THE POTENTIAL ROLE OF HIGH PHOTOSYNTHETIC CAPACITY IN PEST
RESISTANCE MECHANISMS IN Fragaria chiloensis
By
ALEXIS R. VEGA
A dissertation submitted in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY IN HORTICULTURE
WASHINGTON STATE UNIVERSITY Department of Horticulture and Landscape Architecture
MAY 2005 ii
To the Faculty of Washington State University:
The members of the Committee appointed to examine the thesis of ALEXIS R. VEGA find it satisfactory and recommend that it be accepted.
______Chair
______
______
iii
ACKNOWLEDGMENTS
One of the most powerful factors in which science is based is people interconnections, in many different ways, directly, through discussion, teaching and even dreaming awake, or indirectly, through formal written communications along the time vector, producing a cumulative flux of expertise that goes beyond the grasp and life of any science worker. This flux sustains the exponential character of knowledge generation, a remarkable human capacity that is, in turn, the base for innovation, for make improvements even over the better, over and over again.
A Ph.D. dissertation is part of that web of interconnections, both in it generation and consequences, and because of that, I would like to acknowledge the support of the members of my original committee (1994-2000), Drs. J. Scott Cameron (Chair), Patrick P. Moore, Lynell K.
Tanigoshi and Stephen F. Klauer, with special mention to my former adviser, Dr. Cameron, who allow me to explore concepts and facts following my own holistic approach to reach the goals of my project. Also, I am grateful to Dr. Moore for his patience guiding me in the rigorousness and proper English language writings. I would also like to thank my new committee, integrated by
Drs. John K. Fellman, (Chair), Kathleen Willemsen and Larry Hiller, which kindly accept the responsibility to guide a graduate student after several years of leave status, allowing me to finish this adventure. Special thanks are devoted to Dr. Fellman, who was a key person to solve many long-distance logistic problems and that endured many delays created by my parallel academic work for the University of Chile, 6.000 miles away from the WSU.
iv
I would also like to thank Dr. Chuhe Chen for his assistance in the photosynthesis and spectrum analysis area, as well, to the entire crew at the Washington State University-Vancouver Research and Extension Unit. Also, I thank to many students from Clark College (Vancouver, WA), that in a year and a half gave me an important help in tedious and lengthy laboratory protocols through their work-studies credits, with special thanks to Jamie McCall, for her invaluable assistance, even after finishing her work-studies’ assignment.
Finally, I would like to thank many people that directly or indirectly helped me in my project or encouraged me to continue in spite of many extra-academic problems that plagued this work, among others, my fellow faculty friends at the University of Chile, and the wholehearted support and love of my family.
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THE POTENTIAL ROLE OF HIGH PHOTOSYNTHETIC CAPACITY IN PEST
RESISTANCE MECHANISMS IN Fragaria chiloensis
Abstract
by Alexis R. Vega, Ph. D. Washington State University May 2005
Chair: John K. Fellman
Fragaria chiloensis (L.) Duch., a strawberry native from the Pacific coast of North and South
America was one of the parent species, along with F. virginiana from North America, of the cultivated strawberry (F. x ananassa), which came from a single cross between both parents.
This created a rather narrow genetic variation on the descendants of the original cross, allowing to some researcher to propose an expansion of the genetic base of F. x ananassa with native germplasm, which show several useful agronomic traits, among others, pest resistance and high photosynthetic capacity. A research was carried out to test the hypothesis that pest resistance mechanisms in the Fragaria genus are more likely to be present in genotypes with high photosynthetic capacity, as their require extra energy to be operative. It was confirmed previous findings communicated in the literature that the Fragaria genus has a high phenotypic variability in both traits under study if a wide range of genotypes are tested. Such variability follows a continuous distribution along the observed response ranges, suggesting polygene systems. No strong association between photosynthetic capacity and pest resistance variables was found, however, genotypes placed at the extreme of the observed response ranges, did show consistency
vi
with the hypothesis. Also, it was determined that the photosynthetic capacity did not segregate under the experimental conditions, however, it was demonstrated that most of the variability observed in photosynthetic capacity in Fragaria can be linked to the leaf residual conductivity to the CO2 (gr). Some pest resistance variables do segregate in the F1 generation from a single cross
(total leaf phenolics concentration, total leaf protein and trichome density). Some pest resistance
mechanisms appear to be elicited by the feeding upon plants by the arthropod Otiorhynchus
sulcatus (L.) (Black vine weevil), some of them in a systemic fashion (phenolics). More studies
are required to determine where the pest resistance mechanisms reside in the Fragaria genus.
vii
TABLE OF CONTENT
Page
ACKNOWLEDGMENTS ...... iii
ABSTRACT ...... v
LIST OF TABLES ...... … x
LIST OF FIGURES ...... xiv
DEDICATION ...... xvi
1. INTRODUCTION ...... 1
2. LITERATURE REVIEW ...... 3
2.1. PHOTOSYNTHESIS – BREEDING ...... 3
2.2. PEST RESISTANCE – BREEDING ...... 7
3. MATERIAL AND METHODS ...... … 10
3.1. Physiological characterization of selected Fragaria genotypes ranging in pest resistance
and photosynthetic capacity ...... 10
3.2. Physiological characterization of two Fragaria genotypes, one pest resistant and the other
pest susceptible, in response to black vine weevil fed upon foliage ...... 19
3.3. Physiological characterization of progeny and parents of a cross between pest susceptible
and pest resistant Fragaria genotypes ...... 21
4. RESULT AND DISCUSION ...... 23
4.1. GAS EXCHANGE ...... 23
4.1.1. Selected pest resistant and pest susceptible Fragaria genotypes ...... 23
4.1.2. Weevil-Plant interaction ...... 35 .
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Page
4.1.3. Observation on progeny ...... 35
4.2. FLUORESCENCE ...... 45
4.2.1. Selected pest resistant and pest susceptible Fragaria genotypes ...... … 45
4.2.2. Weevil-Plant interaction ...... … 51
4.2.3. Observations on progeny ...... … 53
4.3. LEAVES FOURTH DERIVATIVE CHLOROPHYLL'S ABSORBANCE
SPECTRUM ...... … 58
4.3.1. Selected pest resistant and pest susceptible Fragaria genotypes ...... … 58
4.3.2. Weevil-Plant interaction ...... … 62
4.3.3. Observations on progeny ...... … 67
4.4. CHLOROPHYLL CONTENT ...... … 74
4.4.1. Selected pest resistant and pest susceptible Fragaria genotypes ...... … 74
4.4.2. Plant-weevil interaction ...... …. 81
4.4.3. Observations on progeny ...... … 85
4.5. LEAF PROTEIN ...... 89
4.5.1. Selected pest resistant and pest susceptible Fragaria genotypes ...... 89
4.5.2. Weevil-Plant interaction ...... …...... 94
4.5.3. Observation on progeny ...... …...... 97
4.6. CARBON ISOTOPE DISCRIMINATION ...... …...... 100
4.6.1. Selected pest resistant and pest susceptible Fragaria genotypes ...... …...... 100
4.7. BIOMASS PARTITIONING ...... …...... 108
4.7.1. Selected pest resistant and pest susceptible Fragaria genotypes ...... 108
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Page
4.7.2. Observation on progeny ...... 117
4.8. LEAF TOTAL PHENOLS CONTENT ...... …...... 124
4.8.1. Selected pest resistant and pest susceptible Fragaria genotypes ...... 124
4.8.2. Weevil-Plant interaction ...... 125
4.8.3. Observation on progeny ...... 128
4.9. TRICHOME DENSITY .………...... ….. 128
4.9-1. Selected pest resistant and pest susceptible Fragaria genotypes ...... ….. 129
4.9-2. Observation on progeny ...... …. 132
4.9. LEAF AREA EATEN ...... … 133
5. CONCLUSIONS ...... … 137
6. LITERATURE CITED ...... … 139
x
LIST OF TABLES
Page
Table 3.1. Main characteristics of Fragaria genotypes selected from the
literature for their physiological characterization...... …………. 13
Table 4.1-1. Steady state instantaneous CO2 assimilation rates, intercellular
CO2, and intercellular to ambient CO2 ratio of some greenhouse-
grown Fragaria genotypes...... ………………….. 24
Table 4.1-2. Correlation coefficients (Pearson) between some photosynthetic
parameters for 26 Fragaria genotypes...... ………….. 29
Table 4.1-3. Steady state instantaneous residual CO2 and water conductivities,
water vapor evaporation and water use efficiency of some
greenhouse-grown Fragaria genotypes...... ………... 32
Table 4.1-4. F-number for some photosynthetic variables using the Stepwise
linear multiple regression variable selection procedure for the
photosynthetic CO2 assimilation (Ala)...... ……….. 34
Table 4.1-5. Steady state instantaneous gas exchange variables for Totem
(Fragaria x ananassa) and ZB-15 (Fragaria chiloensis) genotypes
being fed on by black vine weevil (Otiorhynchus sulcatus)...... ………. 36
Table 4.1-6. Steady state instantaneous gas exchange variables of 45
greenhouse-grown F1 Fragaria genotypes (from a single cross),
plus their parents, Totem (F. x ananassa) and ZB-15 (F.
chiloensis)...... ……………… 41
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Page
Table 4.1-7. Steady state instantaneous gas exchange variables of 45 greenhouse-
grown F1 Fragaria genotypes (from a single cross), plus
their parents, Totem (F. x ananassa) and ZB-15 (F. chiloensis). ..…………. 43
Table 4.2-1. Chlorophyll fluorescence parameters of some greenhouse-grown
Fragaria genotypes...... ………… 46
Table 4.2-2. Pearson correlation coefficients between fluorescence and
photosynthetic parameters for selected pest resistance and pest
susceptible Fragaria genotypes...... …...... ……. ….. 50
Table 4.2-3. Chlorophyll fluorescence variables for three levels of Black vine
weevil (Otiorhynchus sulcatus) impact on leaves of two Fragaria
genotypes (‘Totem’ [F. x ananassa] and ZB-15 [F. chiloensis]). ...……. ….. 52
Table 4.2-4. Chlorophyll fluorescence parameters for 45 greenhouse-grown F1
Fragaria genotypes (from a single cross), plus their parents, ‘Totem’
(F. x ananassa) and ZB-15 (F. chiloensis)...... ….……. ….. 55
Table 4.4-1. Leaf chlorophyll content of selected, according to their pest resistance
level, Fragaria genotypes...... ….…… ….. 76
Table 4.4-2. Correlation coefficients (Pearson) between chlorophyll content and
photosynthetic parameters for selected, according to their pest
resistance level, Fragaria genotypes...... …….…….…. 79
Table 4.4-3. Leaf chlorophyll content of ‘Totem’ (Fragaria x ananassa) and ZB-15
(Fragaria chiloensis) genotypes fed on by black vine weevil
(Otiorhynchus sulcatus)...... …...... …….……….. 82
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Page
Table 4.4-4. Pearson correlation coefficients between chlorophyll content and
some photosynthetic and fluorescence parameters for ‘Totem’
(Fragaria x ananassa) and ZB-15 (Fragaria chiloensis) leaves being
fed on by black vine weevil (Otiorhynchus sulcatus)...... …..……….. 84
Table 4.4-5. Chlorophyll content of leaves of 45 greenhouse-grown F1 Fragaria
genotypes (from a single cross), plus their parents, Totem (F. x
ananassa) and ZB-15 (F. chiloensis)...... ……………. 86
Table 4.5-1. Leaf total soluble protein, Ribulose 1,5-biphosphate
carboxylase/oxygenase (Rubisco) content and percentage of Rubisco
of total soluble protein content of selected, according to their pest
resistance level, Fragaria genotypes...... …………… 91
Table 4.5-2. Leaf Total soluble protein, Ribulose 1,5-biphosphate
carboxylase/oxygenase (Rubisco) and percentage of Rubisco of total
soluble protein content for 45 greenhouse-grown F1 Fragaria
genotypes (from a single cross), plus their parents, Totem (F. x
ananassa) and ZB-15 (F. chiloensis)...... …………… 99
Table 4.7-1. Biomass partitioning variables, dry weight basis, of some greenhouse-
grown Fragaria genotypes...... ………….. 111
Table 4.7-2. Pearson’s correlation coefficient between dry weight biomass
partitioning and other physiological variables in pooled data from 26
strawberry genotypes...... …………. 113
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Page
Table 4.7-3. Biomass partitioning variables, dry weight basis, of greenhouse-grown
F1 Fragaria genotypes (from a single cross), plus their parents, Totem
(F. x ananassa) and ZB-15 (F. chiloensis)...... …. 121
Table 4.8-1. Leaf total phenol content, fresh and dry weight basis, of greenhouse-grown F1
Fragaria genotypes (from a single cross), plus their parents, Totem (F. x
ananassa) and ZB-15 (F. chiloensis)...... … 130
xiv
LIST OF FIGURES
Page
Figure 4.3-1. Relative frequency of pooled fourth derivative peak maxima of some
greenhouse-grown Fragaria genotypes...... ……….. 69
Figure 4.3-2. Relative frequency of fourth derivative peak maxima for ‘Totem’ (F. x
ananassa) and ZB-15 (F. chiloensis) genotypes...... …………. 70
Figure 4.3-3. Relative frequency of fourth derivative peak maxima for ‘Totem’ (F. x
ananassa) being fed on by black vine weevil (O. sulcatus)...... ….……….. 71
Figure 4.3-4. Relative frequency fourth derivative peak maxima for ZB-15 (F. chiloensis)
being fed on by black vine weevil (O. sulcatus)...... …...... …. 72
Figure 4.3-5. Relative frequency of fourth derivative peak maxima for F1 genotypes, plus
parents, and 25 selected genotypes according to their pest resistance level.…… 73
Figure 4.5-1. Total soluble leaf protein content of 'Totem' (Fragaria x ananassa) and ZB-
15 (F. chiloensis) genotypes being fed on by Black vine weevil
(Otiorhynchus sulcatus)...... …...... …...... 96
Figure 4.6-1. Carbon Isotope Discrimination (∆) in leaves tissue (dry matter) in 26
Fragaria genotypes, ranked from susceptible to resistant to several pests. ..…. 104
Figure 4.6-2. CO2 discrimination and Ci/Ca ratio relationship for some selected Fragaria
genotypes...... …...... …...... 106
Figure 4.6-3. Relationship between CO2 isotope discrimination and WUE for some
selected Fragaria genotypes...... 109
Figure 4.7-1. Relative partition of the components of the total biomass of selected Fragaria
greenhouse-grown genotypes...... 116
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Page
Figure 4.7-2. Shoot-Root relationship for some selected Fragaria genotypes...... …….... 118
Figure 4.7-3. a) Root system of 2F1 genotype, an advanced selection of crosses between F.
x ananassa and F. chiloensis with more third and fourth order rootlets than
cultivated varieties. b) Root system of plantlets of 'Fern' cultivar (F. x
ananassa)...... …….. 119
Figure 4.7-4. Root-Shoot relationship of 46 Fragaria F1 genotypes (identified by numbers)
and their parents 'Totem' (F. x ananassa) and ZB-15 (F. chiloensis). The
regression equation and fitted line is shown...... …… 123
Figure 4.8-1. Total phenols content (dry weight basis) in leaf tissues in 26 genotypes of
Fragaria, ranked from susceptible to resistant to several pests...... ……… 126
Figure 4.8-2. Leaf total phenols content on 'Totem' (Fragaria x ananassa) and ZB-15 (F.
chiloensis) strawberry genotypes being fed on by Black vine weevil
(Otiorhynchus sulcatus)...... …...... …...... …….. 127
Figure 4.9-1. Leaves trichome density of 26 genotypes of Fragaria, ranked from
susceptible to resistant to several pests. ………………..….…………………. 133
Figure 4.9-2. Leaves trichome density of greenhouse-grown F1 Fragaria genotypes
(from a single cross), plus their parents, Totem (F. x ananassa) and
ZB-15 (F. chiloensis. ……………………………………………….………… 135
Figure 4.10-1. Total Leaf area eaten on two strawberry genotypes fed upon by Black
vine weevil (Otiorhynchus sulcatus). ……………………………….…….. 136
xvi
Dedication
This dissertation is dedicated to my family. They endure a long time of absence and economic limitations throughout this project, especially to "Osita", who gave me so much love and support
to do something that restricted very much my time devoted to her.
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1. INTRODUCTION
The cultivated strawberry (Fragaria x ananassa Duch., Rosaceae) is a fruit crop with which plant breeders have worked in order to obtain locally-adapted varieties. This goal has been achieved due to the genetic diversity and broad range of environmental adaptation of Fragaria, and strawberry has become one of the most widely distributed fruit crops in the world (Larson, 1994).
Primary genetic improvements have been related to yield, fruit quality, photoperiodic response, and pest and disease resistance (Scott et al., 1989).
The genus Fragaria has several species that produce edible fruits of different size, shape and quality, with varying vegetative and physiological characteristics (Staudt, 1989). By the early eighteenth century, the hybridization of F. virginiana Duch. (from North America) and F. chiloensis (L.) Duch. (from South America) occurred spontaneously near Brest, France, evolving the fertile hybrid F. x ananassa (Darrow, 1966). Since late in the 18th century, when systematic strawberry breeding began, many efforts have been undertaken to improve the plant's vegetative and reproductive response to specific environments (Hancock et al., 1996). Most breeding has been done with the parent species (octoploids) and their descendants, making F. x ananassa a highly heterozygous species (Larson, 1994). As a component of these programs, over the three past decades, breeders have been especially interested in using germplasm from centers or subcenters of origin of the parent species of the F. x ananassa hybrid (Bringhurst et al., 1977;
Cameron et al., 1991; Becerra et al., 2001). Evaluation of newly collected material has demonstrated the potential for traits such as salt tolerance, drought tolerance, disease resistance, low chilling requirement (Bringhurst et al., 1977), high photosynthetic capacity, greater water use efficiency (Cameron et al., 1991), and pest resistance (Doss et al., 1991; Shanks and Moore,
1995; Becerra et al., 2001). 2
The Washington State University Small Fruit Breeding Program at the Puyallup Research and
Extension Center has had a strong commitment to strawberry breeding for many years. In conjunction with the Small Fruit Entomology Program at the Vancouver Research and Extension
Unit, pioneering work in pest resistance has been done using genotypes of F. x ananassa, F. virginiana (from North America) and F. chiloensis (from North and South America).
As a component of the small fruit germplasm collection and evaluation activities of the WSU
Research and Extension Unit, Vancouver, WA, this Dissertation has the following objectives:
I) Investigate possible relationships between pest resistance and photosynthetic capacity in some
genotypes of F. x ananassa, F. virginiana and F. chiloensis.
II) Physiological characterization of two Fragaria genotypes, one pest resistant and the other
pest susceptible, in response to Black vine weevil fed upon foliage
III) Physiological characterization of progeny and parents of a cross between pest susceptible
and pest resistant Fragaria genotypes. 3
2. LITERATURE REVIEW
PHOTOSYNTHESIS - BREEDING
The cultivated strawberry (F. x ananassa) appears to have a relative photosynthetic capacity intermediate between F. virginiana (lower) and F. chiloensis (higher), its parental species
(Cameron and Hartley, 1990; Cameron et al., 1991; Larson, 1994). Reported CO2 assimilation rates for the parental species of the cultivated strawberry may reflect the photosynthetic photon flux, nutrient and water availability of the most common natural environments where they evolved (Jurik et al., 1979; Givnish, 1987).
F. virginiana has evolved in habitats reflecting different stages of vegetational succession, ranging from an open, herbaceous strata to sparse understories of mesic forests of the Eastern coast of North America, although, rarely found in mature forests (Jurik, 1983). While F. chiloensis is native to high light intensity environments such as beaches and mountainous regions
(Cameron et al., 1991; Larson, 1994); is also a successional pioneer species, colonizing habitats with a wide range of water, nutrient and light availability (Hancock and Bringhurst, 1979;
Cameron et al., 1991; Becerra et al., 2001). These characteristics and wide adaptability make F. chiloensis a very useful germplasm source for improvement of the cultivated strawberry
(Bringhurst et al., 1977; Cameron and Hartley, 1990; Cameron et al., 1991; Becerra et al., 2001).
In a survey of literature, Larson (1994) found ranges for the photosynthetic assimilation rate
-5 -5 -2 -1 -5 -5 -2 -1 (A) of 7x10 to 15x10 mol CO2 m s in F. virginiana and 15x10 to 30x10 mol CO2 m s in F. chiloensis. Specific values of response to increasing photosynthetic photon flux are influenced by genotype, leaf age, and leaf anatomy (Jurik et al., 1979) or environmental preconditioning, especially temperature and light intensity (Larson, 1994; Hall and Rao, 1999).
Regardless, it has become clear that there are consistent, relative physiological differences among 4 these three Fragaria species. Genotypes of F. chiloensis had higher rates of A as photon flux increased compared to several genotypes of F. x ananassa (Cameron and Hartley, 1990). F. chiloensis has also shown to have greater rates of A than F. virginiana (Larson, 1994).
The apparent high photosynthetic capacity of F. chiloensis as well as other interesting traits, need to be considered in the context of its native environments. The occurrence of a plant population in a certain habitat depends on two groups of factors (Gauhl, 1976): a) the prevailing climatic-edaphic conditions, and b) the physiological mechanisms which the plant has acquired during the course of evolution. The physiological and biochemical characteristics must necessarily be compatible with the habitat if the plant is to be successful in surviving there
(Gauhl, 1976). With reference to photosynthetic capacity, one needs to carefully consider the whole plant energy balance in order to determine if there may be such advantages in certain gene pools. It is important to know if higher photosynthetic capacity can allow a plant to redirect photosynthates to subsystems under stress as a survival strategy. An example of this is foliage under pest attack (Givnish, 1988). The concept of tradeoffs underlies the economics of gas exchange and the associated costs involving the uptake of water and nutrients, mechanical support and interactions with herbivores (Givnish, 1988; Chiarello et al., 1992; Larcher, 1995).
As the plant or plant species have success in colonizing or maintaining its presence in a specific plant community, there is expression of a fitness function or genetic plasticity, due both to differences in allelic expression across environments and to changes among loci that play an important role in determining the phenotype (Scheiner, 1993; Page and Holmes, 1998). Such plasticity means a direct cost to photosynthetic processes, but not only for the expression of the plastic trait, but rather, as a cost of maintaining the genetic and cellular machinery necessary to be plastic. Examples of this include the cost of maintaining regulatory genes and enzymes 5
(Scheiner, 1993), and the cost of repair mechanisms (Pearcy et al., 1987), thus, this cost is always present regardless of the environment in which the plants develop (Givnish, 1987; Scheiner,
1993).
The potential for artificial selection of a plastic trait that may be almost completely under the control of complex, hierarchical physiological processes (genetic physiological variability at population scale) (Mahon, 1983), which can be viewed from two opposing theoretical bases. One approach concentrates on the existence of significant genotypic variability in physiological characters, suggesting that there is opportunity for improving these characters through selection
(Mahon, 1983). But, as physiological processes are very sensitive to environmental conditions, care must be taken to select superior genotypes over a range of environments (Mahon, 1983).
With this precaution in mind, Mahon (1983) stated that there is no reason to believe that the improvement of physiological characters is limited by either genetic resources or the ability to exploit them using conventional breeding methods. With reference to the genus Fragaria, the
"day neutral" photoperiodic response, a complex hierarchical physiological process, has been successfully transferred to the cultivated strawberry from F. virginiana (L.) Duch. spp. glauca
Staudt (Bringhurst et al., 1989; Scott et al., 1989).
Conversely, Gifford et al. (1984), indicated that there have been long term efforts to improve yield by attempts to improve photosynthetic efficiency in breeding for various subsystems of a plant's photosynthetic processes. While these studies have included diffusional, biochemical, and photochemical approaches to improving photosynthesis, these approaches have not been successful, mainly due to the complexity of feedback relationships in the photosynthetic system.
This complexity results because yield is controlled by numerous polygenic, organismic and community traits that have considerable plasticity as a crop develops with multiple co-limiting 6 factors, both physiological and environmental. Under field conditions, it is difficult to obtain improvements of 20% or more in yield with only one controlling step modification, a difference that represents the minimum change for the practical improvement of an agronomic trait (Gifford et al., 1984). Over the history of genetic improvement of yield in field crops, partitioning of photosynthates has been the primary basis for improvement of yields, while total plant biomass remained relatively constant (Gifford et al., 1984).
An important consideration is that F. virginiana, F. chiloensis, and its hybrid F. x ananassa are octoploids (Staudt, 1989). This can impose some restrictions on recombinational variability, mainly because in polyploids a change in a single allele may have little effect on the plant as a whole due to the presence of a number of other similar alleles, and polysomic inheritance greatly reduces F2 variance in quantitative traits (Hancock and Bringhurst, 1979). On the other hand, these octoploids species, pose no restrictions to interspecific crosses, all being fully compatible and producing fertile hybrids (Bringhurst et al., 1977; Becerra et al. 2001). Additionally, some important traits of cultivated strawberries can be recovered after few backcrossing generations
(Bringhurst et al., 1977; Becerra et al., 2001).
From this discussion it can be concluded that screening for useful traits in native Fragaria germplasm requires an integrated approach. Instantaneous characterizations and/or studies focused on one aspect may not provide the same perspective as those focused on the whole plant, or whole communities, the final result of plant evolutionary responses to the environment
(Givnish, 1987, 1988; Mooney et al., 1987; Osmond, 1987; Pearcy, et al., 1987; Larcher, 1995;
Futuyma, 1998; Lambers et al., 1998).
7
PEST RESISTANCE - BREEDING
Crop damage caused by arthropods is a major economic factor in agriculture in tropical and temperate regions of the world, where Coleoptera, Homoptera and Acari are among those with the most significant impact on major crops (Gatehouse, 1991). These also reflect the primary pests of the strawberry in the Pacific Northwest region: weevils (Otiorhynchus sulcatus [L.] and
O. ovatus [F.]), with adults that feed on leaves and larvae which feed on roots (Shanks et al.,
1984), aphids (Chaetosiphon fragaefolii [Cockerell] and C. tomasii [Hille Ris Lambers]), that are phloem feeders (Shank, 1965; Shanks and Finnigan, 1972), and the two spotted spider mite
(Tetranychus urticae Koch), an epidermal and mesophyll feeder (Barritt and Shanks, 1980 a;
Shanks and Barritt, 1980).
There is extensive literature that demonstrates that some genotypes of F. chiloensis, both from
North and South America, and F. virginiana are more resistant to major pest of the cultivated strawberry in the Pacific Northwest (Shanks and Barritt, 1975, 1984; Crock and Shanks, 1982;
Shanks et al., 1984; Doss et al., 1987; Doss and Shanks, 1988), and that resistance can be transmitted in a segregating fashion to the F1 population when F. x ananassa is used as the other parent (Shanks and Barritt, 1975, 1980; Barritt and Shanks, 1980 b; Doss et al., 1991; Shanks and Moore, 1995; Becerra et al., 2001).
High-intensity agriculture, where major crops are grown in monoculture (including strawberry), has broken many natural ecosystems cycles of matter and energy, and has became a thermodynamically unstable system (Odum, 1980; Giampetro, 1994). This has lead to changes such as an increase in the phytophagous insect population, which in turn, has been addressed in the short-term with energy inputs, namely, pesticides, fertilizers, agricultural machinery, improved varieties, transport, etc. (Mitra and Bhatia, 1982; Gatehouse, 1991, Giampietro, 1994). 8
The use of pesticides is highly inefficient in terms of the quantity applied and the plant surface or organ that is protected. Pesticides also introduce strong environmental and health considerations, and can create intense selection pressure on insect populations, causing, at times, rather rapid resistance to such chemicals (Gatehouse, 1991). In addition, plant breeding done in the past, mainly oriented to improve yields, may have eliminated some inherent pest resistance traits
(Gatehouse, 1991).
In strawberry, while modern standards of yield and fruit quality were being achieved, there has been increasing interest in breeding for pest resistance (Bringhurst et al., 1977; Gatehouse, 1991;
Hancock et al., 1996). A pest resistant variety could have less problem with pest adaptation as occurs with pesticides, while becoming more efficient in terms of agroecosystem thermodynamics (closer to optimal ratio between the populations of herbivores and the crop plant populations and/or yield) (Mitra and Bhatia, 1982; Giampietro, 1994). This however does not eliminate damage to the crop or eradicate the pest organism (Angermeier and Karr, 1994).
The basis of plant resistance to insects is either physical and/or chemical (Gatehouse, 1991;
Larcher, 1995; Letourneau, 1997), and is essential for plant survival in nature (Mitra and Bhatia,
1982; Larcher, 1997; Letourneau, 1997). The physical mechanisms are barriers to insect attack such as trichomes, spines, sticky exudates, cuticular waxes and lignified epidermis, while chemical barriers are compounds (secondary metabolites) with actions such as preventing insects from recognizing plant tissue as a suitable food source and/or toxins and antimetabolites tissue
(Bazzaz et al., 1987; Gatehouse, 1991; Larcher, 1995; Letourneau, 1997). Examples of the latter include terpenoids, steroids, phenolics, flavonoids, tannins, alkaloids, nonprotein amino acids, and non-secondary metabolites such as proteins (Gatehouse, 1991; Larcher, 1995). 9
Two limitations to conventional pest resistance breeding are the availability of suitable sources of insect resistance genes, and a resistance based in a polygenic character, where transfer into commercial plants may be a difficult and lengthy process (Gatehouse, 1991). Sources of pest resistance are available in genus Fragaria (Doss et al., 1991; Shanks and Moore, 1995; Becerra et al., 2001).
Plant pest resistance mechanisms represent energy costs for construction and maintenance
(Mitra and Bhatia, 1982; Bazzaz et al., 1987; Larcher, 1995). The construction costs vary significantly according to the carbon:nitrogen ratio and mode of action, where C-based defensive compounds are prevalent under high light conditions, and those N-based under low light availability (Bazzaz et al., 1987). Plant survival and productivity depends upon diversion of its overall resources, while minimizing the construction and maintenance costs of pest-resistance mechanisms for normal growth and development (Mitra and Bhatia, 1982; Larcher, 1995).
Bazzaz et al. (1987), in a literature review demonstrated that high levels of defensive compounds are associated with resource limited environments, slow growth rates, evergreens, late successional habitats, and woodiness. The authors indicate that even though there is a high degree of variability in the allocation of defensive resources among plant species, the variation can also be substantial within a species. At the within species level, the allocation of resources to growth has highest priority, while allocation to defensive compounds increases at supraoptimal resource levels (Bazzaz et al., 1987).
In the genus Fragaria, between and within species screened for pest resistance, significant variability has been found, but levels of allocation to defensive compounds and identification of the mechanisms involved were not investigated (Shanks, 1965; Shanks and Finnigan, 1972;
Shanks and Barritt, 1980; Shanks et al., 1984; Doss et al., 1991; Shanks and Moore, 1995). 10
3. MATERIAL AND METHODS
3.1. Physiological characterization of selected Fragaria genotypes ranging in pest resistance and photosynthetic capacity. Research literature related to pest resistance of F. x ananassa, F. virginiana, and F. chiloensis, was reviewed. Part of the literature reviewed was related to a long term evaluation program of Fragaria germplasm maintained at the Washington State University
(WSU), Vancouver Research and Extension Unit, Vancouver, Washington, where was observed a significant variability in pest resistance between and within Fragaria species, however, an identification of the mechanisms involved were not investigated (Shanks and Finnigan, 1972;
Shanks and Barritt, 1980; Shanks et al., 1984; Doss et al., 1991; Shanks and Moore, 1995).
Based on a selection index applied to the research data, genotypes resistant and susceptible to
Strawberry aphid (Chaetosiphon fragaefolii [Cockerell]), Two spotted mite (Tetranychus urticae
Koch), and Black vine weevil (Otiorhynchus sulcatus [L.]) were selected for physiological characterization. In addition, genotypes previously characterized for photosynthetic capacity
(Foote, 1994) were included in this study, but these had not previously undergone pest resistance characterization.
Selection was done in two steps among genotypes which were characterized for pest resistance in the literature reviewed. Step 1: for each pest and each paper reviewed, using the numerical expression of the variables presented in the work, genotypes were selected in both resistant and susceptible extremes for each variable. Only genotypes presented as statistically different were selected. Step 2: to narrow the genotype number selected in Step 1, to this population of genotypes the selection index described below was applied.
Selection index: for each pest and paper reviewed with two or more pest resistance related numerical variables and with F. x ananassa cv. ‘Totem’ as a susceptible standard for the pest, a 11 geometrical mean was used (Steel and Torrie, 1980) in order to select two genotypes, one with the highest and the other with the lowest index values among the genotypes previously selected in
Step 1 for the same paper. The selection index follow the general expression:
n SI = a1 ∗ a2 ∗...an where, SI : Selection index
n : Total number of numeric variables considered for a given paper.
a1, a2,... an: Value of variables 1, 2, ... n expressed as a percentage of the value observed
for the standard susceptible genotype
Even though, for each type of pest, papers reviewed were not completely comparable with each other, and while the influence of year of the experiment or location could not be neutralized, some pest resistance trends were detected. For purposes of this research, genotypes that retained a relative level of pest resistance across studies were preferentially chosen, as well as those genotypes which appeared only once in the literature reviewed but demonstrated extreme index values of resistance or susceptibility. The selected genotypes are identified in Table 3.1.
All selected genotypes (27), were propagated in a greenhouse at the WSU Vancouver
Research and Extension Unit between May and August 1996. Each mother plant was allowed to produce 5-6 runners, and each runner maintained with its four basal nodes. Any further elongation above the fourth node was trimmed when its length was about 1-2 cm. Runner plantlets from nodes 2 to 4 were rooted in a substrate of vermiculite and peat moss under greenhouse conditions with natural photoperiod (46° North Latitude) and light intensity. Air temperature was maintained at ambient level with extractor fans.
The experiment was set up in late August 1996. Six uniform, four months old clonal plants of each genotype (replications) were selected from those propagated, and arranged in a complete 12 randomized block design. Plants were fertilized every two weeks with 230 ml of a solution with
60 ppm of 20:20:20 N:P:K plus micronutrients (Peters™). In early December 1996, plants were trimmed to synchronize leaf age and were left growing until mid-February 1997, when a normal canopy size was reached. Plants were growing actively under winter conditions, with a natural photosynthetic photon flux density (PPFD) ranging from 350 to 500 µmol m-2 s-1. Temperature was maintained at 20-25°C and photoperiod maintained at 16 hrs, both settings for promoting vegetative growth (Sudzuki, 1992; Larson, 1994). Physiological characterization of the genotypes was performed using methodologies described below.
Instantaneous gas exchange measurements. On February 10-18, 1997, exploratory gas exchange (and fluorescence) measurements were made to establish the daily period in which photosynthetic parameters were stable, as well to determine the light intensity necessary to reach a saturated photosynthetic photon flux density (PPFD, generated by a 1000 Watt high pressure sodium lamp) using a portable CO2 infrared analyzer (Model LCA-2 Analytical Development
Co., Hoddesdon, Herts, U.K.), operated as an open system and equipped with a Parkinson
-1 broadleaf chamber. Carbon dioxide concentration in the greenhouse was 400±13 µL L . CO2 depletion in the chamber was allow to stabilize (~1 minute at a flow of 0.5 L min-1) before measurements were taken. During measurements, air temperature at the cuvette was kept at an average of 24.1±2.3ºC. Based on that preliminary data, on February 19-21, 1997, definitive gas exchange measurements were made between 10:30 and 17:00 h under a saturating PPFD of Table 3.1. Main characteristics of Fragaria genotypes selected from the literature for their physiological characterization. Genotype Species z Characteristics Selection # Name Index y value 1 Benton x Fxa Parent of the series WSU 88061- pest resistant genotypes - 2 CL-5 Fch NA Parent of the series WSU 88061- pest resistant genotypes 53.6 3 WSU 88061-1 Fch x (Fxa) F1 of Benton x CL-5; weevil and mite resistant 24.0 4 WSU-88061-4 Fch x (Fxa) F1 of Benton x CL-5; weevil and Aphid resistant 18.6 5 WSU 88061-5 Fch x (Fxa) F1 of Benton x CL-5; Highest resistance to mites and moderate to aphids 9.1 6 WSU 88061-6 Fch x (Fxa) F1 of Benton x CL-5; resistant to weevils and moderate to aphids and mites 28.8 7 Totem Fxa Standard aphid, mite and weevil susceptible cultivar 100.0 8 GCL-8 Fch NA Weevil resistant; parent of 2C6 and 2F1, weevil resistant genotypes 52.3 9 2C6 Fch x (Fxa) F1 of GCL-8 x WSU 1848; resistant to weevils no relative value 10 2F1 Fch x (Fxa) F1 of GCL-8 x WSU 1848; resistant to weevils no relative value 11 Del Norte Fch NA Former pest resistance standard 15.1 12 O15 x Fch NA High photosynthetic capacity - 13 P11 x Fch NA High photosynthetic capacity - 14 Y59 x Fch NA High photosynthetic capacity - 15 B10 x Fch NA Low photosynthetic capacity - 16 K19 x Fch NA Low photosynthetic capacity - 17 R07 x Fch NA Low photosynthetic capacity - 18 ZB-15 Fch NA Resistant to weevils 42.2 19 TR-18 Fch NA resistant to weevils 38.9 20 PNN-6A Fch SA Resistant to aphid and two spotted mite 13.6 22 ANC-2D Fch SA Low aphid oviposition level 15.3 23 LCO-3H Fch SA High aphid oviposition level 73.0 24 COY-10A Fch SA Aphid and mite susceptible 33.0 25 FRA-472 Fvi Resistant to mites 22.1 26 FRA-1174 Fvi Most mite susceptible genotype 125.0 27 ZB-19 Fch NA Weevil resistant 54.6 z: Fxa, F x ananassa; Fch NA, F. chiloensis from North America; Fch SA, F. chiloensis from South America; Fvi, F. virginiana. y: The smaller the number the more resistant the genotype is to the pest compared to cv. ‘Totem’. See text for calculation of selection index. x: Genotype not characterized in the literature for pest resistance at the experiment set up. 13
14
-2 -1 1200 µmol m s , with the same air CO2 concentration and cuvette conditions than in the preliminary measurements. The terminal leaflet of a 25-30 day old fully expanded leaf per replication was chosen for photosynthetic measurements and labeled. Using standard equations (Moon and Flore, 1986), the following gas exchange variables were calculated on the following bases: Instantaneous carbon dioxide assimilation on leaf area (Ala), dry weight (Adwt), chlorophyll content (Achl), and net photosynthetic assimilation (An); intercellular CO2, Ci; ratio between air and intercellular CO2, Ci/Ca; residual conductance to the CO2, gr; stomatal conductance to the CO2, gs; leaf conductance to the H2O, gw; transpiration rate, E and water use efficiency, WUE.
Fluorescence. The same leaflets used in gas exchange measurements were used for in vivo chlorophyll fluorescence determinations on 22-23 February, 1997, in order to assess photochemical efficiency of photosystem II (PSII) (Fernández-Baco et al., 1998). A portable fluormeter (CF-1000, Chlorophyll Fluorescence Measurement System, P.K.
Morgan Instruments, Inc.) was used. According with the instrument's manual, leaflets were dark acclimated for 15-20 minutes with a clamp-on cuvette before fluorescence measurements were taken. Fluorescence was measured for 90 s as a response to a 700 µmol m-2 s-1 beam of actinic light. The following parameters were calculated directly by the instrument: F0 (non-variable or minimal fluorescence); Fm (maximal fluorescence); Fv
(variable fluorescence [Fm-F0]); Fv/Fm (photochemical efficiency of PSII); Ft (terminal fluorescence); Fq (fluorescence quenching capacity) and t1/2 (half rise time from F0 to Fm).
After fluorescence variables were measured, the entire labeled leaf was harvested for further physiological and biochemical analysis, and put in a plastic bag with a humid paper towel and stored at 4ºC until use. In small-leaved F. chiloensis (Fch) and F. virginiana
15
(Fvi), a second representative leaf was sampled, labeled and kept in the same bag in order to insure sufficient plant material for laboratory analysis.
Attenuance spectra. At room temperature, the same terminal leaflet selected for photosynthetic and fluorescence measurements was used (within 1 to 5 days after harvesting) to characterize chlorophyll spectra by fourth derivative spectroscopy (Chen et al., 1992). Attenuance and fourth derivative spectra were measured using a Shimadzu 265 spectrophotometer (Shimadzu Scientific Instruments, Columbia, Maryland) equipped with an integrating sphere attachment. Four scans from four different points per leaflet were accumulated and normalized to two attenuance units and then 4th derivative calculation, peak wavelengths, amplitudes, and peak-pick procedures were performed using the instrument’s software (Chen et al., 1992).
Chlorophyll content and specific leaf weight. Parallel to 4th derivative spectroscopy measurements were implemented protocols for chlorophyll content and specific leaf weight determinations using the left leaflet. Total chlorophyll and chlorophyll a (Chla) and b
(Chlb) content were determined by extracting chlorophylls with N,N-Dimethylformamide from four 0.2724 cm2 leaf discs per replication (leaflet) and quantifying the results spectrophotometrically (Inskeep and Bloom, 1985) with a Shimadzu 265 spectrophotometer
(Shimadzu Scientific Instruments, Columbia, Maryland). The ratio Chla/Chlb was also determined. From the same leaflet were taken an additional 5 discs from which fresh weight (Fwt), dry weight (Dwt) were determined. Dwt was used to express different variables on a dry leaf biomass basis.
Total soluble protein. After chlorophyll determination, a tissue sample of 300.0-302.0 mg fresh weight was taken from terminal leaflets (kept until then in a plastic bag at 4ºC), put in a microfuge tube, frozen in liquid nitrogen and stored at -20ºC until use for protein
16 and Ribulose 1,5-biphosphate carboxylase/oxygenase (Rubisco) quantification. Protein and
Rubisco quantification protocols had several step in common. Each sample was ground with mortar and pestle under liquid nitrogen with 0.1 g acid washed sand. Then, 10 volumes (v/w) of grinding buffer (100 mM Bicine, pH 8.0, 12.5% glycerol, 10 mM
NaHCO3, 1 mM DL-Dithiothreitol [DTT], 1 mM Phenyl methyl sulfonyl fluoride[PMSF],
10 µM Leupeptin, and 5% [w/v] insoluble Polyvinilpyrrolidone[PVP]) was added and grinding continued until break down the tissue. When grinding was complete, 2 ml of homogenate were transferred to a microcentrifuge tube and centrifuged at 12,063 x g for 5 minutes. An aliquot of 50 µl was taken from the supernatant and assayed for total soluble protein. The remaining supernatant and pellet was kept in the microcentrifuge tube and immediately frozen and stored at -20ºC for further Rubisco determinations. Total protein was determined by the Bradford method (Bradford, 1976), a protocol which involves binding Coomassie Brilliant Blue to the protein, which causes a shift in the absorption maximum of the dye from 465 to 595 nm. This was determined spectrophotometrically in a
Shimadzu model UV-3101PC, UV-VIS-NIR scanning spectrophotometer (Shimadzu
Scientific Instruments, Columbia Maryland).
Rubisco. Enzyme Ribulose-1,5-biphosphate carboxylase/oxygenase (Rubisco; EC
4.1.1.39) was quantified by a protocol that combined procedures of Collataz et al. (1979),
Wessinger et al. (1989) and Foote (1994), where [14C]-carboxyarabinitol biphosphate (14C-
CABP), a substrate analog for the Rubisco carboxylation reaction is bound to both enzyme’s catalytic sites (Collataz et al., 1979). The 14C-CABP was synthesized by reacting
14 0.0224 mM of Na CN (1014.3 µCi) dissolved in 1 ml ddH2O with 0.0204 mM of Ribulose biphosphate (RuBP, dissolved in 1 ml ddH2O) [molar ratio of 1.1 CN to 1.0 RuBP]
(Collataz et al., 1979). Unreacted 14CN was released by addition of 4.13 ml of 1% formic
17 acid (Collataz et al., 1979) and the solution was dehydrated overnight in a fume hood at ambient temperature. The 14C-CABP was resuspended in 10 ml of buffer (50 mM HEPES,
14 10 mM MgCl2, 025 mM EDTA, pH 7.8) to give a final concentration of 2 mM of C-
CABP (Foote, 1994).
For Rubisco quantification, the remaining homogenate from the total soluble protein determination (stored at -20ºC for 13 months) was thawed and then centrifuged at 12,063 x g per 5 minutes at 4ºC (Wessinger et al., 1989). Then, an aliquot of 40µl of the supernatant was added to 100 µl 0.04 mM 14C-CABP in a microcentrifuge tube and incubated at 21ºC per 45 minutes (Foote, 1994). The Rubisco-14C-CABP protein complex was precipitated by the addition of 140 µl of precipitation buffer (100 mM Bicine [pH 8.0], 25 mM MgCl2,
40% w/v PEG [MW 4000]), incubated per 10 min at 21ºC and centrifuged at 12,063 x g per 10 minutes (Wessinger et al., 1989). The supernatant was poured off and the pellet washed with 200 µl of wash buffer (100 mM Bicine [pH 8.0], 20 mM MgCl2, 20% PEG
[MW 4000]) and centrifuged at 12,063 x g per 10 minutes (Wessinger et al., 1989). The wash buffer was then discarded and the pellet was resuspended in 100 µl of resuspension buffer (100 mM Bicine [pH 8.0] and 10 mM MgCl2) and the solution transferred to a 7 ml scintillation vial and 5 ml of scintillation cocktail (Bio Safe II™ [Research Products
International Corp.]) was added (Wessinger et al., 1989). The 14C activity was counted in a
Packard Tri-Carb Liquid Scintillation Analyzer, Model 2100TR (Packard Instrument Co.,
Meriden, Connecticut). Rubisco concentration was calculated from specific activity of the
14C-CABP based on the binding of eight mol of 14C-CABP per mol of Rubisco, and a molecular weight for Rubisco of 560,000 (Collatz et al., 1979).
18
Total phenols. Total phenolic content of leaves was estimated in alcoholic extracts with
Folin-Ciocalteu reagent according to a scaled down combined protocol from Singleton and
Rossi (1965) and Slinkard and Singleton (1977). After 4th derivative analysis and chlorophyll determinations, a sample of 300 mg (Fwt) was taken from the remaining right leaflet (and from the additional leaf in Fch and Fvi if necessary [kept in a plastic bag at
4ºC]) and ground with mortar and pestle under liquid nitrogen. At this point 3 ml of methanol was added to the mortar and the tissue was ground for 3 additional minutes. Two milliliters of homogenate was transferred to a microcentrifuge tube and centrifuged at
12,063 x g for 5 minutes (reference). A 250 µl aliquot from the supernatant was taken and diluted to 1/20 with ddH2O. A 250µl aliquot was taken from the dilution solution and reacted with 125µl of Folin-Cicalteu reagent (Slinkard and Singleton, 1977) for 5-8 minutes and then mixed with 500µl of 15% Na2CO3 and incubated for 2 hours at 21ºC. Total phenolic content was determined spectrophotometrically at 765 nm with a Shimadzu 265 spectrophotometer (Shimadzu Scientific Instruments, Columbia, Maryland), using gallic acid as standard.
Biomass Partitioning. Once all other measurements that required fresh tissues were completed, plants were partitioned into leaves, runners, crowns, roots and inflorescences (if present), and dried at 70ºC for 48 hours, with the exception of crowns, which were dried for 72 hours. Dry weight was measured for each fraction and then stored in paper bags at room temperature until further processing for other variable measurements.
Carbon isotope discrimination (∆13C). Representative leaves of the season’s growth were selected after biomass partitioning measurements (previously dehydrated at 70ºC per 72 h) and were ground with mortar and pestle. An aliquot of 300 mg was transferred to a
19 microcentrifuge tube and kept at room temperature until assayed in a commercial laboratory (Mountain Mass Spectrophotometry, Evergreen, Colorado) for carbon isotope
13 0 ratio (δ C) using a mass spectrophotometer. The “OM-03” secondary standard (-9.0 /00 with respect to Pee Dee Belemnite standard, calibrated in the National Institute of
Standards and Technology), was analyzed along with the plant samples and used to
13 13 13 0 determine δ C. ∆ C was calculated assuming a δ Cair of -8 /00 on Pee Dee Belemnite scale (Peñuelas and Azcón-Bieto, 1992).
Leaf trichomes. Leaf trichome density was measured using a compound microscope. One representative leaf per replication was harvested along with the samples for photometric analysis and fixed and stored until use in 90:5:5 FAA (95% Ethanol:40% Formaline:Acetic acid). One terminal leaflet per replication was examined at 100x, counting trichome intersections with 11 horizontal lines on an ocular micrometric grid. At that magnification, grid surface area was 0.826 mm2 and line separation 45.45µm. Trichome counting was done on the abaxial surface of the leaf and in between veins.
Statistical analysis. Statistical analysis was performed using Minitab (release 10Xtra) software (Minitab Inc., State College, Pennsylvania). Data were analyzed using ANOVA, with Tukey's multiple comparison test applied for mean separation. Multiple linear correlation (Pearson) and multiple regression analyses were performed between some variables.
3.2. Physiological characterization of two Fragaria genotypes, one pest resistant and the other pest susceptible, in response to black vine weevil fed upon foliage. An experiment in which the genotypes ‘Totem’ (F. x ananassa), the standard pest susceptible
20 genotype used in this research, and ZB-15 (F. chiloensis), a black vine weevil resistant native genotype, were both subjected to infestation by black vine weevil (Othiorhynchus sulcatus) under a shaded shelter (70% of full sunlight). The experiment was under a 3x2 factorial design, where the factors were weevil impact upon leaves (3 levels: leaves of plants without weevils, leaves without damage from plants with weevils, and leaves with weevil damage) and the Fragaria genotype (2 levels). Five replications of one plant growing in a 11.0 L volume pot, containing a vermiculite and peat moss mix, were used.
The pot was covered with aluminum foil to reflect the solar radiation and to keep the substrate temperature inside of the biological range for weevils. Pots were over a 14 inches diameter saucer pan, which had the internal vertical wall painted with Fluon™, an non- toxic polymer that prevents weevils from escaping.
Adult black vine weevils were collected in a strawberry field in Vancouver,
Washington, by mid-June 1999 and kept in buckets feeding ‘Totem’ strawberry leaves for two weeks before plant infestation. In order to have an uniform feeding pressure of weevils per plant's above ground biomass, a non-destructive plant biomass measurement was performed before infestation. Biomass units were calculated for each plant as the sum of the product between terminal leaflet's length, width and the length of the pedicel of the leaf.
All expanded leaves per plant were measured, even if they had not reached a final leaf area.
A standard infestation rate of one weevil per each 50 plant biomass units (cm3) was used.
The experiment was set up on July 7, 1999. Ten percent of the initial weevil population per plant was added three times at weekly intervals to compensate for natural mortality. After four weeks of plant-insect interaction, plant measurements were made.
Variables measured were instantaneous gas exchange, attenuance spectra, chlorophyll fluorescence, chlorophyll content, total soluble proteins, total phenols and leaf area eaten.
21
All variables in common with the first part of this research were measured following the same protocols as previously described. The only differences were the use of two newer instruments, a CO2 infrared gas analyzer Model LI-6400 (Li-Cor Inc., Lincoln, Nebraska) for gas exchange measurements and the spectrophotometer Shimadzu model UV-3101PC, equipped with an integrating sphere, for measurements of attenuance spectra, chlorophylls and total phenolics content.
Statistical analysis was performed using Minitab software (release 10Xtra, Minitab
Inc., State College, Pennsylvania). Data were analyzed using Anova, with Tukey's HDS multiple comparison test applied for mean separation. When factor interaction was observed, comparisons between the two genotypes was made using Student's t two sample test. Multiple linear correlation (Pearson) and multiple regression analyses were performed between some variables.
3.3. Physiological characterization of progeny and parents of a cross between pest susceptible and pest resistant Fragaria genotypes. As there were found significant differences in photosynthetic capacity that matched differences in pest resistance in some strawberry genotypes, a cross was made between ‘Totem’ (F. x ananassa) and ZB-15 (F. chiloensis) in late February 1997 under greenhouse conditions. Vegetatively propagated plants of each parent and each of 48 randomly-selected progeny were allowed to produce 5-
6 runners, from which were propagated plantlets obtained from nodes 2 and 3 in order to synchronize physiological age (Cannell et. al., 1988).
A complete randomized block design, with 4 replications per genotype, was set up under greenhouse conditions during the first week of July 1998. Plants were growing in 3 L pots containing a vermiculite and peat moss mix: On August 1-2, 1998, leaves were
22 trimmed off to synchronize leaf age and a new canopy was grown with weekly fertilizer applications (230 ml of a solution containing 60 ppm of 20:20:20 N:P:K plus micronutrients [Peters™]). On September 15, 1998, measurements began. Variables measured were instantaneous gas exchange, attenuance spectra, chlorophyll fluorescence, chlorophyll content, total soluble proteins, Rubisco content, and total phenols. All variables were measured following the same protocols used in earlier experiments of this research; the only differences were the use of the CO2 infrared gas analyzer Model LI-6400 for gas exchange measurements and the spectrophotometer Shimadzu model UV-3101PC, equipped with an integrating sphere, for measurements of attenuance spectra, chlorophyll content and total phenolics content.
Statistical analysis was performed using Minitab™ software (release 10Xtra; Minitab
Inc., State College, Pennsylvania). Data were analyzed using ANOVA, with Tukey's multiple comparison test applied for mean separation. Multiple linear correlation (Pearson) and multiple regression analyses were performed between some variables.
23
4. Results and Discussion
4.1 Gas Exchange
4.1.1 Selected pest resistant and pest susceptible Fragaria genotypes
Although in the literature Fragaria chiloensis (Fch) as a species has been identified as having a higher photosynthetic capacity than F. x ananassa (Fxa) (Cameron and Hartley,
1990), in this experiment this was not found to be the case for the genotypes compared.
There were no significant statistical differences among these genotypes in instantaneous leaf CO2 assimilation rate expressed on leaf area basis (Ala), dry weight (Adwt), chlorophyll content (Achl) and net photosynthesis (An) (Table 4.1-1). In this study, there were no significant differences among Fch genotypes numbers 12, 13 and 14 (Table 4.1-1), previously characterized as having a high photosynthetic capacity, and numbers 15, 16 and
17, (Table 4.1-1) characterized as with low photosynthetic capacity (Foote, 1994). Kelley
(1999), in measuring Ala and Adwt, in a large number of Fch genotypes, found that the species mean in both variables was significantly lower than those of Fxa, F. virginiana
(Fvi) while, in the same research, in studies with fewer genotypes, Fch demonstrated higher photosynthetic rates (Ala and Adwt) than Fxa and Fvi. While variability within different pools of genotypes may not bear out general conclusions concerning differences among species, in this regard, population's sample size is critical in detecting such differences.
Kelley (1999), reported that in Fch from North America, the variability within the range of expression for all genotypes studied in his research was 36% and 39 % for Ala and Adwt respectively.
Table 4.1-1. Steady state instantaneous CO2 assimilation rates, intercellular CO2, and intercellular to ambient CO2 ratio of some greenhouse-grown Fragaria genotypes.
y Genotype Ala Adwt Achl An Ci Ci/Ca z -2 -1 -1 -1 -1 -1 -2 -1 -1 -1 # Name Characteristics (µmol m s ) (µmol kg s ) (µmol mg h ) (mg CO2 dm h ) (µl liter ) (µl µl ) 1 Benton Fxa 15.00 abc x 46.47 cde 17.90 ab 23.76 abc 240.79 bcd 0.601 cd 2 CL-5 Fch Pest Res 12.04 bc 45.89 cde 15.91 ab 19.07 bc 289.86 abc 0.713 abcd 3 88061-1 Adv. Sel. Pest Res 14.74 abc 39.42 de 14.94 ab 23.35 abc 223.93 d 0.559 d 4 88061-4 Adv. Sel. Pest Res 20.17 ab 68.42 abcd 21.03 ab 31.95 ab 242.20 bcd 0.607 cd 5 88061-5 Adv. Sel. Pest Res 17.17 ab 65.77 abcd 20.67 ab 27.20 ab 237.12 cd 0.604 cd 6 88061-6 Adv. Sel. Pest Res 17.65 ab 68.55 abcd 20.15 ab 27.95 ab 264.28 abcd 0.658 abcd 7 Totem Fxa Pest Sus Std 17.95 ab 67.90 abcd 20.64 ab 28.43 ab 243.64 bcd 0.616 bcd 8 GCL-8 Fch Pest Res 17.83 ab 88.67 ab 22.77 a 28.25 ab 277.65 abcd 0.693 abcd 9 2C6 Adv. Sel Pest Res 18.56 ab 64.63 abcd 20.31 ab 29.40 ab 243.38 bcd 0.614 cd 10 2F1 Adv. Sel. Pest Res 20.50 ab 70.96 abcd 20.68 ab 32.47 ab 271.65 abcd 0.673 abcd 11 Del Norte Fch Pest Res 21.36 a 99.27 a 23.34 a 33.84 a 273.06 abcd 0.680 abcd 12 O15 Fch High Phot Cap 18.90 ab 83.53 abc 22.35 a 29.94 ab 276.58 abcd 0.700 abcd 13 P11 Fch High Phot Cap 20.28 ab 76.21 abcd 18.46 ab 32.13 ab 259.02 abcd 0.649 abcd 14 Y59 Fch High Phot Cap 20.02 ab 85.53 abc 20.60 ab 31.70 ab 276.21 abcd 0.697 abcd 15 B10 Fch Low Phot Cap 14.80 abc 53.87 bcde 14.22 ab 23.44 abc 280.88 abcd 0.700 abcd 16 K19 Fch Low Phot Cap 18.26 ab 90.58 ab 24.48 a 28.93 ab 278.32 abcd 0.696 abcd 17 R07 Fch Low Phot Cap 15.94 ab 54.09 bcde 14.63 ab 25.25 ab 263.66 abcd 0.664 abcd 18 ZB-15 Fch Pest Res 19.48 ab 86.50 abc 20.84 ab 30.85 ab 235.78 cd 0.594 cd 19 TR-18 Fch Pest Res 21.75 a 94.37 ab 25.68 a 34.46 a 274.50 abcd 0.698 abcd z: Fxa, Fragaria x ananassa; Fch, F. chiloensis; Fv, F. virginiana; Adv. Sel., Advanced selection (F ch x [Fxa]); Pest Res, Pest resistant; Pest Sus, Pest susceptible; Phot Cap, Photosynthetic capacity according to Foote (1994). y : Variable identification: Instantaneous carbon dioxide assimilation on leaf area basis (Ala), dry weight (Adwt), chlorophyll content (Achl), and net photosynthetic assimilation (An). Ci, intercellular CO2; Ci/Ca, ratio between intercellular and ambient CO2. x: Mean separation within each column (genotypes 1 to 27) by Tukey’s HSD test, P ≤ 0.05. 24
Table 4.1-1. (Continued).
y Genotype Ala Adwt Achl An Ci Ci/Ca z -2 -1 -2 -1 -1 -1 -2 -1 -1 -1 # Name Characteristics (µmol m s ) (µmol kg s ) (µmol mg h ) (mg CO2 dm h ) (µl liter ) (µl µl ) 20 PNN-6A Fch Pest Res 17.73 ab x 64.29 abcd 24.18 a 28.08 ab 296.76 abc 0.746 abc 22 ANC-2D Fch Pest Res 6.82 c 16.59 e 10.23 b 10.81 c 311.41 a 0.787 a 23 LCO-3H Fch Pest Sus 18.61 ab 67.37 abcd 23.71 a 29.47 ab 279.30 abcd 0.681 abcd 24 COY10A Fch Pest Sus 13.92 abc 59.35 abcd 17.15 ab 22.05 abc 273.79 abcd 0.688 abcd 25 FRA-472 Fv Pest Res 14.34 abc 56.59 bcde 24.40 a 22.72 abc 303.53 ab 0.744 abc 26 FRA1174 Fv Pest Sus 12.81 abc 65.20 abcd 16.72 ab 20.29 abc 303.58 ab 0.773 ab 27 ZB-19 Fch Pest Res 19.60 ab 78.65 abcd 22.59 a 31.04 ab 248.98 abcd 0.623 bcd z: Fxa, Fragaria x ananassa; Fch, F. chiloensis; Fv, F. virginiana; Adv. Sel., Advanced selection (F ch x [Fxa]); Pest Res, Pest resistant; Pest Sus, Pest susceptible; Phot Cap, Photosynthetic capacity according to Foote (1994). y : Variable identification: Instantaneous carbon dioxide assimilation on leaf area basis (Ala), dry weight (Adwt), chlorophyll content (Achl), and net photosynthetic assimilation (An). Ci, intercellular CO2; Ci/Ca, ratio between intercellular and ambient CO2. x: Mean separation within each column (genotypes 1 to 27) by Tukey’s HDS test, P ≤ 0.05.
25
26
The relatively low values observed in Ala and Adwt in all three species studied in this research (Fch, Fvi, Fxa), when compared with the literature (Cameron and Hartley, 1990;
Foote, 1994; Kelley, 1999), can be attributed to the winter's low photosynthetic photon flux density (PPFD) conditions observed in this research, which are in agreement with findings of Yoshida and Morimoto, (1997), who also found lower Ala rates in active winter leaves when compared with summer leaves in greenhouse grown ‘Nyoho’ strawberry plants.
Cameron and Hartley (1990) found that in average, four genotypes of Fch have an Ala of
-2 -1 about 7.0 µmol m s (data extrapolated from a graph) when Ala was measured at a PPFD of 300 µmol m-2 s-1, a rate that increases as the PPFD increases, without reaching an asymptotic plateau or an inflection point, even at 2100 µmol m-2 s-1 of PPFD intensity,
-2 -1 when Ala had about 22 µmol m s . In the same study, Fxa showed Ala values of 5 and
14.5 µmol m-2 s-1 when the PPFD was 300 and 2100 µmol m-2 s-1 respectively, which are lower than those observed in the present study for 'Totem' but close to 'Benton', both Fxa genotypes (Table 4.1-1), suggesting an acclimation process oriented to optimize the use of the light resource (Givnish, 1988; Larcher, 1995; Hall and Rao, 1999).
In the present research, those leaves chosen for photosynthetic measurements were 25 to 30 days old, an age at which in Fvi, Jurik et al. (1979), found that Ala was reaching only
70% of its ontogenic maximum, with the latter occurring at the same time of maximum leaf expansion (18 days). This data suggest that the two genotypes of Fvi in this study
(genotypes 25 and 26, Table 4.1-1), were sampled in an ontogenic stage which was latter than in the companion species, but representative of functional winter leaves (Juric and
Chabot, 1986; Yoshida and Morimoto, 1997). In this current research, Ala average rates are higher or close to the maximum ontogenic reported for the same species by Jurik et al.,
27
(1979), suggesting that winter leaves may retain high photosynthetic rates for a longer period of time than the summer ones.
Among Fch genotypes, ANC-2D had a significantly lower photosynthetic rate (as expressed in all bases), than 'Del Norte' and TR-18 genotypes (Table 4.1-1).
Levels of intercellular CO2 (Ci) showed no statistical differences among most of the studied genotypes (Table 4.1-1), with the exception of those in the extremes of the range of observed values. In this regard, ANC-2D and both Fvi genotypes (FRA-472 and FRA-
1174), with high Ci content, were statistically different from ZB-15 and 88061-1 (low Ci). It can be expected that those genotypes with extreme values of Ci , also exhibit similar trends on levels of Ala and An, as it was observed in this research (Table 4.1-1). Correlations
(Pearson) between Ci and Ala and between Ci and An, considering all tested genotypes, have an r of -0.43 in both cases (P=0.03, N=26; Table 4.1-2), indicating a rather low association between those variables, probably reflecting the pooled variability of all genotypes. When genotypes in the extremes of the range observed in Ci are correlated with their own Ala and An, (genotypes number 3, 5, 18, 22, 25, and 26, Table 4.1-1), the association between variables is stronger (r=-0.74, P=0.09, N=6). In this case, a negative correlation coefficient indicates that as photosynthesis is depleting the intercellular CO2 (Ci
), its concentration decreases (Larcher, 1995; Hall and Rao, 1999). Due to this relationship, those genotypes with higher Ci, showed lower values in Ala and An., suggesting that CO2 cannot be assimilated as efficiently as in other genotypes. However, Pearson’s correlation coefficients (r) between Ci and Adwt and Achl (Table 4.1-2) are somewhat more complex to interpret because both ways to express the instantaneous photosynthesis rate are functions of previous biomass allocations, as well as light environment over time (Givnish, 1988;
28
Larcher 1995; Hall and Rao, 1999), factors that cannot be accounted for by instantaneous photosynthetic rates (Field et al., 1992).
The ratio Ci/Ca is the proportion of residual intercellular CO2, and relates the photosynthetic rates with the stomatal and residual conductivities to the CO2, and can serve as an indirect index for the carboxylation efficiency when the CO2 conductivities are known (Field et al., 1992). In Table 4.1-1 the Ci/Ca ratios are shown as well the residual
(gr) and stomatal (gs) conductivities. The overall results show a high variability in Ci/Ca, and the only statistical significant differences are those between genotypes in the extremes of the observed ranges of values (Table 4.1-1). No relationship between pest resistance level or photosynthetic capacity with the Ci/Ca ratio can be hypothesized as, apparently, in the literature there are no reports about consistent differences in the former variables for those genotypes that, in this research, were at both extremes of the Ci/Ca range. As expected, the statistical differences in Ci/Ca are between most of the genotypes that also showed differences in Ci (Table 4.1-1). Ci/Ca showed Pearson correlation coefficients of -
0.42 with Ala and An (P=0.03, N=26), value that is similar to that observed between
Ci with Ala and An (Table 4.1-2).
Table 4.1-2. Correlation coefficients (Pearson) between some photosynthetic parameters for 26 Fragaria genotypes.
z Variable Genotype Ala Adwt Achl An gs gw gr Ci Ci/Ca Ala -0.13 y (µmol m-2 s-1) (0.52)
Adwt -0.07 0.85 (µmol kg-1 s-1) (0.72) (0.00)
Achl 0.12 0.75 0.79 (µmol mg-1 h-1) (0.58) (0.00) (0.00)
An -0.13 1.00 0.85 0.75 -2 -1 (0.52) (0.00) (0.00) (0.00) (mg CO2 dm h ) gs 0.41 0.56 0.70 0.67 0.56 (mmol m-2 s-1) (0.04) (0.00) (0.00) (0.00) (0.00) gw 0.41 0.56 0.70 0.67 0.56 1.00 (mmol m-2 s-1) (0.04) (0.00) (0.00) (0.00) (0.00) (0.00) gr -0.29 0.94 0.70 0.58 0.94 0.26 0.26 (mmol m-2 s-1) (0.15) (0.00) (0.00) (0.00) (0.00) (0.19) (0.19) z : Variable identification: Instantaneous carbon dioxide assimilation on leaf area basis (Ala), dry weight (Adwt), chlorophyll content (Achl), and net photosynthetic assimilation (An). Ci, intercellular CO2; Ci/Ca, ratio between air and intercellular CO2; gr, residual conductance to the CO2; gs, stomatal conductance to the CO2; gw, leaf conductance to the H2O; E, transpiration rate. y: Values in parenthesis are Prob > R under Ho:Rho = 0; N=26. 29
Table 4.1-2. (Continued).
z Variable Genotype Ala Adwt Achl An gs gw gm Ci Ci/Ca
Ci 0.54 -0.43 -0.12 -0.05 -0.43 0.45 0.45 -0.70 y (µl l-1) (0.00) (0.03) (0.55) (0.79) (0.03) (0.02) (0.02) (0.00)
Ci/Ca 0.56 -0.42 -0.11 -0.06 -0.42 0.49 0.49 -0.69 0.99 (µl µl-1) (0.15) (0.03) (0.60) (0.79) (0.03) (0.01) (0.01) (0.00) (0.00)
E 0.52 0.30 0.48 0.52 0.30 0.92 0.92 0.02 0.57 0.63 (mmol m-2 s-1) (0.00) (0.13) (0.01) (0.00) (0.13) (0.00) (0.00) (0.93) (0.00) (0.00) z : Variable identification: Instantaneous carbon dioxide assimilation on leaf area basis (Ala), dry weight (Adwt), chlorophyll content (Achl), and net photosynthetic assimilation (An). Ci, intercellular CO2; Ci/Ca, ratio between air and intercellular CO2; gr, residual conductance to the CO2; gs, stomatal conductance to the CO2; gw, leaf conductance to the H2O; E, transpiration rate. y: Values in parenthesis are Prob > R under Ho:Rho = 0; N=26.
30
31
Cameron and Hartley (1990) and Kelley (1999) found that some cultivars of Fxa have significantly lower gs than representatives of Fch, specially those from North America.
However, in this study, the only statistical difference was between the genotypes 88061-1 and PNN-6A (Table 4.1-3). The latter genotype showed a reduced growth rate in this study.
Among genotypes studied in common with the research of Foote (1994), all showed higher gs values in his study (under field conditions), than in the present research. However, in the latter there was observed a similar trend of differentiation between the genotypes ranked in his research with high (O15, P11 and Y59) and low photosynthetic capacity (B10, K19 and
R07) (Table 4.1-3).
While gr and gs are two of a number of limiting factors in determining photosynthetic capacity (Von Caemmerer and Farquhar, 1981; Field et al., 1992; Larcher, 1995, Hall and
Rao, 1999), they both are usually highly correlated with the photosynthetic rate. In this study, gs had Pearson correlation coefficients with the variously expressed bases of photosynthetic rate ranging between 0.56 to 0.70 (for all P=0.00; N=26); Table 4.1-2). An even stronger association (r) was observed between gr and photosynthetic rates, ranging from 0.58 with Achl (P=0.00; N=26), to 0.94 with both Ala and An (P=0.00; N=26; Table
4.1-2). This degree of association between CO2 conductivities and photosynthetic rates can be expected due the importance for the photosynthetic process of several limiting points or resistances for the CO2 flux to the tylakoids, which are sensed by gs and gr (Larcher, 1995).
When performed a Stepwise multiple regression analysis with all measured variables related to the CO2 diffusional pathway to the chloroplasts on Ala, gr was selected with a very high F number (Table 4.1-4). The model also selected gs, where both conductances
2 account for 97.1% of the observed variation (Adj. R ) in Ala. The regression equation is shown in Table 4.1-4.
Table 4.1-3. Steady state instantaneous residual CO2 and water conductivities, water vapor evaporation and water use efficiency of some greenhouse-grown Fragaria genotypes.
y 3 Genotype gr gs gw E WUE *10 z -2 -1 (mmol m-2 s-1) (mmol m-2 s-1) (mol CO mol H O-1) # Name Characteristics (mmol m s ) (mmol m-2 s-1) 2 2 1 Benton Fxa 61.84 abc x 112.13 bc 179.41 bc 4.08 bc 3.71 abc 2 CL-5 Fch Pest Res 41.95 bc 114.91 bc 183.86 bc 3.57 bc 3.24 abc 3 88061-1 Adv. Sel. Pest Res 66.51 ab 92.29 c 147.66 c 3.25 c 4.71 ab 4 88061-4 Adv. Sel. Pest Res 83.77 a 138.72 abc 221.95 abc 4.09 bc 4.96 a 5 88061-5 Adv. Sel. Pest Res 72.13 ab 122.15 abc 195.45 abc 4.14 bc 4.32 abc 6 88061-6 Adv. Sel. Pest Res 66.44 ab 149.26 abc 238.82 abc 4.56 bc 3.90 abc 7 Totem Fxa cv Pest Sus Std 74.21 ab 129.08 abc 206.53 abc 4.35 bc 4.12 abc 8 GCL-8 Fch Pest Res 64.68 ab 160.39 abc 256.62 abc 5.41 abc 3.30 abc 9 2C6 Adv. Sel Pest Res 79.10 ab 137.27 abc 219.63 abc 4.53 bc 4.25 abc 10 2F1 Adv. Sel. Pest Res 77.34 ab 173.23 abc 277.17 abc 5.58 abc 3.67 abc 11 Del Norte Fch Pest Res Std 78.40 ab 192.37 ab 307.78 ab 5.99 abc 3.65 abc 12 O15 Fch High Phot Cap 68.69 ab 178.67 abc 285.86 abc 6.53 ab 2.97 abc 13 P11 Fch High Phot Cap 81.49 ab 159.32 abc 254.90 abc 5.62 abc 3.63 abc 14 Y59 Fch High Phot Cap 72.01 ab 186.26 ab 298.02 ab 6.00 abc 3.40 abc 15 B10 Fch Low Phot Cap 55.62 abc 145.27 abc 232.43 abc 5.24 abc 2.83 abc 16 K19 Fch Low Phot Cap 66.31 ab 169.76 abc 271.61 abc 5.69 abc 3.20 abc 17 R07 Fch Low Phot Cap 61.05 abc 136.16 abc 217.86 abc 4.66 abc 3.76 abc 18 ZB-15 Fch Pest Res 81.83 ab 152.03 abc 243.26 abc 4.77 abc 4.26 abc 19 TR-18 Fch Pest Res 79.32 ab 200.88 ab 321.40 ab 6.38 ab 3.43 abc z: Fxa, Fragaria x ananassa; Fch, F. chiloensis; Fv, F. virginiana; Adv. Sel., Advanced selection (F ch x [Fxa]); Pest Res, Pest resistant; Pest Sus, Pest susceptible; Phot Cap, Photosynthetic capacity according to Foote (1994)..
y : Variable identification: gr, residual conductance to the CO2; gs, stomatal conductance to the CO2, gw, leaf conductance to H2O; E, transpiration rate; WUE, water use efficiency.
x: Mean separation within each column (genotypes 2 to 27) by Tukey’s HDS test, P ≤ 0.05. 32
Table 4.1-3. (Continued).
y 3 Genotype gr gs gw E WUE *10 z -2 -1 (mmol m-2 s-1) (mmol m-2 s-1) (mol CO mol H O-1) # Name Characteristics (mmol m s ) (mmol m-2s-1) 2 2 20 PNN-6A Fch Pest Res 59.63 abc x 212.91 a 335.66 a 7.85 a 2.36 bc 22 ANC-2D Fch Pest Res 22.59 c 116.10 bc 185.76 bc 4.33 bc 1.70 c 23 LCO-3H Fch Pest Sus 66.63 ab 162.76 abc 260.42 abc 5.10 abc 3.93 abc 24 COY10A Fch Pest Sus 51.59 abc 135.98 abc 217.56 abc 4.83 abc 3.07 abc 25 FRA-472 Fv Pest Res 47.29 abc 165.34 abc 264.53 abc 6.42 ab 2.28 bc 26 FRA1174 Fv Pest Sus 42.57 bc 169.15 abc 270.65 abc 6.44 ab 2.01 c 27 ZB-19 Fch Pest Res 78.86 ab 141.33 abc 226.13 abc 4.54 bc 4.41 ab z: Fxa, Fragaria x ananassa; Fch, F. chiloensis; Fv, F. virginiana; Adv. Sel., Advanced selection (F ch x [Fxa]); Pest Res, Pest resistant; Pest Sus, Pest susceptible; Phot Cap, Photosynthetic capacity according to Foote (1994). y : Variable identification: gr, residual conductance to the CO2; gs; stomatal conductance to the CO2; gw, leaf conductance to H2O; E, transpiration rate; WUE, water use efficiency. x: Mean separation within each column (genotypes 1 to 27) by Tukey’s HDS test, P ≤ 0.05.
33
34
However, as gr involves CO2 diffusional pathways, both under gas and liquid phases, plus the action of several biochemical feedback controlling mechanisms for photosynthetic CO2 assimilation (Taiz and Zeiger, 1991; Salisbury and Ross, 1992; Larcher, 1995, Hall and
Rao, 1999), more focused studies are required to determine the specific bases for differences observed in A due to gr. In following sections other variables involved in photosynthetic performance will be addressed and correlated with conductance values.
Other variables measured that are coupled to the CO2 diffusion towards photosynthetic centers are the evaporation of water vapor from the leaf (E), its conductivity (gw) and water use efficiency (WUE). As the main flux of water vapor is through stomata, the trend in observed values match proportionally those of the CO2 conductivities (Table 4.1-3), which explain the correlation coefficient between gs and gw of 1.0 (P=0.00; N=26), and between E and gs and gw, with r=0.92 in both cases (P=0.00; N=26; Table 4.1-2).
Table 4.1-4. F number for some photosynthetic variables using the Stepwise linear multiple regression variable selection procedure for the photosynthetic CO2 assimilation (Ala). F-to-enter a variable to the model: 4.00; F-to-remove a variable from the model: 4.00; d.f.: 32.
Variable z F-to-Remove from model F-to-Enter to the model gs 130.2594 gr 769.6319 gw 0.0488 E 2.1673 WUE 3.7070 Ci 0.0477
2 2 Regression equation: Ala = 0.03713 gs + 0.17798 gr R = 0.973; Adjusted R = 0.971 z : Variable identification: gs, stomatal conductance to the CO2; gr, residual conductance to the CO2 ; gw, leaf conductance to the H2O; E, transpiration rate; WUE, water use efficiency; Ci, intercellular CO2.
35
4.1.2 Weevil-Plant interaction
When “Totem (Fxa) and ZB-15 (Fch) genotypes were infested with black vine weevil (O. sulcatus), no significant differences were observed among the levels of weevil impact over leaves, which suggests that under these experimental conditions, there was no photosynthetic compensation in leaves with damage or in leaves without damage of weevil infested plants when compared to leaves of non-infested plants (Whitman et al., 1991,
Trumble et al., 1993). Conversely, there were significant differences in nearly all variables among genotypes (Totem vs. ZB-15), with the exception of Achl and WUE (Table 4.1-5). In the latter, as the WUE is a ratio between the moles of CO2 fixed and the moles of water transpired, this ratio was not able to detect differences between both genotypes even though, ZB-15 had higher rates of E. Since ZB-15 is also fixing more carbon, the ratio
WUE was similar to that of Totem (Table 4.1-5). As in Ci and Ci/Ca were detected significant factor interactions, it is not possible to relate the results to a particular factor
(Ott, 1993), but for all other variables the factors were independent in their effects (Table
4.1-5). These results follow the same general pattern observed in plants not infested with weevils in previous experiments. This would more directly relate to the basis of pest resistance and how those resistant plants distribute, and eventually, redistribute photoassimilates under insect attack (Mitra and Bhatia, 1982; Bazzaz et al., 1987; Clark and Harvell, 1992).
4.1.3 Observation on progeny
The observed results in photosynthesis-related variables are presented in the Table 4.1-6, where the parents are presented along and compared with their progeny. When instantaneous
Table 4.1-5. Steady state instantaneous gas exchange variables for Totem (Fragaria x ananassa) and ZB-15 (Fragaria chiloensis) genotypes being fed on by black vine weevil (Othiorhynchus sulcatus). Factor Weevil Impact Genotype Factors Level No weevils Weevils - Leaf Weevils - Leaf Totem ZB-15 interaction Variable z without damage with damage -2 -1 y x w Ala (µmol m s ) 17.11 a 17.74 a 18.96 a 13.97 a 21.91 b NS
-1 -1 Adwt (µmol kg s ) 52.64 a 59.43 a 51.81 a 49.34 a 59.91 b NS
-1 -1 Achl (µmol mg h ) 28.17 a 26.62 a 31.21 a 26.69 a 30.63 a NS
-2 - An(mg CO2 dm h 27.11 a 30.04 a 28.12 a 22.13 a 34.72 b NS 1)
-1 Ci (µl l ) 277.40 a 280.50 a 277.70 a 284.20 a 272.87 b S
-1 Ci/Ca (µl µl ) 0.693 a 0.701 a 0.694 a 0.710 a 0.682 b S
-2 -1 gr (mmol m s ) 62.23 a 67.36 a 64.83 a 49.27 a 80.34 b NS
-2 -1 gs (mmol m s ) 190.52 a 224.70 a 192.14 a 162.53 a 242.38 b NS
-2 -1 gw (mmol m s ) 337.3 a 401.5 a 334.9 a 283.07 a 432.73 b NS
z: For variable identification see next page.
y: Averages and statistical significance according to a 3x2 Factorial ANOVA (3 levels of weevil impact on leaves and 2 genotypes).
x: Mean separation in both factors (weevil impact and genotype) by Tukey’s HDS test, P≤0.05.
w: NS, No significant interaction between factors; S, significant, both at P≤0.05. 36
Table 4.1-5. (Continued).
Factor Weevil Impact Genotype Factors Level No weevils Weevils - Leaf Weevils - Leaf Totem ZB-15 interaction Variable z without damage with damage E (mmol m-2 s-1) 5.50 y a x 6.83 a 6.66 a 5.08 a 7.58 b NS w
WUE*103 3.11 a 2.90 ab 2.65 a 2.77 a 2.99 a NS (molCO2 mol H20-1) z : Variable identification: Instantaneous carbon dioxide assimilation on leaf area basis (Ala), dry weight (Adwt), chlorophyll content (Achl), and net photosynthetic assimilation (An). Ci, intercellular CO2; Ci/Ca ratio between air and intercellular CO2; gr, residual conductance to the CO2; gs, stomatal conductance to the CO2; gw, leaf conductance to the H2O; E, transpiration rate; WUE, water use efficiency. y: Averages and statistical significance according to a 3x2 Factorial ANOVA (3 levels of weevil impact on leaves and 2 genotypes). x: Mean separation in both factors (genotype and weevil impact) by Tukey’s HDS test, P≤0.05. w: NS, No significant interaction between factors; S, significant, both at P≤0.05. 37
38
photosynthetic rate is expressed on leaf area (Ala) and net (An) basis, the pattern of statistical
differences is the same. The observed variation among the genotypes (Table 4.1-6) is less than
that observed in the characterization of genotypes selected according with their pest resistance
level (Table 4.1-1). In comparing parents and progeny there are few statistically significant
differences. The parents themselves follow a trend similar to that observed in the experiment
with black vine weevil, although the values in this experiment are higher, probably because the weevil experiment was carried out under a shade net (70% of full sun), conditioning leaves for a lower PPFD (Lichtenthaler, 1985; Givnish, 1988; McKierman an Baker, 1992, Murchie and
Horton, 1998). In both experiments, measurements were made at the end of summer, which further support the idea that lower values in Ala and An, and lack of statistical differences in the
first experiment, in late winter (Table 4.1-1), may have been related to low PPFD (Lichtenthaler,
1985; Givnish, 1988; ; McKierman an Baker, 1992, Murchie and Horton, 1998). In Ala and An, the pest resistant parent, ZB-15, had significant higher average rates than most of its progeny and the other parent, being not different only to five of its progeny genotypes (Table 4.1-6). This confirms ZB-15 as a high photosynthetic capacity genotype, while ‘Totem’ instead, is almost at the opposite end of the observed range of values, although, not statistically different from any of its progeny. This range of values in Ala and An , and the parents position in it, suggests a segregation of F1 progeny with intermediate values, somewhat closer to ‘Totem’, and thus likely
without transgressive segregation. The lack of statistical significance among most of the
genotypes also suggests a lack of enhanced photosynthetic capacity in the progeny due to any
contribution from ZB-15. Since this parent was used as female parent in this cross, it would
appear in this case that high photosynthetic capacity is not a direct maternal effect since
chloroplasts are transmitted by the cytoplasm of the female parent, and that any related control
may reside in the nucleus (Klein and Salvucci, 1995). Two possible types of control could 39
preliminary be suggested: One is that genes that are expressed independently of the chloroplast
genome are involved, and/or the other possibility of involvement of genes which interact with the chloroplasts’ DNA (Jiang et al., 1993; Klein and Salvucci, 1995).
Only a few genotypes have significantly different Adwt rates (Table 4.1-6). In absolute numbers, most of the progeny genotypes are in the middle between parental values for Adwt, where ZB-15 is close to the upper end of the range of values and ‘Totem’ is at the lower end of it. A different distribution of genotypes can be observed in Achl, (Table 4.1-6), where the
chlorophyll content causes a shift in relative positions among genotypes. The parent ZB-15 has the highest Achl numerical value, with ‘Totem’ close to it and most of the progeny below both
parents’ means. ZB-15 is significantly different from 18 progeny genotypes, while ‘Totem’ is not
different from any progeny genotype. As ZB-15 an 'Totem' showed no differences in Achl and
Adwt but they were in fact different in Ala and An (Table 4.1-6), the high photosynthetic capacity
of ZB-15 when compared to 'Totem' could be related to other basis or photosynthetic processes but not as a consequence of the chlorofill content or leaf biomass.
For Ci, ZB-15 is in the middle of the observed range of values, with ‘Totem’ towards the
lower end of the range. Half of the progeny is above ZB-15. Statistical differences were found
between genotype 12 (Table 4.1-6) with the highest numerical value, compared with ‘Totem’
and genotypes 47, 20, 38, 23, 15, and 21 (the order listed indicates increasing numerical
differences), as well between genotypes 17, 31 and 28 when compared to genotypes 15 and 21.
However, when the Ci values are divided by Ca , very close values, not significantly different, were observed for all genotypes, with a range between 0.6748 and 0.7410. It is possible that photosynthesis measurements were made before the leaves depleted Ci to reach steady state
levels as to give a Ci/Ca ratio in ‘Totem’ and ZB-15 similar to those observed in previous
experiments (Field, et al., 1992). This idea is supported by the fact that the difference in gr 40
between genotypes is clear, with ZB-15 at the top of the range of values (Table 4.1-6), indicating
that if photosynthesis measurements were taken with longer periods of holding the cuvette on the
leaf, the Ci and Ci/Ca ratio in ZB-15 and ‘Totem’ would likely follow the trends observed in the
other experiments. Also, it is clear that the high photosynthetic capacity of ZB-15 is at least in
significant part explained by some component associated with gr. These components were not likely readily transferred to the F1 progeny (Table 4.1-6), where most of the progeny have values
closer to ‘Totem’, the pollen donor, with some genotypes even below the latter.
Also, as would be expected from the previous experiments, ZB-15 exhibited a high gs (Table
4.1-7), a fact that could also be masking the Ci concentration before it reached a steady state in
the CO2 flux to the chloroplasts (Field, et al., 1992). ‘Totem’ was at the opposite extreme of the
range for gs, significantly lower than ZB-15. The latter also differs from genotypes 15 and 21, while genotypes 24 and 25 are different from genotype 15, while all other combinations between genotypes were without statistical significance (Table 4.1-7). Similar distribution of genotypes in both extremes of their respectives ranges of values was observed in gs, gw, and E (Table 4.1-7),
where genotypes 17, 24, 25, 39 and 49 were clustered in the upper end and genotypes 15, 21, 23,
38, 43, and 'Totem' were at the lower end in each one of those variables. Such consistency in
genotypes’ relative positions along variables is not unexpected as gs, gw and E are all dependent
on stomatal aperture, which is basically the parameter that controls CO2 and water vapor
conductivities (Salisbury and Ross, 1992; Larcher,1995, Hall and Rao, 1999), and as all
photosynthetic variables recorded represent a single gas exchange instantaneous steady state, it
can be assumed that stomatal aperture was the same for each photosynthetic variable. In WUE
however, ‘Totem’ showed one of the best ratios (net carbon gain per unit of transpirated water),
with ZB-15 in the middle of the range and more than half of the progeny below it (Table 4.1-7),
even though statistical differences were only found between the two genotypes in the Table 4.1-6. Steady state instantaneous gas exchange variables of 45 greenhouse-grown F1 Fragaria genotypes (from a single cross), plus their parents, Totem (F. x ananassa) and ZB-15 (F. chiloensis).
Genotype z ALA Adwt Achl An Ci Ci/Ca Identific. -2 -1 -1 -1 -1 -1 -2 -1 -1 -1 (µmol m s ) (µmol kg s ) (µmol mg h ) (mg CO2 dm h ) (µl liter ) (µl µl ) 2 21.43 b y 99.46 ab 8.20 abc 33.90 b 281.00 abc 0.702 a 3 21.53 b 93.75 ab 8.78 abc 34.05 b 276.50 abc 0.691 a 4 21.68 b 101.56 ab 7.69 abc 34.38 b 273.00 abc 0.683 a 5 21.05 b 106.87 ab 6.67 bc 33.35 b 276.00 abc 0.691 a 6 21.93 b 97.62 ab 9.12 abc 34.75 b 280.75 abc 0.702 a 7 19.78 b 106.36 ab 7.30 abc 31.33 b 288.75 abc 0.723 a 8 21.45 b 94.78 ab 8.26 abc 33.98 b 284.75 abc 0.712 a 9 20.18 b 88.49 ab 8.35 abc 31.93 b 279.75 abc 0.700 a 10 22.58 b 99.83 ab 8.12 abc 35.73 b 279.75 abc 0.700 a 11 19.40 b 80.36 b 6.72 bc 30.70 b 286.75 abc 0.717 a 12 20.48 b 77.80 b 8.57 abc 32.48 b 296.25 a 0.741 a 13 20.58 b 102.74 ab 6.67 bc 32.58 b 279.25 abc 0.699 a 14 19.38 b 109.09 ab 6.08 c 30.65 b 286.50 abc 0.717 a 15 18.35 b 83.87 ab 6.38 c 29.05 b 263.25 c 0.658 a 16 21.00 b 84.26 ab 8.35 abc 33.28 b 284.00 abc 0.711 a 17 21.58 b 86.57 ab 9.23 abc 34.15 b 292.25 ab 0.732 a 18 20.80 b 115.01 ab 6.29 c 32.93 b 270.75 abc 0.678 a 19 22.33 b 91.91 ab 8.64 abc 35.33 b 274.25 abc 0.686 a 20 21.68 b 102.18 ab 8.59 abc 34.30 b 267.00 bc 0.668 a 21 20.25 b 91.10 ab 6.69 c 32.05 b 262.75 c 0.658 a 22 24.08 ab 116.04 ab 7.84 abc 38.15 ab 272.75 abc 0.683 a 23 21.80 b 85.60 ab 8.87 abc 34.50 b 266.50 bc 0.667 a 24 22.70 ab y 111.04 ab 7.44 abc 35.90 ab 283.00 abc 0.708 a 25 23.40 ab 111.24 ab 8.34 abc 37.08 ab 282.75 abc 0.708 a z: For variable identification see end of Table y: Mean separation within each column (genotypes 2 to 50) by Tukey’s HSD test, P≤0.05. 41
Table 4.1-6. (Continued). Genotype z ALA ADW Achl An Ci Ci/Ca Identific. -2 -1 -1 -1 -1 -1 -2 -1 -1 -1 (µmol m s ) (µmol kg s ) (µmol mg h ) (mg CO2 dm h ) (µl liter ) (µl µl ) 26 21.15 b 101.35 ab 6.71 bc 33.50 b 273.75 abc 0.685 a 27 20.73 b 111.24 ab 6.61 bc 32.85 b 289.00 abc 0.723 a 28 20.70 b 103.75 ab 6.74 bc 32.80 b 290.50 ab 0.727 a 31 20.18 b 82.86 ab 7.71 abc 32.00 b 292.25 ab 0.732 a 32 20.68 b 105.68 ab 7.43 abc 32.75 b 285.25 abc 0.714 a 33 20.35 b 125.74 a 6.89 bc 32.25 b 281.25 abc 0.704 a 34 20.98 b 99.57 ab 6.60 c 33.22 b 275.25 abc 0.689 a 35 19.90 b 102.97 ab 6.38 c 31.53 b 278.25 abc 0.696 a 36 21.95 b 101.97 ab 7.25 bc 34.73 b 285.75 abc 0.715 a 37 21.75 b 85.59 ab 8.10 abc 34.48 b 274.50 abc 0.687 a 38 20.80 b 91.67 ab 7.30 abc 32.95 b 267.00 bc 0.668 a 39 22.23 b 92.03 ab 8.06 abc 35.18 b 288.50 abc 0.722 a 40 21.20 b 98.72 ab 7.41 abc 33.58 b 287.25 abc 0.718 a 41 20.23 b 92.51 ab 7.15 bc 32.03 b 275.75 abc 0.690 a 42 20.55 b 91.42 ab 7.10 bc 32.55 b 279.75 abc 0.700 a 43 20.10 b 91.83 ab 6.45 c 31.83 b 269.25 abc 0.674 a 44 22.75 ab 92.32 ab 9.27 abc 36.03 ab 281.50 abc 0.705 a 45 21.50 b 113.30 ab 7.33 abc 34.05 b 269.50 abc 0.675 a 46 21.65 b 99.22 ab 7.24 bc 34.35 b 275.25 abc 0.690 a 47 23.25 ab 80.17 b 9.85 ab 36.75 ab 267.25 bc 0.670 a 48 20.85 b 85.73 ab 7.63 abc 32.95 b 271.50 abc 0.681 a 49 ZB-15 28.73 a 111.20 ab 10.50 a 45.48 a 277.75 abc 0.696 a 50 Totem 19.50 b 73.77 b 8.83 abc 30.95 b 268.75 bc 0.672 a z : Variable identification: Instantaneous carbon dioxide assimilation on leaf area basis (Ala), dry weight (Adwt), chlorophyll content (Achl), and net photosynthetic assimilation (An). Ci, intercellular CO2; Ci/Ca, ratio between air and intercellular CO2. y: Mean separation within each column (genotypes 2 to 50) by Tukey’s HSD test, P≤0.05. 42
43
Table 4.1-7. Steady state instantaneous gas exchange variables of 45 greenhouse-grown F1 Fragaria genotypes (from a single cross), plus their parents, Totem (F. x ananassa) and ZB-15 (F. chiloensis).
z 3 Genotype gr gs gw E WUE * 10 Identific. -2 -1 -2 -1 -2 -1 -2 -1 -1 (mmol m s ) (mmol m s ) (mmol m s ) (mmol m s ) (mol CO2 mol H2O ) 2 76.3 b y 262.58 abc 482.0 ab 6.52 ab 3.32 abc 3 77.9 b 248.84 abc 453.2 ab 6.28 b 3.46 abc 4 79.6 b 243.92 abc 443.0 ab 6.08 b 3.60 a 5 76.6 b 246.16 abc 447.7 ab 6.57 ab 3.22 abc 6 78.3 b 268.46 abc 493.8 ab 6.60 ab 3.33 abc 7 68.5 b 261.65 abc 479.5 ab 6.48 ab 3.08 abc 8 75.4 b 276.06 abc 505.5 ab 6.68 ab 3.23 abc 9 72.1 b 239.95 abc 435.3 ab 6.16 b 3.27 abc 10 80.7 b 276.69 abc 511.5 ab 6.75 ab 3.36 abc 11 67.5 b 248.79 abc 452.7 ab 6.45 ab 3.05 abc 12 69.3 b 301.99 ab 565.7 ab 7.18 ab 2.89 abc 13 73.6 b 246.91 abc 449.3 ab 6.45 ab 3.26 abc 14 68.0 b 252.98 abc 461.7 ab 6.89 ab 2.84 abc 15 70.3 b 180.62 c 316.7 b 6.89 b 3.31 abc 16 74.1 b 272.64 abc 503.5 ab 5.55 ab 2.94 abc 17 74.1 b 310.78 ab 586.2 a 7.71 ab 2.80 c 18 76.9 b 230.64 abc 416.3 ab 6.58 ab 3.19 abc 19 81.7 ab 258.16 abc 472.0 ab 6.17 ab 3.11 abc 20 81.4 ab 251.07 abc 463.0 ab 6.92 ab 3.22 abc 21 78.0 b 211.12 bc 378.0 ab 6.32 b 3.26 abc 22 88.3 ab 280.41 abc 519.0 ab 7.46 ab 3.24 abc 23 81.9 ab 236.07 abc 428.8 ab 6.44 ab 3.40 abc 24 80.3 b 295.91 ab 553.3 ab 7.68 ab 3.00 abc 25 82.9 ab 305.99 ab 574.7 a 7.86 ab 3.00 abc 26 77.2 b 242.40 abc 440.5 ab 6.81 ab 3.11 abc 27 71.8 b 280.82 abc 519.8 ab 7.45 ab 2.79 c 28 71.4 b 286.13 abc 531.5 ab 7.45 ab 2.82 c 31 69.1 b 286.47 abc 534.0 ab 7.24 ab 2.80 c 32 72.6 b 280.38 abc 523.5 ab 7.12 ab 2.95 abc 33 72.5 b 251.38 abc 459.0 ab 6.65 ab 3.07 abc 34 76.4 b 244.92 abc 446.3 ab 6.60 ab 3.22 abc 35 71.7 b 234.68 abc 424.0 ab 6.53 ab 3.05 abc 36 77.3 b 287.65 abc 535.3 ab 7.32 ab 3.00 abc 37 79.3 b 252.29 abc 461.5 ab 6.60 ab 3.31 abc z: For variable identification see end of table. y: Mean separation within each column (genotypes 2 to 50) by Tukey’s HSD test, P≤0.05.
44
Table 4.1-7. (Continued).
Z 3 Genotype gr gs gw E WUE * 10 Identific. -2 -1 -2 -1 -2 -1 -2 -1 -1 (mmol m s ) (mmol m s ) (mmol m s ) (mmol m s ) (mol CO2 mol H2O ) 38 77.9 b y 222.43 abc 401.7 ab 6.20 b 3.44 abc 39 77.1 b 304.51 ab 571.5 ab 7.52 ab 2.97 abc 40 73.9 b 289.22 abc 541.8 ab 7.11 ab 3.02 abc 41 73.3 b 240.18 abc 438.0 ab 6.37 b 3.19 abc 42 73.4 b 263.40 abc 489.3 ab 6.67 ab 3.12 abc 43 74.8 b 220.78 abc 397.3 ab 6.24 b 3.27 abc 44 80.9 b 288.15 abc 536.7 ab 7.10 ab 3.25 abc 45 80.3 b 234.31 abc 423.0 ab 6.55 ab 3.29 abc 46 78.9 b 252.00 abc 460.0 ab 6.56 ab 3.35 abc 47 87.1 ab 251.16 abc 458.0 ab 6.68 ab 3.53 abc 48 77.1 b 241.39 abc 440.7 ab 6.23 b 3.41 abc 49 ZB-15 104.5 a 323.61 a 586.5 a 9.05 a 3.26 abc 50 Totem 72.8 b 204.84 bc 364.7 b 5.52 b 3.59 ab z : Variable identification. gr, leaf residual conductance to the CO2; gs, stomatal conductance to the CO2; gw, leaf conductance to the H2O; E, transpiration rate and WUE, water use efficiency.
y: Mean separation within each column (genotypes 2 to 50) by Tukey’s HSD test, P≤0.05.
upper part of the range (4 and ‘Totem’) and four genotypes in the lower part of the range (28, 17,
31, 27; Table 4.1-7). Even though ZB-15 has the highest gw, as well the highest E, it was not the
least efficient genotype in terms of water use, because ZB-15 also had the highest gs and gr, coupled with the ability to fix more CO2 molecules per unit of time (Ala, An), and per chlorophyll
content (Achl) than some other genotypes (Table 4.1-6), compensating in some degree for its
greater loss of water.
45
4.2 Fluorescence
4.2.1 Selected pest resistant and pest susceptible Fragaria genotypes
F0 observed in 26 genotypes showed no differences among most of them (Table 4.2-1), nor
any trends related to literature's pest resistance characterization. The only differences were
between K19 and Fvi genotypes (the latter with the highest numerical values in the range) when
compared with ‘Totem’ and 88061-4 (both with the lower values in the range; Table 4.2-1).
As Fvi is a species adapted to understory environments and possesses a shade leaf
morphology when under low PPFD conditions (Larson, 1994; Kelley, 1999), some differences in
fluorescence emission compared with sun adapted species can be expected. Logan et al. (1997)
concluded that understory plants must rapidly respond to sunflecks to prevent photooxidative
damage, but also rapidly disengage the protection after the sunfleck has passed.
In this experiment, plants were growing under greenhouse conditions with a PPFD of 300 to
500 µmol m-2 s-1, similar to the upper range of ambient light levels in a typical understory
(Chazdon and Pearcy, 1991). Under shaded conditions, wavelengths between 700 to 750 nm increase up to 10 fold relative to those between 400 and 700 nm (McKiernan and Baker, 1992;
Larcher, 1995). As shade plants possess a lower amount of PSII per unit of chlorophyll than do sun plants (McKiernan and Baker, 1992; Larcher, 1995), they are more prone to photoinhibition
(Öquist, et al., 1992), due to a sudden change to higher PPFD (sunfleck), and, as a response, a
large transient rise in fluorescence is produced (McKiernan and Baker, 1992).
In this context, a first instantaneous response to supraoptimal PPFD could be a high level of
F0 (Demmig and Björkman, 1987). In this research, the intensity of the actinic light of the
fluormeter probe was set to a PPFD of 700 µmol m-2 s-1 (200 to 400 µmol m-2 s-1 higher than
Table 4.2-1. Chlorophyll fluorescence parameters of some greenhouse-grown Fragaria genotypes.
y Genotype F0 Fm Fv Fv/Fm Ft Fq t1/2 z # Name Characteristics (ms) 1 Benton Fxa 319 ab x 1306 a 987 a 0.751 a 214 b 1092 a 70.5 ab 2 CL-5 Fch Pest Res 396 ab 1517 a 1121 a 0.734 a 370 ab 1147 a 53.3 ab 3 88061-1 Adv. Sel. Pest Res 265 ab 1486 a 1221 a 0.817 a 278 ab 1208 a 75.3 ab 4 88061-4 Adv. Sel. Pest Res 215 b 1294 a 1080 a 0.830 a 224 b 1070 a 96.7 a 5 88061-5 Adv. Sel. Pest Res 320 ab 1687 a 1367 a 0.805 a 341 ab 1346 a 66.3 ab 6 88061-6 Adv. Sel. Pest Res 302 ab 1474 a 1172 a 0.775 a 250 b 1224 a 79.8 ab 7 Totem Fxa Pest Sus Std 214 b 1344 a 1131 a 0.833 a 247 b 1098 a 94.0 a 8 GCL-8 Fch Pest Res 405 ab 1609 a 1205 a 0.741 a 331 ab 1278 a 64.0 ab 9 2C6 Adv. Sel Pest Res 322 ab 1315 a 993 a 0.721 a 377 ab 937 a 56.0 ab 10 2F1 Adv. Sel. Pest Res 238 ab 1225 a 987 a 0.802 a 244 b 885 a 78.5 ab 11 Del Norte Fch Pest Res 277 ab 1562 a 1285 a 0.814 a 259 ab 1304 a 67.3 ab 12 O15 Fch High Phot Cap 262 ab 1399 a 1137 a 0.795 a 261 ab 1138 a 61.8 ab 13 P11 Fch High Phot Cap 250 ab 1361 a 1111 a 0.807 a 248 b 1113 a 71.2 ab 14 Y59 Fch High Phot Cap 246 ab 1369 a 1123 a 0.810 a 236 b 1133 a 77.8 ab 15 B10 Fch Low Phot Cap 261 ab 1372 a 1110 a 0.805 a 265 ab 1108 a 63.2 ab 16 K19 Fch Low Phot Cap 392 a 1704 a 1312 a 0.752 a 298 ab 1407 a 55.5 ab 17 R07 Fch Low Phot Cap 370 ab 1475 a 1106 a 0.737 a 255 b 1220 a 60.3 ab 18 ZB-15 Fch Pest Res 293 ab 1593 a 1308 a 0.806 a 284 ab 1321 a 51.8 ab 19 TR-18 Fch Pest Res 265 ab 1234 a 969 a 0.783 a 284 ab 950 a 77.7 ab 20 PNN-6A Fch Pest Res 386 ab 1557 a 1172 a 0.733 a 367 ab 1190 a 67.4 ab z: Fxa, Fragaria x ananassa; Fch, F. chiloensis; Fvi, F. virginiana; Adv. Sel., Advanced selection (F ch x [Fxa]); Pest Res, Pest resistant; Pest Sus, Pest susceptible; Phot Cap, Photosynthetic capacity according to Foote (1994). y: For variable definitions see end of table. x: Mean separation within each column (genotypes 1 to 27) by Tukey’s multiple range test, P ≤ 0.05. 46
Table 4.2-1. (Continued).
y Genotype F0 Fm Fv Fv/Fm Ft Fq t1/2 z # Name Characteristics (ms) 22 ANC-2D Fch Pest Res 341 ab x 1419 a 967 a 0.755 a 287 ab 1133 a 62.7 ab 23 LCO-3H Fch Pest Sus 276 ab 1503 a 1269 a 0.816 a 300 ab 1202 a 80.7 ab 24 COY10A Fch Pest Sus 341 ab 1419 a 967 a 0.755 a 287 ab 1133 a 62.7 ab 25 FRA-472 Fvi Pest Res 431 a 1878 a 1448 a 0.764 a 426 a 1453 a 36.5 b 26 FRA1174 Fvi Pest Sus 458 a 1804 a 1347 a 0.745 a 334 ab 1471 a 61.8 ab 27 ZB-19 Fch Pest Res 268 ab 1360 a 1092 a 0.793 a 272 ab 1088 a 75.2 ab
z: Fxa, Fragaria x ananassa; Fch, F. chiloensis; Fvi, F. virginiana; Adv. Sel., Advanced selection (F ch x [Fxa]); Pest Res, Pest resistant; Pest Sus, Pest susceptible; Phot Cap, Photosynthetic capacity according to Foote (1994).
y : Fluorescence parameters: F0, non-variable fluorescence; Fm, maximal fluorescence; Fv, variable fluorescence (Fm-F0); Fv/Fm, ratio that correlates with the photochemical efficiency of PSII; Ft, terminal steady-state fluorescence; Fq, fluorescence quenching capacity,
and t1/2, half rise time from F0 to Fm. x : Mean separation within each column (genotypes 1 to 27) by Tukey’s multiple range test, P ≤ 0.05. For variable F0, due to variance heterogeneity, the Kruskal-Wallis non-parametric Anova procedure was used. In the latter, for mean separation, means of ranks created by the non-parametric Anova were pairwise compared by the Z test at P≤0.05.
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48
ambient PPFD), which could be the cause of higher F0 observed in both Fvi species, FRA-472
and FRA-1174, (Table 4.2-1; Demming and Björkman, 1987; Ögren and Sjöström, 1990).
Both, in Foote's (1994) research and in the present study, there were not statistically
significant differences in F0 in those Fch genotypes common to both experiments (O15, P11,
Y59, B10, K19 and R07). However, a high standard deviation was observed in these
measurements (data not shown), variability that is not unusual in fluorescence measurements as
reported by Lazár and Nauš (1998). This variability has been related to spectra flattening,
distortion, and reabsorption caused by pigment concentration, differences in leaf thickness, non-
uniform leaf surface, and varying optical properties of cells, masking in some degree the
characteristics of the flourescence itself (Šesták and Šiffel, 1988; 1997), situation that could
contribute to the observed lack of differences between genotypes (Milliken and Johnson, 1992).
No differences were found in Fm, Fv and Fv/Fm among the genotypes (Table 4.2-1), similar
to results reported by Foote (1994) using a number of the same genotypes.
For Ft measurements there were significant differences among genotypes. FRA-472 (Fvi)
had the highest value in the observed range (Table 4.2-1), significantly greater than several
genotypes of differing levels of pest resistance and photosynthetic capacity. As Ft is the terminal
fluorescence level after a decay process from Fm, high values may indicate that light stress is still affecting the leaf. To determine if that is the case, studies of fluorescence and non-photochemical quenching are necessary (Krause and Weis, 1988).
There were no significant differences in Fq as to relate them to the high values of Ft observed in FRA-472. Another estimator of the plastoquinone pool is t1/2 (Fernández-Baco, et.
al., 1998), a variable in which FRA-472 was significantly different from ‘Totem’ and 88061-4,
with the former having a fast time of reaction (36.5 ms vs. 94.0 ms in ‘Totem’; Table 4.2-1). One
possibility is that the faster rise time is related to a greater number of pigment molecules
49
associated with the PSII antenna, a characteristic of shade plants such as FRA-472
(Lichtenthaler, 1988; Larcher, 1995; Lambers et al., 1998). However, the system by which fluorescent energy is dissipated is more complex, where fluorescence rise kinetics depend upon
PSII interconnection, PSII heterogeneity, size of the plastoquinone pool, rate of reoxidation of plastoquinone A, and the rate of electron transport beyond PSI, including carbon metabolism and
+ rate of electron donation to P 680 (Krause and Weis, 1991; Hall and Rao, 1999).
As fluorescence parameters are sensing individual components of a more complex,
integrative process (photosynthesis), intermediate Pearson correlation coefficients are usually
observed between some of them and rates of CO2 assimilation, especially under comparative
situations of stressed and non-stressed plants (Lichtenthaler, 1988; Krause and Weis, 1991;
Demmig-Adams et al. 1997). However, due to the high physiological plasticity of
photosynthesis, fluorescence parameters are not always a good predictor of CO2 assimilation
under normal photosynthetic conditions (Walker, 1988; Jiménez et al. 1997), and additional
variables are usually required in order to assess photosynthetic status (Schreiber, 1983; Krause and Weis, 1988). In the present study, intermediate Pearson correlation coefficients were found between fluorescence (F0, Fv/Fm and t1/2) and photosynthetic (Ala, gr and WUE) parameters
(Table 4.2-2). These results are to be expected because those fluorescence variables are related to
photochemical efficiency of PSII (Krause and Weis, 1988; 1991). The strongest relationship was observed between F0 and gr (r= -0.649, P=0.000/ N=26), where the latter denotes the influence of
intercellular CO2 supply to photosynthesis. If gr is decreasing or is small, F0 will increase
because there are not enough molecules of CO2 to be reduced under normal PPFD conditions
(Walker, 1988; Krause and Weis, 1991). Similarly, if WUE decreases, F0 increases, and in both
situations, with higher or increasing F0, a decrease in Ala can be expected (Carter et al. 1990;
Ögren and Sjöström, 1990).
Table 4.2-2. Pearson correlation coefficients between fluorescence and photosynthetic parameters for selected pest resistance and pest susceptible Fragaria genotypes.
z F0 Fm Fv Fv/Fm Ft Fq t1/2
y x Ala -0.539 -0.281 0.036 0.462 -0.312 -0.257 0.402 (µmol m-2 s-1) (0.004) (0.166) (0.860) (0.018) (0.121) (0.206) (0.041)
Gr -0.649 -0.344 -0.027 0.534 -0.388 -0.323 0.460 (mmol m-2 s-1) (0.000) (0.085) (0.896) (0.005) (0.050) (0.107) (0.018)
gs 0.041 0.052 0.166 0.003 0.089 0.063 -0.0252 (mmol m-2 s-1) (0.841) (0.801) (0.418) (0.987) (0.667) (0.759) (0.903)
E 0.234 0.190 0.220 -0.145 0.231 0.185 -0.207 (mmol m-2 s-1) (0.251) (0.354) (0.281) (0.481) (0.256) (0.367) (0.310)
WUE -0.604 -0.310 -0.064 0.502 -0.385 -0.295 0.510 -1 (mol CO2 mol H2O ) (0.001) (0.123) (0.756) (0.009) (0.052) (0.143) (0.007)
z : Fluorescence parameters: F0, non-variable fluorescence; Fm, maximal fluorescence; Fv, variable fluorescence (Fm-F0); Fv/Fm, ratio that correlates with the photochemical efficiency of PSII; Ft, terminal steady-state fluorescence; Fq, fluorescence quenching capacity, and t1/2, half rise time from F0 to Fm.
y : Photosynthetic parameters: Ala, instantaneous carbon dioxide assimilation on leaf area basis; gr, leaf residual conductance to the CO2; gs, stomatal conductance to the CO2; E, transpiration rate; WUE, water use efficiency.
x : Pearson correlation coefficient. In parenthesis Prob > |R| under H0: Rho=0; N =26
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51
The observed Pearson correlation coefficients between Fv/Fm and t1/2 and Ala, gr and WUE
ranged from 0.402 to 0.534 (both P=0.00; N=26; Table 4.2-2).
4.2.2 Weevil-Plant interaction
When plants of ‘Totem’ and ZB-15 were infested with Black vine weevil (Otiorhynchus
sulcatus), significant differences in F0, Fv/Fm and t1/2 were observed between leaves of non-
infested plants and those with weevil damage (Table 4.2-3). As F0 increased and Fv/Fm decreased
in leaves with weevil damage, PSII photochemical efficiency decreased, a response that has been
associated with environmental stresses (Krause and Weis, 1991, Lambers et al., 1998). The
nature of lower Fv/Fm in leaves with weevil damage could be due to an onset of leaf senescence
(Šesták and Šiffel, 1997), and/or indicating changes in leaf metabolism related to defensive mechanisms, as both could be induced by insect damage (Bazzaz et al., 1987; Gatehouse, 1991;
Baron and Zambryski, 1995).
Statistically significant differences were observed in F0 and Fv/Fm between leaves with and
without weevil damage in weevil infested plants, indicating that a new fluorescence response is
elicited by insect damage (Welter, 1989; Table 4.2-3).
The only parameter statistically different between leaves of plants without weevil infestation
and leaves without damage from weevil-infested plants was t1/2 (Table 4.2-3). As the latter
showed t1/2 values similar to leaves with weevil damage and both were significantly different from leaves of plants without weevil infestation, an early systemic reaction to insect feeding activity may be suggested (Whitham et al., 1991; Baron and Zambryski, 1995). An observed faster t1/2 in non-damaged leaves of plants infested with weevils could be associated with a build
up in the number of chlorophyll molecules in the PSII antenna (Lichtenthaler, 1988). At the same time there were no statistical differences between leaves of plants without weevils and leaves
Table 4.2-3. Chlorophyll fluorescence variables for three levels of Black vine weevil (Othiorhynchus sulcatus) impact on leaves of two Fragaria genotypes (‘Totem’ [F. x ananassa] and ZB-15 [F. chiloensis]).
Factor Weevil Impact Genotype Factors Level No weevils Weevils - Leaf Weevils - Leaf Totem ZB-15 interaction Variable z without damage with damage y x w F0 285 a 276 a 364 b 354 b 263 a NS
Fm 1590 a 1713 a 1632 a 1880 b 1410 a NS
Fv 1305 a 1437 a 1268 a 1526 b 1147 a NS
Fv/Fm 0.821 b 0.837 b 0.774 a 0.810 a 0.812 a NS
Ft 328 a 355 a 323 a 426 b 245 a NS
Fq 1262 a 1358 a 1309 a 1454 b 1165 a NS t1/2 (ms) 73.0 b 59.3 a 55.7 a 51.4 a 73.9 b NS
z : Variable identification: F0, non-variable fluorescence; Fm, maximal fluorescence; Fv, variable fluorescence (Fm-F0); Fv/Fm, ratio that correlates with the photochemical efficiency of PSII; Ft, terminal steady-state fluorescence; Fq, fluorescence quenching capacity, and t1/2, half rise time from F0 to Fm. y: Averages according to a 3x2 Factorial ANOVA (3 levels of weevil impact on leaves and 2 genotypes). x: Mean separation in both factors (genotype and weevil impact) by Tukey’s multiple range test, P≤0.05. w: NS, No significant interaction between factors at P≤0.05.
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53
without damage in weevil-infested plants for other fluorescence or photosynthetic parameters
(Tables 4.2-3 and 4.1-5 respectively). It is not clear if this observation in t1/2 corresponds to an
early stage of a photosynthetic compensatory mechanism to lost leaf area due to weevil damage
(Krischik and Denno, 1983; Welter, 1989; Whitman et al., 1991; Trumble et al., 1993).
Additional experimentation is required in order to observe the evolution of fluorescence and
photosynthetic response to damage during feeding by weevils.
When genotypes ‘Totem’ and ZB-15 were compared, all fluorescence parameters measured
exhibited significant differences with the exception of Fv/Fm, probably due to compensation by
greater PSII efficiency observed in leaves without weevil damage (Table 4.2-3). As there were
no interactions among factors, it appears that these differences are due mainly to genotype.
ZB-15 had lower values of F0 , Ft, and Fm than ‘Totem’, indicating that the latter is dissipating more energy as fluorescence than the former, a response that could be related to a
more efficient flow of electrons through ZB-15's PSII (Öquist, et al., 1992), however, ZB-15 also
had a greater t1/2 , making it more difficult to determine a specific mechanism which explains this general response.
4.2.3 Observations on progeny
Contrary to the observed response in some of the fluorescence variables in the previous section with plants of ‘Totem’ and ZB-15 without insect feeding, fluorescence parameters in this experiment were not significantly different between both genotypes (Table 4.2-4).
For non-variable fluorescence (F0), means of both parents were similar, with 58% of
progeny genotypes distributed above the parental means and 31% below. Only genotypes located
at both extremes ends of the observed distribution of means were statistically different (Table
4.2-4). Similar patterns were observed for parents and progeny for Fm, Fv, and Fq (Table 4.2-4). 54
Progeny genotypes 3, 11, 13, 14 and 33 were clustered at the upper end of the observed range of
means in F0, Fm, Fv, and Fq, while genotypes 24, 34 and 47 were clustered in the lower end of the
range for the same variables. Similarly to F0, statistical differences in Fm, Fv and Fq were only
observed between genotypes at the extreme ends of the ranges of values. Further studies are
required to determine if the consistency observed on the relative positions in the ranges of values
of the same genotypes across variables is an indication of an eventual closeness to each clone's
population mean. This inference is supported by the relationship between variables as F0, Fm, Fv and Fq, which represent different, sequentially timed, phases of the same fluorescence response,
with medium to strong linear associations between them, as Pearson correlation coefficients
between F0 and Fm, Fv and Fq were r=0.742, 0.626 and 0.710 respectively (P=0.000 and N=47),
and between Fm and Fv and Fq were r=0.986 and 0.976 respectively (P=0.000 and N=47).
However, such consistency does not explain the observed photochemical efficiency of PSII
(Fv/Fm; Table 4.2-4), a ratio which is also sensitive to physiological processes beyond the
primary photochemical reactions (Krause and Weis, 1991; Hall and Rao, 1999).
In Fv/Fm there were more F1 genotypes distributed between both parents (Table 4.2-4), but again, only those at the extremes of the range were statistically different. The distribution pattern
is different for Ft however, with ZB-15 closer to the lower end of the range of expression, with
‘Totem’ above ZB-15 and 63% of their progeny located at the upper end of the mean's range. In
Ft, genotypes 2 and 16 at the high end of the mean's range are significantly different from
genotypes 49, 18, 36, 23, 38, 24, and 47, all of them at the lower end of the range, while
genotype 7 is also different from genotype 47. In t1/2 both parents are very similar in the rank of
means, with both at the upper end of the range and statistically different from genotype 13
(Table 4.2-4). Other 11 genotypes at the upper end of the numerical range are statistically
Table 4.2-4. Chlorophyll fluorescence parameters for 45 greenhouse-grown F1 Fragaria genotypes (from a single cross), plus their parents, ‘Totem’ (F. x ananassa) and ZB-15 (F. chiloensis).
z Genotype F0 Fm Fv Fv/Fm Ft Fq t1/2 Identific. (ms) 2 338 abc y x 2013 abc 1675 abc 0.831 abc 462 a 1551 a-e 64.3 abc 3 317 abc 1991 abcd 1674 abc 0.839 abc 417 abc 1574 a-e 72.0 abc 4 265 abc 1889 abcd 1624 abc 0.858 ab 354 abc 1534 a-e 80.0 ab 5 285 abc 1653 abcd 1368 abc 0.821 abc 364 abc 1289 a-f 74.2 abc 6 280 abc 1899 abcd 1619 abc 0.852 ab 365 abc 1533 a-e 64.0 abc 7 328 abc 1983 abcd 1655 abc 0.833 abc 440 ab 1543 a-e 53.5 abc 8 282 abc 1574 abcd 1292 abc 0.818 abc 293 abc 1280 a-f 67.8 abc 9 345 abc 1877 abcd 1532 abc 0.817 abc 382 abc 1496 a-f 65.5 abc 10 256 abc 1625 abcd 1422 abc 0.839 abc 421 abc 1257 b-f 77.8 abc 11 328 ab 2027 abc 1699 abc 0.836 abc 357 abc 1670 ab 56.5 abc 12 339 ab 1617 abcd 1279 abc 0.788 c 323 abc 1295 a-f 55.8 abc 13 328 abc 2052 ab 1724 ab 0.839 abc 430 abc 1622 abc 41.2 c 14 402 a 2067 ab 1664 abc 0.804 bc 387 abc 1680 a 52.8 bc 15 277 abc 1601 abcd 1325 abc 0.824 abc 266 abc 1336 a-f 62.5 abc 16 285 abc 1910 abcd 1625 abc 0.851 ab 461 a 1449 a-f 60.3 abc 17 276 abc 1565 abcd 1289 abc 0.821 abc 277 abc 1289 a-f 91.0 a 18 256 abc 1507 bcd 1252 abc 0.826 abc 264 bc 1244 c-f 68.5 abc 19 244 abc 1524 abcd 1281 abc 0.834 abc 327 abc 1198 def 69.0 abc 20 298 abc 1938 abcd 1640 abc 0.843 abc 343 abc 1596 abcd 69.0 abc z : Fluorescence parameters : F0, non-variable fluorescence; Fm, maximal fluorescence; Fv, variable fluorescence (Fm-F0); Fv/Fm, ratio that correlates with the photochemical efficiency of PSII; Ft, terminal steady-state fluorescence; Fq, fluorescence quenching capacity, and t1/2, half rise time from F0 to Fm. y: Mean separation within each column (genotypes 2 to 50) by Tukey’s multiple range test, P ≤0.05. x : Variable with heterogeneous variances; in this case, a non-parametric Anova procedure was applied (Kruskal-Wallis); means separation was done applying the Z test (P ≤ 0.05) over the ranks created by the non-parametric Anova.
55
Table 4.2-4. (Continued).
z Genotype F0 Fm Fv Fv/Fm Ft Fq t1/2 Identific. (ms) 21 255 abc y x 1534 abcd 1279 abc 0.829 abc 293 abc 1241 c-f 80.5 ab 22 247 abc 1650 abcd 1403 abc 0.850 ab 303 abc 1346 a-f 83.8 ab 23 218 bc 1539 abcd 1320 abc 0.857 ab 258 bc 1281 a-f 83.8 ab 24 236 abc 1486 cd 1250 abc 0.841 abc 253 bc 1233 c-f 71.0 abc 25 266 abc 1484 cd 1206 c 0.808 bc 319 abc 1166 ef 67.0 abc 26 310 abc 1923 abcd 1613 abc 0.839 abc 347 abc 1599 abcd 62.3 abc 27 306 abc 1982 abcd 1676 abc 0.843 abc 404 abc 1577 a-e 57.0 abc 28 290 abc 1879 abcd 1590 abc 0.846 abc 339 abc 1541 a-e 59.0 abc 31 288 abc 1583 abcd 1295 abc 0.817 abc 303 abc 1280 a-f 76.8 abc 32 279 abc 1717 abcd 1439 abc 0.837 abc 334 abc 1383 a-f 68.3 abc 33 319 abc 2079 a 1755 a 0.847 abc 418 abc 1661 ab 66.5 abc 34 223 bc 1413 d 1220 bc 0.847 abc 276 abc 1167 ef 87.3 ab 35 286 abc 1756 abcd 1470 abc 0.836 abc 315 abc 1441 a-f 62.8 abc 36 218 bc 1545 abcd 1327 abc 0.857 ab 263 bc 1282 a-f 74.3 abc 37 253 abc 1695 abcd 1442 abc 0.847 abc 333 abc 1362 a-f 77.0 abc 38 248 abc 1465 cd 1217 bc 0.828 abc 257 bc 1208 c-f 76.8 abc 39 275 abc 1532 abcd 1257 abc 0.815 abc 272 abc 1260 b-f 75.5 abc 40 280 abc 1739 abcd 1459 abc 0.838 abc 358 abc 1381 a-f 76.8 abc 41 280 abc 1559 abcd 1278 abc 0.816 abc 286 abc 1273 a-f 86.3 ab 42 245 abc 1438 d 1193 c 0.827 abc 339 abc 1099 f 83.0 ab z : Fluorescence parameters : F0, non-variable fluorescence; Fm, maximal fluorescence; Fv, variable fluorescence (Fm-F0); Fv/Fm, ratio that correlates with the photochemical efficiency of PSII; Ft, terminal steady-state fluorescence; Fq, fluorescence quenching capacity, and t1/2, half rise time from F0 to Fm. y: Mean separation within each column (genotypes 2 to 50) by Tukey’s multiple range test, P ≤0.05. x : Variable with heterogeneous variances; in this case, a non-parametric Anova procedure was applied (Kruskal-Wallis); means separation was done applying the Z test (P ≤ 0.05) over the ranks created by the non-parametric Anova. 56
Table 4.2-4. (Continued).
z Genotype F0 Fm Fv Fv/Fm Ft Fq t1/2 Identific. (ms) 43 288 abc y x 1704 abcd 1417 abc 0.829 abc 288 abc 1416 a-f 79.5 ab 44 233 bc 1773 abcd 1540 abc 0.868 a 306 abc 1467 a-f 89.5 ab 45 257 abc 1640 abcd 1383 abc 0.841 abc 280 abc 1360 a-f 69.5 abc 46 252 abc 1828 abcd 1576 abc 0.861 ab 367 abc 1461 a-f 73.0 abc 47 210 c 1432 d 1222 bc 0.850 ab 243 c 1189 def 83.8 ab 48 239 abc 1676 abcd 1437 abc 0.856 ab 343 abc 1333 a-f 77.5 abc 49 ZB-15 270 abc 1626 abcd 1356 abc 0.833 abc 264 bc 1362 a-f 79.3 ab 50 Totem 256 abc 1612 abcd 1356 abc 0.841 abc 303 abc 1309 a-f 80.5 ab z : Fluorescence parameters: F0, non-variable fluorescence; Fm, maximal fluorescence; Fv, variable fluorescence (Fm-F0); Fv/Fm, ratio that correlates with the photochemical efficiency of PSII; Ft, terminal steady-state fluorescence; Fq, fluorescence quenching capacity, and t1/2, half rise time from F0 to Fm. y: Mean separation within each column (genotypes 2 to 50) by Tukey’s multiple range test, P ≤0.05. x : Variable with heterogeneous variances; in this case, a non-parametric Anova procedure was applied (Kruskal-Wallis); means separation was done applying the Z test (P ≤ 0.05) over the ranks created by the non-parametric Anova.
57
58
different from genotype 13. For t1/2, 70% of the progeny were below ZB-15, towards the lower
end of the range.
In general, for all variables related to chlorophyll fluorescence, there was a continuous
distribution of means among the progeny, a response typical of quantitative traits. There were
few statistical differences, mainly between genotypes at the extremes of the observed range of
means, due that the phenotypic expression is centered, in most cases, around the parents.
4.3 Leaves Fourth Derivative Chlorophyll’s Absorbance Spectrum
4.3.1 Selected pest resistant and pest susceptible Fragaria genotypes
All chlorophyll a and b 4th-derivative bands found by Chen et al. (1992) in pooled data from
80 Fragaria genotypes were detected in the present study (red dots in Figure 4.3-1). Observed relative frequency of genotypes for each 4th-derivative band was low, ranging between 3.4% for
chlorophyll a peak maxima at 705 nm (Ca705), to 14.7% at chlorophyll a 684 nm peak maxima
(Ca684; Fig. 4.1.3.1). All other characteristic 4th-derivative peak maxima bands cited in Chen et
al. (1992) for chlorophyll a and b or bands without name were detected with intermediate
frequencies in the above range. Five of these (Cb640, Cb652, Cb658, Ca678, Ca684), however,
were not perfectly centered in chlorophylls’ characteristic wavelengths given by French et al.
(1972), but were close enough to be part of the original spectral multiband envelope (Daley, et al., 1986, 1987 c), (Fig. 4.3-1).
Differences between peak maxima observed in this research and those mentioned in the literature as chlorophylls’ “universal peaks of absorption” (French, et al., 1972; Brown and
Schoch, 1981), may reside in the presence of other pigments, different associated proteins or structural components of leaves (Brown and Schoch, 1981; Daley et al., 1987 b; 1987 c; Hobbie, 59
1997), producing genotype-specific leaf absorption spectral characteristics (Brown et al. 1974;
Brown, 1983; Daley, et al., 1987 a, 1987 b, 1987 c; Chen et al., 1992). Also were detected a number of peak maxima not mentioned in the literature along the entire wavelength range scanned (black dots between 600 and 750 nm in Figure 4.3-1 ).
Due to the low frequency of genotypes for each 4th-derivative peak maxima detected in this
research, as well the presence of additional bands not mentioned in the literature, it appears that
the genus Fragaria has considerable variability in 4th-derivative absorbance bands in the entire
chlorophylls’ absorption spectra range (Fig. 4.3-1), which may aid in germplasm identification
(Daley et al., 1986, Daley, et al., 1987 b; Chen et al., 1992, Kelley, 1999), and even might be useful in determining ancestry (Daley et al., 1987b).
Kelley (1999) in studying the 4th-derivative bands of 48 Fragaria genotypes pooled together
found that the spectral band Cb649 was associated with Ala (r=0.49), while Chen et al. (1992),
working with 80 Fragaria genotypes, found a similar relationship (Cb649 with Ala, r=0.66). In
the latter study, no association was observed between the Cb649 4th-derivative band and
chlorophyll a and b content (r= -0.08 and -0.12 respectively), indicating that the relationship is
based on factors other than chlorophyll content. In the present study, Cb649 was detected only
in 14.7% of 27 Fragaria genotypes, suggesting that this association may not be consistent in this genus. No information was given about the relative frequency of Cb649 in Kelley’s (1999) work,
while in Chen et al. (1992), even though an absolute frequency was given, it was referred to the total number of bands detected and not to the total number of genotypes screened. The reason to
calculate frequencies based on the total number of bands, pooling the 4th-derivative peak maxima
of all genotypes together rather than based in the number of genotypes, is the high variability
observed in the data, even in a single leaflet (Chen, C. personal communication). In the present 60
study, in any of its three parts, no genotype showed a relative frequency higher than 55% for any
4th-derivative peak maxima found (based on 240 pooled spectra/genotype), and no higher than
25% when all genotypes’ peak maxima were pooled together (1728 or 3072 pooled spectra per experiment, 16 spectra per genotype).
Twelve chlorophyll 4th-derivative bands (Ca630, Cb635, Cb640, Cb649, Cb660, Cb665,
Ca670, Ca677, Ca684, Ca690, Ca699, Ca710) had very close companion bands (Fig. 4.3-1) that may be either another peak maxima or just spectral envelopes of those mentioned bands (Daley et al., 1987c). Butler and Hopkins (1970a, 1970b) indicated that the positions of 4th-derivative
bands may correspond, but perhaps not precisely, to the wavelength maxima of the individual
components referred to in the original non-derived absorption spectrum. This can occur due to
excessive fragmentation of the absorption bandwidth (Brown and Schoch, 1981), which suggests
that the peak maxima, if observed, may be useful in discriminating molecular differences
between genotypes, but not necessarily in representing differences in function.
Possible spectral envelopes were observed for an additional ten bands (608, 613, 617, 622,
657, 690, 715, 725, 731 and 739 nm) reported in the research of Chen et al. (1992) as seen in
Figure 4.3-1, which were outside the wavelength range that French et al. (1972) found for
chlorophyll a. However, in the present study, if the observed companion bands are actual
spectral envelopes of the 4th-derivative peak maxima in common with Chen et al. (1992), these
spectral envelopes are dispersed in a wider non-symmetrical range than the 95% confidence
intervals calculated in Chen et al. (1992) for each peak maxima. Daley (1990), when validating
the model of French et al. (1972) for chlorophyll 4th-derivative peak maxima also incorporated
“prominent shoulders” to the pooled peak maxima for frequency determination, which indicate
the importance of spectral envelopes in the research of these authors. From these facts and 61
theoretical discussions about the interpretation of 4th- derivative spectra (Butler and Hopkins,
1970a, 1970b; French et al. 1972; Brown and Schoch, 1981; Shrager, 1983; Daley et al. 1988;
Holler et al. 1989; Yoder and Daley, 1990), it appears that the idea that the boundaries
determined by the 4th derivative between peak maxima and spectral envelopes may not be as
clear as the mathematical tool suggests (Butler and Hopkins, 1970a; Brown and Schoch, 1981;
Shrager, 1983). If a specific peak maxima has a spectral envelope with a rather continuous
family of closely associated wavelengths in the amplitudes of peak maxima detected by the 4th- derivative analysis, this may differentiate among genotypes without really detecting the real amplitude which should represent the biological meaning of that family of absorption bands
(Brown and Schoch, 1981; Shrager, 1983). This is especially true if the light absorbance is occurring in the light harvesting antennae pigment-protein complexes, whose specific function is to absorb a wide range of PPFD wavelengths and reduce them by resonance to a single wavelength to be delivered to the respective reaction center (Daley, 1990; Taiz and Zeiger, 1991;
Salisbury and Ross, 1992). Also, light scattering properties of biological materials (Hobbie,
1997), could be a factor in producing non-symmetrical spectral envelopes (Butler and Hopkins,
1970a).
To avoid artifact 4th-derivative bands, Butler and Hopkins (1970a) suggested a validation of
4th-derivative bands by calculating the second derivative curve of the same original spectrum,
which produces a corresponding series of peak minima which should match the wavelengths of
the actual 4th peak maxima. Also, to reduce noise to signal in 4th-derivative spectral analysis,
Daley et al. (1988), suggested the accumulation of about 20-40 spectra per replication. In the
present studies, 16 spectra per replication (leaflet) were taken. 62
To extend the interpretation of 4th-derivative spectra, a possible complementary analytical technique is cluster analysis, which if applied to the peak maxima and spectral envelopes, may produce groupings or families among absorption peaks which share a common biological function. Also, these absorption peak families can be quantitatively measured by their integrated area below the 4th-derivative spectrum curve. In the present study, results of an exploratory cluster analysis performed on peak maxima wavelengths are shown in Figure 4.3-1. Even though for some major chlorophyll peaks the clusters found are in agreement with the presence of shoulder bands (Cb640, Cb649, Cb665, Ca684, Ca710), cluster analysis also separated very close peaks into different groups which biologically may represent a single family of bands
(Ca630, Cb660, Ca673). In addition, some clusters united together peaks that have a clear individual identity in the chlorophyll absorption bands (Cb653 with 660 and Ca695 with 699;
Fig. 4.3-1). As there is no technique that can render unequivocal band identification for in vivo plant material, the best approach to studying chlorophyll absorption spectra appears to be an integrative view which compares and contrasts analytical tools with the known biology of the system under study.
4.3.2 Weevil-Plant interaction
In this experiment, when 4th-derivative spectra of all treatments was pooled together for each genotype, 4th-derivative peak maxima were detected in all intervals in ‘Totem’ and ZB-15, with only three exceptions in the entire wavelength range scanned (600-750 nm). In these cases
‘Totem’ had no band at 723 nm and ZB-15 had no band at 719 and 725 nm (Fig. 4.3-2). In all other bands detected in both genotypes, 4th-derivative peak maxima relative frequency ranges from the same value for both genotypes to a maximum difference between them of 30% at the 63
683-685 nm interval, where peak maxima relative frequencies were 42.5% and 12.5% for
‘Totem’ and ZB-15 respectively (Fig. 4.1.3.2). The 4th-derivative band at 684 nm originates in a
chlorophyll a-protein complex which is simultaneously in the light-harvesting chlorophyll a/b-
protein complexes (LHPC) and the PSII reaction center (Daley, 1990). The difference in relative
frequency observed between ‘Totem’ and ZB-15 at this peak maxima is based on the average of
240 spectra accumulated for each genotype, thus a difference in the PSII/LHPC components can be suggested between ‘Totem’ and ZB-15, with the latter having lower concentration of this molecular entity than ‘Totem’. However, when peak maxima relative frequencies observed over the entire wavelength range (600-750 nm) in both genotypes were compared by a two-sample t- test, no statistically significant differences were detected due to similar pooled averages and standard deviations.
Another wavelength interval that may suggest differences between ‘Totem’ and ZB-15 in
peak maxima leaf absorbance is 650-652 nm, with peak maxima at 651 nm, which was detected
in ‘Totem’ at a frequency of 27.5%, while in ZB-15 only 2.5%. This peak has not been
mentioned in the literature about the genus Fragaria, but it was considered by French et al.
(1972) as part of the peak maxima for Cb649, which in this experiment was detected with low
frequency in both genotypes (2.5% and 7.5% in ‘Totem’ and ZB-15 respectively). The 649 nm
peak originates in chlorophyll b from the LHPC (Brown and Schoch, 1981, 1982; Daley, 1990)
and shifting or broadening of its band is in part a consequence of companion protein molecules.
The integrity or native state of these molecules is destroyed during isolation of chloroplast
membranes or chlorophyll molecules, indicating that the in vivo leaf spectra found by Chen et al.
(1992) and in this research should not necessarily match perfectly the in vitro spectra references
of French et al. (1972) and Brown and Schoch (1982). At the same time, stable differences 64
between in vivo plant material may represent genetic differences (Daley, et al., 1987 a, 1987 b,
1987 c).
Another possible difference between ‘Totem’ and ZB-15 in relative frequency of peak maxima are at 669 nm (Ca670), 701 nm (no name) and 707 nm (Ca703-710), with both genotypes differing 17.5% in relative frequency, and 639 nm (Ca640), 657 nm (no name) and
681 nm (no name) with a 15% of difference in relative frequency. There were other smaller differences in relative frequency between both genotypes, but the variability is likely greater than the apparent differences between both genotypes.
In ‘Totem’, the 737 nm band (no name) had the highest relative frequency (52.5%) detected
in this experiment (Fig. 4.3-2). This band may be related to a more general PT740 peak maxima, which may correspond to phototransformed products (PT) of shorter wavelength originating in chlorophyll-protein complexes (Daley, 1990). The second most frequent bands determined belong to ‘Totem’ at 687 nm (already discussed) and to ZB-15 at 721 nm (PT720), in both cases with a detection frequency of 42.5% (Fig. 4.3-2).
When spectra of leaves from plants without weevils and with weevil damage were compared, complex differences in peak maxima relative frequency were observed (Fig. 4.3-3), however, a two sample t-test applied to the entire wavelength range did not detect statistical differences between both types of leaves. Assuming that the 160 spectra pooled together in this case for peak maxima relative frequency detection are a representative sample for each treatment, the observed relative differences between 4th-derivative spectra of leaves from plants
without weevils and plants with weevil damage ranging between 15 to 25% may be further be studied to isolate eventual spectral responses to leaf damage. A total of eleven peak maxima were detected having relative differences between both types of leaves in the range of 15 to 25%. 65
At 713 nm, a band not mentioned in the literature but which may be associated with the 715 peak
maxima (no name) detected by Chen et al. (1992), had 25% higher peak maxima relative
frequency in damaged leaves of ‘Totem’ when compared with leaves of plants without weevils
of the same cultivar (Fig. 4.3-3). An additional four peak maxima had a 20% difference in
relative frequency between both types of leaves, with three of them (Cb665, Ca705 and PT721)
having lower values in damaged leaves and only at 625 nm peak maxima (no name), did
damaged leaves have a higher value. A 15% difference between damaged and control leaves was
observed at 659 nm (Cb660), 681 nm (Ca680), Ca693, Ca707, PT731, and 733 nm (associated
with PT731). Peak maxima at 659, 681, 713 and 731 nm had higher values in damaged leaves,
while peak maxima at 693, 707 and 733 nm had higher values in non-damaged leaves. Aside
from the possibility of identification of some molecular entities that produce the 4th-derivative
absorption bands with the reported relative differences, there is no information as to why those
molecular components of the photosynthetic machinery showed a change, if statistically
significant, in their relative frequencies observed as a consequence of leaf damage. As the data in
this case was analyzed for a single genotype at a time, it would be expected that fewer bands
would be detected than in pooled data from a population of genotypes, as was the case with
‘Totem’ clones present in the previous experiment, where several 4th-derivative peak maxima
detected there (Fig. 4.3.1), were not present in the experiment discussed here (Fig. 4.3-3). Also,
in those peak maxima bands found in common with the research of Chen et al. (1992), bands at
613 and 649 nm were not present in damaged leaves but they were detected with low relative
frequency in non-damaged leaves ( ≅ 10%). Conversely, bands at 629 nm (Cb630), Ca673,
Ca695, and Ca709 were present only in damaged leaves, also with low relative frequency 66
( ≅ 10%). Due to the low frequency of these bands observed in both cases, no conclusions can be
drawn about these bands.
In ZB-15, four 4th-derivative bands were detected with a 20% difference in peak maxima
relative frequency between leaves of plants without weevils and leaves with weevil damage (629
nm [Cb630], 635 nm [Cb630], 643 nm [no name] and Ca675 (Fig. 4.3-4). Fourteen peaks had a
15% difference in relative frequency between leaves from plants without weevils and leaves of
plants with weevil damage. Among the latter differences, bands at 617 (no name), 623 (no
name), 627 (no name), 641 (Cb640), Cb653, 681 (Ca680), 721 (PT720), and 741 nm (PT740)
had higher relative frequencies in damaged leaves than in leaves of plants without weevils, while
bands at 621 (no name), 629 (Cb630) , 647 (no name), Ca673, 679 (Ca677) and 683 (Ca684) nm
had higher relative frequency in control plants (with no weevils, Fig. 4.3-4).
Among those peak maxima detected in Fragaria by Chen et al. (1992), four peaks were not detected in ZB-15 in the present study (621 nm [no name], Ca703, 715 nm [no name] and 745 nm [4th-derivative marker]). Three additional bands were not present in damaged leaves (607 nm
[4th-derivative marker], 613 nm [no name] and Ca673), but they were detected with low relative frequency (10-15%) in plants without weevils (Fig. 4.3-4).
Given that no statistically significant differences were detected between ‘Totem’ and ZB-15 by a two sample t-test performed over the entire range of pooled wavelengths (600-750 nm),
more research is required to assess if the relative differences observed are a stable physiological
response to weevil leaf damage or if they are a result of sample variability.
67
4.3.3 Observations on progeny
Pooled spectra from 45 progeny genotypes plus their parents studied in this experiment
(3072 spectra) showed an average relative frequency of 10.39% for peak maxima observed, with band detection at 2 nm intervals between 607 to 745 nm. All bands found in the pooled spectra of 80 Fragaria genotypes by Chen et al., (1992) were detected in the present study, with relative frequencies ranging between 5.8% at 635 nm (Cb630) to 23.5% at 739 nm (PT740). As with the other parts of this research, many peak maxima in common with those detected in Fragaria by
Daley et al. (1986; 1987 a; 1987 b; 1988) and Chen et al. (1992) (Fig. 4.3-5, red dots) have companion bands that suggest a family of spectra rather that a single peak maxima (Brown and
Schoch, 1981; Shrager, 1983; Daley et al., 1987 c; Daley, 1990). This was noted by Daley et al.
(1987 a) for Ca 693 in some clones of F. chiloensis, were they observed a “prominent peak envelope” after warm weather, however, in their research, that specific spectral envelope was not present in F. virginiana under the same environmental conditions.
It is interesting to note that some bands not detected in ‘Totem’ and ZB-15 in the weevil- feeding experiment were present in the pooled data from progeny plus their parents, ‘Totem’ and
ZB-15 (629 nm [Cb630], 641 nm [Cb640], Ca695, Ca703, 715 nm [no name]), suggesting that one or both parents have the genes which are encoding for the specific proteins that bind chlorophyll a and b at the LHPC, which produce light absorbance at those wavelengths.
Between 710 and 745 nm two tendencies in relative frequency were observed, one grouping values around 10% of detection and the other clustering frequencies around 18% of detection, which may reflect the genetic heterogeneity of ‘Totem’ and ZB-15, as the lower group of relative frequencies may indicate broad genetic contributions to the parents from progenitor species or ancestry. The latter idea is based on the low relative frequency observed for this wavelength 68 range (710-745 nm) in the first part of this research (Fig. 4.3.1), where there was greater genetic variability than in the latter experiment with progeny and parents. In the upper cluster between
710 and 745 nm (Fig. 4.3-5) the genetic contribution of both parents is apparent, as both of them have high relative frequencies in some bands in this wavelength range (Figs. 4.3-3 and 4.3-4).
25 4th Der. band mentioned in the literature 4th Der. band mentioned for Fragaria in (Chen et al .,1992) 4th Der. band without name
Ca Cb Cb Cb Ca 673 Ca Ca Ca 697 Ca French et al. (1972) chlorophyll bands 630 640 649 653 660 665 670 675 677 684 693 695 699 20 703 710
670.9 649.2 15
684.0 601.6 633.9 656.1 664.2 10 626.1 747.0 612.0 618.0 698.1 642.0 691.0 709.1 5 677.0
715.0 720.2 731.9 737.3 607.2 742.3 596.3 726.1 750.0 0 704.0 596 599 603 607 611 615 619 623 627 631 635 639 643 647 651 655 659 663 667 671 675 679 683 687 691 695 699 703 707 711 715 719 723 727 731 735 739 743 747 750 597 601 605 609 613 617 621 625 629 633 637 641 645 649 653 657 661 665 669 673 677 681 685 689 693 697 701 705 709 713 717 721 725 729 733 737 741 745 749
Figure 4.3-1. Relative frequency of pooled fourth derivative peak maxima of some greenhouse-grown Fragaria genotypes. Histogram resolution is 2 nm. Modified French et al., (1972) chlorophyll nomenclature: Ca, chlorophyll a; Cb, chlorophyll b; the number associated with chlorophyll acronyms corresponds to French’s chlorophyll “universal” peak maxima wavelength in nanometers. Peak maxima wavelength groups generated by cluster analysis are delimited by ellipsoids. For each group, the centroid is indicated in nanometers.
69
60 Totem all * ZB-15 all 4th Der. band without name 4th Der. band mentioned for Fragaria in Chen et al. (1992)
French et at. (1972) chlorophyll Ca Cb Cb Cb Ca 673 Ca Ca Ca 697 Ca 630 50 bands 640 649 653 660 665 670 675 677 684 693 695 699 703 710
40
30
20
* 10 * * * * 0 596 599 603 607 611 615 619 623 627 631 635 639 643 647 651 655 659 663 667 671 675 679 683 687 691 695 699 703* 707 711 715 719 723 727 731 735 739 743 747 750 597 601 605 609 613 617 621 625 629 633 637 641 645 649 653 657 661 665 669 673 677 681 685 689 693 697 701 705 709 713 717 721 725 729 733 737 741 745 749
Figure 4.3-2. Relative frequency of fourth derivative peak maxima for ‘Totem’ (F. x ananassa) and ZB-15 (F. chiloensis) genotypes. Spectra from treatments with and without weevils were pooled together in each genotype and resolved to 2 nm intervals. Lines connecting values observed in ‘Totem’ and ZB-15 are only a visual reference to facilitate genotype comparison. Modified French et al. (1972) chlorophyll nomenclature: Ca, chlorophyll a; Cb, chlorophyll b; the number associated with chlorophyll acronyms corresponds to French’s chlorophyll “universal” peak maxima wavelength in nanometers.
70
60 Totem No Weevils Totem with Weevils Damage 4th Derivative band without name * 4th Der. band mentioned for strawberry in (Chenet al., 1992) * * French et al. (1972) chlorophyll Ca Cb Cb Cb Ca 673 Ca Ca Ca 697 Ca 50 bands 630 640 649 653 660 665 670 675 677 684 693 695 699 703 710
40 * * 30 * * * 20 * * * * * 10 * * ** *** * * * * * * * * 0 596 599 603 607 611*615 619 623 627 631 635 639 643 64*7 651 655 659 663 667 671 675 679 683 687 691 695 699 *703 707 711 *715 719 723 727 731 735 739 74*3 747 750 597 601 605 609 613 617 621 625 629 633 637 641 645 649 653 657 661 665 669 673 677 681 685 689 693 697 701 705 709 713 717 721 725 729 733 737 741 745 749
Figure 4.3-3. Relative frequency of fourth derivative peak maxima for ‘Totem’ (F. x ananassa) being fed on by black vine weevil (O. sulcatus). All replications per treatment were pooled together and resolved to 2 nm intervals. Lines connecting values of each treatment are only a visual reference to facilitate treatment comparison. Modified French et al. (1972) chlorophyll nomenclature: Ca, chlorophyll a; Cb, chlorophyll b; the number associated with chlorophyll acronyms correspond to French’s chlorophyll “universal” peak maxima wavelength in nanometers. 71
60 ZB-15 No ZB-15 with Weevils 4th Der. band without name 4th D*er. band mentioned for strawberry in Chenet al., 1992)
French et al. (1972) Chlorophy* ll Ca Cb * Cb Cb Ca 673 Ca Ca Ca 697 Ca 50 bands 630 640 649 653 660 665 670 675 677 684 693 695 699 703 710
40
30 * * 20 * * * * ** * * ** ** 10 * * ** * * * ** * 0 596 599 603 *607 61*1 615 61*9 623 627 631 635 639 643 647 651 655 659 663 667 67*1 675 679 683 687 691 695 699 703* 707 711 715* 719 723 727 731 735 739 74*3 747 750 597 601 605 609 613 617 621 625 629 633 637 641 645 649 653 657 661 665 669 673 677 681 685 689 693 697 701 705 709 713 717 721 725 729 733 737 741 745 749
Figure 4.3-4. Relative frequency fourth derivative peak maxima for ZB-15 (F. chiloensis) being fed on by black vine weevil (O. sulcatus). All replications per treatment were pooled together and resolved to 2 nm intervals. Lines connecting values of each treatment are only a visual reference to facilitate treatment comparison. Modified French et al. (1972) chlorophyll nomenclature: Ca, chlorophyll a; Cb, chlorophyll b; the number associated with chlorophyll acronyms correspond to French’s chlorophyll “universal” peak maxima wavelength in nanometers. 72
25 F1+Parents Selected Fragaria genotypes
Chla Chlb Chlb Chla 673 Chla 697 Chla 630 640 649 653 660 665 670 675 677 684 693 695 699 703 710 20
15
10
5
0
596 599 603 607 611 615 619 623 627 631 635 639 643 647 651 655 659 663 667 671 675 679 683 687 691 695 699 703 707 711 715 719 723 727 731 735 739 743 747 750 597 601 605 609 613 617 621 625 629 633 637 641 645 649 653 657 661 665 669 673 677 681 685 689 693 697 701 705 709 713 717 721 725 729 733 737 741 745 749
4th Derivative band not mentioned in the literature Chlorophyll a light absortion 4th derivative band (French, 1972) * 4th Derivative band mentioned for strawberry in Chen et. al (1989) Chlorophyll b light absortion 4th derivative band (French, 1972) Figure 4.3-5. Relative frequency of fourth derivative peak maxima for F1 genotypes, plus parents, and 25 selected genotypes according to their pest resistance level. All replications per experiment were pooled togheter and resolved to 2 nm intervals. Lines connecting values of each experiment are only a visual reference to facilitate treatment comparison. Modified Frenchet al. (1972) chlorophyll nomenclature: Ca, chlorophyll a; Cb, chlorophyll b; the number associated with chlorophyll acronyms correspond to French's chlorophyll "universal" peak maxima wavelength in nanometers. 73
74
4.4. Chlorophyll content
4.4.1. Selected pest resistant and pest susceptible Fragaria genotypes
A wide range of chlorophyll a content on a leaf area basis (ChlaLA) was observed among the 27 genotypes included in this study (Table 4.4-1). Pest resistant genotypes were distributed across the entire range of ChlaLA, while pest susceptible genotypes were observed among the lower two thirds of the observed means. No trends in ChlaLA were observed among those genotypes classified by Foote (1994) as having a high (O15, P11 and
Y59) or low photosynthetic capacity (B10, K19, R07; Table 4.4-1).
Chlorophyll b content on a leaf area basis (ChlbLA) showed a smaller range of
-2 variation among genotypes than did ChlaLA (0.072 and 0.250 mg m respectively). For
ChlaLA and ChlbLA, genotypes 2F1, R07, B10 and 88061-4 where at the upper extreme of the numerical range of values, with statistically significant differences only with several genotypes clustered at the lower end of the observed range (Table 4.4-1). Genotypes PNN-
6A, ANC-2D, FRA1174 and FRA472 maintained similar relative positions at the lower end of the range for both ChlaLA and ChlbLA (Table 4.4-1).
Values for total chlorophyll content on a leaf area basis (TChlLA) were lower across species than those values reported for summer conditions for Fragaria by Foote (1994) and
Kelley (1999), but similar to those found in those studies when total chlorophyll was expressed on a dry biomass basis (TchlDwt). Leaves in the current study were thinner than those growing under summer conditions, a response that can be expected in plants growing under low PPFD conditions (Chabot and Chabot, 1977; Lichtenthaler, 1985; Givnish,
1988; Lambers et al., 1998).
Species-specific responses have been reported for leaf chlorophyll content of Fragaria grown under the same environmental conditions (Chabot and Chabot, 1977; Foote, 1994;
75
Kelley, 1999), where leaves of F. virginiana had lower ChlaLA content than those of F. chiloensis (Kelley, 1999). In the present research, FRA472 and FRA1174, both F. virginiana genotypes, were consistently in the lower end of the observed range of means for ChlaLA, ChlbLA and TChlLA, and were statistically different from only a few F. chiloensis genotypes (Table 4.4-1). In TChlDwt, FRA1174 had an intermediate value in the range observed, statistically different from FRA472, where the latter retained its lower position in chlorophyll content (Table 4.4-1), suggesting anatomical and/or morphological differences between both F. virginiana genotypes.
For TChlLA, a relative ranking of genotypes similar to those observed for ChlaLA and
ChlbLA was observed. This was expected as these two variables are components of TChlLA,.
However, when total chlorophyll was expressed as TChlDwt, a different genotype distribution was observed over the numerical range with more homogeneous groups detected by Tukey’s HSD test than for TChlLA (Table 4.4-1), suggesting interaction between leaf anatomy/morphology and chlorophyll content (Chabot and Chabot, 1977;
Wild and Wolf, 1980; Robinson and Osmond, 1994; Murchie and Horton, 1998; James et al. 1999).
The ratio Chla/Chlb is sensitive to the quality and intensity of PPFD (Givnish, 1988;
De la Torre and Burkey, 1990; Robinson and Osmond, 1994; Murchie and Horton, 1998), however, changes in Chla/Chlb are not always related to changes in PSII/PSI stoichiometry and photosynthetic rates (Murchie and Horton, 1998). Under similar PPFD conditions,
Chla/Chlb ratio may be useful in differentiating among genotypes (Araus, et al., 1986;
Givnish, 1988; Murchie and Horton, 1998), as well, between ecotypes (Björkman and
Holmgren, 1963; Givnish, 1988).
Table 4.4-1. Leaf chlorophyll content of selected Fragaria genotypes, according to their pest resistance level.
y Genotype ChlaLA ChlbLA TChlLA TChlDwt Chla/Chlb z -2 -2 -2 -1 Name Characteristics (g m ) (g m ) (g m ) (g kg ) Benton Fxa 0.479 a - f x 0.161 abcd 0.553 abc w 7.21 c - f 2.97 abc CL-5 Fch Pest Res 0.412 b - g 0.145 abcd 0.481 abc 7.27 c - f 2.83 abc 88061-1 Adv. Sel. Pest Res 0.516 a - d 0.176 abc 0.598 abc 8.97 a - e 2.96 abc 88061-4 Adv. Sel. Pest Res 0.532 abc 0.176 abc 0.613 abc 8.87 a - e 3.04 abc 88061-5 Adv. Sel. Pest Res 0.478 a - f 0.159 abcd 0.551 abc 9.11 a - e 3.00 abc 88061-6 Adv. Sel. Pest Res 0.508 a - d 0.168 abc 0.585 abc 9.76 abc 3.02 abc Totem Fxa Pest Sus Std 0.502 a - e 0.158 abcd 0.573 abc 9.41 a - d 3.18 a GCL-8 Fch Pest Res 0.432 a - g 0.145 abcd 0.499 abc 10.75 ab 2.97 abc 2C6 Adv. Sel Pest Res 0.510 a - d 0.164 abcd 0.584 abc 8.74 a - e 3.10 abc 2F1 Adv. Sel. Pest Res 0.575 a 0.190 a 0.662 a 9.53 a - d 3.05 abc Del Norte Fch Pest Res Std 0.490 a - f 0.165 abcd 0.566 abc 11.37 a 2.97 abc O15 Fch High Phot Cap 0.464 a - g 0.146 abcd 0.529 abc 10.04 abc 3.18 a P11 Fch High Phot Cap 0.553 ab 0.174 abc 0.630 ab 11.35 a 3.16 ab Y59 Fch High Phot Cap 0.514 a - d 0.162 abcd 0.586 abc 10.79 a 3.17 a B10 Fch Low Phot Cap 0.545 abc 0.178 abc 0.626 ab 9.59 a - d 3.06 abc K19 Fch Low Phot Cap 0.404 c - g 0.153 abcd 0.479 abc 10.16 abc 2.76 bc R07 Fch Low Phot Cap 0.542 abc 0.182 ab 0.626 a 9.16 a - e 2.98 abc z: Fxa, Fragaria x ananassa; Fch, F. chiloensis; Fv, F. virginiana; Adv. Sel., Advanced selection (F ch x [Fxa]); Pest Res, Pest resistant; Pest Sus, Pest susceptible; Phot Cap, Photosynthetic capacity. y : ChlaLA and ChlbLA, chlorophylls a and b respectively, expressed on leaf area basis; TChlLA, Total chlorophyll on leaf area basis; TChlDwt, Total chlorophyll on dry weight basis; Chla/Chlb, chlorophyll a to b ratio. x: Mean separation within each column (genotypes 1 to 27) by Tukey’s HSD test, P≤0.05. w : Variable with heterogeneous variances; in this case, a non-parametric Anova procedure was applied (Kruskal-Wallis); means separation was done in a pairwise fashion using the Z test at P≤0.05. 76
Table 4.4-1. (Continued).
y Genotype ChlaLA ChlbLA TChlLA TChlDwt Chla/Chlb z # Name Characteristics (g m-2) (g m-2) (g m-2) (g kg-1) ZB-15 Fch Pest Res 0.491 a - f x 0.159 abcd 0.563 abc w 10.77 a 3.08 abc TR-18 Fch Pest Res 0.464 a - g 0.158 abcd 0.538 abc 10.00 abc 2.95 abc PNN-6A Fch Pest Res 0.373 d - g 0.135 bcd 0.439 abc 6.79 def 2.71 c ANC-2D Fch Pest Res 0.357 fg 0.131 cd 0.421 bc 4.47 f 2.72 c LCO-3H Fch Pest Sus 0.428 b - g 0.153 abcd 0.502 abc 7.81 b- e 2.85 abc COY10A Fch Pest Sus 0.428 b - g 0.143 abcd 0.494 abc 8.95 a - e 2.98 abc FRA-472 Fv Pest Res 0.325 g 0.118 d 0.382 c 6.31 ef 2.74 c FRA1174 Fv Pest Sus 0.362 efg 0.130 cd 0.424 bc 9.29 a - d 2.78 abc ZB-19 Fch Pest Res 0.497 a - f 0.157 abcd 0.567 abc 9.74 abc 3.16 ab z: Fxa, Fragaria x ananassa; Fch, F. chiloensis; Fv, F. virginiana; Adv. Sel., Advanced selection (F ch x [Fxa]); Pest Res, Pest resistant; Pest Sus, Pest susceptible; Phot Cap, Photosynthetic capacity. y : ChlaLA and ChlbLA, chlorophylls a and b respectively, expressed on leaf area basis; TChlLA, Total chlorophyll on leaf area basis; TChlDwt, Total chlorophyll on dry weight basis; Chla/Chlb, ratio between chlorophyll a and b. x: Mean separation within each column (genotypes 2 to 50) by Tukey’s HSD test, P≤0.05. w : Variable with heterogeneous variances; in this case, a non-parametric Anova procedure was applied (Kruskal-Wallis); means separation was done in a pairwise fashion using the Z test at P≤0.05.
77
78
In the present study, F. chiloensis genotypes demonstrated a broad range of Chla/Chlb values
(Table 4.4-1). F. chiloensis genotypes O15 and Y59 were significantly different for Chla/Chlb
from K19, ANC-2D, PNN-6A (all F. chiloensis) and FRA472 (F. virginiana). O15 and Y59
were classified by Foote (1994) as having high photosynthetic capacity. While in the present
research O15 and Y59 had means in the upper third of the observed means’ range of Ala, Adwt and An, only a few statistically significant differences were detected with genotypes K19, ANC-
2D, PNN-6A and FRA472, all of them clustered in the lower third in the range of means of the aforementioned photosynthetic variables (Table 4.1-1). While chlorophyll contains the basic components of the photosynthetic machinery, no linear relationship was observed between
Chla/Chlb and Achl as the Pearson correlation coefficient between both variables was 0.04
(P=0.83; N=26; Table 4.4-2).
Chla/Chlb values ranged from 2.71 to 3.18, which are in the same range observed by Kelley
(1999) in Fragaria, although, without a clear differentiation between F. virginiana and F. chiloensis as that author found. In the present research, F. virginiana genotype FRA472 was statistically different from ‘Totem’ and four F. chiloensis genotypes, while FRA1174 (F. virginiana) was not different from any other genotype (Table 4.4-1). All six genotypes previously studied by Foote (1994) (O15, Y59, P11, B10, R07 and K19) had higher values of
Chla/Chlb than those observed by that author, a response contrary to what would be expected due to the winter-growing PPFD conditions prevailing in this experiment (Lichtenthaler, 1985;
Givnish, 1988), where changes in the concentration of chlorophyll a and b are part of adaptive mechanisms to compensate for lower levels of PPFD (James et al., 1999). However, there are reports of higher Chla/Chlb ratio for winter leaves in xerophytic plants of mediterranean
79
Table 4.4-2. Correlation coefficients (Pearson) between chlorophyll content and photosynthetic parameters for selected Fragaria genotypes, according to their pest resistance level.
z ChlaLA ChlbLA TChlLA TChlDwt Chla/Chlb (gm-2) (g m-2) (g m-2) (g kg-1) y x Ala 0.55 0.49 0.54 0.731 0.55 (µmol m-2 s-1) (0.004) (0.011) (0.005) (0.000) (0.003)
Adwt 0.22 0.14 0.20 0.81 0.35 (µmol kg-1 s-1) (0.290) (0.481) (0.003) (0.000) (0.079)
Achl -0.10 -0.51 -0.11 0.0.34 0.04 (µmol mg-1 h-1) (0.619) (0.512) (0.598) (0.086) (0.825)
An 0.54 0.49 0.54 0.73 0.55 -2 -1 (mg CO2 dm h ) (0.004) (0.012) (0.005) (0.000) (0.003)
z : ChlaLA, chlorophyll a content on leaf area basis, ChlbLA, chlorophyll b on leaf area basis; TChlLA, total chlorophyll on leaf area basis; TChlDwt, total chlorophyll on dry weight basis; Chla/Chlb, chlorophyll a to chlorophyll b ratio.
y : Instantaneous carbon dioxide assimilation on leaf area basis (Ala), dry weight (Adwt),
chlorophyll content (Achl), and net photosynthetic assimilation (An).
x : Pearson correlation coefficient. In parenthesis Prob > Runder H0: Rho=0; N=26.
ecosystems (Kyparissis and Manetas, 1993), where summer is typically characterized by water
stress and low growth rates (Montenegro, 1987), conditions that were not present in this study,
but not uncommon to the natural environments where some F. chiloensis ecotypes can be found
(Darrow, 1966; Cameron et al., 1991; Larson, 1994).
Pearson correlation coefficients between ChlaLA and ChlbLA and photosynthetic rates
expressed on different bases demonstrated mixed results (Table 4.4-2). Correlation coefficients
of ChlaLA and ChlbLA with Ala and An ranged from 0.49 to 0.55 (P=0.00-0.01; N=26; Table 4.4-
2), which denotes an intermediate level of association, while correlation coefficients of the same
chlorophyll variables with Adwt and Achl ranged between -0.10 and 0.22 (P=0.29-0.62; N=26),
80
indicating that there was no linear association between the content of both types of chlorophyll
and Achl. Foote (1994) measured chlorophyll content in F. chiloensis during August and
September in two consecutive years and found low correlation coefficients (Pearson) between
ChlaLA and ChlbLA with Ala when measured in August (respectively, r=0.38 and -0.05 the first
year, and 0.16 and -0.13 the second year), while a higher correlation was found for the same
variables in measurements made in September (respectively, r=0.58 and 0.51 the first year and
0.69 and 0.72 the second year). Foote (1994) suggested some nutritional factors prevailing in his
research as a possible cause for the seasonal pattern observed in chlorophyll content and
correlation coefficients. In the present study, leaf sampling for chlorophyll determinations was
done to active growing greenhouse plants in late winter, a period in which photosynthetic rates
were lower than those measured by Foote (1994) in F. chiloensis and similar to those found in
winter in strawberry cv. ‘Nyoho’ growing under greenhouse conditions by Yoshida and
Marimoto (1997). This may have been a partial consequence of the low chlorophyll content
expressed on ChlaLA, ChlbLA and TChlLA bases due to the low incoming PPFD (350-500 µmol
m-2 s-1) (Givnish, 1988; Salisbury and Ross, 1992, James et al., 1999). However, when total chlorophyll content was expressed on dry weight basis (TChlDwt), the highest Pearson correlation
coefficients were observed when TChlDwt was correlated with Ala, Adwt, and An (r=0.73, 0.8 and
0.73; P=0.000 and N=26; Table 4.1.4.2), probably due by the thicker leaves of F. chiloensis
when compared with F. x ananassa (Foote, 1994). The correlation coefficient between TChlDwt and Achl was only 0.34 (P=0.086; N=26; Table 4.4-2), the lowest among the different A basis. A
similar observation was also made in the weevil experiment (next section).
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4.4.2 Plant-weevil interaction
Weevil-damaged leaves showed no statistically significantly differences in ChlaLA, TChlLA and
TChlDwt when compared to leaves of control plants, however, in ChlbLA, damaged leaves had
significantly lower chlorophyll b than did the control (Table 4.4-3). As the contribution of
chlorophyll b to the total chlorophyll content is about 3 times lower than chlorophyll a (Salisbury
and Ross, 1992; Hall and Rao, 1999), the change in ChlbLA was not statistically detected in
TChlLA.
Non-damaged leaves from plants under weevil attack had significantly higher content of
chlorophyll a, b and total chlorophyll (Table 4.4-3) than both, damaged and control leaves,
suggesting a response of a systemic nature, which was originated in, or as a consequence of,
damage to other leaves. As leaves with significantly higher TChlLA and TChlDwt demonstrated no differences in photosynthetic rates (Table 4.1-5), no compensation in photosynthetic rates as a consequence of higher chlorophyll concentration was observed at the time of measurements.
However, among chlorophyll fluorescence parameters, t1/2 was significantly lower in undamaged
leaves of weevil-infested plants (Table 4.2-3), indicating a coordinated response with the
increase of chlorophyll content, as both factors are interdependent (Lichtenthaler, 1988). In the
event that there was a systemic reaction to weevil damage, it may have been detected prior to the
development of a photosynthetic response. Controlled time course studies are required to
accurately determine whether photosynthetic rate increases occur in response to weevil damage to foliage.
As for Chla/Chlb there were interactions among factors (level of weevil impact on leaves and genotype), thus the individual contribution of each factor to the responses observed cannot be isolated. However, all values of Chla/Chlb were above the reported average for C3 plants
(Salisbury and Ross, 1992), a condition that is most likely to occur under high PPFD
Table 4.4-3. Leaf chlorophyll content of ‘Totem’ (Fragaria x ananassa) and ZB-15 (Fragaria chiloensis) genotypes fed on by black vine weevil (Othiorhynchus sulcatus).
Factor Weevil Impact Fragaria Genotype Factors Level No weevils Weevils - Leaf Weevils - Leaf Totem ZB-15 interaction Variable z without damage with damage -2 y x w ChlaLA (g m ) 0.459 b 0.524 a 0.431 b 0.402 b 0.541 a NS
-2 ChlbLA (g m ) 0.133 b 0.158 a 0.115 c 0.114 b 0.157 a NS
-2 TChlLA (g m ) 0.514 b 0.593 a 0.476 b 0.449 b 0.607 a NS
-1 TChlDwt (g kg ) 6.79 b 8.12 a 6.08 b 6.82 a 7.18 a NS
Chla/Chlb 3.47 3.32 3.75 3.56 3.47 S
z : ChlaLA and ChlbLA, respectively, chlorophyll a and b on leaf area basis; TChlLA, Total chlorophyll on leaf area basis; TChlDwt, Total chlorophyll on dry weight basis; Chla/Chlb, chlorophyll a to chlorophyll b ratio. y: Averages according to a 3x2 Factorial ANOVA (3 levels of weevil impact on leaves and 2 genotypes). x: Mean separation in both factors (weevil impact and genotype) by Tukey’s HSD test, P≤0.05. w: NS, Non significant interaction between factors; S, significant interaction, both at P≤0.05.
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83
(Lichtenthaler, 1985; Araus et al., 1986; Givnish, 1988). These Chla/Chlb values were also, on
average (3.52), higher than the reported average for plants in the previous section (2.98),
supporting the assumption stated in that discussion concerning the response of chlorophyll content to the low PPFD conditions prevailing during that experiment.
In comparing genotypes, ZB-15 had significantly higher chlorophyll content than ‘Totem’ as expressed as ChlaLA, ChlbLA and TChlLA, while no differences were detected in TChlDwt (Table
4.4-3). This suggests that F. chiloensis ZB-15’s thicker leaves (Foote, 1994) account for the
difference in chlorophyll content per unit of leaf area, but not per unit of dry biomass. As there
were significant differences in Adwt between ‘Totem’ and ZB-15 (Table 4.1-5), chlorophyll content alone does not explain the higher photosynthetic capacity of ZB-15, but it is a contributing factor along with gr and t1/2.
Pearson correlation coefficients between ChlaLA, ChlbLA and TChlLA with gr were 0.68, 0.58
and 0.66 respectively (P=0.000; N=30; Table 4.1.4.4), while correlations between TChlDwt and
Chla/Chlb with gr were 0.08 and -0.03 (P= 0.67 and 0.85 respectively; N=30). These results,
suggest that chlorophyll content (leaf area basis) and gr play a role in the differences in Ala, Adwt and An observed between ‘Totem’ and ZB-15 (Table 4.1-5).
Pearson correlation coefficients (r) between ChlaLA, ChlbLA and TChlLA with t1/2 were approximately 0.58 (Table 4.4-4), while r between the same chlorophyll variables and F0, FV and
Fm fluctuated between -0.42 and -0.68 (Table 4.4-4). However, Pearson correlation coefficients
between TChlDwt and these three chlorophyll fluorescence variables varied between 0.01 and -
0.31 (Table 4.4-4). Since there was an intermediate degree of association between TChlLA and
fluorescence parameters (Table 4.4-4), the fluorescence response, especially t1/2, is 84
Table 4.4-4. Pearson correlation coefficients between chlorophyll content and some photosynthetic and fluorescence parameters for ‘Totem’ (Fragaria x ananassa) and ZB-15 (Fragaria chiloensis) leaves being fed on by black vine weevil (Othiorhynchus sulcatus).
z ChlaLA ChlbLA TChlLA TChlDwt Chla/Chlb (gm-2) (g m-2) (g m-2) (g kg-1) y x Ala 0.68 0.60 0.67 0.13 -0.07 (µmol m-2 s-1) (0.000) (0.001) (0.000) (0.501) (0.702)
Adwt 0.54 0.51 0.54 0.43 -0.19 (µmol kg-1 s-1) (0.002) (0.003) (0.002) (0.017) (0.323)
Achl -0.10 -0.20 -0.13 -0.51 0.46 (µmol mg-1 h-1) (0.583) (0.287) (0.507) (0.004) (0.010)
An 0.68 0.60 0.67 0.13 -0.07 -2 -1 (mg CO2 dm h ) (0.000) (0.001) (0.000) (0.498) (0.706)
gm 0.68 0.58 0.66 0.08 -0.03 (mmol m-2 s-1) (0.000) (0.000) (0.000) (0.674) (0.854)
F0 -0.68 -0.65 -0.68 -0.31 0.30 (0.000) (0.000) (0.000) (0.091) (0.109)
Fm -0.64 -0.54 -0.62 -0.08 0.01 (0.000) (0.002) (0.000) (0.679) (0.953)
Fv -0.54 -0.42 -0.51 0.01 -0.08 (0.002) (0.020) (0.004) (0.977) (0.679)
T1/2 0.58 0.53 0.58 0.20 -0.18 (0.001) (0.003) (0.001) (0.301) (0.345)
Fq -0.63 -0.52 -0.61 -0.18 0.02 (0.000) (0.003) (0.000) (0.340) (0.910) z : ChlaLA, chlorophyll a content on leaf area basis, ChlbLA, chlorophyll b on leaf area basis; TChlLA, total chlorophyll on leaf area basis; TChlDwt, total chlorophyll on dry weight basis; Chla/Chlb, chlorophyll a to chlorophyll b ratio.
y : Instantaneous carbon dioxide assimilation on leaf area basis (Ala), dry weight (Adwt), chlorophyll content (Achl), and net photosynthetic assimilation (An). gr, CO2 residual conductance; F0, non-variable fluorescence; Fm, maximal fluorescence; Fv, variable
fluorescence (Fm-F0); t1/2, half rise time from F0 to Fm and Fq, fluorescence quenching capacity.
x : Pearson correlation coefficient. In parenthesis Prob > Runder H0: Rho=0; N=30. 85
also dependent on components other than chlorophyll content, which may also have contributed
to the apparent systemic response observed in t1/2 (Table 4.2-3); Fernández-Baco, et al., 1998), as
previously discussed in the fluorescence section.
4.4.3. Observations on progeny
ChlaLA content observed in this experiment was higher than in the other two experiments,
with an average across genotypes of 0.475 g m-2 and a range between 0.384 and 0.541 g m-2.
‘Totem’ and ZB-15, genotypes common to all three experiments carried out in this research, had
ChlaLA, ChlbLA, TChlLA and TChlDwt averages (Table 4.4-5) similar to those observed in
comparing genotypes in the experiment with weevils (Table 4.4-3), but higher than in the first
experiment.
For ChlbLA and TChlLA, ZB-15 had the highest average, being significantly greater than 5
(ChlbLA) and 2 (TChlLA) progeny genotypes (Table 4.4-5), while ‘Totem’ was in the lower third
of the numerical range for ChlbLA and TChlLA and with no statistical differences with other genotypes (Table 4.4-5). The proportion of genotypes with means between their parents was
64% for ChlbLA and 71% for TChlLA , while 36% and 29% genotypes, respectively, were below
‘Totem’. The results observed for ZB-15 in ChlaLA, ChlbLA and TChlLA (Table 4.4-5) are in
addition to high values observed in gr for this genotype (Table 4.4-6), in explaining, in part, the
high photosynthetic rates (Ala, An) that were observed for this genotype (Table 4.1-6). As was
observed for gr, no progeny genotype had values above ZB-15 in ChlaLA, ChlbLA and TChlLA.
However, in TChlDwt, the relative positions of genotypes along the numeric range of means was
different, with 29 progeny genotypes above ZB-15, and ‘Totem’ positioned in the low extreme
Table 4.4-5. Chlorophyll content of leaves of 45 greenhouse-grown F1 Fragaria genotypes (from a single cross), plus their parents, Totem (F. x ananassa) and ZB-15 (F. chiloensis). z Genotype ChlaLA ChlbLA TChlLA TChlDwt Chla/Chlb Identification. (g m-2) (g m-2) (g m-2) (g kg-1) 2 0.443 abc y 0.113 abcd 0.485 abc 9.73 abc 3.92 a 3 0.443 abc 0.113 abcd 0.485 abc 9.03 abc 3.92 a 4 0.473 abc 0.116 abcd 0.515 abc 10.23 abc 4.09 a 5 0.482 abc 0.125 abcd 0.530 abc 11.48 abc 3.86 a 6 0.429 abc 0.113 abcd 0.473 abc 8.80 abc 3.82 a 7 0.392 bc 0.100 cd 0.430 bc 9.94 abc 3.93 a 8 0.469 abc 0.116 abcd 0.511 abc 9.70 abc 4.05 a 9 0.437 abc 0.108 bcd 0.475 abc 8.91 abc 4.10 a 10 0.492 abc 0.123 abcd 0.537 abc 10.22 abc 4.01 a 11 0.442 abc 0.111 abcd 0.483 abc 10.52 abc 4.00 a 12 0.502 abc 0.129 abcd 0.551 abc 9.00 abc 3.88 a 13 0.478 abc 0.120 abcd 0.523 abc 11.24 abc 3.98 a 14 0.436 abc 0.115 abcd 0.481 abc 11.57 ab 3.80 a 15 0.487 abc 0.125 abcd 0.534 abc 10.41 abc 3.91 a 16 0.490 abc 0.130 abcd 0.541 abc 9.30 abc 3.76 a 17 0.447 abc 0.115 abcd 0.491 abc 8.47 bc 3.89 a 18 0.463 abc 0.115 abcd 0.504 abc 11.98 a 4.04 a 19 0.490 abc 0.124 abcd 0.535 abc 9.52 abc 3.96 a 20 0.417 abc 0.105 bcd 0.456 abc 9.19 abc 3.98 a 21 0.490 abc 0.125 abcd 0.537 abc 10.57 abc 3.91 a 22 0.499 abc 0.126 abcd 0.546 abc 11.16 abc 3.98 a 23 0.489 abc 0.121 abcd 0.533 abc 8.89 abc 4.05 a 24 0.485 abc 0.126 abcd 0.533 abc 11.05 abc 3.85 a z : Chla LA, ChlbLA and TChlLA chlorophyll a, b and total chlorophyll expressed on leaf area basis; TChlDwt, Total chlorophyll on dry weight basis; Chla/Chlb, chlorophyll a to b ratio.
y: Mean separation within each column (genotypes 2 to 50) by Tukey’s HSD test, P≤0.05. 86
Table 4.4-5. (Continued). z Genotype ChlaLA ChlbLA TChlLA TChlDwt Chla/Chlb Identification. (g m-2) (g m-2) (g m-2) (g m-2) 25 0.457 abc y 0.118 abcd 0.502 abc 10.16 abc 3.87 a 26 0.508 abc 0.130 abcd 0.557 abc 11.49 abc 3.91 a 27 0.449 abc 0.116 abcd 0.494 abc 11.35 abc 3.88 a 28 0.494 abc 0.126 abcd 0.541 abc 11.74 ab 3.92 a 31 0.488 abc 0.127 abcd 0.534 abc 9.44 abc 3.86 a 32 0.421 abc 0.107 bcd 0.461 abc 10.12 abc 3.92 a 33 0.384 c 0.095 d 0.419 c 11.17 abc 4.03 a 34 0.516 ab 0.128 abcd 0.563 abc 11.45 abc 4.03 a 35 0.471 abc 0.120 abcd 0.517 abc 11.48 abc 3.91 a 36 0.503 abc 0.122 abcd 0.547 abc 10.92 abc 4.12 a 37 0.522 a 0.134 abc 0.573 ab 9.72 abc 3.86 a 38 0.500 abc 0.126 abcd 0.547 abc 10.28 abc 3.98 a 39 0.510 abc 0.139 ab 0.564 abc 9.96 abc 3.67 a 40 0.477 abc 0.123 abcd 0.523 abc 10.38 abc 3.90 a 41 0.485 abc 0.122 abcd 0.530 abc 10.24 abc 3.98 a 42 0.504 abc 0.129 abcd 0.553 abc 10.39 abc 3.89 a 43 0.524 a 0.136 ab 0.575 ab 11.30 abc 3.87 a 44 0.469 abc 0.129 abcd 0.521 abc 9.07 abc 3.68 a 45 0.427 abc 0.110 abcd 0.469 abc 10.65 abc 3.90 a 46 0.518 ab 0.132 abc 0.567 abc 11.21 abc 3.94 a 47 0.525 a 0.135 abc 0.576 ab 8.50 bc 3.90 a 48 0.512 ab 0.135 abc 0.564 abc 9.90 abc 3.78 a 49 ZB-15 0.541 a 0.144 a 0.597 a 9.91 abc 3.78 a 50 Totem 0.451 abc 0.118 abcd 0.496 abc 8.05 c 3.84 a z : Chla LA, ChlbLA and TChlLA chlorophyll a, b and total chlorophyll expressed on leaf area basis; TChlDwt, Total chlorophyll on dry weight basis; Chla/Chlb, chlorophyll a to b ratio.
y: Mean separation within each column (genotypes 2 to 50) by Tukey’s HSD test, P≤0.05. 87
88
of the range (Table 4.4-5). As observed for TChlDwt, ZB-15 was not significantly different from the other genotypes and ‘Totem’ was different only from progeny genotypes 18, 28, 14. Thus it can be concluded that the progeny’s chlorophyll content, independent of the basis in which it is expressed, is very close to that of the parents and that the statistical differences observed have a component of leaf morphology as an interacting factor.
For Chla/Chlb, no significant differences were observed in this study (Table 4.4-5), however, the observed means were higher than those reported for Fragaria genotypes growing under summer field conditions for two consecutive years in two different studies (Foote [1994], and
Kelley [1999]). However, a third year of measurements undertaken by Kelley (1999) reported Chla/Chlb values similar to those observed in this experiment. Based on the results of this research and of Chabot and Chabot (1977), Foote (1994) and Kelley (1999), it is safe to assume than in Fragaria there is a seasonal and year to year variation in the content of chlorophyll (leaf area basis), and also in Chla/Chlb. The range of values observed in Chla/Chlb in this experiment (3.67 - 4.13; Table 4.4-5) were similar to those mentioned by Lichtenthaler
(1985) for leaves of several plant species growing in sunny and extremely sunny environments, even though, in this experiment, plants were under greenhouse conditions, receiving less total and PPFD light than under field conditions.
Considering the numerical range of the genotype means only, both parents were at the lower end of the range, with just three progeny genotypes below them (Table 4.4-5).
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4.5. Leaf Protein
4.5.1. Selected pest resistant and pest susceptible Fragaria genotypes
Leaf total soluble protein content of several species and subspecies of Fragaria was studied
by Kelley (1999), who found higher soluble protein content, on a leaf area basis, in F. chiloensis
when compared with F. x ananassa and F. virginiana. No differences, however, were observed
between these species when protein content was expressed on fresh and dry weight bases. In the present study, a high variability in total soluble protein was observed among genotypes (dry weight basis), with a range of 5.99 to 26.03 mg g-1 (Table 4.5-1). This range indicates a broad
phenotypic expression in Fragaria genotypes and agrees with the concept that for each type of
leaf structure and life span there is a particular balance in the use of photosynthates for protein
synthesis in order to meet the requirements of specific environmental conditions (Givnish, 1988;
Chiariello et al., 1992; Larcher, 1995; Lambers et al., 1998). This occurred even though, the plants in this study were grown under the same low PPFD conditions.
Alpert and Mooney (1986) reported that nitrogen allocation within the whole plant in F.
chiloensis (and presumably in other species in this genus), follows a seasonal pattern dictated by
the presence and developmental stage of runners, which represent a sink for nitrogen from the
mother plant’s leaves. Since the optimization of nitrogen use changes significantly only when the
plant is actually limited by the availability of inorganic nitrogen (Stitt and Shulze, 1994), and
since leaf nitrogen is largely present in chloroplasts, especially in the form of Rubisco (Küppers,
1996, Lambers et al., 1998), those findings of Alpert and Mooney (1986) may represent an
indirect reference for leaf protein partitioning in Fragaria.
In the present study, as protein content was determined in leaves of mother plants, and with
most of the genotypes having runners of different developmental stage and/or size, part of the
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variability observed in total soluble protein may be related to ontogenic genotype-specific
nitrogen partitioning patterns within the whole plant (Alpert and Mooney, 1986, Givnish, 1988;
Larcher, 1995; Lambers et al, 1998). Also, as these leaves developed in a relatively low PPFD environment (300-500 µmol m-2 s-1), they can be expected to have a lower total soluble protein
content than those which developed under higher light conditions (Givnish, 1988; Lambers et al.,
1998). This observation is valid in the present research with ‘Totem’ and ZB-15, genotypes that were also used in the two other experiments carried out in late summer, where the total soluble protein content observed in late winter was 38.2% and 27.6% of the average of both summer experiments for ‘Totem’ and ZB-15 respectively.
Seven homogeneous groups of genotypes were detected by the Tukey’s HSD test in which the means were not significantly different from one another. No pest-susceptible genotype was above the 60th percentile for total soluble protein content (12.78 g g-1 dwt, Table 4.5-1), and no
trend was observed below this percentile among genotypes classified according to their pest
resistance level. Also, no trend was observed in total soluble leaf protein content among F. chiloensis genotypes which Foote (1994) described as having high (O15, P11 and Y59) or low
(B10, K19 and R07 ) photosynthetic capacity (Table 4.5-1).
Shade tolerant F. virginiana genotypes FRA-472 and FRA-1174 were near the 50th percentile
(11.35 g g-1 dwt) in the range of total soluble protein. Both FRA-472 and FRA-1174 were
significantly different from Del Norte and 88061-5 (F. chiloensis and F1 of (F. x ananassa) x F. chiloensis respectively; Table 4.5-1).
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Table 4.5-1. Leaf total soluble protein, Ribulose 1,5-biphosphate carboxylase/oxygenase (Rubisco) content and percentage of Rubisco of total soluble protein content of selected, according to their pest resistance level, Fragaria genotypes.
Genotype Total Soluble Rubisco Rubisco Proportion z Name Characteristics Protein Content of Total Soluble (mg g-1 dwt) (mg g-1 dwt) Protein (%) Benton Fxa 8.17 e-g y 4.04 c-g 51.4 ±18.3 w CL-5 Fch Pest Res - x - - 88061-1 Adv. Sel. Pest Res 9.08 d-g 3.99 d-g 46.4 ±11.6 88061-4 Adv. Sel. Pest Res 12.94 c-g 5.76 b-g 45.9 ±12.5 88061-5 Adv. Sel. Pest Res 23.47 ab 9.38 a 39.7 ± 3.9 88061-6 Adv. Sel. Pest Res 8.95 d-g 3.75 e-g 43.3 ±10.1 Totem Fxa Pest Sus Std 7.53 e-g 3.96 d-g 53.2 ± 6.6 GCL-8 Fch Pest Res 15.20 b-f 7.59 a-c 51.0 ± 6.8 2C6 Adv. Sel Pest Res 10.12 c-g 4.84 c-g 47.9 ± 4.6 2F1 Adv. Sel. Pest Res 11.61 c-g 4.09 c-g 37.3 ±12.3 Del Norte Fch Pest Res 26.03 a 8.71 a-b 35.2 ±10.5 O15 Fch High Phot Cap 17.75 a-d 6.79 a-f 40.1 ±15.3 P11 Fch High Phot Cap 19.21 a-c 7.52 a-d 37.8 ± 7.1 Y59 Fch High Phot Cap 11.97 c-g 4.59 c-g 38.3 ± 7.1 B10 Fch Low Phot Cap 13.89 c-g 5.78 b-g 47.1 ±16.6 K19 Fch Low Phot Cap 17.48 a-d 7.10 a-c 41.6 ±12.1 R07 Fch Low Phot Cap 7.91 e-g 2.95 g 37.9 ± 6.3 ZB-15 Fch Pest Res 16.34 b-e 8.43 ab 52.5 ± 8.5 TR-18 Fch Pest Res 12.58 c-g 5.72 b-g 46.2 ± 6.1 PNN-6A Fch Pest Res - - - ANC-2D Fch Pest Res 6.32 fg 2.98 g 47.9 ± 8.3 LCO-3H Fch Pest Sus 5.99 g 3.21 fg 52.6 ± 8.8 COY10A Fch Pest Sus 8.74 d-g 4.54 c-g 51.9 ± 1.5 FRA-472 Fv Pest Res 11.09 c-g 4.14 c-g 38.8 ± 9.4 FRA1174 Fv Pest Sus 12.31 c-g 5.14 b-g 41.6 ± 8.4 ZB-19 Fch Pest Res 9.43 d-g 4.73 c-g 50.6 ± 9.5 z: Fxa, Fragaria x ananassa; Fch, F. chiloensis; Fv, F. virginiana; Adv. Sel., Advanced selection (F ch x [Fxa]); Pest Res, Pest resistant; Pest Sus, Pest susceptible; Phot Cap, Photosynthetic capacity according to Foote (1994).
y: Mean separation within each column by Tukey’s HSD test (P ≤ 0.05).
w: No statistically significant differences were detected in this variable. Statistical analysis was performed to the angular transformation x = arcsine % . Data presented is the original percentage and its standard deviation.
x: Missing replications.
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Normally, in studies of plant adaptation to different irradiant levels, the photosynthetic rate is expressed as function of leaf dry weight or protein content in order to indirectly incorporate leaf construction costs (Givnish, 1988). In the present study, the Pearson correlation coefficient between Adwt and total soluble protein content on a dry weight basis was 0.59 (P=0.002; N=24),
the highest value among the different bases for expression of A. In Kelley’s (1999) study, the
Pearson correlation coefficient between Adwt and total soluble protein content also showed the
highest value, however, the degree of association found by that author was stronger (r=0.99;
P=0.01 and N=48) than in the present research. In the present study, Fv was the only other
photosynthetic parameter which had some degree of linear association with the total soluble
protein content (r=0.45; P=0.026 and N=24), which may reflect the protein component of the
chlorophyll a-protein complex of PSII antenna, the source of the photosynthetic fluorescence
emission (Krause and Weis, 1991).
Jiang et al. (1993) demonstrated for soybean leaves that one of the primary regulators of photosynthesis at the physiological level is content of the Rubisco holoenzyme, the molecule that represents, on average, 40% of the leaf total soluble protein, with a range between 10% to 80% depending on the plant species (Huffaker, 1982). Foote (1994), working with eight F. chiloensis genotypes, found that Rubisco was, on average across genotypes and measurement dates, 40% of the total soluble protein in the leaf. In the present study, Rubisco was, on average across genotypes, 44.8% of the total soluble protein content of the leaf. The range of relative Rubisco content (on a total soluble protein basis) reported by Foote (1994) was 34% to 46%, while in the present study it was 35.2% to 53.2% (Table 4.5-1). The higher upper limit in relative Rubisco content observed in the present study probably reflects the greater diversity of genotypes
screened compared to Foote’s (1994) research, as well as because of the greater variability
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observed across genotypes for total soluble protein content (Table 4.5-1). The Pearson
correlation coefficient between Rubisco and total soluble protein content was r=0.94 (P=0.000;
N=24), indicating a high degree of linear association between these variables. Nine out of ten
genotypes that were above the 60th percentile in total soluble protein content were also in the
same group in Rubisco content (Rubisco 60th percentile = 5.63 g g-1 dwt). The only exception for
Rubisco content was the genotype TR-18, which was immediately below the 60th percentile. As
was also observed for protein content, no pest susceptible genotypes were present above the 60th percentile and no trend was observed below it for both pest resistance level and photosynthetic capacity (Table 4.5-1).
‘Totem’ and ZB-15 Rubisco content were lower than that observed in the same genotypes in an experiment carried out in late summer (50.1% and 75.3% of the summer level respectively), which agrees with the common observation in C3 plants that under low PPFD, Rubisco content is
lower than in leaves of the same plant or species under full sunlight (Huffaker, 1982; Givnish,
1988; Eskins et al., 1991).
Moore et al., (1998) indicated that leaf Rubisco content can be used as a biochemical
indicator of the photosynthetic capacity of a species, since within a given species adjustments in
Rubisco content commonly result in corresponding adjustments in photosynthetic rate. The
previous statement agrees with the observed differences in photosynthetic capacity in ‘Totem’
and ZB-15 when both were measured in late winter and summer. However, in comparing the
photosynthetic capacity of different species, in addition to the Rubisco concentration modulated
by the long term PPFD level, there is also a short term response of Rubisco to transient increases
in PPFD (sunfleks or IRGA’s set PPFD). In this situation, Rubisco’s specificity factor, which
indicates the partitioning of carboxylase and oxygenase functions of the enzyme, may play an
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even more important role than the enzyme’s concentration in determining the photosynthetic
performance of different genotypes (Evans and Seeman, 1984; Kent and Tomany, 1995).
4.5.2. Weevil-Plant interaction
In this experiment, only leaf total soluble protein content was measured. For this variable a
significant difference between ‘Totem’ and ZB-15 was detected, but there were no statistical
differences in total protein content among plants attacked by weevils compared to controls
(Figure 4.5-1), indicating that there was no significant response to direct weevil damage. There
was also no change in the protein content of non-damaged leaves of weevil infested plants. This
would indicate the lack of a systemic reaction impacting protein content under the reported experimental conditions. However, specific defensive-oriented proteins are one of the common mechanisms used by plants to limit damage by herbivores (Ryan, 1983; Waterman and Mole,
1989; Baron and Zambryski, 1995; Tomlin and Borden, 1997). The pest resistant genotype ZB-
15 appears to have a higher level of total soluble proteins compared to ‘Totem’, the pest susceptible standard genotype, thus the possibility that a fraction of the ZB-15 soluble protein content may have a constitutive defensive role (Ryan, 1983; Givnish, 1988; Chiarello, et al.,
1992; Konarev, 1996; Tomlin and Borden, 1997) can not ruled out. This possibility requires additional research in order to be confirmed.
Coley et al. (1985) mentioned that, in comparing defensive strategies between plant species, defensive allocation should be greater in plants growing in less productive sites, as is the natural environment of ZB-15 (Ziolkouski Beach Park, Winchester Bay, Oregon; Doss and Shanks,
1988). This may suggest that if a plant species has a high photosynthetic capacity even under those limiting conditions, it may still be feasible from a bioenergetic point of view, that a
95 proportion of its photosynthates would be allocated to defensive proteins (Givnish, 1988). In such marginal environments, in general, plants rely on root fungal symbionts as an aid in the uptake of mineral nutrients (Brundrett, 1991; Tobar et al., 1994). In strawberry there are reports of commercial varieties that demonstrate positive effects of vesicular-arbuscular mycorrhizal fungi in the plant’s mineral nutrition (Werner et al., 1990; Paraskevopoulou-Paroussi, 1997), growth and yield (Niemi and Vestberg, 1992; Paraskevopoulou-Paroussi, 1997), and protection from pathogen and arthropods, among them, black vine weevil (Gange at al., 1994). As mycorrhizal fungi are a direct cost of a plant’s photosynthates (Wang et al., 1989), those with a high photosynthetic capacity should be able to withstand higher levels of mycorrhizal infection, and should, in return, obtain enough mineral nutrients to complete the life cycle, especially in nutritionally-poor edaphic environments (Stahl et al., 1988). Apparently there is no information about levels and specificity of mycorrhizal infection in Fragaria plants under natural conditions, nor concerning correlations of mycorrhizal infection and the plant’s competitiveness in natural and agricultural plant communities. This is an important line of research, especially with principles of sustainable agriculture extending to intensively cultivated commercial crops such as strawberry (Gliessman et al., 1996; Altieri, 1995).
Considering that in the other two experiments of this research there were no statistical differences between ‘Totem’ and ZB-15 in Rubisco’s relative content on a total soluble protein basis, it can be expected that the higher protein concentration observed in ZB-15 in the present study (Fig. 4.5-1) may also suggest a higher Rubisco content compared to ‘Totem’, but further research is needed to confirm this possibility.
96
120
100
80
60 Totem 40 ZB-15 20
0
-20
Treatment
Factor Weevil Impact Genotype Level No weevil No damage Damage Totem ZB-15 Tukey HSD 48.9 a 41.1 a 42.3 a 16.2 a 72.0 b P 0.05
Figure 4.5-1 . Total soluble leaf protein content of 'Totem' ( Fragaria x ananassa ) and ZB-15 ( F. chiloensis ) genotypes being fed on by Black vine weevil ( Othiorhynchus sulcatus ). Averages in the Table are from a 3x2 factorial ANOVA Mean separation by Tukey's HDS Test (P< 0,05).
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4.5.3. Observation on progeny
In this evaluation carried out in late summer, total soluble protein content averaged 23.82 mg g-1 dwt across genotypes, with a range between 12.45 and 46.29 mg g-1 dwt (Table 4.5-2).
There were no statistically significant differences between ‘Totem’ and ZB-15, the parent genotypes. However, ZB-15 had the highest total soluble protein content, statistically different from 17 progeny genotypes, 16 of them below the 50th percentile (21.46 mg g-1 dwt). ‘Totem’, with an average of 23.25 mg g-1 dwt was very close to the 60th percentile (23.37 mg g-1 dwt).
Forty percent of the progeny genotypes had means between both parents. As ‘Totem’ was not significantly different from any progeny genotype, the variation for total soluble protein of this parent was in the same range of variation as its F1 progeny. Other statistical differences were detected between genotype 36 and genotypes 5, 19, 6 and 17, as well between genotype 14 and genotypes 19, 6 and 17. No other pairwise genotype combinations were found to be significantly different.
For Rubisco content, no significant differences were found between parents, nor when each parent was compared to the progeny. The only statistically significant difference was detected between progeny genotypes 33 and 16 (Table 4.5-2). For progeny distribution along the observed range of values, only genotype 33 had a mean in the 90th percentile, while ZB-15 was immediately below it. The position of ‘Totem’ in the range was above the 75th percentile, however, the variability of the data indicates that the progeny genotypes with means below this point may have individual replication values in any position below the 90th percentile.
The relative proportion of Rubisco over total soluble protein content was 41.7% and 23.6% for ‘Totem’ and ZB-15, proportions very different from values observed in the same genotypes in the experiment carried out in late winter (53.15% and 52.51% respectively). Foote (1994)
98
found for Fragaria chiloensis genotypes K19 and O15, in a second year of measurements, an
increase in Rubisco content of 31 and 35% respectively. The present research suggests that
seasonal variation in Rubisco content may exist in Fragaria as for ‘Totem’ and ZB-15 the
observed means were respectively 7.90 and 10.19 mg g-1 dwt in summer versus 3.96 and 8.43 mg
g-1 dwt in late winter. Considering similar observations across seasonal variations in total soluble
protein content for both genotypes, with a higher values in summer than in winter, it is clear that
the relative partitioning of nitrogen into Rubisco in ‘Totem’ and ZB-15 is higher in late winter
than in summer. This pattern may be related both to the low incident PPFD in winter (Givnish,
1988), which has as a consequence lower Rubisco synthesis and activation (Hofer, et al., 1986,
Gutteridge and Gatenby, 1995), and to Rubisco degradation activity, which in winter can be
significantly lower than from April to August in the Northern Hemisphere (Peñarrubia, et al.,
1988).
With reference to the progeny genotypes, the only statistically significant differences in
Rubisco as a percent of total protein was found between genotype 36, situated below the 20th percentile, and genotypes 17 and 31, both with means greater than the 80th percentile (Table 4.5-
2). In this variable, ’Totem’ was greater than the 60th percentile and ZB-15 below the 25th percentile. This suggests that ZB-15, under summer conditions, not only can maintain a high
Rubisco content but it also may have the potential to invest more photosynthates and nitrogen in other proteins than Rubisco when compared with ‘Totem’ and 75% of the progeny genotypes.
This supports the empirical observation that leaves of ZB-15 are longer-lived than leaves of
‘Totem’, as leaves with longer life spans require a higher investment of nutrients, structural molecules, and energy than leaves with shorter life spans (Kikuzawa, 1991).
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Table 4.5-2. Leaf Total soluble protein, Ribulose 1,5-biphosphate carboxylase/oxygenase (Rubisco) and percentage of Rubisco of total soluble protein content for 45 greenhouse-grown F1 Fragaria genotypes (from a single cross), plus their parents, Totem (F. x ananassa) and ZB-15 (F. chiloensis).
Genotype Total Soluble Protein Rubisco Rubisco Proportion of Identific. (mg g-1 dwt) (mg g-1 dwt) Total Soluble Protein (%) 2 24.37 abcd z 9.99 ab 45.8 ab 3 23.15 abcd 7.84 ab 34.4 ab 4 16.43 bcd 7.33 ab 47.9 ab 5 15.03 cd 7.86 ab 52.7 ab 6 12.58 d 5.82 ab 44.6 ab 7 27.42 abcd 10.10 ab 38.3 ab 8 22.87 abcd 7.85 ab 38.0 ab 9 17.53 bcd 8.33 ab 46.8 ab 10 27.28 abcd 8.74 ab 38.5 ab 11 18.39 bcd 5.99 ab 33.1 ab 12 17.46 bcd 7.42 ab 47.3 ab 13 30.30 abcd 7.74 ab 26.9 ab 14 40.01 abc 9.11 ab 25.0 ab 15 34.87 abcd 6.30 ab 18.8 ab 16 17.45 bcd 5.40 b 34.1 ab 17 12.45 d 7.47 ab 59.7 a 18 35.22 abcd 8.17 ab 30.9 ab 19 13.81 d 6.81 ab 49.7 ab 20 17.77 bcd 6.12 ab 34.6 ab 21 32.08 abcd 8.34 ab 26.7 ab 22 21.27 abcd 8.78 ab 43.0 ab 23 18.83 bcd 7.42 ab 42.8 ab 24 23.90 abcd 7.03 ab 29.4 ab 25 18.68 bcd 8.75 ab 47.6 ab 26 25.10 abcd 8.40 ab 33.6 ab 27 23.24 abcd 6.89 ab 36.5 ab 28 19.17 bcd 7.22 ab 37.7 ab 31 15.58 bcd 8.99 ab 59.4 a 32 31.61 abcd 6.73 ab 22.5 ab 33 32.09 abcd 12.79 a 50.6 ab 34 23.30 abcd 9.58 ab 40.6 ab 35 24.90 abcd 8.68 ab 34.6 ab
z: Mean separation within each column (genotypes 2 to 50) by Tukey’s HSD test, P=0.05.
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Table 4.5-2. (Continued).
Genotype Total Soluble Protein Rubisco Rubisco Proportion of Identific. (mg g-1 dwt) (mg g-1 dwt) Total Soluble Protein (%) 36 41.27 ab z 6.97 ab 15.9 b 37 23.44 abcd 8.78 ab 39.2 ab 38 23.41 abcd 10.13 ab 49.9 ab 39 22.71 abcd 6.96 ab 34.9 ab 40 21.92 abcd 7.20 ab 33.2 ab 41 16.83 bcd 6.89 ab 39.6 ab 42 22.01 abcd 5.65 ab 26.3 ab 43 24.43 abcd 7.08 ab 39.5 ab 44 20.15 bcd 7.73 ab 45.2 ab 45 22.07 abcd 8.57 ab 52.0 ab 46 6.86 abcd 8.32 ab 22.5 ab 47 20.25 bcd 6.73 ab 33.6 ab 48 23.80 abcd 6.86 ab 31.9 ab 49 ZB-15 46.29 a 10.19 ab 23.6 ab 50 Totem 23.25 abcd 7.90 ab 41.7 ab
z: Mean separation within each column (genotypes 2 to 50) by Tukey’s HSD test, P=0.05.
4.6. Carbon Isotope Discrimination
4.6.1. Selected pest resistant and pest susceptible Fragaria genotypes
Variations in carbon isotope composition in land plants are principally associated with
photosynthetic carboxylation enzymes (Griffiths, 1991; Ehleringer and Osmond, 1992; O’Leary
et al. 1992; Knight et al., 1994; Lambers et al., 1998), diffusional fractionation and leaf internal
CO2 concentration (Griffiths, 1991; O’Leary et al., 1992), and thus, to the ratio Ci/Ca (Francey, et al., 1985; Ehleringer and Osmond, 1992; Henderson et al., 1998). When leaf anatomical or physiological controls for CO2 diffusional rates are involved, such mechanisms also influence
WUE as CO2 and water vapor share the same pathways in and out of leaves (Larcher, 1995;
Lambers et al., 1998).
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Carbon isotope discrimination observed among 26 Fragaria genotypes showed, as expected
(Ehleringer and Osmond, 1992), a narrow range of values (21.825 to 25.580‰), which is within
13 the characteristic ∆ C range described for C3 plants (Griffiths, 1991). Most genotypes showed
low data dispersion, with statistically significant differences among some of them, however, no
trends according to pest resistance or photosynthetic capacity rankings were observed (Fig. 4.6-
1). Genotypes CL-5 and 'Benton' and those of their progeny tested in this experiment, genotypes
88061-1, 88061-4, 88061-5 and 88061-6, were all at or below the 40th percentile in ∆13C
(23.282‰; Fig. 4.6-1), suggesting that related genotypes may have less variability in this trait than that observed with a sample of unrelated genotypes.
All F. chiloensis genotypes studied in common with the research of Foote (1994) (genotypes
O15, P11, Y59, B10, K19 and R07) showed higher ∆13C values in the present study compared to
those reported by that author (averaging 23.88‰ and 18.85‰ respectively). A possible cause of
the higher ∆13C in the present study may have been the elevated relative humidity under the
experimental conditions (greenhouse, late winter, with >80% RH) than in the summer field
conditions in Foote’s (1994) experiment. High levels of relative humidity (> 80%) allow plants
to have stomata open in higher proportion and for a longer period of time, increasing ∆13C as a consequence of higher gs and Ci compared to dryer air conditions (Ehleringer et al., 1992; Hall et
al., 1994; Kohorn et al., 1994; Henderson et al., 1998).
Genotype 2F1 had the lowest ∆13C under the experimental conditions (Fig. 4.5-1) which
where promoting 13C discrimination. This response indicates that 2F1, among those genotypes
tested, is more efficient using Ca and is a good candidate for a long-term WUE test under field
conditions to determine the precision of ∆13C as an estimator of long term WUE. 2F1 was
significantly different from seven other genotypes. In the other extreme of the range observed in
102
∆13C was the genotype FRA-472 (F. virginiana), with the highest value (25.58‰; Fig. 4.6-1),
which may be in part related to its low growth rate and low biomass production (see section 4.7 ,
Table 4.7-1). However, there are reports, reviewed by Hall et al., (1994), which suggest that a
high ∆13C in some plant species would be adaptive to wet environments, as a low ∆13C would be adaptive to dry environments. Apparently, there is no information about growth and ∆13C of
FRA-472 in its native environments. FRA-472 was significantly different from twelve other genotypes, including the other genotype of F. virginiana included in this study (FRA-1174; Fig.
4.6-1). ‘Totem’ and ZB-15 were not different from other genotypes, and both showed values close to the 50th percentile (∆13C = 23.536‰; Fig. 4.6-1).
13 The theory underlying ∆ C in C3 plants is well established, with an abundant body of
experimental data supporting its validity (Griffiths, 1991; Ehleringer and Osmond, 1992;
Ehrelinger et al., 1992; O’Leary et al., 1992; Raven, 1992; Hall et al., 1994). A general
13 synthesis of the parameters and relationships involved in ∆ C by C3 plants is given by the
following expression (Ehleringer et al., 1992; O’Leary et al., 1992; Hall et al., 1994):
∆ = a + (b - a)Ci/Ca - d Equation (1)
where,
∆ = Carbon isotope discrimination
a = 13C discrimination caused by diffusion in the air
b = 13C discrimination caused by carboxylation
Ci/Ca = ratio between the concentration of CO2 in the air (Ca) and inside of the leaf (Ci)
d = Discrimination caused by respiration and other processes. This parameter is assumed to be
negligible and is omitted from the equation (O’Leary et al., 1992).
103
The parameter b reflects mainly discrimination by Rubisco, which is approximately 27‰ for
C3 plants (Griffiths, 1991; Ehleringer et al., 1992; Hall et al., 1994). In the present study b was
calculated with the Equation (1) (see above), using coefficients from the regression equation of
13 ∆ C on Ci/Ca (Fig. 4.6-2). The resulting value for b was 25.9‰, which is close enough to assume that Rubisco discrimination in this sample of Fragaria genotypes is in the normal range
of expression for C3 plants under homogeneous environmental conditions (Griffiths, 1991;
Ehleringer et al., 1992; Hall et al., 1994). In the present study, Rubisco content, but not activity,
was measured. Rubisco content showed no linear association with ∆13C (r =0.09; N=26; P =
0.68), as also was observed in Fragaria by Foote (1994). This response can be expected as the variation in Rubisco carboxylase activity follows a typical enzymatic Michaelis-Menten non- linear pattern, and its 13C discrimination is more dependent on a number of environmental and
biological factors than its content (O’Leary et al., 1992; Hall et al., 1994; Lloyd and Farquhar,
1994). Environmental influences can be assumed as a factor which is in part responsible for the
differences in F. chiloensis ∆13C values observed, for the same genotypes studied by Foote
(1994) and in the present study.
13 A positive linear correlation coefficient (Pearson) was observed between ∆ C and Ci/Ca
(r=0.46; N=26; P=0.02), as predicted by ∆13C theory (O’Leary et al., 1992; Hall et al., 1994),
however, caution should be used in interpreting these results, as the ratio Ci/Ca in the data presented was obtained through the use of instantaneous gas exchange measurements, which may have low precision in estimate the long term dynamics of Ci/Ca (Hall et al., 1994). To
13 evaluate individual genotype performance in ∆ C and Ci/Ca, there are complementary analytical tools which can be applied. One consists of measuring gas exchange parameters of plants over short periods of time in constant environments, extracting non-structural carbohydrates and
27
26
25
24
23
22
21
b-f b-f c-f ef d-f b-f a-f a-d a-e f a-f ab a-f a-f d-f a-c b-f a-f a-f a-d a-e a-f a-e a b-f c-f 20 Benton 88061-1 88061-5 Totem 2C6 Del Norte P11 B10 R07 TR-18 ANC-2D COY-10A FRA-1174 CL-5 88061-4 88061-6 GCL-8 2F1 O15 Y59 K19 ZB-15 PNN-6A LCO-3H FRA-472 ZB-19
Figure 4.6-1. Carbon Isotope Discrimination (∆) in leaves tissue (dry matter) in 26 genotypes of Fragaria, ranked from susceptible to resistant to several pests (See Table 3.1 in Material and Methods). Mean separation among genotypes by Tukey's HSD Test, (P≤0.05). Vertical lines are standard deviations. 104
105
13 determining ∆ C using these extracts and Ci/Ca (Hall et al., 1994). Also, cluster analysis can be useful in discriminating among multivariate responses in genotype selection work. For example, the isolated cluster identifying genotype 2F1 (Fig. 4.6-2), identifies the combination of factors that situated this genotype far from the others, which may be useful for genetic improvement depending on the goals of a breeding program. The position of 2F1 indicates that this genotype
13 had the lowest ∆ C and was intermediate for Ci/Ca among those genotypes studied, suggesting
13 that in this case, gs may have a lesser role than Rubisco in ∆ C expression. Also, those clusters
situated in the high end of the observed range of Ci/Ca ratios, which includes genotypes PNN-
6A, ANC-2D, FRA-472 and FRA-1174 (Fig. 4.6-2) have medium to high ∆13C and low total
biomass (Table 4.7-1). This indicates that these genotypes may have a relatively higher carbon
discrimination by Rubisco and less by gs when compared with the rest of the tested genotypes
because they have higher values for Ci content (Table 4.1-1). Conversely, genotypes with low
values in the Ci/Ca range, especially clusters containing genotypes 88061-1, 88061-4 and 88061-
5 (Fig. 4.1.6.2), had lower Ci content (Table 4.1-1), higher total biomass (Table 4.7-1), and
13 medium to low ∆ C (Fig. 4.6-2). These genotypes in the lower range of Ci/Ca likely have a
13 higher relative contribution of gs to ∆ C, and a smaller relative contribution by Rubisco than
those genotypes in the higher range of Ci/Ca ratios.
Usually WUE is the most important factor for which ∆13C is used as estimator in plant
ecophysiology (Flanagan and Ehleringer, 1991; Griffiths, 1991; Ehleringer and Dawson, 1992;
Hall et al., 1994), and in plant breeding (Ehdaie and Waines, 1994; Hall et al., 1994; Knight et
al., 1994; Kohorn et al., 1994; Johnson and Rumbaugh, 1995; Araus et al., 1998). It is well
established in the literature that C3 plants can be expected to have a strong negative Pearson
26 CO 2 Dis. = 18.424 + 7.66 (Ci/Ca)
r 2 = 0.23; r = 0.48, N=26; P=0.01 FRA-472 O15 25 K19 GCL-8 PNN-6A
2C6 ANC-2D 24 COY-10A P11 LCO-3H Del Norte ZB-15 TR-18 Totem Y59
88061-1 Benton R07 Cl-5 FRA-1174 23 ZB-19 88061-6 B10
88061-5 88061-4 22 2F1
21 0.56 0.58 0.6 0.62 0.64 0.66 0.68 0.7 0.72 0.74 0.76 0.78 0.57 0.59 0.61 0.63 0.65 0.67 0.69 0.71 0.73 0.75 0.77 0.79
Figure 4.6-2. CO2 discrimination (∆) and Ci/Ca ratio relationship for some selected Fragaria genotypes. Genotype identification is according Table 3.1 and ovals denote boundaries of genotype clusters determined by multivariate analysis. 106
107
correlation coefficient between ∆13C and long term WUE (Ehleringer and Dawson, 1992; Hall et
al., 1994; Knight et al., 1994; Johnson and Rumbaugh, 1995; Henderson, 1998). In this study,
the Pearson correlation coefficient of ∆13C with instantaneous WUE was r=-0.51 (P=0.01;
N=26), a value that allows inference of a relationship between both parameters, but not strongly
enough to represent long term WUE. For such a relationship one would expect a stronger correlation coefficient (Hall et al., 1994, Lambers et al., 1998), as ∆13C is sensitive to long term
WUE dynamics and its resulting dry matter accumulation (Ehleringer et al., 1992), especially under drought conditions (Ismail and Hall, 1993; Hall et al., 1994). In add, under instantaneous
steady state gas exchange conditions it cannot be assumed that the leaf has achieved an isotopic
steady state (Harwood et al., 1998).
As expected, genotype distribution along the instantaneous WUE range follows a pattern
similar to the Ci/Ca range, as both variables are related to stomatal aperture dynamics (Field et
al., 1992, Larcher, 1995, Lambers et al., 1998). The Pearson correlation coefficient between
instantaneous WUE and Ci/Ca was r=-0.93 (P=0.000; N=26). Because of this relationship,
genotypes with low performance in Ci/Ca due to gs, also have a low performance in WUE due to
gw, where gs and gw have a Pearson correlation coefficient of 1.0 (P=0.000; N=26). In both
parameters, Ci/Ca and WUE low performance in each is matched by higher performance
observed in ∆13C (Figs. 4.6-2 and 4.6-3 respectively). This demonstrates the increasing
13 importance of gs and gw as causal factors in observed ∆ C as both conductivities decrease along
a gradient of genotypic responses (Figure 4.6-3).
When WUE is plotted against ∆13C, each of the genotypes PNN-6A, ANC-2D, FRA-472 and
FRA-1174 create an independent cluster which is situated at the lower end of the observed range
13 of WUE (Fig. 4.6-3). Given the relationship among the parameters WUE, Ci/Ca and ∆ C, it is 108
not surprising that in all of them, genotypes PNN-6A, ANC-2D, FRA-472 and FRA-1174 had
lower growth rates (empirical observation) among the sample of Fragaria genotypes used in this
study, and also lower total dry biomass (Table 4.7-1), indicating that their overall low
performance is consequence of a complex combination of factors.
Genotypes 2F1 and B10 were independent, single-genotype clusters, but with intermediate
WUE and good relative performance in ∆13C among the rest of the genotypes studied. Genotypes
88061-1, 88061-4, 88061-5 and ZB-19 belong to the cluster with a better combination of WUE and ∆13C values (Fig. 4.6-3), making them candidates to be tested for WUE under field
conditions, as they also had higher biomass than the genotypes in the other extreme of the WUE
range (Table 4.7-1). The rest of the genotypes with intermediate WUE had greater ∆13C, and
were classified in three clusters (Fig. 4.6-3) where contributions of gs and gw might be not as
decisive for the observed genotypic performance in ∆13C as for genotypes at each end of the
range of WUE values.
4.7. Biomass partitioning
4.7.1. Selected pest resistant and pest susceptible Fragaria genotypes.
High variability in total biomass (dry weight basis) was observed among the selected
Fragaria genotypes (Table 4.7-1). However, only leaves and crown biomass were somewhat
related to the genotype factor according to the Pearson's correlation coefficient (-0.53 and -0.50;
Table 4.7-2). It was observed that total biomass was associated with variable degree to the ci/ca ratio (r=-0.59), WUE (r=0.62), chlorophyll content (r=0.83), carbon isotope discrimination discrimination (r = -0.64) and with the biomass (dry weight) of some organs of the plant 26 13 C = 25.675 - 0.596 (WUE) FRA-472 r 2 = 0.28
25 O15 K19 PNN-6A
GCL-8
ANC-2D COY-10A 24 2C6 Del Norte LCO-3H Y59 P11 ZB-15 TR-18 Totem R07 CL-5 88061-6 23 FRA-1174 Benton ZB-19 B10 88061-1
CO2 Discrimination (o/oo) 88061-5
88061-4 22 2F1
21 1.65 1.8 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4 4.2 4.4 4.6 4.8 5 1.7 1.9 2.1 2.3 2.5 2.7 2.9 3.1 3.3 3.5 3.7 3.9 4.1 4.3 4.5 4.7 4.9 WUE
Figure 4.6-3. Relationship between CO2 isotope discrimination and WUE for some selected Fragaria genotypes. Genotype identification is according Table 3.1. Ovals denote boundaries of genotype clusters determined by multivariate analysis. 109
110
(Table 4.7-2). Given that none of the measured instantaneous photosynthetic variables had a
correlation coefficient (Person) with the total biomass higher than 0.59 (Table 4.7-2), and that
the latter was associated with the leaves biomass with only a r=0.73, probably, other variables
are also related to the genotypic response in total biomass. The low association of instantaneous
photosynthetic variables with the total biomass do not precludes the importance of the photosynthesis to the biomass accumulation and partitioning processes, rather, is a signal of the lack of representativity of a single instantaneous photosynthesis measurement (Field et al.,
1992). The latter is consequence of the variability in photosynthetic activity throughout the experimental time due to the interaction between ambient and endogenous factors (Hall and Rao,
1999). In some conditions, specially when there is one or more stress factors affecting the plant, the carbon isotope discrimination is a good index for estimate the overall cumulative photosynthetic performance during the growing season, and it is an even better index for estimate WUE (Kirda, et al., 1992; Johnson, 1993; Lambers et al., 1998). Under the experimental conditions of this study, there were no stress factors affecting the plants, which can explain in part the rather low correlation between the C13 discrimination and the total biomass
accumulation (r= -0.64; Table 4.7-2), as plants were not forced to accept C13 in addition to the
normal C12 as substrate for carbon photosynthetic assimilation.
When leaves biomass is added together to that of runners, which were in high proportion just
leaf tissue at the end of the experiment (empirical observation), the resultant figure is highly
correlated with the total biomass (r=0.98; Table 4.7-2), demonstrating the importance of the
runner's photosynthetic tissue for the overall accumulation of biomass during the elapsed
experimental time. Even though there were no photosynthesis measurements to the runner's
leaves, it can be expected that the photosynthetic performance of runners', same age, fully
Table 4.7-1. Biomass partitioning variables, dry weight basis, of some greenhouse-grown Fragaria genotypes.
Genotype Leaves Runners Crowns Roots Reproductive Total z Name Characteristics (g ) (g ) (g ) (g ) Structures (g) Biomass (g) Benton Fxa 6.67 cd y - x 2.81 efg 1.38 a – e 1.03 a 11.90 gh CL-5 Fch Pest Res 2.31 d 6.97 cd 0.61 fg 0.41 cde - 10.31 gh 88061-1 Adv. Sel. Pest Res 26.65 a 0.49 d 8.95 a 3.77 ab 1.23 a 40.68 a – e 88061-4 Adv. Sel. Pest Res 23.53 a 22.70 abc 5.57 bcd 4.70 ab - 56.57 a 88061-5 Adv. Sel. Pest Res 18.10 ab 20.69 abc 3.77 cde 2.22 abcd - 44.77 abc 88061-6 Adv. Sel. Pest Res 7.03 cd 24.42 ab 1.81 efg 1.66 a – e - 35.15 a – f Totem Fxa Pest Sus Std 6.60 cd 9.61 bcd 3.13 def 2.64 abcd 1.68 a 23.65 c – h GCL-8 Fch Pest Res 1.83 d 14.93 bcd 0.91 fg 0.87 a – e - 18.58 f – h 2C6 Adv. Sel Pest Res 20.29 ab 11.75 bcd 7.17 ab 4.20 ab 1.21 a 44.02 abcd 2F1 Adv. Sel. Pest Res 21.87 ab 20.01 abc 6.16 bc 4.74 a 1.87 a 54.05 a Del Norte Fch Pest Res 0.91 d 20.01 abc 0.50 g 1.28 a – e - 22.73 d – h O15 Fch High Phot Cap 1.59 d 13.18 bcd 0.53 g 0.85 a – e - 16.15 fgh P11 Fch High Phot Cap 2.27 d 25.96 ab 0.97 fg 1.18 a – e - 30.38 b – g Y59 Fch High Phot Cap 4.65 cd 10.69 bcd 1.27 efg 0.63 a – e - 17.24 fgh B10 Fch Low Phot Cap 7.46 cd 34.14 a 2.17 efg 2.00 a – e - 45.77 ab K19 Fch Low Phot Cap 0.93 d 9.07 bcd 0.41 g 0.42 de - 10.82 gh R07 Fch Low Phot Cap 12.68 bc 34.31 a 2.81 efg 2.81 a – e - 52.60 a ZB-15 Fch Pest Res 2.51 d 17.16 bcd 0.76 fg 0.91 a – e - 21.34 e – h TR-18 Fch Pest Res 1.55 d 13.26 bcd 0.52 g 0.61 a – e - 15.93 fgh PNN-6A Fch Pest Res 0.53 d 1.45 d 0.26 g 0.09 e - 2.33 h z: Fxa, Fragaria x ananassa; Fch, F. chiloensis; Fv, F. virginiana; Adv. Sel., Advanced selection (F ch x [Fxa]); Pest Res, Pest resistant; Pest Sus, Pest susceptible; Phot Cap, Photosynthetic capacity according to Foote (1994). y: Mean separation within each column (genotypes 1 to 27) by Tukey’s multiple range test, P≤ 0.05. x: No plant material in this category for this genotype. 111
Table 4.7-1. (Continued).
Genotype Leaves Runners Crowns Roots Reproductive Total z Name Characteristics (g ) (g ) (g ) (g ) Structures (g) Biomass (g) ANC-2D Fch Pest Res 0.36 d y 2.57 d 0.25 g 0.20 e - x 3.38 h LCO-3H Fch Pest Sus 2.71 d 1.43 d 1.69 efg 0.78 a – e - 6.62 h COY10A Fch Pest Sus 3.75 cd 17.06 bcd 1.54 efg 1.23 a – e - 23.59 c – h FRA-472 Fv Pest Res 0.85 d 0.88 d 0.67 fg 0.38 e - 2.79 h FRA1174 Fv Pest Sus 1.24 d 1.14 d 1.42 efg 0.92 a – e - 4.73 h ZB-19 Fch Pest Res 4.18 cd 12.34 bcd 1.05 fg 0.99 a – e - 18.57 fgh
z: Fxa, Fragaria x ananassa; Fch, F. chiloensis; Fv, F. virginiana; Adv. Sel., Advanced selection (F ch x [Fxa]); Pest Res, Pest resistant; Pest Sus, Pest susceptible; Phot Cap, Photosynthetic capacity according to Foote (1994).
y: Mean separation within each column (genotypes 1 to 27) by Tukey’s multiple range test, P ≤ 0.05.
x: No plant material in this category for this genotype.
112
113
Table 4.7-2. Pearson’s correlation coefficient between dry weight biomass partitioning and other physiological variables in pooled data from 26 strawberry genotypes. The Photosynthetic Tissue correspond to the biomass of leaves and runners added together. Numbers below each correlation coefficient are the respective P values; (n=26).
Dry Weight Biomass Genotype Leaves Runners Crowns Root Fruit Photosynt. Total Tissue Biomass Genotype -0.530 -0.165 -0.504 -0.493 -0.434 -0.414 -0.468
Ci/Ca 0.556 -0.635 -0.239 -0.632 -0.600 -0.442 -0.523 -0.585 0.000 0.240 0.000 0.001 0.024 0.006 0.002
WUE -0.519 0.640 0.309 0.596 0.623 0.334 0.576 0.623 0.000 0.125 0.001 0.000 0.095 0.002 0.000
Ala/gm -0.586 0.660 0.249 0.649 0.630 0.445 0.544 0.608 0.000 0.220 0.000 0.000 0.023 0.004 0.001
Chla -0.476 0.587 0.690 0.523 0.677 0.388 0.816 0.819 0.002 0.001 0.006 0.000 0.050 0.000 0.000
Chlb -0.490 0.647 0.666 0.574 0.711 0.387 0.833 0.844 0.000 0.002 0.002 0.000 0.051 0.000 0.000
Tchl -0.482 0.601 0.689 0.535 0.687 0.391 0.824 0.829 0.001 0.000 0.005 0.000 0.048 0.000 0.000
∆-13C 0.356 -0.609 -0.609 -0.527 -0.618 -0.335 -0.610 -0.641 0.001 0.001 0.006 0.001 0.094 0.000
Rubisco -0.195 -0.142 0.301 -0.239 -0.163 -0.336 0.132 0.054 0.508 0.153 0.260 0.446 0.109 0.534 0.802
Runners -0.165 0.233 0.386
Crowns -0.504 0.956 0.064 0.000 0.990
Root -0.493 0.930 0.363 0.911 0.000 0.148 0.000
Fruit -0.434 0.567 -0.167 0.705 0.652 0.005 0.307 0.000 0.000
Photos. -0.414 0.727 0.837 0.582 0.779 0.200 Tissue 0.000 0.000 0.005 0.000 0.431
Total -0.468 0.827 0.735 0.714 0.873 0.342 0.984 Biomass 0.000 0.000 0.000 0.000 0.128 0.000
114
expanded leaves was similar to that of the same type of measured crown's leaves (Schaffer et al.,
1986), with differences in the carbon partitioning pattern.
In this experiment, the most important variables associated with the total biomass
accumulation, according with the Stepwise variable selection regression procedure, were the
ratio ci/ca (which indicates the carboxylation efficiency), total photosynthetic tissue biomass
(leaves plus runners dry weight) and RUBISCO content. The model that describes the pooled
total biomass accumulation pattern for the 26 Fragaria genotypes evaluated had a R2 (adjusted) of 0.977, which indicates that almost all the observed variation in total biomass is accounted for by those three variables.
Also, there was a high variability among genotypes in the biomass partitioning to different organs (Fig. 4.7-1). Most of the F. chiloensis genotypes had lower values in leaf biomass than F. x ananassa and the hybrids between both species but, in turn, showed a higher proportion of runners' biomass. The latter response shows an important investment of the wild strawberry species in organs that confer them a better dispersion of vegetative propagules and competition abilities under native habitats when there are no an environmental stress factor acting upon them
(Alpert and Mooney, 1986; Schmid, 1990). Conversely, if there some environmental stress factors are affecting the plants, and given that strawberry is a perennial species, it can be expected a lower investment of photosynthates to runners (vegetative propagules) and more to reproductive organs (recombinant propagules), as a plastic adaptive response in order to facilitate the permanence of that species in that specific niche (Schmid, 1990). However, across habitats, in strawberry wild species, the investment to the receptacle tissue (which is most of the commercial fruit biomass), is less than in cultivated varieties (Darrow, 1966; Hancock, et al.,
1996). Such biomass partitioning abilities of F. chiloensis are more important under natural environments than in cultivated agroecosystems (Alpert and Mooney, 1986; Schmid, 1990;
115
Lambers et al., 1998). In the latter environment, the cultivated strawberry is a monoculture
species, near optimal ground coverage densities and without or minimum runner growth, as a
consequence of breeding (Hancock et al., 1996) and/or its elimination by means of cultural
practices (Galletta and Bringhurst, 1990), changing photoassimilate’s partitioning to a bigger
reproductive effort than in wild species, mainly oriented to the receptacle size (Hancock et al.,
1996).
In most studied genotypes in this research, the combined biomass of leaves and runners
accounted for most of the plant's biomass, followed in proportional importance by the crown's
biomass (Fig. 4.7-1). Root biomass always was in low proportion when compared to the total
biomass, being particularly small in F. chiloensis genotypes, where each unit of root biomass is
able to produce more units of total biomass than in the other Fragaria species. Only F. x
ananassa or some of its hybrids with F. chiloensis, had reproductive biomass at the
measurements time (Fig. 4.7-1).
In comparing shoot to root biomass, most F. chiloensis genotypes also showed the ability of this species to have less root construction costs by the way of having a smaller root system than the F. x ananassa genotypes, which, in turn, may imply that the former have a greater efficiency for water and nutrient absorption per unit of root biomass (Fig. 4.7-2), a desirable characteristic if the plant is growing under low fertility soil environments. The best example of the latter observation are ‘Totem’, the standard pest susceptible cultivated variety and F. chiloensis genotypes B10 and R07, which, having all of them similar root biomass, those native genotypes have, proportionally, the twice of shoot biomass (Fig. 4.7-2). However, those genotypes of F. chiloensis with the smaller growth rate (data not shown) and smaller shoot biomass, also showed the smaller root biomass, with the lowest root-shoot cartesian coordinates, defined by a common
100%
80%
60%
40%
Proportion of Total Biomass 20%
0% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 22 23 24 25 26 27 Genotype
Leaves Runners Crowns Roots Flower/Fruit Clusters
Figure 4.7-1. Relative partition of total biomass components of selected Fragaria greenhouse-grown genotypes. 116
117
cluster in Figure 4.7-2. The average root/shoot (R/S) ratio for the genotypes of this cluster
(excluding genotype 20) was 5,28, value that contrast to that observed for genotypes in the
highest cluster (R/S ratio = 10,01). Genotype 20 was excluded for calculate the r/s mean as it was
under strong stress, with almost no growth along the experimental period.
Both F. virginiana genotypes, which showed a small total biomass, also are in the same
cluster that is grouping the smaller root-shoot relationship genotypes, which is consistent with
the rather smaller total biomass found in this species when compared to F. x ananassa and
similar or little smaller than F. chiloensis (Darrow, 1964), both under natural or experimental
conditions (empirical observation).
Genotypes 88061-4 and 2F1 showed both, high root and shoot biomass (Fig. 4.7-2), where
the root system had more rootlets of third or fourth order (< 1 mm on diameter), than the other
genotypes (Fig. 4.7-3), characteristic which has been associated to a more evolved root system,
with a greater ability to explore the soil and lower mycorrhizal dependence under natural
conditions (Malloch, et al., 1980; Lambers et al., 1998).
The regression equation between root and shoot biomass of the studied genotypes showed a
linear tendency (R2 = 0,73), across a wide phenotypic expression (Fig. 4.7-2), which can be
exploited in breeding programs if those traits have an adequate segregation (Hancock et al.,
1996).
4.7.2. Observation on progeny
The response in total biomass, dry weight basis, across 46 F1 genotypes (from a single cross),
and their parents 'Totem' (F. x ananassa) and ZB-15 (F. chiloensis) averaged 36.2 g, which was
118
60 Y = 6.995 + 9.843X R 2 = 0.73 4 17 50 10 15 5 9 40 3
6 30 13
24 7 18 11 20 27 14 8 19 12 1 10 2 16
20 22 25 23 26 0 012345
Figure 4.7-2. Shoot-Root relationship for some selected Fragaria genotypes. Numbers identify genotypes according Table 3.1, and ovals denote boundaries of genotype clusters determined by multivariate analysis.
close to the mode (37,37 g), with a range of 47,19 g between the minimum (10.12 g; genotype
33) and the maximum (57.31 g, genotype 23). Averages of 'Totem' and ZB-15 parents were no statistically different between them and from any of their progeny genotypes (Table 4.7-3).
There were only few pairwise statistical comparisons significantly different (Table 4.7-3), mainly between genotypes at both extremes of the observed range of values. For example, genotype 33 was different from 16 other siblings (Table 4.7-3), while genotype 1, with 12.55 g of total biomass, was different from 12 other F1 genotypes that had higher total biomass average
(Table 4.7-3). The relative response pattern of the latter example also was observed when allocation to shoot and root were studied through a regression analysis (Fig. 4.7-4), where those
119
a b
5 cm 5 cm
Figure 4.7-3. a) Root system of 2F1 genotype, an advanced selection from crosses between F. x ananassa and F. chiloensis with more third and fourth order rootlets than cultivated varieties. b) Root system of plantlets of 'Fern' cultivar (F. x ananassa).
12 genotypes which were different from genotype 1 in total biomass, all had a shoot dry weight above of 43,31 g, grouping in the upper right position in the scatter plot, while genotype 1, was at the opposite end of the values (lower left position; Fig. 4.7-4).
Considering all progeny genotypes, total biomass showed a continuos distribution, with values beyond the means of both parents. This response is similar to a transgressive segregation pattern, even though, they were a F1 generation. Usually, transgressive segregation is more likely to be observed at the F2 generation as a consequence of a quantitative trait (King and Stansfield,
1997; Miglani, 1998). Biomass partitioning and total biomass are quantitative traits. Taking in
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account the means numerical values, and without considering the replications variation, only
16.7% of progeny genotypes were below the ZB-15 parent total biomass (25.7 g), while 58.3%
of progeny had values higher than the 'Totem' parent (35.6 g; Table 4.7-3). Only 25% of progeny
were in between both parents total biomass values.
A multiple correlation (Pearson) data analysis, showed that biomass variables had little or no
linear association with instantaneous photosynthesis variables. The higher correlation coefficient
observed was between the photosynthetic rate A (dry weight basis) and leaves dry weight, with
r = -0.40 (n=47; P=0,004). This low correlation coefficient can be expected to some extent, not
as lack of association between those studied variables, but rather as a low relative contribution
among many other factors that are influencing or regulating the total biomass phenotype.
Usually, when the experimental period allows a complete phenophase development (as it was in
this experiment), and the trait is quantitative (its expression depends on the coordinated action of
many genes), the response is a dynamic equilibrium through time, and a broad range of
phenotypic response can be expected among individuals when genetic recombination has
occurred (Griffiths et al., 1996).
As ZB-15 is a genotype collected from the wild, with no previous gene insertions by human breeding, it can be expected that it should have a good fitness to its original ecological niche as a consequence of a coevolutionary process (Futuyma, 1998), while 'Totem', as a cultivar with many ancestors chosen by the breeder's criteria, has somewhat lost some abilities to dwell in natural ecosystems (Kelley, 1999). According to Kelley (1999), there is a necessity to reincorporate useful genes to the cultivated strawberry in order to recover some abilities regarding stress resistance (pest, drought, photosynthetic capacity, etc.), which also, may improve the negative energetic balance in the cultivated strawberry, as more energy is required
Table 4.7-3. Biomass partitioning variables, dry weight basis, of greenhouse-grown F1 Fragaria genotypes (from a single cross), plus their parents, Totem (F. x ananassa) and ZB-15 (F. chiloensis).
Genotype Leaves Runners Crowns Roots Total Biomass (g) Identification. (g ) (g ) (g ) (g ) 1 10.18 bc z 9.29 ab 2.00 ef 1.75 a 12.55 cd 2 9.62 c 16.39 ab 2.06 ef 2.71 abcd 30.77 abcd 3 11.31 bc 14.77 ab 3.24 c – f 3.57 abcd 32.88 abcd 4 15.06 abc 21.20 ab 5.58 a – e 5.85 abcd 47.69 ab 5 10.32 bc 22.30 ab 3.22 c – f 3.77 abcd 39.62 abcd 6 8.41 c 14.49 ab 2.07 e – f 2.90 abcd 26.63 abcd 7 8.16 c 10.68 ab 2.81 def 2.34 bcd 23.98 abcd 8 14.85 abc 13.93 ab 4.24 a – f 2.32 bcd 35.33 abcd 9 12.43 bc 26.98 a 4.47 a – f 3.95 abcd 47.83 ab 10 10.16 bc 21.20 ab 4.78 a – f 4.51 abcd 40.65 abc 11 7.70 c 10.25 ab 3.27 c – f 2.96 abcd 24.18 abcd 12 9.53 c 20.94 ab 3.08 c – f 3.14 abcd 36.69 abcd 13 9.35 c 9.91 ab 3.03 c – f 4.21 abcd 25.45 abcd 14 9.09 c 9.51 ab 3.34 c – f 3.18 abcd 25.12 abcd 15 13.88 abc 20.36 ab 3.90 c – f 4.89 abcd 43.03 ab 16 12.56 bc 17.76 ab 3.61 c – f 4.34 abcd 38.26 abcd 17 12.61 bc 16.61 ab 2.52 def 3.33 abcd 35.07 abcd 18 9.23 bc 17.05 ab 4.80 a – f 6.29 ab 37.37 abcd 19 14.09 abc 15.56 ab 3.95 c – f 4.61 abcd 38.20 abcd 20 12.73 bc 21.30 ab 4.30 a – f 4.84 abcd 43.16 ab 21 16.73 abc 21.74 ab 6.19 abcd 4.87 abcd 49.52 ab 22 12.92 bc 16.15 ab 4.21 a – f 4.73 abcd 38.00 abcd 23 28.28 a 14.18 ab 8.11 a 6.74 a 57.31 a 24 14.75 abc 19.20 ab 3.87 b – f 4.99 abcd 36.41 abcd 25 16.01 abc 14.33 ab 5.24 a – e 4.61 abcd 40.18 abcd
z: Mean separation within each column (genotypes 1 to 50) by Tukey’s multiple range test, P≤0.05. 121
Table 4.7-3. (Continued).
Genotype Leaves Runners Crowns Roots Total Biomass (g) Identification. (g ) (g ) (g ) (g ) 26 10.41 bc z 13.91 ab 2.07 ef 3.00 abcd 29.39 abcd 27 7.78 c 12.05 ab 2.71 def 4.27 abcd 26.81 abcd 28 11.03 bc 15.41 ab 3.13 c – f 3.54 abcd 33.10 abcd 31 12.46 bc 11.72 ab 3.93 c – f 2.81 abcd 30.92 abcd 32 8.04 c 6.99 b 2.82 def 2.13 bcd 19.97 bcd 33 3.52 c 4.44 b 1.10 f 2.16 cd 10.12 d 34 10.80 bc 20.87 ab 5.68 a – e 4.61 abcd 41.95 abc 35 8.95 c 11.44 ab 2.39 def 3.36 abcd 26.14 abcd 36 10.67 bc 21.25 ab 4.93 a – f 5.02 abcd 41.86 abc 37 8.16 c 10.98 ab 1.95 ef 2.47 bcd 23.56 abcd 38 12.06 bc 26.52 a 4.37 a – f 4.15 abcd 47.10 ab 39 18.91 abc 19.32 ab 5.53 a – e 5.56 abcd 49.32 ab 40 14.95 abc 21.73 ab 6.12 abcd 5.58 abcd 48.38 ab 41 12.88 bc 27.88 a 4.46 a – f 5.04 abcd 50.25 ab 42 24.93 ab 6.20 b 6.24 abcd 5.94 abc 43.31 ab 43 15.66 abc 17.27 ab 4.32 a – f 4.19 abcd 37.23 abcd 44 16.29 abc 20.48 ab 4.41 a – f 5.08 abcd 46.26 ab 45 16.51 abc 13.43 ab 4.61 a – f 3.98 abcd 38.43 abcd 46 12.31 bc 18.98 ab 3.31 c – f 4.66 abcd 39.25 abcd 47 28.71 a 7.52 b 6.87 abc 5.22 abcd 46.44 ab 48 12.74 bc 16.36 ab 4.04 b – f 5.48 abcd 38.62 abcd 49 ZB-15 8.50 c 12.60 ab 2.87 c – f 1.73 cd 25.69 abcd 50 Totem 16.30 abc 10.74 ab 8.01 ab 3.25 abcd 35.60 abcd
z: Mean separation within each column (genotypes 1 to 50) by Tukey’s multiple range test, P ≤0.05.
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123
60 Y = 11.35 + 5.27 Root Biomass 2 R = 0.57 r = 0.75 23 50 21 41 44 47 39 9 38 20 15 40 40 4 43 34 Totem 10 24 5 45 25 42 46 36 18 8 12 17 16 19 22 48 30 28 2 31 3 26 ZB-15 6 13 27 1 7 11 35 Shoot Biomass (g) 20 37 14 32
10 33
0 1.73 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 Root Biomass (g)
Figure 4.7-4. Root-Shoot relationship of 46 Fragaria F1 genotypes (identified by numbers) and their parents 'Totem' (F. x ananassa) and ZB-15 (F. chiloensis). The regression equation and fitted line is shown.
to grow the crop than the energy obtained back with the harvest. Major source of useful genes in the Fragaria genus are native genotypes (Cameron et al., 1991; Becerra et al., 2001).
In the present research, some of the differences observed between both parents may come
from their evolutive background. Some differences can be expected to be transferred in some
extent to the progeny, like tolerance or resistance to pathogens or pest, which usually depend on
few genes. However, traits depending on polygenes, specially when the species is polyploid,
have less chance to produce a practical change in the progeny, like photosynthetic capacity
(Gifford et al., 1984; Lawlor, 1995), aspect which was demonstrated for Fragaria in this
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research (Tables 4.1-6 and 4.1-7). With regards to the pest resistance, it is easier to change the
phenotype of cultivated plants either through conventional breeding or genetic engineering when
the traits depend upon few genes (Becerra et al., 2001), but little has been considered about the
energy trade-off of insert a new energy demand to the organism, mainly when the trait is
constitutive, whose genes are expressed in a permanent fashion (Mahon, 1983), without
compensation in the plant's energy budget. More studies are required to improve the
photosynthetic efficiency in Fragaria in a practical way, however, experimental data for other
species indicate that an improvement in Pn is not likely to come from altering light harvesting
system, electron transport chains or ATP and NADPH synthesis systems, as crop production is a
function of many interlinked processes, from the chloroplast level to the plant-environment
interactions (Lawlor, 1995).
4.8. Leaf total phenols content
4.8.1 Selected pest resistant and pest susceptible Fragaria genotypes
Two of the three genotypes with the higher leaf total phenols concentration (dry weight
basis), are the same regarded in the literature as standards for pest resistance in the Fragaria
genus ('Del Norte' and ZB-15; Shanks et al., 1984; Doss and Shanks, 1988). Both genotypes,
plus genotype 88061-5, had higher phenols content than 'Totem', the pest susceptible standard.
Genotype 88061-5 was an advanced selection in the WSU strawberry breeding program, indicating that phenols concentration is a trait that could be transferred to the progeny by conventional breeding techniques.
There are more than 700 compounds that have been found in plants that have the basic molecular structure of a phenol (Smith, 1989), most of them secondary metabolites with
125 protection functions against several environmental stresses, among them, resistance to pest and disease (Smith, 1989; Montllor, 1991).
The defensive mode of action of phenols will vary according to their chemical structure, concentration and if their biosynthesis is constitutive or facultative, the latter induced by the pest or disease attack (Smith, 1989). It appears that the most common pest resistance mechanism due to phenols is based mainly on a deterrent effect, with little or no direct antibiosis effect (Smith,
1989, Montllor, 1991). In some cases, have been demonstrated a digestive impairment of some insects larvae or negative reproductive effects (Smith, 1989; Montllor, 1991). In Fragaria, the mechanism of action seems to be at least a deterrent effect, however, more specific studies are required.
Genotypes described by Foote (1994) as having either high (O15, P11 and Y59) or low photosynthetic capacity (B10, K19 and R07), showed no differences in leaf phenols content from genotypes regarded with high or low pest resistance (Fig. 4.8-1).
4.8.2 Weevil-Plant interaction
When 'Totem' and ZB-15 were under Black vine weevil attack (O. sulcatus), 'Totem' showed an apparently systemic response in phenols concentration, as leaves without damage in plants under insect attack had similar concentration than those with insect damage, both significantly higher from leaves of plants without insect attack (Fig. 4.8-2). This kind of response could be considered as facultative, which only is present when elicited by the action of the herbivore over the plant (Smith, 1989). Conversely, in ZB-15 there was no change in phenols concentration in plants under weevils attack, showing similar levels to those of 'Totem' without insect pressure.
The overall response of ZB-15 was significantly lower than 'Totem' (Fig.4.8-2).
126
150
135
120
105
90
75
60
Total Phenols (mg/g dwt) 45
30
15 c-f a-f abc def f ab b-f a-f b-f a f a-f dfe a-f abcd a-f dfe c-f ef a-e a-f a-f b-f b-f c-f bf 0 1 3 5 7 9 11 13 15 17 19 22 24 26 2 4 6 8 10 12 14 16 18 20 23 25 27 Genotype
Figure 4.8-1. Total phenols content (dry weight basis) in leaf tissues of 26 selected Fragaria genotypes, ranked from susceptible to resistant to several pests (See Table 3.1 for genotype identification). Mean separation among genotypes by Tukey's HSD Test, (P ≤ 0.05). Vertical lines are standard deviations.
As phenols did not change in ZB-15 under insect attack, the defensive mechanism against herbivores that this species has, compared with that of 'Totem', may be based either in the type of phenols (and if they are or not bound to glucosides to be active against insects; Rowell-Rahier et al., 1987), or have no connection to phenols (Montllor, 1991; see next section). Before discard a defensive role of phenols in ZB-15, a characterization of the specific phenols
127
140
120
100
ZB-15 80 Totem 60
40
20 b a a bbb 0 No Weevils Weevils Weevils No Weevils Weevils Weevils No Leaf Leaf No Leaf Leaf Damage Damage Damage Damage Treatment
Factor Weevil Genotype Level No weevil No leaf damage Leaf damage Totem ZB-15 Tukey 93.9 a 56.1 b P 0.05 58.2 a 83.4 b 83.6 b
Figure 4.8-2. Leaves total phenols content on 'Totem' (Fragaria x ananassa) and ZB-15 (F. chiloensis) strawberry genotypes being fed on by Black vine weevil (Othiorhynchus sulcatus). Averages in the table are from a 3x2 factorial Anova. Letters above treatment identification give the statistical significance of an One-way Anova. In both cases, mean separation by Tukey’s HSD Test, (P ≤ 0.05). Vertical lines are standard deviations.
and their defensive activity should be done (Waterman and Mole, 1989). The same is valid for
'Totem', as the increase in leaf phenols concentration when under weevil attack was not enough as to lower the levels of foliage damage, response that also have been reported for aphids
(Montllor, 1991).
128
Of both species, only 'Totem', when under insect attack, requires extra energy for increase
leaf phenols concentration, situation that may change the photosynthate partitioning, apparently,
without compensation as the photosynthetic rate did not change (Table 4.1-5). If the latter is a stable response, less energy should be devoted in 'Totem' to other biological processes when phenols biosynthesis is increased (Gatehouse, 1991).
4.8.3 Observation on progeny
Leaf phenols concentration in F1 progeny and their parents was very similar, with only few
differences among the pooled genotypes (Table 4.8-1). When leaf total phenols was expressed
on a fresh weight basis, no F1 genotype was different from their parents, however, when
expressed on a dry weight basis, a more reliable measure, one F1 genotype (#28) showed higher
(almost the double) phenols concentration than both parent genotypes (Table 4.8-1). Considering
that the F1 genotype sample was only of 48 individuals, a rather small sample for detect genetic
changes, the existence of one F1 genotype with a significantly higher phenols concentration
among this progeny sample may indicate that phenols concentration can be changed by
conventional breeding. To assess that potential, new directed crosses must be done, in order to determine heritability estimates for this trait (Griffiths et al., 1996).
4.9. Trichome density
Trichome density per a defined unit of leaf area was measured, rather than trichome number, because trichomes in Fragaria have an irregular shape, where one trichome can produce one or more intersections counts between a eyepiece grid and any part of the trichome structure when observed under optical microscope at 100x. Besides, a density of this structures gives a better
129
understanding of its three-dimensional mechanical effect over insects than a simple count of them. This variable was not measured in the weevil-plant interaction experiment.
4.9.1. Selected pest resistant and pest susceptible Fragaria genotypes
Trichome density, expressed as intersections of trichome structures with microscope's
eyepiece reticle per square millimeter of leaf area (abaxial), showed only few differences among
this selected Fragaria genotypes. Genotypes 7 and 25 ('Totem' and F. virginiana respectively)
had less trichome density than genotypes 20 and 22 (both F. chiloensis; Fig. 4.9-1). The far
fewer leaf hairs of 'Totem' compared with F. chiloensis genotypes has been reported previously
(Doss et al., 1987).
Part of the lack of differences among Fragaria genotypes in Figure 4.9-1 may be related to
the high variability in the measurements. Even though leaf age was standardized by trimming the
experimental plants and after some weeks of new growth, leaves in the same crown position
were sampled, still could be some differences in leaf age that could be partial cause of the
variability observed in trichome density among clonal plants (replications). Similar variability in
trichome density has been reported for seedlings from crosses between F. x ananassa and F.
chiloensis (Doss and Shank, 1988; Doss et al., 1991), and between clones of F. chiloensis
(Hancock and Bringhurst, 1979). In Fragaria, trichome number or density is decreasing as the
leaf ages (Doss and Shanks, 1988), because of mechanical forces (empirical observation). This
diminishing trichome density, without replacing, makes sense from a defensive viewpoint, as a
young leaf may represent a bigger loss for a plant than an older, less physiologically active, one,
with the latter closer to the compensation point and lower photosynthetic efficiency (Yoshida
and Morimoto, 1997). In some F. chiloensis genotypes, like CL-5 (genotype #2, Figure 4.9-1),
Table 4.8-1. Leaf total phenol content, fresh and dry weight basis, of greenhouse-grown F1 Fragaria genotypes (from a single cross), plus their parents, Totem (F. x ananassa) and ZB-15 (F. chiloensis). Genotype Leaf total phenols (fwt) Leaf total phenols (dwt) Identification. (mg g-1) (mg g-1) 1 18.28 ± 7.44 z ab y - 2 9.63 ± 3.61 ab 38.12 ± 14.10 b – e x 3 6.35 ± 3.25 ab 23.55 ± 12.51 e 4 11.86 ± 5.36 ab 46.97 ± 20.13 a – e 5 10.70 ± 8.14 ab 47.19 ± 41.46 a – e 6 11.87 ± 10.40 ab 44.92 ± 39.39 b – e 7 16.27 ± 12.89 ab 66.74 ± 47.65 abc 8 13.75 ± 3.92 ab 52.57 ± 19.67 a – e 9 12.03 ± 6.35 ab 43.82 ± 23.73 b – e 10 9.60 ± 8.81 ab 32.30 ± 26.14 cde 11 9.86 ± 1.99 ab 32.51 ± 20.72 cde 12 9.52 ± 2.44 ab 34.63 ± 9.86 cde 13 6.09 ± 1.91 ab 27.01 ± 8.68 b – e 14 8.50 ± 8.01 ab 39.61 ± 36.87 b – e 15 10.37 ± 6.40 ab 42.22 ± 26.61 b – e 16 15.50 ± 6.65 ab 59.57 ± 29.29 a – e 17 21.21 ± 9.41 a 76.91 ± 31.42 ab 18 12.12 ± 4.50 ab 52.67 ± 19.94 a – e 19 15.35 ± 8.08 ab 57.82 ± 29.80 a – e 20 5.26 ± 2.61 b 20.61 ± 8.74 a – e 21 17.12 ± 8.91 ab 52.01 ± 21.91 a – e 22 7.97 ± 1.03 ab 33.94 ± 5.41 cde 23 10.40 ± 4.08 ab 35.32 ± 12.38 cde 24 14.99 ± 5.08 ab 58.54 ± 36.19 a – e z: Mean ± Standard deviation y: Mean separation within this column (genotypes 1 to 50) by Tukey’s multiple range test, P ≤0.05. x: Mean separation within this column (genotypes 2 to 50) by LSD multiple range test, P≤ 0.05. 130
Table 4.8-1 (Continued). Genotype Leaf total phenols (fwt) Leaf total phenols (dwt) Identification. (mg g-1) (mg g-1) 25 12.70 ± 8.44 z ab y 50.33 ± 75.71 a – e x 26 15.51 ± 15.84 ab 66.35 ± 75.11 abc 27 5.00 ± 1.810 b 22.07 ± 9.81 a – e 28 21.54 ± 14.07 a 84.47 ± 46.25 a 31 10.30 ± 5.41 ab 40.01 ± 20.00 b – e 32 9.91 ± 3.57 ab 43.23 ± 16.69 b – e 33 13.28 ± 8.41 ab 65.78 ± 44.81 abcd 34 9.35 ± 2.29 ab 38.86 ± 10.56 b – e 35 10.88 ± 3.84 ab 43.13 ± 13.49 b – e 36 10.43 ± 5.71 ab 40.73 ± 23.39 b – e 37 15.91± 11.06 ab 65.75 ± 46.15 abcd 38 10.39 ± 4.35 ab 40.39 ± 16.38 b – e 39 10.62 ± 1.66 ab 41.90 ± 7.29 b – e 40 12.54 ± 11.10 ab 49.94 ± 49.94 a – b 41 12.58 ± 3.83 ab 48.05 ± 48.05 a – e 42 10.47 ± 4.39 ab 42.93 ± 42.93 b – e 43 8.00 ± 2.94 ab 30.86 ± 30.86 cde 44 12.14 ± 1.44 ab 46.96 ± 46.96 a – e 45 10.90 ± 2.95 ab 47.39 ± 47.39 a – e 46 12.46 ± 7.13 ab 47.61 ± 47.61 a – e 47 14.20 ± 6.78 ab 49.24 ± 49.24 a – e 48 12.29 ± 9.31 ab 45.86 ± 45.86 a – e 49 ZB-15 11.31 ± 6.91 ab 43.20 ± 43.20 b – e 50 Totem 9.99 ± 5.02 ab 38.90 ± 38.90 b – e z: Mean ± Standard deviation y: Mean separation within this column (genotypes 1 to 50) by Tukey’s multiple range test, P≤ 0.05. x: Mean separation within this column (genotypes 2 to 50) by LSD multiple range test, P≤ 0.05. 131
132
the removal of trichomes rendered it as susceptible to weevil feeding as a commercial variety
(Doss et al., 1991), indicating that in that genotype there is no other defensive mechanism.
No differences in leaf trichome density were found among genotypes described by Foote
(1994) as with high or low photosynthetic capacity, neither with reference to pest resistance with
exception of 'Totem', where part of its susceptibility to pests can be related to its very low
trichome density (Fig. 4.9-1).
4.9.2. Observation on progeny
Among F1 genotypes and their parents, almost no differences were observed in trichome
density (Fig. 4.9-2). In this experiment, with few exceptions, also was observed a high variation
among replications of each genotype, probably given by patchiness of non-controlled factors in the experimental greenhouse, which probably were not cancelled by the random blocking as the block effect in the Anova was statistically significant (Tukey HSD, P ≤ 0.05). Factors that can influence trichome density are leaf age (Doss and Shanks, 1988), which should be very similar among sampled leaves, mechanical forces, like wind, which is not relevant inside a greenhouse, light exposure (Larcher, 1995, Lambers et al., 1998), which had some gradient inside the greenhouse that should be cancelled by random blocking, soil water status (Larcher, 1995), which should be homogeneous in the experiment, temperature (Lambers et al., 1998), that had
some patchiness because of a heater with fan. As there were no control and measurements of
those factors and any other non identified, it is not possible to conclude about the observed
variability in trichome density in this experiment, however, this trait has been reported as a pest
resistance mechanism for this genus (Hancock and Bringhurst, 1979; Doss and Shank, 1988;
Doss et al., 1991). It is important to consider that there were no significant block effects in
another measured variables.
133
300
250
200
150
100
Trichome density (intersections/mm2) 50
ab ab ab ab ab ab b ab ab ab ab ab ab ab ab ab ab ab ab a a ab ab b ab ab 0 1 3 5 7 9 11 13 15 17 19 22 24 26 2 4 6 8 10 12 14 16 18 20 23 25 27 Genotype
Figure 4.9-1. Leaves trichome density of 26 genotypes of Fragaria, ranked from susceptible to resistant to several pests (See Table 3.1 for genotype identification). Mean separation among genotypes by Tukey's HSD Test, (P ≤ 0.05). Vertical lines are standard deviations.
4.10.1. Leaf area eaten
This variable was only measured in the Weevil-Plant interaction experiment. Clearly, there was a higher damage produced by weevils to leaves of 'Totem' than to ZB-15 (Fig. 4.10-1). In this experiment was demonstrated the previous classification of both genotypes regarding pest resistance. 'Totem' was more susceptible to Black vine weevil than ZB-15. However, there is no enough information as to discard a coupled tolerance effect to the observed resistance of ZB-15, generated by other mechanism. Some reports indicate that the resistance to Black vine weevil
134
can be transferred to part of the F1 genotypes from crosses between F. chiloensis and F. x ananassa. (Shanks et al., 1984; Doss et al., 1991). Genotypes like CL-5, GCL-8, ZB-15 and TR-
18 (respectively, genotypes # 2, 8,18 and 19 in Figure 4.9-1), not only produce a deterrent effect to Black vine weevil, showing less leaf area eaten, but also they diminish the insect fecundity in the pre-ovoposition period, either under greenhouse or in the field (Shanks, et al., 1984).
Part of the resistance showed by ZB-15 could come from the trichome density (Fig. 4.9-1) and total leaf soluble protein (Fig. 4.5-1), both significantly higher than in 'Totem'. As some proteins, among them, enzymes, can have a direct role in defensive mechanisms of plants
(Rhoades, 1983), more research is needed to determine if there is a role of proteins in defensive mechanisms of ZB-15.
Given the variability in trichome density, and the stability of the pest resistance trait in ZB-
15, trichome density is not the only pest resistance mechanism of this genotype. The extra cost in photosynthates that represent the higher concentration of leaf proteins and higher trichome density can be afforded by ZB-15, which showed a higher photosynthetic capacity than 'Totem',
(Table 4.1-5).
135
250
200
150
100
50 Trichome density (Intersections / mm2) ab abc abc abc abc abc abc abc abc ab abc abc abc abc abc abc abc abc abc a abc abc abc abc bc abc c a abc abc abc a ab abc abc abc abc abc abc abc abc abc abc a abc abc abc abc 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 31 33 35 37 39 41 43 45 47 49 2 4 6 8 10 12 14 16 18 20 22 24 26 28 32 34 36 38 40 42 44 46 48 50 Genotype
Figure 4.9-2. Leaves trichome density of greenhouse-grown F1 Fragaria genotypes (from a single cross), plus their parents, Totem (F. x ananassa) and ZB-15 (F. chiloensis). Mean separation among genotypes by Tukey's HSD Test, (P≤0.05). Vertical lines are standard deviations.
136
50
45
40
35 1000) 30
m2 x a 25
20
15 Leaf area eaten (c 10 b 5
0 Totem ZB-15
Figure 4.10-1 Total Leaf area eaten on two strawberry genotypes fed upon by Black vine weevil (Othiorhynchus sulcatus). Totem (Fragaria x ananassa, pest susceptible standard), and ZB-15 (F. chiloensis, weevil resistant), were growing under a 30% shade net shelter, with natural photoperiod and temperature regimes. Mean separation of pooled data of all replications per genotype was performed using the Two-sample T test (P≤ 0.05). Vertical lines are standard deviations.
137
5. CONCLUSIONS
For Objective I).
-The Fragaria genus is highly heterozygous in most of the studied variables.
-When selected genotypes of the Fragaria genus are pooled together, no correlation exists
between photosynthetic capacity and pest resistance level.
-Only comparing genotypes with a stable position at both extremes of the observed ranges of
photosynthetic capacity and pest resistance there is a positive correlation between both variables.
-Higher photosynthetic capacity in Fragaria is related to an increased residual conductivity to
the CO2 (gr).
- Photosynthetic variables like chlorophyll concentration, chlorophyll absorption spectra and its
fourth derivative, chlorophyll fluorescence, and leaf Rubisco content, have intermediate degree
of correlation with photosynthetic capacity.
-Carbon isotope discrimination and biomass have no linear relationship with photosynthetic
capacity or pest resistance level.
For Objective II)
-Some parameters of chlorophyll fluorescence change under pest attack
-The relative frequency of 4th derivative chlorophyll light absorption peaks change when the plant is under pest attack.
-Pest resistance in Fragaria could be related to leaf protein and trichome density.
- Pest resistance mechanisms in Fragaria are constitutive and facultative.
-Standard pest susceptible genotype does not compensate the extra cost of facultative pest defense.
138
-Standard Pest resistant genotype has a constitutive pest defense mechanism that can be
sustained by a high photosynthetic capacity.
-Leaf total phenolics concentration is either a constitutive or facultative defense mechanism in
Fragaria.
For Objective III)
-The Fragaria genus is highly heterozygous in most of the variables evaluated, where a sample of the F1 progeny (of a single cross), showed a continuous distribution of responses.
-In some traits can be expected a transgressive segregation pattern, showing some potential for
breeding programs.
- For other traits, depending on polygenes, like photosynthetic capacity, there is no detectable
transference to the F1 progeny.
-More studies are required for those pest resistance traits that appear as having potential for
Fragaria breeding programs, among others, obtain heritability estimates to assess the feasibility to transmit those traits to the progeny.
139
6. LITERATURE CITED
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Altieri, M.A. 1995. Agroecology. The science of sustainable agriculture. Westview Press,
Boulder, Colorado. 433 p.
Angermeier, P.L. and Karr, J.R. 1994. Biological integrity versus biological diversity as policy
directives. BioScience 44(10):690-697.
Araus, J.L.; Alegre, L. Tapia, L.; Calafell, R. and Serret, M.D. 1986. Relationships between
photosynthetic capacity and leaf structure in several shade plants. Amer. J. Bot.
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