6.1 - Concepts and components of RGR

The most useful and widely used analysis is the concept of relative growth rate (RGR) and the simple RGR equation, which derives from the growth of cell populations with unrestricted resources – that is where light, space and nutrient supply are not limiting.

Growth models developed from populations of single cells can be extended mathematically to cover complex multicellular organisms where whole-plant growth is expressed in terms of leaf area and nutrient resources. Such growth indices are not intrinsic properties of plants, but rather mathematical constructs with functional significance. These concepts can be traced to the early 1900s and have proved increasingly useful for studies of growth and developmental responses in natural and managed environments.

6.1.1 - Cell populations

A small population of unicellular organisms presented with abundant resources and ample space will increase exponentially (Figure 6.1a). Population doubling time Td (hours or days) is a function of an inherent capacity for cell division and enlargement which is expressed according to environmental conditions. In Figure 6.1(a) doubling times for these two populations are 1 and 2 d for fast and slow strains respectively.

Fig 6.1.png

Figure 6.1. A population of cells unrestricted by space or substrate supply will grow exponentially. In this hypothetical case, a fast-growing strain of a single-celled organism with a doubling time of 1 d starts on day 0 with a population of n cells which increases to 120·n by day 7. In this example, n=10. The slow-growing strain with a doubling time of 2 d takes twice as long to reach that same size. When data for cell numbers are ln transformed, exponential curves (a) become straight lines (b) where slope = r.

Exponential curves such as those in Figure 6.1(a) are described mathematically as

\[N(t)=N_0e^{rt} \tag{6.1}\]

 where N(t) is the number of cells present at time tN0 is the population at time 0, r determines the rate at which the population grows, and e is the base of the natural logarithm. By derivation from Equation 6.1

\[r=\frac{1}{N}\frac{\text{d}N(t)}{\text{d}t} \tag{6.2}\]

and is called relative growth rate with units of 1/time. The doubling time is Td = (ln 2)/r.

If a population or an organism has a constant relative growth rate then doubling time is also constant, and that population must be growing at an exponential rate given by Equation 6.1. The ‘fast’ strain in Figure 6.1(a) is doubling every day whereas the ‘slow’ strain doubles every 2 d, thus r is 0.69 d–1 and 0.35 d–1, respectively.

If cell growth data in Figure 6.1(a) are converted to natural logarithms (i.e. ln transformed), two straight lines with contrasting slopes will result (Figure 6.1b). For strict exponential growth where N(t) is given by Equation 6.1,

 \[\text{ln }N(t)=\text{ln }N_0+rt\tag{6.3}\]

 which is the familiar slope-intercept form of a linear equation, so that a plot of ln N(t) as a function of time t is a straight line whose slope is relative growth rate r, and intercept is ln N0

In practice, r is inferred by assessing cell numbers N1 and N2 on two occasions, t1 and t2 (separated by hours or days depending on doubling time — most commonly days in plant cell cultures), and substituting those values into the expression

\[r=\frac{\text{ln }N_2-\text{ln }N_1}{t_2-t_1}\tag{6.4}\]

which expresses r in terms of population numbers N1 and N2 at times t1 and t2, respectively.

If growth is exponential, Eq. 6.3 will be linear and any two time points and the natural logarithm of their corresponding population sizes will give an estimate of the growth rate, r. However, if relative growth rate r is not constant, then growth is not exponential but the concept of relative growth rate is still useful for analysis of growth dynamics in populations or organisms. Equation 6.3 is then used to compute average relative growth rate between times t1 and t2 even though population growth might not follow Equation 6.1 in strict terms. In that case plots analogous to Figure 6.1(b) will not be straight lines.

6.1.2 - Plant biomass

In whole plants, cell number is an impractical measure of growth. Instead, fresh or oven-dried biomass (W) is generally taken as a surrogate for cell growth and referenced to the number of days elapsed between successive observations. Relative growth rate is now known as RGR rather than r and measured in days or weeks rather than hours.

Relative growth rate, RGR (d–1), can be expressed in terms of differential calculus as \(RGR=\frac{1}{W}\frac{\text{d}W}{\text{d}t}\) (compare Equation 6.2.) so that RGR is increment in dry mass (dW) per increment in time (dt) divided by existing biomass (W). Averaged over a time interval t1 to t2 during which time biomass increases from W1 to W2, RGR (d–1) can be calculated from

\[\text{RGR}=\frac{\text{ln }W_2-\text{ln } W_1}{t_2-t_1} \tag{6.5} \]

which is analogous to Eq, 6.4. Net gain in biomass (W) is the outcome of CO2 assimilation by leaves minus respiratory loss by the entire plant. Leaf area can therefore be viewed as a driving variable, and biomass increment (dW) per unit time (dt) can then be divided by leaf area (A) to yield the net assimilation rate, NAR (g m–2 d–1), where

\[\text{NAR}=\frac{1}{A}\frac{\text{d}W}{\text{d}T} \tag{6.6}\]

Averaged over a short time interval (t1 to t2 days) and provided whole-plant biomass and leaf area are linearly related (see Radford 1967),

\[\text{NAR}=\left(\frac{W_2-W_1}{t_2-t_1}\right)\left(\frac{\text{ln }A_2-\text{ln }A_1}{A_2-A_1}\right) \tag{6.7}\]

NAR thus represents a plant’s net photosynthetic effectiveness in capturing light, assimilating CO2 and storing photoassimilate. Variation in NAR can derive from differences in canopy architecture and light interception, photosynthetic activity of leaves, respiration, transport of photoassimilate and storage capacity of sinks, or even the chemical nature of stored products.

The following treatment assumes for simplicity that photosynthesis and the assimilation of CO2 occurs only in leaves, even though for many herbaceous or succulent species it occurs to a lesser degree also in stems. Since leaf area is a driving variable for whole-plant growth, the proportion of plant biomass invested in leaf area will have an important bearing on RGR, and can be conveniently defined as leaf area ratio, LAR (m2 g–1), where

\[\text{LAR}=\frac{A}{W}\tag{6.8}\]

LAR can be factored into two components: specific leaf area (SLA) and leaf weight ratio (LWR). SLA is the ratio of leaf area (A) to leaf mass (WL) (m2 g–1) and LWR is the ratio of leaf mass (WL) to total plant mass (W) (dimensionless). Thus,

\[\begin{align} \text{LAR} &=  \frac{A}{W_L}\frac{W_L}{W} \\
 &=  \text{SLA} \times \text{LWR} \end{align} \tag{6.9} \]

As an aside, average LAR over the growth interval t1 to t2 is

 \[\text{LAR}=\frac{1}{2} \left( \frac{A_1}{W_1}+\frac{A_2}{W_2} \right) \tag{6.10}\]

Expressed this way, LAR becomes a more meaningful growth index than A/W (Equation 6.8) and can help resolve sources of variation in RGR.

If both A and W are increasing exponentially so that W is proportional to A, it follows that

\[\frac{1}{W}\frac{\text{d}W}{\text{d}t}=\frac{1}{A}\frac{\text{d}W}{\text{d}t}\times\frac{A}{W}\tag{6.11}\]

0r (substituting Equations 6.5, 6.6 and 6.8)

\[\text{RGR}=\text{NAR}\times \text{LAR} \tag{6.12}\]

As LAR can be broken into SLA and LWR (Equation 6.9) then

\[\text{RGR}=\text{NAR}\times \text{LWR} \times \text{SLA} \tag{6.13}\]

Sources of variation in RGR partitioned this way provide useful insights on driving variables in process physiology and ecology. For an expanded discussion on methodological issues associated with the determination of RGR in experimental populations see Poorter and Lewis (1986).

Increases in leaf area over time can be a more useful basis for measuring plant growth rates than biomass increases, particularly as non-destructive techniques for measuring leaf area are now available. Plant growth rate can be measured as the relative increase in leaf area over time, by substituting total plant leaf area for total biomass in the conventional RGR equation.

\[\text{RGR}_\text{A} =\frac{\text{ln } LA_2 - \text{ln } LA_1}{t_2-t_1} \tag{6.14} \]

where RGRA is relative leaf area expansion rate, LA is total plant leaf area and t is time at two time intervals, t1 and t2, preferably 2-3 days apart.

Growth indices in summary

Five key indices are commonly derived as an aid to understanding growth responses. Mathematical and functional definitions of those terms are summarised below.

Growth index

Mathematical definition

Units

Functional definition

Relative growth rate

RGR

\(\frac{1}{W}\frac{\text{d}W}{\text{d}t}\)

d-1

Rate of mass increase per unit mass present (efficiency of growth with respect to biomass)

Net assimilation rate

NAR

\(\frac{1}{A}\frac{\text{d}W}{\text{d}t}\)

g m-2 d-1

Rate of mass increase per unit leaf area (efficiency of leaves in generating biomass)

Leaf area ratio

LAR

\(\frac{A}{W}\)

m2 g-1

Ratio of leaf area to total plant mass (a measure of ‘leafiness’ or photosynthetic area relative to respiratory mass)

Specific leaf area

SLA

\(\frac{A}{W_L}\)

m2 g-1

Ratio of leaf area to leaf mass (a measure of thickness of leaves relative to area)

Leaf weight ratio

LWR

\(\frac{W_L}{W}\)

dimension-less

Ratio of leaf mass to total plant mass (a measure of biomass allocation to leaves)