quantification of resource capture for crops - decagon … · 2010-05-20 · quantification of...

Quantification of Resource E l Capture Efficiency for Cultivar ImprovementImprovement

Gaylon S. CampbellDecagon Devices, Inc.g

Pullman, WA.

Maximum Potential Potato Yields

Kunkel and Campbell (1987) Am. Potato J.

Th M d lThe ModelYield = HI * B Hi is harvest index B is total crop biomass B is total crop biomass

B = RUE * FI * SB = RUE FI S RUE is Radiation Use Efficiency (biochemical) FI is intercepted radiation fraction (canopy structure) FI is intercepted radiation fraction (canopy structure) S is solar radiation incident on the crop (environment)

We could conclude:We could conclude

Some of the plots yielded the maximum possible for that environment and growing season lengthg g g

Plots yielding less than modeled values Had low RUE (stress, disease...)or Had low FI (senescing canopy, poor canopy structure)

Even higher yields might come from Even higher yields might come from Potatoes with higher RUE Lengthening the growing seasong g g g

O tliOutline

Resource capture concepts Light capture and biomass productionL g p m p Measuring light interception and radiation

use efficiency Water capture and biomass production Water capture and biomass production A bit of history Transpiration vs. total ETp Measuring transpiration efficiency Conclusions

Si l M d l f R C tSimple Models for Resource Capture

Resource: A form of energy or of matter that plants need in order to grow or reproduce

Capture: The process by which any organ – Capture: The process by which any organ above or below ground removes a resource from its environment to maintain metabolismmetabolism

Monteith (1994)

RResources

Carbon Dioxide

Light (solar radiation)

W Water

Nutrients Nutrients

Li ht C t M d l tiLight Capture Model assumptions

B = RUE * FI * S Light limits production (light assumed to g p g

be total solar radiation) B includes only the above ground biomass RUE is conservative (genetically RUE is conservative (genetically

determined)

B d F * Caution: Since B and FI * S are sums, a linear relationship between them will always exist. This approach is only useful if S is limiting.

V l d R f RUEValues and Ranges for RUE

C3 Annuals 1.2 – 1.7 g/MJ

C4 Annuals 1.7 – 2.0 g/MJ

C Oil 1 3 1 6 /MJ C3 Oil crops 1.3 – 1.6 g/MJ

Legumes 1 0 – 1 2 g/MJ Legumes 1.0 1.2 g/MJ

Tuber and root 1.6-1.9 g/MJ

Stockle and Kemanian (2009)

S f t th t ff t RUESome factors that affect RUE

From the table C3 vs. C4 metabolism3 . 4 m m Legume High sink strength (tuber)

Others RUE decreases with increasing vapor RUE decreases with increasing vapor

deficit of the atmosphere RUE increases under strong diffuse

radiationradiation

T d t i RUETo determine RUE

RUE = B/FI*S Measure B – harvest, weigh, dry, weigh

Measure S – pyranometer and data logger

Measure fractional interception

For this canopy FI is close to 1.0 For th s canopy F s c os to . – you don’t need to measure it

For this canopy FI is much smaller – it d t b dneeds to be measured

M i li ht i t ti i iMeasuring light interception in canopies

Light below a canopy is extremely variable

Many measurements are required to accurately characterize light levelscharacter ze l ght levels

The AccuPAR LP-80 has 80 light sensors in a 80 cm long bar for rapid cm long bar for rapid below-canopy measurements

St t FISteps to measure FI

Level the LP-80 above the canopy and make a measurement of incident light

Level the LP-80 below the canopy at several locations and measure transmitted light

The LP-80 shows fractional transmission (TR)

FI = 1 – TR (TR may need to be converted to a daily value as shown in the LP-80 manual)

Interception vs. absorption of radiation by canopies

Campbell and van Evert (1994)

Early Growth Analysis

Exponential growth at early time

300

400

Linear growth as canopy closes

200

300

Bio

mas

s

py(FI approaches 1)

0

100B

00 10 20 30 40

Time

The Expolinear Growth Equation The Expolinear Growth Equation (Goudriaan and Monteith, 1990)

)]}(exp[1ln{ bm ttrcB 300

400

)]}(exp[1ln{ bmm

ttrr

B

cm is max. absolute 200

300

Bio

mas

s

Lost time

growth raterm is max. relative

growth rate 0

100

growth ratetb is represents “lost

time” from incomplete

0 10 20 30 40

Time

canopy closure

M i FI l iMeasuring FI on sparse, low canopies

Digital images can be i processes using

suitable algorithms to determine green gcover

O tliOutline

Resource capture concepts Light capture and biomass productionL g p m p Measuring light interception and radiation

use efficiency Water capture and biomass production Water capture and biomass production A bit of history Transpiration vs. total ETp Measuring transpiration efficiency Conclusions

Wh l t d t t tWhy plants need to capture water

Taiz and Zeiger (1991)

Photosynthesis (P) and Transpiration Photosynthesis (P) and Transpiration (T) for a Leaf

PhotosynthesisTranspirationDgCCgT

CCgP

i

cicac

)()(

p

Transpiration efficiencyDk

DCCg

TP

DgCCgT

cicac

vvaviv

)(

)(

Transpiration efficiency

Normalized efficiency CCkDDgT

cica

v

7.0 Normalized efficiency

Water capture modelDkTP

Water capture modelD

C l i f th l f l iConclusions from the leaf analysis

Th i P/T i ll d i i ffi i The ratio, P/T is called transpiration efficiency (TE). It is the mass of carbon fixed per unit mass of water used (typically a small number b 0 1 d 1%) between 0.1 and 1%)

Photosynthesis (and therefore dry matter Photosynthesis (and therefore dry matter production) is proportional to transpiration

Ph i li i h i d Physics puts limits on what genetics can do to improve water use efficiency of plants

M C l i f th l f l iMore Conclusions from the leaf analysis

T i i ffi i d d Transpiration efficiency depends on environment (vapor deficit of air)

Arid regions (with high vapor deficit) have lower dry matter production per unit water used than do humid regions (P = T*k/D)used than do humid regions (P = T k/D)

Transpiration efficiency varies dramatically di l l d over a diurnal cycle and over a season as vapor

deficit changes

M C l i f th l f l iMore Conclusions from the leaf analysis

T i i ffi i d d h Transpiration efficiency depends on the difference between external and internal CO2concentration [k = 0.7*(Cair – Cint)]

Species which maintain low internal CO2concentration have high transpiration efficiencyff y

C4 species, maintain lower internal CO2concentrations than do C3, so have higher transpiration efficienciestranspiration efficiencies

As atmospheric CO2 concentrations increase transpiration efficiency increases

V l /R f k (D*TE)Values/Ranges for k (D*TE)

Corn 9 – 12 Pa

Potato 7 Pa

Alf lf 4 P Alfalfa 4 Pa

Soybean 4 Pa Soybean 4 Pa

Tanner & Sinclair (1983)

Plants differ in water use efficiency: An ld told concept

F H Ki (U f Wi i ) 1890 1902 F. H. King (U. of Wisconsin) 1890-1902

J A Widtsoe (Utah State U ) 1902 J. A. Widtsoe (Utah State U.) 1902

T. A. Kiesselbach (U. of Nebraska)

Briggs and Shantz (1913)

B i d S h t (1913)Briggs and Schantz (1913)

“One of the most striking features of water requirement measurements is the marked qdifference in efficiency exhibited by different plants in the use of water. The millet, sorghum, and corn groups have g g pbeen found the most efficient, while alfalfa, and sweet clover are the least efficient in producing dry matter with a p g ygiven amount of water. The small-grain crops have a water requirement intermediate between the legumes and gcorn.”

B i d S h t (1913) tBriggs and Schantz (1913) cont.

“M bl diff i th t “Measurable differences in the water requirement also exist between different varieties of the same crop, and this

t th ibilit f d l i suggests the possibility of developing through selection strains which are still more efficient in the use of water.”

Widt ’ WUE i t d 1902 Widtsoe’s WUE experiments around 1902

H t d t i TEHow to determine TE

Measure B – Harvest, weigh, dry, weigh

Measure T by weighing containers or monitoring soil

istmoisture

But weight loss is transpiration But we ght loss s transp rat on and soil evaporation – biomass is proportional just to transpirationtranspiration

How do we compute Transpiration in the Fi ldField

Total water loss is transpiration (T) plus evaporation (E)

When soil water is not limiting PET = PT + PE When soil water is not limiting PET = PT + PE PT = FI * PET PE = (1 – FI) * PET PET computed from weather records (Penman-

Monteith Formula)

Again, measurements of FI are required

B tt t d t i k D * TEBetter to determine k = D * TE

Calculate D from temperature and humidity data

D = es – ea = es(1 – RH)

Daily course of vapor deficit

25

30

2

2.5

15

20

ratu

re (C

)

1.5

2

efic

it (k

Pa)

Daytime ave1.6 kPa

5

10

15

Tem

per

0.5

1

Vapo

r De

vapor

TempDaily ave.1.2 kPa

0

5

2AM

4AM

6AM

8AM

10AM

12PM2P

M4P

M6P

M8P

M10

PM12

AM

0

vapordeficit

2 4 6 8 10 12 2 4 6 8 10 12

C ld TE di tl ?Could we measure TE more directly?

Carbon isotope discrimination

Sim lt n s t nspi ti n nd Simultaneous transpiration and photosynthesis measurements

Measurement of stomatal conductance

Measurement of canopy temperature

Di t f t t l d tDirect measure of stomatal conductance

Steady State Porometerleaf

R1h1

sensorsR2

h2

211

RCC

RRCC vvvvL

Teflon filter

2

21 RRRvs

1211 RRhRvs

12

12 hhvs

P t b d f Porometer can be used for

Measuring maximum daytime conductance (cultivars with high conductance likely have low TE)low TE)

Measuring dark conductance Water lost in the dark doesn’t contribute

to dry matter Low dark conductance correlates with low Low dark conductance correlates w th low

Cci in soybean (Earl and Walden, 2009)

C l iConclusions

The resource capture paradigm can be useful for identifying and removing limitations to productionproduction

When water and nutrients are plentiful light is th li iti s It is l d i is the limiting resource. It is analyzed in terms of three factors: available solar radiation, interception by the crop canopy,

d th ffi i f i f di ti and the efficiency of conversion of radiation to biomass

C l iConclusions

Both interception and radiation use efficiency are subject to genetic manipulation.

When water is limiting biomass production When water is limiting, biomass production can be predicted from a transpiration efficiency and a knowledge of the amount of water transpired water transpired.

The transpiration efficiency is not constant, but decreases as the vapor pressure deficit f th i iof the air increases

C l iConclusions

Transpiration efficiency is subject to genetic manipulation and depends on internal CO2concentrationconcentration

Appropriate field instrumentation can help in identifying cultivars with high RUE or high TE

For references, questions, or to access thi t ti t this presentation go to

www.decagon.com

or

www.junipersys.comj p y m

ReferencesKunkel, R. and G. S. Campbell. 1987. Maximum potential potato yield in the

Columbia Basin USA: Model and measured values. Am. Potato J. 64:355Monteith, J. L. 1994. Principles of resource capture by crop stands. In Monteith, , p p y p ,

J. L., R. K. Scott and M. H. Unsworth eds. Resource Capture by Crops. Nottingham University Press.

Stöckle, C.O. and A.R. Kemanian. 2009. Crop radiation capture and use efficiency: A framework for crop growth analysis In Crop Physiology (Vefficiency: A framework for crop growth analysis. In Crop Physiology (V. Sadras and D. Calderini Eds). Academic Press, Elsevier Inc. p 145-170.

Campbell, G. S. and F. K. van Evert. 1994. Light interception by plant canopies: efficiency and architecture in J L R K Scott and M H Unsworth edsefficiency and architecture. in J. L., R. K. Scott and M. H. Unsworth eds. Resource Capture by Crops. Nottingham University Press.

Goudriaan, J. and J. L. Monteith. 1990. A mathematical function for crop growth. Annals of Botany 66:695-701.

ReferencesTaiz, L., and E. Zeiger. 1991. Plant Physiology. Benjamin/Cummings, N. Y.Briggs, L. J. and H. L. Shantz. 1913. The water requirement of plants; II A

review of the literature. USDA Bureau Plant Industry Bull. 285.yEarl, H. J. and A. E. Walden. 2009. Why does dark adapted leaf conductance

predict water use efficiency of soybean? Agronomy Abstracts AnMtgsAbstracts2009.55299

Tanner, C. B. and T. R. Sinclair. 1983. Efficient water use in crop production: research or re-search? In H. M. Taylor et al. (ed.) Limitations to Efficient Water Use in Crop Production. ASA, Madison WI p. 1-27.

Richards R A G J Rebetzke M Watt A G Cordon W Spielmeyer and RRichards, R. A., G. J. Rebetzke, M. Watt, A. G. Cordon, W. Spielmeyer and R. Dolferus. 2010. Breeding for improved water productivity in temperate cereals: phenotyping, quantitative trait loci, markers and the selection environment. Functional Plant Biology 37:85-97.