hemisphere (Inman-Bamber1994, ��; Robertson et al. 1996a, ��; Singels et al. 2005, �•).


per meter of reduction in row spacing. This ben-efit declined to 18% in the ratoon crop harvestedat 325 days (Singels & Smit 2009).

Cultivars

The rate of canopy development is one of the traitsthat most easily distinguish cultivars from oneanother and a trait that is often highly regardedby growers. Yet little has been published on theradiation interception efficiency of different cul-tivars. Irvine (1975) suggested that LAI would bea useful selection criterion because it is correlatedwith yield (r ∼ 0.5) and is easy to distinguishwhen plants are young. NCo367 was considerablymore efficient than N12 when starting in Febru-ary (summer) in South Africa, and Q138 was moreefficient than Q117 when planted in July (winter)in Australia (Fig. 21.10).

PHOTOSYNTHESIS

Rates of photosynthesis per unit leaf area for indi-vidual leaves were greater for sugarcane than forZea and Sorghum spp. within the C4 species groupand considerably greater for the C4 group thanfor the C3 group (Gifford 1974). In young plantsof CP73-1547, photosynthesis of leaf 7 reached amaximum of about 30 �mol m−2 s−1 14 days afterit emerged and declined to about half this rate 34days later (Vu et al. 2006). The mean photosynthe-sis rate for young, fully expanded leaves of Q138,similar to young CP73-1547 leaves, was 30.5 �molm−2 s−1, and for young Q183 leaves was 35.5 �molm−2 s−1 (Inman-Bamber et al. 2008). Mean photo-synthesis at the start of the culm elongation phaseof several clones exceeded 50 �mol m−2 s−1 whenmeasured before 11:00, but these rates declined by20% in the afternoon (Inman-Bamber et al. 2011).

Photosynthesis of whole plants of Q138 andQ183 responded to radiation according to theasymptotic equation:

A = 18.6(1 − exp(−0.03394.PAR/18.6)),

R2 = 0.9 (21.5)

where A is the photosynthesis of whole plants in�mol m−2 s−1, and PAR is radiation in �mol m−2

s−1, and 18.6 is the asymptote.

Photosynthesis per unit area averaged overall leaves would therefore reach about 19 �molm−2 s−1 when saturated with light (Inman-Bamber et al. 2008). Thus, for sugarcane growingwith nonlimiting water, light, and fertilizer undernormal CO2 and temperatures, photosynthesis perunit leaf area of single leaves is in the 30–50 �molm−2 s−1 range (see also Vu et al. 2009), while pho-tosynthesis of whole plants is considerably lowerthan this rate.

In one study, biomass accumulation of pottedplants was closely related to whole plant photosyn-thesis as one would expect (Inman-Bamber et al.2009), but it is yet to be shown if biomass andsingle leaf photosynthesis and yield are well cor-related for field-grown sugarcane. Irvine (1975)attempted to do this for 10 Saccharum sponta-neum and 10 S. officinarum genotypes and theirhybrids and found no correlation with cane orsucrose yield. Gifford (1974) lists the many fac-tors that may detract from the potential advantageof having high rates of photosynthesis in youngsingle leaves. These include other aspects of theleaves, their area and angle, as well as influencesof the sink tissue including respiration and feed-back effects. However, Long et al. (2006) showedthat leaf photosynthesis and yield are indeed cor-related when the variation in other components ofthe source–sink system is limited. This is clearlydemonstrated in recent research on elevated CO2,photosynthesis, and biomass accumulation (Longet al. 2006).

Photosynthesis of young sugarcane leaves was20% greater in elevated (∼720 ppm) than in ambi-ent CO2. Elevated CO2 also enhanced leaf area by31% and stem fresh weight (cane yield) by 55.5%(Vu et al. 2006). Similar results were obtainedwhen sugarcane was grown at ambient (∼370ppm) and elevated (∼720 ppm) CO2 for 50 weeksin open-top chambers. Single leaf photosynthesisper unit area was increased 30% and biomass 40%by the increase in CO2 (de Souza et al. 2008).

RUE

RUE is defined as the mass of abovegroundbiomass accumulated by a crop per MJ of


solar radiation (approximately 400 to 3000 nm)intercepted by the green leaf canopy. Sinclairand Horie (1989) developed equations for maizeand sorghum to derive RUE from values oflight-saturated leaf photosynthesis such as thosereported above. Using their relationship for maizeand maximum rates for leaf photosynthesis of 30to 50 �mol m−2 s−1, we may expect RUE for sug-arcane to be about in the 1.5 to 1.7 g MJ−1 range.RUE in terms of PAR (400 to 700 nm) would beabout twice these values because PAR (Eq. 21.2)has about half the energy value of solar radia-tion. RUE was determined empirically for sugar-cane by regressing biomass yield against cumula-tive solar radiation intercepted (Robertson et al.1998). Maximum RUE was obtained by progres-sively removing data points until a maximum R2

was obtained. Maximum RUE was 1.72 g MJ−1

for a plant crop and 1.59 g MJ−1 for a ratoon crop,but average RUE was much lower (1.47 and 1.44g MJ−1, respectively) because biomass failed toincrease rapidly after it had reached ∼50 t ha−1

(Robertson et al. 1996a). The reduction in growthand RUE toward the end of the growth cyclewas explained partly through the loss of culmsdue to lodging and smothering. As we have seen,many tillers and leaves senesce through assimilatestarvation and these are often not fully recoveredwhen determining biomass. Muchow et al. (1997a)made allowance for unrecovered leaves (trash) andobtained maximum RUE close to 2 g MJ−1. Sin-clair and Muchow (1999) tabulated RUE for awide range of crops and concluded that sugarcanewas one of the most efficient. One reason offeredfor the higher RUE in sugarcane than in maizewas the lower energy content of sucrose, whichrequired only 1.2 g of assimilate per g comparedto 1.4 g for 1 g of starch, protein and lipids foundin maize seeds.

Park et al. (2005) also concluded that sugar-cane is one the most productive crops in termsof RUE but that in many cases, yields are lowerthan expected because growth rate slows downbefore the crop is harvested. The so-called reducedgrowth phenomenon (RGP) could occur 6 monthsbefore harvesting or not at all and appeared tobe associated with lodging, reduced leaf N, andculm loss, although none of these effects were

conclusive. Lodging caused yield losses of 2.1 to5.5 t sucrose ha−1 in experiments where someplots were allowed to lodge naturally and oth-ers were prevented from doing so with scaffold-ing (Singh et al. 2002). Culm death contributedto this loss only to a limited extent (0.3 to 0.6 tha−1). In one experiment, RUE was maintained ata high level (∼1.9 g MJ−1), up to nearly 90 t/habiomass in plots where lodging was prevented.Growth rate slowed in lodged plots after about 55t ha−1 biomass had accumulated. The possible fac-tors underpinning RGP was recently reviewed byvan Heerden et al. (2010). Factors thought to beresponsible included culm death, lodging, declinein specific leaf N, feedback on photosynthesis bysucrose accumulating in the culm, and respira-tion of sucrose. Whole plant and single leaf pho-tosynthesis measurements on nine high-sucroseand nine low-sucrose clones indicated that sucroseaccumulation was not responsible for the observeddecline in photosynthesis with crop age despiteevidence for local feedback within the leaf (Inman-Bamber et al. 2011).

In the APSIM Sugarcane model, maximumRUE is assumed to be 1.8 g MJ−1 for plantcrops and 1.65 g MJ−1 for ratoon crops (Keat-ing et al. 1999). RUE and plant populationcan be reduced after lodging. Conditions underwhich lodging generally occurs were establishedby Inman-Bamber et al. (2004) based on biomassyield, antecedent soil moisture, and in-storm rain-fall. Observed biomass accumulation was slowafter lodging and a 30% reduction in RUE mayaccount for this.

DRY MATTER PARTITIONING

The value of the sugarcane crop delivered to themill is often estimated using formulas with termsfor sucrose, brix, and fiber contents on a fresh massbasis; however, SC of fresh mass (SCF) is usu-ally the dominant factor. An increase in sucroseyield due to improved SCF is up to 1.8 timesmore valuable than a sucrose yield increase dueto increased cane yield (Jackson et al. 2000). Thisis because increased cane yield is associated withincreased marginal costs in harvesting, transport,


and milling, whereas an increased SCF is not.Unfortunately, in many countries there has beenvery little improvement in the % sucrose extrac-tion for a long time (Fig. 21.1)

HI

The high efficiencies of radiation capture and usein sugarcane are not matched by high efficien-cies in the distribution of biomass (dry matter) tothe commercially important component (sucrose)when compared to maize (grain). The averageHI was 0.52 (0.41 to 0.62) for maize in Aus-tralia (Unkovich et al. 2010), and, from the dis-cussion to follow, we can expect HI for high-yielding commercial sugarcane cultivars to bebetween 0.3 and 0.4.

A short review of components of HI on a drymatter basis was provided by Inman-Bamber et al.(2002). The fraction of culm in crops with high drybiomass (>50 t ha−1) was about 0.8 for some Aus-tralian cultivars (Robertson et al. 1996a) and was0.66 for two Hawaiian cultivars (Evensen et al.1997). For one South African cultivar, culm frac-tion reached a maximum of 0.7 (Inman-Bamber &Thompson 1989). Robertson et al. (1996a) sug-gested that the reported range in maximum culmfraction (0.66 to 0.8) could be due to variableamounts of trash recovered during sampling.

Muchow et al. (1996) reported remarkable sim-ilarity in SC of culms on a dry weight basis (SCD)in the published data on some Australian, SouthAfrican, Mauritian, and Hawaiian cultivars. Theysuggested that maximum SCD has been stable at0.5 g g−1 across cultivars and across locations forseveral decades. Robertson et al. (1996b) con-cluded that SC tends toward a common max-imum of 0.48 g g−1 for some Australian andSouth African cultivars over a wide range of waterregimes and N supply. Rostron (1972) showed thatSCD in NCo376 changed little after 56 weeks ofgrowth under irrigated conditions.

Berding (1997) challenged the conclusion ofMuchow et al. (1996) that maximum SCD was sta-ble across cultivars and crop classes. He showedthat SCD in unselected clones of sugarcane var-ied from 0.44 to 0.60 g g−1; however, most ofthese clones had SCD in the 0.50 to 0.56 g g−1

0 100 200 3000.0

0.15

0.30

0.45

0.60

Distance from base (cm)

SC

(g

g–1

DM

)

Mass per stalk (g)0 to <50

50 to <100100 to <150150 to <200200 to <250

Fig. 21.11. Mean sucrose content (on a dry matter basis,SCD) of 20 cm stalk segments of NCo376 grouped by stalkdry mass versus stalk height. Bars are 2 x one standard errorof the mean. From Inman-Bamber et al. (2002).

range. While Berding (1997) challenged the 0.5 gg−1 maximum SCD presented by Muchow et al.(1996), his data did not directly challenge the dom-inant effect of culm biomass on SC.

Partitioning to sucrose within the culm

The link between culm mass and SCD as pro-posed by Muchow et al. (1996) was obvious whenSCD of 20 cm segments of NCo376 were groupedaccording to mean mass per culm from which thesegments were taken (Inman-Bamber et al. 2002).At the base of the culm, SCD increased markedlywith the first two 50 g increments in culm mass,and then mean SCD per segment reached a maxi-mum of about 0.55 g g−1 (Fig. 21.11). The gradientin SCD toward the top of the culm was similar foreach culm mass class. It was therefore the mass(or length) of culm with near maximum SCD thatdetermined the SCD of whole culms. This type ofpattern has been demonstrated for brix content offresh cane by van Dillewijn (1952) and Fernandesand Benda (1985)

From Fig. 21.11, maturation in sugarcane canbe described in two phases, one in which theSC of basal internodes is increasing and theother in which the SC of basal internodes hasreached a maximum. In the second phase, further


increments in SC of whole culms depend mostlyon ripening of distal internodes. Once the cropis through the first phase, seasonal variation inSC of whole culms is largely due to partition-ing to sucrose in distal internodes mediated byfactors such as water and nutrient stress, tem-perature, and chemical ripening, which affect leafand culm elongation more than they affect pho-tosynthesis (Inman-Bamber et al. 2002). Singelsand Bezuidenhout (2002) developed equations forthis concept and distinguished between cultivarson the basis of their response to ripening stimulisuch as low temperature or water stress. They pos-tulated that cultivars with high whole-culm SCD

respond to ripening stimuli more than those with alow whole-culm SCD and display a steeper down-ward gradient in SCD toward the top of the culm(Singels et al. 2005).

Water stress

The outcome for the plant of expansive growthbeing more sensitive to water stress than photo-synthesis is that photoassimilate (sucrose), whichwould otherwise be required for leaf and culmexpansion, can be diverted to the culm for stor-age when expansion is suppressed by water stress.This phenomenon has been exploited by growers(Chapter 4) who often attempt to enhance SCF

by withholding irrigation in the period beforeharvest, a practice known as drying-off. SCF

increased up to 18% in experiments with variousdrying-off treatments in South Africa (Robert-son & Donaldson 1998). In a rainout shelter exper-iment, sucrose yield was 11.8 t ha−1 in the well-watered treatment and 10.7 t ha−1 in cane deniedwater for 5 months (Inman-Bamber & de Jager1988). Cane yield was reduced from 108 to 75t ha−1 by the latter treatment, but SCF contentincreased from 10.9 to 14.3% (a 31% increase).

SCD in young sugarcane culms increased 62%when water stress was imposed at the 14th leafstage, which is long before drying-off would nor-mally be done in practice. At this point, SCD

in well-watered plants was only 15% (Inman-Bamber 2004). The relatively high partitioning tosucrose in the dry treatment came at the expenseof new culm fiber and nonsucrose solutes. Water

stress imposed at a later stage (23 mature leaves)increased HI from 32 to 37% when the crop washarvested 5 months later (Inman-Bamber 2004).The diversion of biomass to sucrose came fromboth the tops and the fiber in the culm. The smallsoluble nonsucrose pool (<5% of biomass) wasnot affected by treatment (Inman-Bamber 2004).The greatest difference in dry matter partition-ing in favor of the dry treatment occurred whenan average of 3.7 leaves per plant had been lostdue to water stress. If the crop had been harvestedat this stage, then the dry treatment would haveyielded 3.6 t ha−1 sucrose more than the wet treat-ment. These data indicate that a loss of three tofour leaves would indicate the best time to harvestto benefit from increased sucrose storage duringdrying off.

A good understanding of the source–sink mech-anisms giving rise to this result could lead toboth increased sucrose yields and water savings.Conversely, misunderstanding of the ripeningresponse could lead to losses in sucrose yield.Robertson et al. (1999) showed that SC on a freshmass basis remained higher in dry-down treat-ments than fully irrigated treatments, even whenthe cane yield in the dry-down treatments hadbeen reduced by as much as 50% by water stress.Thus, sucrose yield losses can arise by paying toomuch attention to SC when managing irrigationduring the dry-off period.

Source–sink relations

Opinions differ as to whether sucrose storage isa priority sink for photoassimilate or whethersucrose simply accumulates when demands forhigher priority sinks have been met. Pammenterand Allison (2002) conducted pot and field exper-iments in which partial defoliation or shading wasused to reduce photosynthesis and these treat-ments increased the proportional partitioning ofassimilates to sucrose in the stem. From this itwas concluded that sucrose storage, rather thanvegetative growth, receives priority in the alloca-tion of assimilate. McCormick et al. (2008) shadedall but the third fully expanded leaf for 14 days toperturb the source–sink balance in 12-month-oldsugarcane. SC in immature culm tissue declined,


while assimilation rate in unshaded leavesincreased by 57% in compensation. The resultssupported the notion that sink demand can limitsource activity and that genetic disruption of suchfeedback may lead to increased sucrose yield. Sin-gle leaf and whole plant photosynthesis of ninehigh-sucrose and nine low-sucrose clones was notrelated to the large variation in SC, which wasalways low in upper (distal) internodes, leading tothe conclusion that sucrose in the culm does notfeedback on photosynthesis (Inman-Bamber et al.,2011).

Inman-Bamber et al. (2009) proposed that thevariation in SC and sucrose accumulation amongsugarcane genotypes could be explained by vari-ations in net photosynthesis and in partitioningof photoassimilate, regardless of the nature andimportance of mechanisms linking photosynthe-sis and sucrose storage and regardless of whethersucrose is a priority sink.

Photosynthesis and expansive growth weremanipulated with irrigation in a glasshouse exper-iment to determine how assimilate supply and usewould affect sucrose accumulation in two high-sucrose and two low-sucrose clones from a seg-regating population (Inman-Bamber et al. 2009).Low-sucrose clones developed both more culmsper pot and a higher leaf mass relative to culm massthan the high-sucrose clones. The higher leaf massdid not result in additional photosynthesis and soplaced an additional demand on photoassimilatein these clones and delayed the accumulation ofsucrose in the culm. Sucrose accumulation wasexplained to a large extent (72%) by a model withterms for photosynthesis, PER, and plant popula-tion. Limiting expansive growth while maintain-ing photosynthesis enhanced sucrose accumula-tion in both low- and high-sucrose clones suchthat the SC of low-sucrose clones increased tolevels found normally in high-sucrose clones, atleast for some internodes (Inman-Bamber et al.2009).

Manipulating source–sink in this way resultedin SCD of 67% for internode 20 of Q117 (Fig.21.12), suggesting that the maximum SCD forwhole culms (∼50%) discussed earlier may be wellbelow the physiological limit. Similarities in theSC profile for a high-sucrose clone on 1 May and a

low-sucrose clone on 21 March indicated that lowSC clones might simply need more time (and radi-ation) to develop the high concentrations found inhigh-sucrose clones (Inman-Bamber et al. 2009).A second experiment was conducted using thesame clones but with temperature rather thanwater stress to manipulate the source–sink sys-tem (Inman-Bamber et al. 2010). This experi-ment essentially confirmed the conclusions of thewater stress experiment and validated the modelfor sucrose accumulation based on photosynthesis,PER, and culm population.

Seasonal effects

Rainfall and temperature vary through the seasonin many sugarcane production regions, giving riseto relatively predictable seasonal variations in SCF

and SCD, which normally reach maximum valuesin spring in southern Africa and Australia. Theopening and closing dates of sugar mills dependon this variation to a large extent.

Data in Figure 21.12 suggest that there is littlechange in SCD of basal internodes once a ceilingvalue of about 0.55 is obtained for culms weigh-ing more than 150 g dry mass. However, in SouthAfrica, seasonal effects on SC in 0 to 20 cm and 20to 40 cm segments were evident in culms weigh-ing more than 150 g (Inman-Bamber et al. 2002).SCD of basal sections of the culm was lowest inautumn, highest in spring, and decreased duringsummer (Fig. 21.13). The decrease in mean SCof the two basal segments of large culms duringsummer could mean that stored sucrose was remo-bilized to support renewed growth in summer,amounting to a real loss in accumulated sucroseyield. The mass of sucrose per segment was sub-ject to the same seasonal variation as SC (Fig.21.13), indicating that changes in SC were due tochanges in sucrose mass per segment, rather thandilution by other solutes and cell wall constituents(Inman-Bamber et al. 2002).

POTENTIAL, ATTAINABLE, ANDACTUAL YIELDS

Leibig’s law of the minimum, which impliesthat yield is always limited by a single factor, is


Low sucrose KQ97-2835 High sucrose Q117

Suc

rose

con

tent

of d

ry m

atte

r (g

g–1

)

0.00

0.14

0.28

0.42

0.56

0.70

0.00

0.14

0.28

0.42

0.56

0.70

Internode number counting from the top of the stalk

1 11 21 31 1 11 21 31

21 M

ar1

May

Fig. 21.12. Sucrose content of dry matter determined on two dates in 2007 for internodes of two clones grown with minimal(◦—) and moderate (�- - -) water stress. Bars are 2 x standard error of the mean. From Inman-Bamber et al. (2009).

0 100 200 300

Day of Year

Suc

rose

mas

s(g

per

seg

men

t)

Juic

e pu

rity

(%)

SC

D (

g g–1

DM

)

0.42

0.48

0.54

0.60

10

15

20

90

95

(a)

(b)

85

Fig. 21.13. (a) Sucrose content (SCD) and (b) mass of stalksegments, 0 to 20 cm (- - -) and 20 to 40 cm (—) and juicepurity of 0 to 40 cm segment (·····) of NCo376 for stalks weigh-ing more than 150 g DM and sampled at 2-month intervals.Stalks were segmented from the base upwards. Bars are 2 xone standard error of the mean. From Inman-Bamber et al.(2002).

probably still the basis of our attempts to raiseagricultural production through management ofinputs such as water and nitrogen. Penning deVries (1982) elaborates on this law by identifyingfour production levels, where yields in level 1 arelimited by factors such as radiation and temper-ature, which are generally impossible to control,and where yields in levels 2, 3, and 4 are lowerlargely due to factors that can be controlled. Theselimitation levels need not be consistent throughthe growth cycle of a crop but could vary from dayto day, with one factor limiting growth one dayand another the next. Rabbinge (1993) as citedby Kropff et al. (1997) coined the terms potentialyield, in which radiation and temperature are lim-iting (level 1), attainable yield, in which water andnutrients are limiting, and actual yield, in whichpests, diseases, and weeds are limiting.

Potential yield

Potential and attainable yield was estimated for theSouth African sugar industry by Inman-Bamber


(1995b) and for the Australian sugar industryby Muchow et al. (1997b) using the Canegroand APSIM models, respectively. Potential sugaryield varied with latitude in the 32◦S to 25◦Srange (subtropics) because of the dominant roleof latitude on radiation (Muchow et al. 1997b).Annual potential sugar yields for Nambour, Aus-tralia (26.6◦S), and Big Bend, Swaziland (26.9◦S)were similar (∼21 t ha−1), and so were yields forGrafton, Australia (29.6◦S), and Mt. Edgecombe,South Africa (29.6◦S), similar at ∼17 t ha−1. Thiswas true despite APSIM-Sugarcane being basedon Q117 and Q138 (Keating et al. 1999) andCanegro being based on NCo376 (Inman-Bamber1991).

Annual potential sugar yields were generallygreater in the tropics (22 to 31 t ha−1) than the sub-tropics (17 to 22 t ha−1) but the direct relationshipbetween yield and latitude broke down particu-larly for regions like Babinda, Australia, whereannual rainfall is 2 to 7 m (Muchow et al. 1997b).The highest annual sugar yield obtained fromsmall plots during the building of the APSIM-Sugarcane model was 28 t ha−1 (Keating et al.1999), which was slightly greater than the esti-mated annual average potential yield (27 t ha−1) forthe region concerned (Burdekin, Australia). Thehighest yields for NCo376 measured in releasedvariety trials (RVT) in South Africa and Swazi-land were about 22 t ha−1 for five fully irrigatedsites–Komatipoort, Makatini, Mhlume, Pongola,and Simunye–and this agreed well with the poten-tial yield for these areas predicted using Canegro(Fig. 21.14)(Inman-Bamber 1995b).

APSIM-Sugarcane and Canegro capture mostof the important yield-building processes dis-cussed in this chapter and are therefore usefulfor defining potential yield (limited by radiationand temperature) at least within the countrieswhere they were developed. Most of the exper-iments used to build and verify these models haveused commercially grown, nongenetically modi-fied cultivars and fairly conventional crop manage-ment. Clearly, if radiation capture and RUE can beimproved through breeding, GM, or through cropmanagement, then these potential yields can beexceeded. Moore et al. (1997) cited two observedsucrose yields (33 and 35 t ha−1) that were con-

siderably higher than the mean annualized yieldsreported by Muchow et al. (1997b).

Attainable yield

Water and mineral nutrients, primarily N, are theinputs that limit yield in many countries (Chapters5, 8, 9, and 10). Canegro deals quite well with waterdeficits and APSIM with water, and N. Canegrowas used to estimate the extent that water is lim-iting in South Africa in two soils (Inman-Bamber1995b). Simulated yields of rain-fed sites werecomparable with the yields from experiments atthose sites. It is likely that the observed and sim-ulated yields would be more similar if the cor-rect soil properties and management inputs weretaken into account as was done for 64 experimentalyields at three sites where simulated and observedyields differed less than 5% (Inman-Bamber et al.1993). Differences between attainable and poten-tial yield will vary greatly depending on rainfall. InSouth Africa, irrigation is essential where attain-able yields in poor soils are more than 75% belowpotential (Inman-Bamber 1995b).

Actual yield

Potential and attainable yields, usually derivedfrom models such as APSIM-Sugarcane andCanegro, allow us to benchmark production interms of yield actually obtained. McGlinchey andDell (2010) used the ratio of actual to attainableyield (performance ratio) for crop managementdecisions about replanting when actual yields werelower than expected. The performance ratio wasmaximum (0.87) for plant crops and deep soils anddeclined with ratoon age, particularly for poor soil(Fig. 21.15).

Muchow et al. (1997b) demonstrated remark-able variation in sugar yields of individual fieldsat four locations in Australia. Maximum yieldswere equivalent to potential yields, but these wereobtained on less than 5% of the area harvested.District mean yields were 53 to 69% of potentialyields.

Attempts to raise actual yield, as defined, maybe more rewarding than attempts to address otheryield-limiting steps considered in this chapter.


3010 2 10 40 6 26 15 106 70

The number of experiments at each site

72 372 8 33 20 6 12 5

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Fig. 21.14. Box and whisker plots for annualized sucrose yield of NCo373 obtained from released variety trials at rain-fed sites(clear boxes) and irrigated sites (shaded boxes) in southern Africa. Mean simulated yields (lines) for these sites were obtainedfrom Canegro, assuming full irrigation (no water stress regardless of soil type) or no irrigation on a shallow Cartref soil (—) and adeep Shorrocks soil (- - -). The top and bottom of each box are values for the upper (u) and lower (l) quartile yields, respectively.The line within the box is the median yield. The whiskers span yields (if any) in the u to u + 1.5(u-l) or the l to l - 1.5(u-l) range;any yields outside the range of the whiskers but within u + 3(u-l) or l - 3(u-l) are shown as asterisks; and yields greater or lessthan these are shown as open circles. Data from Inman-Bamber (1995b).

Class 1: Deep, well structured, well drainedClass 2: Sandy alluvial, well drainedClass 3:Shallow structured, well drainedClass 4: Vertic, cracking clay, impeded drainageClass 5: Duplex, coarse top soil overlying gleyed material

0 5 10 15 20Ratoon

1

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0.8

0.7

0.6

0.5

0.4

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Fig. 21.15. Ratio of actual to attainable yield for successive ratoons and five soil types. From McGlinchey & Dell (2010).


One way to do this is to use growth models toestimate target yields that could be achieved withgiven radiation, temperature, rainfall, and irriga-tion regimes, and then to help growers identifyfields that are underperforming to help correctpossible limiting factors. Various consultants offersuch a service in several parts of the world.

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