Effects of C 0 2 concentration
on photosynthesis, transpiration and productionof greenhouse fruit vegetable crops^e^STfPromotor: Dr. ir. H. Challa
hoogleraar in de Tuinbouwplantenteelt
in het bijzonder de beschermde teelt

Stellingen
Verbreding en verbetering van de C02-toediening in kassen zal de produktie van de
Nederlandse glastuinbouw met miljoenen guldens perjaar verhogen.

Stomata have been delegated the task of providing food while preventing thirst.
(Raschke, 1976).

3

ledere 100 umol mol'' verhoging van de C02-concentratie in hettrajekt van 200 tot
1200 umol mol'1 leidt bij tomaat, komkommer en paprika planten tot 3 à 4 % en bij
aubergine tot circa 11% verlaging van de stomataire geleidbaarheid.
(Oitproefschrift).

4

In een niet geventileerde kas heeft C02-dosering slechts beperkte invloed op deverdamping van een gewas.
(Ditproefschrift).

5

Het vóórkomen van een 'midday depression' bij een gewas ineen kasisgrotendeels
te verklaren uit het dagelijks verloop van de omgevingsfaktoren.
(Ditproefschrift).

6

Verhoging van de C02-concentratie veroorzaakt een verschuiving van allocatie vanbiomassaten gunstevandevruchten,alleen indienC02-toedieningeentoename van
het aantal vruchten aan de plant teweeg brengt(Ditproefschrift).

7

HeteffektvandeC02-concentratieopdeproduktievanvruchtgroentengewassen laatzich goed beschrijven door de vuistregel X = 1.5 * (1000/C)2, met C de C 0 2
concentratie in umol mol'1 en X de relatieve verhoging van de produktie in % per
100 umol mol"1 C 0 2 .
(Ditproefschrift).

Pulsgewijs (of intermitterend) doseren heeft geen aantoonbare voordelen boven
continu doseren.
(Ditproefschrift).

Gezien de sterke fluctuatie van de C02-concentratie van de buitenlucht, zou
optimalisatie van deC02-doseringgebaseerd moetenworden op momentane, lokale
meting van de C02-concentratie buiten de kas.

/jdofcfcos \gyg
10 Hetisgewenstbijoptimalisatievan deCOj-dosering nietalleen economische, maar
vooral ookecologischedoelstellingen natestreven;inde praktijk isditte realiseren
door aan de ecologische effekten economische konsekwentieste verbinden.
11 Alsmaatregelen ter beperking van hettoenemend broeikaseffekt worden uitgesteld
tot de modellen hieromtrent gelijkluidende resultaten geven, zullen de thans
waarneembare tendensen tot veranderingen in het klimaat statistisch significant
worden.
12 Het milieu zou ermee gediend zijn als de Landbouwuniversiteit aan landbouwkundigepromovendidetitel 'Doctorinde Landbouw-en Milieuwetenschappen' pasverleende nadat zij ook in de milieuwetenschappen een proevevan bekwaamheid
hadden afgelegd.
13 HetfeitdatdeNefyto(NederlandseStichtingvoorFytopharmacie)sterkpleitvooreen
Europese regeling van bestrijdingsmiddelengebruik (Platform, oktober 1993) iseen
teken van geringefiducie inde besluitvaardigheid van deEG.
14 Detoenemende commercialisering en daaruit voortvloeiende eigen profilering van
onderzoeksinstanties en voorlichtinggevende organisaties verzwakt het landbouwkennissysteemen daarmeedeontwikkelingvande Nederlandse land-entuinbouw.
15 Door de schaalvergroting in het basisonderwijs gaan minder kinderen lopend offietsend naar school: gewenning van de schooljeugd aan het dagelijks gebruikvan
de auto is schadelijk voor de volksgezondheid en voor het verkeersbeeld in detoekomst.

Stellingen behorendbijhetproefschrift'Effects of COj concentration on photosynthesis, transpiration and production ofgreenhouse fruitcrops', doorEllyM.Nederhoff. Wageningen, 25 oktober1994.

JJMQSVÖV^SC

Elly M. Nederhoff

Effects of C 0 2 concentration
on photosynthesis, transpiration and productionof greenhouse fruit vegetable crops

Ontvangen
24OKT. 1994
UB-CARDEX

Proefschrift
ter verkrijging van de graad vandoctor in de Landbouw- en Milieuwetenschappen,
op gezag van de rector magnificus,
Prof. Dr. C.M. Karssen,in het openbaar te verdedigen
op dinsdag 25 oktober 1994
des namiddags te vier uur
in de aula van de Landbouwuniversiteit te Wageningen

W\- S0^Q ^The work for this thesis was conducted at

The Glasshouse Crops Research Station
P.O.Box 8 - 2670 AA Naaldwijk - The Netherlands
telephone 01740-36700 - fax 01740-36835

CIP-GEGEVENS VOOR DE KONINKLIJKE BIBLIOTHEEK, DEN HAAG
Nederhoff, Elly M.
Effects of C 0 2 concentration on photosynthesis, transpiration and production ofgreenhouse fruit vegetable crops.
Dissertation Wageningen.- With réf.- With summary in DutchISBN 90-5485-318-2
Subject headings:carbondioxide, C 0 2 , glasshouse,greenhouse, photosynthesis,
production, transpiration.

Abstract
Nederhoff E.M., 1994. EffectsofC02 concentrationonphotosynthesis, transpirationandproduction of greenhouse fruit vegetable crops. Dissertation. Agricultural University,
Wageningen, The Netherlands. Summariesin English and Dutch. 213 p.
The effect ofthe C 0 2 concentration ofthe greenhouse air (C) in the range 200
to 1100 umol mol"' was investigated in tomato (Lycopersicon esculentum Mill.),cucumber (Cucumis sativus L), sweet pepper (Capsicum annuum L.) and eggplant(Solanum melongena L ) , grown in greenhouses.
The effect of C on canopy net photosynthetic C 0 2 assimilation rate (orphotosynthesis, P)was expressed by a set of regression equations, relating Pto PAR, C
and LAI.A rule of thumb ('C0 2 -rule') was derived, approximating the relative increaseof P caused by additional C 0 2 at a certain C. This C0 2 -rule is: X = (1000/C)2 * 1.5(X in % per 100 umol mol" 1 , and C in umol m o l ' ) . Two models for canopy
photosynthesis were examined by comparing them with the experimental
photosynthesis data. No 'midday depression' in Pwas observed.
The effects of C on leaf conductance (g) and on rate of crop transpiration (£)
were investigated. An increase of 100 umol mol"1 in C reduced g by about 3-4% insweet pepper, tomato and cucumber and by about 11% in eggplant. The effect of C on
Ewas analyzed by combining the regression equation for g with the Penman-Monteithequation for £ C had only a relatively small effect on E, owing to thermal andhydrological feedback effects. The decoupling of g and Ewas quantified. No timedependent variation or 'midday depression' in £wasobserved,and no significant effectof C on average leaf temperature was established.
In five experiments, the effect of C on growth and production and on specificfeatureswere analyzed: light useefficiency was increased by about 10to 15% per 100
umol mol"1 increase in C; fruit set of sweet pepper was greatly increased by high C;
allocation of biomass to fruits was increased by high C in sweet pepper and cucumber;specific leaf area (SLA) was reduced by 15 to 20% at 150 to 250 umol mol ' increase
in C (except in cucumber); dry matter content (DMC) of vegetative organs slightly
increased at high C (also not in cucumber); fruit production (dry weight) was mostaffected by C in sweet pepper; fresh weight fruit production per unit C 0 2 was highest
in cucumber; fruit quality was not influenced by C. High C promoted the 'short leaves
syndrome' in tomato and 'leaf tip chlorosis' in eggplant, probably related to calcium
and boron translocation, respectively. The observed effect of C on production waslarger than expected on the basis of the C0 2 -rule. Intermittent C 0 2 supply (ICS) could
under normal ventilation accomplish only a limited increase in average C, and hence
a limited increase in production. No physiological advantages of ICS were revealed.
Key words: carbon dioxide, C 0 2 concentration, conductance, cucumber, decoupling,
eggplant, feedback, glasshouse, greenhouse, growth, photosynthesis, production,
stomata, sweet pepper, tomato, transpiration.

Opgedragen aan mijn vader
en aan de nagedachtenis van mijn moeder

Voorwoord
Een proefschrift schrijven was voor mij al jaren een wens en in het
najaar van 1990 kreeg ik de gelegenheid dit voornemen uit te voeren. Bij mijn
onderzoek op het Proefstation in Naaldwijk aan licht, ventilatie, fotosynthese en
groei was vanzelf ' C 0 2 ' komen bovendrijven, en de verzamelde informatie
leendezich goedvoor een proefschrift. Ermoesten nogeen aantal experimenten
worden verricht, maar daarvoor wist ik mij verzekerdvan uitstekende assistentie
in de persoon van Erik de Ruiter. Als promotor stelde ik me voor Prof. Challa in
Wageningen, en gelukkig bleek hij bereid die taak op zich te nemen.Toen ook
thuis de randvoorwaarden in ordewaren,ben ik eind 1990gaan schrijven:eerst
artikelen voor wetenschappelijke tijdschriften en vervolgens de ontbrekende
stukken om een proefschrift samen te stellen.
Met genoegen en voldoening kijk ik nu terug op de afgelopen vier jaar,
waarin dit boekje tot stand is gekomen. Graag wil ik op deze plaats eenieder
bedanken, zonder wie het nooit zou zijn geworden wat het nu is.
In de eerste plaats dank ik van harte mijn leermeester, Prof. H. Challa.
Hij heeft alle stukken inverschillende stadiadoorgelezen enwist daarbij feilloos
de zwakke plekken te vinden, om mij vervolgens weer op het goede spoor
zetten. Hugo, ik waardeer het bijzonder dat je altijd een paar uur voor mij konvinden, ondanks alle drukte, en veelal ten koste van je vrije tijd. Bedankt voorde leerzame, efficiënte en heel plezierige samenwerking !
Alle experimenten voor dit proefschrift zijn verricht op het Proefstationvoor Tuinbouw onder Glas in Naaldwijk. Het bestuur, de direktie en het
voormalig direktieteam (de heren Kooistra en van Oosten) van het Proefstation
ben ik zeer erkentelijk dat ze mij tijd en gelegenheid hebben gegeven om tepromoveren. Ook dank ik Gerard Welles (hoofd van de afdeling Teelt en
Kasklimaat) en Sjaak Bakker (hoofd van de sektie Kasklimaat) voor het in mij
gestelde vertrouwen.
Alle medewerkers van de sektieen de afdeling bedank ik voor de primasamenwerking, waarbij ik enkele personen met name wil noemen. In de eerste
plaats Erik de Ruiter, die door zijn zeer bekwame assistentie bij velerlei
werkzaamheden en dankzij zijn zelfstandige aanpak mij veel tijd voor schrijven
heeft gegeven. Ad de Koning, kollega promovendus, bedank ik voor dewaardevolle diskussies en nieuwe inzichten en voor de gezellige momenten op
en buiten het werk. Met Sjaak Bakker heb ik de afgelopen 12V2jaar alle 'lief enleed' van het werk gedeeld, de eerste jaren als kamergenoot en de laatste jaren
heeft hij als mijn direkte chef mijn belangen bepleit.

Verder wil ik bedanken: Rein de Graaf, Ton Rijsdijk en Gonnie
Bergman, die belangrijk hebben bijgedragen aan de arbeidsintensieve
porometingen en Reinspeciaalvoorzijn verdampingsmetingen;JoopVegter, diedestijds het fotosyntheseonderzoek heeft uitgevoerd; Gerard van Holsteijn, bij
wie ik altijd terecht kon met vragen over praktijktoepassingen; Jan van Uffelenen Krijn Buitelaar, met wie ik in enkele experimenten heb samengewerkt.
Op de achtergrond, maar niet minder belangrijk, was voor mij de hulp
van Leen Spaans, Ben Zonneveld en Leo van de Bos bij diverse computeraangelegenheden en van Bernhard van der Kaay op gebied van statistiek.
Bernhard,ook bijzonder bedankt voor het uitpuzzelen vandevorm vande C 0 2 vuistregel.Wim van Winden bedank ikvoor hetopsporen van literatuur en voor
zijn adviezen over de Engelsetaal. Bij hetexperimentele werk heb ik steeds een
beroep kunnen doen op de medewerkers van de Tuin en de Technische Dienst
van het Proefstation. Aan al deze en aan alle niet genoemde Naaldwijkse
kollega's mijn welgemeende dank. Hans Gijzen en Ep Heuvelink ben ik
erkentelijk voor hun 'Wageningse' inspiratie, David Lawlor (Rothamsted, U.K.)
voor zijn kritisch kommentaar op enkele stukken en Saskia Prinsen voor delaatste kontrole van delen van het manuscript.
Op het thuisfront heeft Leo, behalve voor onmisbare morele steun, ook
gezorgd voor praktische ondersteuning op gebied van computers. Bovendien
heeft hij alle grafieken voor dit proefschrift vervaardigd. Leo, 'ons proefschrift'
is af !! Het was fijn dat je, als unieke niet-altijd-fulI-time werkende huisvader,vaakvoor thuis beschikbaar was.Aan Paulien,Marloes enJoris heb ikte danken
dat ik in de afgelopen jaren part-time werkte en daardoor ook heel veel andere
leuke dingen heb gedaan. Verder bedank ik mijn toegewijde hulpen. Mijn
ouders ben ik dankbaar voor zoveel, onder andere voor de kansen die ze mij
van jongs af aan gegeven hebben. Graag draag ik dit proefschrift aan hen op.
Het Proefstation in Naaldwijk zal binnenkort voor mij verleden tijd zijn.
Ik heb er altijd met veel plezier gewerkt, dankzij de kollegiale werksfeer, devanzelfsprekende samenwerking en de open gedachtenuitwisseling. Daarbij
komt dat het werken voor de praktijk gewoon leuk is en bijzonder motiverend.
Het hier beschreven onderzoek is, zoals al het werk van het
Proefstation, uitgevoerd met als doel de Nederlandse glastuinbouw verder teontwikkelen. Ik hoop dat de glastuinbouw sterk en op een gezonde basis zal
kontinueren.Mijn wens isdat de resultaten van mijn werk mogen bijdragen aan
het optimaliseren van het telen onder glas.

Maasdijk, september 1994

XI

Contents
ABSTRACTV

VOORWOORDVII

CONTENTSXIACCOUNTXVAPPENDICES

XVII

I
II
III

Acronyms
Symbols and parameters with values and units
Unit conversions

XVII
XVII
XX

1 GENERAL INTRODUCTION
1.1 FIELD OF RESEARCH
1.2 C 0 2 ENRICHMENT IN PRACTICE
1.2.1 Carbon dioxide properties and units
1.2.2 History of C 0 2 enrichment and related research
1.2.3 Current methods of C 0 2 enrichment
1.2.4 Harmful gases
1.2.5 Rate of C 0 2 supply in greenhouses
1.2.6 Control and strategy of C 0 2 supply
1.3 DESCRIPTION A N D ANALYSIS OF THE PROBLEM
1.3.1 Problem description
1.3.2 Problem analysis
1.4 RESEARCH QUESTIONS, OBJECTIVES A N D APPROACH
1.4.1 Restrictions to the research
1.4.2 Research questions
1.4.3 Objectives of the thesis
1.4.4 Approach and structure of the thesis

2 EFFECTS OF C 0 2 ON CANOPY NET PHOTOSYNTHESIS
2.1 INTRODUCTION
2.1.1 Outline of the problem
2.1.2 Objectives
2.1.3 Approach and structure of the chapter
2.2 MATERIALS A N D METHODS
2.2.1 Crops, greenhouses and environmental factors
2.2.2 Principle of the photosynthesis measurements
2.2.3 Photosynthesis measurements
2.2.4 Data processing
2.3 ACCURACY OF THE MEASUREMENTS
2.3.1 Type of errors

1
1
5
5
5
6
8
9
10
12
12
13
15
15
16
16
17

19
19
19
21
21
22
22
24
25
27
28
28

XII

2.4

2.5

2.6

2.7

2.8

2.3.2 Incidental errors in the measurement
2.3.3 Regular measuring error
2.3.4 Conclusion
REGRESSION MODEL A N D CHARACTERISTICS OF CANOPYPHOTOSYNTHESIS
2.4.1 Regression model
2.4.2 Regression models fitted to the measurements
2.4.3 Characteristics of canopy photosynthesis
2.4.4 Remarks and conclusions
TIME-DEPENDENT VARIATION IN PHOTOSYNTHESIS
2.5.1 Midday depression
2.5.2 Approach
2.5.3 Results
A 'C0 2 -RULE' DERIVED FROM THE MEASUREMENTS
2.6.1 Introduction
2.6.2 Approach
2.6.3 Results and discussion
TEST OF T W O EXISTING MODELS
2.7.1 Models, parameters and units
2.7.2 Modified Acock model
2.7.3 Modified Thornley model
2.7.4 Procedure
2.7.5 Results
2.7.6 Discussion
DISCUSSION

3 EFFECTS OF C 0 2 O N LEAF CONDUCTANCE AND CANOPY
TRANSPIRATION
3.1 INTRODUCTION
3.1.1 Outline of the problem
3.1.2 Stomata
3.1.3 Other conductances
3.1.4 Diffusion
3.1.5 Units of conductance
3.1.6 Stomatal action
3.1.7 Relation between conductance and transpiration
3.1.8 Decoupling factor
3.1.9 Leaf temperature
3.2 OBJECTIVES A N D APPROACH
3.2.1 Objectives
3.2.2 Experimental approach
3.3 METHODOLOGY
3.3.1 Set-up of experiments
3.3.2 Measuring conductance3.3.3 Measuring transpiration

28
29
31
32
32
33
34
37
38
38
38
38
41
41
41
43
44
44
45
46
47
49
52
55

57
57
57
59
59
60
60
60
61
62
63
64
64
64
66
66
68
68

XIII

3.4

3.5

3.6

3.7

3.3.4 Analysis of conductance measurements
69
3.3.5 Analysis of transpiration measurements (Penman-Monteith model) . 70
3.3.6 Coupling between conductance and transpiration
72
3.3.7 Data processing
72
EFFECTS OF C 0 2 O N LEAF CONDUCTANCE A N D CANOPY
TRANSPIRATION OF SWEET PEPPER
74
3.4.1 Materials and methods
74
3.4.2 Results
76
3.4.3 Discussion
81
EFFECTS OF C 0 2 O N CONDUCTANCE A N D TRANSPIRATION OF
TOMATO A N D CUCUMBER
84
3.5.1 Materials and methods
84
3.5.2 Results
86
3.5.3 Discussion
90
EFFECTSOF C 0 2 O N LEAFCONDUCTANCE A N D ESTIMATED CANOPY
TRANSPIRATION OF EGGPLANT
93
3.6.1 Materials and methods
93
3.6.2 Results
96
3.6.3 Discussion
96
SYNTHESIS A N D DISCUSSION
102
3.7.1 Effects of C 0 2 concentration on leaf conductance102
3.7.2 Calculated effect of C 0 2 concentration on transpiration (decoupling) 102
3.7.3 Time-dependent variation in transpiration (midday depression)105
3.7.4 Consequences of stomatal closure for leaf temperature
106
3.7.5 Approach and results considered107

4 EFFECTS OF C 0 2 CONCENTRATION ON GROWTH AND
PRODUCTION

109

4.1 INTRODUCTION
109
4.1.1 Outline of the problem and approach for research
109
4.1.2 Growth rate (GR) and light use efficiency (LUE)110
4.1.3 Fruit set
110
4.1.4 Allocation of dry matter
111
4.1.5 Fruit properties
112
4.1.6 Morphological adaptations to high C 0 2
112
4.1.7 Nutrient concentration in leaves
113
4.1.8 Intermittent C 0 2 supply (ICS)114
4.2 OBJECTIVES A N D EXPERIMENTS
115
4.2.1 Objectives
115
4.2.2 Experiments
115
4.3 EFFECTS OF CONTINUOUS A N D INTERMITTENT C 0 2 SUPPLY O NGROWTH A N D PRODUCTION OF CUCUMBER
116
4.3.1 Growth and production of cucumber at two C 0 2 concentrations(cucumber experiment 1)

116

4.3.2 Production of cucumber under continuous or intermittent C 0 2(cucumber experiment 2)

120

XIV
4.4 EFFECTS OF CONTINUOUS A N D INTERMITTENT C 0 2 SUPPLY O NFRUIT SET A N D YIELD OF SWEET PEPPER
124
4.4.1 Introduction
124
4.4.2 Materials and methods
124
4.4.3 Results
125
4.5 EFFECTS OF C 0 2 , PLANT DENSITY A N D PRUNING O N LEAF
DEFORMATION (SLS) A N D FRUIT PRODUCTION OF TOMATO
130
4.5.1 Introduction
130
4.5.2 Materials and methods
132
4.5.3 Results
136
4.5.4 Discussion
137
4.6 EFFECTS OF C 0 2 O N LEAF TIP CHLOROSIS (LTC) A N D FRUITPRODUCTION OF EGGPLANT
143
4.6.1 Introduction143
4.6.2 Materials and methods
144
4.6.3 Results
146
4.6.4 Discussion
150
4.7 SYNTHESIS A N D DISCUSSION
153
4.7.1 Structure153
4.7.2 Growth and production of cucumber
155
4.7.3 Growth and production of sweet pepper
155
4.7.4 Growth and production of tomato
157
4.7.5 Hypothesis explaining species-specific features
159
4.7.6 Growth rate (GR) and light use efficiency (LUE)161
4.7.7 Fruit set
162
4.7.8 Allocation of dry matter
163
4.7.9 Morphological characteristics
164
4.7.10 Fruit production
166
4.7.11 Fruit properties
168

5 FINAL DISCUSSION
5.1
5.2
5.3
5.4
5.5

RESULTS CONSIDERED
THE 'C0 2 -RULE'
SIDE EFFECTS OF C 0 2 ENRICHMENT
INTERMITTENT C 0 2 SUPPLY (ICS)EVALUATION OF THE APPROACH

RECOMMENDATIONS FOR PRACTICAL HORTICULTURE

171
171
172
176
178
180

183

SUMMARY187

SAMENVATTING193

REFERENCES199

CURRICULUM VITAE

217

XV

Account
The chapters 2, 3 and 4 are compilations of published articles, which wereenhanced when necessary and reorganized to fit into the structure of the thesis.
CHAPTER 2
Nederhoff E.M. & J.G. Vegter, 1994. Photosynthesis of stands of tomato,
cucumber and sweet pepper measured in greenhouses under various C 0 2
concentrations. Annals of Botany 73: 353-361.
Nederhoff E.M. & J.G. Vegter, 1994. Canopy photosynthesis of tomato,
cucumber and sweet pepper in greenhouse: measurements compared tomodels. Annals of Botany 73: 421-427.
CHAPTER 3
Nederhoff E.M., A.A. Rijsdijk & R. de Graaf, 1992. Leaf conductance and rateof crop transpiration of greenhouse grown sweet pepper {Capsicum annuumL.) as affected by carbon dioxide. Scientia Horticulturae 52: 283-301.
Nederhoff E.M. & R. de Graaf, 1993. Effects of C 0 2 on leaf conductance andcanopy transpiration of greenhouse grown cucumber and tomato. Journal of
Horticultural Science 68: 925-937.
Nederhoff E.M., 1992. Effects of C 0 2 on greenhouse grown eggplant {Solanum
melongena L). I: Leaf conductance. Journal of Horticultural Science 67:
795-803.
CHAPTER 4
Nederhoff E.M. & J.A.M. van Uffelen, 1988. Effects of continuous andintermittent carbon dioxide enrichment on fruit set andyield of sweet pepper{Capsicum annuum L.). Netherlands JournalofAgricultural Science 36:209217.
Nederhoff E.M., A.N.M, de Koning & A.A. Rijsdijk, 1992. Leaf deformation andfruit productions ofglasshousegrowntomato{Lycopersicon esculentum Mill.)
as affected by C 0 2 , plant density and pruning. Journal of Horticultural
Science 67: 411-420.
Nederhoff E.M. & K. Buitelaar, 1992. Effects of C 0 2 on greenhouse grown
eggplant {Solanum melongena L.) II: Leaf tip chlorosis and fruit production.
Journal of Horticultural Science 67: 805-812.

Appendices (symbols andunits)

XVII

Appendices
Appendix I

acronymAcronyms

meaning

units

CER
DM
CP
DMC
ICS
LAI
LAR
LTC
LUE

carbon dioxide exchange rate
dry mattercompensation point
dry matter content%
intermittent C 0 2 supply
leaf area index, leaf area per area cropped ground arealeaf area ratio (leaf area per plant dry weight)
cm 2 g ,2 „-1
leaf tip chlorosis
light use efficiency in relation to photosynthesis
ugJ"1or quantum yield
mol mol 'LUElight use efficiency in relation to dry matter production
g MJ'
2
PAR photosynthetically active radiation (400-700 nm), light energy fluxWm
2or photosynthetically active radiation, photon flux
umol m" s 2 „-1
PRESS predicted error sum of squares
RH
relative humidity%
SLA
specific leaf area
cm 2 g'SLS
short leaf syndrome
VPD vapour pressure deficitkPa

Appendix II Symbols and parameters with values and units

symbol
a
aA
ar
b
bA
br
C
C'
cc
cg
c,
cx

meaning [value]
constant relating model and measurement
constant in the Acock photosynthesis model [8.5E-5]
constant in C0 2 -ruleconstant relating model and measurement
constant in the Acock photosynthesis model [2.1 E-2]
constant in CO,-rule
C 0 2 concentration
C 0 2 concentration after unit conversion
unit conversion for C 0 2 [1.83E-3]
unit conversion [1000]
unit conversion considering time [3600]
parameters in regression equation for conductanceunits
m3 J '

m 2 s J"1
% (100 mol mol"1) i\-iumol mol"1g m"3
3g m" (umol mol" 1 )_1
g kg"1s h"1

XVIII

Appendices (symbols and units)

continue Appendix II Symbols and parameter with values and units

D
D
E
F.
Gc
8
h
1
1'

J
Jo
K
K
L
Lc
m
N
N
P
Pe
Px

P

Q
Re

R'
R
r
S
So

Sc
s
T
T
t
t»

V
u,V

X
z

vapour pressure deficit
diffusion coefficient
rate of transpiration of the crop
ratio of average PAR at leaf level relative to top
rate of C 0 2 emission from the ground
conductance for water vapour
average height of the greenhouseincident PAR (400-700 nm), photon flux
1 derived from global radiation
incident PAR (400-700 nm), light energy flux
J on top of the canopy
extinction coefficient for light
coupling between conductance and transpiration
leaf area index (LAI)
rate of loss of C 0 2 to the outsidetransmission coefficient for light
concentration of N 2 0
umol mol"1
number of moles
photosynthesis rate of canopy
photosynthesis rate of leaves
parameters in regression equation for photosynthesispressure
global radiation
crop dark respiration rate
parameter for crop dark respiration per leaf area
molar gas constant [8.31]
resistance for water vapour
incident light flux (PAR), during previous week
S on top of the canopy
rate of supply of carbon dioxide
slope of saturated water vapour curve at air temperaturetemperature
absolute temperaturetime
parameters in regression of leaf temperaturevolumewind speed
relative effect of the C 0 2 concentration
path lengthkPam sg m"2 s 1—
2 1
g m" h"mm s"1mumol s'm" 2umol s'm" 2
Wrrï2
WnV2
—
2

-2

m m
g m"2 h"'——g h"1m"2 (ground)g s'm" 2 (leaf area)
Pa
Wrrï2
1 2
g h" m (ground)g s"1m"2 (leaf area)
Jm o l ' PC1
s m"1
WITÏ2

Wm"2
g m 2 h1
kPa K"'CKs or hm3
m s"1% (100 umol mol"1)"'mAppendices (symbols andunits)

XIX

continue appendix II Symbols and parameter with values and units
Greekainitial light use efficiency
or light utilization or photosynthetic efficiency
convertible to quantum yieldßparameter for maximum photorespirationyapparent psychrometric constant [0.067]
e
error
AT
difference in temperature0
curvature in the photosynthesis-light curve [0.95]\
air exchange rate$'
air exchange factorA.
vaporization energy of water [2.45E6]
pc
gas density of C 0 2 [1.83 at 20 °C and 101.3 kPa]p*c p volumetric heat capacity of air [1240]
T
conductance to C 0 2 transfer

subscripts
Aabcbelonging to the (modified) Acock modelof air (VPD, temperature) or of the ambient (C0 2 concentration)of boundary layer (conductance)of carbon dioxide
or: at canopy level, i.e. incident (global radiation, PAR)or: of the canopy, of the crop (photosynthesis, respiration)calc

calculated

ec
empty
g
L

with estimated conductance (transpiration)
without crop
gross
leaf, of leaves

1leaf, of leaves

f-a
m
max

between leaf and air (VPD, temperature)maximum
maximummeanmean, averagemeas measured (transpiration)model modelledmcwith measured conductance (transpiration)nnet (radiation, photosynthesis)0
on top of the canopy (radiation)paccording to the Penman-Monteith equation (transpiration)rradiation based (transpiration)Tbelonging to the (modified) Thornley modelt

at time t

gJ"1
mol mol"1
g m"2 s'kPa K
K or C
m h"1
h"'
Jkg"1
kg m"3
Jm"3 K"1
m s"1

XX

Appendices

Appendix III(symbols and units)

Unit conversions

a. Carbon dioxide
dimension
ratio of C 0 2 to air, in volume:units
1 vpm = 1 ul I"1 = 1 ml m"3 =1 cm m 3 = 0.0001 % (volume)

ratio of C 0 2 to air, in moles:

1 ppm = 1 umol mol"1 = 1 mmol kmol"1

ratio of C 0 2 to air, in weight:

1 mg kg"1 = 0.0001 % (weight)

weight of C 0 2 per volume of air:

1 mg m"3 = 1 ug I"1moles C 0 2 per volume of air:

1 umol m"3partial pressure:

1 Pa = 10 ubar

Conversion (at 20 °C and 101.3 kPa):
1 vpm = 1 ppm = 1.53 mg kg"1 = 1.83 mg m"3 = 41.6 umol m 3 = 0.101 Pa(after Lawlor, 1993)
b. Carbon dioxide flux (C0 2 exchange rate, photosynthesis rate)
1 g m"2 h"1 - 6.3 umol m"2 s"1 (at 20 °C and 101.3 kPa)c. Conductance
1 mm s"1 « 0.042 mol m 2 s 1 (at 20 °C and 101.3 kPa)d. Photosynthetically Active Radiation
1 W m 2 PAR - 4.5 umol m 2 s"1 PAR(McCree, 1972; Meek et al., 1972)
e. Global radiation «• Photosynthetically Active Radiation
1 W m"2 global radiation - 2 umol m"2 s"1 PAR(Thimijan & Heins, 1983; Meek et al., 1984)
f. Light Use Efficiency
1 ug J 1 - 0.0052 mol mol"1

/.1 Field of research

1 General introduction
1.1

FIELD OF RESEARCH

Carbon isaprincipal element for life, asitcomprises amajor part of thedry matter in living organisms (about 50%, Levanon et al., 1986; about 30-40%
in tomato plants, Ho, 1976). The carbon in the terrestrial food pyramid is
acquired almost exclusively by green plants,taking up carbon dioxide gas (C0 2 )from the surrounding air. C 0 2 enters the stomatal cavities of the plant throughthe stomata in the leaf surface, and is assimilated to carbohydrates at thechloroplasts under the use of light energy. The rate of C 0 2 assimilation (i.e.
photosynthesis) is influenced by the amount of C 0 2 present in the vicinity of theplant. Supply of additional C 0 2 to the surrounding air usually accelerates theassimilation rate, and hence promotes the production of agricultural crops(Kimball, 1986). This effect is based on decrease of the C 0 2 uptake limitationand suppression ofthe photorespiration. Theeffect of the C 0 2 concentration (C)of the air on the production of greenhouse crops is generalized in Fig.1.1.
Increase of C can be achieved relatively easily in aclosed environment
such asagreenhouse. Theterm greenhouse is used here for astructure covered
with glass or plastic of considerable size (at least man's height), in which a crop
can be grown; it protects the crop from external conditions and enables a
grower to manipulate the crop's environment. C, as well as temperature andhumidity of the air, are the main environmental conditions that are controlled
in greenhouses.
C 0 2 enrichment, i.e. supply of either pure C 0 2 or C0 2 -rich combustiongas, is a powerful tool to enhance the horticultural production. It has becomecommon practice in the greenhouse industry (see section 1.2.2). Without
enrichment, C may drop below the normal outside atmospheric concentration,
which is about 350 umol m o l 1 at present. Enrichment in a closed greenhouseaims at raising C up to twice or thrice this atmospheric concentration:
recommended is 700 to 900 umol mol"1 (Mortensen, 1987). During ventilation,
the achieved concentration isusually (far) lower, dueto lossof apart ofthe C 0 2
supplied by exchange of greenhouse air and outside air. The C range occurringin a well controlled greenhouse cultivation varies roughly from 200 to 1200
umol mol"1.
The favourable effect of high C is particularly valuable at highradiation,becausethe rateofphotosynthesis increaseswith increasing radiation.

1

Chapter 1 General introduction__ _160^ 140vPO^""*—_-^^^fe__^^^^^Mfl^^^^^B^^^^^^m^^^^^^^^^^^v^^^^^^^^^^^
^^^^^
/^^
_- - - —
.^
- ^~

120C

O
fi 100u

1 80-

/

.

"

•

/

>

/

4-»

-5 4 0 <D

^

-

y

Q.
0) 6 0 "

20-

o0

!

200

1

400

1

600

1 •

800

1

1000

1

1200

C 0 2 concentration (umol mol"1)
Fig.1.1 Relativeproduction (%) ofgreenhouse fruit vegetable cropsas function ofthe"average C02 concentration(pmolmot1) during thecultivation, with theproduction at
340 umol mot' asreference (100%).
• • I B 95%confidence interval of themeanof theobservations
95% confidence interval of the observations.
After Nederhoff (1987), revised by H.W. de Ruiter.Sources: Anonymous, 1984 (Grower 101(2):30);
BuitelaarANederhoff, 1991(Croenten+Fruit/Clasgroenten1(39):32-33);Calvert&Slack,1975(J.Hort.Sci.
50: 61-71); Frydrych, 1984 (Acta Hort. 162:271-278); Hand, 1989 (Grower 112(18): 19-21); Hand &Slack, 1988(Grower 109(6):27-34); Hartz etal., 1991(J-Amer.Soc.Hort.Sci. 116:970-973); Hayman &Talent,1987(Grower 107(7):25-27);Hei) & vanUffelen, 1984 (ActaHort. 162:29-35); Heinsetal.,1984(Acta Hort. 162: 21-28); Kimball, 1983 (Agronomy ) . 75: 779-788); Kimball & Mitchell, 1979
(J.Amer.Soc.Hort.Sci.104: 515-520); Nederhoff, 1988 (Acta Hort. 229: 341-348); Nilsen et al., 1983
(Sci.Hort.20: 1-14); Peet& Willits, 1982(HortScience 17:948-949); Peet& Willits, 1984(Sci.Hort. 24:
21-32);Slack,1985(Grower 103(2):23-27); Slack& Hand, 1985(J.Hort.Sci. 60:507-516); Slack& Hand,
1986(J.Hort.Sci.61: 303-306); Slack etal., 1988(J.Hort.Sci. 63: 119-129); Uffelen & Nederhoff,1985(G+F (41)22: 40-43); Uffelen & Nederhoff, 1986 (G+F 42(1): 28-29); Willits & Peet, 1989
(Agric.For.Meteor. 44: 275-293); Yelleetal., 1990 (J.Amer.Soc.Hort.Sci. 115:52-57).

A complication is that high radiation is usually accompanied by a high rate of
air exchange for cooling and hence by agreat lossof C 0 2 from the greenhouse.
This makes it difficult to achieve high C in combination with high light. Froman environmental point of view, excessive emission of C 0 2 to the atmosphereis unacceptable. From a grower's point of view, the costs for C 0 2 supply must
be compensated by the resulting monetary benefits, i.e. C 0 2 enrichment needs
to be economically optimized.

7.1 Fieldof research

Besides the positive effects already mentioned, also negative effects oflong-term high C may occur, which may reduce the performance of the crop
later in the season. This implies that C 0 2 supply needs to be optimized byphysiological criteria aswell, thus insuring the quality of the plants and hence
the production inthe longterm. Not much isknown yet about optimization withrespect to long-term responses to C. Some aspects of this issue are to beinvestigated in the present study. A proper analysis of the problem is made insection 1.3.2, after a description of the current practice (section 1.2.3), of thegrowers' observations and of lacks in the present knowledge (section 1.3.1).
Some debate is going on in the Netherlands these days, about thedesirability of further increasingthe horticultural production,which isthe resultand even the purpose of C 0 2 enrichment. Nevertheless, in spite of an
overproduction of some fruit vegetables on macro scale at present, increase of
production isconsidered absolutely necessaryfor individual growersto enhancetheir fruit production, in order to compensate for increasing production costs
and decreasing market prices. A relatively new objective in agriculture is to
reduce the inputs (energy, fertilizers, pesticides) and the amount of waste(materials, fertilizers, pesticides, carbon dioxide, nitrous oxide) per unit output,
or vice versa, to increase the production relative to the input and the waste(increased efficiency of the production). Improving the strategy for C02
enrichment can serve to achieve both objectives: increase of production and of
efficiency.
Carbon dioxide belongs to the 'greenhouse gases' that are held
responsible for the global warming (IPCC, 1990). The present study, however,is restricted to the effects of C on greenhouse crops, from a horticultural pointof view. When C 0 2 issupplied into agreenhouse, asmaller or larger part of thisgas is released into the atmosphere. This is considered a serious drawback,which must be minimized. This study aims at optimizing the C 0 2 supply andthus minimizing the losses. Inaddition, itwill providethe necessary information
to another project in Naaldwijk, dedicated to energy use and C 0 2 emission byhorticultural enterprises inview ofthe environmental targets (Vermeulen & Van
De Beek, 1993).
The crops investigated here are the four major greenhouse fruit
vegetable crops: tomato (Lycopersicon esculentum Mill.), cucumber (Cucumis
sativus L), sweet pepper (Capsicum annuum L.) and eggplant (Solanum
melongena L). These crops are of great economic value: the figures for yield in
the Netherlands overthe year 1992, in million kgand in million Dutch guilders(with 1 Dutch guilder - 0.5 U.S.Dollar), respectively, are:tomato 610 and 820;

3

4

Chapter 1 General introduction

cucumber 470 and 490; sweet pepper 195 and 580; eggplant 27 and 73.These
products together represent 62 % of the turnover of fresh vegetables marketedat the Dutch auctions (LEI/CBS, 1993). As the value of vegetables andornamentals produced in greenhouses in the Netherlands is over 6000 million
guilders peryear, it isobvious that small improvements, e.g. in C 0 2 enrichment,
may yield a few hundreds of million guilders on an annual basis.
The experimental work has been guided by the state of the art and by
actual questions concerning C 0 2 enrichment in the greenhouse horticulturalindustry in the Netherlands (which belongs to the most advanced in the world).
Because of this demand for practical relevancy, the scope of the work is fairly
wide, so that not all aspects are thoroughly investigated for all crops.

1.2

1.2

C0 2 ENRICHMENT IN PRACTICE

1.2.1

Carbon dioxide properties and units

CO2 enrichment

Carbon dioxide (C0 2 ) is under normal conditions a colourless, acid,non-toxic gas, with boiling point -78.5 °C. The molecular weight is 44.01
g mol 1 . The gas density at normal atmospheric pressure (101.3 kPa) is 1.98
kg m"3 at 0 °C and 1.83 kg nV3 at 20 °C. The density relative to air is 1.53.
The amount of C 0 2 in the air can be defined in different dimensions
and expressed in different units (Appendix III). Unit conversion can be made byusing the ideal gas equation:
p*V=N*R*T

eqn. 1.1
3

where N is number of moles, V is volume (m ), p = pressure (Pa), T istemperature (K) and R is molar gas constant (8.31 J mol"1 K"1). In the present
work, the C 0 2 concentration of the air (C) is expressed in umol mol"1, which
numerically equals ppm, vpm, pi I"1etc. Usually umol mol"1 is used in scientific
literature, while ppm, vpm and pi I"1 are commonly used in the horticultural
practice.
1.2.2

History of CO-, enrichment and related research

One ofthe earliest stepson the path to C 0 2 enrichment may have been
the 'discovery' of photosynthesis, roughly between 1770 and 1845. The firstmodern experiments on effects of C on plants were done at the end of the lastcentury and the beginning of this century (e.g. Brown & Escombe, 1902). In thetwenties andthirties experiments were done in Englandon Ceffects on tomatoes
in greenhouses (Owen et al., 1926) and on types of fuels as source of C 0 2(Bolas & Melville, 1935). Someofthe early experiments (e.g.Brown & Escombe,
1902) were apparently disturbed by impurities in the gas supplied, whereas on
the other hand, many early trials yielded results similar to those of recent work(overview by Wittwer, 1986).
The first practical application of C 0 2 enrichment in greenhouses wasreported already at the end of the 19th century in Germany and England. Later,in 1931, C 0 2 was used on some scale in Germany (Wittwer, 1986). In the
Netherlands, afew experiments in the twenties and thirties gave no convincing
results, and consequently C 0 2 control was not commercially practised in thattime (review by Van Berkel, 1986). On the other hand, it has been common
practice for many years to heavily mulch the soil with organic material for C 0 2
enrichment.

6

Chapter 1 General introduction

The revolution came in 1961, when somegrowers intheWestland area
(inthe Netherlands) installed somesimple kerosene (paraffin) burnersfor heating
their lettuce (new fastgrowing varietiesthatwere susceptibletofrost injury). The
burners releasedthe flue gases inthe greenhouse. Somegrowers who used theirburners also by day saw a noticeable increase in growth of their lettuce plants(Steiner, 1962). This was ascribed to a higher temperature during day time andto elevated C. Also in other countries, the benefits of C 0 2 enrichment were reestablished only after 1961 (Wittwer, 1986; Bauerle et al, 1986).
Thanks to the work of Gaastra (1959) the growers' observations werequickly recognized and understood, which has certainly stimulated the fast
application and development of techniques. Also in other countries at the endof the fifties and early sixties, carbon dioxide enrichment received renewed
attention from researchers. In 1962 on the 16th International Horticultural
Congress Meetings in Brussels, numerous papers about C 0 2 were published byseveral European researchers,followed by articles intradejournals and scientificjournals.Thefirst experiments on C 0 2 atthe Glasshouse Crops Research Stationin Naaldwijk took place in 1962, with a number of vegetables and flowers (Van
Berkel & Van Winden, 1963).
Meanwhile, the practical application of C 0 2 enrichment increased
rapidly. First the simple kerosene burners or propane burners with automatedcontrol were used and later a new automated kerosene burner was introduced(Van Berkel, 1986). In 1970, natural gas (low-sulphur) became available for thegrowers in the Westland area,afuel that proved to be perfectly suitable for C 0 2
supply. Growers switched overto natural gasburners,either small burners insidethegreenhouse,or one large burner with acentral heatingsystem.Growers withacentral heater startedextractingflue gasfrom the chimney and inserting it into
the greenhouse. After 1979, an infra red gas analyzer for C 0 2 becamecommercially available. The installation of this sensor in many greenhouses
marked a revolution in the C 0 2 enrichment history.
Since the eighties, C 0 2 enrichment is a standard measure in mostgreenhouses. It was estimated in 1979 that 80% (cucumber) to 95 % (sweet
pepper) of the greenhouse areawith acentral heating system was supplied withflue gas C 0 2 , as well as the majority of the chrysanthemum, rose and lily
producing greenhouses (Van Berkel, 1986).
1.2.3

Current methods of C 0 2 enrichment

C in the (semi-)closed environment of a greenhouse frequently drops
below the ambient level, whenever the photosynthesis is larger than the C 0 2
influx by supply and air refreshment. With such so-called C 0 2 depletion, C issometimes aslow as150 umol mol"1(Heij & De Lint, 1984; Drakes, 1984). C 0 2

1.2

C02 enrichment

depletion is very unfavourable for plant growth and production (Fig. 1.1). The
principal objective of C 0 2 enrichment is therefore preventing depletion (Slack& Hand, 1986). Elevation of C considerably beyond the outside concentrationis accomplished in general only at limited ventilation.
Carbon dioxide can beobtained invariousways:aspure (liquid) carbon
dioxide gasfrom refiliable steel bottles or from abulk storagevessel (Nederhoff,
1994b);or by combustion of an appropriate fossil fuel (Hand, 1982), either withsmall burners inside the greenhouse or with one large burner belonging to acentral heating system, optionally connected with a heat storage facility(Nederhoff, 1994b). Liquid C 0 2 is normally free of impurities and is therefore
the safest source. It is easily transportable and distributable (low volume, as it
is 100% C0 2 ). Moreover, its availability is not related to production of heat.
Hence pure C 0 2 isconsidered asthe ideal method for enrichment (Hand, 1982;
Mortensen, 1987). The price of the commercially available pure C 0 2 cannot
compete usually with that of C 0 2 obtained by combustion of natural gas. The
feasibility of a C 0 2 source or system depends on economic factors.
C 0 2 from burners in the greenhouse
Combustion of fossil fuel is the oldest and still most common method
for C 0 2 enrichment. The least complicated method isusing small burners inside
the greenhouse. Such burners release heat andflue gasestogether directly in thegreenhouse (although there are some types with a chimney). A major
disadvantage isthat they are usedprimarily for heating,whereas C is consideredof minor importance. Hence, in winter the concentrations of C 0 2 and of
concomitant noxious gasesfrequently becomeextremely high,while on warmerdays no C 0 2 is supplied at all. Secondly, most small burners can operate only
on full capacity, which makes the control very inaccurate (on/off) and the
distribution of C 0 2 far from homogeneous (Nederhoff, 1994b). Thirdly, it isvirtually impossible to monitor for incomplete combustion, ascan be done witha central burner.
Central burner and heat storage
The alternative method for flue gas C 0 2 supply is by using a large
burner connected to a central hot-water pipe heating system. The flue gases ofsuch a burner can be made available for C 0 2 enrichment. Combustion
produces, besides C 0 2 , also a substantial amount of heat: 1 m3 natural gas (at20 °C and 101.3 kPa atmospheric pressure) yields about 35 MJ heat (grosscalorific value) and 1.8 kg C 0 2 (Nederlandse Gasunie, 1988). If C 0 2 isdemanded while heating is not necessary, e.g.on warmer days,the heat can be
stored in aday-to-night heat storage facility and brought into the greenhouse at7

8

Chapter 1 General introductionnight. The central heating system enables enrichment during far more hours inspring and autumn than can be achieved with small burners in the greenhouse,because C 0 2 and heat are produced outside the greenhouse and can be
introduced separately into the greenhouse. The presence of a heat storage
facility enables enrichment in summer, provided the nights are cool enough toneed heating.
The storage system is usually a well insulated hot water tank with avolume between 30 and 130 m 3 per ha greenhouse. When the watertemperature of a medium size heat storage tank (75 m3) is increased by 60 °C,
C 0 2 can be supplied during 10 hours per day at a rate of about 12 g m 2 h"1(Nederhoff, 1994b), which is almost three times the 'standard' supply rate
(section 1.2.5). In the Netherlands approximately 1000 ha of greenhouse area,
mostly used for fruit vegetable production, is equipped with a heat storage
facility.
C 0 2 distribution system
C 0 2 enrichment from a central boiler requires an adequate C 0 2transport and distribution system of sufficient capacity (Nederhoff, 1994b). The
volume of flue gases to be transported depends on the desired C 0 2 supply, on
the C 0 2 content and the temperature of the flue gas. Each 1 m 3 natural gas
combusted with the required amount of air (8.5 m3) produces almost 10 m 3 fluegas (0°C and normal atmospheric pressure) with about 10 % C 0 2 (Nederlandse
Gasunie, 1988).A centrifugal fan extracts the flue gasfrom the stack and dilutes
it with air if necessary. The gasstream isblown into amain transport duct to thegreenhouse,where it isdistributedthrough anetof perforated, polyethylene layflat ducts of 50 mm diameter.
1.2.4

Harmful gases

The composition of flue gas is determined by the fuel used and by thetechnical properties ofthe burner. Combustion gasesof sulphur-free natural gas,
asused in the Netherlands, consist of C 0 2 , H 2 0 and inevitably also some NO x .
With incomplete combustion,e.g.dueto insufficient air supply, other gases may
be released aswell, such as lethal carbon monoxide (CO), phytotoxic ethylene(C2H4) and other unsaturated hydrocarbons. The risk that supply of flue gas C 0 2
causes harmful concentrations of noxious gases in the greenhouse can be
minimized by some simple measures:• limiting the supply by maximizing the C 0 2 set point (e.g. 1200 umol mol"1)• using burners that satisfy the modern regulations for low NO x production(in last years the emission of NO x is reduced rigorously by technicalimprovements on the burners, owing to new legislation; Kooiman, 1990)

1.2

C02 enrichment• stopping the insertion of flue gases in case of incomplete combustion(a carbon monoxide device is often used to switch off the enrichment assoon as excessive CO is detected in the flue gas).
1.2.5

Rate of C 0 2 supply in greenhouses

The amount of C 0 2 to be supplied varies substantially. Under given,static conditions, the required C 0 2 supply rate to achieve a desired C, or theachievable C at acertain supply rate,can be calculated usingthe mass-balanceof C 0 2 . The rateof C 0 2 supply (Sc)equalsthe rateof photosynthesis (P) plus therate of C 0 2 loss by ventilation (Lc). C 0 2 emission from the soil is neglected. Ina simplified approximation (steady state assumed), Lc depends on the air
exchange rate (Ç in m3 m"2 h_1) and on the difference in C 0 2 concentration
between greenhouse air (C) and ambient air (Ca). Thus Sc is approximated by:
Sc = S * (C- Ca ) * pc + P

eqn. 1.2

with Sc(supply rate) and P(canopy photosynthesis rate) in g m 2 h_1 and pc thedensity of C 0 2 gas (1.83 kg m"3 at 101.3 kPa atmospheric pressure and 20 °C).
Whenever C equals Ca, Sc must only compensate P (about 1 to 5 g m"2 h"1),
independently of Ç. In other cases, Çcan be calculated with an appropriate
model for ventilation (Bot, 1983; Nederhoff et al., 1985; De Jong, 1990;
Fernandez & Bailey, 1992). To give an order of magnitude: according to Bot(1983), Çis about 20 m h ' at window opening 20% and wind speed 4 ms" 1 .
When C is 700 umol mol"1, Lc is around 13 g m ' 2 h"1 and Sc should be 14-18
g m"2 h"1. With higher ventilation rates or higher target C, the required supply
rate would be even higher, but this is only hypothetical.
A generally recommended standard (minimum) supply rate isto supply
the flue gas of 25 m3 ha"1 h"1 natural gas, equivalent to 4.5 g m"2 h"1 C 0 2 (Van
Berkel & Verveer, 1984, in accordance with Hand, 1984). This rate is usually
sufficient to maintain a high C (about 1000 umol mol"1) in a closed greenhouseand to prevent C 0 2 depletion in aventilated greenhouse. Often the supply rate
is fixed or maximized on this 4.5 g m"2 h"1 for practical or economic reasons.
Excessive supply of C 0 2 is undesired. At higher C, the C 0 2 waste byleakage and ventilation is considerable. Rapid supply while ventilators areclosed may lead to extremely high C, which, in the best case, does notcontribute to the photosynthesis, and may even be unfavourable. C in the orderof several thousands umol mol"1, which frequently occurs in cold winters ingreenhouses with hot air heaters, may cause severe injury to crops (Holländer
& Krug, 1991). Increased supply of flue gas increases the risk of reaching
threshold levels of harmful gases.

910Chapter 1 General introduction

1.2.6

Control and strategy of C 0 2 supply

C 0 2 is more or less scarce and expensive, and C 0 2 supply may havenegative side effects (section 1.3). So deciding on C 0 2 supply requires greatcare. Decision making, also C 0 2 management, involves various time horizons:
short-term (control), medium-term (strategy) and long-term (investments). C 0 2
control in a strict sense may be considered essentially as set point realization.
It comprises instantaneous actions, such as opening valves, activating burners,
starting fans or electro motors etc., for supply of pure C 0 2 or of flue gas. This
control is based on comparing the actual, measured C with a target value (setpoint). C is mostly measured with an IRGA (Infra Red Gas Analyzer) of a
relatively inexpensive type (different manufacturers, overview in Pallas, 1986).
Instantaneous C 0 2 control is usually delegated to a C 0 2 controller, either an
IRGA that can switch the C 0 2 supply on/off, or a climate control computer.
A C 0 2 strategy is defined here as a (computerized) procedure for C 0 2
enrichment with a time horizon of days or weeks, that generates the set points
for a C 0 2 controller. A computerized strategy uses a number of settings(parameters in the strategy-algorithm) that can be set by the grower. Two simple
strategies aresupply ataconstant rateand supply to aconstant level (set point).
A strategy commonly...
applied incommerciallyavailable computers (Fig. 1.2)
calculates the instantaneous set
point in dependence of the heat
demand and the ventilation rateo low(usually relative w i n d o w
Q.
opening). It uses three C 0 2 set
O mmpoints: high, low and minimum.
uHigh C (e.g. set at 800
umol mol"1) is taken as set point
as long as heating is required;
low C (e.g. 500 umol mol"1) isconditions
the set point when there is no
heating:! yesheat demand and no or little
ventilation (this ventilation level
ventilating:! no I limited I increasing! muchis set); minimum C (e.g. set at
350 umol mol"1) is aimed atwhen thegreenhouse isFig. 1.2 Exampleof a commonly applied
ventilated to a certain extent
strategy for C02 supply, with set point
dependenton theconditions (PTC,7992).
(also set).

1.2

C02

enrichment

An alternative C 0 2 strategy is known as 'pulsed' or 'intermittent' C 0 2
supply (Clough & Peet, 1981; Enoch, 1984; Mortensen, 1984). The principle issupplying C 0 2 periodically in short pulses, while the ventilation windows aretemporary closed. When the air temperature rises to a certain level, theventilators must be opened and C inevitably declines. This would theoreticallyresult in a more efficient utilization of the carbon dioxide gas. Moreover,positive effects of high C would be accomplished, while negative side effects(long-term adaptation to high C) would be prevented.
All currently used, commercially available strategies, simple or moresophisticated, require a number of settings (such as C 0 2 set points, or in theexample described above, ventilation levels). There are virtually norecommendations and no methods on atheoretical basisto estimatethe optimalvalue of the settings. Therefore, attempts are made to design alternative control
strategies, based on quantitative knowledge of the processes involved,
represented by simulation models. By comparing estimated costs and benefits,
the economically optimal C can be calculated. The processes considered arephotosynthesis, associated production and C 0 2 losses by air-exchange, and theconstraints are the actual conditions and prices of C 0 2 and of the product(Challa & Schapendonk, 1986; Seginer et al., 1986; Nederhoff, 1988). It must
be emphasized that such strategies deal with instantaneous optimization of theC 0 2 supply, ignoring the long-term aspects.

11

12

Chapter 1 General introduction

1.3

DESCRIPTION AND ANALYSIS OF THE PROBLEM

1.3.1

Problem description

After the wide-spread introduction of C 0 2 enrichment in the eighties,
it was generally experienced that C 0 2 enrichment indeed brought about thewell-known increase of production (Fig. 1.1). However, there were also clear
indications for undesired side effects of high C. For example, high C wassometimes accompanied by markedly reduced air humidity, indicating an(undesirable) reduction of crop transpiration (De Koning, 1989). This could
hamper the uptake of nutrients into the crop: e.g. high C aggravated chlorosisof leaves in eggplant (Buitelaar, 1991). Sometimes damage or adaptation wasobserved after long-term C 0 2 enrichment: in summer, high C promoted leaf
deformation intomato on awide scale (VanVelden, 1990).Theaffected tomato
cultures had a high production in summer, but performed less well in autumn.
In the past, severe leaf damage used to occur in greenhouse crops after C 0 2
enrichment (mostly with flue gases, containing harmful gases, section 1.2.4).
The various effects of C on plants have different response times. The
positive effect of C on photosynthesis is instantaneous; the effects on theassociated growth and fruit production come to expression with some delay;
possible adaptations of plants to high C are observed mostly after some weeks
of high C; reduction of transpiration, due to high C occurs almost
instantaneously,whilethe resultingnutrient deficiency may appear laterand canhave a long-lasting impact.
Many publications about C 0 2 effects on crop growth and production
have appeared since the beginning of this century (section 1.2.2). However, theunderstanding of the integrated effects of C in practical cultivations is stillinsufficient. Many questions are still actual,for example concerning effect of C
on transpiration and the impact of this on the cultivation; strategies for optimal
C 0 2 supply in relation to instantaneous conditions; pros andconsof intermittent
C 0 2 supply ascompared to supply to aconstant C; effect of C on harvest index
and fruit dry matter content.
Another problem in relation to C 0 2 enrichment, is the increased
emission of carbon dioxide gas by leakage or ventilation. The amount of C 0 2
emitted depends onthe air exchange rateandonthe C 0 2 concentration (section
1.2.5). Wasting C 0 2 gas (or wasting energy) is undesirable from an economic
point of view, and is no longer acceptable in view of the consequences for theenvironment.

1.3 Problem analysis

It will be clear that proper application of C 0 2 supply is a complicatedmatter, because positive and negative effects, short-term and long-term effects
play a role. This means that C 0 2 supply should be considered as an
optimization problem, taking into account all relevant aspects. It must beemphasized that these questions refer to practical problems, so can be studied
the best under practical conditions.
The grower decides about C 0 2 supply by choosing the actual settingsof the control device or control computer for C 0 2 enrichment (section 1.2.6).
Growers generally aim at maximizingthe annual financial outcome (yield minus
costs), which requires a high production at relatively low costs on an annual
basis. So from this point of view, the policy regarding C 0 2 enrichment is tomaximize the growth and production in the longer term (for the duration of acultivation), whereby the costs must be compensated by the revenues. Thisapproach contributes to careful useof C 0 2 , but it does not explicitly account for
reduction of the C 0 2 emission to the atmosphere. The targets of reducing C 0 2
emission can be incorporated explicitly in a new generation of climate control
and optimization systems that is being developed (Bakker et al., 1994).
1.3.2

Problem analysis

In order to specify the problem, some important considerations inrelation to C 0 2 enrichment are stated here and explicated below:
1. high C enhances the rate of net C 0 2 assimilation, growth and production
2. high C may cause (negative) side effects on plants
3. extremely high C causes severe injury to plants
4. noxious gases in combustion gases are detrimental for plants
5. C 0 2 enrichment is accompanied by costs (investments and running cost)
6. emission of 'greenhouse gases' to the environment must be reduced.
Ad 1. High C generally increases the rate of net C 0 2 assimilation,(photosynthesis) i.e. dry matter production, which results ultimately in the wellknown increase in fruit production. Fig. 1.1 surveys the results of a number ofexperiments with greenhouse crops, reported in the literature. The small bandin the figure shows that the general trend of the C 0 2 effect on production forms
a saturation curve, with a similar shape asthe photosynthesis-C0 2 relationship.
The wide band demonstrates that the variation in the C 0 2 effect on production
is considerable. According to Kimball (1986), the estimated relative effect of adoubling of the atmospheric C 0 2 concentration on production varies between+ 1 1 % and +32% for the fruit vegetable crops. Also within one crop (tomato or

13

14

Chapter 1 General introduction

cucumber) a wide variation in results can be found, while reports about sweet
pepper and eggplant are scarce (Kimball, 1986).
The largevariability isplausible,asfruit production isthe ultimate resultof many underlying processes of which many are sensitive to the conditions,for instance net photosynthesis, flowering, fruit set, dry matter allocation andformation of fresh biomass. Moreover, the production might be affected
negatively by deficiency of water or minerals, by pests, diseases, physiologicaldisorders and by side effects of high C (see below). Also species-specificresponsesto C, aswell asparticular conditions intheexperiments reported, may
contribute to the large variability in results.
Ad 2. Three types of (negative) side effects of high C can be distinguished:a. reduced stomatal opening (Raschke, 1975), and hence reduced rate oftranspiration. Reduced transpiration may increase the leaf temperature and the
supply to the leaves of some nutrients, such as calcium and boron, that aretranslocated almost exclusively by the transpiration flow through the xylem(Mengel & Kirkby, 1978). Reduction of stomatal opening occurs instantaneously
and is reversible, whereas the resulting problems appear later and are
irreversible. Not much is known about the occurrence and the extent of thisproblem.
b. morphological adaptations after long-term exposure to high C. The mostfrequently reported symptom is increased leaf thickness (reduced SLA),
sometimes reduced leaf area and in addition severe curling of leaves (e.g.
Madsen, 1976). Not much is known about the consequences of reduced active
leaf area on fruit production, and about the response of a canopy with reduced
leaf area to C. It is also not well understood whether C affects othermorphological parameters, such as harvest index (dry matter allocation) andfruit dry matter content.
c. reduced photosynthetic efficiency following prolonged exposure to high C(e.g. Von Caemmerer & Farquhar, 1984; Yelle et al., 1989a,b).
Ad 3. Plant injury due to high C is evident only in case of extremely highconcentrations (e.g. 10000 umol mol"1 C 0 2 , Hollander & Krug, 1991). As these
detrimental effects havebeen acknowledged for manyyearsalready,growers try
to avoid such extremes. SoC normally applied in practice and considered in thecurrent study, is far lower than the estimated threshold levels of C.
Ad 4. Critical concentrations of noxious gases may prevail and may be
extremely detrimental (e.g. in case of ethylene). Therefore accumulation of
noxious gases must be avoided. This can easily be achieved with the present
technology, which is applied on a wide scale (section 1.2.3).

1.4 Objectives and approach

15

1.4

RESEARCHQUESTIONS, OBJECTIVES AND APPROACH

1.4.1

Restrictions to the research

The ultimate objective of this study is to contribute to optimization of
the C 0 2 supply according to economical and ecological criteria. Optimization
requires a proper definition of the targets, and a quantitative description of thesystem involved,with its relations to the environmental conditions. This implies
that all topics (points 1-6) are relevant for C 0 2 optimization. Points 1-4 areimportant as they represent the processes that influence the horticultural
production. Point 5, the economical consequences of C 0 2 supply, is crucial for
horticultural enterprises. Point 6, preservation of the natural environment, is aprincipal concern of the present-day society.
As it was necessary to restrict this study, it was decided to consider justthe physiological aspects of C 0 2 enrichment. Hence, points 5 and 6, whichhave been the incentives for starting the present study, are dealt with in otherstudies in Naaldwijk (economic aspects of C 0 2 enrichment, Vermeulen, 1992;
and targets for C 0 2 emission to the atmosphere, Vermeulen & Van De Beek,
1993). Also point 2c is part of another study presently undertaken (Heuvelink,
1994, pers. comm.). Points 3 and 4 are sufficiently understood for the practical
purpose.Thereforethis study focuses on points 1(stimulatingeffects ofC0 2 ) and
2a and 2b (negative side effects), which comprise the essential effects of C 0 2
enrichment on plants.
The study isalso restrictedwith respect tothe crop species. Investigated
are the four main species in the group fruit vegetable crops in greenhouses,
being tomato (Lycopersicon esculentum Mill.), cucumber (Cucumis sativus L),
sweet pepper (Capsicum annuum L.) and eggplant (Solanum melongena L). In
these crops,the experience and knowledge about C 0 2 effects is most advanced
and C 0 2 enrichment is commonly applied. They have a great economic
importance (section 1.1). The crops are more or less similar with respect togrowth form and cultivation method: they can be grown year round, withplanting in December and ending in November, while also autumn cultivation
exists, with planting in summer and harvesting until December. To exclude thecomplication that C would influence the size of the plant stand in an earlyphase already, the C treatments were applied only to full-grown plants.
It should be remarked that all questions raised concerning effects of C
are related to fruit production, rather than fruit quality. Indeed it was observed
by growers and reported in the literature (Slack et al., 1988) that C does notmarkedly affect the various aspects of fruit quality, other than fruit size.

16

Chapter 1 General introduction

Nevertheless, because fruit quality is extraordinary important in the Dutch
horticulture, also fruit quality aspects were observed in relation to C.
1.4.2

Research questions

Distinguished are main effects and side effects of C on greenhousecrops. With main effects, processes are involved that determine the production,such as photosynthesis, flowering and fruit set, dry matter allocation andformation of fresh biomass. The most import main effect is a stimulation of thephotosynthesis. The main effect of C can also be called quantitative effect or
production-determining effect oreven production-stimulating effect. Side effects
are for example effects on stomatal opening, transpiration and nutrienttranslocation and morphological properties. These might lead to reduction of
production and arecalled production-reducing effects or alsoqualitative effects.
Not much is known about the integrated results of various counteracting effects of C on plants (production-determining and -reducing effects).
Important is also the time aspect, because high C might have a positive effectin the short term in the form of increased photosynthesis, but might work out
negatively in the longterm.The long-term result isthe ultimate cumulative fruit
production. Basedon the problem description and analysis,with the restrictions
taken into account, the following questions for research are formulated:
I. What arethe main effects of C incrops under realistic greenhouse conditions:a. on rate of canopy net photosynthesis and dry matter gain (quantitative
short-term effect)?
b. on cumulative fruit production (quantitative long-term effect) ?
II. If there is a discrepancy in the response of photosynthesis and of fruit
production to C, can this be explained by side effects, either:a. reduced stomatal conductance and consequently reduced transpiration(qualitative medium-term) ?
b. adaptations to long-term exposure to high C, such asadapted morphologicalparameters (qualitative long-term) ?
1.4.3

Objectives of the thesis

The present study aims at analysis andquantification ofthe main effects
and side effects of the C 0 2 concentration (C, 200 -1100 umol mol"1) on growthand fruit production of tomato, cucumber, sweet pepper and eggplant crops inlong-term, semi-commercial cultivations in greenhouses. The outcome of thisstudy must provide a scientific basis for a policy of optimal C 0 2 supply, which
can take advantage of the positive effects, while minimizing the negative
consequences of C 0 2 enrichment.

1.4 Objectives and approach

1.4.4

17

Approach and structure of the thesis

To answer the research questions formulated above, it was consideredessential to collect information on the effects of C 0 2 on crop performance ingreenhouses of at least semi-practical size, in amedium-long term (months, also
during summer) and under 'normal' greenhouse conditions. Research on
environmental conditions requires a great number of identical, andindependently controllable, greenhouse compartments. All compartments mustbe fully computerized regarding climate control and irrigation equipment, inorder to be comparable to practical horticulture. Some greenhouse complexes
at the Glasshouse Crops Research Station (Naaldwijk, The Netherlands) thatmeetthese high requirements were usedfor the presentwork. The intension was
to investigate the processes on the scale of a whole canopy, which hasconsequences for the methods of data acquisition and interpretation.
Before discussing the integrated effects of C on plants, first the effects
of C on canopy photosynthesis (chapter 2) and transpiration (chapter 3) arestudied. The effects of C on the rate of net C 0 2 assimilation were investigatedby measurements inwhole crops in largegreenhouses.The results are comparedto simulation models and used to fit a regression model and to derive a rule ofthumb ('CO r rule'). The effect of C on stomatal conductance and canopy
transpiration is examined to determine whether high C has a significant effecton leaf temperature and leaf nutrient status.
Chapter 4 deals with the integrated effects of C, for instance on
vegetative growth, fruit set, allocation of dry matter, morphological properties
and reproductive production. It istested herewhether the C0 2 -rule applies also
to fruit production. Intwo trials described in that chapter, some treatments withintermittent C 0 2 supply are compared with constant C treatments, with respect
toeffects on growth and production.Alsosomeparticular features aredescribed.
Each feature was investigated in the species that was expected to respond mostclearly to C in this respect.
Chapter 5 reviews to what extent the newly obtained information
contributes to the existing knowledge. Some aspects are reconsidered: thevalidity of the C0 2 -rule, the side effects of C 0 2 enrichment and the approach.
The thesis ends up with recommendations for practical horticulture.

2.1 Introduction

2 Effects of C 0 2 on
canopy net photosynthesis
2.1

INTRODUCTION

2.1.1

Outline of the problem

This thesis aims at analysis and quantification of the effects of the C 0 2
concentration (C)ofthegreenhouse air on growth and production of greenhouse
fruit vegetable crops (section 1.4.3).C primarily affects the net C 0 2 assimilation
rate, shortly called photosynthesis (P), while P, in turn, largely determines
growth and production. Therefore, the effect of C on Pis investigated first, bothby empirical research and modelling. It is briefly outlined herewhy there is stilla need for experiments and models on photosynthesis, in spite of the many
years of photosynthesis research.
Measurements on photosynthesis generally have been done on single
leaves in a cuvette or on afew plants in a chamber. An important shortcomingof such measurements isthat some important conditions (e.g. light interception,
micro climate, crop size and stage) do not sufficiently resemble those of fullgrown, producing crops, where the research questions (section 1.4.2) refer to.
Photosynthesis measurements in somewhat larger plant stands in greenhouses
were performed by a few authors only (Hand, 1973; Dayan et al., 1985;
Matthews et al., 1987; Hand et al., 1992, 1993a). These experiments were
mostly restricted to one crop, short measuring periods, and were often carriedout in a single greenhouse, mostly only at ambient C 0 2 concentration. Hence,
it was felt that the effect of C on Pof greenhouse fruit vegetable crops was notadequately described to form the basis of this study. Moreover, no data sets
were available for parametrisation and validation (verification) of models. For
instance, an explanatory model for canopy photosynthesis of greenhouse crops(Gijzen, 1992)wasto bevalidated by comparison with measured data, but suchdata sets were not available.
A wide variety of models can be found in the literature, ranging froma very simple to a very sophisticated explanatory model containing numerous
state variables. There are great differences among models, also with respect toaccuracy, universality, complexity etc. Itdepends on the purpose,which model
is most appropriate.

19

20

Chapter 2

Canopy photosynthesis

Inorder to select amodel,the purposes of the modelling must be clear.
A model is needed here in the first place as a research tool, i.e. as a method todescribe and generalize the results of the measurements concerning the effectsof Con P.This modelling can beseenasanextension oftheempirical research.
Secondly, aparticular aim isto derive avery simple type of model, a 'C0 2 -rule'that might serve as a rule of thumb for roughly estimating the effect of C on P,
in a fast and easy way. This purpose will be explicated further in section 2.6.
The third objective is to obtain a model, or to test an existing model, which
ultimately can be implemented in a computerized system for C 0 2 control ordecision support.
For the first purpose, a model as a research tool, the absolute level ofpredicted P is less important than the effect of C on P. The second purpose
requires a very simple model, with a minimal number of mathematicaloperations, while the accuracy may be less. The third application requires areasonable absolute accuracy andagood prediction ofthe effects of all relevant
factors. The complexity of the model is less important.
Many photosynthesis models have been published, but not all models
are appropriate for whole canopies, not all account for the effect of C, not all
are properly documented, not many are validated and only a few are tested forgreenhouse crops. For the second purpose, no suitable models can be found in
the literature. For the third purpose, two well-known models are available thatmight suit: the 'Acock model' (Acock et al., 1976; 1978; Acock, 1991) and the'Thornley model' (Thornley, 1976; Thornley et al., 1992). These models do
account for the effect of C on P of a whole canopy; they are compact,easy-to-use andwell-documented. TheAcock model was applied for simulationof tomato growth, for instance by Tchamitchian & Longuenesse (1991), andimplemented in an optimization routine by Jones et al. (1990). The Thornleymodel was applied for cucumber by Hand et al. (1992). Also the model of
Gijzen (1992) is intended for climate control and decision support. This model
will be discussed elsewhere (Gijzen et al., 1995).
In relation to canopy photosynthesis models, it can be questioned
whether Pissimply afunction of instantaneous conditions (PAR,C, temperature,
air humidity, water status) and plant parameters (LAI). There are indications forother influences as well. First there may be a time-dependent variation withina day. This can be a temporary dip, a 'midday depression' (Meidner &Mansfield, 1968), or aslow decline duringthecourse ofthe day (Ito, 1971). Thismight be based on assimilate accumulation, on light, water relations ortemperature, but it was also suggested that there is a type of endogenous
mechanism, more or less independent of external conditions (Meidner &2.1 Introduction

Mansfield, 1968). The occurrence of a time-dependent variation in themeasurements is examined here.
Secondly, the photosynthetic system may adapt to high C. It is often
reportedthatthe photosynthetic efficiency per unit leafarea( C 0 2 exchange rate,
CER) declines after long-time exposure (weeks) to high C (Hurd, 1968; Von
Caemmerer & Farquhar, 1984; Sageet al., 1989; Yelle et al., 1989a,b; Dugal etal., 1990, Bunce, 1992). This topic is not investigated here: it isa main topic inmodern photosynthesis research and it will be investigated on the scale ofgreenhouses in another study (Heuvelink, 1994, pers. comm.).
2.1.2

Objectives

The first objective of the present work isto obtain reliable data sets on
the effects of C on the net photosynthetic C 0 2 assimilation rate (P) of stands ofgreenhouse cucumber, sweet pepper and tomato under 'practical' conditions
and a realistic range of C 0 2 concentration (about 200 to 1100 umol mol"1). The
data sets, intended for modelling, should contain the photosynthetic rate incombination with environmental conditions. The second objective is to derivea rule of thumb for C 0 2 ('C0 2 -rule'), describing the effects of C on Pin global
terms. The third objective is to verify existing models (Acock et al. 1978;
Thornley, 1976) regarding the sensitivity to prevailing C. The research is
restricted to the instantaneous response of Pto C. It is considered whether atime-dependent variation (e.g. midday depression) in canopy photosynthesis
occurs in the measurements.
2.1.3

Approach and structure of the chapter

Canopy photosynthesis was investigated in six semi-commercial
cultivations under practical conditions, mostly with parallel measurements inseveral similar greenhouse compartments with various C 0 2 concentrations.
Before the data were used, they were subjected to a detailed error analysis(section 2.3) and it was checked whether a time-dependent variation within a
day existed in the measurements (section 2.5). The results are presented andgeneralized by a regression equation, fitted to each data set. These regression
models, meant just as a research tool, are used to estimate the main
photosynthesis characteristics and to compare the results of the various crops(section 2.4). The regression equations are used also to derive a rule of thumband it is discussed if one generic rule applies to all experiments (section 2.6).
Finally, the data sets and the derived regression models are compared to two
existing models (section 2.7), usingthe measured instantaneous conditions andmeasured leaf area index as input.

21

22

Chapter2

Canopyphotosynthesis

2.2

MATERIALSAND METHODS

2.2.1

Crops, greenhouses and environmental factors

Experiments were done with cucumber in autumn and spring, sweet
pepper in spring and autumn and tomato in spring. Information about the six
cultures and conditions is given in Table 2.1.Expt 1 was described previously(Nederhoff et al., 1988), while here only the data of that work are used.
Expt 1 differed from expts 2-6 with respect to the facilities. The maindifference was the C 0 2 supply method: in expt 1, C 0 2 was given in pulses,
resulting in a saw-tooth C pattern. In all other experiments, C 0 2 was supplied
continuously through mass-flow controllers, to maintain a constant C. Sweet
pepper (expt 3) was planted and investigated in spring. This crop wasmaintained until the autumn (long season cultivation) and investigated again
until October (expt 4). This old sweet pepper crop was compared to a young,newly planted sweet pepper crop in autumn (expt 5).
Expt 2to 6 were made in a north-south oriented Venlo-type glasshousecomplex, with normal pipe heating and with ventilation windows in the roof.
The compartments had 192 m 2 ground area and 576 m 3 volume. The plants
were grown on rockwool wrapped in plastic. Several times a day, the plants
were supplied with a standard nutrient solution (Sonneveld & De Kreij, 1987)
and the surplus was drained out. As the soil had not been used as a growing
medium for years and was covered with white polyethylene film, emission ofC 0 2 from the soil was considered negligible.
The crops were grown under about 500 umol mol" 1 at no or little
ventilation, and at about outside concentration during ventilation. In this way,
it was attempted to avoid differences between compartments and, moreover, toavoid serious negative adaptation to high C.
A micro-computer connected to a VAX-network (Bakker et al., 1988)
was used to control the heating, ventilation, C 0 2 supply, nutrient solution
supply and the photosynthesis measurements. Climate control parameters wereset according to standard commercial practice. The air temperature wasmonitored with calibrated,screenedand aspirated PT-100sensors, inthe middle
ofeach compartment, 1.5 m abovethe ground.Temperature and radiation wererecorded once a minute, C once per 5 min. The achieved environmental
conditions are summarized in Table 2.1. Photosynthetic active radiation (PAR,i.e. light flux, 400 - 700 nm) was measured with an energy response meter(TFDL, Wageningen, the Netherlands), located outside the greenhouse on ameteorological tower at the Research Station.

23

2.2 Methods

Table 2.1. Information on cultivation and environmental
experiments with canopy photosynthesis measurements

experiment nocrop

conditions in the six

1a

2

3

4b

5

6

cucumbercucumber

pepperpepperpeppertomatobaut., yngspring

Rumba

Blizzard

seasonautumnspringspringcultivar

CoronaLucindeDelphine

aut., old

Delphineplanting date

13.08.87

18.12.87

18.12.87

18.12.87

13.07.88

19.12.88

plant density

1.49/1.92

1.43/1.79

2.52/3.12

2.52/3.12

2.52/3.12

1.85/2.08

3, 4, 7 acompartments2

cropped area (m )

43 a

6, 8

4

4

6, 8

6,8

154

154

154

154

170

start measurem.

c25.8/237

22.3/82

23.3/82

4.8/217

4.8/217

8.2/39end measurem.

c20.10/293

13.5/134

24.6/176

16.10/296

20.11/324

2.5/122nmbr of observ.

1218

348

556

438

1243

1568

LAI (at day) d

3.0 (246)

2.3 (48)0.9 (48)

4.5 (165)

1.9 (223)

1.6(61)

LAI (at day) d

3.5 (262)

3.3 (82)

4.5 (164)

6.9 (223)—

2.4(102)

LAI (at day) d

3.4 (295)

4.1 (136)

5.1 (176)

6.0 (307)

2.8 (333)

3.2(128)

3.4

3.6

2.8

6.7

2.7

2.2

global rad. (W/m 2 ) e

5/189/678

9/136/618

9/166/584

6/100/485

6/111/649

1/150/654

PAR (umol s"' r r f 2 ) e

3/198/639

6/153/599

6/184/581

3/108/425

3/117/630

1/159/573

air temp. (°C) e

18/25/31

19/23/27

18/25/30

19/24/30

14/24/34

12/18/25

128/544//1932

297/ 504//996

284/ 530//1483

296/ 454// 1186292/ 440//956

109/388//945

average LAI

C 0 2 (umol mol ')eexpt / was carriedout in anothergreenhouse complex(Nederhoffetal., 1988)
same cropasin expt3, but investigatedsome months later
date/ day number
plant density (plants/m2) is (1)totalnumberofplantsrelatedto totalgroundarea
and (2)totalnumberofplantsrelated tocroppedarea, excludingmainpath
LAIisleafarea per unit croppedgroundarea (main path excluded)
minimum, meanandmaximumvalues obtainedduringthemeasurements. Globalradiation
outside, PAR atcrop level,temperature andC02 insidegreenhouse

When necessary, an approximated conversion from energy flux to quantum flux
was made (1 W m"2 PAR = 4.5 umol s"1 m 2 ; McCree, 1972; Meek et al., 1984).
PAR was not measured inside the greenhouse, because shading by greenhouse
construction elements would seriously complicate the light measurements. PAR
at crop level was estimated by multiplying the measured outside PAR by acalculated instantaneous light transmission coefficient of the greenhouse cover.
For this reason, a coefficient for overcast sky conditions was determined by

24

Chapter 2

Canopy photosynthesis

using two identical PAR meters, one inside and one outside the greenhouse,yielding a value of almost 70%. The actual instantaneous transmission was
calculated according to Gijzen (1992) with a model of Bot (1983). Input to thismodel were the measured light transmission coefficient under overcast sky, thecalculated sun position and the calculated ratio between diffuse and direct light(Spitters et al., 1986).
Radiation increases the greenhouse air temperature and thus promotes
the automatic ventilation, so it was generally difficult to achieve high C in
combination with high radiation. Hence such conditions were scarce in somedata sets (Fig. 2.1). As the measurements were stopped at high ventilation thatusually goes together with high radiation, incident PAR did not exceed 700
umol s" ™-2
m .
2.2.2

Principle of the photosynthesis measurements

The method applied for measuring canopy photosynthesis was to use
whole greenhouse compartments assemi-open systems, andto approximate theair exchange rate on-line with nitrous oxide (N 2 0) as tracer gas (after Lake,
1966). N 2 0 has the same molecular weight as C 0 2 , is not phytotoxic, isvirtually absent in the outside air, is not absorbed by the plants and is easy tomeasure with an infra-red gas analyzer. C 0 2 was injected into the greenhousewith a measured rate to maintain a set point. The C 0 2 balance of thegreenhouse air, in which the canopy photosynthesis (P) is the only unknown
term, was calculated as:
dC(t) / dt = (G c + Sc - P- Lc )/ (h * pc)

eqn. 2.1

where:
C(t) = C 0 2 concentration (umol mol"1) at time t
G c = rate of C 0 2 emission from the ground (ignored, see above)P= rate of net C 0 2 uptake (g m"2 h"1)
Sc = rate of C 0 2 supply (g nrf2 h"1)
Lc = rate of loss of C 0 2 to the outside (g nrf2 h"1)h= average height of the greenhouse (3 m)
pc = density of C 0 2 (1.83 kg nrf3 at 20 °C and 101.3 kPa).
G c , P, Sc and Lc on a ground area basis (1 g nrf2 h"1 C 0 2 = 6.3 umol nrf2 s"1).
Lc was calculated as follows:
Lc = É' * h * pc * [C(t) - Ca(t)leqn. 2.2

where:
Ca(t) = ambient (outside) C 0 2 concentration (umol mol"1) at time t\'= air exchange factor (h"1)

2.2 Methods

This Ç'wasdetermined with the decay ratemethod (Goedhart et al., 1984): after
the N 2 0 injection was stopped, the concentration declined and Ç' wascalculated from the N 2 0 concentration at time t (N(t) in umol mol"1) by:
\' =
2.2.3

[ I n (N(t2)) - In (Nft,)) ] / At

eqn. 2.3

Photosynthesis measurements

Nitrous oxide was injected from high-pressure bottles up to a peakconcentration of about 100 umol mol" 1 if vents were closed and up to about
300 umol mol" 1 at relatively high ventilation. In the first 10-15 min after
injection, the distribution of N 2 0 was considered insufficiently homogeneous,so these measurements were discarded by an automatic procedure. The
measurements were stopped when the window opening or the wind speed
became too high (i.e. if the air exchange rate approached 3.5 h"1) to avoid
excessive tracer gas usage and inaccurate measurements.
The carbon dioxide concentration of the greenhouse air was kept on its
set point by controlling the supply of pure C 0 2 , using feedback control. The
injection rate was set between 6 and 12 g m"2 h"1, and was recorded bycalibrated thermal massflow controllers (model 5851,Brooks, Veenendaal, The
Netherlands).
The C 0 2 and N 2 0 supply were controlled independently bycomputer-steered solenoid valves, in each greenhouse compartment separately.
The gaseswere led to the compartment and injected there into the air stream ofa centrifugal fan, connected to a network of plastic ducts on the ground. The
C 0 2 valves were opened automatically every 5 min for an interval, proportional
to the difference between the actual and the desired C.
The sampling system in each greenhouse compartment consisted of a
network of 6 mm nylon tubes, with eight inlet points connected to one central
dust filter and one main tube towards the analyzer. The inlets were located in
the upper half ofthe canopy, spreadover thegreenhouse compartment. Outside
air was sampled through an inlet mounted on a location, where it was notdirectly influenced by C 0 2 emission from the greenhouse. A computercontrolled multiplexer switched the sampling every minute between the four
compartments and the outside, yielding a measuring cycle of 5 min. The
sampled air was pumped forward to the gas analyzers. A second pump in ashunt continuously pumped air from the four sampling networks that were notanalyzed, in order to reduce the lag time.

25

26

Chapter 2

Canopy photosynthesis
1200-

b

1000-

.

800-

\" * ..

6 0 0 - :.£r-;?W-«oi .v«- ..
400- 1 * S * « i i «-Ä , - v n - >•

200-

O

O

10O 200 300 400 SOO COO 700

O

I6OO-1**

10O 200 300 4 0 0 500 600 7 0 0
120O-1

£
"5
E
c

o
2

BOO

c
V

U

c
«-'•<J•»\,v» . 1..

8 *°°

o

— i

O

1

1

1

1

1

r

100 200 300 400 500 600 700

ooo- 't

O

—i
1
1
1
1
1
r
10O 200 300 400 500 600 700

e

800-

:

& . " •'

6 0 0 - r i •«,»•-«-

iBjiffiX'V:.
-

400-^*KS?3 *'-.-;-

_.
.
"
#

200-

oO

i

i

i

i •

! '"

I

100 200 SOO 400 500 BOO 700

incident PAR (|jmol s"1m"2)
Fig. 2.1 Incident PAR (umols'1 m2 )andconcomitant C02 concentration(pmol mot1)
in thephotosynthesis measurements, a- f arethesixexperiments asin Table 2.1.

2.2 Methods

Two infra-red gasanalyzers (type G, Hartmann and Braun,Frankfurt, Germany),
were used to measure the concentration of C 0 2 and N 2 0 . The ranges were 0300 for N 2 0 and 0-1000 and 0-2000 umol mol" 1 for C 0 2 . Both analyzers were
calibrated at least once aweek with pure nitrogen for zero calibration and withcertificated calibration gases for span calibration. As the C 0 2 analyzer was
slightly sensitive to the N 2 0 gas, and vice versa, the measurements werecorrectedforthis cross-sensitivity.Thiswasestablished regularly with calibration
gases.
2.2.4

Data processing

The measurements were controlledand recorded bythe micro computerthat was also usedfor environmental control.Thedatawere transferred over the
network to aVAX computer. Every night, the dataof the previous 24 hours were
processed automatically with a FORTRAN routine. Further analysis was donewith the statistical package GENSTAT (Payne & Lane, 1987).
Someform of averagingwas requiredto reducethe number ofdata (over30.000 rough data records) and to filter out certain type of errors.An importanterror was caused by supply of C 0 2 (Sc in eqn. 2.1): a high Sc in one 5-mininterval could result in a negative value of calculated P in that particularinterval, followed by ahigh calculated Pinthe next interval.To reduce this typeof measuring errors, the calculations on the C 0 2 balance (eqn. 2.1-2.3) were
performed over three consecutive 5-min measuring cycles. The rate of change
in C (dC(t) / dt) was calculated as the difference in C at the start and the endof this 15-min interval, divided by the time. For C(t) the average C 0 2
concentration inthis interval wastaken,which was allowed becauseCwas kept
fairly constant. The air exchange factor inthis period was calculated with linear
regression on the logarithms of the measured N 2 0 concentration (eqn. 2.3).
Before further analysis, the data records were averaged over 30 min intervals.
The choice of the length of the smoothed interval is based on someconsiderations. Smoothing over longer time intervals generally leads to loss of
information, while the use of shorter intervals would increase the inaccuracy inobserved P. An interval length of 30 min was considered a reasonable
compromise for stable as well as unstable conditions (i.e. with constant orchanging light and vents), regarding the time constants of the C 0 2 supply andcontrol system.
Thedatasetsobtained consisted of 348to 1568 data records, containing
30 min average values of measured canopy photosynthesis, PAR and C.

27

28

Chapter 2

Canopy photosynthesis

2.3

ACCURACY OF THE MEASUREMENTS

takenhorn: EM. Nederhoff & J.G. Vegter,1994a, Annalsof Botany73: 353-361.

2.3.1

Type of errors

Asthe photosynthesis measurements were performed automatically andcontinuously during day and night, some types of incidental errors in themeasurements could not always be avoided. Apart from those errors, there wasalso the regular inaccuracy in the measurements. It is first explained how theincidental errorsoccurred and how theywere discardedfromthedata sets.Then
the regular measuring error is estimated.
2.3.2

Incidental errors in the measurement

To investigate the presence and size of errors, the photosynthesis
measurements were done in the greenhouse compartments when they were
without crop (P empty ). These 'zero-measurements' could reveal only theincidental errors and an off-set (deviation from 0) in the measurements. P empty
varied from 0 to about -0.3 g m"2 h"1, which is considered too large an error
compared to photosynthesis at low light conditions. Three conditions weredetected as possible sources of error.
Determination of Pwas sometimes obviously incorrect for about 5 minafter the ventilation rate had changed drastically. Secondly the measurements
could be disturbed by human activity (opening of doors). These activities had
to be recorded, but this was overlooked sometimes during the long-term
measurements. In the third place, air was not only exchanged with the outside,
but also with the corridor, by leakage through the inner glasshouse walls. To
maintain the same C 0 2 and N 2 0 concentration in the corridor as in the outside
air, the vents of the corridor had to be open, but they may occasionally havebeen closed.
Before analysis,all datawere checked for such incidental errors. Periodsof disturbance were detected from an anomalous course of observed P, contrary
to the course of PAR and C, or from exceptional measurements at night, whennormally afairly stable respiration ratewas observed. Ifthe measurements were
obviously disturbed or suspected,the data for that period (some hours to somedays) were rigorously discarded. The ultimate numbers of reliable data used in
the analysis, are given per experiment in Table2.1.

2.3 Accuracyofmeasurements

2.3.3

Regular measuring error

Error analysis
Apart from incidental errors, all observations contain an uncertainty i.e.
inaccuracy or error. The error in calculated P depends on the errors in theunderlying measurements.Combiningandrearrangingtheequations usedforthe
calculation of P(eqn. 2.1-2.3) yields:
P= Sc - a p * {(C2 - CD + (0.5 * C1 + 0.5 *C2 - Ca) * [ln(N1) - ln(N2)]}
eqn. 2.4
where C1 = C 0 2 concentration at time t1 and C2 at time t2; C a = outside C 0 2
concentration, N1 = N 2 0 concentration at time t1 and N2 at t2; Sc = C 0 2
supply rate and a = h * pc/ (t2 -11). Each of the measurements used in eqn.
2.4 (C1,C2, C a , N 1 , N2, Sc) contains an error (e). Thus C1 must be replacedby C1 + e c 1 and P should be P + e p , etc. in eqn. 2.4. The errors in thesemeasurements (e c 1 , e C2 , e Ca , e N 1 , e N 2 and eSc) are 'partial measure errors'. The
properties of the resulting overall error (ep) will be derived from those of thepartial errors.
It is likely that the errors in the measurements made by one sensor (e.g.
the C 0 2 analyzer) are correlated, at least to a large extent. Hence, the relative
errors in C I , C2 and C a are assumed equal and the same holds for N1 and N2.
It is not probable, although possible,that the measurements of different devices
are correlated. In case of complete correlation between measurements of one
analyzer, only three measuring errors play a role: e c , e N and eSc.
Thetwo gasanalyzerswerefrequently calibrated,(seeabove), permitting
to assume low errors inthe C 0 2 and N 2 0 measurements.Arbitrarily, the relative
standard errors in these measurements are taken 5%. The error in Sc depended
on the accuracy of the mass-flow controllers. Based on their specifications, thisrelative standard error can be assumed a few percent, but also for thismeasurement a 5% relative standard error was assumed.
First order error analysis
When the measuring errors are not too large, a good indication of thestandarderror can beobtained by first order error analysis (e.g.Lindgren, 1968).
The standard error in P(ep) is found by:
e p = £ i b, * 6jeqn. 2.5

where ej (with i = 1to n) replaces the partial errors (e c 1 , e C2 , e Ca , e N1 , e N 2 , eSc
or e c , e N , eSc). Eachcoefficient bj isthe first partial derivative of eqn. 2.4 to thati t h element. By analysis of eqn. 2.4 (and by a numerical method aswell), it was

29

30

Chapter2 Canopyphotosynthesis

determined that a relative error ec in the C 0 2 measurements resulted in a
relative error in observed P of magnitude ILC/Pl * e c . Notice that eqn. 2.4
contains Lcin a concealed form. An error in N1 and N2 (as long asthe relative
errors were equal) did not have any effect on eP (eqn. 2.3). A relative error ofeSc in the C 0 2 supply rate caused a relative error ISC/ PI * eSc in P.
Eqn. 2.4 and 2.5 were applied to the data sets, under the assumptionthat the errors in the measurements of one analyzer were correlated.The ratios
ILC/ Pi and ISC/ PI were determined for all observations. Table 2.2 presents foreach data set the 95% quantile of these ratios. For example, the 95% quantileof ILC/PI is 1.1 in expt 2, meaning that the value of this ratio is below 1.1 in
95% of the observations. Consequently, a relative standard error of 5% in C
causes less than 5.5% relative standard error in P, in 95% of the observations
in expt 2. Fully correlated relative errors in N1 and N2 have no influence on P
(eqn. 2.3).
The overall relative standard error in Pcaused by the different sourcesof error can now be found as the root of the sum of squares of the partial
relative standard errors,taking into account the factors ILC/ PI and ISC/ PI. In all
experiments,the resultingestimated overall relative standarderror appears to bein the order of ±10%, at least if the majority of the observations is considered(Table 2.2) and under the assumption that the errors of different devices are notcorrelated. The use of 95% quantiles implies that in 5% of the observations, theestimated partial error is larger than the values presented.

Table 2.2. Estimatedrelativestandarderror(in %)in observedcanopyphotosynthesisrate(P), and 95% quantilesof someratiosusedfor error analysis.Valuesof P< 0.1
wereignoredin thecalculation of the quantiles.
experiment:

2

3

4

5

95%-quantile of I Lc/ PI

ÏTÏ

~2

Ö

ÏÏ.

95%-quantile of I Sc/ PI
relative standard error (%)

1.2
8.1

1.7
10.4

1.5
9.9

1.6
10.0

6
2A~
1.0
11.6

Error analysis on artificial data
The same approach with eqn. 2.4 and 2.5 was applied to an artificial
dataset,consistingofvariousfictive but realistic combinations of Sc,C1, N1 andN2, with Ca = 350 umol mol"1 and with C2 = C1 (constant C 0 2 level). The

2.3 Accuracyofmeasurements

conditions chosen covered the ranges present in the experimental data sets. If
the measurements ofoneanalyzer areassumedcompletely correlated,and if thepartial standard errors aretaken 5%, the relative standard error ePis5% as well.
If the partial errors would be independent (which is not realistic), the relative
standard error ePwould be larger. Usually, ePwould be below 10%, except if
low photosynthesis rates are low (P < 0.5 g m"2 h"1) or if high C 0 2 supply rates
are combined with high C 0 2 exchange with the outside.
2.3.4

Conclusion

Based on the results of both the theoretical error analysis and the error
analysis on artificial data, it is concluded that the estimated relative standard
error in observed photosynthesis rate (P) is in the order of 10%, ignoring somelarge relative errors occurring under particular conditions. Very high relative
errors are possible, particularly at high C in combination with high ventilation
rates,and secondly at low P.Thefirst condition is rare inthe measurements, thesecond condition, low P, occurs very frequently, e.g. at the beginning andending of aday. The relatively good accuracy of the majority of data permits to
use the data for interpretation and modelling. On the other hand, the possible
large relative errors at low Prequire attention at the analysis and interpretation.

31

32

Chapter 2

Canopy photosynthesis

2.4

REGRESSION MODEL AND CHARACTERISTICS
OF CANOPY PHOTOSYNTHESIS

takenfrom: EM. Nederhoff & J.G. Vegter,1994a, Annalsof Botany73: 353-361.

2.4.1

Regression model

The photosynthesis data were analyzed by fitting a multiple regression
equation to the data of each experiment. This was not an attempt to develop a
new photosynthesis model,but amethodto synthesizetheexperimental results.
For the dependence of Pboth on light and on C, a double rectangular
hyperbolic relation was chosen (Thornley & Johnson, 1990). Adding aterm fortemperature appeared notto be useful,because of the high correlation between
temperature and PAR. The leaf area index (LAI) was considered in two ways: asaturation term [elog(LAI)] multiplicative to the terms for light and C accounted
for the light interception effect. LAIwas considered to also represent the amountof biomass, which determines the maintenance respiration. This effect was
expressed by an additive linear term [p 6 *LAI]. In the model fitting procedure,
however, itappearedthatwith mostdatasets,the regressionequation performed
significantly better if the term elog(LAI) was omitted. Also some other variantsof the proposed model were tested, but the best fit was found by the model:
P = PT + p 2 * [ I/ (p3 + I )] * [C / (p 4 + Q ] + p 5 * L

eqn. 2.6,

where p n is a parameter, I is incident PAR at crop level (in umol s"1 m"2), C the
C 0 2 concentration (in umol mol"1) and Lthe leaf area index (LAI in m 2 m"2) as
measured regularly during the cropping period (Table 2.1).
The common photosynthesis characteristics could not be obtained
directly from the fitted equation, but were calculated, as follows:• maximum canopy photosynthesis rate (Pmax) asPunder high PARand high C;• light compensation point as PAR where P is zero;• light useefficiency (LUE, light utilization efficiency, photosynthetic efficiency
or photochemical efficiency, or ifexpressed in mol C 0 2 per mol photons also
called quantum yield) as initial slope of the photosynthesis-light curve;• C 0 2 compensation point as the C 0 2 concentration where P is zero;• C 0 2 use efficiency (or C 0 2 utilization efficiency or carboxylation efficiency
or mesophyll conductance) as Pper unit C 0 2 at C 0 2 compensation point;• relative effect of a C 0 2 step from 350 to 700 umol mol" 1 on P.
Most calculations were made at two levels of C or at two levels of light. Lwas
set to the average value of the measured LAI.

2.4 Regression model

33

Table 2.3. Parameters p, top5 of the multiple regression equationp=Pi +?2 * [ l /(Pa + I )] * [C/(p4 + C)] + ps * L (eqn.2.6) fitted to the canopy
photosynthesis data of the six experiments (see Table 2.1), with P= rate ofnet canopy
photosynthesis (gm'2 h'1); I = incident PAR (pmol s'1 m'2); C = C02 concentration(umol mot1) and L= LAI. Between brackets thestandard error.
p, & p5 andp2 & p3 andsometimes p2 & p4 were highly correlated (r> 0.5).
p,

p2

p3

p4

p5

r2

1. cucumber -1.39(0.2)

8.3(0.4)

268(21)281(19)0.23(0.07)

82.5

2. cucumber

1.33(0.3) 17.1(2.6)

771(125)262(57) -0.54(0.08)

90.9

3. pepper-0.51(0.1)

25.8(5)1202(233)

464(72) -0.08(0.02)

89.5

4. pepper

1.15(0.4) 36.8(14)1929(770)

205(63) -0.26(0.06)

87.0

5. pepper-2.48(0.1)

9.3(0.8)573(55)119(24)0.71(0.04)

87.6

6.tomato-0.78(0.0) 11.9(0.6)

577(42)

221(14)0.18(0.02)

89.2

parameter

2.4.2

Regression models fitted tothe measurements

Table 2.3 presents the fitted parameter values; Table 2.4 gives somephotosynthesis characteristics calculated with this model, and Fig. 2.2 theresulting curves. The regression model explained 83 to 9 1 % of the variance inthe data (r2 in Table 2.3). Parameter p5, describing an effect of LAI, is rather
variable (positive and negative). This is explicable, because this term accounts
for the maintenance respiration with LAI representing the amount of biomass.
As P is affected negatively by much biomass, p5 is negative in crops with aconsiderably increased LAI.
The values found for some of the characteristics (Table 2.4) may slightly
depend on the type of regression model (eqn. 2.6) applied in the analysis (Peat,1970). It should be remarked that in expt 3 four data (P > 4.5 g m"2 h"1) wereignored in the fitting procedure, as they severely reduced the fit. These points
were extreme compared to previous and subsequent measurements.
The six experiments yielded rather different results (Table 2.3 and 2.4
and Fig. 2.2), but it seems that a large variability is in the nature ofphotosynthesis, already at the level of a leaf, and so certainly also on the levelof acanopy (Acock et al., 1976;Jones et al., 1991a; Hand et al., 1993a). A partof the variation found in the literature may be due to the fact that ingreenhouses C is more variable than in the open field. In the following, theresults arecompared with the literature and relatedto the prevailing conditions.

34

Chapter2

Canopyphotosynthesis

Table 2.4. Values of some canopy photosynthesis characteristics calculated with thefitted regression equations (Table 2.3); between brackets the standard error,
C.P. = compensation point; LUE = light use efficiency.

experiment:naverage LAI
a

P
' max

2

( g m" h ' C 0 2 )Pma* / LAI(gm"2 h"' ) alight C.P. b

1

2

3

4

5

6

1218

348

556

438

1243

1568

3.4

3.6

2.8

6.7

2.7

2.2

4.8

8.0

8.6

5.2

6.5

(0.1)

(0.6)

(0.7)

1.4

2.2

3.1

(0.04)

(0.2)

(0.3)

----

40/27

53/37

86/53

54/40

(|jmol s"1 m"2)(2)/(1)(3) / (2)(3) / (2)(2) / (2)

LUE b ( mol m o l ' )0.10/0.15

0.08/0.11

0.06/0.09

0.07/0.10

(0.3)

(0.2)

1.9

2.9

(0.1)

(0.1)

51 / 4 2

32/24(1)/(1)(D/(1)

0.07/0.09 0.08/0.10

standard error (0.001 * )(6) / (7)(5) / (7)(3T/(4)(4) / (7)(3) / 3)c o 2 C.P. c

37/27

29/16

54/27

20/9

19/11

18/11

(3) / (2)(4) / (2)(4) / (2)(4) / (2)(3) / (2)(1)/(0.7)

7.6 / 1 0 . 9

10/19

6.5/14

15/36

13/23

11 / 1 8(0.2) / (0.3)(1)/(2)(0.3)/(1)(2) / (6)(1)/(2)(0.3)/(1)

36/34

33/30

53/46

26/24

18/16

27/26

(6)/ (6)(3)/ (3)(D/(1)( ^mol mol' 1 )C 0 2 useeffic.

c d

'

1

( m h" )C 0 2 effect (%)

c

350 - 7 0 0 pmol mol"'abc(2)/(1)(5)/ (5)22(5)/ (4)(2) / (3)incidentPAR 1350pmol s' m (300Wm )and C02 WOOpmol mol"'
two C02 levels: 350and WOOpmol mol''
two levels of PAR: 450and 1350pmol s' m2 (100and300 Wm'2) atcroplevelC02 concentration increased fromcompensation point to 10pmol mot' more

2.4.3

Characteristics of canopy photosynthesis

Light saturation and maximum photosynthesis

In none of the six experiments was the rate of photosynthesis saturated
at the prevailing light conditions (700 pmol s"1 m"2). This is in accordance withother findings: most of the surveyed photosynthesis curves showed no lightsaturation or only at high PAR(Handet al., 1993a).Theseauthors observed thatthe photosynthesis rate of an eggplant canopy approached saturation at 900
pmol s"1 m"2 PAR, whereas under high C this occurred at even more light.
Warren Wilson et al. (1992) observed light saturation only at 2500 pmol s"1m"2.
The calculated values for Pmax (Table 2.4) varied from 5 to 9 g m"2 h"1
C 0 2 uptake per ground area, which compares with a value of 9 g m"2 h"1
measured by Warren Wilson et al. (1992).The ratio Pmax/Lwas between 1.5 and3gm"2h"1; it was highest for the crops with about the lowest LAI (expt 3 and 6).

2.4 Regression model

Thiscanbeexplained byarelatively high light interception ofall leaf layers,i.e.
a relatively low mutual shading. Canopy Pmax/L is lower than Pmax of single
tomato leaves (e.g.Jones et al., 1991a),which isalso explained bytheeffect ofmutual shading of leaf layers in afull-grown canopy.
Light related characteristics
The calculated light compensation points (Table 2.4)were between 32
and 86 umol s"1 m"2PARat lowC.Thereview by Warren Wilson et al. (1992)
showed values within the range 45 to 100(extremes of 180) umol s"1m"2.Thelight compensation point normally decreaseswith increasing C(Warren Wilson
et al., 1992; Hand et al., 1993a), asalso seen in our calculated data.
The calculated initial light useefficiency (LUE)ofthecanopy at lowC
was 11to 18 ugJ"1(C0 2 uptake perunit incident PAR-energy), i.e.0.06to0.10
mol mol"1(mol C 0 2 per mol intercepted PAR-photons, Table 2.4).At the lightcompensation points, the LUEwas slightly lower (data not presented). These
values areoftheorder of magnitude reported for canopies (Acock et al., 1976;
Handetal., 1993a) andsomewhat higher thanfor leaves (Farquharetal., 1980).
Goudriaan et al. (1985) cited that the measured LUE rarely exceeds 17 ug J'1(0.09 mol mol"1), while from theoretical considerations the maximum leafLUE
is approximately 25(0.13 mol mol"1). Soinexpt 1at high CourcalculatedLUE
is unrealistic. A higher LUE at higher C (Table 2.4) is consistent with theliterature (Farquhar et al., 1980; Hand et al., 1993a).
The conversion efficiency for light at100W m"2andlowC ranged from0.015 to 0.05 mol mol"1 (data not presented), which compares with values
reported by Warren Wilson et al. (1992) and Hand et al. (1993a).
C 0 2 related characteristics
The C 0 2 compensation point (Table 2.4) was 18 to 53 umol mol"1 at
100 W m"2 and 8 to 27 at high light. Acock et al. (1976) reported C 0 2
compensation of atomato canopy of 63 umol mol"1. Our values compare very
well with data determined by Farquhar et al. (1980), although these were forleaves.Somewhat higher values were reportedforasingle leaf (Goudriaan et al.,1985) andfor a single plant in acuvette (Nilwik, 1980).
TheC 0 2 useefficiency attheC 0 2 compensation point was between6.5
and 15 m h 1 (g m"2 h"1 C 0 2 exchange per g m"3 C0 2 ) at low light and itwas
higher athigh light.TheC 0 2 useefficiency washighest inexpt 4,explicable by
the high LAI. The observed range compares with the value derived byGoudriaan et al. (1985) and it is slightly higher than the value estimated byJones et al. (1991a).

35

36

Chapter2

Canopyphotosynthesis

E
4—»

c
o
o

incident PAR (pmol s"1 m 2 )Fig. 2.2. Net canopy photosynthesis rate (Pin g m'2 h~' C02 uptake related to groundarea)calculated with the fitted regression model (Table2.3) asfunction of incident PAR(umol s'' m'2 ) , with for L the average measured LAI (Table 2.1).
Calculated for 350 pmol mot1 C02 (; and 700 umol mot1 C02 ().
Thin lines indicate 95% confidence limits, a-f are the six experiments asin Table 2.1.

2.4 Regression model

The effect of C on P is shown in Table 2.4 and in Fig.2.2. Note thestrong response to C and light in expt 3 andthe relatively weak responses in
expt 5, both young sweet pepper crops. Also Pmaxand Pmax/ L were higher in
expt 3than inexpt 5,although thecalculations were made with equal lightand
about thesame LAI. Inexpt 5, both LAIandaverage light were low (Table2.1),
probably explaining the overall low photosynthesis rates. A low LAI is
responsible for a low response to light (e.g.Thornley & Johnson, 1990), while
unfavourable light conditions causethat Pislowandtheresponse of PtoClesspronounced (e.g.Gaastra, 1959).
In addition, some seasonal acclimation might play arole, although thiscannot be proven. It was observed that the specific leaf area was markedly
greater in expt 3 than in expt 5. Thethinner leaves in expt 3 can be regarded
as 'winter leaves' and those in expt 5 as 'summer leaves'. Ludwig & Withers(1978) observed different responses of summer andwinter leaf photosynthesis
to light andC, associated with different rates of photorespiration.
2.4.4

Remarks and conclusions

The large variability in calculated photosynthesis curves (Fig.2.2)andcharacteristics (Table 2.4) - although not larger than in the literature - isattributed to several factors:
a. correlation between factors: asmall photosynthetic apparatus (lowLAI)
decisively reduces the response of the canopy to light and reduces Pmax;
low light conditions cause that the effect of C is less clearly observable.
b. limited ranges of C and light conditions in the measurements (high light in
combination with high C were rare in some experiments, Fig. 2.1);
c. measuring errors (estimated 10% and occasionally higher);d. errors in the estimation of incident PARquantum flux (the lighttransmission coefficient of the greenhouse cover, the unit conversion);e. fast variations in PARandC, while 30-min average values were used
(inducing overestimation of calculated P,dueto the non-linearity ofP)f. seasonal variations or adaptations to climatic conditions;g. factors influencing photosynthesis that were not accounted for inthe
regression equation, such as plant age,size, plant condition, sink strengthof fruits, nutrition, water status, air temperature and humidity;h. genetic differences between species.
Points a to d are relevant, asfollows from the discussion above. Point e is ofminor importance. Point f might perhaps play a role, e.g. as discussed withrespect to the differences between expt 3 and 5. Also point gand h might betrue,butthepresent data material cannot provide evidenceforparticular effects.

37

38

Chapter 2

Canopy photosynthesis

2.5

TIME-DEPENDENT VARIATION IN PHOTOSYNTHESIS

2.5.1

Midday depression

Since a long time, it isfrequently reported inthe literature that canopy
photosynthesis mayshow adepression inthecourse ofthe day [seefor instance
Meidner & Mansfield (1968),quoting apublication of 1921 andMadsen (1976),
referring toa publication of 1938]. Such adip iscalled 'midday depression' or
more particular 'midday closure ofstomata' (Meidner &Mansfield, 1968). Someauthors reported a lower P in the afternoon than in the morning hours undersimilar light conditions (hysteresis, e.g. Ito, 1971). Some authors (e.g. Meidner& Mansfield, 1968) suggested that the depression is partly caused by an
endogenous mechanism. On the other hand, it is often discussed which
conditions induced this depression, for instance high temperatures (Heath &Orchard, 1957), water stress (Kitano & Eguchi, 1993), inhibition by excessive
light (Correia et al., 1990) or saturation with starch (Ito, 1971;Madsen, 1976).
2.5.2

Approach

Itwas investigated ifthere wasatime-dependent variation in measured
P, irrespective of the main environmental conditions. This was done bycomparison of measured P(Pmeas)toa'standard' value of P(Pmode|), andto relate
the relative difference [(Pmeas- Pmodel)/ Pmeas]tothetime oftheday. Pmodel must
be obtained by a photosynthesis model that accounts exclusively for
instantaneous effects on P,for instance the model of Acock et al. (1976) or ofThornley (1976). It is preferred to determine Pmode,with the fitted regression
equation (Table 2.3),because these were direct results ofthepresent work andthey were also solely based on instantaneous effects. In case of a midday
depression, Pmeas would be lower than 'normal', so the model would
overestimate the canopy photosynthesis, andthe relative difference would be
negative in the afternoon. A regression line (linear or polynomial) fitted tothe
data, would show a negative trend.
2.5.3

Results

Fig. 2.3 shows the curves of [( Pmeas- Pmode,)/ Pmeas] versus time of theday. First, it can be seen from Fig.2.3athat expt 1 hasthe largest variance inthe data, which is in accordance with the lowest value for r2 (percentage ofvariance explained, inTable 2.3).This plot shows anumber of deeply negativevalues. In this particular experiment, theoverestimation of Pcould be ascribed2.5•• . . • . . ; . ;

10

• . "

12

1

..- •

.

.

Time-dependent variation

39

•

—;—

10

14

12

14

16

„• .

. :-L^::üv:»\..;<r:;*:A.i .

J

" •JV
af
•'.•••*i4v^;'-JriSei.j
iV4L

1 :

%

» -

- •V«x « * S i S A 70* --"Ott' :*'• >. *.-..iV,:>^.t-* ' ' - . ""•
j "='

12

14

16

18

10

12

14

16

'.'• ' . '16time of the day (h)Fig. 2.3 Relative difference in canopy photosynthesis asmeasured and estimated withthe regression equations (Table 2.3) [ (Pmeas - Pmodel)/ Pmeas ] versus time of the day.
Some extreme values are outside the plots, a - f are the experiments as in Table 2.1.

40

Chapter 2

Canopy photosynthesis

to inaccurate measurements, due to not constant C 0 2 concentration (Nederhoff
et al., 1988). In all other experiments C 0 2 was supplied to a constant level.
Generally, the lines plotted in the figures show no systematic decline
during the course of the day. The polynomial curve fitted isoften negative after
16:00, but it isalsooften negative inthe early morning hours.This indicates that
other aspects (for instance the calculation of light interception at lower sun
altitudes) play a role, rather than a midday depression.
It must be emphasized that no photosynthesis measurements wereavailable of very sunny summer days. So the measurements do not provide
evidence for the non-existence of a midday depression in general, but it can beconcluded that a midday depression did not have asignificant influence on thepresent photosynthesis measurements. This conclusion is in accordance withresultsof Handet al. (1992 and 1993a) and Heuvelink (1995a).The latter author
also did not observe hysteresis in canopy photosynthesis of tomato ingreenhouses on sunny summer days under high C.

2.6

Rule of thumb

2.6 A 'C02-RULE' DERIVED FROM THE MEASUREMENTS
2.6.1 Introduction
One of the purposes of the work on photosynthesis is to establish a'C0 2 -rule', i.e. a rule of thumb describing in global terms the effects of C on
production.This is intendedto beapplied by growers andadvisers,for obtaining
asound estimation ofthe expected effect of C 0 2 enrichment. Itcan be a helpful
tool in economic studies and global explorations concerning C 0 2 enrichment.
It is assumed preliminary that the C0 2 -rule can be derived from analysis of theeffect of C on canopy photosynthesis, and that this relation can be transformed
to a relation for the effect of C on growth and production (in chapters 4 and 5).
The C0 2 -rule is intended to be asimilar tool asthe 'light-rule', a rule ofthumb for light utilization. The light-rule, stating: ' 1 % more light provides 1 %more production', was introduced in the seventies (Verhaegh, 1980) and isgenerally applied in the Dutch greenhouse horticulture since then. This simple
linear relationship without light saturation provides a reasonable estimation of
the effect of a difference in light on fruit production. It isconsidered to be valid
in the longer term, i.e. for the duration of atomato cultivation (Buitelaar, 1984;
Challa, 1984). A similar linear dependence was reported by other authors (e.g.
Cockshull et al., 1992).
For the effect of C on P or on growth or production, such a simple
description does not exist, but there iscertainly a need for it in the horticultural
practice. A rule of thumb must, by definition, be a simple expression, allowing
aquick approximation, preferably without usingacalculator. This conflicts withthe fact that the response curve is a saturation type of curve with a (negative)
intercept (Fig.1.1 and 2.2). Gifford (1980) proposed the empirical relationship:
G = G0 * (1 + ß * In ( C / C0 )),with G the net growth and with the subscript
0 indicating areference C 0 2 concentration.Thisequationwas referredto as 'thesimplest one-parameter equation that also shows diminishing returns withincreasing C 0 2 ' (Goudriaan & De Ruiter, 1983). However, this equation is still
too complex for a rule of thumb.
2.6.2

Approach

In search of a simple description of the effect of C on P, it was decided
to focus on the relative effect (X in %) of an increase of 100 umol m o l ' C 0 2 atgiven C. The relative effect declines exponentially with increasing C and tends
to zero. A C 0 2 concentration of 1000 umol mol"1 was (preliminary) chosen as
reference.

41

42

Chapter2

Canopyphotosynthesis

O

£
o
o
Ol
Q.

O
u
u

ê
CD
CD

>

C 0 2 concentration (pmol mol" 1 )Fig. 2.4 Comparison of the 'C02-rule' and the fitted regression equations (Table 2.3)
regarding calculated relative effect of C02 concentration on photosynthesis (in % per
100pmol mot' C02). a - f are the six experiments as in Table 2.1

C02-rule IX=(1000/ Cf * 1.5], eqn. 2.7b

fitted regression equations with incident PAR = 350 pmol s'1 m2
fitted regression equations with incident PAR = 7400 umol s"' m2.

2.6

Rule of thumb

For describing the saturating decline, a statement of the form '1000/C' wasproposed. To approximate the exponential relationship, the ratio 1000/C wasquadrated. It was investigated if the relative effect of 100 umol mol"' increase
in C 0 2 at a certain C could be described by an expression of the form:
X = a, * ( 1000/C )2 + br

eqn. 2.7a

The approach was to adjust this model to make it fit to the regression equations
obtained in the six photosynthesis experiments (Table 2.3). The issuewas not tofind the best fit, but to find one equation with an acceptable fit to all six
experiments. The parameters ar and br should preferably get an easy-toremember value.
2.6.3

Results and discussion

After testing various parameter settings, it was found that a value of 1.5
for parameter argave acceptable results in general,while parameter b,could be
ignored. So the resulting 'C0 2 -rule' proposed here, is:X = ( 1000/C) 2 * 1.5

eqn. 2.7b,
1with 1000 and C expressed in umol mol" , and with the relative effect (X) in %.
In view of the issue, the statistical significance of the fitted parametersar and b, of eqn. 2.7a is not essential. Instead, this C0 2 -rule (with br = 1.5) iscompared to the regression equations, which were fitted to the data sets (Table
2.3). In expt 4, 5 and 6, the C0 2 -rule overestimates the effect (Fig. 2.4).
Parameter b,should be around 1.3to fit to these experiments. In section 2.4.3,
it was already discussed that expt 5 showed a weak response, due to low LAI
and low light. It isarbitrarily decided that ingeneral the proposed C0 2 -rule with
br = 1.5,gives satisfactory resultswhen compared tothe empirically establishedregression models. So the C0 2 -rule may be used as a rule of thumb to roughly
estimate the effect of C on canopy photosynthesis of tomato, cucumber andsweet pepper in greenhouses under normal conditions.

43

44

Chapter 2

Canopy photosynthesis

2.7

TEST OF TWO EXISTING MODELS

EM. Nederhoff & J.C. Vegter,1994b, Annals of Botany73: 421-427.

2.7A

Models, parameters and units

Two well-known models were selected that might be useable forcomputer control or decision support systems concerning C 0 2 enrichment(section 2.1.1): the 'Acock model' (Acock et al., 1976; 1978; Acock, 1991) andthe 'Thomley model' (Thornley, 1976; Thornley et al., 1992). These models arecompact, easy to use, well-documented and applied by several other authors.
These models were to be tested by comparison with the data sets.
Thetwo models havethe main parameters in common,which are listed
below. To distinguish between the two, a subscript A (for Acock) or T (forThornley) is added when necessary. Further a subscript I (for leaf) or c (forcanopy) is sometimes added. To enable comparison of the modelling results,
some unit conversion isapplied,e.g.with respect to C and light use efficiency.
The photosynthesis and respiration rates are purposely expressed in different
units for leaves and for canopies.
The common parameters are:P, = leaf photosynthesis rate (g s"1 m"2leaf area)
Pc = canopy photosynthesis rate (g h"1 m 2 (cropped) ground area)
Rc = rate of crop dark respiration of the canopy (g h"1 m"2 ground area)
R' = parameter for crop dark respiration rate, related to leaf area(g s"'m 2 leaf area)a = initial light use efficiency (light utilization or photosynthetic efficiency)(gJ"1)convertible to quantum yield (1gJ"1~0.0052 mol C 0 2 per mol PAR)C = C 0 2 concentration (pmol mol"1)
C' = C 0 2 concentration after unit conversion (g m 3)
where: C' = cc * C; with cc = 1.83E-3 g m 3
x = conductance to C 0 2 transfer (ms"1)
J = flux of incident photosynthetically active radiation (400-700 nm, W m'2)
L = leaf area index (LAI in m2 m"2)
The subscripts used are:
A = Acock modelg = grossc = canopyo = at top of canopy

T = Thornley modeln = netI = leaf

2.7 Testof two models

2.7.2

45

Modified Acock model

The model for canopy photosynthesis of Acock (Acock, 1991) is similar
to the leaf photosynthesis model in earlier work (Acock et al., 1976; 1978).
These authors considered this early model a satisfactory empirical descriptionof the response to light and C of acrop grown in rows (Acock et al., 1976). The
addition in the newer model (Acock, 1991) is that it accounts for the fact thatthe parameters Rand Tof the leaves change with depth inthe canopy. They are
assumed dependent on the average light received by the leaves in the previous
week. The gross photosynthesis rate is calculated as:
Pcg,A= « c , A * J o * T C , A * C ' * 3 6 0 0 / ( a e # A * J o + T c A * C ' )eqn. 2.8.
Here J0 (PAR at the top of the canopy) rather than J( (average PAR at leaf level)
should be used (Acock, 1992, pers. comm.). The light extinction in the canopy
iscalculated with the classic light extinction formula (Monsi & Saeki, 1953) andis incorporated in the calculation of the C 0 2 conductance (x c A ):xc,A = aA/ (b A * K) * In { [ bA * S0 * K + (1 - m) ] /[ b A * S 0 * K * exp(-K * L) + (1-m) ] }eqn. 2.9,

where:
K = extinction coefficient for light (-)
m = leaf transmission coefficient for lightS = average PAR during previous week (W m"2), S0 is at top of the canopy
aA = constant (8.5E-5 m3 J'1; Acock et al., 1978; Acock, 1991)
bA = constant (2.1E-2 m2 sJ"1; Acock et al., 1978; Acock, 1991)
Canopy light use efficiency (occA) isderived from leaf light useefficiency (cc(;A ):« C A = «!,A * [1 - exp(-K * L)/ (1 - m)]eqn. 2.10.

To obtain the canopy net photosynthesis rate (Pcn A) the gross photosynthesis(P cg A ) is reduced with a canopy respiration rate (R cA ), all in g h~'m"2ground,according to:
Pcn.A = P C g , A - RC,A

eqn. 2 . 1 1 .

Modification. Acock (1991)distinguished photorespiration (calculatedfrom C 0 2
and0 2 concentration atthe chloroplast andfrom C 0 2 and0 2 conductance) andmaintenance respiration (dependent on turnover costs of various leaf
components). Growth respiration was not considered part of the photosynthesis
process. We prefer not to include parameters of which the values are notavailable, like the mentioned 0 2 parameters. Therefore, crop respiration is

46

Chapter 2

Canopy photosynthesis

approximated here (in accordance with Acock et al., 1978)as follows:R

C A = R'A * L * 3600

eqn.2.12,

This equation accounts forthe increasing crop respiration when thecrop grows
during the season. This approach is simple and straightforward. It does notaccount explicitly foravariation in Rof leavesofdifferent depths inthecanopy.
Note that RcA isexpressed ing h"1 m 2 ground area andR'A in gs"1m"2 leaf area.
Here RcA andR'A include the respiration of thewhole crop, whereas Acock etal. (1978) used a leaf respiration term, containing just the leaf component ofdark respiration, divided byLAI.
2.7.3

Modified Thomley model

Inthemodel ofThornley (Thornley, 1976;Thornley et al., 1992)the leaf
photosynthesis rate (P<,T) is simulated by a non-rectangular hyperbola. It is
written explicitly by:
P t T = 1 / ( 2 * 6 ) * { a , , T * J I + P l m ,TSQRT(( a«, T * J,+ P, m,T )2 - 4 * 0 * au T * J( * P, mJ )}eqn. 2.13
where:
6= parameter for curvature of light response curve (0.95)
P(m,T = light saturated value of leaf photosynthesis rate (gs"1 m"2 leaf area)
Both P(m T and a t T (initial leaf light use efficiency) depend on the C 0 2
concentration ( C in g m"3), according:P(m,T = t t T * C 'eqn. 2.14

anda t T = « ( m , T * ( 1 - ( ß / P ( m , T ) ) eqn. 2.15
with:«i m,T = ' e a f light useefficiency at high C (g J"1)ß= parameter for maximum photorespiration (g m"2 s'1 )Canopy net photosynthesis rate ( P c n T in g h 1 m"2) is calculated as:
Pcn T = L * Pt T * 3600 - Rc T

eqn.2.16

with
R c , T = R c m , T * [1 -EXP(-L * R'T * 3 6 0 0 / R c m T )eqn.2.17

with Rcm T = maximum crop dark respiration (0.72 g h"1m"2). Again R'T isexpressed i n g s-1 m"2 leaf area andPcandRcin g h"1 m"2cropped ground area.

2.7 Testof two models

Modification.Toestimate thelight interception, Thornley et al. (1992) assumed
a standard overcast skylight distribution, auniform distribution of light overthe
total leaf area and black canopy rows. Five components of PAR in different
directions were estimated, based on the row dimensions. We think, however,that it is undesirable for real applications, to have to useaccurate estimations
ofthe(changing) canopy sizes andtoestimate five PAR components. Therefore,
although we are aware of the importance of the light interception part in themodel,wesimplify this partbyreplacingtheextensivecalculations and complex
assumptions by one simple equation. Our modification assumes that J, isapproximated by giving it a fixed fraction (Fj) of J0. Fj is defined as the ratio
J, / J0with 0 < F, < 1, andwith J, theaverage PARat leaf level andJ0 PARon
top of the canopy (W m"2 ). Thus:
J( =Jo * Fj

eqn.2.18

Fjmust be derived from radiation measurements inside the canopy or must be
fitted, asdone in this work.
2.7.4

Procedure

The canopy net photosynthesis rate was calculated with the models,
using the 30-min recordings of J0, S0, C andthe observed LAI as input. J0was
obtainedfrom outsidemeasured PAR,multiplied bythecalculated instantaneoustransmission factor ofthegreenhouse cover (section2.2.1). S0wasobtained fromthe PAR recordings by the meteorology service on the Research Station in
Naaldwijk, also multiplied by thecalculated transmission. C was measured in
the experiments. Lwasobtained by interpolating LAI measured periodically.
All modelling and calculating was done with the statistical package
GENSTAT (Payne & Lane, 1987). The goodness of fit between model
calculations and measurementswasexpressedbytheintercept (a),slope (b) andpercentage ofvariance explained (r2)ofthe relation Pmode] = a+ b * Pmeasandby
the predicted error sumof squares (PRESS),which wascalculated as
Z (Pmodei• Pmeas)2 / ( n - 1)• Further in run ii the residuals were examined byplotting (Pmeas- Pmodel)and (Pmeas - Pmodel/ Pmea5)versus C andversus PAR (plots
are not presented).
Both models were tested with all six data sets in various ways:
run i. both modelswith theoriginally published ('standard') parameter values;
run ii. both models with relevant parameters tuned toeach particular dataset;
run iii. modified Acock model tuned to onedata set(expt 6, tomato) andapplied to all data sets;
run iv. modified Thornley model with only the light interception (parameter Fj)
fitted to each data setandthe other parameters standard.

47

48

Chapter 2

Canopy photosynthesis

In run i, the 'standard' parameter values were those reported in the original
papers (Acock et al., 1976 (expt no.4); Acock et al., 1978 and Thornley et al.,1992) as mentioned in Table 2.5 and 2.7, respectively. In run ii, the main
adjustable parameters were fitted using a GENSTATfitting routine, to obtain thebest agreement between the model and the measured photosynthesis data.
Acock et al. (1976) regarded a, Rand x asadjustable. Parameter m has
only a very weak influence on the calculations, so this was assigned a fixedvalue (0.10, which is about the average of the 'standard' values). Also bA was
kept at its standard value, in accordance with Acock (1991). K is theoreticallyof great importance, although varying the value of K between 0.6 and 0.8
caused only little difference in the fitting results. Nevertheless, Kwas estimatedas well. With two data sets (expt 4 and 5), however, the fitting routine did not
succeed in estimating all four relevant parameters in one run.Therefore, K was
given acertain value in the range from 0.10 to 2.00 (increased by 0.02 in every
new calculation) and at each value of K, the parameters cct A , R'A and aA werefitted (aAdetermines TC A ).Thecombination of parameterswith the highest r2 andthe lowest PRESSwas considered the most adequate (only in expt 4 and 5).
The background of run iii with the Acock model was that perhaps somemain circumstances (greenhouse, cultivation method) were principally different
in our experiments and in the experiments that Acock used for the modelling.
This might have a significant effect. Hence, we tested if adjusting the model toone of our data sets would improve the fit to the other data sets.
Thornley et al. (1992) regarded all parameters asadjustable, of which aand Twere relatively important. In run ii,the parameters a I m T , ß, x u , R'T and
Fj were fitted, while 6 and Rc m T were kept at their standard values. In themodified Thornley model, Fj (the ratio J ( / J0, eqn. 2.18) was introduced toreplace the light interception calculation. F, is an essential parameter with adominant influence onthe calculation, but itsvaluewas not known. In addition,F, was fully correlated with cc(m T and hence an auxiliary parameter (a', m T = a,m T * Fj) had to be used in run ii.Then Fjwas fitted separately in run iv, while
all other parameters were kept standard. Subsequently a ( m; T could bedetermined from a' ( m T / Fj (results in Table 2.8). A final test as in run iii with
the Acock model was not possible with the Thornley model, because the lightinterception factor (Fj) was always unknown. Instead, run iv demonstrated how
the Thornley model performed if only Fj was adjusted to the measurements.
Finally the response of both models to the prevailing C was examinedby comparing the photosynthesis - C 0 2 curves of the two tuned, modified
models and of the regression equations derived from the measurements (section
2.4).The regression model wasconsidered asreference,asit reflectedthe resultsof representative measurements. Becauseonly the responseto C isstudied here,
the other conditions were assumed constant, as indicated at Fig. 2.5.

2.7

Testof two models

2.7.5 Results
Modified Acock model
Table 2.5 presents the standard and fitted values of the modified Acockmodel and Table 2.6 the goodness of fit of the various runs. The simulations
with the standard parameter set ST1 (sweet pepper, Acock et al., 1976) mostly
underestimated the photosynthesis rateat high photosynthesis (Table 2.6, run i).
With the parameter set ST2 (tomato, Acock et al., 1978) the fit was equal orworse in all cases (data not presented).
In run ii,which involved parameter fittingtoeachexperiment separately,
the agreement between calculations and measurements was the best, as could
be expected. The PRESS was decreased to 0.1 - 0.2 and of the relation
Pmodei = 3+ b * PmeaSured'^ w a s improved. No correlation was found between theresiduals and C nor between residuals and PAR.
In run iii,with the model adjusted to expt 6 (tomato) and applied to theother data sets, the PRESSand the r2 were more or less comparable to those of
run i, and worse than of run ii (Table 2.6). This demonstrates that the fit does
not depend on certain conditions (greenhouse, cultivation method), typical forour series of measurements.
Modified Thomley model
The results aregiven inTable 2.7 and 2.8.The modified Thomley modelwith standard parameters (run i) largely overestimated the measured data of all
experiments (data not shown), because the light extinction calculation wasomitted and not replaced by an alternative estimation (in run i, F, was taken 1).
In run ii, with all parameters fitted to each experimental data set,the fit
and the parameter values were reasonable, except in expt 3 (discussed below).
Also with this model the residuals were not related to C or PAR. In run iv, with
only parameter Fj fitted to the data sets, the performance was in most cases
acceptable as well, mostly comparable to that in run ii (Table 2.8). This
demonstrates the dominant influence of the light interception in this model.
Models' sensitivity to C 0 2 compared
Fig. 2.5 shows the comparison of the three photosynthesis-C0 2 curves.
Inexpt 2 (Fig.2.5b), thethree curves were about equal; in expt 4 (Fig.2.5d), the
95% confidence interval of the regression model was rather wide; in the otherexperiments, the curves partly overlapped and partly were distinct. In expt 1, 5
and 6the model calculations came out higher than the regression line. It should
be noted that with other values for PAR and LAI taken, the results would havebeen slightly different.

49

50

Chapter2

Canopyphotosynthesis

Table 2.5. Parameters of the modified Acock model. 'Standard' parameter sets fromAcock et al. (1976 and 1978, resp.) and 1 to 6 the sets of parameter values (withstandard error) fitted in run ii to the six experiments. bA=2.1 E-2 m2 sJ'\ m=0.10.
_ _—_data setug J"'
13.7

Standard-2

—
—

10.1

1. cucumber

1218

22.1 (1.7)

2. cucumber

348

3. pepper

556

Standard-1

4. pepper

438

urn'3 J"'pg s"1m"2
0.82

85

38
14

43 (1.4)

32 (2.4)

0.61 (0.1)

17.8 (0.9)

85 b47 (3.4)

1.43 (0.4)

16.0(0.7)

77 (5.2)

73 (3.9)

1.45 (0.2)

18.9 (0.6)

85b27(1.6)b

46 (1.8)

0.60 c0.42 c57 (2.2)

0.94 (0.0)

85

5. pepper

1243

22.7 (0.5)

85

6. tomato1568

21.1 (0.7)

89 (2.2)

0.52

convertibletoquantumyield with 1 gj~' »0.0052 mol mot'value assumedc
bestfittedvaluedeterminedbyprocedure described intext

Table 2.6. Goodness of fit of the modified Acock model to the data of thesix experiments in run i, ii and Hi. PRESS (predicted error sum of squares) is(pmodei - pmeasured)2/(n - V in (g m'2 h'')2>' a is the intercept, b the slope and r2
the percentage of variance explained of the relation Pmodel = a + b * Pmeasured.
run

run i
with parameters
expt standard (Tbl 2.5, ST1)
PRESS
1.

a

b

run iii
with parameter« asfitted totomato (Tbl 2.5 , data set 6)

run iiwith fitted parameters(Tbl 2.5, datasets 1-6)
r2

PRESS

a

b

r2

PRESS

a

b

r2

0.32 0.06

0.80 74.8

0.22 0.26 0.80

80.4

0.47

0.09

1.12 77.5

2. 0.24 0.06

0.73 87.9

0.16 0.12 0.87

88.1

0.21

0.11

1.01 87.5

3. 0.25 0.35

0.73 84.4

0.20 0.16 0.84

85.7

0.55

0.53

1.02 84.8

4.

0.51 -0.34

0.63 84.5

0.15 0.12 0.81

83.3

0.53 -0.53

0.86 83.3

5. 0.11 0.12

0.73 81.2

0.09 0.12 0.79

82.8

0.18

1.02 80.2

6.

0.65 88.8

89.3(0.11) (0.11) (0.89) (89.3)

0.26 0.07

0.11 0.11 0.89

0.19

2.7 Testof two models

51

Table 2.7. Parameters of the modified Thornley model. 'Standard' parameters
are from Thornley et al. (1992). 1to 6 are the setsof parameter values (withs.e.) fitted in run ii to the six experiments. 6 = 0.95, Rcm T = 0.72 g h'1 m2.
• I m,Tug m"2s'1 10" m sdataset

HT

R'T

-t

ugs"1 m 2

400

15.0

50

-

17.0

-

1. cucumber

1218

16.2(0.4)

0.26 (0.002)

31 (8)

3.0 (0.04)

23 (.3)

2. cucumber

348

15.0(1.1)

0.28 (0.004)

58 (24)4.6 (0.3)58(9)0.28 (0.005)400b15.0(1.3)64(10)

56b

5.8 (0.5)66(12)'Standard'

556

3a. pepperc17.6 (0.8)
20.5 (0.8)

0.19(0.003)

4. pepper

556
438

16.2(1.1)

0.19(0.002)

64(13)

3.0 (0.3)52(8)5. pepper1243

14.1 (0.6)

0.35 (0.002)

42 (13)4.8 (0.1)72(4)6. tomato1568

14.8 (0.2)

0.50 (0.004)

111 (5)7.0(0.1)46(4)3b. a s 3 aacand b as at Table 2.5
same data setas atexpt3a,but with otherpreset valuefor ß

Table 2.8. Goodness of fit of the modified Thornley model to the data of the six
experiments in run ii and iv. PRESS (predicted error sum of squares) is(Pmodei - pmeasunJ 2/(n - 1) ' " (g m'2 n'^2 /' a ' s tne intercept, b the slope andr2 the percentage of variance explained of the relation Pmodel = a + b *P,
measured'expt

run iiwith al parameters fitted,
includ. Fj (Tbl 2.7, dataset 1-6)

run iv
with F,fitted (see Tbl 2.7)
and other parameters standard

PRESS

a

b

r2

PRESS

a

b

r2

1.
2.

0.21

0.24

0.81

80.7

0.36

-0.07

0.93

74.4

0.17

0.13

0.87

87.0

0.19

0.11

0.88

85.8

3a.

0.35

0.22

0.73

74.1

0.35

0.26

0.71

74.0

3b.c

0.37

0.24

0.71

72.9

0.38

0.25

0.71

71.7

4.

0.12

0.09

0.86

86.1

0.13

0.07

0.87

85.8

5.

0.07

0.07

0.88

87.7

0.08

0.10

0.84

86.1

6.

0.13

0.11

0.88

86.8

0.21

-0.04

0.93

81.7

c

same experimentas atexpt3a,but with otherpreset valuefor ß

52

Chapter 2

Canopy photosynthesis

2.7.6

Discussion

Fitted parameters
Parameter fitting leads by definition to agood fit, unless the structure of
the model is incorrect. The results, both with theAcock model andthe Thornleymodel, and the fact that the residuals of run ii were not related to PAR and C
demonstrate that basically the models were correct and adequate to fit our
canopy photosynthesis measurements.We discuss herewhether thefitted valuesof our parameters were sensible.
The important parameter for leaf light useefficiency (<x( )came out on
16 - 23 ugJ' (or 0.08 - 0.12 mol mol"1) in the Acock model (Table 2.5). Someof these values were higher than usually observed as maximum values for leaf
initial light use efficiency (0.017 ug J 1 * 0.09 mol mol 1 ), although thetheoretical maximum is far higher (Farquhar et al., 1980; Goudriaan et al.,1985). Acock et al. (1976) reported a range from 5 to 25 ug J"1 for a of thewhole canopy. It is concluded that the Acock model fitted to our data only if
unusually high values of the light use efficiency were accepted.
The values of a fitted by the Thornley model were 1 4 - 1 7 . 6 ug J"1 (or0.07 - 0.09 mol mol"1), and an extreme value of 20.5 ug J"1 (or 0.11 mol mol"1)
in expt 3 (Table 2.7). These values were not much different from those derived
from our own measurements (section 2.4.3) and those reported in the literature(see 'standard' values in Table 2.5 and 2.7).
The values of K fitted by the Acock model were in two cases higher
than commonly reported (K> 1.0).Monsi & Saeki (1953), however, determinedvalues up to 2,the higher values particularly in canopies with horizontal leaves
in a mosaic-like leaf distribution. The cucumber spring crop (expt 2) was sucha crop.
The values of aA (determining C 0 2 conductance, TC A ) in the Acockmodel were about equal to, or lower than, the standard values (Table 2.5). Also
T tT in the Thornley model came out lower than the standard values (Table 2.7),
except in expt 3a, owing to correlation with ß (see below). The fairly low xt
might be explained by the moderate light intensities and the relatively high C
in our experimental data. Both conditions significantly reduce the leaf
conductance by stomata closure (Raschke, 1975; chapter 3).
The fitted values for crop dark respiration (R' in Table 2.5 and 2.7)
ranged from 23 to 73 ugs"1m"2leaf area.The 'standard' values were 14, 38 and50 ug s"1 m"2 leaf area, but these values were supposed to involve just the leaf
component of dark respiration. In Acock et al. (1976) the values for dark
respiration of the crop varied from 75 to 200 ug s"1 m"2 (probably m 2 groundarea). Sothe fitted values andthe variation in values agree with published data.

2.7 Testof twomodels

C 0 2 concentration (pmol mol" 1 )Fig. 2.5 Sensitivity of photosynthesis models to prevailing C02 concentration. Canopy
net photosynthesis rate (P in g h'1 m'2 ground area) as function of C02 concentration(pmol mor'), calculated for 100 W m'2 incident PAR,and for observed LAI (Table 2.1).
a - f are the six experiments as in Table 2.1.
regression model fitted to measurements, with 95% confidence limits;
modified Acock model with fitted parameters (Tables2.5 and 2.6ii);
modified Thornley model with fitted parameters (Tables2.7 and 2.8H)

53

54

Chapter 2

Canopy photosynthesis

The fitted values for parameter ß (photorespiration) in the modified
Thornley model were far lower than the reported value. Because in expt 3, thefitting ofthefour selected parameters could not beachieved, ßwas preset. With
the standard value (ß = 400 ugm 2 s 1 ), t t Tcame out far lower than in the otherexperiments. If ßwas chosen in the same order of magnitude asthe other fitted
values (56 ug m"2 s~1), also the value of T I T was in agreement with the othervalues of x(, T (Table 2.7, expt 3b). So further (e.g. in Fig. 2.5) data set 3b wasused for this experiment.
Responses to C 0 2 and light
The responses to C are shown in Fig. 2.5. The curves of the regression
model were explained by the conditions duringthe measurements (section 2.4).
For example, the apparently weak response of Pto C in expt 5 (Fig. 2.5e), wasexplained by poor light conditions during the measurements. At low light, theeffect of C is less pronounced (Gaastra, 1959). It is remarkable, but not
explicable, that the modified Acock model and the modified Thornley modelboth hada higher maximum photosynthesis rate and astronger response to lightand C than the actual crop in expt 1, 5 and 6.
Inthe C 0 2 range below 500 umol mol"1,theThornley model responded
stronger to Cthan the Acock model and than the regression equation (Fig. 2.5).
Incontrast to the Acock model,the Thornley model accounts for the Ceffect ona (eqn.2.14 and2.15).Moreover, theThornley model usesalinear dependencyof P(m,To n C (eqn. 2.14), while a weaker relation would be more realistic. A
shortcoming of the Acock model is that it does not account for the effect of C
on the light useefficiency a (only on the gross photosynthesis Pcg A ). The fitting
routine established only one value for a for the whole data set. For atest, a in
the Acock model was calculated per data record, in dependence of measured
C, using the theory of Goudriaan et al. (1985). However, this enhancement did
not improve the performance of the modified Acock model.
Finally, it isconcluded from Fig.2.5 andfrom the fact that the residualsof run ii were not correlated with Cand PAR,that the modified Thornley model
performed moderately, and the modified Acock model reasonably.

2.8 Discussion

2.8

DISCUSSION

Here the approach for photosynthesis research isevaluated, particularly
with respect to the measurements, as these comprised the greater part of thework. Because it was emphasized that the measurements had to be done on alarge scale (whole greenhouses), rather than on laboratory scale, it isreconsidered what the reason was for this approach and if it has been
worthwhile. Further, the reliability of the obtained results is evaluated.
Generally, after a model has been developed, it needs to be evaluated,possibly by comparison with reality (i.e. validated). The reality of a large
greenhouse production system cannot be imitated by a small cuvette, becauseof the following differences. In cuvettes mostly leaves or seedlings areinvestigated during a short observation period, whereas in greenhouses large
crops can be investigated for a longer period, including the harvest period. The
conditions in a small-scale set-up are normally constant; often artificial light isused with a light flux far below that of the natural light. In greenhouses,
however, the natural light conditions occur, with large fluctuations and highamplitudes. In a cuvette, the leaves are directly lit, whereas in a greenhousecrop there is a great temporal and spatial variation in light interception. Thisimplies that a model of leaf photosynthesis must be combined with a model for
light distribution, to calculate the crop photosynthesis. Respiration, which has
a great impact on net photosynthesis, comprises more components in a canopy
than in a single leaf.
The aspects mentioned are all implicitly incorporated in large-scale
experiments,where netcanopy C 0 2 uptake ismeasured incombination with therelevant explaining conditions. The argumentation for this approach is that theobtained data can directly be used for validation of a model, while the model
can be implemented in practical applications without further enhancements (e.gthe model of Gijzen, 1992; Gijzen et al., 1995). The data were also used toderive the so-called C0 2 -rule, describing the effects of C 0 2 on photosynthesis.
Becausethis rule isderivedfrom measurements insemi-commercial cultivations,
it is directly applicable to practical situations. Without measurements ingreenhouses, such results could not be accomplished directly.
Important for the merits of the obtained data sets istheir reliability. The
accuracy of the photosynthesis measurements was estimated by error analysis(section 2.3). This showed that the majority of the data is reasonably accurate(± 10%) and about 5% ofthedata contain a large inaccuracy. However, Fig.2.3
reveals a large variance, indicating that many observations (Pmeas) have a large
relative discrepancy to the 'standard' canopy photosynthesis (Pmode|) under theconditions recorded. This is not necessarily caused by to inaccuracy in thephotosynthesis measurements, but can be ascribed partly to errors and

55

56

Chapter 2

Canopy photosynthesis

inaccuracy in the measurements of the environmental conditions (input to theregression equation that yielded Pmode,in Fig. 2.3).
For instance, the light received by the canopy was approximated frommeasurements outside. This was done on purpose, because light measurements
inside the greenhouse always give serious complications by local shading of thesensor. An estimation of the instantaneous light transmission coefficient wascalculated on the basis of sun altitude and estimated ratio of direct and diffuse
light (section2.2.1).Thisestimation contributestothe inaccuracy. As Presponds
to quantum flux, while energy flux was measured,this conversion increased theinaccuracy. The measurements of the C 0 2 concentration might have an
inaccuracy of about 5%, in spite of frequent calibration. Air temperature
measurements are estimated to be fairly accurate (± 0.2 °C), which error ishardly of importance for the photosynthesis calculation.
The variance in Fig. 2.3 is considered an inevitable consequence ofmeasuring in semi-practical greenhouses. The spreading in the data iscompensated for by the great number of observations, and hence the data sets
were considered suitable for interpretation and modelling. The percentage ofvariance explained by the regression equation, may be increased by a morerefined analysis.
It is concluded that the data sets are valuable, as they arecomplementary to other, more refined measurements in laboratory experiments.
Theyprovide information onthefunctioningofactual cropsunder representative
conditions. It isaccepted that measurements on this scale are lessaccurate thanpossible in laboratory experiments.

3.1 Introduction

3 Effects of C 0 2
on leaf conductanceand canopy transpiration
3.1

INTRODUCTION

3.1.1

Outline of the problem

Besides the positive effects of a high C 0 2 concentration (C) on plants
mainly viathe photosynthesis (chapter 2),also negative sideeffects of high Careknown (section 1.3). Some side effects might be caused by a reduction of thestomatal conductance (g) and hence of the canopy transpiration (E) underelevated C.
High C may improve the water use efficiency by increased
photosynthesis and reduced transpiration (Kimball & Idso, 1983; Morison &Gifford, 1984; Radoglou et al., 1992; Bowes, 1993),which isfavourable in caseof scarcity of good water. In other cases, however, reduced transpiration may
be more or less disadvantageous: it may increase the leaf temperature,
particularly under high radiation, and in the long term, it may induce local
mineral deficiencies of those nutrients that depend for translocation on thetranspiration flow (Mengel & Kirkby, 1978). Excessive leaf temperatures andinsufficient nutrient translocation are unfavourable for plant growth and fruit
production.
Stomata respond to C of the surrounding air. A C 0 2 concentration ofseveral thousands umol mol"1 can disorganize the stomata, so that they arewidely open, even at night (Hollander & Krug, 1992). For the range underconsideration (about 200 -1100 umol mol"1), it isoften observed that increased
C decreases the stomatal opening (Freudenberg, 1940; Heath, 1948; Kuiper,
1961; Raschke, 1975; Burrows & Milthorpe, 1976; Morison, 1987). There is nocommon opinion about the effect of C on E.It is sometimes reported that highC reduces the transpiration of greenhouse crops (Mortensen, 1987). Such aneffect was indeed established on the scale of leaves and plants in controlledenvironment chambers (Janes, 1970), or in 'mini-greenhouses' (Shaer & Van
Bavel, 1987). In other experiments on transpiration, however, no significant C

57

58

Chapter 3 Conductance and transpiration

effect was observed (Stanghellini, 1987; Jolliet & Bailey, 1992). These latter
experiments were done in large greenhouses.
C does not directly affect E,other than through the stomata. About therelation between g and E, two views can be found, a physiological one:"transpiration is considerably controlled by stomata" (e.g. Raschke, 1975) anda physical one: "transpiration is determined by environmental factors, mainly
radiation and vapour pressure deficit" (e.g. Penman, 1948; Stanghellini, 1987).
Jarvis &McNaughton (1986) investigatedconductance and transpirationin systems of different scale (single pore, leaf, plant, canopy, region) andconcluded that "one cannot naively extrapolate from one scale to the next".
These authors proved that the scale of the system determines to what extent the
conductance and transpiration are related, which can be expressed by a socalleddecoupling factor. Decoupling of conductance andtranspiration is owing
to feedback effects (Burrows & Milthorpe, 1976; Jarvis, 1985; Jarvis &McNaughton, 1986), which can be particularly strong in greenhouses (Aubinet
et al., 1989). Therefore the feedbacks needed to be considered here. The
principle is exposed in Fig. 3.1 (section 3.1.7).
Another point of discussion iswhether stomata adapt to long-term highC, like the photosynthetic efficiency appears to do (e.g. Von Caemmerer &Farquhar, 1984; Yelle et al., 1989a,b). Imai & Murata (1978) observed such anadaptation of stomata, but Jones and Mansfield (1970) found that the stomatalbehaviour generally did not adapt to long-term C 0 2 conditions. Hicklenton &Jolliffe (1980) reported that the stomatal resistance did not adapt to C in theearly stage of leaf development, whereas a number of other features related toleaf photosynthesis did adapt. Radoglou & Jarvis (1992) observed that thestomatal density and stomatal index arenot affected by C; Penuelas & Matamala(1990) found that the stomatal index has not changed in response to the raiseof the C 0 2 concentration in the atmosphere in the last centuries. A goodunderstanding of the occurrence of stomatal adaptation in greenhouse cultures
is required.
Finally, it can be questioned if there is a time-dependent variation intranspiration. It has been reported that crops might have a 'midday depression'or declining photosynthetic and transpirational activity during the course of theday, as mentioned for photosynthesis in section 2.1.1 and 2.5. Also this aspectneeds to be considered under realistic greenhouse conditions. Before theobjectives are formulated in section 3.2.1, first some basic features about
conductance and transpiration are exposed.

3.1 Introduction

3.1.2

Stomata

Stomata are pores with their adjacent guard cells, in the epidermis ofleaves, through which C 0 2 enters and water vapour leaves the leaf interior.
Stomata are roughly 20 urn long and the pore area (pore density multiplied by
maximum pore opening) lies in the order of 0.5 and 1.2% of the leaf area
(Ticha, 1982). The number of stomata is about 1 per 5 cells (stomatal index) or
100 - 450 stomata per mm 2 (stomatal density) in the lower side of a fully
expanded leaf of a greenhouse fruit vegetable crop. The number of stomata issignificantly higher in the lower (abaxial) leaf side than on the upper (adaxial)
leaf side in most plant species (Cay & Hurd, 1975; Ticha, 1982; Woodward &Bazzaz, 1988).
The rateof gasexchange between leaf and environment is not primarily
dependent on size, index or density, but on the average degree of opening of
the stomata. The stomata are continuously in motion and do not all have thesame relative opening at a certain moment. Opening and closing of a stoma is
controlled by variations in osmotic pressure in the two guard cells, which ismediated by the quickly varying concentration of K+in these guard cells, whichis influenced by two internal feedback loops, a C 0 2 and a H 2 0 loop (Raschke,1975). These are affected by internal and external conditions (see below). The
stomata operate according to a refined strategy, optimizing either thetranspiration or the C 0 2 assimilation,while achievingasecond-best solution forthe other process. So C 0 2 assimilation and transpiration are influenced bystomatal opening, but in turn, these processes have a (direct or indirect) effecton the stomatal opening (Farquhar et al., 1978; Jarvis & Morison, 1981).
3.1.3

Other conductances

The stomata form one of the barriers for gases in the pathway fromambient air to the interior of plant leaves. Other internal barriers, in series withthe stomata, are formed by the cell walls and the substomatal cavity. The
resistances of these barriers are negligible (Burrows & Milthorpe, 1976;
Monteith, 1973). Parallel with the path through the stomata isthe path throughthe cuticle. However, the cuticle resistance isso large,that this path usually canbe neglected compared to conduction through the stomata. Therefore, thestomatal conductance is often considered equal to leaf conductance (thecombination of stomatal andcuticle conductance),which can be measured witha porometer. An important external barrier between leaf and surrounding air isformed by the boundary layer. The boundary layer conductance is of the sameorder of magnitude asthe leaf conductance and may have an important impact
on the gasexchange. Hence,the boundary layer conductance must be carefully
considered (section 3.3.5).

59

60

Chapter 3 Conductance and transpiration

3.1.4

Diffusion

Transition of gasesthrough astoma is adiffusion process.According to
the gas diffusion theory, the flow rate (F in m 3 m"2 s"1) of a gas through a
medium is described by F = -D * dC/dz with C the gas concentration(umol mol"1), z the path length (m) between two points x and y and D the
diffusion coefficient (D H 2 0 =2.19E-5 *(T/273) 1 8 and D C 0 2=1.40E-5 *(T/273) 1 8
m 2 s"1). For a finite length z, this is approximately equal to:
F = g * (Cx - Cy)

eqn. 3.1
1

1

with g = 1/r = D/z. g is conductance (m s" ) and r is resistance (s rrf ) to gas
transfer. So stomatal conductance can be defined as the proportionality
parameter relating the water vapour flux through the pore, to the driving force(Burrows & Milthorpe, 1976 and Jarvis & Morison, 1981).
In the same medium, the conductances for C 0 2 and for H 2 0 are
different, becauseof different diffusion coefficients, depending onthe molecularweights of the gases. It is generally adopted that the leaf conductances of C 0 2
and H 2 0 are related as g ( C 0 2 = 0.6 * g( H 2 0 , and the boundary layer
conductances as g b C 0 2 = 0.7 * g b H 2 0 (Burrows & Milthorpe, 1976;
Goudriaan & Van Laar, 1978).
3.1.5

Units of conductance

Instudies on transpiration, the stomatal opening ispreferably expressedasconductance orconductivity, ratherthan asresistance,because resistancecan
give a misleading impression. At wide stomatal opening, the resistance (with ahyperbolic curve if plotted against stomatal opening) shows only very smallchanges,whereas changes in conductance (related linearly to stomatal opening)are still large (Burrows & Milthorpe, 1976; Hall et al., 1976). The units used arem s"1 or mm s"1 (mm 3 water vapour transfer per mm 2 leaf area per second).
Alternatively, the unit mol m"2s"1issometimes used(conversion inAppendix III).
3.1.6

Stomatal action

Stomatal conductance at a particular time is determined by various
conditions, like incident quantum flux, humidity of the ambient air, leaf
temperature, ambient carbon dioxide concentration and mineral nutrition. Alsointernal plant parameters play arole, like leafwater potential, leafage, leaf ABAcontent (influenced by previouswater stress)andmineral composition (Burrows& Milthorpe, 1976). Drought stress leads to stomata closure. Plants that haveexperienced (drought) stress are more sensitive to C 0 2 (Lenz & Huch, 1986),
which is probably caused by a higher content of ABA (Raschke, 1975; Davies

3.7 Introduction

et al., 1 9 8 1 ; W i l l m e r et al., 1988). Also certain cultivation measures may havean influence, e.g. high fruit load may increase the stomatal conductance (Hall& Milthorpe, 1978).
Stomata tend to close in response to increasing C (section 3.1.1). In
addition, several interactions are k n o w n between C and other factors w i t hrespect to stomatal conductance (Morison, 1987). A concept of a response
pattern of g to C is that the stomata tend to conserve a constant internal C 0 2
concentration (Cj), or (at varying ambient C 0 2 , C a ) a constant ratio C, / C a(Goudriaan & V a n Laar, 1978; Bell, 1982). This explains the large stomatal
aperture at more light, i.e. at higher photosynthesis rate (higher F in eqn. 3.1).
Also the partial stomata closure at high C is in line w i t h this concept.
3.1.7

Relation between conductance and transpiration
It seems logical that reduction of stomatal conductance causes a

reduction in transpiration. However, conductance and transpiration aredecoupled to some extent, particularly in greenhouses (Burrows & M i l t h o r p e ,1976; Jarvis, 1985; Jarvis & M c N a u g h t o n , 1986). This is explained in Fig. 3 . 1 ,depicting the course of eventsf o l l o w i n g a stepwise increase in
C.

High

C

causespartialstomatal closure (reduced g) andthus initially reduces f of leaves.
Reduction of the transpirationslightly

increases

the

leaf

temperature and decreases theabsolute h u m i d i t y (i.e. increases
the vapour pressure deficit, V P D air), first in the boundary layer
and later also in the surrounding
air. Increased leaf temperatureand reduced absolute humidity
imply an increase of the vapour
pressure deficit

betweenthestomatal cavities and the air(VPD-leaf-air). A n increase inV P D reduces g (Bakker, 1991a),thus enforcing the effect of C on
g. O n the other hand, increased
.,„„.
,-,,
. .
V P D increases t through a larger0°
driving force, thus counteracting
the effect of stomata closureF'S- 3]
Schematic representation of thethermal and hydrologie feedback loops.-„«.,„„^,-„„ ; tJ ,^influencing leaf conductance and canopy
transpiration of plants in a greenhouse.
symbols:+ synergistic; - antagonistic effect.

61

62

Chapter 3 Conductance and transpiration

through C on E. The phenomenon of adapting leaf temperature with its
consequences is called 'thermal feedback' and the adapting air humidity with
its consequences is 'hydrologie feedback'.
Inanopen field cultivation,only the air humidity insidethe canopy will
adapt, while in a protected cultivation also the humidity of the greenhouse air
will be affected. This explains that the gain (i.e. the strength) of the feedback
loops is usually stronger in a greenhouse than in the open field. The gain
depends on the conditions, like ventilation rate and size of the crop. The
hydrologie feedback isstronger in agreenhouse with lessventilation, weaker inawell ventilated greenhouses and negligible in the open field. The thermal andhydrologie feedbacks are more important with larger LAI (Aubinet et al., 1989).
Hence, it is not surprising that different results were reported (section 3.1.1)
regarding effects of C on transpiration of greenhouse crops.
3.1.8

Decoupling factor

Jarvis & McNaughton (1986) definedadecouplingfactor (Û)to describe
how the saturation deficit at the leaf surface near the pores is linked to that of
the air outside the boundary layer. This same decoupling factor Q was used torelate changes in conductance and transpiration. Q indicates then the extent ofcontrol of one entity by the other, e.g.:
dE/ E = (1-Q) * dgs / g5

eqn. 3.2

Ü isdimensionless with values between 0(fu11 coupling) and 1(full decoupling).
A value of Q close to unity indicates that the transpiration is insensitive tochanges in stomatal conductance. As described above, the coupling between
stomata and transpiration is weak (Ci is high) in a greenhouse-canopy system,
which must be ascribed to the feedback. This can be illustrated by comparing
different systems: single pore, leaf, canopy.
At one single pore, without a boundary layer above it, the external
conditions are not influenced by the small amount of water vapour transpired
through this pore into the space, so the conditions near the pore and in thesurrounding air are strongly linked. Hence Q is close to 0 and the water vapour
flux under given conditions is fully controlled by the stomatal opening. If a leaf
with a boundary layer is considered, with numerous pores, the humidity near
the leaf surface is influenced by the transpiration rate through these pores. The
conditions in the boundary layer are less linked to that inthe surrounding air (Qbetween 0 and 1) and the transpiration is not only dependent on the pore
opening. In a whole canopy, the conditions near the pores and in thesurrounding air areusually weakly coupled (Qcloseto 1).This holds particularly3./ Introduction

at a high boundary layer resistance, i.e. low air velocity. The impact of stomata
on transpiration issmall under thesecircumstances. Because in greenhouses the
air velocity is usually low, the boundary layer effect is strong and conductanceand transpiration are largely decoupled. In addition, the absolute humidity isadapted, not only in the boundary layer, but even in the surrounding air of aclosed greenhouse.
3.1.9

Leaf temperature

The temperature of a leaf depends on in- en effluxes of energy, in theform of short- and long-wave radiation, convection, évapotranspiration (orcondensation) and a storage flux (photosynthesis and thermal energy). Under
normal Dutch greenhouse conditions,atdaytime,the leaftemperature is usuallyhigher than the average temperature of the surrounding greenhouse air. The
main energy efflux is caused by evaporation (Stanghellini, 1987). This can be
regarded as 'leaf cooling by transpiration'. The possible influence of elevated C
on thisenergy balance consists of areduction ofthe leaftranspiration (by partial
stomata closure) and consequently an increase in leaf temperature.

63

64

Chapter 3 Conductance and transpiration

3.2

OBJECTIVES AND APPROACH

3.2.1

Objectives

The work in this chapter aims at quantifying the effects of the C 0 2
concentration (200 - 1100 umol mol"1) on stomatal conductance, canopy
transpiration and leaf temperature of the fruit vegetable crops tomato, sweet
pepper, cucumber and eggplant in greenhouses. This must enable evaluating
relations ofthese features with possible negative side effects of C 0 2 enrichment(increased leaftemperature and in chapter 4 nutritional aspects).Also a possible
adaptation of the stomatal response to long-term C 0 2 enrichment had to be
examined, aswell asthe occurrence of amidday depression. Because the effectof C on transpiration may appear so differently when observed on different
scales, the investigations were done in greenhouses of a considerable size andunder realistic conditions, to allow transfer of the conclusions to practicalhorticulture.
3.2.2

Experimental approach

To investigate the effects of C on leaf conductance and transpiration,these entities were measured in full-grown crops in large greenhouses under
different, controlled C 0 2 concentrations between about 200 and 1100
umol mol" 1 . For leaf conductance, a regression model was fitted to themeasurements, which describes the dependence of gon radiation, air humidity,
C 0 2 concentration and optionally leaf temperature.
With transpiration, the effect of C is primarily an effect of stomata
closure (i.e. of g) and secondly of adapted VPD-air and leaf temperature.
According to Jarvis (1981), variations in transpiration rate can be estimatedadequately by the Penman-Monteith combination equation (P-M model,Monteith, 1965, section 3.3.5), implemented with leaf conductancemeasurements from a diffusion porometer. So it is assumed that the effect of C
on Ecan be approximated by the P-M model for the effects of g on E, combinedwith the regression equation for the effect of C on g, with the adapted VPD
taken into account by using the actual (measured) VPD values as input data. It
was tested if this approach yielded a satisfactory description of canopy
transpiration, by comparing measured and calculated transpiration at various C.
The P-M model was preferred above other models, because it is auniversal, well-established, well-documented and yet a simple model. In a
comparison of measurements and models, a simplified Penman model gave
good predictions on average (Jolliet & Bailey, 1992). However, the individual

3.2

Objectives and approach

65

variations were large, because that version of the model did not account for
stomatal conductance. The extensive Penman-Monteith combination equation,
however, which is used here, incorporates the stomatal conductance. In workof Zhang & Lemeur (1992), the P-M model results were close to measuredévapotranspiration.
To describe the effect of C on E,it is necessary to know what the effectis of achange in g on E.It is beyond the scope of this study to perform detailed
measurements on leaf conductance, leaf temperature, transpiration, airtemperature, humidity and turbulence, with their spatial variation, aswell as of
the boundary layer and the feedback loops in the crop-greenhouse system. It
was considered sufficient to obtain aglobal description of the relation of g and
E. Hence, the relation between g and E was investigated on the basis of
calculations with the regression equation for g and the P-M model for E,after
validation of these calculations with the measurements.

66

Chapter 3 Conductance and transpiration

3.3

METHODOLOGY

3.3.1

Set-up of experiments

Conductance and transpiration were measured in four experiments,
where the C 0 2 concentration was varied. All experiments were performed in
Venlo-type glasshouses, either in one greenhouse compartment (tomato), or intwo (sweet pepper and eggplant) or in three (cucumber). The compartments
were large enough (over 150 m 2 ) to avoid edge effects in the measurements
and to be comparable with commercial greenhouses, for instance regardinghydrologie feedback effects. Eachcompartment was independently controllable
with respect to environmental conditions and irrigation. Climate control,
irrigation and data acquisition were made by a micro computer connected to a
VAX network (Bakker et al., 1988).
The greenhouses were provided with a pipe heating system and withventilation windows in the roof. Both were used exclusively for temperature
control. In contrast to artificially controlled chambers, it is difficult in large
greenhouses to maintain a desired humidity. Although some humidity control
is possibly by means of heating and ventilating, it was preferred in all
experiments notto control,but only to recordthe air humidity. Temperature andhumidity were measured by calibrated, shielded and aspirated PT-100
psychrometers (dry and wet bulb temperatures), about 1.5 m above the ground.
The data of three sensors per compartment were averaged and used for the
analysis. More specific information on climatic conditions is given per
experiment.
During most measurements, no severe heating was necessary.
Nevertheless it must beconsidered how the heating pipe temperature should betaken into account in the analysis. It has been suggested that warm heating
pipes promote the crop transpiration (De Graaf & Van Den Ende, 1981).
However, this is no particular heating pipe effect (i.e. no direct radiative effectof the heating pipes) but an effect of increased temperature and decreased air
humidity on transpiration (Jolliet & Bailey, 1992).Also Stanghellini (1987) foundthat a particular effect of the heating pipes on transpiration was relatively
negligible, provided the resulting actual air temperature and humidity weretaken intoaccount. Hencetemperature and humidity ofthe greenhouse air wereconsidered asfactors in a multifactor analysis and heating pipe effects were nottaken into account as a distinct factor.
All cultivation measures were made in a standard way, i.e. according
to the current guidelines for the commercial practice. Certain conditions

3.3 Methodology(drought stress, fruit load) might have an impact on the stomatal behaviour(section 3.1.6). To prevent drought stress, much care was paid to optimize thewater supply. The plants,all grown on rockwool,were frequently irrigated, from
5 times per day in spring up to 35 times per day in summer. The plants were
irrigated with a standard nutrient solution,different for each crop (Sonneveld &Straver, 1989). The required amount and frequency of irrigation was calculatedwith asimple transpiration model (De Graaf, 1988). Always an oversupply was
given, mostly of about 30%, and the excess was drained out. The amount ofdrain water was measured and the signal was used for feedback control of theirrigation.
Pure C 0 2 was supplied through a distribution network, consisting of
perforated polyethylene tubes, 3.2 m apart onthe ground, below the plants. The
C 0 2 supply was automatically controlled, according to a certain strategy(described per experiment).
VPD-leaf-air was derived from the measured dry and wet bulb air
temperature and measured leaftemperature, assumingsaturatedvapour pressurein the stomatal cavities. Leaf temperature was measured during the leaf
conductance measurements with athermocouple inthe porometer. Inatest withmeasurements on a great number of leaves, this sensor gave on average equalvalues as a separate, hand-hold thermocouple attached to the leaves.
Photosynthetically Active Radiation (PAR, or light flux, waveband
400 - 700 nm)was usedfor analysis of leaf conductance, while global radiation
was the explaining factor for transpiration, in accordance with the theory(Raschke, 1975; Jarvis, 1981). PAR at leaf level was measured with aquantum-sensor (Ll-190s-1, LI-COR, Lincoln, Nebraska) mounted on theporometer. Hence, these PAR measurements were done only during the
conductance measurements. Global radiation outside was measured
continuously with a solarimeter (type CM11, Kipp, Delft, the Netherlands) on ameteorologietower. When required,an approximation of PARwasderived fromthese measurements by unit conversion (Appendix III).
The transmission of the glasshouse cover for diffuse light wasdetermined occasionally under an overcast sky, using two identical energyresponse PAR meters (TFDL, Wageningen, The Netherlands). One was placedoutside and one inside the greenhouse above the canopy. This coefficient was
found to be 55% in the glasshouse used for the eggplant experiment and 65 to
70% in the other experiments. The actual transmission of the glasshouse cover,
however, may fluctuate considerably, particularly when overcast and sunny
weather conditions alternate. Except in sweet pepper, the instantaneoustransmission was computed according to Gijzen (1992) using the transmission

67

68

Chapter 3 Conductance and transpiration

model of Bot (1983), the measured transmission coefficient for diffuse light, thecalculated sun position and the calculated ratio between diffuse and direct
radiation (Spitters et al., 1986).
The measuring cycle was 1 min for global radiation, temperatures andtranspiration, and 4 min for C 0 2 . These data were averaged over the timeinterval required for one series of conductance measurements (8 to 20 min).
3.3.2

Measuring conductance

Leaf conductance for water vapour was measured with a null-balancesteady state (continuous flow) porometer (model 1600, Li-Cor, Nebraska, USA),
attached to a single leaf. About 20 to 60 seconds after a leaf was enclosed, thereading was transferred to a portable micro-computer.
Mostly 10 (sometimes 20) leaves were sampled in one series,to obtain
one average value. This took about 8 (or 16) min. The leaves were selected at
random, so usually in subsequent cycles other leaves were sampled. Stomatal
aperture declines with ageing of leaves (Field, 1987; Willmer et al., 1988) andstomata of older leaves respond less sensitive to Cthan those of younger leaves(Lenz & Huch, 1986). To standardize for leaf age, always full-grown, but still
fairly young leaves were sampled on a standardized position (different perexperiment). Conductance was always measured on the underside of leaves
only, because by far the greatest number of stomata occur on this side in mostcommonly applied species (Ticha, 1982). Because conductance was measured
comparatively under low and high C, itwas sufficient to measure only the lower
leaf side.
3.3.3

Measuring transpiration

Transpirationwasmeasured (except ineggplant) byweighing lysimeters,
consisting of high accuracy balances (type ED-60-T, Berkel-Patent, Rotterdam,
the Netherlands). The capacity was 90 kg and the inaccuracy about 10 g(resolution 2 g, reproductivity 6-8 g). There were three lysimeters percompartment, one on the east side and two on the west side of the double plantrows under the gutter. Basically the results of the three lysimeters percompartment were averaged before data analysis (details described per
experiment). Each lysimeter, located in the middle of a crop row, carried arockwool slab with two or three plants (different per experiment). These plants
received the same treatment, including water supply, as all other plants in thecompartment.

3.3 Methodology

The lysimeters were connected to the VAX computer and weremonitored every minute. A decrease in the weight of the whole system (plants,
rockwool and drain collector) was a direct indication of transpiration. Surplus
water drained out of the system andwasweighed separately. The calculation oftranspiration was corrected for water deliveries and for drain. The lysimeters
were sampled every min, and the readings were smoothed over intervals of 8
to 20 min.
3.3.4

Analysis of conductance measurements

The instantaneous measurements ofgwere analyzed with regression, toaccount for the effects of various factors. Based on the literature (section 3.1.6)
the following factors were considered most relevant: incident PAR (light flux atcrop level, lc), VPD-leaf-air (D { _a), C 0 2 concentration (C) and optionally leaf
temperature (T{ ). Other factors were assumed equal in the crops to becompared, or negligible. An equation of Burrows & Milthorpe (1976) was used
to relate g to PAR:g = c / * (1 - c 2 * EXP(-c3 * lc))

eqn. 3.3.

For the effect of VPD-leaf-air on g the equation was: g = c / ' * EXP(-c4 * D{.a)(Bakker, 1991a). For the response of g to C the same exponential curve waschosen, because g responds similarly to VPD and to C (Burrows & Milthorpe,1976), thus: g = c / " * EXP(-c5 * C). The effect of leaf temperature (T{ ) on
stomatal conductance can be described by g = c / ' " / (1 + c 6 * (Tt - c 7 ) 2 )(Stanghellini, 1987).
Some correlation between certain factors was inevitable (e.g. a highradiation is generally accompanied by high temperature, high VPD-air and lowC), but it was checked that fairly wide ranges of combinations of conditions
were present in the measurements andthat Cwas not correlated to VPD (Tables
3.1, 3.2, 3.5, 3.6, 3.9, 3.10).Also some interactions between factors might exist,
with respect to stomatal response. Thus the regression equations for the effects
ofvariousfactorswerecombined by multiplication (Stanghellini, 1987), yielding
the following regression equation for four factors:
g = c, * (1 - c2 * EXP(-c3 * lc)) * EXP(-c4 * D(.a) * EXP(-c5 * C) /(1 + c 6 * (T( - c7)2)
eqn. 3.4.
The parameters c1 to c 7 were fitted to the data. Parameter c 1 represents thesaturation value of conductance, c 5 describes the C 0 2 influence and c 7 is theleaf temperature at which g is maximal. The regression analysis was built up

69

70

Chapter 3 Conductance and transpiration

stepwise, by fitting first just the PARterm (eqn. 3.3), then adding the other terms
one after each other and ending up with the full equation (eqn. 3.4).
The multiplicative structure of eqn. 3.4 allowed the expression of the C
effect in one simple relative figure, derived from parameter c 5 . The relative
decrease in conductance was expressed in % per 100 umol mol" 1 increase of
C. The results are valid at any level of radiation, VPD-leaf-air and C, in therangesachieved inthe measurements (presented per experiment), and under thecondition that other factors than C remained constant.
3.3.5

Analysis of transpiration measurements (Penman-Monteith model)

The impact of radiation on transpiration was examined with the simple
linear equation (yielding Er ):Er = c 8 * 1000 * Q n / A,

eqn. 3.5

with Athe vaporization energy of water (2.45E6Jkg"1) andwith afactor for unit
conversion (1000 g kg"1). Q n was net (absorbed) radiation,obtained from global
radiation measured outside, corrected for transmission through the greenhousecover (estimated per experiment), reflection by leaves andtransmission throughthe row crop. The sizes of these effects are highly variable. The amount of lightabsorbed by the crop (relative to the incoming light) depends on the row
dimensions, the sun altitude and the sun position, relative to the orientation of
the rows (Gijzen & Goudriaan, 1989; Hand et al., 1993b). For a plain
approximation, it was assumed that reflection on the crop and transmission
through the crop together were 30% (after Monteith & Unsworth, 1990). Thus
Q n was 0.7*Q C . The contribution of long wave radiation in the energy balance
was assumed negligible.
As proposed by Jarvis (1981), the transpiration of the canopy can be
described as a function of radiation, air humidity and estimated leaf
conductance, with the use of the Penman-Monteith (P-M) model (Monteith,
1965; Jarvis, 1981 and Jarvis et al., 1981), as follows:E

p = (s * Q n + P * c p * D a * gb) I ( A. * (s + y * (1 + gb I g)))eqn. 3.6,
31

where p*c isthe volumetric heat capacity of air (1240 Jm" K" ), A, the latent
heat of vaporization of water (2.45E6 J kg"1), Y the apparent psychrometricconstant (0.067 kPa K"1), s the slope of the saturated water vapour pressure
curve at air temperature (ranging from 0.145 at 20 °C to 0.244 kPa K"1at 30 °C)
and gb the boundary layer conductance. Q n was approximated as above. The
P-M model requires VPD-air as input, under the assumption that the3.3 Methodology

temperatures of leafand air do notdiffer too much (theestimated difference wasusually less than 2 °C in the measurements).
The parameter g b requires special attention. g b represents the
conductance of the air between the leaf surface andthe greenhouse atmosphereat acertain reference height. It actually includes the conductances for diffusion
out of the boundary layer and from inside-the-canopy to outside-the-canopy.
Several descriptions can be found in the literature for the various conductances(e.g. boundary layer conductance, external conductance, aerodynamic
conductance) and it is not always clear which conductance is meant exactly.
The conductances depend on wind speed and leaf properties. Not much is
known about wind speed inside greenhouses, particularly not about variation in
turbulence inside the canopy under various window openings and variable
outdoor wind speed etc.
It was decided to work with one value for g b for all four crops in all
situations, in spite of different average leaf sizes and variation in wind speed.
This seemedthe best approach becauseof uncertainty about spatial variation in
conditions and uncertainty about turbulence. In addition, Stanghellini (1987)
concluded that the fluctuations in external resistance are extremely small
compared to the large fluctuations in internal (i.e. stomatal) resistance.
In order to approximate a value for g b , an average was sought ofindications in the literature. In work with a synthetic leaf in a canopy,
Stanghellini (1985) found an external resistance of 10 mm s"1. Zhang & Lemeur(1992)establisheddiurnal averagesofaerodynamic conductance between 7 and
12 mm s"1. gb may also be approximate from estimated leaf boundary layer
conductance. It is possible to measure g b , as proposed by Kitano & Eguchi(1989), but this is a huge undertaking. There are some simple approximations
available, e.g. as proposed by Burrows & Milthorpe (1976): g b = (u/w)05/ab,where u is wind speed in cm s"1, wthe diameter of a leaf in cm and a b a value
between 1.3 (outdoor and growth chambers) and 3.4 (laminar flow conditions),
yielding gb in cm s"1. For an approximation, it is assumed that u = 50 cm s'(partial ventilation), w = 15 cm, a b = 2. This yields gb = 0.9 cm s"1. In an
extensive experiment, Kitano & Eguchi (1990) observed values between 3 and12 mm s"1 for leaf boundary layer conductance. Based on these and otherindications (Monteith & Unsworth, 1990; Aubinet et al., 1989) a value of 10
mm s"1 was adopted for gb in eqn. 3.6.
The P-M model has some other complications. First the leaf area index
is assumed to play no role ('single leaf' or 'big leaf' model, Monteith, 1963), atleast when LAI is reasonably large (Monteith, 1965). Secondly, g in the P-M
equation represents the canopy conductance. This is a somewhat abstract

71

72

Chapter 3 Conductance and transpiration

parameter, which can theoretically be obtained by integration of leaf
conductance multiplied by area of individual leaves, weighted for theircontribution to the total transpiration (Jarvis, 1981). In the present experiment,
however, g was measured in the top of the crop, and it was higher than the
average conductance of all leaves in the canopy, owing to higher light intensity
at the top. This may lead to an overestimation of the canopy transpiration.
The reason for performing the leaf conductance measurements only on
young, mature leaves in the top of the plants,though, was that spatial variationof other factors was excluded in this way (the variability in leaf age, irradiance,
humidity), thus enabling to establish the effects of C on leaf conductance. Thisapproach was considered acceptable for two reasons. The top of the plants
attribute by far the largest part of the canopy transpiration (Hurd, 1969; De
Graaf, 1991), so largely determine the canopy conductance. Secondly, only the
relative effect of C on canopy transpiration was regarded.
3.3.6

Coupling between conductance and transpiration

Quantification of the effect of C on transpiration, required a goodunderstanding of the relation between conductance and transpiration (section
3.2.2). Thiswas studied by calculating the coupling factor K,using afictive data
set. Kexpresses the relation between a change in g and a concomitant change
in E,as follows:
K = [(£ 2 -f,)/ f m e a n ] / [(fe-g,)/ g mean ]eqn. 3.7

g was calculated with the regression equation and Fwith the P-M model. The
subscripts 1and 2 refer to two situations to becompared. K(after Aubinet et al.,1989) is comparable to 1 - Q ( Q of Jarvis & McNaughton, 1986; eqn. 3.2). K
was established for several steps of C and for several assumed conditions (airtemperature, global radiation and VPD). VPD-leaf-air was assumed equal to
VPD-air, after it was checked that the effect of this simplification on K was
negligible.
3.3.7

Data processing

The conductance measurements of several days were pooled andanalyzed as one data set per experiment (some exceptions are mentioned).
Pooling was necessary to obtain data sets large enough for regression analysis.
Because leaf conductivity was always measured on young, mature leaves in the
top of the plants, the data can be assumed independent of plant age, day
number etc. No systematic effects of day number on conductance were found3.3 Methodology(an exceptional day in eggplant is mentioned). If more than one greenhousecompartment was usedfor the measurements, itwas checkedthat no differences
existed in stomatal and transpirational behaviour under equal conditions at thesame time, between the different plant stands.
Rate of transpiration was recorded continuously during the whole
cultivation period with 1-min readings, and the data were averaged over theintervals of leaf conductance measurements (8to 20 min).Also the transpiration
datadid not reveal asystematic day effect over arelatively short period (weeks),
when plant size did not markedly change. Therefore also the transpiration data
were pooled over a certain period.
All data analysis was done using the statistical package GENSTAT(Payne & Lane, 1987).

73

74

Chapter 3 Conductance and transpiration

3.4

EFFECTS OF C 0 2 ON LEAF CONDUCTANCE AND
CANOPY TRANSPIRATION OF SWEET PEPPER

E.M. Nederhoff, A.A Rijsdijkand R. de Graaf,1992, ScientiaHorticulturae 52: 283-301.

3.4.1

Materials and methods

Crop, greenhouse and environment
Sweet peppers {Capsicum annuum L, cv. Mazurka) were sown on 6
October and planted on 7 December 1989. Plants were grown on rockwool
slabs and received standard nutrition (Sonneveld & Straver, 1989). There werefour rows of pepper plants per 3.20 m, at adensity of 3.1 plants per m 2 and twostems per plant. Plant length was 1.75 m and LAI was around 2 on 25 April.
This increased to length of 2 m and LAI of around 4 by the end of June.
Red fruits were harvested regularly, with care taken to avoid excessive
fruit removal, because this might lead to appreciable stomatal closure (Hall &Milthorpe, 1978). The fruit production followed a normal pattern with about 1
kg m"2 harvested by 25 April and around 6 kg m"2 by 26 June.
The experiment was performed in two compartments (12 m x 12.8 m)of a north-south orientated Venlo-type glasshouse with a ridge height of 3.9 m.
Measurements oftransmissivity oftheglasshouse cover cameout on 70%, underovercast sky as well as under direct sun shine at high sun altitude. In thisexperiment, the transmission of the glasshouse cover was assumed 70% under
all circumstances.
Heatingtemperature setpointswere25/15 °C (day/night) and ventilation
started at 26/16 °C. A so called 'minimum ventilation' of 5 to 15% of the
maximum opening was applied from May onward, particularly effective under
low light conditions. This isa measureto stimulate transpiration and inthis way
promote root growth. Irrigation was controlled by feed-forward (on-line
calculation of transpiration with a model of De Graaf, 1988) and feed-back(weighing of drain water). In summer the crop was irrigated 10 to 30 times per
day with a surplus of 33% of the calculated water demand.
Pure C 0 2 was supplied computer-controlled through a network on thesoil. Cwas monitored with an infra-red gas analyzer (URAStype 3G, Hartmann
and Braun, Frankfurt, Germany), which was calibrated with calibration gases
before every measuring day. Air was sampled continuously on eight places ineach compartment, at about 1.5 m height.
Normally, except on measuring days,C 0 2 set points were equal in bothcompartments and according to the practical regime:450 - 550 with little or no
ventilation and around 350 umol mol" 1 with much ventilation. On measuring3.4 Sweet pepper experimentdays (except on day 173) the C 0 2 concentrations were different in the twocompartments. High and low Cwere alternated per measuring day over the twocompartments, to prevent differences in growth between the two crops.
Conductance and transpiration measurements
The measurements were conducted on 25 April, 2 and 16 May, 13, 22,
27 and 29 June 1990 (day numbers 115, 122, 136, 164, 173, 178, 180),
between 7:00 and 21:00 h.
Leaf conductance for water vapour was measured with the Li-Cor-1600
diffusion porometer. The porometer was attached to the lower side of mature,green, healthy leaves, exposed to full light, in the upper 0.4 m of the crop. A
series of 20 readings was made, which lasted about 15 min. The next series of
20 was sampled in the other location (these data are not used here). The
measuringcycle was between 60to 90 min. Theenvironmental conditions wereaveraged over the measuring interval.
The rate of canopy transpiration was measured on a 1-min basis, withthree weighing lysimeters. The three data were averaged before analysis. Eachlysimeter carried arockwool slabwith three plants, representing 0.97 m 2 groundarea.
Data analysis
Leafconductance wasanalyzedwith the regression model (eqn.3.3 and3.4) andtranspiration with eqn. 3.5 and 3.6). The conductance data of all sevenmeasuring days were pooled and analyzed in one data set (n=116).
Transpiration was recorded continuously on a 1-min basis during the whole
cultivation. The following data sets were assembled:- transpiration data collected during the conductance measurements (intervalsof ca. 15 min, n=116)- transpiration data collected during the seven measuring days (10 min
averages of periods 7.00 - 21.00 h; n=1176)- transpiration data of measuring days in April/May (n=504)- transpiration data of measuring days in June (n=672).
The latter two data sets are obtained by splitting the large data set. This wasdone becausethe crop gradually changed during the season,e.g. LAI increased.
Transpiration ratesthat were measured (f meas )were compared to thosederived with the P-M model (E ). E was based either on measured values ofg (denoted as E m c , n=116) or on values ofgestimatedwith the fitted regression
equation (eqn. 3.4d, Table 3.3). These latter are denoted as E (n=1176, 504
and 672).

75

76

Chapter 3 Conductance and transpiration

Table 3.1 Ranges of leafconductance,canopy transpiration andenvironmental
conditions, in two (partlyoverlapping)datasets of measurements in sweetpepper.
n = 1176n = 116
day
§
meas

Q
Ta

T|
Da
C

day
conductance
mm s"1transpiration
g m"2 s"12
glob, radiation W m "°C
air temp.
°Cleaf temp.
VPD-air
kPa
|jmol
mot'
C 0 2 cone.

min.

mean

max.

min. mean

115
0.3
0.007
12
18.8
19.5
0.25
308

153
10.3
0.07
370
26.1
26.9
0.99
595

180
27.4
0.16
970
29.8
31.4
2.05
1215

115
0.001
0
18.0
0.03
292

max.

153 1800.07 0.16
366 1005..
26.4 30.2
1.02 2.30
598 1716

Table 3.2 Correlationcoefficientsof leafconductance,crop transpiration andenvironmentalconditions in thesweetpepperexperiment. r(p=001 n=116j = [0.22].
1
1
2
3
4
5
6
7
8
9

conductancetranspiration
day number
compartment
timePAR
air temp.
leaf temp.
VPD-leaf-air

10 co 2

3.4.2

1.00
0.74
0.05
-0.11
-0.18
0.70
0.53
0.49
0.03
-0.58

2

3

1.00
-0.19 1.00
-0.04 -0.01-0.04 0.08
0.96 -0.34
0.68 0.16
0.71 0.11
0.56 -0.36-0.45 0.13

4

9

10

1.00
0.01 1.00
0.00 -0.05 1.00
0.08 0.10 0.62 1.00
0.00 0.16 0.65 0.95 1.00
0.29 0.31 0.58 0.45 0.52 1.00
0.11 -0.06 -0.42 -0.31 -0.29 0.08

1.00

5

6

7

8

Results

Time courses
With equal environmental conditions in the two compartments (day173), g and E of the two crops did not differ significantly (Fig. 3.2). This
provided evidence that differences in g, observed on other measuring days,
could be ascribed to the conditions rather than to crop effects. On day 115 (Fig.
3.3), with low C at about 350 pmol mol" 1 and high C between 600 and 1100
umol mol" 1 , conductance was far lower (more than 50% reduction) andtranspiration wasa little lower (approx. 10% reduction) inthe compartment withhigh C. VPD-air was far higher and leaf temperature in the afternoon slightly
higher in the compartment with high C.

3.4 Sweet pepper experiment

600

77

1200-

500

a

300

100

'-

12-

E
E
«so

l
7

local time (h)

9

11

13

1
15

1
17

1
19

1
21

local time (h)Fig. 3.2 Measurements of 22 June 1990 (day 173) on sweet pepper in two glasshousecompartments with equal environmental conditions.
a. Qc = incident global radiation (W m'2)
b. C02 = C02 concentrations (pmol mot')e g= leaf conductance (mm s'1)at top of the crop in full light 'd. Emeas = measured rate of transpiration (gm2 s'1)
' error bars indicate the standard deviation of the measurements (n=20).

78

Chapter 3 Conductance and transpiration- I - "

7

9

11

13

15

17

19

1

21

i° 1-«U

Q u< • > ;

7

**'-

— i — i — i — i — i — i — i
0
11
13
15
17
18
21

local time (h)

7

1
9

1
11

1
13

1
16

1
17

1
19

I
21

local time (h)Fig. 3.3 Measurements of 25 April 1990 (day 115) on sweet pepper in glasshousecompartments with low C02 () and high C02 ()
a. Ta= air temperatures CO;
Qc = incident global radiation (W m'2) (<• • );e. Da = vapour pressure deficits of greenhouse air (kPa)f. Tt = temperature of the leaves (°C) 'b, c, d, 1 as in Fig. 3.2

79

3.4 Sweef pepper experiment

Conductance
Table 3.1 shows the ranges ofconditions and Table 3.2 the linear
correlation between the variables.
Conductance is correlated positively toPAR, air temperature and leaf
temperature and negatively to C, andseems not correlated to VPD-leaf-air.
This is probably caused by correlation
between VPD and temperatures. VPD
and C 0 2 are not correlated.
In Fig.3.4, measured g is plottedversus PAR and the exponential curve(eqn. 3.3) is fitted to the data, yieldingr 2 =49% (Table 3.3). The relative effect ofC, accordingto eqn.3.4d and 3.4f, cameout on 3 . 1 % decrease in g per 100
umol mol" 1 increase in C (parameter c 5
in Table 3.3). Using eqn. 3.4d themeasured effects of PAR, VPD and C 0 2
on g are demonstrated in Fig. 3.7.

25

£

S 1S
do

0

1

1

1

300

600

900

1—

1200

lc (umol s"1m"2)
Fig. 3.4 Measuredconductance (gin mm s1) of sweetpepper versus
incident PAR (lc in umols' m2),
with an exponential curve fitted(eqn.3.3, Table 3.3, r2=49%).

Table 3.3 Fittedvalues ofparameters c1toc7of theregression equations,relatingmeasured leafconductance(gin mms'1) ofsweetpepper to theconditions:
g =c,*(1-c2*EXP(-c3*lc )) *EXP(-c4*Dt.a ) *EXP(-c5*C)/(1+c6*(Ji -c7)2 ) (eqn.3.4)
withlc, D,.a, CandTt asin Appendix II. Daynumber 115- 180(1990),n=116.
7

r2

-

—

49.0

—

—

62.0

eqn.

C

3.3

25.6

0.91 a

25.6

C

1.02

a

3.4b

25.6

C

0.93

a

2.81E-3a—9.42E-4

3.4c

25.6 C

0.91 a1.03E-3a

—

—

3.4d

25.6 C

1.01 a2.64E-33

—

3.4e

25.6

0.88

a

2.87E-3a0.23 a—3.11E-4bC

9.08E-43

1.21E-2

27.9 a

59.3

25.6

C

0.98

a

a

0.23

a

b

0.65E-2a62.2

significantat5%

c

3.4a

3.4f

C

1

significantat 1%

C

2

C

4

C

C

0.92E-30—-

2.28E-3a0.31 a—3

2.76E-35a3.15E-4

setapriori

6—
1.27E-2a

C

—

58.9

26.7 a

50.4

—

62.3

28.9

80

Chapter 3 Conductance and transpiration

Transpiration
Measured transpiration rates are plotted versus global radiation(Fig. 3.5). Eqn. 3.5 fitted to the data yielded: Ex = 0.83 * V 1 * 1000 * Q n(with Q n = Q c *0.7 and n=116). The value 0.83, being parameter c 8 ,equals theratio XE/Qn. It indicates that on average 83% of the absorbed energy wasconverted to latent heat. With the large data set (n = 1176) the same value forc 8 is found. The outcome of c 8 is influenced by the estimation of Q n . Monteith(1965) showed that the ratio hE/Qn varied strongly and increased with increaseof the stomatal conductance. The high values of r2 (91 and 89% respectively),
confirm thattranspiration isexplained to alargeextent by radiation,asgenerally
reported.
Calculated transpiration rates (E ) were compared to measured rates(Fmeas), by fitting the linear: E = a + b * Emeas.Table 3.4 presents the intercept(a), slope (b) and percentage of variance explained (r2) of these linears.Emeas
was in reasonable agreement, not only with E'c, but also with E (Fig. 3.6).
0.20

0.20

0.15

DO

0.10

uf
0.05

0.00
150

300

450

600

Qc (Wrrï 2 )Fig. 3.5 Measured rate of transpiration(Emeasin g m'2 s') of sweet pepper
versus incident global radiation (Qc in
Wm2), with eqn. 3.5 fitted to the data
(n=116, r2=91%).

750(g m"2 s 1 )Fig. 3.6 Rate of transpiration (in g m'2s') according toPenman-Monteith(Epec, eqn. 3.6, with leaf conductanceestimated with eqn. 3.4d) versus
measured transpiration (Emeas ) of sweet
pepper. 1 line of unity; 2 fitted line
(Table 3.4, n=1176, r2=89%).

3.4 Sweet pepper experiment

Table 3.4 Comparison of calculated (E ) and measured (Emeas ) rates of croptranspirationof sweetpepper (ing m'2 s'1),by fitting therelation E = a + b * Emeas.
E mc wascomputed basedon measured valuesof g, and E ^ basedonestimatedvalues ofg (using eqn.3.4d, Table 3.3). Thefourdatasets are partly overlapping.

p,mc
p,ec
p,ec
p,ec

3.4.3

day no115-180
115-136
164-180
115-180

n
116
504
672
1176

g measuredabr'-.001 .93 93„

8 estimated
a
b
r<
.004
.90 91.009.91 89.002.84 91.003.90 89Discussion

Time courses
On day 115 (Fig.3.3), leaf conductance was considerably lower, while
VPD-air and leaf temperature and thus VPD-leaf-air were higher at high C. The
large difference in g is a consequence of the difference in C, but strongly
enforced by different air humidities. High VPD decreases leaf conductance andincreasestranspiration. Hencethedifferences inconductance were largeand thedifference in transpiration small.These observed changes perfectly illustrate thethermal and hydrologie negative feedback loops of the greenhouse-crop system(section 3.1.7 and Fig. 3.1). These feedback effects were stronger on this day
than on most other days, because of a relatively low rate of ventilation (section
3.1.7).
Inthe compartment with high C,the supply was stopped and ventilation
was slightly increased between 10:00 and 12:00 h,which hadconsequences forC 0 2 , VPD-air and leaf temperature. The conductances did not become equalin this time interval, explained only partly by persisting difference in VPD-air.
Probably also aslow stomatal response played a role. Raschke (1972) observedthat the stomatal reaction started a few seconds after a change in C; thehalf-time of closing was less than 2 min, whereas stomatal opening took up toan hour. Also Kuiper (1961)found afasterclosing (5 min)than opening (25 min)of stomata in response to light.
Conductance
It follows from Table 3.3 how leaf conductance is influenced by PAR,
VPD, C 0 2 and leaf temperature. Eqn.3.4a-f were fitted to the data,with a fixedvalue for c, (c, = 25.6, asobtained with eqn. 3.3). If q was not fixed, it varied

81

82

Chapter 3 Conductance and transpiration

too much, probably due to the small number of data relative to the number ofparameters to be fitted. Eqn. 3.3 explained 49% of the variance of the leaf
conductance data. If a term for C was added, r2 became 59% (eqn. 3.4b),
indicating the great impact of C. However, this term probably incorporates also
effects of other factors. Therefore first the effects of PAR and VPD were
calculated and then the additional effect of C (eqn. 3.4a and 3.4d). The
difference in r2 between 3.4a and 3.4d seems small, but is significant with
P<0.10. With PAR and leaf temperature as explaining factors, r2 was 50.4%(eqn. 3.4c) and adding the term for C increased r2 to 59% (eqn. 3.4e). Eqn. 3.4f,
with all factors, gave a better fit than eqn. 3.4e, but not better than eqn. 3.4d.
This indicates that leaf temperature did not contribute to the explanation of thevariance, if PAR,VPD and C 0 2 were already accounted for. Thuseqn. 3.4d wasfound the most appropriate to illustrate the effect of C.
The effect of the environmental factors on conductance is120
demonstrated in Fig. 3.7, where g isS ^—2computed with eqn. 3.4d (Table 3.3)
fordifferentenvironmental conditions.
15The effect of C in the range 200 1
1100umol mol" wassmallerthanthe/ ' • •' /' ' ' "
R
effect of PAR in the range 0 - 1500
10umol s"1 m"2 and of VPD-leaf-air in
I'-'/'••'
60
1•/ ' •"
the range 0.5 - 2.0 kPa.
The relative C effect was
5about 3 . 1 %per 100 mol mol" 1 C 0 2 ,[//.'according to eqn. 3.4d and eqn. 3.4f,
at any level of C 0 2 , VPD-leaf-air andPAR. So elevation of C from 350 to
0 r
i
i
i
i
300
600
900
1200
700 umol mol" 1 , as commonlylc (umol s~'m'2~-2\)
applied, reduced g roughly by 10%
and a C increase from 300 to 1000
Fig.3.7 Calculatedconductance(ginumol mol" 1 reduced g by about 20%,mms\ eqn. 3.4d, Table 3.3)ofsweetat least atconstant VPD-leaf-air. With
pepperasfunction of incident PAR (lceqn. 3.4b and 3.4e, the calculated
in umol s'1m~2), with chosenvalues forC02 (umolmot1) and VPD (kPa).
C 0 2 effect seemed higher, but c5 inline
this equation does not represent the
300 700 WOO 300 700 1000
co2
C 0 2 effect only, asthe effect of VPD
2.0
VPD 0.5 0.5 0.5 2.0 2.0
was not taken into account here.
//'.//•'

'

• •

^

"

"

^

-

-

5

3.4 Sweet pepper experiment

Conductance, transpiration and C 0 2 effects
As shown in Fig. 3.6, the calculated transpiration rate (E ) was, on
average, reasonably in agreement with the measured transpiration rate (f m e a s )It is remarkable that E was slightly lower than fmeas, while an overestimation
could be expected (section 3.3.5). It is concluded from Table 3.4 and Fig. 3.6that the P-M model gives satisfactory results.
The direct relation between measured conductance and transpiration
was fairly small, as r2 was 51% (n=116, figures not shown). This was expected,
because other factors (e.g. VPD) played a role. The approach chosen (section
3.2.2) was to combine the regression model for g with the P-M model for E.
With thesetwo equations combined,anapproximation was made of the
reduction in E, caused by 10% reduction in g. It was observed that the P-M
equation (eqn. 3.6) was fairly insensitive to changes in g, at least if g was highand if the boundary layer conductance (gb) was assumed at 10 mm s"1. A
decrease in conductance of 10% decreased the calculated transpiration by only
1 % at high conductance of 25 mm s"1; by 2.2% at 10 mm s"1; by 7.4% at 1 mms"1 and by 9.7% at very low conductance of 0.1 mm s"1.With a larger boundary
layer conductance, a greater effect of g (and thus of C) on Ewould be found. If
feedback effectsweretaken intoaccount (i.e.enhanced VPD, particularly at low
ventilation) the decrease in g would be larger and the decrease in f would besmaller. The conclusion is that the (direct and indirect) effects of C on stomata
are considerable, whereas the consequences for canopy transpiration are
dampened, as demonstrated in Fig. 3.3.

84

Chapter 3 Conductance and transpiration

3.5

EFFECTS OF C 0 2 ON CONDUCTANCE AND
TRANSPIRATION OF TOMATO AND CUCUMBER

EM. NederhoffA R. de Graaf,1993, Journalof Horticultural Science68: 925-937.

3.5.1

Materials and methods

Crops, greenhouse and environment
Cucumbers (Cucumis sativus L, cv. Jessica) were sown on 1 August
1990 planted on 23 August on rockwool, at adensity of 1.56 plants per m 2 . The
plants were topped mid September, and two side shoots were allowed to growalong the wire (2.2 m height). Three compartments were used for cucumber,which enabled simultaneous comparison ofdifferent C.Themeasurements weremade between 11 September and 30 October 1990.
Tomatoes (Lycopersicon esculentum Mill., cv. Calypso) were sown on
26 November 1990, and placed in the greenhouse on 4 January and planted on
the rockwool slabs on 18 January 1991. The density was 2.08 plants per m 2 .
The plants were not topped, but the top was led over the wire to growdownwards. All sideshootswere pinched out atappearance.The measurements
ontomatowere done only in onecompartment, between 19 February and 3July
1991.
The mature fruits were harvested two (cucumber) and three (tomato)times perweek. The cultivation technique, aswell asthe growth and production
pattern were similar to common commercial practice in the Netherlands.
The greenhouse was the same computer-controlled, Venlo-type
glasshouse complex as used for sweet pepper, with compartments of 12 m x
12.8 m. Also plant nutrition, irrigation, supply of pure C 0 2 and C measuring
were similar (section 3.4.1).
The C 0 2 enrichment strategy during the cultivation was according tocommercial practice, i.e. with a ventilation depending set point. Generally theconcentration varied between 350 and 550 umol mol" 1 . On measurements days,
however, C 0 2 set points in the range 300 to 1200 umol mol" 1 were maintained,
often with two different concentrations in the two compartments or withdifferent concentrations in the morning and the afternoon.
Global radiation was measured outside and multiplied with thecalculated transmission of the glasshouse cover (section 3.3.1).
Photosynthetically Active Radiation was measured with the PAR meter on theporometer. In the tomato experiment, however, these PAR measurements were
not reliable, because of shading by upper leaves.Soincident PARwas estimatedhere(called I') from global radiation, multiplied with the calculated transmission
factor and with a unit conversion factor (Appendix III).

85

3.5 Cucumberandtomato experiments

Table 3.5 Ranges of leaf conductance, canopy transpiration andconditions, obtained in the experiments with cucumber and tomato.
c u c u m b e r in a u t u m n

t o m a t o in Februaryt o m a t o in A p r i l

n=216

n=131

n=55

min.

mean

max.

day

-

254

275

298

8

mm s~'

2.2

12.0

22.4

g m"2 s'

0.007

0.03

0.085

W nrï2

3

266

721

pmol s' m"

7

219

991

28
(31)

°C

19.3

23.6

27.6

T,

°C

19.9

24.3

29.6

Da

kPa

0.29

0.88

kPa

0.32

^mol mol''

233

mea

Q
'r
Ta

D,-a

C

environmental

m i n . mean

max.

min.

mean

max.

57

113

116

119

50

53

8.4

13.6

21.3

12.7

16.6 21.3

0 . 0 1 4 0.032

0.061

0.025

0 . 0 8 8 0.133

280
(279)

498
(892)

190
(74)

619
(293)

925
(870)

18.1

19.9

22.1

20.2

22.1

23.2

19.1

21.4

23.3

21.1

23.4 25.3

2.05

0.32

0.54

0.84

0.13

0.60

1.03

0.92

2.23

0.35

0.59

0.95

0.14

0.65

1.08

578

1667

304

605

1314

306

451

889

Table 3.6
Correlation coefficients of leaf conductance, canopy transpiration andenvironmental conditions (symbols explained in Appendix II)a. cucumber; n=216; r(p= o m n = 2U) = [0.16]
b. tomato; n=186; r. (P = 0.01, n=186) = [0.17j.
a.

Q

8
^meas

0.57

1.00

Q

0.57

0.81

1.00

"c

0.59

0.65

0.71

I'c
Ta

0.54

0.80

0.60

0.62

0.99
0.62

T,

0.49

0.58
0.55

0.61
0.27

0.61
0.47

1.00

0.02

0.59
0.46

0.83

Da
D,.a

0.51

0.38

1.00

0.02

0.58

0.49

0.35

0.50

0.50

0.48

0.98

1.00

co2

-0.26

-0.18

-0.07

0.03

-0.06

0.05

0.12

0.13

0.14

1.00

b.

8
1.00

Em

Q

lc

I'c

Ta

T,

Da

D,.a

c

8

fm

''c

Ta

0.49

1.00
0.62

1.00

'c

1.00
0.71

T,

Da

c

g
1.00

D,.a

meas

0.57

1.00

Q

0.57

0.92

1.00

lc

0.54

0.36

0.49

1.00

I'c

0.56

0.94

0.99

0.44

1.00

Ta

0.65

0.88

0.85

0.36

0.86

1.00

T,

0.60

0.85

0.89

0.55

0.88

0.89

1.00

Da

0.24

0.58

0.59

0.44

0.55

0.56

0.58

1.00

D,.a

0.23

0.56

0.59

0.51

0.55

0.51

0.62

0.98

1.00

co2

-0.48

-0.35

-0.33

-0.21

-0.32

-0.30

-0.31

-0.09

-0.10

c

1.00

86

Chapter 3 Conductance and transpiration

Conductance and transpiration measurements
Theconductance measurementswere performedondays254,255,262,
271, 275, 288, 289, 298 (September/October) of 1990 in three compartmentswith cucumber and on days 50, 5 1 ,52, 53, 56 and 57 (February) and 113, 114,
115, 116, 119 (April) of 1991 in one compartment with tomato. The
transpiration rateswere measured continuously, but only the data of the periods
when conductance was measured, were considered in the data analysis.
The measurements with the Li-cor-1600 porometer were made usually
between 9:00 or 10:00 and 16:00or 17:00 h, in acontinuous cycle. Eachseriesof measurement, consisting of 10readings ondifferent leaves, lasted 8to 10 min
and yielded one average value. Conductance was always measured on theunderside of full-grown, green and healthy leaves in the top of the canopy andin full light. The data were pooled into one data set (n=216) for cucumber andone (n=186) for tomato.
Transpiration was measured by the three lysimeters per compartment.
However, in cucumber only the lysimeter measurements of the east side wereused for analysis and in tomato only the averaged values of the two lysimetersof the west side of the double crop rows under the gutter. The leaf conductancemeasurements were restricted to the same location as the transpiration
measurements (east and west, respectively). Each lysimeter carried two plants,
representing 1.28 m 2 in the cucumber crop and 0.96 m 2 in tomato.
3.5.2

Results

C 0 2 effects on leaf conductance
The rangesof leaf conductance andenvironmental data,obtained in themeasurements, are presented in Table 3.5. Table 3.6 shows that g is correlated
to almost all factors, except VPD, in cucumber. There is a significant negative
correlation between C and g in both crops. In cucumber, simultaneous
measurements were conducted at different C. As an example, one day ispresented with alternating C in two compartments (Fig.3.8). High C reduced g;
f was not significantly affected, although atendency to reduction can be seen.
Measuredgwas plotted versus incident PAR(Fig.3.9).With tomato, thedata of February and April were distinguished by using different symbols andfitting different linear regression lines (Fig. 3.9b). Regression analysis with eqn.
3.4 on the data of each period separately did not give satisfactory results,
probably because the ranges of conditions were too small. Therefore the data
ofthe two periods were combined, on the assumption that the response was notdependent on day number or canopy age. This was reasonable, as in all cases
the same type of leaves (young, almost full-grown leaves in the upper canopypart) were sampled.

3.5 Cucumber and tomato experiments

u

87

—

O"

o-\
10

1
11

1
12

1
13

1
14

1
15

1—
16
17

00

Uj

0.03

E o.o

OH
10

1
11

1
12

1
13

1
14

1
15

1
16

1
17

—i
11

1
12

1
13

1
14

1
15

1
16

1
17

(0
U

a.

24

H

10

1
11

!
12

1
13

1
14

1
IS

local time (h)

1
18

1
17

10

local time (h)Fig. 3.8 Time courses of measurements on 16 October 1990 (day 289)
in two compartments with cucumber.
a. Tajr = air temperature (°C); Q = global radiation outside (W m2b, c, d, e, t 1 as in Fig. 3.2 and 3.3.

)

88

Chapter3 Conductance and transpiration
25

a
+

, +•

•j»?-.+
Û0+

Û0 1<>• 3 K *"*"•

i

i

i

i

i

200

l c (|Jmol s"1 m~

400

600

BOO

1000

l' c (jjmol s"1 m"2)

Fig. 3.9 Leaf conductance (g in mm s~') versus incident PAR (lc in pmol m2 s~')a. cucumber, measured ( • ) and calculated with eqn. 3.4i, Table 3.7 (+ )and regression line (eqn. 3.4g, r2=52%, n=216)
b. tomato, data measured in February ( • ) , measured in April ( • ) ,calculated with eqn. 3.4m for February (+ ) and for April ( X) .
1 = regression line for all data (eqn. 3.4k, r2=34%, n=186)
2 = line for data of February (g = 9.4 + 0.012 * PAR, r2=30%, n=131)
3 = line for data of April (g = 15.4 + 0.0015 * PAR, n.s., n=55).

£
bo

200

400

600

800

—I
200

1000

l c (^imol s"1m"2)

1
400

1
600

1
800

1—
1000

lc (|jmol s"1 m"2)

Fig. 3.10 Leaf conductance (g in mm s'') calculated with regression eqns (Table 3.7)
versus incident PAR (lc in pmol s'1 m'2) with chosen values of VPD-leaf-air (kPa) andC02 (ymol mot').
legend:a. cucumber (eqn. 3.4i)line
b. tomato (eqn. 3.4m).
co 300 700 1000 300 700 1000
2VPD

0.5 0.5 0.5

2.0 2.0

2.0

3.5 Cucumber andtomato experiments

89

Table 3.7 Fittedvalues ofparameters c, toc7oftheregression equations,relatingleafconductance(ginmms~') toenvironmentalconditions:g = C l *(1 -c2*EXP(-c3*lc))*EXP(-c4*D,.a)*EXP(-cs*C )/(1+c6*(T|-c7)2)
a. cucumber (n=216)
b.tomato(n=186).
~ëqn.

q

a. cucumber
3.4g 16.8a
3.4h 21.2a
3.4i
25.0a
3.4j
31.8a
b. tomato
3.4k 18.4a
3.4I
22.0a
3.4m 20.3a
3.4n 22.7asignificant at 1%

~2

~3

Z

c~

0.91a
0.90a
0.91a
0.89a

7.2E-3a6.1E-3a6.5E-3a8.9E-3a

0.20a
0.16a
0.24a

—
3.8E-4a4.3E-4a

0.51a
0.56a
0.44a
0.48a

2.0E-3a2.0E-3a2.5E-3a2.4E-33

~
0.23b
—
0.15a

—
~
3.1E-4a3.0E-4ac7

Z

6.5E-3b 31.Y

F
52
55
61
66
34
35
44
44

significant at5%

Stepwise regression was applied and the results are presented inTable 3.7. The
significance of thedifference in r2 (percentage of variance explained) ofthe
different equations was tested with anF-test. If only PARwas fitted,r2was 52%
in cucumber and34%in tomato. Addition of any other term increased r2
significantly (P<0.01). VPD-leaf-air had only a small impact, whereas thecontribution ofthe C 0 2 term was considerable.
The relative effect ofCongwas calculated with thefitted equations,containing a C term (eqn.3.4i,j and m,n Table 3.7). According to theseequations, each 100 umol mol" 1 increase inC 0 2 , decreased gbyabout 4 % in
cucumber and byabout 3% intomato. The effects ofthe relevant factors on g,
as determined with eqn. 3.4iand3.4m(Table 3.7)forcucumber and tomato,respectively, are shown in Fig. 3.10.
Canopy transpiration and relation toleaf conductance
The ranges of transpiration andenvironmental factors areshown in
Table 3.5.From thecorrelation matrix (Table 3.6)it isevident that f measwas
correlated with all factors mentioned; negatively correlated with C 0 2 andpositively correlated with VPD-air. InFig. 3.11, f meas iscompared toEp, whichis calculated with theP-Mequation, from measured g,VPD-air and estimatedabsorbed global radiation. In cucumber, theP-Mequation overestimatedthetranspiration rate. Intomato, the calculated values tended tobe too high in thelower ranges and toolowinthehigher ranges oftranspiration.

90

Chapter3 Conductance andtranspiration

Table 3.8 Coupling factors (K= [(E2_E} )/E^ear}]/[(g2_g1 )/g
1) relating changes
in leafconductance(gin mms'1) andtranspiration rate(E ing m s'1),causedby C02
steps, atdifferent levelsof radiation outside(Q in W m'2)and VPD(Da in kPa). C02
concentration (in umol mol') indicated by thesubscript, g calculated with eqn.3.4i(Table 3.7) and Ewith eqn.3.6 (Penman-Monteith), with air temperature25 "Cand65%transmission of theglasshouse.

Q
50
50
250
250
1000
1000

Da
0.25
2.00
0.25
2.00
0.25
2.00

§300

§1200

^100

^1200

^300-400^1100-1200^300-1200

0.86
0.65
1.91
1.44
2.14
1.62

0.61
0.46
1.35
1.02
1.52
1.15

0.009
0.033
0.035
0.063
0.130
0.155

0.008
0.030
0.034
0.060
0.124
0.147

0.24
0.29
0.12
0.16
0.11
0.14

0.30
0.36
0.16
0.20
0.14
0.18

0.27
0.33
0.14
0.18
0.13
0.16

The effect of C on Ewas studied by calculating the /(-values, describing therelation between calculated changes in g and f (eqn. 3.7). The results are given
in Table 3.8. According to eqn. 3.4i (for cucumber), an increase of C from 300
to 1200 umol mol" 1 reduced g by 34% (and according to eqn. 3.4m for tomato
by 28%), whereas f was reduced far less. Under all conditions chosen, /(waslessthan 0.4 (for tomato lessthan 0.22). Under higher radiation /(was less than
0.20 (for tomato less than 0.18). A /(-value of 0.2 implies that a 34% reduction
in g was accompanied by less than 7% reduction in E.
3.5.3

Discussion

C 0 2 effects on leaf conductance
It is evident that C has an effect on g, asfollows from the time courses(Fig. 3.8), the correlation matrix (Table 3.6) and the regression equations (Table
3.7). In the correlation matrix, it is remarkable, that between VPD and g, nosignificant correlation was found in cucumber, while in tomato, an unexpected
positive correlation was found. This is probably owing to the relatively small
range of VPD-air in the tomato experiment. The measured leaf conductanceboth of cucumber and tomato plotted versus PAR (Fig. 3.9) show the expectedsaturation pattern (Burrows & Milthorpe, 1976). The scatter in Fig. 3.9 was
expected, because VPD and C 0 2 are not taken into account here. Further, intomato, incident PAR was calculated from radiation measured outside, which
did not account for a difference in radiation between east and west side of arow. The fitted regression lines are shown in Fig. 3.10. The relative C 0 2 effect(3 and 4 % per 100 umol mol" 1 increase in C0 2 ), is in the same order ofmagnitude as that of greenhouse grown sweet pepper (3% per 100 umol mol"C 0 2 , section 3.4.3).

3.5 Cucumber and tomato experiments

91

0.15

't/l

0.08

0.12

0.06

0.09

E
DO
0.04

a
Uj

Uj

0.06

0.03

0.02

0.00
0.02

0.04

0.06

,-2 1, - h(gm^ s )

0.08

0.10

g irf* s 1 )Fig. 3.11 Calculatedtranspirationrate (E in g m'2 s'1)versus measured transpiration(Emeas). E was obtainedwith thePenman-Monteith equation,usingleafconductancemeasured in thetop leaves.
a. cucumber
1 = line of unity
2 = linear regression line (Ep = 0.004+ 1.13 * Em, r2=74%,n=215)
b. tomato,with dataof February (')and April ( • ) distinguished
7= line of unity
2 = linear for all data(Ep = 0.011+0.86 *E^^=91%, n=186)
3 = linear for dataof February (Ep= 0.002+ 1.14 * E^ r2=83%,n=131)
7=77%, n=55).
4 = linear for dataofApril (Ep = 0.016+ 0.79 * E^

Canopy transpiration rate
Inthecomparisonofmeasuredandcalculatedcanopytranspiration rates(Fig. 3.11), most of the scatter is probably caused by inaccuracy in theestimation of incident global radiation. It is improbable that variations intemperature ofthe heating pipes caused much scattering,asthis effect is usuallysmall (Stanghellini, 1987; Jolliet & Bailey, 1992; section 3.3.1).
The fitted lines in Fig. 3.11 deviate from unity, which might be
explained by the fact that the conductance of leaves in the top of the canopy
was used in the calculations, rather than the 'canopy conductance', which
would be lower (section 3.3.5). Although this simplification undoubtedly
influenced the calculation of E, the agreement between E and fmeas was stillreasonable and considered satisfactory (Fig. 3.11). Hence, it is concluded that
the P-M equation implemented with the measured conductance of top leaves,

92

Chapter 3 Conductance and transpiration

can be used adequately to calculate the relative differences in canopy
transpiration, e.g. caused by different C.
The calculated coupling factor K,relating g to E(Table 3.8) is in theorder of magnitude asthose calculated by Aubinet et al. (1989), using the dataof Shaer & Van Bavel (1987). It is concluded that in cucumber and tomato
under near-commercial conditions, the effect of C on stomata is significant,whereas the effect on transpiration issmall and usually negligible, except undervery low radiation.

3.6 Eggplant experiment

3.6

EFFECTS OF C 0 2 ON LEAF CONDUCTANCE AND
ESTIMATED CANOPY TRANSPIRATION OF EGGPLANT

EM. Nederboff, 1992, Journalof Horticultural Science67: 795-803.

3.6.1

Materials and methods

Crop, greenhouse and environment
Eggplant (Solanum melongena L, cv.Cosmos) wassown on 20 October
1990 and planted on 10 December on rockwool slabs. The experiment lasted
until 18 July 1991. Plant density was 2.5 plants per m 2 , with two stems perplant, in two double rows of plants per 3.2 m glasshouse bay.
Fruit setting was stimulated by spraying the flowers once per five days
with Tomatotone (spraying solution of 0.02 volume% 4-chlorophenoxy acetic
acid, a synthetic auxin, Van Ravestijn, 1983). Crop management, e.g. spraying,leaf and fruit thinning (if not part of a treatment) and pest and disease control
were performed according to normal commercial practice.
Themeasurementsweremade inaVenlo-typeglasshousecomplex, withridge height of 3.75 m and with a north-south orientation. The transmission of
the glasshouse cover for diffuse global radiation was about 55%. In four
compartments (16 m x 16 m) an experiment with eggplant was carried out(section 4.6), and in two of these four compartments leaf conductance wasmeasured. Control of environmental factors and irrigation, plant nutrition, C 0 2
supply and data acquisition were similar to those in the other experiments(sections 3.4.1 and 3.5.1). Differences were that the transpiration could not bemeasured and that there was another heating system and another C 0 2
measuring device.
The greenhouse compartments were heated usingeight pipes of 22 mm
diameter per 3.2 m bay, at 0.4 to 0.8 m above the soil. Heating temperature set
points were maintained at around 24/24 °C (day/night) in the first three weeks
after planting, gradually decreased to 22/19 °C in January and February andmaintained at 20/18 °C from March until the end of the experiment. Until theend of February an energy saving screen was closed at night. Ventilation started
in March and was set at 25 °C. From March onward at low irradiance (< 100
W m"2 global radiation outside) a minimum heating pipe temperature of 50 °C
was used. This is a practical method to harden the plants by stimulating thetranspiration. Temperature and air humidity were measured by screened andaspirated PT-100 psychrometers, one in each compartment at about 1.5 m
above the ground.

93

94

Chapter 3 Conductance and transpiration

TheC 0 2 monitor wasan infra-redgasanalyzer,type Ultramat (Siemens,
Munich, Germany), which was zero-calibrated automatically every 24 h andcalibrated with standard gas mixtures every six weeks. The four glasshousecompartments were connected to one C 0 2 analyzer by a multiplexer, taking
four samples in four minutes. Eachcompartment hadone sampler duct with two
inlets on 1.5 m from the ground. The distribution of C 0 2 through a network on
the ground, was examined several times and was found to be homogeneous.
From planting until week 4,theconcentration was kept equal inthe four
compartments at 400 to 600 umol mol" 1 . In week 5 the C treatments werestarted: high C was set 750 umol mol" 1 from week 6 to 29 and low C 450
umol mol" 1 from week 5 to 11 and 350 umol mol" 1 from week 12 to 29. The
achieved concentrations, averaged over week 6 to 29 were 413 and 688
umol mol" 1 respectively (details in section 4.6).
Leaf conductance measurements
Leaf conductance measurements were performed in the twocompartments, on 5 and 7 February, 5 and 6 March, 11 and 12 April, 28 and
29 May 1991 (day of the year 36, 38, 64, 65, 101, 102, 148, 149), mostly from10:00 to 16:00 h. On days 36, 64, 102 and 149, C was kept equal in the twocompartments, to check if the stomatal behaviour adapted to long-term C. On
all other days of the season, C was maintained low and high according to theC 0 2 experiment, during the photoperiod (obtained conditions in Table 3.9).
Leaf conductance was measured (section 3.3.2) with the Li-Cor-1600
diffusion porometer on the lower surface of young, but mature, green andhealthy leaves,that were exposed to full light or sunshine, located in the upper
0.40 m of the third plant of all rows. First 10 leaves were measured in one
compartment, which took about 15 min, and subsequently 10 leaves in thesecond compartment were measured, etc., the two compartments in acontinuous cycle. Leaf temperature and PAR were measured instantaneouslywith athermocouple and aLI-190S-1 sensor, respectively, inthe porometer. The
10 leaf conductance data and the relevant environmental conditions recordedin the measuring interval were averaged,to obtain one data record per interval.
Inthis way, 8 to 14 data points (means of 10 measurements) were obtained per
measuringday,percompartment. Nosystematic differences instomatal response
between the compartments were observed,sothe data ofthetwo compartments
and of all eight measuring days were pooled into one data set (n=156).
Inthegreenhouse used,notranspiration measurements could be carriedout. Therefore, the canopy transpiration rate was approximated, using thePenman-Monteith equation (eqn.3.6, section 3.3.5).Thetranspiration hadto be3.6 Eggplantexperiment95

calculated for the whole season, whereas the required values of leaf
conductance were available only on the eight measuring days. Therefore, leaf
conductance was approximated with the fitted regression equation (eqn. 3.4p,
below) from measured hourly environmental data. For this estimation, Dt_awas
assumed equal to D a . Incident PAR (lc) was approximated from outside global
radiation, assuming 55%transmission of the glasshouse cover and adding a unit
conversion factor (Appendix III).

Table 3.9 Rangesof leaf conductance, canopy transpiration and environmental
conditions in eggplantexperiment.Longtermdatacover5 February - 18July1991.
conductance data set
comp. 6 & 8(n=156)day mm s"1
82
Q Wmumol s"' m
'c
°C
\

2

°C

T,

D a kPa
D(.a kPac umol mol" 1long term data,comp. 6 (n= 1640)

long term data,comp. 8 (n=1640)

min. mean

max.

min.

mean max.

min. mean

36
1.7
48
59
17.3
20.2
(0)
(0)
323

149
17.1
850
806
30.2
31.1
2.2
2.4
1177

36
2.7a
3
18.7
—

118 199
21.0 35.6
335 904
24.5 33.0
—
—
0.7
2.3
—
—
413 915

36
2.4
3
19.0
—
0.1
~
204

95
8.5
404
294
25.2
25.2
0.9
0.9
547

0.2
—
163

max

118 19915.2 3.5
335 904—
24.6 33.3..
0.9 2.4..
688 1234

calculatedfrom measuredenvironmentalconditions

Table 3.10 Correlationcoefficients(r)for themeasured climatic conditions andleaf
conductancein theeggplant(n=156). r (p = 001 ns 156) = [0.19].

time
glob. rad. outside
incident PAR
air temperatureleaf temperature
VPD-air

co2

1
2
3
4
5
6
7

leaf conductance

8

1

2

1.00
0.27
0.28
0.28
0.28
0.21
-0.01
0.24

1.00
0.85
0.90
0.89
0.42
-0.63
0.69

4

5

6

7

8

1.00
0.76 1.00
0.75 0.96
0.26 0.39-0.67 -0.57
0.77 0.67

1.00
0.48
-0.55
0.58

1.00
-0.06
-0.15

1.00
-0.78

1.00

3

96

Chapter 3 Conductance and transpiration

3.6.2

Results

On four measuring days the climatic conditions (particularly C) were
kept equal in the two compartments, sometimes low (around 350 umol mol"1)and sometimes higher (700 - 800 umol mol" 1 ). On thesedays the measured leaf
conductance was not significantly different in both compartments. As an
example, the last measuring day is presented in Fig. 3.12. This indicated that
there was no effect of crop nor of compartment and no adaptation of stomatalbehaviour to long-term C 0 2 enrichment.
AtcontrastingC,asnormally maintainedthroughout thecultivation, leaf
conductance was always lower at higher C, in most cases significantly so. A
typical day is presented in Fig. 3.13. The multiple regression equation fitted tothe pooled data gave the following result:g= 24.5 * (1 - 0.85 * EXP(-4.69E-3 * lc)) * EXP(-0.19 * D,. a ) * EXP(-1.07E-3 * C)

(eqn.3.4p)with r 2 =83.2.The observed effects of PAR,VPD-leaf-air and Con leaf
conductance are visualized by lines computed with this equation (Fig. 3.14).
Parameter c5 (-1.07E-3) represents the relative C effect. It indicates about 1 1 %decrease in g per 100 umol mol" 1 increase in C.
In Fig. 3.13, the transpiration rate calculated with the P-M equation(eqn. 3.6) from measured radiation, VPD-air and leaf conductance, responded
not very pronounced to C. VPD-air was clearly higher at high C, and leaf
temperature tended to be higher. The calculated transpiration, accumulated
between 1 January and 18 July was 4 % lower at high C than at low C (Fig.
3.15). In shorter intervals, however, greater differences occurred, e.g. 15% overa 5-weeks period between 12 February (start of C 0 2 enrichment) and 18 March(start of leaf analysis, section 4.6). For the boundary layer conductance gb, avalue of 10 mm s"1 was assumed (section 3.3.5). If 20 mm s"1 was used instead,the calculated reduction in transpiration at high Ccompared to low Cwould be
6.6% over the whole season and 18% over the 5-weeks period in spring.
3.6.3

Discussion

Leaf conductance and long-term C 0 2 effectElevation of C clearly reduced the leaf conductance, as can be seenfrom the clear negative correlation of g and C (Table 3.10), and from theregression equation (above) and the diurnal courses (Fig. 3.13). To test the
impact ofthe various factors,the regression equation was applied stepwise. First
only PAR was taken into account, which gave r2 of 65% (percentage of thevariance accounted for).With PAR and VPD-leaf-air asfactors, r2 was 76% andwith PAR, VPD-leaf-air and C as factors (eqn. 3.4p), r2 increased to 83%. This
proves the highly significant effect of C on leaf conductance (P<0.001).

3.6 Eggplant experiment

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local time (h)Fig. 3.12 Measurements on 29 May 1991 (day 149) on eggplant in two glasshousecompartments under equal environmental conditions:a. C02 = C02 concentrations (pmol mot')b. g= leaf conductance (mm s~') at top of the crop 'c. Da = vapour pressure deficit of glasshouse air (kPa)d. 7"j = temperature of the leaves CO '' error bars indicate the standard deviation of the measurements (n=10).

98

Chapter 3 Conductance andtranspiration-31 .—.

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local time (h)local time (h)Fig. 3.13 Measurements on 11April 1991 (day 101) on eggplant in two glasshousecompartments, one with low C02 () and one with high CO? ()•
a. Ta = air temperatures CO,
Q = global radiation outside (Wm2 — — — ) ;d. E = calculated rate of crop transpiration (g m'2 s'')b, c, e, f, 1 as in Fig. 3.2 and 3.3

3.6 Eggplantexperiment99

The relative effect of C on
stomatal opening, established with eqn.
3.4p, is about 1 1 % decrease in
conductance per 100 umol mol"1
increase in C (Fig. 3.14). This is about
threetimes stronger than that establishedfor sweet pepper, tomato and cucumber(about 3 - 4 % per 100 umol mol"1,E
sections 3.4.3 and 3.5.3). This confirmsEthe observation of De Koning (1989) thatdoeggplant is exceptionally sensitive to C.
It is not understood why the stomatal
response to C is much stronger in
eggplant than in other crops. It could
have the same (plant specific)
background as the sensitive stomatal
1200
responseof eggplant to water conditions,
reported by Behboudian (1977), Daunay
et al. (1986a,b) and Srinivasa Rao &Fig. 3.14 Leaf conductance (g in
Bhatt (1990). These authors also, had nomm s'\ calculated with the fitted
regressionequation eqn. 3.4p) of
explanation for the exceptional
eggplantversus incident PAR(lcinbehaviour of eggplant. The sensitive
ymol m'2 s~'), with chosen valuesfor
stomatal response to C can be a
C02 (pmolmot') and VPD (kPa).
consequence of the growing conditions,because in glasshouse culture in theco 2 300 700 1000 300 700 1000
Netherlands, eggplant is grown at higher
VPD 0.5 0.5 0.5 2.0 2.0 2.0
temperature and higher air humidity thanother fruit vegetable crops.
Root growth can be suboptimal as a consequence of high humidity(Swalls & O'Leary, 1975; Gislerad & Nelson, 1989) or to high fruit load (Hurdet al., 1979; Quast, 1977). If such a crop is exposed to high radiation, thestomata will partly close through the internal water feedback to prevent water
shortage. Plants that have been exposed to drought stress have a higher ABA
content and are more sensitive to C than well watered plants (Raschke, 1975;
Willmer et al., 1988; Eamus & Narayan, 1989).
Theoretically, the strong stomatal response might be due to a high C
during the cultivation, because high C might sometimes reduce the root growth(Peet & Kroen, 1991), although also the opposite is reported. However, C wasmaintained high in only one compartment and low in the other. If the strong

100

Chapter 3 Conductance andtranspiration

stomatal response was due to high C, than the stomatal response would be
different in the two compartments. This was not the case, as was seen on thedays with equal C in the two compartments (Fig. 3.12).
The measurements of 7 February (data not presented) were the only
ones that did not exhibit a lower leaf conductance at higher C, as in Fig. 3.13.
On this day with low radiation (max. 100 W m"2 global radiation outside), leaf
conductance was low as well (max. 4 mm s') and could not be distinguishedsignificantly in the two compartments, despite different C. A possible
explanation isthat the young plants did not respondto C, because no sensitivity
to C had developed yet. However, this is not supported by the observations inyoung tomato plants. It might better be explained by a low stomatal response
to C under low light (Morison, 1987). Most probable, however, is that theresolution ofthe conductance measurements wastoo low, compared to the lowlevel of conductivity.
Transpiration
Thefact thatthe approximated transpiration rate respondedfar lessthan
conductance to C, also in this experiment with eggplant (Fig.3.15), is based on
the decoupling of conductance andtranspiration, caused by the boundary layer
effect and the feedback loops (section 3.1.7). The average relative humidity
measured in this experiment was lower in the compartments with high C (insummer 5 - 1 0 % lower relative humidity atequal temperatures). Further, at highC, the windows were opened wider (sometimes 10 - 20%) by the control
computer, to achieve the temperature set points. This is explainable, as a
reduced transpiration implies less evaporative leaf cooling.
The cumulative difference in calculated transpiration was 4 % over thewhole season and 15% over acertain period in spring (Fig.3.15).This variationmust beascribed to changes incircumstances. The boundary layer conductanceand the gains of the feedback loops are strongly dependent on the rate of air
exchange with the outside and on the dimensions of the canopy: a small cropwith little transpiration can hardly affect the VPD of the greenhouse air(hydrological feedback small);without ventilation the feedback effects are mostpronounced. Between about day 50 and 75,the hydrologiefeedback was weak,becausethe transpiration was still small andthe ventilation was already started.
A weak feedback implies that g and f a r e more coupled, sothat a reduction ing (through high C) resulted in a marked reduction in E.Later in the season the
feedback declined by increased ventilation and the effect of C on f decreased.

3.6 Eggplant experiment100

day number

1 50

day number

Fig. 3.15 a. Cumulative transpiration (kg m'2) of eggplant at low () and high() C02 concentration ascalculated with thePenman-Monteith equation,using
eqn.3.4p for leafconductance.
b. Relativedifference(%) in calculatedtranspiration betweenthecropsunderlow andhigh C02 concentration (smoothedperweek).

In the P-M equation, parameter g actually indicates the canopy
conductance, whereas hereg ofthe upper leaveswas implemented. Inthe otherexperiments (sections 3.4 and 3.5), the estimations by the P-M model with g of
the upper leaves were reasonably in agreement with measured canopy
transpiration rates. Some arguments for the applied approach were that theupper plant segment comprised by far the largest fraction of the total canopy
transpiration (De Graaf, 1991). The transpiration estimations were used to
explain the incidence of leaf tip chlorosis (section 4.6), which usually arises in
the upper plant part. In addition, for considering relative differences in
conductance, the upper leaves can be used without any problem.

101

200

102

Chapter 3 Conductance and transpiration

3.7

SYNTHESIS AND DISCUSSION

3.7.1

Effects of C 0 2 concentration on leaf conductanceIn the present study, the stomatal response of sweet pepper, tomato,
cucumber andeggplant was investigated under about equal rangesof conditions(although specific demands for temperature and nutrition were taken into
account). The varieties used and the conditions applied were comparable tothose in the commercial Dutch greenhouse industry. It is evident from themeasurements (section 3.4 - 3.6) that leaf conductance strongly depends onradiation, but is also markedly influenced by C.
In two similar compartments, one with low and one with high C, themeasured VPD-air was clearly higher at higher C, caused by a slight reduction
in transpiration. Leaf conductance was lower, caused primarily by higher C(direct effect of C) and amplified by increased VPD-leaf-air (indirect effect of C,
feedback). It must be emphasized that there was no humidity control. The
overall change ing, brought about by direct and indirect Ceffects,can be called'the apparent effects of C 0 2 on leaf conductance'. In real greenhouseconditions, this apparent C effect can be considerable (Fig. 3.3, 3.8 and 3.13).
The real effect exclusively of C on g (derived from the regression
equation accounting for PAR, VPD-leaf-air and C) was far smaller than thisapparent effect: for sweet pepper, tomato and cucumber about 3 - 4 % decreasein leaf conductance per 100 umol mol" 1 increase in C and for eggplant about
1 1 % per 100 umol mol" 1 (in the range of about 200 to 1100 umol mol" 1 ). Fig.
3.16 demonstrates that the stomata of sweet pepper, tomato and cucumber are
equally sensitive to C, whereas the stomata of eggplant responded more than
three times stronger. It can be remarked that an exceptional stomatal responseof eggplant in relation to drought stress was reported in the literature, but nophysiological explanation was proposed (Behboudian, 1977; Daunay et al.,1986a,b; Srinivasa Rao & Bhatt, 1990).
No acclimation of the stomatal response to C could be established,when two plant stands of eggplant were compared, one continuously grownunder low and one under high C. This confirms the results ofJones & Mansfield(1970) and Hicklenton & Jolliffe (1980).
3.7.2

Calculated effect of C 0 2 concentration on transpiration (decoupling)

The impact of leaf conductance on canopy transpiration may becharacterized by the coupling factor, K (Aubinet et al., 1989; eqn. 3.7). K is

3.7 Synthesisanddiscussion
25-i

200

400

600

800

C0 2 ((jmol mol"1)

1000

200

400

600

800

1000

C 0 2 (pinol mol )Fig. 3.16 Calculated leaf conductance (gin mm s'1)versus the C02 concentration(umolmot1) for thefour crops:t= tomato (eqn.3.4n),c = cucumber (eqn.3.4i), p =sweetpepper (eqn.3.4d),e= eggplant(eqn.3.4p).Fortomatoandeggplantthe95%
confidence interval isgiven (. ). VPDJeaf_ajr= /kPa.
a. with incident PAR = 100pmol m' •-2 s'b. with incident PAR = 1000pmol m' ••2 s'.

comparable to 1-Û (Jarvis & McNaughton, 1986, eqn. 3.2), but K explicitly
includes the feedback caused by adapted humidity of the greenhouse air. Some
examples of calculated /(were given in section 3.4.3 and 3.5.3 and Table 3.8.
To demonstrate the limited effect of C on Ein a more general form,g, Eand K
arecalculated for several conditions.Theenvironmental conditions are assumed
constant, sothe feedback effects are ignored.Conductance is calculated with afitted regression equation for leaf conductance (eqn.3.4i, for cucumber) and theconcomitant value oftranspiration with the Penman-Monteith model (eqn. 3.6),
with gh = 10 mm s"1. E and /C10 are presented in Fig.3.17 asfunction of g. To
show the impact of g b , Kisalsocalculated for gb = 20 mm s"1 (K20). It appearedthat K is independent of radiation and VPD, but is slightly dependent on
temperature.
When the hydrologie and thermal feedbacks were taken into account,sothe environmental conditions were not assumed constant, g would decrease

103

104

Chapter3 Conductance andtranspiration

more and E less, so K would be lower than in Table 3.8 and Fig. 3.17. Thisoccurs particularly at low ventilation, which is usually associated with low
radiation and thus low g.
Consideringthat Kin Fig.3.17 isfairly overestimated at low g, it can beconcluded that K (particularly /C10) is usually less than 0.5 and at higher
radiation even less than 0.2. This implies that the decrease in canopy
transpiration, caused by moderate C 0 2 enrichment is in the order of somepercents only, asthe decrease in leaf conductance is 3-4% per 100 pmol mol" 1
in most crops. This agrees with the measurements (Fig. 3.3, 3.8 and 3.13) andwith the work of Stanghellini (1987) and of Jolliet & Bailey (1992), who foundno significant effect of C on transpiration. On the contrary, Shaer & Van Bavel(1987) reported a 15-20% reduction in f for an increase in C of 330 to 1000
pmol mol" 1 . However, their measurements were conducted on small plants inchambers, cooled with fans. In our full-grown canopies in large greenhouses
with natural ventilation (i.e. low turbulence), the aerodynamic resistances will
have been greater and the hydrologie feedback effect (adapted humidity of thegreenhouse air) more pronounced. Both effects reduce the impact of C on E.
K is higher at low g,
but decreases rapidly when gincreases (Fig. 3.17). At low g(i.e. at low radiation), a
considerable reduction oftranspiration is not relevantwith respect to leaf burning.
0.6
When the low light conditions
00
last more than several days, it
0.4
might be harmful from the
U4viewpoint of reduced nutrient
0.05transport, particularly in crops
0.2
with a sensitive stomatal
response to C (eggplant).
Possible negative side effects of
0.0
0.00
10
high C in eggplant are dealt
g (mms"1)
with in section 4.6.
transpirationrate(E in
Fig- 3.17 Calculated
1
2
s'
)
and
coupling
factors (K,g mdimensionless) versus leafconductance (ginmms~'), for various environmentalconditions.
'' andK20 (-K10 (--—) forgb = 10mms-)
forgb = 20 mm s'.

3.7 Synthesis anddiscussion

3.7.3

Time-rdependentvariation in transpiration (midday depression)

Analogue to with photosynthesis (section 2.5), a midday closure ofstomata (Meidner & Mansfield, 1968) might give a dip in the transpiration of a
canopy. Itwasexamined whether amidday depression,or more general atimedependent variation, occurred in the observed transpiration. As withphotosynthesis, this isdone by comparing the measurements to astandard vale,obtained with a model that accounts for instantaneous effects of environmental
factors, and not for an effect of time. For the three available data sets, therelative error (£ meas - Emode |)/ £ mode | is plotted versustime ofthe day (Fig.3.18),
similarly to Fig. 2.3 for photosynthesis. Fig. 3.18 shows no clear tendency orpattern that may indicate a time-dependent variation. The measurements weredone only sometimes under real summer conditions. Notice that the lightinterceptionwasonly roughly approximated.Itwas neglected inthecalculation,that the relative light interception is lower around noon than in the other hours(due to light falling on the path in the N-S oriented row-crop, Hand et al.,1993b). If this effect was considered, the curves would be higher around noon.
Finally, the absence of an endogenous depression do not mean that
there is no decline or depression in the diurnal course. It may occur due toexternal conditions, e.g. deteriorated water supply (Kitano & Eguchi, 1993) etc.
Recently, it was analyzed that canopy transpiration might change during thecourse of the day, through certain conditions that affect the boundary layer(Collatz et al., 1991).
1T

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Ol

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16

-r12

14

time of the day (h)Fig.3.18 Relative differencein canopytranspiration as measuredandcalculated with
thePenman-Monteith equation [(Emeas -Emodel)/ Emodej ] versus time of theday.
a. sweetpepper b. cucumber c. tomato

-r
16

10 6

Chapter 3 Conductance and transpiration

3.7A

Consequences of stomatal closure for leaf temperaturePartial stomata closure increase the resistance for diffusion of gases
through the stomatal pore. The increased resistance for C 0 2 diffusion to thestomatal cavities is largely compensated for by a strong positive effect ofincreased C 0 2 concentration on C 0 2 diffusion (eqn. 3.1). So the net result of
elevated C is an increased C 0 2 uptake (chapter 2).
Water vapour diffusion, however, is reduced,although this reduction isdamped. SoC 0 2 enrichment reduces the efflux of latent heat and thus basicallyincreases the leaf temperature (section 3.1.9). It isone ofthe aims ofthe present
work to quantify the effect of C on the leaf temperature. Leaf temperature wasmeasured by a build-in thermocouple in the porometer, which was calibrated
previously by comparison with a separate, hand-held thermocouple on a great
number of leaves.Theavailable leaftemperature measurements, obtained in the
conductance measurements, are analyzed here.
The observed leaf temperature was compared to the actual air
temperature. The temperature difference between leaf and air (AT;_a) variedroughly between -1 and +2 °C,with afew extremes upto +3.5 °C.These results
are comparable to ranges reported in the literature (Stanghellini, 1987; Collatz
et al., 1991;Zhang & Lemeur; 1992; Grant & Baldocchi, 1992). However, theobservation of ATj_awas not accurate, becauseTawas an average value of some
sensors,all located on some distance of the leaves.An accurate investigation of
ATj_a itself, requires a refined method of measuring and analysis.
The measurements were considered sufficiently accurate, however, forthe purpose ofexamining theeffect of Con average leaftemperature. Therefore,
the measurements of Tjwere exposed to a multiple regression equation, which
accounts for the main factors: global radiation (Q c ), C 0 2 concentration (C), drybulb air temperature (Ta) and VPD of the air (D a ), as follows:
T, = t, + t 2 * Q c + t 3 * C + t 4 * Ta + t 5 * D aeqn. 3.8

This equation was fitted to the data setsof sweet pepper, cucumber, tomato andeggplant (Table 3.11). For tomato and cucumber the large data setswere taken,
including measurements from the east and west side of the rows.

Table 3.11 Effects ofsomeenvironmental factors on leaftemperature (in "Chfittedparameterst,tot5 oftheequation: T, =f,+t2 * Qc+t3 * C+t4 *Tt +ts *Da
sweet pepper
cucumbertomatoeggplant"*1
116 -0.89
299
3.50a
373
7.36a
156 -3.64a

significant at 1%

t2
t3
t4
t5
79E-5a 18E-5
1.04a 0.23
24E-4a52E-5a 0.85a -0.12a
a
31E-4
-6E-6
0.66a 0.03
a
b
25E-5
-75E-5 0.83a 083a

significant at 5%

f
90.3
75.7
83.9
90.9

3.7 Synthesis and discussion

107

The percentage of variance explained (r2) is high. The effect of C on T{
expressed by parameter t 3 , is statistically insignificant in two experiments, andin all experiments, the best estimates for t 3 are extremely low (Table 3.11).
Becausetheairtemperature hasthe main influence,the sameregression analysis
was alsoapplied on AT(_a.This yielded a low r2, but the results were similar: theinfluence of C on AT t . a was negligible. Sovirtually no direct effect of C on leaf
temperature was observed. In Fig.3.3, 3.8 and 3.13, however, Tf was higher athigh C than at low C. This can be ascribed to increased air temperature and air
VPD-air, as shown in the figures.
The conclusion is that the direct effect of C (in the range 200 - 1100
umol mol"1) on leaf temperature of a well watered greenhouse crop undernormal conditions is negligible. This agrees with the findings of Stanghellini(1987). There might be an indirect effect, however, through adapted airtemperature and humidity.
3.7.5

Approach and results considered

Theexperiments ofthe present chapter were undertaken,because itwas
not clear whether C 0 2 enrichment markedly reduces the transpiration ofgreenhouse crops,asthe literaturewas notconsistent inthis matter. The possible
effect of C on transpiration is important because of the possible negative
consequences, such as increased leaf temperature and reduced nutrienttranslocation. The value of this work is that the processes were studied under'natural' greenhouse conditions, which makes that results and conclusions arevalid for practical greenhouse horticulture.
The presentwork yielded aquantitative description ofthe effect of C on
g. It was demonstrated that the apparent effect of C on g is based on a direct
and an indirect effect of C. The indirect effect was caused by thermal andhydrological feedback.
The effect of C on Ewas studied by calculations with fictive data sets,using a derived regression equation for the effect of C on g, and using thePenman-Monteith equation for the effect of g on E.This yielded a generalized,
qualitative insight inthe effects of Con E. On the basis ofthese calculations andthe described observations, it was concluded that C will normally not have adramatic effect on f a n d that the consequences will be mostly not very serious.
The effect of C on leaf temperature (a possible negative side effect) appeared tobe very small. Reduced nutrition translocation (another possible negative side
effect) will probably be serious only in eggplant or only under extreme
conditions (chapter 4).These global conclusions were sufficiently to decide thata further, more thorough analysis of the transpiration processes was notnecessary in view of the purpose of the study: evaluating the relation of partial
stomata closure and possible negative side effects of high C.

4.1 Introduction

4 EffectsofC 0 2 concentration
on growth and production
4.1

INTRODUCTION

4.1.1

Outline of the problem and approach for research

Fruit production is the ultimate result of many processes andinterferences. In section 1.4.2, a distinction was made between productiondetermining effects (main effects) and production-reducing effects (side effects)of the C 0 2 concentration (C). The main production-determining effect of C (oncanopy photosynthesis) was studied in chapter 2, and one side effect (partial
stomata closure) in chapter 3.Another important sideeffect, viz. morphological
adaptation to high C, is discussed in the present chapter. It also comprises anintegration of the results of the previous chapters, as the overall effect of C on
production is studied by analyzing the relevant underlying processes andconsidering the side effects of C. Thus this chapter deals with effects of C on:
1. dry matter (DM) production and growth rate
2. fruit set
3. allocation of DM to harvested organs (harvest index)
4. forming of fresh biomass, i.e dry matter content (DMC) of fruits
5. crop morphology, mainly leaf area and specific leaf area (SLA)
6. leaf nutrient concentration
Points 1 to 4 are production-determining effects and points 5 and 6 involve
production-reducing side effects.
The present knowledge about effects of C on production-determining
and production-reducing processes is briefly reviewed below. Also the concept
of intermittent C 0 2 supply (ICS) is explicated. At each topic, the approach forresearch isdescribed.A topic is investigated sometimes only in one experiment,in the crop where it was expected to give the most pronounced response to C.
Some results are only briefly presented in the next sections, and worked out indetail in the synthesis (section 4.7).

109

110

Chapter 4

Growth and production

4.1.2

Growth rate (GR) and light use efficiency (LUE)

The basis of the production process is the canopy photosynthesis (P,chapter 2). After accounting for respiration, an amount of assimilates remains
available for accumulation of the biomass, i.e. for growth. The absolute growthrate (GR) is the increment in total plant dry weight per day, mostly per m 2 . P
and hence GR are strongly dependent on light and C. To enable a comparison
between various cultivations with respect to response to C, the effect of light iseliminated by dividing the increment in total dry weight by the intercepted lightintegral. This yields the average light use efficiency (LUE in g MJ"1).
The approach in the present study was to determine GR and LUE andto relate them to the prevailing C (section 4.3.1 and 4.7.6). Only GR of above
ground biomass was considered. The intercepted light integral was estimatedfrom the daily integrals of global radiation measured outside, multiplied by thelighttransmission coefficient ofthe particular greenhouse (about 0.7), multipliedby the share of PAR in the global radiation (assumed 0.5) and multiplied by theinterception factor ( 1 -e" k *LAI , with k = 0.7, Mon^i & Saeki, 1953).
4.1.3

Fruitset

The number offruits obtained on aplant depends on flowering and fruit
set. Flowering usually does not limit the production in the crops investigated:
many crops, except tomato, have inflorescences in abundance compared to thenumber of fruits that are ultimately set and produced (cucumber: Drews, 1979;
Marcelis, 1992; sweet pepper: Rylski, 1986). Fruit set may limit the production.
Fruit set andgrowth of young fruits may be hampered by limitation of assimilate
availability (Calvert & Slack, 1975; Acock & Pasternak, 1986), which also
depends on C. Slack (1986) reviewed some experiments where C 0 2 supply
increased fruit set of tomato under poor light conditions. Imazu et al. (1967)
observed increased fruit set in eggplant under high C.
The effect of C on fruit set was investigated in an autumn cultivation ofsweet pepper, because in such a cultivation (with planting date in the
Netherlands from end of June to August), fruit set and yield can be relatively
poor, compared to that of a spring crop. The idea was that under dull weather
conditions in this season, the C 0 2 concentration may be low, caused byinsufficient air exchange to supply the C 0 2 necessary for a full-grown crop. It
was investigated (section 4.4) whether the number offruits andtotal fruit weight
production of autumn sweet pepper are improved by C 0 2 enrichment.

4.1 Introduction

4.1.4

Allocation of dry matter

Thefiguresfor DM allocation tofruits show alargevariation. Sometimes
figures in the order of 90 to 95% are mentioned for tomato, sweet pepper andeggplant (Claussen, 1976; Hall, 1977; Hurd et al., 1979; Nielsen & Veierskov,
1988), whereas Bhatt & Srinivasa Rao (1989) gave a figure as low as 35% insweet pepper. Inanextended study ontomato, Heuvelink (1995b) observed thatafter about 100 days 54-60% of the DM was distributed to the fruits in a spring
cultivation. In a late autumn planting, it was far less due to poor fruit set. The
share of the fruits in the total cumulative DM increases as the cultivation
progresses (Rijsdijk et al., 1993a). These authors found the following values forfruit partitioning in almost year-round cultivations: sweet pepper 61-70, tomato
70-72, eggplant 72, and for cucumber in shorter cultivations 67-75%. Marcelis(1992) found for cucumber in the reproductive stage 67%. Comparable figures
were reported for tomato over a long season, e.g. 72% (Hurd et al., 1979; De
Koning, 1993) and 69% (Cockshull et al., 1992).
The allocation of DM depends on many factors, e.g. plant spacing(Widders & Price, 1989; Papadopoulos & Ormrod, 1990), light (Cockshull et al.,
1992; Marcelis, 1993b), temperature (Liebig, 1978; Marcelis, 1993a), fruit load
(Marcelis, 1993a), but not much is known about an effect of C 0 2 (Acock &Pasternak, 1986; Farrar & Williams, 1991). An increased allocation to thereproductive organs at high Cwas observed in soybean (Clough & Peet, 1981).
High C stimulates P, which is a direct effect of C on source. It isdemonstrated by several authors that source does not influence the DM
allocation, but that sink strength appears to regulate the DM allocation (Gifford& Evans, 1981; Schapendonk & Brouwer, 1984; Farrar & Williams, 1991;
Marcelis, 1993a,b). Therefore no direct effect of C on DM allocation was
expected.
The hypothesis tested here is that C has no direct effect, but may haveindirect effects on DM allocation via an influence of C on the number of fruits(see previous section) and thus on sink strength. The approach was tomanipulate both sink and source (by fruit pruning and C 0 2 supply, respectively)
and to determine the relative contribution of the plant segments (i.e. leaves,stems, fruits) in the total above-ground plant dry weight gain. It was examined
whether C affects the DM allocation in normally cultivated and in sink-limited
plants (section 4.3.1 and 4.7.8).

111

112

Chapter 4

Growth and production

4.1.5

Fruit properties

Fruit dry matter content
C 0 2 enrichment enhances production in virtually all crops, owing toenhanced carbon assimilation. Increase of fruit production isachieved either byincrease ofthe number of fruits,or by increased averagefruit weight, or by both.
It depends on the fruit load, influenced by fruit setting and fruit pruning, whichof these effects is most pronounced. It is important in this respect to distinguishbetween fresh weight and dry weight fruit production. It istheoretically possiblethat a higher fruit DM production in combination with a higher fruit DMC
results in a reduced fresh weight fruit production. It is generally accepted that
C does not affect fruit DMC (Idso & Kimball, 1988; Slack et al., 1988; Ho &Grimbly, 1990).
The approach in the present experiments was to record total fresh fruit
weight, average fruit weight and fruit DMC at every harvest, and to relate theresults to C.
Fruit quality
The quality of the marketed products isextremely important in presentday horticulture. Little is known about the effects of C 0 2 enrichment during
cultivation on the quality of fruits. Some properties of tomato fruits have been
investigated in C 0 2 experiments, and mostly no effect at all or only small,statistically insignificant effects were found. Davies & Winsor (1967) observed
no difference in reducing sugar and total solids content in tomato fruits of C 0 2
enriched andnon-enriched plants. Kretchman & Bauerle (1971) reported asmall
decrease in percentage off-colour fruits and fruits with cracks under high C, andasmall increase in percentage first classtomato fruits.The same authors saw nosignificant differences in fruit size, puffiness (hollowness), shape and average
number of defects per tomato fruit. Nilsen et al. (1983) observed no significant
difference in tomato fruit quality under two C 0 2 concentrations. Slack et al.
(1988) found no effect of C on concentration of reducing sugar and firmness(compressibility) of tomato fruits. In the present work, the most relevant quality
characteristics of fruits were considered in relation to C.
4.1.6

Morphological adaptations to high C 0 2

Various effects of long-term high C on crop morphology have beenreported, mainly with respect to leaf morphology. In young crops, high C may
increase leaf area as a direct result of increased photosynthesis, e.g. in young
cucumber plants (Aoki & Yabuki, 1977). Insoybean aclear decrease of leaf area

4.1 Introduction

113

under high C was observed (Acock & Pasternak, 1986). The leaf area depends
on the leaf weight per plant and on the SLA (in cm 2 g"1 dry weight). Many
authors observed under high C a considerable increased leaf dry weight,
accompanied by aslightly increased leaf area, implying areduced SLA(Madsen,
1976; Clough & Peet, 1981;Frydrych, 1984; Jolliffe & Ehret, 1984; Goudriaan& Bijlsma, 1987).
Morphological adaptations in the form of reduced SLA appear to be
extremely serious in tomato, particularly in summer (Van Velden, 1990). The
tomato leaves arethen short, thick, stiff, curled and somewhat crisp, grey-green
to purple coloured, sometimes with necrotic spots and leaf tips (Fig. 4.4).
Growers describe the phenomenon as 'short leaves' and as this is a goodcharacterization, the term 'short leaves syndrome' (SLS) is used here.
It was investigated whether SLSor reduced SLA in tomato is associatedwith a long-lasting surplus of assimilates, i.e. a low sink/source ratio. In an
experiment (section 4.5), an attempt was made to induce SLS and to compare
the effect of C on production in a sound crop and in an SLSaffected crop. The
approach was to manipulate the sink/source ratio by leaf pruning,fruit pruning,plant density and C 0 2 supply.
4.1.7

Nutrient concentration in leaves

Another possible side effect of C 0 2 enrichment is reduction of thenutrient concentration in plants. Two mechanisms may play a role. In the firstplace, high C causes a reduction in stomatal opening and hence a (small)
reduction in rate of transpiration (section 3.6.2), with a reduced translocation ofnutrients as possible consequence. Internal mechanisms to compensate for
reduced passive nutrient transport are redistribution of nutrients via the phloem
and increased, selective uptake of necessary elements. As far as known, theelements calcium and boron lack both mechanisms (Mengel & Kirkby, 1978).
Sothe availability of Ca and Bfor growing plant organs (leaves, buds, apex andfruits) is strongly related to the transpiration rate, although recent studies showthat Ca is not solely dependent on passive mass flow (Atkinson, 1992).
Low transpiration may induce calcium deficiency (Bangerth, 1979;
Adams, 1986; Ehret & Ho, 1986; Bakker & Sonneveld, 1988; Holder &Cockshull, 1990) or boron deficiency (Von Michael et al., 1969). Certain
similarities were noticed between Caand B, regardingtheir mobility and visible
symptoms of deficiency (Marschner, 1986), and certain interactions between B
and Ca were observed in eggplant (Jyothi & Shanmugavelu, 1985).
Secondly, high C stimulates the DM production, and hence C 0 2
enrichment increases the requirement of nutrients. If the uptake of nutrients is
not increased to the same extent as the assimilate production, the nutrient

114

Chapter 4

Growth and production

concentration inthe DM decreases (Porter & Grodzinski, 1984; Enget al., 1985;
Kuehny et al., 1991), which isoften called a 'diluting effect'. The combinationof increased DM production and reduced Catranslocation owing to high C, may
beexpected to cause afall in the concentrations of some nutrients, particularly
in rapidly growing, non-transpiring organs. Indeed many authors observed athigh C, a lower content of nutrients, mostly calcium, nitrogen and magnesium(Peet et al., 1986; Yelle et al., 1987; Penuelas & Matamala, 1990; Peet &Kroen, 1991; Tripp et al., 1991a).
The effect of C on nutrient concentrations in plant organs wasinvestigated with eggplant (section 4.6), because the stomatal response of
eggplant isstronger than that of other crops (section 3.7.1). Inaddition, eggplantsuffers sometimes from leaf tip chlorosis (Fig.4.6), which appeared to be more
severe under high C (Buitelaar, 1991).
Itwas investigated whether high C in eggplant induces leaftip chlorosis(LTC) and whether this is associated with leaf boron deficiency. The effect ofhigh C on fruit production was considered (section 4.6).
4.1.8

Intermittent C 0 2 supply (ICS)In the eighties, the concept of intermittent C 0 2 supply (ICS) was
proposed as a method, which enabled plants to take advantage of C 0 2
enrichment, while preventing (negative) adaptations to long-term high C. ICS
means that C 0 2 is supplied in short periodical pulses (Clough & Peet, 1981;
Enoch, 1984; Mortensen, 1984). More recently, Dugal et al. (1990) foundpositive effects of ICSon photosynthesis of young tomato seedlings. According
to thework of Enoch (1984),Zipori et al. (1986) supplied C 0 2 intermittently andalso operated the ventilation windows intermittently, in order to increase theC 0 2 useefficiency. Only whiletheventilatorsweretemporarily closed,C 0 2 wasto be supplied and when the windows had to be opened to prevent excessive
temperatures, the supply was to be stopped.
In the present study, two experiments were conducted, where ICS wascompared to C 0 2 supply to a constant concentration (sections 4.3.2 and 4.4).
However, ventilation was not done intermittently, becausethis would affect the
average temperature and humidity, and would unnecessarily complicate theanalysis of the results. Intermittent ventilation was considered no practical
option, due to wearing off of the ventilation installation and moreover, because
reduced ventilation may deteriorate the fruit quality: Slack et al. (1988) foundthat delaying the ventilation in favour of C 0 2 enrichment reduced the fruit
quality so much that the financial loss exceeded the saving in C 0 2 and theincrease in production, even in atemperate climate. Soventilation was done inboth treatments as normally, i.e. on the basis of greenhouse air temperature.

4.2 Objectives and experiments

4.2

OBJECTIVES AND EXPERIMENTS

4.2.1

Objectives

115

The objective of the present chapter is to analyze and quantify theeffects of Con growth and production ofgreenhouse fruit vegetable crops undernormal operating conditions, by investigating the effects of C on underlying
processes, i.e. growth rate, fruit set, dry matter allocation, dry matter content,
crop morphology and leaf nutrient content.
4.2.2

Experiments

Thefollowing experiments were carried out,which are presented in thischapter according to species:• two experiments with cucumber, dealing with effects of Con growth and fruit
production. Inthe second experiment, the effects of intermittent and constantlevel C 0 2 enrichment were compared (section 4.3).
• an experiment on effects of C on fruit set of sweet pepper, and again on
intermittent C 0 2 supply (section 4.4).
• morphological adaptation to high C in tomato (SLS). It was investigatedwhether C has an effect on SLSand whether the effect of C on production isdifferent in an SLS-affected crop and in a sound crop (section 4.5).
• an experiment on the occurrence of a form of leaf chlorisis (LTC) in eggplantin relation to C and leaf boron content (section 4.6).
In all experiments, the relevant growth and production parameters wererecorded, to quantify the effects of C on underlying processes (section 4.7).
All experiments were done in medium-size, semi-commercial
greenhouses under 'normal' greenhouse operating conditions, with sufficient
capacity for C 0 2 supply and with appropriate C 0 2 control. A facility waspresent to scrub (filter) the greenhouse air, to maintain a low C.
The work is restricted to effects of C in the production phase, to avoid
unnecessary complications in the analysis of the results. Seedlings and young,vegetative plants respond to C by forming more leaves (by weight and area)(Klapwijk & Wubben, 1984; Aoki & Yabuki, 1977). This would lead to a large
photosynthetic apparatus inthe C 0 2 enriched crop atthe start of the production
phase.Therefore,theC 0 2 treatments were startedonly when the (estimated) leaf
area index exceeded 1. The time between planting and start of the C 0 2
treatments was at least 2 weeks in cucumber and in summer planted sweet
pepper, and at least 4 weeks in the tomato and eggplant experiment.
Observations were done only on above-ground organs. The omissionsof root weight in the observations was assumed to induce no great errors.
Marcelis (1992) observed that the root weight at the end of an experiment was
only 2.6% of the final, accumulated plant dry weight produced.

116

Chapter 4

Growth and production

4.3

EFFECTS OF CONTINUOUS
AND INTERMITTENT C 0 2 SUPPLYON GROWTH AND PRODUCTION OF CUCUMBER

4.3.1

Growth and production of cucumber at two C 0 2 concentrations(cucumber experiment 1)

Objectives
High C increases the growth rate (GR) and light use efficiency (LUE,
section 4.1.2). It isquestioned whether C has an effect on dry matter allocation(section 4.1.4). Based on the literature, it is expected that source strength(availability of assimilates) hasnoeffect per seon dry matter allocation, whereas
sink strength (number of fruits) can have an effect.
An experiment was conducted to obtain information about the effects of
C on GR and LUE,vegetative and generative (i.e. reproductive) production andon the allocation of assimilates in cucumber. Besides two levels of C, also twolevels of fruit pruning were applied, to get a better insight into the effects ofchanges in source and in sink on dry matter allocation.
Experimental set-up and facilities
Cucumber plants (cv. Aramon) were planted on rockwool on 14 July
1993 in sixVenlo-typegreenhousecompartments, atadensity of 1.35 plants per
m 2 . From 28July onward,two levels of Cwere maintained:three compartments
were controlled at 350 and three at 700 umol mol" 1 by day. In eachcompartment, the plant standwas divided into two experimental plots,one plot
had the normal fruit load, while in the other plot %of the inflorescences andyoung fruits were removed.The harvest started on 4 August andthe experiment
was ended on 19 October. On 24 August and 14 September some older leaves
were pruned away to prevent fungus diseases. The removed leaves were
weighed per plot.
Pure C 0 2 was supplied automatically through distribution tubes on thesoil. Cwas measuredwith calibrated infra-red gasanalyzers (Ultramat, Siemens,
Munich, Germany). Eight greenhouse compartments were connected to one
analyzer by means of a multiplexer, which resulted in a measuring cycle of 8
min. Inthis experiment the C 0 2 concentration, fruit production, fruit DMC andvegetative growth were observed. Three days a week fruits were harvested,counted and weighed; second class fruits were weighed. Occasionally the fruit
DMC was determined on samples of whole fruits by weighing, drying (48 h at
80 °C in aforced ventilation oven) and weighing again.Vegetative growth wasobserved regularly (every 2 or 4 weeks) by harvesting 3 plants per experimental
plot and determining the number of leaves and shoots, leaf area, fresh and dryweights of leaves and stems.

4.3 Cucumber

117

Table 4.1 Main plant characteristics of cucumber expt 7,on two observation dates.
wt = weight, av= average, fr = fruit.
treatment:

unpruned

fruit- joined

L S D

0.05

low
(364)

high
(620)

low
(364)

high
(620)

a. 26 August
number of leaves(m 2 )number of shoots (m~2)
total shoot length (mm"2)
dry wt leaves ( g m 2 )dry wt pruned leaves a (gm 2)
dry wt stems (gm 2)
DMC leaves (%)
DMC stems (%)
DMC fruits, 30Aug(%)
av fruit wt (11-25 Aug) (g)LAISLA (cm 2 g~' dry weight)
LAR (cm 2 g ' dry weight)

57.1
2.7
2.1
98.8
11.1
67.5
12.7
6.1
3.9
0.59
3.1
315
187

56.6
2.4
2.0
103.9
14.6
72.1
13.1
6.3
4.0
0.65
3.0
289
170

84.5
3.6
3.9
125.8
11.9
92.8
12.4
6.2
3.9
0.69
4.1
323
186

87.7
3.6
3.8
135.9
19.2
109.0
12.8
6.5
3.8
0.74
3.8
283
156

13.2
0.7
0.9
5.2
2.9
5.9
0.5
0.3
0.25
0.05
0.9
53
30

b. 19 Octobernumber of leaves(m 2 )number of shoots (m~2)
total shoot length (m m"2)
dry wt leaves ( g m ' 2 )dry wt pruned leaves b (gm 2)
dry wt stems ( g m 2 )DMC leaves (%)
DMC stems (%)
DMC fruits, 14 Oct(%)
av fr wt (20Sep-21 Oct) (g)LAISLA (cm 2 g"' dry weight)
LAR (cm 2g"1 dry weight)

110
7.1
5.5
114
23.9
103
14.3
6.9
3.7
0.43
3.3
293
153

109
7.8
6.3
98
38.5
104
13.9
7.6
3.5
0.46
3.0
303
147

122
7.1
6.1
120
36.2
113
14.2
6.9
3.5
0.45
3.7
304
157

129
10.0
8.3
129
48.6
146
13.7
7.5
3.4
0.44
3.9
298
140

29
1.9
1.9
5.8
10.5
0.3
1.0
0.4
0.06
0.2
9.3
10.6

C02:
(umol mol"1)\eafpruningof24August

leafpruningof 14 September

Results
The achieved C 0 2 concentrations were on average 364 and 620
umol mol" 1 for low and high C, respectively, over the period 28 July - 19
October (Fig. 4.1a). On 12 August, four weeks after planting and two weeks
after the start of C 0 2 supply, the C 0 2 enriched plants were clearly larger than

12 0

Chapter 4

Growth and production

4.3.2

Production of cucumber under continuous or intermittent C 0 2(cucumber experiment 2)

Objective
The objective of this experiment is to test the practical value ofintermittent C 0 2 supply (ICS, section 4.1.8) in cucumber. Two treatments withintermittent C 0 2 supply were compared with two constant C 0 2 concentrations,with respect to their effects on cucumber fruit production and on C 0 2
expenditure. In order to investigate just the effects of C, ventilation was done
equally in all treatments, so ICSwas not combined with intermittent ventilation,
as proposed by Enoch (1984).
Experimental set-up
Four C treatments were applied in duplicate. The two constant level
treatments had a set point of 300 and 450 umol mol" 1 , respectively. In the ICS
treatments 8 min C 0 2 supply was followed by a period of 82 or 172 minwithout enrichment. The C 0 2 treatments aredenoted as'300', '450', '8/90' and'8/180'. C 0 2 was given only by day. C was controlled automatically by supplyof pure C 0 2 through adistribution network of plastic tubes, 3.2 m apart, on thesoil. In the low C treatment, scrubbing (filtering) was applied. The scrubber
consisted of a chemical filter (sodasorb, NaOH + Ca(OH) 2 ), provided with aventilator system, placed inthe greenhouse. Theventilator was switched on/off,
depending on C (Heij & Van Uffelen, 1984). The amount of C 0 2 supplied in 8
min was controlled by a solenoid valve, with the opening time (seconds per
minute) proportional to the difference between the actual C and 500
umol mol" . In this way, the C 0 2 valve was opened the full 8 min per cycle
during much ventilation,and proportionally shorter ifventilation was less.Cwas
measuredwithcommercially available infra-redgasanalyzers(Siemens,Munich,Germany), which were calibrated frequently. Each meter measured one seriesof Ctreatments, with a measuring cycle of 8 min.
Crop and facilities
In eight compartments (9.6 m x 6 m) of a Venlo-type glasshousecomplex, cucumber (cv. Lucinde) was planted in soil on 14 January 1986; theCtreatments started on 29 January; the first harvest was on 27 February and theexperiment was ended on 23 June. Plant density was 1.35 plants per m 2 , withfour rows per 3.2 m. Regularly some leaf pruning was applied, which was anormal measure in a dense canopy to prevent fungus diseases and to improve
the quality of the fruits by increasing the irradiance on the fruits.

4.3 Cucumber

121

The environmental conditions maintained in the experimental
greenhousewere similar tothose incommercial greenhouses andwere setequalin all compartments (exceptfor C0 2 ). Theenvironmental factorswere controlled
by amini computer. Day temperature for heating was 23 and night temperature
20 °C initially. Ventilation started at 26 °C. The air temperature was measured
every minute with a screened, aspired thermocouple in the middle of eachcompartment. The plants were irrigated twice a week and fertilized whennecessary.
Observed were C and fruit production. In addition, in this experimentalso the C 0 2 expenditure was recorded as relative flow rate multiplied by thetime in seconds that the C 0 2 valve in a compartment was opened. The
recordings were summed and then expressed in relative units.

Table 4.3 Results of cucumber expt2 with four C02 concentrations.
av= average, cum = cumulative. '300*' refers to correction forscrubbing (see text)
C 0 2 treatment
av. C0 2 concentration (umol mol')relative C0 2 expenditure (%)
relative cum. production (%)'300*'

318
100
100

;

45(y

459
1180
129

'8/90' '8/180' LSD 005

379
360
110

355
190
108

28
200
2.1

Results and discussion
The C treatments always showed clear differences in achieved C(Fig. 4.2a and Table 4.3). The amount of carbon dioxide spent was recorded inrelative figures (Table 4.3). Because attreatment '300' the scrubbers had filteredout carbon dioxide gas, a correction was necessary to make this treatment
suitable as reference. It is obvious that without scrubbing, C in the treatment'300' would have been higher during a number of hours per day (indicated by'300*') and hence the production would have been higher. A correction was
made, based on two assumptions: that the average C in the low C treatment
would have been 20 umol mol" 1 higher if no scrubbing was applied (an evenhigher value would have been realistic too, see control treatment in section
4.4.3) and secondly that C has a linear effect on production in this small range.
The thus corrected relative production figures are given in Table 4.3. The
increase in production caused by ICStreatment '8/90' compared to '300*' wasabout Vs of the increase caused by continuously high C. About the same ratio
was observed for C 0 2 expenditure.

122

Chapter 4

Growth and production

14

~i
18

week number

r
22

26

week number

Fig. 4.2 Results of cucumber expt 2. Points are individual observations and lines
represent mean of two replicates. Results are not corrected for effect of scrubbing.
CO2 treatments:>'300';«'450';'8/90' ;'8/700'.
a. weekly averages of C02 concentration (pmol mot', 10.00-16.00 h)
b. C02 expenditure in relative figuresc. rate of fruit production (kg m2 week')
d. cumulative fruit production (kg m'2)

4.3 Cucumber

The differences between the two ICS treatments were not statisticallysignificant (Table 4.3), but treatment '8/180' seemed more efficient, because theC 0 2 expenditure was 1/6 and the production 1/4 of that at high C. However,iftreatment '300' was corrected by 30 umol mol" 1 (which was also realistic) theapparent advantage of treatment '8/180' disappeared.
These results imply that the effect of C is about proportional to theamount of C supplied, which findings agree with the literature: if 'partial' or'fractional' enrichment was compared to constant level supply, the fruit
production of cucumber was linearly relatedto C(Slack & Hand, 1985)or to theenrichment time (Willits & Peet, 1989).

12 3

12 4

Chapter 4

Growth and production

4.4

EFFECTS OF CONTINUOUS AND INTERMITTENT C 0 2
SUPPLY ON FRUITSET AND YIELD OF SWEET PEPPER

EM. Nederhoff&f.A.M. vanUffelen, 1988, NetherlandsJournalofAgriculturalScience 36:209-217.

4.4.1

Introduction

In an autumn cultivation of sweet pepper (with planting date in the
Netherlands from end of June to August), fruit set and yield can be relatively
poor compared to those of a spring crop. Fruit set is especially problematicduring periods of relatively warm, calm or dull weather, which are not unusualin autumn. In such periods, the air influx from outside is low, due to the calm
conditions and C 0 2 supply is sometimes sparse, e.g. in greenhouses withcombustion gas enrichment and with limited heat storage.
The hypothesis isthat the poor fruit set under such conditions is caused
by limited assimilate availability (section 4.1.3), dueto low C in the greenhouse
air. The objective of the experiment was to investigate whether number of fruits
and total fruit weight production of autumn sweet pepper are improved by C 0 2
enrichment. In addition, the effects of intermittent C 0 2 supply (ICS) andenrichment to a constant level were compared (section 4.1.8).
4.4.2

Materials and methods

Experimental set-up and facilities
Theexperiment was carried out intwelve compartments of aVenlo-type
greenhouse of 9.6 m x 6 m each. Sweet pepper (cv. Bolero) was planted on 15
July 1985 in soil, at a density of 2.5 plants per m 2 . Carbon dioxide enrichment
started on 1 August. Harvesting started on 1 October and was finished on 19
November. The young plants were initially kept vegetative by weekly
defloration/defruiting (removing all setflowers andyoungfruits).Toexamine theC effect on fruit set under various weather types (including unfavourable
conditions, seesection 4.1.3),fruit setwas allowed for different groups of plants
on different dates: 5, 13, 21 and 30 August (each compartment had the same
four plots with fruit set dates in duplicate). As always in sweet pepper
cultivation, the lateral shoots were topped in a young phase, to stop themgrowing. In all treatments a small and about equal amount of biomass wasremoved in this way.
The greenhouse climate was computer controlled. Except for C, theenvironmental conditions maintained in the experimental greenhouse wereequal in all compartments. Set point for heating was 21 by day and 15 °C bynight and ventilating started 2 °C above the heating set point. This relatively

4.4

Sweetpepper

125

wide dead zone was applied in order to diminish (unnecessary) C 0 2 losses.
During the whole period, a small ventilation (minimum of 5 % of the window
opening) was maintained continuously.
Carbon dioxide treatments
In the experiment the following six C treatments were applied in
duplicate: continuous C of 250, 350 and 450 umol mol" 1 ('250', '350' and'450') and intermittent C 0 2 supply (ICS) with one C 0 2 pulse of 8 min per 40
min ('8/40') or per 104 min ('8/104') and acontrol treatment, without supply or
filtering. C was controlled during day time only, by supply of pure C 0 2 and in
the treatment '250' by scrubbing (section 4.3.2). In the ICStreatments, the fluxof C 0 2 was adapted by hand to the averageventilation, sothat in eight minutes
the concentration rose to about 400 to 800 umol mol" 1 (depending on
ventilation). C was measured with a commercially available C 0 2 analyzer(Siemens, Munich, Germany), which was calibrated frequently. Eightcompartments were measured by one device, resulting in a measuring cycle ofeight min.
Observations
The relevantenvironmental conditions were recordedon aonemin basis(only C once per 8 min). Observations on the crop were:• fruit set: removed set flowers were counted on 13, 21 and 29 August• yield: every week the ripe, red fruits were harvested, weighed and counted.
Atthe end ofthe season (19 November) all maturefruits were harvested (maturegreen or red/green fruits separated from the red ones)• vegetative plant parameters: on five dates two plants per compartment were
sampled. Number of leaves, leaf area,fresh and dry weights of leaves and stems
were recorded.
4.4.3

Results

Table4.4 presentsthe average, measured Cduring daylight hours. Itwas
not possible to maintain the low set point properly at 250 umol mol" 1 , due tothe high ventilation in the autumn period and the limited capacity of the C 0 2
filtering installations. Unexpectedly, the averageC inthe control treatment washigh (344 umol mol" 1 ), especially in early August. This can be explained by
C 0 2 release from the soil, limited uptake by the young crop and mainly by
influx of C 0 2 from the environment during ventilation. In this region, close toa large industrial area,the C 0 2 concentration ofthe outside air isregularly high.

126

Chapter 4

Growth and production

Table 4.4 C02 concentration (umol mol') in the sweet pepper experiment,
measured during daylight hours, averaged over two replicates.
datecontinuous C 0 2

intermittent

control

LSD
P<0.05'250' '350''450''8/40' '8/104'

329

325

431

378

387

371

58.2

13-20 Aug

296

333

462

461

399

337

36.7

21-29 Aug

310

332

458

464

398

327

38.2

01-31 Aug

314

332

450

428

396

350

38.6

01-30 Sept04-12 Aug

271

331

453

476

423

332

26.0

01-31 Oct

299

345

458

478

442

341

18.5

01-15 Nov

343

379

432

432

411

353

48.5

1 Aug-15 Nov

306

346

448

453

418

344

27.5

Table 4.5 Vegetative plant parameters of sweet pepper, at 22 October in six C02
treatments, averaged over two plants per compartment and over two compartments.
Leaf area in m2/plant; fresh weights (fre wt) and dry weights (dry wt) in g/plant; DMC
in %; SLA and LAR in cm2 g' dry weight.
continuous CO- (umol mol"1)
C treatment
average C

'250'

'350'

'450'

306

346

448

# of leaves

204.8

173.3

159.5

leaf area

1.308

1.108

0.996

fre wt Ivs

289.0

247.3

fre wt st

400.3

dry wt Ivs

40.2

dry wt st

ANOVAaintermittent

control

LSD"
P<0.05'8/40''8/104'

453

418

I.S.

200.3

171.8

163.8

n.s.

l.s.

1.134

1.091

0.948

n.s.

235.5

n.s.

259.0

239.9

216.8

n.s.

325.3

328.8

n.s.

396.0

340.3

324.5

n.s.

36.3

35.8

n.s.

39.8

34.3

32.9

n.s.

55.3

44.5

46.2

n.s.
0.95

344

51.3

45.8

45.6

n.s.

DMC leaves

13.9

14.7

15.2

l.s.

15.3

14.3

15.2

DMC stems

12.8

14.1

13.9

n.s.

13.9

13.1

14.2

n.s.

SLA

326.0

305.0

278.1

l.s.

285.7

318.6

288.3

20.4

LAR

143.7

135.2

122.3

l.s.

120.3

138.6

120.0

15.2

ANOVA: analysisof variance on thedifferences betweencontinuous C02 levels:
l.s.= linear component significant, n.s.= no significanceat P< 0.05.
leastsignificant difference,calculated overall treatments.

4.4

Sweetpepper

Table 4.6 Fruit set of sweet pepper (number of removed fruits per m2) at six C02
treatments, at three dates of defloration/defruiting, averaged over two compartments.

control

LSD"

continuous C0 2

intermittent

C treatment
averageC'250' '350' '450'
306 346 448'8/40' '8/104'453
418

non-cumulative
13Aug.
21Aug.
30Aug.

5.8
13.5
8.0

8.8
18.3
11.6

13.3
26.0
15.9

7.8
22.8
17.8

8.9
19.7
12.9

9.0
16.8
9.8

n.s.
6.2
n.s.

cumulative
21Aug.
30Aug.

19.3
27.3

27.2
38.8

39.4
55.3

30.6
48.4

28.6
41.5

25.8
35.6

10.5
17.2

P<0.05344

leastsignificant difference,calculated overall treatments

Table 4.7 a. Cumulative fruit production of sweef pepper (number of red
fruits per m2) at six C02 treatments, averaged over two compartments.
b. average fruit weight (g)continuous C0 2

intermittent

control

LSD"
P<0.05

C treatment
averageC

'250'
306

'350'
346

'450'
448

'8/40'
453'8/104'418

344

a. yield
1 Oct c29 Oct d
19 Nov d
19 Nov all e

0.8
7.4
13.4
16.2

3.4
10.5
16.3
18.4

4.2
14.5
21.3
23.6

1.8
12.9
20.0
22.4

1.9
9.5
17.9
20.4

1.6
8.9
15.5
18.3

n.s.
4.3
2.2
2.1

b. avfrwt
1 Oct
29 Oct19 Nov
19 Nov all 6

210
183
173
166

189
175
168
165

207
177
171
168

180
171
165
163

216
189
177
173

189
182
175
169

38
13
12
11

least significant difference,calculated overall treatments
only fruitsfrom firstfruit set treatment
datafrom all fruit set treatments
all maturefruits,including greenand red/green

127

128

Chapter4

Growthandproduction

The vegetative crop parameters observed on 22 October are shown in
Table 4.5. Similar results were found o n other sampling dates. The growth rate
(rate of dry weight gain between t w o dates) is presented in section 4.7.3. Some
calculated parameters show a significant C 0 2 effect: leaf D M C was higher athigher C; SLA and leaf area ratio (LAR) were lower at higher C. In thecontinuous C 0 2 treatments, number of leaves and leaf area were smaller athigher C. Some other tendencies to reduced vegetative growth at higher C were
not significant, maybe o w i n g to a large variability between individual plants andthe small number of plants sampled.

30

70

25

0) 20
3
C

E
c

C
O

15

U

-a iocs

10

i

250

1

300

350

1

400

1

450

C 0 2 (umol m o l ' )

1

1

500

250

300

1

350

1

400

1—

450

C 0 2 (umol mor')

Fig.4.3 Resultsof sweet pepper versusaverage, measured C02 level (pmol mot') in thepreceding period (dataper compartment). Linear regression (Y= aX + b) fitted throughnon-intermittent C02 treatments ('250', '350' & '450' and control).
a. Fruit set (number of fruits per m2)
1.
B-D
setting 14-21 Aug. vs. C02 of 13-20 Aug.; a=.07, b= -6.9, r=.62
2o.osetting 22-30 Aug. vs. C02 of 21-29 Aug.; a=.05, b= -5.0, r=.77
3. - - A - A - setting until 30 Aug. vs.C02 of4-29 Aug.; a=.18, b= -24.9, r=.68
b. Fruit production (number of fruits per m2)
1. •B-D
at 1Oct. vs. C02 in Sept.; a=.02, b= -3.7, r=.65
2o.o
until 29 Oct. vs. C02 in Oct.; a=.05, b= -5.9, r=.86
3. - - » - A - until 19 Nov. vs. C02 1Aug.- 15 Nov.; a=.05, b= 0.1, r=.96
Open symbols: non-intermittent; closed symbols: intermittent C02 supply

500

4.4

Sweetpepper

Fruit set increased by elevated C (Table 4.6). The number of harvested
fruits doubled with C increasing from 306 to 448 umol mol" 1 . The average fruit
weights were not different (Table 4.7). The decreased vegetative growth andincreased generative growth implied that more biomass was allocated to thefruits. In Fig. 4.3a the fruit set in each compartment is related to average C,
measured in that compartment during the preceding period (mentioned at thefigure). Fig.4.3b showsthe samefor fruit harvest.According tothesefigures,the
ICS treatments tended to perform slightly less than the non-intermittent
treatments.The amount of second classfruits (1.5to 2.7 % ofthetotal yield, notincluded in the data) was not significantly related to C.
The ICS treatment '8/40' and the constant level treatment '450' had ancomparable averageC(Table4.4). SLA, LARand DMC of leaves andstems were
not different between '8/40' and '450' (Table 4.5). The treatment with lessfrequent supply ('8/104') exhibited a lower leaf DMC and a higher SLAand LAR
than '8/40' and '450', which is only partly explained by the lower average C(Table 4.4). It is not explainable why the control treatment (with about equal
C 0 2 concentration as the treatment '350'), had almost equal DMC, SLA and
LAR asthe treatments '450' and '8/40'. These aspects require further research.

129

13 0

Chapter 4

Growth and production

4.5

EFFECTS OF C0 2 , PLANT DENSITY AND PRUNING
ON LEAF DEFORMATION (SLS) AND
FRUIT PRODUCTION OF TOMATO

EM. Nederhoff, A.N.M. de Koning& A.A. Rijsdijk,1992, Journalof Hort Science67: 411-420.

4.5.1

Introduction

Morphological adaptations due to high C in the form of reduced leaf
area (section 4.1.6) appear to be most serious in tomato. A producing tomato
crop often shows an extremely low leaf area index in summer (De Koning,1993) and growers experienced that C 0 2 enrichment in summer reduced leaf
sizesfurther and even caused a kind of leaf deformation intomato (Van Velden,
1990).The leaveswere short,thick, stiff, curled and somewhat crisp, grey-green
to purple coloured, sometimes with necrotic spots and leaf tips (Fig. 4.4).
Nevertheless, such a summer tomato crop is usually very productive, but laterin the seasonthe production may fall behind. Theterm 'short leaves syndrome'(SLS) was introduced for this phenomenon (section 4.1.6). SLS is undesirable,
because apparently light interception, and hence crop photosynthesis andproduction are lower than in well foliated crops. Fruit quality may be affected
negatively, sincefruits aremoreexposedto solar radiation (Adegoroye & Jolliffe,
1987; Janse, 1988). Many (Dutch) tomato growers apply C 0 2 enrichment insummer by using a heat storage tank, and the risk of severe SLSdue to high C
is regarded a major drawback of C 0 2 enrichment.
Some authors (Madsen, 1976; Nagaoka et al., 1979; Tripp et al.,1991a,b) described a feature in tomato that resembles SLS. Nagaoka et al.
(1979), for instance, described several morphological disturbances: leaves
becamethick, twisted and purple coloured at high light intensity combined withhigh C and at low night temperature (8 °C). These authors assumed that thedisorder was caused by accumulation of assimilates. Frydrych (1984) induced
leaf hypertrophy and reduced SLA by removing buds and fruits in tomato andsweet pepper. Van Gurp (1991) reported that fruit pruning reduced the lengthof leaves.
The factors that arebelieved to reduce SLA, andto induce SLS,are highradiation, high C and fruit pruning. These factors have in common that they all
reduce the sink/source ratio. Therefore, it is proposed here as a working
hypothesis that the phenomenon of reduced SLA can be considered as a
symptom of overproduction of assimilates, i.e. of low sink/source ratio or sinklimitation. Sink limitation meansthat the production of assimilates by the leaves

4.5 Tomato (SLS)

exceedsthe capacity ofthe sinks (mainly fruits) for receiving assimilates. Sofruit
production is sink-limited if there are insufficient fruits on the plant. Peet (1984)
reported sink limited fruit production in soybean after partial defloration.
SLS has a negative effect on fruit production, both on the short and the
medium term. In late spring and early summer, when SLSoccurs and when thelight conditions arefavourable, fruit production is limited by sink limitation. On
overcast days, or later in summer when the average light flux declines, the leaf
area of an SLS-affected canopy is too small for an optimal light interception.
The objective of the present work is to investigate whether SLS (orreduced SLA) is associated with, or caused by, a long-lasting surplus ofassimilates, i.e. a low sink/source ratio. Therefore the sink/source ratio wasvaried by applying two treatments of C 0 2 and two treatments of nighttemperature (four climate combinations in triplicate), multifactorially combinedwith two plant densities andthree pruningtreatments (leaf pruning,fruit pruning
and unpruned control). According to the working hypothesis, high C 0 2 , lower
plant density (higher source) and fruit pruning (lower sink) would induce SLS
and leaf pruning (lower source) would enlargethe areaof new leaves.The effectof C on production was compared in a sound crop and an SLSaffected crop.

Fig.4.4 Tomato plant fromtheexperiment, showingthe'shortleaves syndrome' (SLS).

131

132

Chapter 4

Growth and production

4.5.2

Materials and methods

Facilities, crop and conditions
The experiment was conducted in 12 compartments (9.6 m x 5.7 m) ofa Venlo-type glasshouse with a maximum height of 3.3 m. Ventilation was bywindows inthe roof and heatingwith five heating pipes of 51 mm diameter, per
3.2 m. Measuring, control and data recording of environmental data was done
by a microcomputer in a network (Bakker et al., 1988). Pure C 0 2 from bulk
storage was supplied through a network of nylon tubes on the ground, 3.2 m
apart. C was measured every 4 min with an infra-red gas analyzer (typeUltramat, Siemens, Munich, Germany). The gas analyzers were automaticallycalibrated each day with azero filter (drift) and every two weeks by hand using
calibration gases (gain).
Tomato plants (cv.Calypso),were planted on 10May 1990on rockwool
slabs in a recirculating system. A standard nutrient solution (Sonneveld &Straver, 1989) was supplied in sufficient amounts (10 - 30% oversupply). Plant
density was 2.1 and 3.1 plants nrf2, with the rows 0.8 m apart.
Standardcommercial practiceswereapplied:pollinationwith an 'electricbee' three times aweek; removing side shoots at appearance once a week. Six
lower leaves per plant were removed on 31 May and another 2 leaves on 12
June, in all treatments. Some double trusses were diminished to normal
proportions. The first harvest was on 25 June.The experiment was finished andthe crop was harvested on 31 July 1990.
The average day totals of global radiation in May, June and July were22.7, 16.9 and 20.9 MJ m"2 d"1 respectively, which was 9% higher than the
average of the last 20 years. The measured environmental conditions in theglasshouse compartment can be seen from Fig. 4.5.
Treatments
The following treatments applied:
1. CQ 2 : low C (350 umol mol"1) and high C (550 umol mol"1) from sunrise tosunset. Until 13June Cwas kept equal in all 12 compartments (on average 362
umol mol"1) to avoid variations in plant growth inthe early phase. From 13June
until the end of the experiment, low C, maintained in 6 compartments, was on
average 370, and high C in the other 6 compartments was on average 510
umol mol" 1 (Fig. 4.5a).
2. Night temperature: low (18 °C) and high (22 °C) night temperature from
20:00 to 5:00 h. Until 13 June heating temperatures were 21/20 °C (day/night)
andventilation temperatures 22/21 °C for all compartments. After midJune until
the end of the experiment the set points for heating were 22 °C by day and 18

4.5 Tomato (SLS)or 22 °C, for the low and high night temperature, respectively, by night.
Ventilation temperatures were then 0.2 °C above heating temperatures.
Minimum heating pipe temperature was 45 °C (day and night), with aproportional decrease with increasing solar radiation (-0.1 °C per 1 W m"2above 100 W m"2). Achieved temperatures are given in Fig. 4.5b,c.
3. Plant density: low (2.1) and high (3.1 plants m~2) plant density. Each plot ofplant density was 23 m 2 in area and consisted of six rows, of which only threerows were used for observations, one was a guard row near the wall and two
were guard rows to the other plant density.
4. Pruning: leaf pruning (removing one third of leaves), fruit pruning (removing
one third of fruits) and control (unpruned). In the leaf pruning treatment, eachthird leaf was removed, in addition to the leaf picking in all treatments. In the
fruit pruningtreatments each second,fifth, eighth andeleventhfruit ofeachtruss
was removed. In the control no additional leaf pruning or fruit pruning wasapplied.
Thetwo levels of C andtwo night temperatures gavefour combinations
ofclimatic factors,which were applied intriplicate. Ineachofthe 12 glasshousecompartments both plant densities were present, and within each density onerow (3.8 m2) was fruit-pruned, one row leaf-pruned and one row remained
unpruned. This resulted in 72 experimental plots in total, each plot consistingof 8 or 12 plants (in the low and high density, respectively). The plants in theguard rows were not pruned. To minimize the consequences of mutualinterference, the experimental plots were randomized.
Plant densities were maintained from planting until harvest; Cand nighttemperaturetreatments startedtwo weeks beforethefirst harvest andthe pruning
treatments were both applied twice; 7 days before and 9 days after the first
harvest.

Observations
The severity of SLS in all 72 plots was assessed visually on a relative
scale between 1and 5: a higher mark being recorded if leaves were shorter andmore affected. Data of six observations (three observers and two occasions, 20
and 30 July) were averaged to one data set before statistical analysis.
At the end of the experiment (31 July) destructive measurements weredone in all experimental plots. In each plot, four top segments with 12 leaves(> 1 cm) and one whole plant were harvested. The whole plant was split into
a top segment and a lower part. The top segments had grown after the leaf
pruning treatment had been applied. Leaf area of top leaves was measured witha planimeter (LI-3100, LI-COR, Lincoln, Nebraska). For all samples (five plant

133

134

Chapter4

Growthandproduction

23-

b

^

ro

night

22-

20-

u
•5 1 9 -

r18-

19

23

25

27

i
21

i
23

i
25

i
27

21

23

25

27

i
29

week number

week number

Fig.4.5 Environmental conditions in tomato experiment, measured in 12 experimental
compartments, averaged per week over three compartments.
a. CO2 concentration (umol mot', 10:00-16:00 h)b. air temperature CC) by night (22:00-4:00 h)c. air temperature CC) by day (10:00-16:00 h)d. relative humidity (%) by day (10:00-16:00 h)•
low C02, high night temp.;
low C02, low night temp.;
high C02, low night temp;•

high C02, high night temp.

4.5 Tomato (SLS)

1 35

tops and one lower plant part per plot) fresh and dry weights (dried 48 hours in
a forced air oven at 80 °C) of leaves (including petioles) and stems were
determined.
A rough approximation of total leaf area was made from measured SLA
oftop leaves and dry weight oftotal foliage.Thiswas done insteadof measuring
total leaf area, which was virtually impossible because of the curliness of theolder, by SLS affected leaves.
The effect of SLS on fruit production was studied by weighing andcounting the harvested fruits three times a week from 25 June until 31 July.
Fruits with blossom end rot were weighed and counted separately. Fruits thatremained on the plants at the end of the experiment were measured as well.
Fruit DMC was determined on five fruits per experimental plot from the harvestof 27 July.
Starch content of the leaves was determined in the fruit and leaf pruning
treatments (48 plots).On 30July, between 15:00 and 16:00 h, in each plot eightleaveswere sampled,all beingthe 15th leaffrom thetop. Leaf 15was an almost
fully expanded leaf, grown during the treatment period. Leaves were dried (24h at 100 °C) immediately after picking. The analysis was done using highperformance liquid chromatography (Carbopack PA1, DIONEX, Breda, The
Netherlands), after enzymatic hydrolysis, as described by Van De Woestijne &Van Elderen (1990).
Data analysis and notation
Main effects of C, night temperature, plant density and pruning wereanalyzed statistically with four factor ANOVA, using GENSTAT (Payne & Lane,
1987). The least significant difference was calculated with the Student's tdistribution (double-sided) with probability 95%.
Night temperature had no marked effects on relevant characteristics andno interactions with other factors. Also Tripp et al. (1991b) found no effect ofnighttemperature onfoliar deformation orfoliar starchconcentration.Therefore,
inthe current work, night temperature effects arenot presented or discussed andresults of other treatments are averaged over both temperatures treatments.
Table4.9 summarizes the main effects ofthefactors Cand plant density;
Table 4.10 of the pruning treatments and Table 4.11 shows the results of thethree factor analysis. No three-factor interactions existed and only some twofactor interactions were significant.
Effects are described below as a percentage increase (+) or decrease (-)
relative to the response at the lowest level of the factor. The effects of thepruning treatments are given relative to the unpruned treatment.

136

Chapter4

4.5.3

Results

Growthandproduction

Leaf growth
The degree of SLSwas assessed in three ways, as leaf area and SLA of
12 top leaves and asthe visual score of degree of SLS. Leaf area and SLA wereboth inversely correlated with the degree of SLS,with a high correlation (Table
4.8). In fact were all vegetative characteristics mentioned (degree of SLS, SLA,
leaf area, DMC of leaves and stem and leaf starch content) highly correlated(P<0.01).
SLS (Tables 4.9a and 4.10a) was more severe at high C, at low plantdensity and with fruit pruning. Leaf area of top leaves (Tables 4.9b and 4.10b)
was influenced by C (-9%) and plant density (+29%). SLA of top leaves (Tables
4.9c and 4.10c) was lower at high C (-14%) and it was higher at high plantdensity (+16%).
Stem DMC (Tables 4.9d and 4.1Od)was higher atelevated C (+5%) andlower at high density (-10%) and leaf pruning (-7%). Thedifferences were small,but statistically significant. Differences in leaf DMC were less pronounced but
similar in direction. Starch content of leaves (Tables 4.9e and 4.10e) was
influenced by C (+36%), plant density (-22%) and by pruning only in high plantdensity (Table 4.11d).
In summary, most characteristics related to SLS were significantly
affected by C and plant density, and only weakly by pruning.
Fruit production
On 13June,when thetreatments were started,the plants carried almost
20 young fruits, with an estimated total fruit weight of 250 g/plant (fresh) or 15
g/plant (dry). Because those fruits were grown before the treatments were
imposed, total harvest was not the most appropriate characteristic to evaluate
the effects of C and pruning on fruit production. Therefore, the green fruits
present on the plant at the end of the experiment, completely grown during thetreatment period, were considered the best criterion (Table 4.11e). Harvested
fruit weight and total fruit weight are presented only as main effects (Tables
4.9f,gand 4.10f,g).
C had no effect on rate of appearance of leaves and trusses. Also fruit
set was hardly different between low and high C, because virtually all flowers
set to fruits under the summer light conditions, which can be seen from analmost equal number of fruits harvested (Table 4.9f,i). High C generally
enhanced the production of fruit weight (Table 4.9f,g). The C 0 2 effect wassignificant only in the treatment with least severe SLS (highdensity/unpruned,Table 4.11e). In these crops, high C increased harvested fruit4.5 Tomato (SLS)

weight by 1 1 % , and the green fruits on the plant by 3 1 % , resulting in an 18%
increase of total fruit weight.
Leaf pruning reduced total fruit weight by 13% (Table 4.10g),
explainable by a reduced photosynthesis. Fruit pruning decreased the harvested
weight by 23% (Table 4.1Og), which was in accordance with the amount offruits removed. However, the weight of fruits on the plants (Table 4.11e)
exhibited no significant effects of pruning nor of C at low plant density.
Theweight offruits with blossom end rot was on average 0.4 kg m"2 andrepresented about 10% of the number of harvested fruits. The percentage ofblossom end rot fruits (Table 4.9h) was not significantly affected by C 0 2 . The
blossom end rot percentage was higher at low plant density, which were theplants with most severe SLS.
The average weight of good quality fruits (Tables 4.9i and 4.10i) was 79
g,with small effects ofdensity (-5%), leaf pruning (-9%) andfruit pruning (+5%).
In the treatments with least SLS,average fruit weight was affected by C (+7%,data not shown). An increase of average fruit weight by elevated C is inaccordance with literature (e.g. Acock & Pasternak, 1986). Fruit DMC (Tables
4.9j and 4.1Oj) was slightly lower at high C than at low C and was highest in
the fruit-pruned crops.
4.5.4

Discussion

Approximated sink/source ratios
For abetter comparison ofthe treatments,the order of magnitude of thechange in sink/source ratio,causedby eachtreatment wasestimated,asfollows.
Sink, represented by the number of fruits m"2,was affected by plant density (3.1
compared to 2.1 plant m"2 is +50%) and by fruit pruning (one third of fruits
removed is -30% in mid June, which decreased to -20% later, because newly
formed trusses were not pruned).
Source, beingthe daily crop photosynthesis,was influenced by Cand bylight interception, i.e. by LAI. This was affected by leaf pruning (one third ofleaves removed,-30%),by plant density and by SLS.The initial difference in LAI
between low and high density was 50% (2.1 versus 3.1 plants m"2). Due toincreasing SLSat wider planting,the difference in LAI increased to 55% in mid
June and 65% later. Elevated C enhanced SLS,causing a 12% lower leaf areaat the end of the experiment compared to low C. The combined effects ofreduced leaf area and enhanced crop photosynthesis by C 0 2 enrichment wereroughly approximated with a simulation model (Challa, 1990).

137

138

Chapter4

Growthandproduction

Table 4.8 Correlation coefficient (r) for the vegetative characteristics of tomato,n = 48 for leaf starch content and n = 72 for all other characteristics.
r<p=o.oi,n=48) = [0-33] and r(Ps00, n=72) = [0.27].
characteristic1

degree of SLS

1

1.00

2

3

4

5

leaf area of top leaves

2

-0.63

1.00

specific leaf area (SLA)

3

-0.38

0.42

1.00

DMC leaves

4

0.55

-0.64

-0.63

1.00

DMC stems

5

0.36

-0.41

-0.73

0.86

1.00

leaf starch content

6

0.61

-0.55

-0.30

0.55

0.32

6

1.00

Table 4.9 Main effects of C02 concentration (low = 370, high = 510 umol mot1 on
average) and plant density (low = 2.1, high = 3.1 plant/m2) on some characteristics oftomato, observed at the end of the experiment (31 July).
All data averaged over two night temperatures and three pruning treatments.

a.

characteristic

units

degree of SLS

Ttreatment

co2

rel.

plant density

b. leaf area of top leaves8m 2 p.p.

co2
plant densityc.

2

SLA of top leaves 8-1

co2
plant density

d. DMC stems%

co2
plant densitye.

starch content leaves%

co2
plant densityf.

harvested fruit weight

kgrn2

g-

total fruit weight 'kgnrï 2co2
plant density

co2
plant density

h. blossom end rot fruits%

co2
plant densityi.

average weight of fruitsg

J-

DMC fruits%

co2
plant density

co2
plant density

low

high

F.pr.

2.4
3.4

3.8
2.8

0.001
0.003

0.174
0.145

0.158
0.187

0.156
<0.001

159.5
137.4

137.5
159.6

0.003
0.002

12.8
13.8

13.4
12.4

0.001
<0.001

2.83
3.75

3.84
0.034
2.93 <0.001 h

6.86
6.13

7.34
8.07

0.003
<0.001

9.71
8.60

10.67
11.80

0.009
<0.001

9.0
12.6

10.6
6.9

n.s.
<0.001

77.6
81.2

80.7
77.1

0.206
<0.001

5.88
5.80

5.74
5.82

0.046
n.s.

relative score:1= normally expanded leaves; 5 = extremelyshort leaves*> thetopsegment hadnotbeenexposedto theleafpruning treatment
interactions exist
i harvestedfruits+ fruitson theplant at31 July

4.5 Tomato (SLS)139

Table 4.10 Main effects of the pruning treatments on some crop characteristics oftomato, observed at the end of the experiment, averaged over all other treatments.
prun ng treatment
characteristic

units

leaf

fruit

no

P
r

0.95

LSD0.05

a. degree of SLS

rel.'

3.0

3.3

3.0

<0.0010.18

b. leaf area of top leaves 8

m 2 p.p.

0.158

0.171

0.169

0.184

0.015

2

158.3

c. SLA of top leaves8

140.6

146.7

0.028

13.0

13.6

13.3

<0.001

0.41

%

3.54

3.13

-

0.007

0.30 hkg m"2kg m"2

7.52

6.03

7.75

<0.001

0.37

10.10

8.93 11.56<0.0010.67

e. starch content leavesf.

harvested fruit weight

g- total fruit weight'
h. blossom end rot fruits
i. average weight of fruits

J- DMC fruits
f-i

-1

12.4

d. DMC stems

cm 2 g
%

%

8.6

10.0

10.8

0.100

2.0

g
%

73.2

84.2

80.0

<0.001

1.9

5.69

5.91

5.83

<0.001

0.07

explainedat Table4.9

Table 4.11 Resultsof tomato, at two plant densities, three pruning treatments and two
C02 levels (L = 370, H = 510 pmol mot1 on average). Observations at the end of theexperiment (31 July), averaged over two night temperatures.
2

low (2.1 pi . m" )plant density:
pruning:high (3.1 pi . m 2 )LSD0.05'k

leaf

fruit*

none

leaf

fruit none

L
H

2.5
4.0

3.1
4.2

2.7
3.9

2.1
3.5

2.2
3.8

1.8
3.5

.37/.57A66

L
H

0.15
0.13

0.16
0.13

0.15
0.14

0.17
0.17

0.22
0.17

0.19
0.20

.041/.028/.033

L
H

149
142

145
116

149
124

181
160

160
142

173
141

26.0/25.5/25.2

L
H

3.2
4.3

3.2
4.4

-

2.9
3.9

2.1
2.9

-

L
H

2.08
2.40

2.04
2.19

2.97
3.14

2.61
3.27

3.46
3.92

3.94
5.18

co2
a. degree of SLS'b. leaf area t o p 8(m2 p.p.)c. SLA top leaves(cm2 g 1 )d. leaf starch(%)
e. fruits on plant(kg m"2)8.56/.60/.94

f- 1 explained at Table 4.9

threevalues for LSD(005I : firstfor comparing equallevels of C02 andplantdensity,
secondforequal C02 andthird forall othercases.
these treatments arecompared in thediscussion (section 4.7)

1.1/1.1/1.1

140

Chapter 4

Growth and production

Combining these various effects on sink and source resulted in thefollowing estimates: smallest change in sink/source ratio by C 0 2 treatment(initially 17% lower sink/source ratio at higher C declining to 10%); greatest
change by fruit pruning (30 to 20% lower sink/source ratio) and intermediatechange by higher plant density and by leaf pruning (about 20% higher
sink/source ratio).
Short leaves (SLS)

C 0 2 enrichmentgenerally increasestheproduction ofassimilates,i.e.thesource. Inaccordance with theworking hypothesis, high Cincreased the degreeof SLSand decreasedthe leaf areaand SLA oftop leaves (Table 4.9a,b,c). It also
increased the DMC of leaves and stems (Table 4.9d), as well as leaf starchcontent (Table 4.9e). The high correlation between characteristics (Table 4.8)
enables us now to define SLS by objective criteria, like reduced leaf area andreduced SLA, rather than by the subjective description of SLS, the original
observation by growers. Decreased SLA at higher C is consistent with previous
research (Madsen, 1976; Acock & Pasternak, 1986), and the same is true forincreased DMC and leaf starch content at high C (Idso & Kimball, 1988; Acock& Pasternak, 1986; Tripp et al., 1991b). These characteristics may indicate asurplus of assimilates.
Lower plant density increases light interception and hence the source(photosynthesis on a per plant basis). So lower plant density increased SLS,as
expected. Plant density had by far the largest effect on fruit weight, partly
becausethetreatment wasstartedatplanting,whereastheothertreatments werestarted five weeks later. As high C and low density had similar effects, in theplots with low-density/high-C the symptoms of SLSwere most severe, leaf areaand SLA were smallest and leaf starch content was highest, whereas at highdensity/low-C the opposite was found (Table 4.11).
Pruning had only small effects on leaf weight and SLS. Tripp et al.
(1991b) also found no effect of fruit removal on foliar deformation. An
explanation for the relatively small effects of pruning might be that changes insink/source ratio had a more local effect (Fisher, 1977; Ho & Hewitt, 1986),
rather than an effect on the whole plant. This would imply that removal ofleaves reduced growth of nearby fruits (lower average fruit weight, asobserved,
Table 4.1Oi), rather than of the apex. Also fruit removal can have its largest
impact somewhat lower in the plant, without strong effects on the apex.
Leaf starch content of the 15th leaf from the top was highly correlatedwith SLS(Table 4.8), and similar results were found by De Kreij (1991, 1992).
Tripp et al. (1991b)also reported an increase of leaf starchwith increasing foliar
deformation, but they concluded that no causal relationship existed. In highplant density, leaf starch was lower with fruit pruning than with leaf pruning4.5 Tomato (SLS)141(Table 4.11d). This was not expected, but is in agreement with observations ofAmmerlaan et al. (1986), who found that removal of tomato fruits caused
accumulation of starch inolder leaves and reduction ofstarch inyounger leaves.
In the present work, only young leaves (nearly full grown) were sampled. It is
unexplained why the starch content presented here differed from that reportedby Ammerlaan et al. (1986). Tripp et al. (1991b) observed no effect of fruit
removal on foliar starch. Because of the variability in results, starch content is
not considered an appropriate indicator of sink/source ratio.
Hypothesis for underlying mechanism ofSLS
Nutrient deficiency might play a role with the incidence of SLS. Tripp
et al. (1991a)observed that foliar deformation increased over the season, while
foliar potassium (K) decreased in parallel. They observed in two out of eightcultivars a lower Kcontent in crops with more deformation and concluded that
K deficiency caused the phenomenon. This conclusion seems questionable,
because adeclining trend in Kcontent in tomato leaves iscommonly observed(Voogt, 1988).
There seem to be more indications that SLS is caused by deficiency of
calcium inthe apex.Cropswith SLSfrequently havesymptoms ofCa deficiency,
like yellow margins of young leaves and scorched leaf tips. Lower Ca uptake
induced both severe SLS and blossom end rot in fruits in work of De Kreij(1991) and also in the present experiment blossom end rot seemed associatedwith SLS (Table 4.9a,h). Blossom end rot is caused by Ca deficiency (Ehret &Ho, 1986). In recent work, De Kreij (1992) could induce severe SLS by a low
Ca supply. Ca deficiency in leaves can reduce leaf area of tomato (Holder &Cockshull, 1990; Bakker, 1991b). It is possible that Ca deficiency at leaf
initiation or during early leaf growth,might cause an invisible injury, manifested
later as reduced leaf size.
It is perceptible that a low sink/source ratio may lead to Ca deficiency
in plant organs. Fruits are supplied with water to a large extent by the phloemsap (under some conditions 85 to 99%, Ho et al., 1987). The relative
contribution of the phloem is larger if assimilate availability is greater, which isthe case in a C 0 2 enriched crop. Because phloem contains very little Ca(Bangerth, 1979; Adams, 1986), a high assimilation rate might induce Ca
deficiency. The Ca containing xylem flows to the transpiring leaves and only
small amounts reach the non-transpiring organs. This theory was postulated by
Ho (Clover, 1991) for tomato fruits, but might also apply to the apex, assuming
the apex to be asink with a low transpiration, like fruits.Another way of putting
it, is that high C increases the C 0 2 assimilation, so that the available Ca is

142

Chapter 4

Growthandproduction

distributed over alarger amount of biomass (dilution effect, Porter & Grodzinski,
1984; Eng et al., 1985; Kuehny et al., 1991). The Ca content of the apex was
not observed, as only the 15th leaf was sampled. No literature was found that
could support this hypothesis (Ho, 1994, pers. comm.).
The relatively large effect of C on leaf growth might be explained by anadditional effect of C on the plant Ca content. High C causes partial stomatalclosure, and subsequently reduces crop transpiration (chapter 3), which can
reduce the Ca translocation in the plant. The lower relative humidity measured
in the compartments with high C (Fig.4.5d) confirms that the transpiration was
reduced. (Inasemi-closed system asagreenhouse,a low air humidity isadirectconsequence of low rate of crop transpiration). It iswell known that particularly
Cadeficiency canoccur atreducedtranspiration (Bangerth, 1979;Adams, 1986;
Ehret & Ho, 1986; Holder & Cockshull, 1990; Bakker, 1991b) because thiselement is transported with the transpiration flow. The reduction of the Cacontent was even more pronounces in the apex (Ehret & Ho, 1986) or in theyoungest leaves (Armstrong & Kirkby, 1979), than in other organs at reduced
transpiration.
Conclusions and recommendations
It is concluded that C 0 2 enrichment is beneficial for fruit production,
unless the crop suffers severely from SLS. With elevated C (around 510
umol mol"1) compared to low C (370 umol mol"1)the increase of fruit weight on
the plants atthe end of the experiment was 19% on average. Itwas insignificant
in crops with severe SLS and 3 1 % in the crop with the least SLS (highdensity/unpruned).
As a method of avoiding short leaves, it can be recommended toincrease the plant density or, in an early planted year-round crop, to maintainan extra shoot on the plants in spring. Further research is required to clarify themechanism behind leafdeformation (SLS)insummer. It isparticularly interesting
to investigate the role of calcium in the incidence of SLS.

4.6 Eggplant (LTC)

4.6

EFFECTS OF C 0 2 ON LEAF TIP CHLOROSIS (LTC)
AND FRUIT PRODUCTION OF EGGPLANT

EM. Nederhoff& K. Buitelaar, 1992, JournalofHorticulturalScience 67:805-812.

4.6.1

Introduction

In glasshouse cultivation of eggplant, frequently leaf chlorosis occurs. It
is considered a problem, because of possible reduction of production capacity.
Two types of chlorosis may occur at the sametime in the same canopy, but thetwo types have not clearly been distinguished until now. Most common ischlorosis causedby magnesium deficiency andcharacterized by irregular yellow
spots in the interveinal mesophyll of older leaves (Mengel & Kirkby, 1978;
Winsor & Adams, 1987). It prevails in bursts from spring until the end of thecultivation. The present work, however, deals with a form of chlorosis, thatbegins on the distal end of the leaf, near the main vein, both in the veins andthe mesophyll. It is called here leaf tip chlorosis (LTC). It gradually covers thewhole leaf and finally leads to loss of the leaf. Frequently a leaf with LTC has
a break across the main vein, caused by brittleness. LTC usually arises in
April/May in the upper half of the plants or in growing side shoots, andparticularly inextremely large,young leaves (Fig.4.6). LTC isstimulated by C 0 2
enrichment (Buitelaar, 1991).
Until now, only magnesium was considered in relation to chlorosis in
eggplant (e.g. De Kreij, 1989). However, LTC closely resembles the symptomsof boron deficiency (Shorrocks, undated; Roorda Van Eysinga & Smilde, 1981;
Winsor & Adams, 1987). Symptoms similar to LTC in eggplant were observedin young sweet pepper leaves, where they were accompanied by leaf boron
deficiency (Sonneveld, 1991).
The following hypothesis is proposed here to explain the observed
stimulating effect of C 0 2 on LTC. High C 0 2 reduces stomatal conductance andhence plant transpiration, at least to some extent (section 3.6.2). In eggplanteven a remarkably sensitive stomatal closure in responseto C 0 2 was measured(section 3.6.1). Reduced canopy transpiration may imply a reduction intranslocation of the nutrients calcium and boron, which are transported almost
exclusively by the xylem (Mengel and Kirkby, 1978). As those elements are
relatively immobile (i.e. not redistributed), their availability for plant organs isstrongly related to the rate of transpiration. Low transpiration induced B
deficiency intheyoungest leavesoftobacco (Von Michael et al., 1969). Anothereffect of elevated C 0 2 is that it increases the dry matter production, and thus

143

144

Chapter4 Growth andproduction

Fig.4.6 Subsequentstages of leaftip chlorosis(LTC) in eggplantleaves, as observedin the experiment.

further decreases the concentration of some nutrients inthe dry matter ('diluting
effect'). By these two processes, high C might induce B deficiency in fast
growing, young leaves.
The aim of the present experiment was to investigate whether high C in
eggplant induces leaf tip chlorosis and whether this is associated with leaf B
deficiency. The effect of high C on fruit production was considered.
4.6.2

Materials and methods

The experiment was conducted in four identical compartments (16 m x16m) of a computer-controlled, Venlo-type glasshouse complex. Twocompartments received low C and two high C: the achieved average C 0 2
concentrations were 413 and 663 umol mol" 1 , respectively (means over 2

4.6 Eggplant (LTC)

145

compartments, over week 6 to 29, Fig. 4.7b). Pure C 0 2 was supplied througha net work of perforated tubes on the ground, 3.2 m apart. C was monitored byan infra red gas analyzer, type Ultramat (Siemens, Munich, Germany), with ameasuring cycle of 4 min.
Heating temperatures were 24/24 °C (day/night) in the first three weeks,
gradually decreased to 20/18 °C, maintained from March until the end of theexperiment. Ventilation temperature was 25 °C from March onward. Global
radiation outsideanddry andwet bulb airtemperatures inthegreenhouses were
measuredevery min. Theaverageachievedenvironmental conditions are shownin Fig. 4.7.
Eggplant (cv. Cosmos) was sown on 20 October and planted on 10
December 1990 on rockwool at adensity of 2.5 plants per m 2 , with two shoots
per plant. The first harvest was 11 February and the last on 18 July (end ofexperiment).
Each compartment contained 24 experimental plots, in which several
subtreatments were multifactorially combined with the C 0 2 treatments. All
experimental plots were located in the rows under the ridge, whereas the rows
under the gutters and near the compartment walls were guard rows. The ridgerows consisted of three experimental plots of 8 plants each, plus two guard
plants in the beginning and three at the end. The subtreatments are notconsidered in this paper, asthere were no interactions with C. Presented are themain C 0 2 effects, averaged over all subtreatments. Further details on crop andenvironment were given in section 3.5.
Observations
The incidence of LTC was measured on 15 April, 27 May and 16 July.
All leaves from one double guard row (58 plants) per compartment that wereclearly affected by LTC (more than 10% yellow) were removed, weighed andmeasured. The severity of LTC was also visually assessed in all 24 plots percompartment on 12 April, 16 May and 28 June.Three observers independently
scored on a relative scale from 0 to 5, for the degree of LTC. The three scores
were averaged before statistical analysis.
Plant growth parameters were determined on 16 April on 3 plants percompartment. Leaf area and fresh and dry weight of leaves were measured; dryweight after 48 hours at 80 °C in a forced ventilated oven.
Leaf contents of K, Ca, Mg, P, N-total, N 0 3 , Fe, Zn and B were
determined as described by De Bes (1986) on samples of 16 leaves. Leaves of
two standard plots per compartment were previously labelled, and sampled onfour dates between 18March and 10June, inthree ageclasses (young, medium,14 6

Chapter 4

Growth and productionold). The samples contained leaves with and without LTC. On 10 June also asample of exclusively leaves with LTC was taken. Sampling for B analysis
requires great care, because of the great non-uniformity. However, this is only
the case at extremely high B contents, and negligible at low levels (Oertli,
1994).
Fruits were harvested every week from 11 February until 18July. Fruits,
separated into first and second class (smaller than ca. 180 gram),were counted
and weighed for each experimental plot. Fruit DMC was determined four times
between 24 June and 9 July on separate samples from four fruit growth stages,
from low and high C. Fresh and dry weights of fruits and calyces were
determined, as well as volumes of fruits.
Keeping quality was investigated for fruits of four harvesting dates
between 28 March and 21 June. Ten harvested fruits of some selected plots
were stored under controlled conditions (20 °C and 90% relative humidity). The
firmness of fruits and quality of calyces were assessed directly after harvest andone and two weeks later.
4.6.3

Results

Leaves and chlorosis
The destructive plant measurements of 16 April showed no significant
differences in plant fresh and dry weight and LAI between low and high C,
possibly due to the small number of sampled plants. LAI was about 2.7. SLA
was significantly smaller at high C than at low C (185 and 214 cm 2 g"1 DM,
respectively), which is in accordance with literature (Acock & Pasternak, 1986).
The incidence of LTC revealed significant differences between low andhigh C in number, weight and area of yellow leaves (Table 4.12). High C
induced 2 to 3 times asmany yellow leaves than low C. The accumulated areaof removed, chlorotic leaves was about 0.06 and 0.15 m 2 per plant for low andhigh C respectively. This is 0.16 and 0.38 m 2 per m 2 respectively, and related
to the estimated final leaf area, it is 3.2 and 7.5%, respectively. In commercial
situations sometimes far more severe damage by LTC prevails. The visualassessment of degree of LTC also revealed highly significant differences for C 0 2
effects (Table 4.13a). SLA was clearly lower and DMC was higher at high C inthe (partly) yellowed leaves (Table 4.12e,f).
Fruit production and quality
The production rate was always higher at high C than at low C and thedifference increasedduringthe season(Fig.4.7d).Cumulative production (Table
4.13b) was increased by 10% at 25 March (6 weeks after first harvest) and by

147

4.6 Eggplant (LTC)800, - . 700

"5
_ 600
O

£
500

O
u
400

300

200

28

-\
5

1
10

1
15

1
20

1
25

1
30

2.0-

d

I

j*

<U
<D

£
(N

•D

,\ I

00

u

_*
S
ra
^
0.8^
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o

*V

'y

3

•*
/
/ i T

2 0.4-

i 11

•o

Q.

~l
5

1
10

1
15

1
20

week number

125

0.0
30

'

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u

20

V

1 '

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MM"E 1.224\iV 'i
i v 't

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fl

II

i
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week number

Fig. 4.7 Results of the eggplant experiment with low C02 ()
and high C02 (and) , asobserved in four compartments.
a. Q = global radiation outside the glasshouse (MJm'2 week'1)
b. C02 = average C02 concentration (umol mot1, 9:00 - 18:00 h)c. Tair = average air temperature ("C, 9:00 - 18:00 h)d. production rate (kg m'2 week'1), averaged over two replicates.

i
25

i
30

148

Chapter4

Growthandproduction

Table 4.12 Leaf tip chlorosis (LTC) of eggplants at low (413) and high C02
concentration (663 pmol mot' on average).
a. number of yellow leaves per plantb. fresh weight of yellow leaves (g/ plant)c. area of yellow leaves (m2/ plant)
d. yellow leaf area relative to estimated total leaf area (%)
e. specific leaf area (SLA)of yellow leaves (cm g'1 dry weight)
f. dry matter content (DMC in %) of the (partly) yellow leaves.
All differences between low and high C02 are significant, except those with '='.
LSD isgiven for the accumulated values only (P=0.1, n=2).

date:

15 April

27 MayC0 2 :

low

high

low

a. # y Ivs
b. wt y Ivs
c. area y Ivs
d. rel.area y Ivs
e. SLAy Ivs
f. DMC y Ivs

0.15
1.57
0.01
0.8
219
14.9

1.73
9.08
0.03
3.0
186
17.7

1.60
9.4
0.03
2.4
241
14.7

accumulatedhigh

16 July
low
high

4.38
20.7
0.07
4.8
195
16.6

0.99 2.83
7.8
19.0
0.03
0.05
2.7
1.2
191
167
16.6 ==16.8

2.7
8.9
18.8 48.7
0.06 0.15
3.2
7.5
217 182
15.5 =16.9

lowhigh LSD ai

Table 4.13 Effects of low and high C (413 and 663 pmol mot1 on average, resp.)on some characteristics of eggplant:a. degree of leaf tip chlorosis on a relative scale (0= no, 5 = severe yellow leaves);b. cumulative production of fruits (kg m'2) (class 1and 2) on four dates;
c. cumulative number of harvested fruits per m2 (class 1and 2) on four dates.

a. degree of LTC (relative)

b. cum. prod, (kg m"2)

c. cum. number of fruits (m 2 )

date

lowC

12 Apr
16 May28Jun
25 Feb
25 Mar
27 May18Jul
25 Feb
25 Mar
27 May
18Jul

0.2
0.8
1.4
0.67
2.58
10.83
19.50
4.2
13.1
43.1
76.0

high C

1.2
1.9
2.5
0.66
2.85
13.27
24.10
4.2
13.9
49.7
88.5

LSD,

0.05

0.42
1.08
0.72
n.s.
0.1
0.7
2.4
n.s.
0.3
1.3
5.6

5.1
14.7
.018
0.90
18.9
n.s.

4.6 Eggplant (LTC)

149

Table 4.14 a. boron and b. magnesium concentration (pmol g1 dry matter) of
eggplantleaves. Variables: plant fruit load (FL, n = normal, I = low); leafage(LA,y= young,m= medium, o= old)andC02 concentration(L = 413, H = 663pmol mot1
on average). Statistical significancediscussed in section4.6.4.

FL
LA
a. B
n
y
n
m
n
o
1
y
1
m
1
o
avrg
n+l
ya
b. Mg
avrg

18 MarL
H

15 AprL
H

13 May
H
L

10Jun
H
L

average
L
H

1.37
1.88
1.43
1.94
1.66
1.40

1.12
2.21
1.07
1.81
1.56
1.10

1.24
0.91
2.65
1.43
1.00
2.50
1.62
1.34

0.97
0.78
2.20
1.14
0.80
2.71
1.44
1.06

0.96 0.82
0.84 0.79
1.15 0.86
0.93 0.77
0.97 0.82-

1.08 0.90
1.26 1.06
1.17 0.98
-

1.31
1.25
1.52
1.43
1.36
1.56
1.36
1.37

1.05
1.27
1.30
1.11
1.16
1.51
1.20
1.08

209

210

206

204

202 177

228

211

205

229

sample exclusivelycontainingyoungleaves affectedbyleaftip chlorosis

24% at 18 July. Number of fruits harvested per m 2 was initially 6% higher andlater 16% higher at high C (Table 4.13c). Average fruit weight was slightly
higher at high C than at low C (Table 4.13b,c). The relative number of secondclass fruits was 7 - 1 1 % of the total number of fruits and was not significantly
different for low and high C.
The maturation period of the fruits (duration between anthesis andharvest) was determined frequently and showed no effect of C, as it was on
average 32.5 and 32.3 days for low and high C, respectively. Also fruit DMC
did not show an effect of C: on 16 April the average fruit DMC was 7.6 and
7.3%, on 9 July it was 8.2 and 7.9% and of the calyces it was 12.4 and 12.1%,
for low and high C, respectively. The specific gravity offruits was 0.57 and 0.56
g ml" 1 , respectively. Fruit quality (firmness), assessed directly after harvest andone andtwo weeks later, was not significantly different but tended to be slightly
better from high C. The quality of the calyx (colour green or brown, and thepercentage rot)was on average notdifferent inthetwo C 0 2 treatments (data notpresented).
Nutrient contents
The boron concentration (Table 4.14a) of the leaves was generally low.
The differences in B data could not be tested with ANOVA, because of15 0

Chapter 4

Growth and production

non-orthogonality of the data.Therefore regression analysis was applied. Boroncontent was significantly lower (P<0.05) in young leaves than in older leaves.
In all cases except one, leaf B content was lower at higher C. The
negative effect of Con Bcontent was found both in young and older leaves, but
young leaves were most relevant, as LTC usually arises there. B concentration
in young leaves was on average 0.29 umol g"1 (21%) lower at high C than at
low C (P<0.01). The sample with exclusively yellow leaves had an even lower
B content than the other samples, consisting of leaves with and without LTC.
The concentration of magnesium (Table 4.14b) and other nutrients
exhibited only non-systematic or small differences, insignificant with this low
number of samples. Soother nutrients than boron were considered irrelevant for
the incidence of LTC.
4.6.4

Discussion

Leaf boron content
The leaf boron concentrations measured (Table 4.14a)were below thosereported for Bdeficiency: in tomato, the normal Bcontent is between 3 and 10
umol g"1 (dry weight) and deficiency occurs around 1 umol g"1 (Shorrocks,
undated). In tomato a B content of 1.2 umol g"1 caused deficiency symptoms(Gupta, 1983); B levels of 0.5-0.9, 2.1 and 3.0 umol g"1 corresponded withsevere, considerable and slight deficiency symptoms, respectively (Adams &Winsor, 1974). Baevre (1990) observed in tomato plants growing in peat, a leaf
B content above 3 umol g" 1 , and positive effects of increased B supply.
It is generally accepted that boron (like calcium) is almost exclusivelytranslocated by the mass flow in the xylem and hardly redistributed (Michael etal., 1969;Mengel & Kirkby, 1978;Oertli, 1994), sothat the leaf B concentration
depends on the transpiration. This explains also the lower B concentration inyoung leaves compared to older leaves.
The calculated transpiration (section 3.5.2) was only slightly reduced
over the whole cultivation period, but if considered over the period from thestart of C 0 2 enrichment until the date when leaves were first harvested foranalysis (12 February until 18 March) the calculated transpiration was about
15% lower at high than at low C. In this period the sampled young leaves had
expanded and it is presumable that this period had been critical for thedevelopment of B deficiency in the growing young leaves.
Boron content in young leaves was 2 1 % lower at high C than at low C,
both on 18 March and 15 April. This difference is larger than the calculateddifference in transpiration. It may be explained by a additional dilution effect,
asthe DM production increased considerably by C 0 2 enrichment. It is beyond

4.6 Eggplant (ITC)

the scope of this work to determine the magnitudes of the transpiration effectand the dilution effect on the leaf B concentration, because this requires
measurements on individual leaves.
The lower B concentrations at high C were not caused by a lower B
supply, as all four compartments received the same nutrient solution. Samplesof the solution taken from the rockwool slabs, had B concentrations of about
100 umol I"1 (at pH 6.2) in February and around 60 umol I"1 (at pH 6.3) later inthe season, which is supposed to be sufficient (Sonneveld & Straver, 1989). B
uptake is favoured by a lower pH of the nutrient solution (Adams & Winsor,
1974; Mengel and Kirkby, 1978) and by a higher B supply (Sonneveld & De
Bes, 1984, Baevre, 1990). However, recent observations demonstrate that ahigher supply can not always prevent deficiency symptoms (Sonneveld, 1992,
pers. comm.).
Recently, the experiment was repeated (Rijsdijk et al., 1993b), but
extended with some levels of B supply. A reduced B supply hardly decreased
the leaf B content. Only an extremely low supply gave a significant lower
content and severe LTC. High Cclearly aggravated LTC,but in spite ofthis, also
remarkably increasedthefruit production.These resultsconfirm those presented
above, but also this second experiment could not elucidate the background ofboron in this respect.
It can be conclude that the observations confirm the hypothesis: high C
decreased leaf conductance and transpiration (section 3.5.2); high C wascorrelated with reduced leaf B concentration; high C aggravated leaf tip
chlorosis; leaves with LTC had the lowest B concentration. It is the most likely
explanation that B deficiency, because of reduced transpiration at high C,
caused the observed LTC. However, more specific research on boron is desired
to further confirm the causal relationship between B and LTC, and if required,to find ways to increase the leaf B content.
Fruit production
Accumulated fruit production was 24% higher at elevated Cthan at low
C. This C 0 2 effect on fruit production is in the order of magnitude as generally
reported in the literature (Kimball, 1986; Mortensen, 1987). SoC 0 2 enrichment
increased fruit production, despite an increase of LTC. The light interception
capacity ofthe canopy was relatively little affected by LTC,because ofthe large
leaf area (LAI of about 5. For comparison: tomato often has an LAI of about 2,
mainly due to the cultivation measure of removing older leaves). Obviously thesmall negative effect of reduced active leaf areawas morethan compensated forby the increased photosynthetic rate per unit leaf area.

151

152

Chapter 4

Growth and production

These compensation aspects were verified with a simulation model for
light interception and photosynthesis (Gijzen, 1992). The model calculations
yield a rather crude approximation, as it was made for fixed conditions (airtemperature 25 °C, global radiation outside 600 W m"2 and reference C of 500
umol mol"1). It does not account for the light interception by yellow leaves andfor the fact that a partly yellow leaf is still partly active. These two latter
simplifications will partly compensate for each other.
The model demonstrates that a 10% decrease in LAI would cause 6.5%
reduction in calculated canopy photosynthesis if LAI 1.5 and 1.35 werecompared; a 3% reduction if LAI of 3 and 2.7 were compared and only 1 % if
LAI of 5 and 4.5 were compared. Increasing C from 413 to 663 umol mol" 1would increase the simulated canopy photosynthesis by 23% at LAI of 1.5 andby 2 1 % at LAI of 5. So it is obvious that the positive effect of C 0 2 enrichment
is far larger than the effect of a (small) loss of leaf area by LTC. A marked
reduction of LAI would be disadvantageous at low LAI, i.e. severe LTC isundesirable in early spring, whereas a (limited) reduction of LAI is acceptable
in a full grown canopy. The increasing difference in fruit production between
low and high C during the season is explained partly by the declining impactof leaf loss by LTC on canopy photosynthesis.
The total production was clearly favoured by C 0 2 enrichment, despite
increased leaf tip chlorosis. The recommended C in greenhouse cultivation isusually 700 to 900 umol mol" 1 (Mortensen, 1987). The C actually achieved insummer is far lower, as it is determined by technical, climatic and economic
factors (Nederhoff, 1994a,b). The results of this experiment show that in spring(when high C can beachieved), it isadvisable not to supply C 0 2 excessively ina young eggplant crop (with a low LAI), for instance not to exceed 700
umol mol" 1 , in order to prevent or limit the incidence of LTC.

4.7 Synthesis and discussion

4.7

SYNTHESIS AND DISCUSSION

4.7.1

Structure

15 3

Section 4.7 first gives an overview for each crop species of the observed
growth and production in relation to the C 0 2 concentration. A hypothesis is
proposed to explain the species-specific features. Subsequently, the various
aspects introduced in section 4.1 (growth rate, light useefficiency, fruit set, DM
allocation, leaf morphology, fruit production and fruit properties) arediscussed.
Section 4.7.5 presents an hypothesis, which is used to explain several
observations (section 4.7.6 - 4.7.9). The overall effect of C on fruit production
is discussed (section 4.7.10) by comparing the observed fruit production to the'C0 2 -rule'.
4.7.2

Growth and production of cucumber

Vegetative growth
In cucumber (section 4.3.1), a low and a high C 0 2 treatment wereapplied, with average C of 364 and 620 umol mol" 1 , respectively, over theperiod 28July until 19 October. The two Ctreatments were applied in triplicate
and were multifactorially combined with two pruning treatments: the plants
were either unpruned or fruit-pruned (2/3 of the inflorescences removed).
Therewere many interactions betweentheCtreatments andthe pruning
treatments. Vegetative growth was increased by high C in the first two weeks of
C 0 2 enrichment, but after four weeks, most vegetative parameters were notsignificantly different between low and high C, at least in the unpruned
cucumber crop (Table 4.1a). Also in other studies it was found that vegetative
growth was stimulated by high C in the first weeks, while the differences inplant size soon levelled off or disappeared completely (Aoki & Yabuki, 1977;
Klapwijk & Wubben, 1984; Kriedemann & Wong, 1984; Peet, 1986; Rijsdijk etal., 1992). In the fruit-pruned crops, however, C 0 2 enrichment resulted in ahigher weight of leaves and stems, and these differences still existed after somemonths (Table 4.1).
The vegetative dry weight gain between 28 July and 19 October was
about equal for low and high C in the unpruned crop, while it was significantly
increased by high C in the fruit-pruned crop (Table 4.2). On several observation
dates, SLA and LAR were often not significantly affected by C or were lower athigh C, particularly in the fruit-pruned crops (Table 4.1).
Fruit pruning significantly enhanced vegetative growth, for instancevisible by a larger LAI (Table 4.1). This is explained by the fact that growing

15 4

Chapter 4

Growth and production

shoots became the major sinks for assimilates instead of fruits. These results
agree with work of Marcelis (1993a) with cucumber, where decrease of thenumber of fruits per plant favoured vegetative growth. Fruit pruning did not
significantly affect SLA inthe current work. Also Marcelis (1993c) observed that
SLA of cucumber plants did not respond to fruit pruning, except that it
decreased when all fruits had been removed.
Fruit production
The onset of cucumber fruit production was sometimes found to occur
a few days earlier in a C 0 2 enriched crop than at low C (Enoch et al., 1970;
Nederhoff & Schapendonk, 1985). Rijsdijk et al. (1992) found that the period
between anthesis and harvest was one day shorter at high C, whereas Enoch etal. (1976) did not find such aneffect. Inthe present work, the harvest started on
the same day, but the first harvest was greater at high C than at low C. The
different observations are explainable, because the time for harvesting a
cucumber does not depend on ripeness, but on weight or size, and aharvestable size is reached earlier under high C. The period of fruit growth isinfluenced also by other factors, for instance temperature, light and number ofcompetitive fruits (Marcelis, 1993a,b,c, respectively). This aspect was notquantified in the present work.
Fruit production (fresh as well as dry weight) was always bigger athigher C. In both experiments with cucumber, both the number offruits and theaverage fruit weight were increased by high C, whereas fruit DMC was not
significantly affected. In expt 1 in the unpruned treatment, fresh weight fruit
harvest increased by 34%, 2/3 of which was caused by an increased numberof harvested fruits and 1/3 by increased average fruit weight. Dry weight fruit
production increased by 32%, 4/5 of which can be ascribed to the increased
assimilation rate (apparent from an increased rate of dry weight gain) and 1/5
to a shift in DM allocation in favour of the fruits. In the fruit pruning treatment,
the effect of C was a 20% increase in fresh weight fruit production, completely
owing to increased number of fruits. Also dry weight fruit production increased
by 20%, almost completely caused by increased assimilation under high C.
Fruit pruning reduced the number of harvested fruits only slightly. The
relatively small reduction is explained by the increased growth of new lateralshoots with inflorescences in the fruit-pruned crops (section 4.7.5).

4.7 Synthesis and discussion

4.7.3

15 5

Growth and production of sweet pepper

Vegetative growth
Of sweet pepper (section 4.4) the two extreme C 0 2 treatments arecompared here: '250' and '450' with average C of 301 and 454 pmol mol" 1 ,respectively, over the period 8 August - 22 October.
High C tended to reduce the vegetative growth with respect to weightsof leaves and stems and leaf area (Table 4.15). LAI was smaller, due to reduced
absolute leaf weight per plant and reduced SLA. However, LAI was stillreasonably large. Reduced vegetative growth is ascribed to competition for
assimilates by growing fruits. This is particularly important in sweet pepper(Daunicht & Lenz, 1973; Hall, 1977; Rylski, 1986; Hubert, 1988; Klapwijk,
1988; Van Uffelen, 1988; Bhatt & Srinivasa Rao, 1989), but occurs also in
eggplant (Claussen, 1976), tomato (Van Gurp, 1991), cucumber (Marcelis,
1993a) and other crops (Gifford & Evans, 1981). Because aC 0 2 enriched sweet
pepper crop bears more fruits (owing to better fruit set and less abortion ofyoung fruits, section 4.4), the competition with vegetative growth is stronger in
a C 0 2 enriched crop than in an unenriched crop. Vegetative growth in sweet
pepper plants is also restricted artificially because newly formed lateral shoots
are topped, to prevent further growth. However, plants in low and high C weretopped exactly equally.
Fruit production
Production was increased by increased fruit number, while average fruit
weight was unaffected. The observed improvement in fruit production andreduced vegetative growth at high C imply that the DM allocation wasappreciably shifted from vegetative to generative (reproductive) organs by C 0 2
enrichment (see below, section 4.7.8). This shift in allocation caused a
considerable part (1/3) of the increase in sweet pepper dry weight fruit
production,while the other 2/3 wascaused by increased C 0 2 assimilation rate.
The relative difference in fruit production was 46 %, at C increasingfrom about 300 to 450 pmol mol" 1 . This appears to be a great response,
compared to for example Fig. 1.1. The main explanation is probably earliness:
the C 0 2 enriched plants had a higher early production than the non-enrichedplants. It can be seen that the relative difference levelled off in the course oftime (Table 4.7). Inthe short harvest period,this earliness still had an impact on
the total harvest data. Secondly, C considered is low, and hence the C effectstrong. Thirdly, the shift in DM allocation is appreciable, and additional to theincreased photosynthesis.

156

Chapter4 Growth andproduction

The results generally correspond to previous reports on sweet pepper:
Enoch et al. (1970) also found better fruit set; Milhet & Costes (1975) found far
better fruit set and no difference in average fruit weight after C 0 2 enrichment;
Daunicht & Lenz (1973) found aconsiderable increase in partitioning of DM to
the fruits at elevated C.

Table 4.15 a. Growth and dry matter allocation of sweetpepper over the period
8 August- 22 October. Dry weightgain of various plant segments and ofvegetative,
generativeandtotalabove-groundplant tissue, andweightratios. Absolutegrowthrate(GR)is dry weight gain per day. Light useefficiency (LUE) is dry weight gain peramountintercepted PAR.
b. Someplant parameters attheendof theexperiment(see alsoTable4.4 -4.7).
C 0 2 'treatment' and (average):a. dr wt gain 8 Aug•

'250' (306)'450' (448)LSD0.05

68.1

58.6

n.s.

98.7

83.9

n.s.

•22 Oct

leaves (g m"2)2

stems (gm" )2fruits harvested (g m"

75.8

165.2

26

fruits on plant (g m"2)

89.1

60.2

n.s.

fruits pruned (g m"2)

)

10.4

19.1

n.s.

2

vegetative (g m )

167

143

n.s.

2

generative (g m" )

175

244

n.s.

2

342

386

n.s.

ratio leaf / total (%)

19.9

15.2

3.1

ratio generative / total (%)

51.2

62.6

6.4

GR (g m"2d"1)

4.56

5.15

n.s.

LUE (g MJ-')

1.7

2.1

n.s.

3.3

2.5

0.54

SLA (cm g')

326

278

16

LAR (cm2 g')

144

122

12

DMC leaves (%)

13.9

15.2

0.7

DMC stems (%)

12.8

13.9

1.2

total (g rn )b. stationary 22 October
LAI2

4.7 Synthesis and discussion

4.7.4

157

Growth and production of tomato

Vegetative growth
Tomato (section 4.5) was grown at two C 0 2 concentrations after 13
June: 370 and 510 umol mol" 1 . At high C compared to low C, weights of leaves
and stems were higher, SLA and LAR were lower (Table 4.16) and DMC andstarchcontent of leavesandstemswere higher (Table4.9d,e).These phenomena
are characteristic for the 'short leaves syndrome' (SLS, sections 4.1.6 and 4.5).
SLSwas stimulated by a number of factors, e.g. high C, low plant density (i.e.
high irradiance per leaf),fruit pruning.Two cropsthatwereextremewith respect
to SLSarecompared here:crop-1 with plant density 3.1, without pruning, hardly
affected by SLS;crop-2, with plant density 2.1 and with fruit pruning, suffering
severely from SLS.
The approximated LAI of tomato seemed to be about equal at low andhigh C (Table 4.16b), in spite of a tendency to higher leaf weight at high C(Table 4.16a). The overall effect of C was a reduction of leaf area (Table 4.9).
In crop-2 (with SLS) the approximated LAI was small, both at low and high C(Table 4.16b). Low values of LAI have been observed often in tomato, forinstance De Koning (1993) reported an LAI as low as 1.3 for a producing cropin summer. A small leaf area ispartly caused by picking the older leaves, which
is a normal procedure in practical tomato cultivations. Notice that crop-2 had
a 30% lower plant density than crop-1, sothe difference in LAI between crop-2
and crop-1 must be ascribed for the greater part to the lower plant density andonly for a small part to reduced leaf area per plant (Table 4.11c).
Fruit production
The relation between C and tomato fruit production was complicatedand variable (Table 4.11e). There was a relation (probably causal) between C
and SLS (section 4.5.4) and also a relation between SLS and response of
production to C. In the crop with severe SLS (crop-2) there was only astatistically insignificant tendency to increased fruit production at high C. Thisdisappointing effect of C in crop-2 is explainable, as SLS is a symptom of
relative assimilate abundance, and C 0 2 enrichment aggravated this problem.
Inthe sound crop (crop-1), the fresh weight of harvested fruits increasedby 14%, and the fresh weight of fruits on the plant by 3 1 % by high C, resulting
in 18% increase of the total fruit dry weight production in crop-1. This increase
must be ascribed to increased assimilation only, as the allocation was not
significantly changed (Table 4.16a). High Cfavoured the fruit weight still on theplants (to be harvested in August) far more than the fruits production harvestedby the end of July. This is explicable, because the earlier harvested fruits were158

Chapter4

Growthandproduction

g r o w n partly before the start of the C 0 2 treatment (section 4.5.3). In tomato, theresults of a treatment are apparent only after a w h i l e , due t o the long fruit
growth period.

Table 4.16 a. Growth and DM allocation of tomato over period 10 May - 31 July.
Estimated dry weight gain of various plant segments and of vegetative (veg.), generative(gen.)and total above-ground plant tissue, and weight ratios. Absolute growth rate (GR)is dry weight gain per day; light use efficiency (LUE) is dry weight gain per amountintercepted PAR. low C = 370, high C = 510 umol mol'' average.
b. Some plant parameters at the end of the experiment (seealso Table 4.9-4.11).
crop -1 acrop-2 b

low C

highC

low C

highC

60.4

73.3

65.0

76.7

LSD

0.05

a. growth 10 May - 31 Jul
leaves on plant (g plant')
1 c

14.9

leaves pruned (g plant" )

18.8

18.8

18.8

18.8

-

stem (g plant"1)

68.4

78.9

85.8

99.4

9.8

161.9

180.8

159.8

169.3

12

fruits harvested (g plant"1)
1

79.7

103.8

64.4

68.8

22

1

vegetative (g plant" )

148

171

170

195

23

1

generative (g plant )

242

285

224

238

24

total, veg.+gen. (g plant 1 )

389

456

394

433

36

total, veg.+gen. (g m" )

1223

1432

788

866

96

ratio leaf / total (%)

20.5

20.2

21.2

22.0

2.7

ratio gen./ total (%)

61.9

62.4

57.0

55.1

3.8

2

1

14.9

17.5

9.6

10.6

1.2

LUE (gMJ" )

2.8

3.4

2.2

2.4

0.25

3.3

3.2

2.0

1.8

0.03

174

141

145

116

22

81.7

67.7

61.4

50.2

11

fruits on plant (g plant" )2GR (g m d" )1b. stationary 31 Jul
LAI (approximated) d1

SLA of top leaves (cm g" )1

LAR (cm g" )crop-1,soundcrop,density3.7plants perm2,without fruitpruning
crop-2,with SLS, density2.1plantsperm2,with fruitpruningC. average weightoverall treatments
LAIcould notbemeasured, but was approximated fromleafdry wt,SLA andplant density

4.7 Synthesis anddiscussion

4.7.5

Hypothesis explaining species-specific features

Tomato,sweet pepperandcucumber showedsimilarities and differencesin response to C (Table 4.17). One difference is that cucumber (unpruned
treatment), in contrast to tomato and sweet pepper, did not show a clear
reduction of SLA and leaf area and no increase in DMC of vegetative organs athigh C. Another difference isthat in tomato the DM allocation was not affected
by C,whereas itwas incucumber and particularly in sweet pepper. The specificgrowth and production behaviour are explained below by sink and source
relationships.
The source activity, i.e. canopy photosynthesis, determines theavailability of assimilates. Itdepends mainly on light andC andon LAI.The sinkstrength is the demand for assimilates, determined by number, size andphysiological age of fruits and by number of growing points and immature
leaves per unit ground area.
Important facts are that sink rather than source determines the DM
partitioning (section 4.1.4),and secondly that arelatively high source comparedto sink means an overproduction of assimilates. Such a sink limitation, i.e. low
sink/source ratio, usually causes storage of assimilates in leaves and reductionof SLA.There aresomecases reported,where sink limitation caused suboptimal
fruit production (e.g. Peet, 1984; see also section 4.5.4).

Table 4.17 Summary of theC02 effects ongrowth and production
asobserved in cucumber (section 4.3.1),sweet pepper (section 4.4)
andtomato (section 4.5). Datafrom Tables 4.2,4.3, 4.15 and4.16.
Symbols: - no tendency, t increase, I decrease, with increasing C;
betweenbrackets: statisticallyinsignificant tendency.
cucumber sw.pepper tomato
leaf area index

"

i

I

SLA

-

1

I

(1)

I

(0

t

t

t
T

(dry) weight leaves(dry) weight stems-

DMC leaves
DMC stems-(t)fruit production

îtaverage fruit weightî

DMC fruits
allocation to fruits

T
(t)
at

T

T

"

159

16 0

Chapter 4

Growth and production

Cucumber
Cucumber plants arebasically never sink-limited, incontrasttothe othercrops investigated. Cucumber plants continuously produce new lateral shoots,
which are usually not removed. They bear at least one inflorescence per leaf
axil, and sometimes more, particularly after many fruits have been harvested(Drews, 1979). In a normal productive crop, a considerable number of flowers
abort (Marcelis, 1992), indicating that there are more than sufficient potential
sinks formed. Because new shoots with inflorescences appear rapidly andbecause fruits are harvested after a short growth period (10 to 20 days, Rijsdijk
et al., 1993a), sink strength can adapt (increase or decrease) rapidly to fit to theaverageassimilate production. Soacucumber plant caneasily maintain aproperbalance between vegetative and generative growth. Because the assimilates
available can always be used in sinks, and need not to be stored in leaves andstems, SLA in cucumber was not severely affected by C (section 4.7.9).
TomatoA tomato plant has only one main shoot with one vegetative growing
point, asall lateral shoots are removed at appearance. After each third leaf, onetruss is formed. The number of flowers per truss is different between cultivars
and may vary slightly throughout the season,but it isgenerally limited (order ofmagnitude 7-15 flowers per truss). Sothe number of flowers present on a plant
at a certain moment is bound by a maximum, in contrast to the abundant
flowering of sweet pepper, eggplant and cucumber.
In tomato, as in other crops, the number of flowers that set fruit after
pollination, depends basically on the amount of assimilates available. In thepresent experiment, however, the effect of increased assimilation by high C on
fruit setwas almost nil,because under the favourable light conditions (summer),virtually all flowers grew into fruits. So high C can hardly increase the numberof generative sinks on the plants, i.e. C 0 2 supply did not affect the sink strength.
As the DM allocation is regulated by sink strength, rather than source activity,
it is explicable that DM allocation was not changed by C 0 2 supply in tomato.
The growing period of a tomato fruit is 45 to 60 days (Rijsdijk et al.,1993a), which is far longer than that of cucumber. The limited variation in
number of fruits and the long fruit maturation period cause that there isfar lesspossibility for adjusting the sink strength intomato than in cucumber. In periods
with high light and particularly when C 0 2 issupplied,the C 0 2 assimilation rate
can exceed the demand for assimilates. A surplus of assimilates is stored inleaves and stems,which increases the leaf thickness, i.e. reduces SLA. An oversensitive response of atomato crop may even causethe 'short leaves syndrome'(sections 4.5 and 5.3.3).

4.7 Synthesis and discussion

16 1

Sweet pepper
In sweet pepper, the features and also the proposed underlying
mechanism, are least clear. During a short period with favourable conditions,many flowers may set fruit. Subsequently, over a longer period, the fruits willgrow and mature (fruit growth duration 48 to 64 days, Rijsdijk et al., 1993a).
Because in this period the major part of the assimilates is attracted by thegrowing fruits, the vegetative growth and the formation of new flowers andyoungfruits istemporarily inhibited (Daunicht & Lenz, 1973; Hall, 1977; Rylski,
1986;Van Uffelen, 1988; Hubert, 1988; Klapwijk, 1988; Bhatt & Srinivasa Rao,
1989; Van Gurp et al., 1991). This results in a clearly cyclic fruit production(Van Uffelen & Goebertus, 1985).
Due to increased fruit set under high C, the generative sink strength ishigher at high than at low C, which explains the shift in DM allocation towards
the fruits (section 4.7.8). Because fruit growth inhibits vegetative growth andformation of new fruits, the sink strength isfixed for a longer period and cannot
easily adapt to increased assimilate supply, asdescribed for cucumber. As only
a more or less fixed amount of assimilates is demanded by the sinks, theassimilation may sometimes be abundant for aperiod oftime. These assimilates
can be stored in leaves and stems, which explains that also in sweet pepper,
SLA is clearly lower at higher C (section 4.7.9).
4.7.6

Growth rate (GR) and light use efficiency (LUE)

Growth rate(GR)and light useefficiency (LUE)weregivenfor cucumber
in section 4.3.1 and are calculated here for sweet pepper and tomato. GR and
LUE in the present study are based on above-ground dry weight gain. Noticethat LUE depends on the LAI, because light interception is a function of LAI(section 4.1.2).
In cucumber (section 4.3.1), high C increased GR and LUE by about
25%, both in the unpruned andthefruit-pruned crop. LUEof cucumber was 3.4
and 4.3 g MJ'1 (g dry weight per MJ intercepted PAR), for low and high C,
respectively (Table 4.2). This is an increase of 10 % per 100 umol mol" 1 C 0 2 .
With sweet pepper (section 4.4), GR and LUE seemed considerablyincreased by C 0 2 enrichment, as the observed LUE values were 1.7 and 2.1
g MJ" (Table 4.15). However, these data do not allow afirm conclusion about
effects of C on LUE, because of too few samples and too large variability
between samples.
Intomato (section 4.5), GRwas increased by C 0 2 supply by about 17%
in crop-1 and by about 10% in crop-2. LUE data of crop-1 were 2.8 and 3.4
and of crop-2 2.2 and 2.4 g MJ"1, at low and high C, respectively, which was162

Chapter4

Growthandproduction

an increase of 2 1 % in crop-1 and of 9% in crop-2 (Table 4.16). It must beemphasized that these calculations are made over the whole period between
planting and ending of the experiment, while the C 0 2 treatments were started
only at 13 June. No samples were taken at that date, because no plants could
be missed from the plots. Hence the growth over the actual treatment period
were approximated by using estimates for the plant weight on 13 June, basedon similar tomato plantings (De Koning, 1994, pers.comm.). The approximatedrelative effects of C on GR and LUE over the treatment period are at maximum
2% higher than the figures mentioned.
De Koning (1993) observed that GR (rate of above-ground dry weightgain) of tomato, ranged from about 5 to 25 g m"2 d" 1 , with intercepted PAR
ranging from about 1 to 8 MJ d" 1 , and LUE ranging from 3 to 5 gMJ - 1 .
Heuvelink (1995b) observed twelve tomato cultivations and established a LUE
of 2.5 g dry weight per MJ PAR received. Challa et al. (1994) derived a LUE of
3.1 gMJ" 1 .
Summarizing, observed was an increase in LUE by C 0 2 enrichment,
varying from 6 (tomato crop-2) to 11 (cucumber) and 15 (tomato crop-1) % per
100 umol mol -1 C 0 2 . The LUE values observed in cucumber and tomato
compared reasonably with those reported in the literature for tomato. Sweet
pepper had a lower GR and LUE than the other crops. Bruggink & Heuvelink(1987) also found a far lower growth rate of sweet pepper than of tomato andcucumber in young plants. The observed effects of C on GR are discussed in
section 4.7.10, where they are compared to the 'C0 2 -rule'.
4.7.7

Fruitset

Carbon dioxide obviously promoted fruit set and production of sweet
pepper (section 4.4). The number of harvested fruits increased by 46% by C 0 2
supply. This is ascribed to the direct positive effect of C on the rate of C 0 2
assimilation and on carbon translocation (Ho, 1977). Positive effects of C on
fruit set were also found by other authors, e.g. Enoch et al. (1970), Milhet &Costes (1975) in sweet pepper and Calvert & Slack (1975) in a winter plantingof tomato. It must be emphasized that fruit set is usually limited by source intomato in early spring (due to low light), while in summer fruit set of tomato is
usually not critical. The growth of young fruits in cucumber (either winter orsummer planting) is usually not considered a problem.

4.7 Synthesis and discussion

163

4.7.8 Allocation of dry matterIn the literature, a wide range of percentages of DM allocation to fruits
can be found (section 4.1.4). In the present studies, the DM allocation wasdetermined at the end of the cultivation and includes all biomass grown during
the cultivation, including harvested and removed biomass, except roots. So
Tables 4.2, 4.15 and 4.16 present the long-term cumulative DM distribution.
The DM allocation found for cucumber was similar or higher than the reported
values.Those for sweet pepper and tomato were lower than generally reported.
This is explicable, because the present experiments with sweet pepper andtomato covered relatively short periods, while the fruit growth period is long. It
is normally observed in those two crops that the share of the fruits in the
cumulative biomass production gradually increases during the season (Rijsdijk
et al., 1993a).
It is of interest to consider if the C 0 2 concentration affected the DM
allocation. The hypothesis was that sink rather than source determines the
allocation (section 4.1.4). C 0 2 supply influences primarily the source. In someexperiments, sink was manipulated additionally by fruit pruning.
In the unpruned cucumber crop (section 4.3.1), the share of the fruitsin the dry weight gain increased by C 0 2 enrichment at the expense of leaf
growth (Table 4.2). This is in accordance with the hypothesis, because thegenerative sink (number offruits)was remarkably increased by C 0 2 enrichment,
owing to formation of new shoots with inflorescences. The higher demand for
assimilates by the fruits increased the assimilate flow towards the fruits. It
appeared that in this unpruned crop, sink strength of fruits in competition for
assimilates was predominant above that of the vegetative sinks, asfruit growth
was favoured relatively more than vegetative growth by C 0 2 enrichment. Thisis probably partly a numerical matter, as there were more generative thanvegetative sinks in the unpruned treatment.
Reducing the number of generative sinks by means of fruit pruning
stimulated the growth of lateral shoots with inflorescences. So the loss ofgenerative sinks was compensated for by formation of new vegetative andgenerative sinks. Also on the new shoots, frequently 2/3 of the new
inflorescenceswere removed.Theultimate result of C 0 2 enrichment inthe fruitpruned crop was a strong increase both in vegetative and generative dry weight
gain, so that obviously no clear change in DM allocation occurred.
Insweet pepper the contribution offruits inthetotal dry weight gain was
far higher at higher C, while the dry weight gain of leaves and of stems was
lower, not only relatively but even absolutely. This caused that the percentage

16 4

Chapter 4

Growth and production

generative of total dry weight gain was 63% at high C, compared to 51% at low
C (Table 4.15). This is aconsequence of competition: aC 0 2 enriched crop hasa better fruit set (Table 4.6 and section 4.7.7) and hence a larger number offruits on the plant. These fruits form a stronger sink strength, attracting moreassimilates at the expense of vegetative organs. According to the hypothesis,
increased fruit sink strength is responsible for increased DM allocation to fruits.
This corresponds to findings of other authors (section 4.7.3) that fruit growth
suppresses the vegetative growth in sweet pepper.
Intomato,theestimated DM allocation was compared between low andhigh C in crop-1 (with high density, without pruning, little SLS) and in crop-2(with low density,fruit pruning,severeSLS).Thecontribution offruits in biomass
production was significantly lower in crop-2 than in crop-1, which is a directconsequence of fruit pruning. This was also found in tomato by Hurd et al.
(1979). In contrast to cucumber, tomato could not compensate for the removed
fruits by forming extra shoots or fruits. So reduction of generative sink strongly
reduced DM allocation to the fruits. This in accordance with the hypothesis on
DM allocation (section 4.1.4), that sink rather than source determines the DM
allocation.
There was no significant effect of C on DM allocation (Table 4.16),
which is also in accordance with this hypothesis. C 0 2 enrichment did notchange the sink strength in tomato, shown by almost equal numbers of fruits
harvested in the two C 0 2 treatments. This experiment was done in summer,
when tomato usually sets fruit easily (notice that this tomato crop was sinklimited, section 4.5). In contrast to the present work, Frydrych (1984) observedthat C 0 2 enrichment in tomato plants increased the DM allocation to the fruits.
Inthat case,however, fruit setwasenhanced by C 0 2 supply, leadingto a higher
generative sink strength. Thus these observations also fit the hypothesis.
4.7.9 Morphological characteristics
Specific leaf area (SLA)SLA was reduced by elevated C in sweet pepper, tomato and eggplant.
The reduction was 15 to 20%, at C increasing by 150 to 250 pmol mol" 1 .
Because SLA isaffected by somany other factors, it was not attempted to derivea relation between SLA and C from few data.
In general, SLA is reduced by high C, aswell as by bright light. This is
usually ascribed to a surplus of carbohydrates relative to the assimilate demand
i.e. sink limitation (Hurd, 1968;Jolliffe & Ehret, 1984;Acock & Pasternak, 1986)
or more particularly to accumulation of starch in leaves (Madsen, 1976;

4.7 Synthesis and discussion

16 5

Goudriaan & De Ruiter, 1983; see Farrar & Williams, 1991). Other authors
observed more densely packed palisade mesophyll cells and also more layersof these cells (seeAcock & Pasternak, 1986). Inthe present tomato experiment,
the leaf starch content was significantly higher at elevated C, but the starchcontent observed on 31 July was too low to explain the difference in SLA.
Therefore, obviously the amount of structural DM per leaf area was increased.
Reduction of sink strength basically has a similar effect on SLA as
increasing the source. SLA tended to be lower in a fruit-pruned crop of tomato(Table 4.10), but not in cucumber (Table 4.1). The fact that in cucumber SLA
was not influenced by C and fruit pruning, is explicable because this crop canmaintain aproperly balanced sink/source ratio (section 4.7.5). According to theliterature, fruit pruning reduced the SLA in various experiments, e.g. in sweet
pepper and tomato (Frydrych, 1984), in sweet pepper (Bhatt & Srinivasa Rao,1989), but in cucumber only after complete fruit removal (Marcelis, 1993d).
Hence, reduced SLAcan be regarded ascharacteristic of morphological
adaptation of a canopy to assimilate abundance, which can be a consequenceof high C. The 'short leaves syndrome' in tomato can be regarded an extreme
form of this adaptation, enforced by other effects (sections 4.5 and 5.3).
Reduced SLA is particularly undesirable in canopies with a low LAI (asusually intomato): such acrop would favour from increased leaf area (increased
light interception capacity) and not from increased leaf thickness. In a canopy
with a large LAI (for example full-grown eggplant, section 4.6.4, or sweet
pepper), the effect is less harmful.A low SLA seems in any case adissipation ofenergy, as the biomass is not used for increase of production, nor for increaseof the production capacity.
Dry matter content of vegetative organs
The DMC of vegetative parts was slightly increased in sweet pepper
leaves (Table 4.5), tomato leaves and stems (Table 4.9d) and tended to be
increased in eggplant leaves (Table 4.12f). In cucumber, DMC of leaves andstemswas not consistently influenced by C (Table 4.1). An increased leaf DMC
was often reported. According to Idso & Kimball (1988), the DMC of plants is
not influenced by C, except that leaves can have a higher value, owing tostorage of starch. Indeed in tomato ahigher DMC was accompanied by a higher
leafstarchcontent, butthis could notcompletely explain thedifference in DMC.
The absence of such a tendency in cucumber is ascribed, again, to the easilyadjustable sink/source ratio (section 4.7.5).

16 6

Chapter 4

Growth and production

4.7.10 Fruit production
Quantity of fruit production
The total DM and fruit production of the four crops investigated wereshown in previous tables,andaresummarized inTable4.18.The relative effects
of C per unit C 0 2 (% per umol mol" 1 , abbreviated hereto % u"1)are calculated.
Thefigures for relative fresh and dry weight fruit production response areequal,
because fruit DMC was not affected by C. After Slack et al. (1988), the absoluteincrease in harvestedfruit weight perweek perumol mol" 1 C 0 2 was calculated.
The response of DM production to C was highest in tomato and lowest
in sweet pepper. The response of fruit production to C (absolute increase in dry
weight and relative increase indry orfreshweight) appeared by farthe strongest
in sweet pepper. This isexplainable by earliness, low C (farfrom saturation) andshifted DM allocation in favour of the fruits (section 4.7.3).

Table 4.18 Approximated effects of C02 concentration on fruit production in
cucumber (Table4.2), sweetpepper (Table4.7 and 4.15), tomato (Table4.16) andeggplant (Table 4.13). Fruit production observed at low (L) and high (H) C arecomparedin absolute(abs.) or relative (rel.) sense.

co2

cucumber| aepperwithout
fruitpruning pruned
harvest duration (weeks)

tomatoeggpl-

crop-1 crop-2
SLS
sound

12

12

7

5

5

22

average C 0 2 level(umol mol"1)

L
H

364
620

364
620

306
448

370
510

370
510

413
663

total D M production

L

819

874

342 a

389

394

1021

1092

386

a

456

433

-

2

(g m )
rel. effect on total D M

Hproduction ( % u')

H

0.096

0.097

0.086 a

0.12

0.07

-

fresh weight harvested

L

16.79

17.15

2.69

8.40

5.12

19.5

H

22.11

20.66

3.96

9.33

5.37

24.1

1.73

1.14

1.28

1.33

0.36

0.84

0.062

0.041

0.100

0.074

0.020

0.064

0.12

0.08

0.33

0.08

0.03

0.09

(kg m"2)L

abs. effect on fresh weight
harvest (g m"2 week"' u')abs. effect on dry weight
harvest (g m"2 week"1 u"1)
rel. effect on fresh & dryweight harvest ( % u"1 )datafrom Table4.15,covering ashorterperiod thanin Table 4.7

4.7 Synthesis anddiscussion

With respect to the absolute difference in fresh weight of fruits,
cucumber shows the strongest response to C and eggplant the weakest. Also
sweet pepper responded less than cucumber, despite the strong response inproduction of fruit dry weight. These results are explainable by the differencesin fruit DMC (cucumber 3.6, tomato 5.6, eggplant 7.6 and sweet pepper 8%,
independently of C). The second cucumber crop and tomato crop-2 lagged
behind infruit production,explainable byfruit pruning.Alsoother authors foundthat cucumber responded stronger with respect to fresh weight fruit production,
than tomato (Slack & Hand, 1985; Slack et al., 1988).
Production compared to the 'C0 2 -rule'
The observed relative effects of Con fruit production arecompared here
to the expected relative effect at a particular C, based on the C0 2 -rule (eqn.
2.7b). This rule describes only the effects of C on DM production, so if there isan additional influence of C on DM allocation, this will cause a discrepancy
between observed and expected relative effect of C. Also possible negative
effects interfering with the fruit production process might be revealed by thiscomparison. The relative effects are expressed in % (pmol mol"1)"1, which isabbreviated to % p"1.
In cucumber, grown at C of 364 and 620 umol mol" 1 , respectively, theexpected relative C effect was about 2 1 % , or 0.08 % p"1.The observed relative
effect on growth rate (GR, i.e. rate of DM production) was 0.095 % p"1, which
exceedstheexpected value.Theobserved relativeeffect on fruit production was
0.12 % p"1 in the normal cultivation, and 0.08 % u"1 in the fruit-pruned crop.
This difference between the two crops can be explained only partly by the shift
in DM allocation under high C in the normal cultivation.
In sweet pepper, the C range considered was 306 to 448 pmol mol" 1 ,and the expected relative effect was 2 1 % (or 0.15 % p"1). The relative effect of
C on DM production (although calculated over only a part of the production
period) was 0.09 % p"1. The relative effect on fruit production was extremely
high (46%or 0.33 % p"1),which was ascribed to several effects (section 4.7.3).
Eggplant was investigated in the C range between 413 and 663
pmol mol" 1 . The expected relative effect was 0.07, and the observed effect was
0 . 0 9 % p' 1 .
Tomato was investigated inthe range 370 to 510 pmol mol" 1 , where theexpected relative effect was about 0.10 % p"1.The observed relative effect of C
on DM production was 0.12 % p"1.The total fruit production, with the fruits on
the plants included (section 4.5.3 and Table 4.11e), increased by 0.12 % p"1.

1 67

16 8

Chapter 4

Growth and production

which exceeds the expected relative effect. Crop-2 responded far less, due to
SLS and partial deflowering.
Generally, the C0 2 -rule yielded too small values (except in tomato
crop-2), when applied to fruit production. In sweet pepper, an additional effectof increased DM distribution to fruits and somewhat earlier production in C 0 2 enriched crops (Table 4.7) can explain a part of the discrepancy between
expected C and observed C effect. It will be discussed in section 5.2 whether
conditions as light flux and leaf area index can explain the underestimation by
the C0 2 -rule. A preliminary conclusion isthat generally the C0 2 -rule provides
a conservative approximation of the effect of C on fruit production.
4.7.11 Fruit properties
Weight and dry matter content of fruits
The average fruit weight was generally increased by C 0 2 enrichment(cucumber, Table 4.1; tomato,Table4.9i; eggplant,Table4.13b,c), as reported
by many authors (e.g.Acock & Pasternak, 1986). Only in sweet pepper, C had
nosignificant effect on the averagefruit weight (Table 4.7b), in accordance with
Milhet & Costes (1975). This might be explained by the fact that the fruits thatwere set additionally (owing to C 0 2 enrichment) were mainly fruits on lateralshoots, which usually lag behind in growth.
Fruit DMC tended to decrease slightly at high C in tomato (Table 4.9j)
and eggplant (section 4.6.3), and was not significantly affected by C in
cucumber (Table 4.1). No effect ofCon fruit DMC wasexpected (section 4.1.5).
The reduction in DMC that was observed sometimes might be explained byindirect effects,for instance bythefactthat areduced stomatal conductance andtranspiration at high C may increase the relative water content. DMC of tomato
fruits was higher in the fruit-pruned crop than in the unpruned crop (Table
4.1Oj), which corresponds to the fact that fruit DMC increases with decreasing
number of fruits on the plant Marcelis (1993b).
Fruit quality
Various aspects of fruit quality have been considered in several
experiments. Inearlier work (Nederhoff & Schapendonk, 1985), cucumber fruits
were judged for the colour, directly after harvest and after storage undercontrolled conditions. The fruits of the non-enriched crop were initially slightly
greener,which wasexplained by higher irradiance inthe lessdensecanopy, but
the difference levelled off during two weeks of storage. In sweet pepper (section
4.4.3) and tomato (section 4.5.3), no significant differences in external fruit

4.7 Synthesis and discussion

quality were observed. There was a tendency for increased blossom end rot intomato at high C, but it was not significant. Blossom end rot was discussed inrelation to calcium (section 4.5.4). Eggplant fruits (section 4.6.3) from low andhigh C did not differ with respect to specific mass and occurrence of secondclass fruits. Also no C 0 2 effect was found on firmness, colour of fruit and calix
and percentage calix rot of eggplant fruits, either directly after harvest or after
storage under controlled conditions. The fact that hardly any aspect of fruit
quality was significantly affected by C, agreeswith the literature (section 4.1.5).

16 9

5.7 Resultsconsidered

171

5 Final discussion
5.1

RESULTS CONSIDERED

The work presented in the previous three chapters has enhanced theinsight in effects of the C 0 2 concentration on some important physiologicalprocesses of greenhouse fruit vegetable production.Thefollowing results can beconsidered as new contributions to the existing knowledge: data files withphotosynthesis measurements,the 'C0 2 -rule', quantification of stomatal response
to C, improved insight in the relation between stomata and transpiration,
demonstration of the insignificance ofthe effect of C on leaftemperature and of
the absence of an endogenous 'midday depression' in the transpiration andphotosynthesis measurements, analysis of differences between crops regarding
sink/source ratio and DM partitioning, hypothesis for the incidence of 'shortleaves' in tomato and advice for effectively preventing it, explanation for theincidence of leaf tip chlorosis in eggplant, test of intermittent C 0 2 supply.
The results obtained fulfil the main objectives and related researchquestions (section 1.4). Considering canopy photosynthesis (P, chapter 2), theobserved effects of C on P were presented by a set of regression equations.
These generalized the results and demonstrated the effect of C on certain
photosynthesis characteristics, in reply to research question la. In view of the
aim to establish a rule of thumb for C effects, the 'C0 2 -rule' was proposed (seenext section). Another objective was to test a simulation model for canopy
photosynthesis to be applied in climate control and decision support systems.
After two well-known models were tested, it was concluded that certain
applications would require a model that accounts better for effects of C on P.
It is anticipated that a more elaborated model, assembled from described
physiological knowledge, probably gives a better performance (Gijzen et al.,1995).
The effect of C on DM production and fruit production was quantified
in several experiments (chapter 4), inview of researchquestion lb.The observed
effects of C on production were compared to the C0 2 -rule, because this is aneasy and generic description of the C 0 2 effect. In one particular case (tomato
crop-2), the observed C effect was lower than that predicted by the C0 2 -rule,
dueto negative side effects of C 0 2 enrichment. Two side effects of high C were
investigated: reduced transpiration (chapter 3) and morphological adaptation(chapter 4). The discussion on side effects (section 5.3) gives an answer toresearch questions IIa & Mb. Also intermittent C 0 2 supply, intended to avoid
side effects of high C, is discussed further (section 5.4).

17 2

Chapter 5

Final discussion

5.2

THE 'C02-RULE'

The C0 2 -rule proposed was: X = (1000/C)2 * 1.5 (eqn. 2.7b), with X
the relative effect of an increase in C (in % per 100 umol mol" 1 ). The merits ofa rule of thumb need no discussion, but important is its validity, i.e. its
capability for predicting the effect of C. It must be considered what theconsequence is of not accounting for the interaction of C 0 2 with light and withtemperature; and whether the rule is applicable at low and high LAI, etc.
A point of discussion is, why the observed effects of C on fruit
production were higher than the effect of C on Pcalculated by the C0 2 -rule, as
seen in section 4.7.10. It was expected that fruit production, an overall result,would show a lower response than the photosynthesis-based C0 2 -rule. It is
possible that the crops in the photosynthesis experiments were adapted to highC (although it was attempted to avoid this), whereas in the later experiments
these adaptations were prevented better. Another possible explanation is aneffect of earliness under high C, for instance in the sweet pepper experiment(section 4.7.3). A third possible explanation isthat the average light flux played
a role.
In order to establish the validity and restrictions of this C0 2 -rule, andto test the significance of interactions of C and light, the C0 2 -rule is comparedto calculations with a canopy photosynthesis model (Gijzen, 1994, pers.
comm.). This model isbasedon the leaf photosynthesis model of Farquhar et al.
(1980), the light interception model of Gijzen (1992) and Spitters et al. (1989).
This model ispreferred for testingthe C0 2 -rule, because it isprobably at present
the most appropriate for this purpose. It comprises adetailed calculation of the
response of P to the main environmental factors, based on described
physiological knowledge. The model will be discussed in great detail in otherstudies (Gijzen et al., 1995; Heuvelink, 1995a). Some comparisons between
model and rule are presented in Fig.5.1.
Light is by far the most important factor determining the response of P
to C, far more important than temperature, and also more important than LAI,
if LAIexceeds 2 (Fig.5.1). At low light, the C0 2 -rule overestimates the responseof P to C. At medium high light, the relative effect simulated by the model
agrees very well with the relative effect approximated by the C0 2 -rule,irrespective of LAI and temperature. The interaction with light explains why in
Fig. 2.3 the C0 2 -rule compared very well with the regression lines of expts 1,
2 and 3 (with relatively high light conditions, see Table 2.1), while the ruleoverestimated the observations ofexpts4, 5 and 6 (lower light conditions, Table
2.1). Notice that the C0 2 -rule was established arbitrarily after comparison withthe regression lines (section 2.6).

173

5.2 C02-rule

ê

30

O)

>
20-

\.ft
r

\

\^\
\ !^
10\

5 ^

O^s^
~^^^0200

400

600

800

200

C 0 2 concentration

I
400

I
600

I
800

I

1000

(|jmol mol" 1 )Fig. 5.1 Comparison of the relative effect of the C02 concentration (in % per
100 pmol mot') calculated by the 'C02-rule' and by the model of Gijzen (1994).
'C02-rule'[X = ( 1000/C f * 1.5 ]model of Gijzen at low light (100 umol m2 s"' PAR intercepted)
model of Gijzen at medium light (500 pmol m'2 s' PAR intercepted)
model of Gijzen at high light (1000 pmol m'2 s' PAR intercepted).
a. LAI=1,1=25°C;
b. LAI=5, T=25 °C; c. LAI=3, 1=20 °C; d. LAI=3, 1=30 °C.

174

Chapter5

Final discussion

The higher relative response to C at high light also explains that theobserved responses of fruit production were higher than estimated by the C 0 2 rule, as discussed in section 4.7.10. Since the C0 2 -rule was derived fromphotosynthesis measurements under moderate light conditions, the C0 2 -rulerevealed a moderate response to C. The effects of C on production, in contrast,
were studied mainly under summer light conditions.
Finally, the C0 2 -rule is compared to the C0 2 -production curve, which
was derived previously from data from the literature (Fig. 1.1). The two curves
compare favourably (Fig.5.2), which confirms the conclusion that the C0 2 -rulemay be usedto approximate the effect of C on production. The reason why the
curve based on the literature is somewhat lower than that of the C0 2 -rule, isagainthe average lightflux. Many experiments referredto in Fig. 1.1,were done
under poor light conditions,duethe practical problem ofobtaining high C underhigh radiation influx.

160
140

c 120-ou 100O

80

a> 60
'Z3
— 40
0)

A
V

20

0
200

400

600

800

1000

1200
1

C 0 2 concentration (umol mol" )Fig. 5.2 Relative production (%, with 100% at 340 umol mol"') of greenhouse fruit
vegetable crops, according to the literature (Fig. 1.1) and according to the C02-rule.
^ • ^ B 95% confidence interval of mean ofthe observations,
95%confidence intervalof the observations
symbols: • X= 1.5 A (1000/Cf A X= 1.2* (1000/Cf v X = 1.8 * (1000/Cf

5.2 C02-rule

The conclusion is that the rule is roughly applicable to instantaneous(and also daily) canopy photosynthesis, as well as to production. If production
must be predicted for unfavourable light conditions, or if clear negative side
effects (e.g. leaf deformation) are expected, the C0 2 -rule may yield anoverestimation. In this case the multiplication factor (1.5 in eqn. 2.7b) may be
adjusted downwards. Similarly, when clear positive effects are known to occur
in a certain case (e.g. increased DM allocation to the harvestable parts, or highlight influx), one can account for these effects by increasing the multiplication
factor. The lower and higher boundary of the multiplication factor will be in theorder of 1.2 and 1.8, respectively, as was estimated on the basis of thephotosynthesis regression lines (section 2.6.3) and production data from theliterature. Fig. 5.2 shows these lower and higher boundaries of the C0 2 -rule.
As the C0 2 -rule agrees reasonably well with the curve obtained fromdata of various flower and vegetable crops (Fig. 5.2), it can be concluded that
the C0 2 -rule can be used as a generic rule for greenhouse crops. It must beemphasized again that it is not more than a rule of thumb, not appropriate toaccount for refined differences.

175

17 6

Chapter 5

Final discussion

5.3

SIDE EFFECTS OF C 0 2 ENRICHMENT

Possible side effects of high C are partial stomata closure and reduced
transpiration, secondly morphological adaptation, and thirdly reduced
photosynthetic efficiency. Two side effects have been dealt with in different
chapters, and here below these are considered in a more integral discussion.
Partial stomatal closure does reduce the transpiration, but only to asmall extent (section 3.7.2). This appeared not to cause direct problems, neither
regarding increased leaf temperature (section 3.7.4), nor regarding fruit quality
or smaller fruit quantity (except in tomato crop-2). Possible indirect effects ofreduced transpiration, however, might arise from a reduced uptake of nutrients.
This is similar to reduced nutrient uptake at low transpiration, due to high air
humidity. In this case the reduced nutrient content appeared to be mostpronounced in the apex and youngest leaves (Armstrong & Kirkby, 1979; Ehret& Ho, 1986). Several authors reported a reduced leaf mineral concentration in
response to high C (Porter & Grodzinski, 1984; Eng et al., 1985; Peet et al.,
1986; Kuehny et al., 1991).
In the eggplant experiment, high C aggravated leaf tip chlorosis (LTC),
probably due to boron deficiency in young, rapidly growing leaves. In the
eggplant cultivation under investigation, the production was not negatively
affected by LTC, because the effect of the loss of some active leaf area was notdisadvantageous in this crop with a large leaf area. However, reduced uptakeof a nutrient might also be at the basis of SLS, which certainly is a harmful
phenomenon. There may be a relation or interaction between Ca and B(Armstrong & Kirkby, 1979;Jyothi & Shanmugavelu, 1985; Jones et al., 1991b).
The effects of Ca and Bdeficiency are being studied further in new projects at
the Glasshouse Crops Experimental Station in Naaldwijk (De Kreij, 1994, pers.
comm.).
Reduction of specific leaf area (section 4.7.9) is considered acharacteristic of morphological adaptation of the canopy to high C, or more in
general, adaptation to assimilate abundance (i.e relative sink limitation). An
extreme form of this adaptation is the 'short leaves syndrome' in tomato.
However, this is not solely caused by sink limitation, but also by reduced
calcium translocation at high C. The conclusion that reduced stomatal
conductance and morphological adaptation are both involved in SLS, causing
the weak response of fruit production to C, may be an answer to researchquestion II for this particular case (section 1.4.2). It is of interest to investigate
if calcium is involved in general in the adaptation of SLA to the conditions.

5.3 Side effects

177

SLS and LTC are considered no serious drawback of C 0 2 enrichment
per se, but the result of a number of factors. As both occur under particularconditions only, there are measure to prevent them, without ceasing the C 0 2
supply. Deficiency of B, probably causing LTC, occurred mainly in young,relatively fast growing leaves (transpiring organs) after a period of lowtranspiration. The assumed Ca deficiency in the tomato apex (a non-transpiringorgan), which is probably at the basis of SLS, was associated with a low
sink/source ratio. As discussed previously, good production results can beachieved if the C 0 2 supply is continued (at an acceptable rate), while SLS intomato is avoided by increasing sink/source ratio or in eggplant by toleratingsome LTC, asthis is not necessarily disadvantageous. Only in extreme cases, amodest C 0 2 supply is recommended.
As long as a canopy is not closed (i.e. does not completely cover thesoil area), high C promotes the leaf growth,thus increases the light interception
and canopy photosynthesis (Gifford & Evans, 1981). After canopy closure, leaf
area growth has lesseffect on light interception. In addition,the increase of leaf
area may be restricted by reduction of SLA of newly formed leaves grown underhigh C. These processes explain the strong positive effect of high C 0 2 on plant
growth early in the cultivation, and the declining effect later (section 4.7.2).
Besides these morphological adaptations, also physiological adaptation occurs,
as declining photosynthetic efficiency per unit leaf area ( C 0 2 exchange rate,
CER) after long-term C 0 2 enrichment (Hurd, 1968; Tanuka & Fujita, 1974;
Clough & Peet, 1981; Dugal et al., 1990). It has been suggested that thisphotosynthetic adaptation to elevated C might be related to feedback inhibition
by nutrient deficiency (Dugal et al., 1990; Bunce, 1992). This might affect thephotosynthetic efficiency in several ways. There are, for example, indications
that the Caconcentration in thexylem sap influences the stomatal conductancereaction pattern (Atkinson et al., 1990). New research on photosynthetic
adaptation on the scaleof whole crops in greenhouses is intended by Heuvelink(1994, pers. comm.).

17 8

Chapter 5

Final discussion

5.4

INTERMITTENT C0 2 SUPPLY (ICS)

Two experiments were done with ICS, one with cucumber (section
4.3.2) and one with sweet pepper (section 4.4). It must be emphasized that
ventilation was notdone intermittently, but inthe standardway, i.e. onthe basisof temperature. This was done in order to avoid effects of temperature andhumidity (section 4.1.8) and hence deterioration of the crop and fruit quality(Slack et al., 1988).
ICSclearly reduced the C 0 2 expenditure and also reduced the average
C 0 2 concentration achieved. Hence it is logical that the increment inproduction was lower than with constant high C. Mostly, the resulting fruit
production was reducedabout proportionallytothe reduction inC.These results
agree with those of Slack & Hand (1985) and Willits & Peet (1989), who foundno particular favourable effects of 'partial' or 'fractional' enrichment. The
adaptations of the crop to C were not clearly less pronounced under ICS thanunder a constant C. The treatments with low-frequent intermittent supply
appeared to give slightly better results, but the differences were insignificant.
Various reports about ICSare available in the literature. Clough & Peet(1981) introduced ICS, intermittent on the basis of days. Their results wereintermediate to those of continuous low and high C, i.e. growth was about
proportional to the average C. Mortensen (1984) compared ICS on hourly basiswith continuously high C and with a treatment without enrichment inchrysanthemum and saintpaulia cultivars. The results were different between
species and between cultivars.Thesameauthor concluded laterthat continuous
high C generally had effects superior to those of ICS (Mortensen, 1986). In an
experiment under sub-tropical conditions (Zipori et al., 1986), ICS combinedwith intermittent ventilation, gave better results than selective enrichment only
when the ventilation windows were closed. Dugal et al. (1990) reportedthat ICS
yielded the same daily sum of photosynthesis asconstant high C did. However,the photosynthesis measurements were made on excised leaves of tomato
seedlings, and the measuring conditions (particularly humidity near the leaves)
were not representative for a full-grown producing crop in a greenhouse. Thishas probably affected the stomatal conductance in an unrealistic way.
Based on the presented experiments and the literature, the following
considerations are made:• intermittent supply greatly reduces the expenditure of C 0 2 compared tosupply to a constant level, particularly under ventilation;• a limited C 0 2 supply (e.g. ICS) under a normal ventilation regime canaccomplish only a limited increase of the average C;• fruit production was often found to be in accordance with the average C;• thus ICS can accomplish only a limited increase in fruit production;

5.4 Intermittent C02 supply

1 79• in cucumber, the efficiency of C 0 2 utilization was about equal in a constanthigh C and in an ICStreatment; only low-frequent ICSseemed more efficient;• insweet pepper, ICSgavesimilar morphological adaptations asconstant C did(atcomparable average C),only low-frequent ICSseemedto induce relatively
less morphological adaptation;• noclear physiological advantagesordisadvantagesof intermittent C 0 2 supply
could be observed compared to constant level supply.
Thechoice of aC 0 2 regime isalways amatter ofeconomic optimization. Whenthe product price is low, it is not feasible to increase the production at theexpense of much C 0 2 . Under unfavourable economic conditions, it might
therefore be useful to save on carbon dioxide expenditure by using ICS. So ICS
can be afeasible option, if the expenditure of C 0 2 must be greatly reduced for
economic reasons, or if the C 0 2 supply must be stopped for technical reasons,for example if aC 0 2 generator (burner) must be stopped frequently because ofexcessive heat production.

18 0

Chapter 5

Final discussion

5.5

EVALUATION OF THE APPROACH

At the end of this study, the pros and cons of the approach and theconsequences for the validity of the conclusions areconsidered.The aim of thisstudy was to investigate the effect of C on greenhouse crops under practicalconditions. All experiments were done in full-grown canopies in medium-size
greenhouses.
The reason for using relatively large-scale facilities was to achieve
realistic conditions, for instance with respect to interactions between stomatal
conductance, greenhouse air humidity, leaf temperature and transpiration(feedback effects). Small-scale experiments may easily lead to incorrectconclusions in this respect (section 3.1.1). The present work demonstrated a
decoupling between stomata and transpiration in canopies in greenhouses, sothat the response of the transpiration rate to variations in C was restricted.
For canopy photosynthesis and transpiration research, it was necessary
to use whole canopies rather than a few plants in a cuvette, as the lightinterception and the climatic conditions should be comparable to those in real
greenhouse cultivations (discussed in section 2.8). Fruit production can only be
studied in canopies in their reproductive phase, i.e. in crops of a considerable
size and age.Adaptation of acrop to the conditions requires acertain period oftime. There points are all arguments to conduct experiments on the scale of areal greenhouse.
For investigating climatic conditions, it is inevitable to use a separate
greenhouse compartments for each treatment level. So an experiment with anumber of C 0 2 concentrations, set up with sufficient replicates for statisticalanalysis, requires a large number of identical greenhouse compartments. Theseshould be equipped with sophisticated technical facilities, in order to obtain
practical conditions. There are probably no greenhouse research facilities in theworld that fulfil these requirements. The facilities of the Glasshouse Crops
Research Station in Naaldwijk are well equipped, but the number of identicalcompartments is still limited. Most experiments were done with not more than
two or three replicates. Hence, the results showed sometimes a clear tendency,
but the natural variability in responses andthe limited replications impeded thestatistical significance of some results, e.g. in case of C effects on growth ofsweet pepper (section 4.4).
Another drawback of the approach was that the practical problems that
occur in normal greenhouse cultivations, also bothered the experiments. For
instance, high radiation forced the ventilation windows to be opened, which
impeded to maintain high C at high light influx. Although this condition
resembles practical horticulture, it is an omission in the data, which hindered5.5 Evaluation of the approach

181

firm conclusions about for instance maximum photosynthesis rate and midday
depression.
Another disadvantage of working in large greenhouses is that theconditions could not be manipulated as in small-scale or in laboratory
experiments. For instance in the transpiration measurements, the air humidity
could not be controlled without affecting the air temperature (by heating or
ventilating) and/or the canopy transpiration. Therefore, air humidity was not
actively controlled, but was recorded as it was, and used as input factor in theanalysis.
The set up of the study was to investigate several topics one by one.
Measurements on canopy photosynthesis were made in a separate series ofexperiments and the measurements on leaf conductance were done in anotherseries. In both series, C was deliberately maintained equal in different
compartments (except on measuring days),to avoid differences between crops.
Hence, the long-term effect of C on growth and production had to be studied
in a new series of experiments. It was considered a disadvantage that theobservations on various aspects could not be combined, or at least be done in
the same cultivation. Hence, for example the rule of thumb for C 0 2 effects,
derived from photosynthesis measurements, was compared to fruit production
data observed in other experiments. Yet certain observations cannot fully be
explained, because several factors were different in the various series ofexperiments.

Recommendations

Recommendations
for practical horticulture
Preventing morphological adaptation to high C
C 0 2 enrichment reduces the specific leaf area (SLA, leaf area per unit
leaf dry weight), as a consequence of increased assimilate production. C 0 2
enrichment might disturb the balance between assimilate production by thesource and assimilate utilization in the sinks. As an example in tomato, high C
increases the source strength, but cannot affect the sink strength (the apex anda limited number of trusses). A too low sink/source ratio in tomato severely
reduces the SLA, and even causes leaf deformation, in the form of small andcurled leaves,called 'short leaves syndrome' (SLS).This may occur also in othercrops (e.g. ornamentals) with comparable conditions.
It is recommended as a method to minimize the harmful effects ofincreased source, to increase the shoot density. This decreases the source bymutual shading of leaves and increases the sink by increasing the number ofvegetative and generative sinks per unit ground area. The shoot density can beenhanced either by choosing a more narrow plant distance, or in a winterplanted year-round crop, by maintaining an extra shoot on the plants in spring.
In other crops, particularly in cucumber, the sink strength (number of growing
shoots andfruits) easily adaptsto the increased source strength.When measures
to prevent adaptation are not effective, the C 0 2 supply may be restricted.
C 0 2 supply in relation to stomata closure
Increase of the C 0 2 concentration decreases the stomatal conductanceconsiderably. The net overall effect of C 0 2 supply on transpiration of a crop ina greenhouse, however, is a relatively small decrease (the extent of the effects
depends on the conditions). The reduction in transpiration is restricted byadapted air humidity and leaf temperature (feedback effects).
Reduced transpiration may reduce the translocation of the nutrientscalcium and boron, which is disadvantageous in the long term. Particularly
during a longer period of low light conditions, it is required to give extra
attention to maintaining sufficient transpiration (by ventilating, heating, preconditioning) and nutrient uptake (supply and uptake conditions). Only if aserious threat for insufficient nutrient uptake exists, it is advisable to restrict the

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Effectsof C02

C 0 2 supply. This is not very disadvantageous under poor light, because thepotential photosynthesis is low, and thus the deprivation small.
Under high light conditions, the transpiration issufficiently high, sothata reduction caused by high C is usually not critical for nutrient translocation.
However, it is possible that local nutrient deficiencies occur as a consequenceof increased phloem import atthe expense of calcium containing xylem import.
Hence, it is recommended to be aware of the Ca supply to non-transpiringorgans (fruits, apex). Reduced transpiration will theoretically increase the leaf
temperature, but this effect appeared to be small.
Concern for a 'midday depression'
No evidence was found for an endogenous midday depression or
declining photosynthetic and transpirational activity during the course of a day.
Hence there is no reason from this view point, to cease the C 0 2 supply during
midday. The potential C 0 2 uptake is highest at high light, i.e. at midday.
However, a critical requirement is that the water supply and water uptake
capability of the crops are optimal.
Maximum C 0 2 concentration
Aiming for C 0 2 concentration at about threefold the outside value (i.e.
1000 umol mol" 1 at present) has been recommended for some years already.
Arguments werethat canopy photosynthesis tendsto saturate atabout that level,
whereas the risk for possible disadvantages increases (see above). In case of
supply of flue gases from a combustion installation, the risk of accumulation ofharmful gases is an extra reason for restricted supply. The results of the present
work, conducted in semi-practical greenhouses, substantiate the generalrecommendation, from a physiological point of view.
Under some conditions, 1000 umol mol" 1 might be supra-optimal, forexample in tomato when the sink/source ratio is obviously disturbed. Eggplant
hasan extraordinary strong stomatal sensitivity to C. Reduced transpiration may
induce leaftip chlorosis, butthis is not necessarily harmful.Whenever the effectof C 0 2 enrichment is suspected, also in other crops, it is advised to restrict the
supply. At twofold the outside concentration, a large positive effect on P is
obtained, due to the saturation (3/4 of the effect of threefold the outside level,
according to the C0 2 -rule) and the negative effect on stomata is acceptable, as
the stomatal response is linear (3-4 % per 100 umol mol"1).

Recommendations

Minimum C 0 2 concentration
At a high light influx, the absolute quantity of C 0 2 uptake by the cropis of course greater than at low light, and the relative effect of high C appears
more pronounced at high light (Fig.5.2). C 0 2 enrichment isconflictingwith thehigh rate of ventilation, which normally accompanies high radiation. It is
recommended for bright weather conditions to consider the supply of C 0 2 atleast to maintain the outside concentration, because of the relatively strong
effect of increased C at high light and at low C (Fig.5.1 and 5.2). According to
the C0 2 -rule, an increase in C from 250 to 350 umol mol" 1 generally increases
the production by 25%, and at high light even more. The feasibility and thetechnical solution (pure C 0 2 , heat storage) must be considered for individual
cases.
Intermittent C 0 2 supply (ICS)Intermittent C 0 2 supply can be recommended asamethodto reduce theexpenditure of C 0 2 . However, the effect of ICS on production is reduced inparallel with the reduction in average C. No clear advantages nor disadvantages
were observed regarding plant physiological responses. When the C 0 2 supply
must be strictly limited for economic reasons, or should be done intermittently
for technical reasons, there is no reason to advise against ICS.
C0 2 -rule
The 'C0 2 -rule' derived in this study was: X= (1000/C)2 *1.5,with Xthe
relative effect of an C increase, in % per 100 umol mol" 1 . It can be used as arule of thumb for C 0 2 effects, i.e. as a tool for macro studies and global
explorations concerning C 0 2 enrichment. It provides aglobal approximation of
the effect of C on canopy photosynthesis and also on fruit production. The
dependence of the C effect on the light conditions is ignored in the C0 2 -rule.
Whenever a certain positive condition is known (e.g. high light intensity or
favourable assimilate distribution to fruits) or a certain negative condition (SLS
in tomato),these effects can betaken into account additionally by adjusting themultiplication factor (now 1.5)to about 1.2at unfavourable conditions or to 1.8
at favourable conditions.

185

Summary

Summary
Growing under glass offers the opportunity to benefit from thestimulating effect of elevated C 0 2 concentration (C) of the air on plant growth.
In greenhouse horticulture, C 0 2 enrichment is commonly applied to enhance
the production. In chapter 1 of this dissertation, the history of C 0 2 enrichment
in greenhouses is reviewed and the current methods for C 0 2 supply aredescribed. The generalized effect of C on the production of greenhouse crops
is demonstrated by a C0 2 -curve, based on literature data.
The main effect of elevated C is an increase of the net C 0 2 assimilation
rate; other possible effects of C are influences on flowering, fruit set, dry matterallocation to fruits and dry matter content of fruits. Also negative side effects
may occur. The objective ofthis thesis isanalysis andquantification ofthe mainand side effects of C in the range 200 to 1100 umol mol"1 on growth andproduction of tomato (Lycopersicon esculentum Mill.), cucumber (Cucumis
sativus L), sweet pepper {Capsicum annuum L.) and eggplant (Solanum
melongena L),grown ingreenhouses.All experimentswere performed with fullgrown crops in semi-practical greenhouses, under normal operating conditions.
Photosynthesis
The effect of C on canopy net photosynthetic C 0 2 assimilation rate (orphotosynthesis, P)was investigated in chapter 2. Particular aims were to derivea rule of thumb for overall calculations concerning the effect of C on P, and totest a model to be used in climate control and decision support systems.
Measurements were done in six cultivations, each using some greenhousecompartments. The method involved an accurate estimation of the greenhouse
C 0 2 balance, using nitrous oxide (N 2 0) as tracer gas to determine on-line theexchange ratebetween greenhouse andoutside air.Theobtained photosynthesis
data comprised an estimated inaccuracy of about 10%, except larger errors
under particular circumstances in 5% of the data.
A set of regression equations, relating Pto PAR, C and LAI,was fitted tothe measurements, and explained 83 to 9 1 % of the variance. The main canopy
photosynthesis characteristics calculated with these fitted regression equations
were reasonably in accordance with data from the literature or could be
explained by the conditions.

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Effectsof CO2

A rule of thumb ('C0 2 -rule') was derived from the fitted regression
equations. This C0 2 -rule stated X = (1000/C)2 * 1.5, with X in % per 100
umol mol"1,andC in umol mol"1. Itapproximates the relative increaseof canopy
photosynthesis, caused by a 100 umol m o l 1 increase at a certain C.
Two modelsforcanopy photosynthesis (Acock etal., 1978and Thornley,1976)were examined by comparing them with theexperimental photosynthesis
data. Measured environmental conditions and measured LAI were input to themodel. The (modified) models performed reasonably, but the Thornley modelin particular did not adequately represent the effect of C on P. The
photosynthesis measurements were analyzed for the occurrence of timedependent variations in P, irrespective of the conditions (e.g. 'midday
depression'). No indications werefoundof anendogenousdepression or decline
in the diurnal course of P.
Transpiration
The effects of C on conductance (g) of leaves (i.e. of stomata) and on
rate of crop transpiration (E) were investigated in chapter 3. In sweet pepper,
tomato and cucumber, measurements were done in greenhouse compartmentsthat were usually exposed to equal C, but on measuring days, simultaneously
exposed to different C.
Leaf conductance was measured on the upper leaves, using a steadystate diffusion porometer. Measurements were done during a number of days inseveralgreenhousecompartments.Multiple regressionequations,describing theeffects of PAR,VPD-leaf-air, C and optionally leaftemperature on g, were fitted
to the measured data. The fitted equations demonstrated that 100 umol mol"'increase in C in the range 300 to 1200 umol mol"1 reduced g by about 3 to 4 %in sweet pepper, tomato and cucumber and by about 1 1 % in eggplant. These
relative effects arevalid at any level of C, VPD and PAR, if VPD and PAR would
remain constant. In eggplant, g was measured in two glasshouse compartments
where the crops were exposed continuously to low or high C. The stomatalbehaviour of eggplant did not adapt to long lasting C 0 2 conditions.
Generally, partial stomata closure reduces the leaf transpiration, which
reduces the air humidity (in the boundary layer and in the surrounding
greenhouse air) and may slightly increase the leaf temperature. So an increase
in C usually leads to a marked increase in VPD-leaf-air, which enforces theeffect of elevated C on g and counteracts the effect of C on E. Thesephenomena, known ashydrologieandthermal feedback effects,were observed.
Ratesof croptranspiration, measured with three weighing lysimeters percompartment, were highly correlated to radiation. The effect of C on E wasSummary

analyzed by combining the regression equation for g (see above) with thePenman-Monteith equation for E. Calculations by this combination, using
measured environmental conditions as input data, agreed reasonably withmeasured E.
The relation between g and Ewas expressed by a coupling factor, K(relative change in calculated Edivided by relative change in calculated g). Thiswas estimated to be mostly lessthan 0.2, except at low radiation. This implies
that the reduction of the transpiration rate of greenhouse crops caused by(moderate) C 0 2 enrichment isusually small oreven negligible,except under low
light conditions. In eggplant, however, the reduction can be larger, due to thestronger stomatal response to C. Itwas, for instance, 15% in a certain period in
spring.
Notime-dependent variation or 'midday depression'wasobserved inthetranspiration measurements (as in the photosynthesis measurements). Also no
significant effect of C on average leaf temperature was established.
Growth and production
The effects of C on growth and production are studied by investigating
the underlying processes in five experiments (chapter 4). Some features were
investigated only in one species, that was known to respond clearly in thisrespect.
Inan autumn cultivation of cucumber, the effects of Con vegetative andgenerative parameters were quantified. Two C 0 2 concentrations (364 and 620
umol mol"1 on average) were maintained intriplicate, multifactorially combinedwith two treatments of fruit pruning (unpruned and 2/3 of inflorescences
removed). High C stimulated vegetative growth only in the first weeks. Later,
mainly fruit production was favoured by high C, thus increasing the relative
allocation of biomass to the fruits. DMC of vegetative parts and SLA were notmarkedly affected by fruit pruning nor by C in this cucumber experiment.
In sweet pepper, the number of harvested fruits was increased by 46%
by highC(450 umol mol"1)compared to low C(about 300 umol mol"1), whereas
the average fruit weight was not affected. The vegetative growth was lower athigh C. This implies that the allocation of biomass to the fruits was strongly
increased by high C, owing to increased sink strength by fruits (at high C more
fruits were set). Leaf DMC was higher and SLA was smaller at high C.
Tomato in summer commonly suffers from a type of morphological
adaptation, called here 'short leaves syndrome' (SLS),characterized by severely
reduced SLA. As a working hypothesis, it was postulated that SLS is aconsequence of an oversupply of assimilates relative to the sink capacity (i.e.

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sink-limitation or low sink/source ratio). Intwelve glasshousecompartments, thesink/source ratio was varied by maintaining two levels of C 0 2 (350 and 550
umol mol"1)multifactorially combinedwithtwo plantdensitiesandthree pruning
treatments.C 0 2 enrichment andwider plantingenhanced SLS,i.e.decreased theleaf area and SLA. In crops with little SLS symptoms, C 0 2 enrichment
considerably increased the fruit production, whereas in crops with severe SLS,C 0 2 enrichment aggravated SLS and had no significant effect on fruit
production.
The mechanism proposedto explain SLSintomato, isthat local calcium
deficiency arises through two processes. The first is that high C increases theassimilate availability (source strength), implying that the phloem flux into thesinks increases, at the expense of the calcium-containing xylem influx. The
second process is that high C reduces the transpiration and hence thetranslocation of calcium. This leads to a lower Ca content, possibly (according
to the literature) most pronounced inthe apex. It isoften reportedthat a low Ca
content in the apex reduces the area of newly formed leaves. The combinationof small leaves (due to Ca deficiency in the apex) and thick leaves (due tostorage of assimilates) is manifest asSLS.
Asthe stomata ofeggplant appearedto be more sensitiveto Cthan thoseof the other crops investigated, this species is particularly of interest to study anutrient-based disorder. Eggplant often shows chlorosis on the distal end of theleaves (leaf tip chlorosis, LTC) in spring, particularly under high C. An
experiment was done to investigate the effects of C on LTC, on leaf boron
content and on fruit production of eggplant. Two levels of C 0 2 (413 and 663
umol mol"1) were maintained in duplicate. The results support the hypothesisthat LTC is related to reduced boron content in young,fast growing leaves. LTC
and boron deficiency were significantly more severe at high than at low C.
However, fruit production was 24% higher at high C than at low C, despite
more severe LTC.This isexplicable, because this crop had a large LAI (of about5), so the loss of some active leaf area hardly affected canopy photosynthesis.
Analysis of the growth and production data obtained in the fiveexperiments, revealed the following:• Light useefficiency (LUE)was increased by C 0 2 by about 10to 15% per 100
umol mol"1 increase in C.
• Fruit set of sweet pepper was greatly increased by high C.
• Allocation of biomass (i.e. DM distribution) to fruits was increased by high C
in sweet pepper and cucumber, explained by increased sink strength.

Summary• (Except in cucumber) increase of C by 150 to 250 umol m o l ' reduced thespecific leaf area (SLA) by 15 to 20% and slightly increased the dry matter
content (DMC) of vegetative organs, owing to assimilate abundance.
• Fruit production (dry weight) was affected by C the most in sweet pepper,
owing to increased C 0 2 assimilation and increased DM allocation to fruits athigh C.
• Cucumber showed the largest increase in fresh weight per unit C 0 2 ,explainable by a low fruit DMC.
• Fruit quality was not influenced by C, which was in accordance with theliterature.
The observed effects of C on fruit production were compared with theC0 2 -rule (seeabove),which wasderived from photosynthesis measurements. In
all crops, the observed effect was larger than the expected effect, based on thisC0 2 -rule. This was ascribed mainly to favourable light conditions in the
production experiments.
Intermittent C 0 2 supply (ICS) was tested, which was proposed in theliterature asa method to maintain a high C 0 2 useefficiency. In cucumber (expt2) two continuous C 0 2 concentrations and two ICStreatments were comparedin duplicate. ICS reduced the C 0 2 use considerably, but reduced the incrementin production about proportionally. In sweet pepper, three continuous levels,
two ICS regimes and a control were compared in duplicate. The results withrespectto setting andyield were not better at ICSthan atcontinuous C 0 2 levels,
if related to average, measured C.
Conclusions• Partial stomata closure hardly hasaneffect on leaftemperature nor any direct
effect on fruit production. A possible indirect effect of reduced conductance inthe long term is reduced nutrient contents in the crop. This may play a role incertain features,for example leaftip chlorosis ineggplant (associatedwith boron
deficiency) and short leaves in tomato (explained by local calcium deficiency).
• No endogenous 'midday depression' (dip or decline in photosynthesis andtranspiration), was observed in the experiments, under the condition that thecrop was well supplied with water and capable of adequate water uptake.
• High C generally increased the light utilization (LUE), fruit set (except intomato),allocation ofdry mattertofruits,dry mattercontent ofvegetative organs
and considerably increased fruit production. High C generally reduced SLA.
• Many features were explicable by considering the effect of C on thesink/source ratio. High C basically increases the source, but it may indirectly

191

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EM. Nederhoff

Effectsof C02

increase the sink strength as well (by better fruit set in sweet pepper andformation of more new shoots in cucumber).
• In the C0 2 -rule [ X = (1000/C)2 * 1.5, with X in % per 100 umol mol"1 andC in umol mol"1] the multiplication factor (1.5) may be adjusted to theconditions (in particular the average light level): upwards to about 1.8 in caseof favourable (light) conditions, or downwards to about 1.2 under poor (light)
conditions.TheC0 2 -rule agreedreasonablywell with theC0 2 -curve,which wasa generalized description of the effect of C on production.
• Intermittent C 0 2 supply (ICS) under standard ventilation could accomplish
only a limited increase in average C, and hence a limited increase inproduction. No physiological advantages (nor disadvantages) of ICS wereobserved.

Samenvatting

193

Samenvatting
Telen onder glas biedt de mogelijkheid maximaal te profiteren van het
stimulerende effekt van verhoogde C0 2 -concentratie van de lucht (C) op
plantengroei. Inde glastuinbouw wordt op grote schaal C0 2 -dosering toegepast
om de produktie te verhogen. In hoofdstuk 1van deze dissertatie wordt kort degeschiedenis van C0 2 -dosering in kassen belicht en gangbare methoden voor
dosering beschreven. Het effekt van C 0 2 op produktie van kasgewassen wordt
weergegeven door middel van een C0 2 -curve, gebaseerd op literatuurgegevens.
Het belangrijkste effekt van C0 2 -dosering is verhoging van de netto
fotosynthese snelheid. Andere mogelijke effekten zijn beïnvloeding van bloei,
vruchtzetting, droge stof verdeling naar de vruchten en droge stof gehalte vande vruchten. Ook kan C0 2 -dosering nadelige neveneffekten oproepen.
Doelstelling vandit proefschrift ishetanalyserenen kwantificeren vande hoofden neveneffekten van C in het bereik van 200 tot 1100 umol mol"1 op groei en
produktievandegewassentomaat(Lycopersicon esculentum Mill.), komkommer(Cucumis sativus L), paprika (Capsicum annuum L.) en aubergine (Solanum
melongena L.) in kassen. Alle experimenten werden uitgevoerd met volgroeide
gewassen in semi-praktijk kassen, onder normale teeltcondities.
Fotosynthese
Hoofdstuk 2 is gericht op onderzoek naar het effekt van C op de netto
C 0 2 assimilatie (of fotosynthese, P) van het gewas. Speciale doelstellingen
hierbij zijn het afleiden van een vuistregel om globaal het effekt van C op Pte
kunnen schatten,en het testen van een model,geschikt voor klimaatregeling en
beslissingsondersteunende systemen. In zes experimenten werden in meerdere
afdelingen metingen verricht. Degebruikte methode berust opeen nauwkeurige
schatting van de C0 2 -balans van de kas. Daarbij werd gebruik gemaakt van
lachgas (N 2 0) als tracergas om on-line de ventilatiesnelheid te bepalen. De
verkregen fotosynthesedata bevatten eenonnauwkeurigheid van ongeveer 10%,afgezien van grote relatieve fouten die onder bepaalde omstandigheden
optreden (in ca. 5% van de data).
Uit de metingen is een set van regressievergelijkingen afgeleid, die P
relateren aan PAR, C en LAI. Hiermee kon 83 tot 9 1 % van de variantie
verklaard worden. De belangrijkste gewasfotosynthesekarakteristieken die met

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E.M. Nederhoff Effects of C02

deze gefitte regressievergelijken werden berekend, waren redelijk inovereenstemming met data uit de literatuur of konden goed verklaard worden
door de omstandigheden.
Een vuistregel voor C 0 2 effekten is afgeleid met behulp van deregressievergelijkingen. DezeC0 2 -regel, die luidt X= (1000/C)2 * 1.5, berekent
bij benadering het relatieve effekt op de gewasfotosynthese van een verhoging
van 100 umol mol"1 bij een zekere CO z -concentratie C (X in % per 100
umol mol"1, and C in umol mol"1).
Twee modellen voor gewasfotosynthese (Acock et al., 1978 en vanThornley, 1976) zijn onderzocht door ze te vergelijken met de experimenteel
bepaalde fotosynthese gegevens. De (enigszins aangepaste) modellen voldeden
redelijk, maar vooral het Thornley model berekende het effekt van C op P niet
adekwaat. Defotosynthesemetingenwerdenookgeanalyseerdvoor het optreden
vaneentijdsafhankelijk variatie in P,onafhankelijk vandeomstandigheden (b.v.
eenzogenaamde 'midday-depression'). Erwerden geen aanwijzingen gevonden
voor het bestaan van een endogene depressie of daling in Pgedurende de dag.
Transpiratie
Het effekt van C op geleidbaarheid (g)van blad (of van stomata) en op
desnelheid van verdamping door het gewas (E) zijn onderzocht in hoofdstuk 3.
In paprika, tomaat en komkommer werden metingen gedaan in verschillende
kascompartimenten, waar gelijke C0 2 -concentraties werden aangehouden.
Alleen op meetdagen werd het nivo verschillend ingesteld. Metingen werden
verricht gedurende verscheidene dagen in meerdere kasafdelingen.
Geleidbaarheid werd gemeten met een steady-state diffusie porometer.
De metingen werden geanalyseerd met multiple regressie. De gefittevergelijkingen beschrijven het effekt van PAR, VPD-blad-lucht, C en optioneel
bladtemperatuur opg.De analysetoonde aandat per 100 umol mol"1 verhoging
vanC(in hetbereik 300tot 1100umol mol'1)ggereduceerd werd met ongeveer
3 à4 % inpaprika,tomaat en komkommer en met circa 11% in aubergine. Deze
percentages gelden bij ieder nivo van C, VPD en PAR, mits VPD en PAR
constant blijven. Bij aubergine werd g gemeten in twee kasafdelingen, een met
constant hoog en een met altijd laag C. Het gedrag van de stomata vertoonde
geen aanpassing aan C waarbij het gewas opgroeide.
Partiëlesluitingvanstomataveroorzaakt eendalingvande verdamping,die vervolgens de luchtvochtigheid verlaagt (in de grenslaag en in de kaslucht)
en mogelijk de bladtemperatuur enigszins verhoogt. Dit heeft tot gevolg dat de
VPD-blad-lucht merkbaar toeneemt, wat het effekt van verhoogd C op g

Samenvatting

195

versterkt en het effekt van C op f tegenwerkt. Deze zogenaamde hydrologische
en thermische feedback effekten werden in de waarnemingen opgenomen.
Gewasverdamping, gemeten met drie weegschaal-lysimeters perkasafdeling, was sterk gecorreleerd met straling. Het effekt van C op E werd
bestudeerd door gebruik te maken van de genoemde regressievergelijkingenvoor g, in combinatie met het Penman-Monteith model voor E. Berekeningen
met deze combinatie, waarbij gemeten klimaatomstandigheden als
invoergegevens dienden, bleken redelijk overeen te komen met de metingen.
De relatie tussen g en f werd tot uitdrukking gebracht met een
zogenaamde koppelingsfaktor, /("(relatieve verandering in berekende f gedeeld
door relatieve verandering in berekende g). Volgens berekeningen was deze K
meestal lager dan 0.2, behalve bij lage straling. Dit betekent dat afname inverdamping als gevolg van (gematigde) C0 2 -dosering gering is en meestal
verwaarloosbaar, behalve bij weinig licht. Bij aubergine kan het effekt echtersterker zijn, vanwege de sterkere stomataire gevoeligheid voor C, zo werd
bijvoorbeeld 15% reduktie vastgesteld over een periode in het voorjaar.
Erwerd geen tijdsafhankelijke variatie ('midday depression') gevonden
in de metingen (evenmin als indefotosynthesemetingen). Ook werd geen effekt
van C op de gemiddelde bladtemperatuur vastgesteld.
Groei en produktieHet effekt van C op groei en produktie werd geanalyseerd door deonderliggende processen te bestuderen in vijf experimenten (hoofdstuk 4).
Sommige aspekten werden slechts in een gewas bekeken, waarvan bekend was
dat het duidelijk reageert in dit opzicht.
Ineen herfstteelt van komkommer werd het effekt van C op vegetatieveengeneratieveparametersgekwantificeerd.TweeC0 2 -concentraties(364en 620
pmol mol"1 gemiddeld) werden aangelegd in drievoud, multifactorieel
gecombineerd mét twee vruchtdunningsbehandelingen (ongedund en met
verwijdering van 2/3 van de vruchtbeginselen). Hoog C stimuleerde devegetatieve groei alleen in de eerste weken. Daarna werd vooral devruchtproduktie gestimuleerd. De droge stof verdeling naar de vruchten was
hoger bij hoog C dan bij laag C. DMC (droge stof gehalte) van de vegetatievedelen en SLA (specific leaf area) werden niet door C beïnvloed in dit
experiment met komkommer.
Bij paprika was het aantal geoogste vruchten 46% hoger onder hoog C(450umöl mol"1)vergeleken met laagC(ongeveer 300 umol mol' 1 ),waarbij het
gemiddeld vruchtgewicht ongeveer gelijk was. Devegetatieve groei was minder
bij hoogC dan bij laagC. Dit houdt in dat de relatieve verdeling van biomassa

196

E.M. Nederhoff

Effectsof C02

naar de vruchten sterk was toegenomen door hoog C, tengevolge van een
sterkere sink-werking door de vruchten (bij hoogCwaren meer vruchten gezet).
DMC van de bladeren was hoger en SLA was lager bij hoog C in paprika.
Tomaat heeft in de zomer vaak te lijden van bepaalde morfologische
aanpassingsverschijnselen ('kort blad' of 'short leaves syndrome', afgekort SLS),
vooral gekenmerkt door sterk gereduceerde SLA. Als werkhypothese werd
gesteld dat SLSveroorzaakt wordt door een overmaat van assimilaten, relatief
ten opzichte van de sink capaciteit (dus lagesink/sourceverhouding ofwel sinklimitering). In twaalf kascompartimenten werd de sink/source verhouding
gevarieerd door twee C0 2 -concentraties aan te houden (350 en 550
umol mol"1) en dit te combineren met twee plantdichtheden en driesnoeibehandelingen. C0 2 -dosering en ruimere plantafstand verhevigden het
optreden van kort blad. In gewassen met geringe mate van SLS, kon C 0 2 doseringdevruchtproduktie behoorlijk verhogen,terwijl ingewassen met ernstig
kort blad, C 0 2 geen statistisch betrouwbaar effekt had op de produktie.
Ter verklaring van kort blad in tomaat wordt een mechanisme
voorgesteld, gebaseerd op calcium gebrek, dat kan ontstaan door twee
processen. Ten eerste verhoogt C0 2 -dosering de beschikbaarheid van
assimilaten (source sterkte), wat inhoudt dat er een grotere floeemstroom desinks bereikt. Dit gaat ten koste van de calcium-bevattende xyleemstroom. Ten
tweede wordt door hoog C de verdamping wat verminderd, zodat het transport
van calcium afneemt. Dit kan lokaal het calcium gehalte verminderen, wellicht(volgens de literatuur) met name in de apex. Het is bekend dat een laagcalciumgehalte indeapextot gevolg heeft dat nieuw gevormde bladeren kleiner
blijven. De combinatie van klein blad (door lokaal calcium gebrek) en dik blad(door opslag van de overmatige assimilaten) manifesteert zich als SLS.
Omdat de stomataire reaktie op Cgevoeliger bleek tezijn bij aubergine
dan bij de andere onderzochte gewassen, was aubergine bij uitstek geschikt
voor onderzoek aan afwijkingen inverband met voeding.Aubergine vertoont in
het voorjaar vaak bladpuntvergeling (leaf tip chlorosis, LTC),vooral onder hoog
C 0 2 . In een experiment werd het effekt onderzocht van C op LTC,
boriumgehalte van het blad en vruchtproduktie bij aubergine. Twee nivo's van
C 0 2 (413 en 663 umol mol"1) werden in duplo aangelegd. De resultaten
ondersteunden de hypothese dat LTC veroorzaakt wordt door een laagboriumgehalte in jonge, snelgroeiende bladeren. LTC en boriumtekort waren
ernstiger bij hoog dan bij laag C. De vruchtproduktie was echter belangrijk
hoger (24%) bij hoog dan bij laag C, ondanks LTC. Dit is verklaarbaar, omdat
dit gewas een hoge LAI had (ongeveer 5), zodat enig verlies van aktief bladnauwelijks de gewasfotosynthese kon beïnvloeden.

Samenvatting

197

Analysevandevelegroei-en produktiegegevensbrachten onder anderede volgende zaken aan het licht:• De lichtbenuttingsefficientie (LUE) was 10 tot 15% hoger per 100 umol mol"1
stijging in C.
• Vruchtzetting van paprika werd sterk gestimuleerd door verhoogd C.
• Verdeling van biomassa (droge stof) naar de vruchten was hoger onder hoog
C in paprika en komkommer, wat verklaard werd door verhoogde sink-sterkte.
• Behalve in komkommer, zorgde een verhoging in C met 150 tot 250
umol mol"1 voor een verlaging van de SLA met 15 tot 20% en een kleine
verhoging van het DMC van de vegetatieve organen, tengevolge van
assimilatenoverschot.
• Vrucht produktie (droge stof) werd het sterkst beïnvloed door C in paprika,
ten gevolge van een verhoogd C 0 2 assimilatie en verhoogde droge stofverdeling naar de vruchten bij hoog C.
• Komkommer vertoonde de sterkste toename in vers gewicht produktie per
eenheid C 0 2 , te verklaren door een laag DMC van de vruchten.
• Vruchtkwaliteit werd niet beïnvloed door C, wat overeenkomt met deliteratuur.
• In alle gewassen was het waargenomen effekt van C op produktie groter dan
het effekt berekend met de C0 2 -regel (zie boven). Dit kon worden
toegeschreven aan betere lichtomstandigheden in de produktie-experimenten.
• Intermitterend C 0 2 doseren (ICS) werd getest onder normale ventilatie. In
komkommer verlaagde ICS het verbruik van C 0 2 , maar verkleinde het gunstige
effekt op de produktie in ongeveer gelijke mate. Bij paprika bleken zetting en
produktie niet beter bij ICS dan bij een constant C0 2 -nivo, gerelateerd aan
gemiddelde C.

Konklusies• Partiële sluiting van stomata heeft nauwelijks effekt op bladtemperatuur engeen direkt effekt op produktie. Op de lange termijn heeft hoog C mogelijk een
indirekte invloed in de vorm van verlaagde concentratie van nutriënten in het
gewas. Dit kan leiden tot bijvoorbeeld bladpuntvergeling in aubergine (doorboriumgebrek) en kort blad in tomaat (samenhangend met calcium gebrek).
• In de metingen werden geen aanwijzingen gevonden voor een endogene'midday depression' (dipofdaling infotosynthese enverdamping),althans onderde voorwaarden van goede watervoorziening en wateropnamecapaciteit.
• C0 2 -dosering verhoogde meestal de lichtbenutting (LUE), vruchtzetting(behalve in tomaat), droge stof verdeling naar de vruchten, droge stof gehalte
van de vegetatieve delen en de produktie, en verlaagde de SLA.

198

E.M. Nederhoff Effects ofC02• Veel verschijnselen konden verklaard worden door een effekt van C op de
sink/source verhouding: hoog C verhoogt de source, maar kan indirect ook desink versterken,bijvoorbeeld door beterezetting in paprika en meer scheutgroei
in komkommer.
• De C0 2 -regel [X = (1000/C)2 * 1.5, met X het relatieve effekt van C 0 2 in %per 100 umol mol"1, and C in umol mol"1], kan aangepast worden aan deomstandigheden, met name het lichtnivo. Devermenigvuldigingsfaktor (1.5) zal
bij gunstige (licht) omstandigheden ongeveer 1.8bedragen en bij minder goede(licht) omstandigheden ongeveer 1.2. De C0 2 -regel was redelijk inovereenstemming met de C0 2 -curve op basis van literatuurgegevens.
• Intermitterend C 0 2 doseren (ICS) kon onder normale ventilatie
omstandigheden het gemiddelde C0 2 -nivo slechts beperkt verhogen, en daardoor de produktie beperkt stimuleren. Er werden geen bepaalde fysiologischevoor- of nadelen gekonstateerd.

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Curriculum vitae
Elly(Elisabeth Maria) Nederhoffwerd geboren in Gouda op 20 oktober 1956.
Na de lagere school doorliep zij de ß-richting van het Coornhert Gymnasium in
Gouda. Zij raakte bekend met de glastuinbouw via vakantie- en zaterdagwerk.
In 1975 begon zij aan de toenmalige Landbouw Hogeschool in Wageningen en
koos de plantkundige oriëntatie. Zij onderbrak de studie voor bestuurswerk bij
een studentenvereniging en behaaldevervolgens in 1979 het kandidaatsdiploma.
Voor stagewerkte ze vier maanden bij 'Besor Experimental Station' in Israël aan
fotosynthesemetingen in kassen en drie maanden bij 'Soltuna' op Curaçao aan
diverse teeltexperimenten. Haar afstudeervakken waren tuinbouwplantenteelt,
plantenfysiologie en meet- & regeltechniek. Voor dit laatste vak deed zij viermaanden experimentele metingen in kassen van het Proefstation in Naaldwijk.
In 1982 behaalde zij het Wageningse ingenieursdiploma in de studierichting
Tuinbouwplantenteelt.
Na het afstuderen werkte ze drie jaar in tijdelijk dienstverband in het kader
van onderzoek naar energiebesparing bij de sektie Kasklimaat van de afdeling
Teelten Kasklimaat van het Proefstationvoor Tuinbouw onder Glas in Naaldwijk.
Naderhand werd de aanstelling omgezet vantijdelijk naar permanent en in 1988
van full-time naar half-time. Zij werkte onder meer aan ventilatie, licht,
assimilatie belichting, fotosynthese, C 0 2 en luchtverontreinigingseffekten op
gewassenen maaktedeel uit vandewerkgroep 'kasklimaatbesturing van dejarennegentig'. In de periode 1990-1994 heeft zij zich toelegd op het onderwerp C 0 2
en hierover een proefschrift geschreven.