Interactions Between Rootstock Genotype and Soil Environment

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INTERACTIONS BETWEEN ROOTSTOCK GENOTYPE AND SOIL ENVIRONMENT

AFFECT SCION PHYSIOLOGY AND MINERAL NUTRITION OF APPLE

NADIA ANTONELLA VALVERDI

A dissertation submitted in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY

WASHINGTON STATE UNIVERSITY Department of Horticulture

DECEMBER 2019

To the Faculty of Washington State University:

The members of the Committee appointed to examine the dissertation of

NADIA ANTONELLA VALVERDI find it satisfactory and recommend that it be accepted.

Lee Kalcsits, Ph.D., Chair

Stefano Musacchi, Ph.D.

Katherine M. Evans, Ph.D.

Lailiang Cheng, Ph.D.

ii ACKNOWLEDGMENT

I would like to acknowledge the support, guidance, mentoring, kindness and patience of my advisor Lee Kalcsits during these three years and a half. Lee, thank you for welcoming me in your laboratory and for your willingness to work with me. Also, for creating a workspace that feels more like a family than co-workers. Moreover, thank you for letting me grow at my pace, being there always supporting and guiding me when I needed redirection. I feel that I have obtained all the tools and more that I was searching with this degree, to be ready to move forward in my professional career as a scientist. More important, you made me believe in myself and that is something I will be always thankful for.

I would also like to acknowledge my committee members for their support and guidance during the development of my research. Thank you for your constant feedback and knowledge which made this research journey even more nourishing, and challenging, making me think outside my area of expertise and allowing me to growth as a professional.

Additionally, I want to acknowledge my co-workers (friends) during these three years which without your help, support, friendship, laughter and advices this journey would have been very hard. I really have learned from each one of you, and this research is the result of all our knowledge and experience. Thank you for making my time in the laboratory to feel like working with friends.

Finally, I would like to acknowledge Hector, thank you for all your support, advices, statistical teaching hours, editing, and emotional support. Amor, sin vos no me imagino como habria logrado esta meta.

iii INTERACTIONS BETWEEN ROOTSTOCK GENOTYPE AND SOIL ENVIRONMENT

AFFECT SCION PHYSIOLOGY AND MINERAL NUTRITION OF APPLE

Abstract

by Nadia Antonella Valverdi, Ph.D. Washington State University December 2019

Chair: Lee Kalcsits

Irrigation is essential for many apple production regions, which elevates the risk in the future where water shortages will likely occur. Soil environment is a critical factor contributing to tree growth and development. Apples are composite woody perennials composed of a genetically distinct rootstock and scion. Rootstock genotypes can strongly vary in vigor and productivity. However, the interactions between rootstock genotypes and soil moisture and temperature have not been extensively studied. The objective of this research was to evaluate the influence of rootstock genotype on scion physiological and nutritional responses under different soil environmental conditions. In the greenhouse, ‘Honeycrisp’ and ‘Gala’ apple cultivars were grafted onto G41,

G890, M9, and B9 rootstocks. In the field, ‘Honeycrisp’ was grafted onto the same rootstock genotypes. Two irrigation treatments were established: a water-limited and a well-watered control for both experiments. Physiological measurements such as leaf gas exchange, stem water potential, shoot growth, and quantum yield of photosystem II (ΦII) were made every two weeks since the onset of the experiments. At the end of each experiment, tree growth was assessed, and nutrient concentration and carbon isotope composition (δ13C) was measured in roots, stem, and leaves. In

iv both experiments, water limitations reduced aboveground biomass and, to a lesser extent, root biomass. When G890 was used as a rootstock, growth and mineral nutrient accumulation was more plastic to water limitations. ‘Gala’ on all rootstocks and both scions on G890 had elevated mineral nutrient uptake. Water-limited conditions increased the nutrient concentration in roots and stems but had no effect on leaves. ‘Honeycrisp’ grafted onto G890 was the most responsive to drought indicated by decreasing stomatal conductance, reducing net CO2 exchange rates, ΦII, and ultimately, shoot growth. In contrast, B9 maintained growth and stomatal conductance when water-limited and had the highest δ13C and lowest stem water potential. These ﬁndings demonstrate differential responses of rootstock genotypes to soil environment and indicate opportunities for selection of rootstocks that are more suitable in water limited regions.

v TABLE OF CONTENTS

Page

ACKNOWLEDGMENT...... iii

ABSTRACT ...... iv

LIST OF TABLES ...... x

LIST OF FIGURES ...... xiii

CHAPTER ONE: LITERATURE REVIEW ...... 1

Introduction ...... 1

Apple ...... 1

'Honeycrisp’ Apple ...... 2

Physiological Disorders in ‘Honeycrisp’ Apple ...... 3

Apple Rootstocks ...... 4

Plant Nutrient Uptake and Soil Properties ...... 6

Plant Nutrition ...... 10

Plant Water use ...... 11

Plant Responses to Temperature ...... 14

Photosynthesis and Photoinhibition in Apple ...... 15

Linking Nutrient Dynamics with Plant Productivity and Responses to Abiotic Stress ...... 17

Scope of Research ...... 19

Objectives: ...... 19

vi References ...... 20

CHAPTER TWO: APPLE SCION AND ROOTSTOCK CONTRIBUTE TO NUTRIENT

UPTAKE AND PARTITIONING UNDER DIFFERENT BELOWGROUND

ENVIRONMENTS ...... 32

Abstract ...... 32

Introduction ...... 34

Materials and Methods ...... 37

Results ...... 40

Discussion ...... 44

Conclusions ...... 50

References ...... 51

CHAPTER THREE: ROOTSTOCK GENOTYPE AFFECTS FRUIT QUALITY, NUTRIENT

UPTAKE AND DISTRIBUTION OF ‘HONEYCRISP’ APPLE DURING ORCHARD

ESTABLISHMENT ...... 66

Abstract ...... 66

Introduction ...... 68

Materials and Methods ...... 71

Results ...... 75

Discussion ...... 78

Conclusion ...... 82

References ...... 84

vii CHAPTER FOUR: DIFFERENTIAL LEAF-LEVEL PHYSIOLOGICAL RESPONSES TO

WATER LIMITATIONS IN APPLE INDUCED BY ROOTSTOCK GENOTYPE UNDER

FIELD AND CONTROLLED ENVIRONMENT CONDITIONS ...... 102

Abstract ...... 102

Introduction ...... 104

Materials and Methods ...... 107

Results ...... 112

Discussion ...... 115

Conclusion ...... 119

References ...... 121

CHAPTER FIVE: ROOTSTOCK AND SCION GENOTYPES AFFECT HYDRAULICS AND

ANATOMICAL FEATURES OF APPLE TREES UNDER WATER STRESS...... 136

Abstract ...... 136

Introduction ...... 138

Materials and Methods ...... 140

Results ...... 144

Discussion ...... 146

Conclusion ...... 149

References ...... 150

CHAPTER SIX: CONCLUSION AND FUTURE WORK...... 169

viii Introduction ...... 169

Objectives: ...... 169

Conclusion ...... 170

Future work ...... 172

ix LIST OF TABLES

Page

Table 1. 1. The top six apple cultivars grown and consumed in the United States (U.S. Apple

Association, 2017)……………………………………………………………………………….29

Table 1. 2. Relative tree size of Geneva® rootstocks cultivars relative to Bud-9, M9-T337, and

M26 for Washington State (Auvil, 2016)...... 30

Table 1. 3. Nutrient movement from the soil to the roots for nitrogen, phosphorus, potassium, calcium, magnesium, and sulfur (Cornell University, 2010; Barber et al. 1963)...... 31

Table 2. 1. Root, stem and leaf biomass (grams dry weight), total leaf area (cm2) and root:shoot biomass ratio (±SE; n=3) for ‘Gala’ and ‘Honeycrisp’ apple cultivars in combination with four rootstocks: Bud-9 (B9), G41, G890, and M9-T337 (M9) under water limitations or elevated soil temperatures compared to the control…………………………………………………………….56

Table 2. 2. Nitrogen, calcium, potassium, and magnesium concentration (mg/g) for roots, stems and leaves of ‘Gala’ and ‘Honeycrisp’ scion genotypes in combination with Bud-9 (B9), G41,

G890, and M9-T337 (M9) rootstocks genotype grown in untreated control, water-limited, or elevated soil temperature treatments. Different letters denote significant differences among columns determined using a Tukey’s mean separation test (alpha = 0.05). ***, ** and * indicate significance in differences among means at p-values <0.0001, <0.01 and <0.05, respectively. .. 57

Table 2. 3. Nitrogen, calcium, potassium, and magnesium content (mg) for roots, stems and leaves of ‘Gala’ and ‘Honeycrisp’ scion genotypes in combination with Bud-9 (B9), G41, G890, and M9-

T337 (M9) rootstocks genotype grown in untreated control, water-limited, or elevated soil temperature treatments. Different letters denote significant differences among columns determined

x using a Tukey’s mean separation test (alpha = 0.05). ***, ** and * indicate significance in differences among means at p-values <0.0001, <0.01 and <0.05, respectively...... 58

Table 2. 4. Nitrogen, calcium, potassium and magnesium partitioning among roots, stems and leaves of ‘Gala’ and ‘Honeycrisp’ apple scion genotypes in combination with Bud-9 (B9), G41,

G890, and M9-T337 (M9) rootstocks genotype under untreated control, water-limited, or elevated soil temperature treatments. Different letters denote significant differences among columns determined using a Tukey’s mean separation test (alpha = 0.05). ***, ** and * indicate significance in differences among means at p-values <0.0001, <0.01 and <0.05, respectively...... 59

Table 3. 1. Average environmental data from WSU-Sunrise and WSU-TFREC AgWeatherNet weather stations for 2017 and WSU-Sunrise for 2018 of the months April to October………….88

Table 3. 2. Soil test results for the WSU-Sunrise orchard. Samples taken on April 2017...... 89

Table 3. 3. Root, stem and leaf biomass (grams dry weight), total leaf area (cm2) and root:shoot biomass ratio (± standard error; n = 3) for ‘Gala’ and ‘Honeycrisp’ apple on cultivars Bud-9 (B9),

G41, G890, and M9-T337 (M9) under water limitations or elevated soil temperatures compared to an untreated control. Values at the bottom correspond to the p-values of factors and its interactions that were signiﬁcant for at least one variable...... 90

Table 3. 4. Nitrogen, calcium, potassium, and magnesium concentration (mg/g) for roots, stems and leaves of ‘Honeycrisp’ apple on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotype under two irrigation treatments. Different letters denote significant differences among columns determined using a Tukey’s mean separation test (α = 0.05). Different letters indicate significance in differences among means at p-value < 0.05...... 91

Table 3. 5. Nitrogen, calcium, potassium, and magnesium content (mg) for roots, stems and leaves of ‘Honeycrisp’ apple on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotype under

xi two irrigation treatments. Different letters denote significant differences among columns determined using a Tukey’s mean separation test (α = 0.05). Different letters indicate significance in differences among means at p-value < 0.05...... 92

Table 3. 6. Fruit quality parameters, number of fruit per tree, yield per tree, individual fruit size

(mm), individual fruit weight (g), fruit firmness (Kg), and fruit soluble solids content (SSC) for

‘Honeycrisp’ apple on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotypes under two irrigation treatments. Different letters denote significant differences among columns determined using a Tukey’s mean separation test (α = 0.05). Different letters indicate significance in differences among means at p-value < 0.05...... 93

Table 3. 7. Fruit nutrient concentration (mg/g) for ‘Honeycrisp’ apple on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotypes under two irrigation treatments. Different letters denote significant differences among columns determined using a Tukey’s mean separation test (α = 0.05).

Different letters indicate signiﬁcance in diﬀerences among means at p-value < 0.05...... 94

Table 4. 1. Average environmental data for April to October in 2017 and 2018 at Wenatchee,

WA……………………………………………………………………………………………...125

xii LIST OF FIGURES

Page

Figure 2. 1. Mean soil volumetric water content during the growing season for control, water- limited, and elevated soil temperature treatments...... 60

Figure 2. 2. Daily average root-zone temperature recorded through the growing season for elevated soil temperature and control treatments...... 61

Figure 2. 3. Mean mid-day stem water potential (MPa) for ‘Gala’ and ‘Honeycrisp’ apple cultivars grafted on B9, G41, G890, and M9 rootstocks grown under water-limited (WL) or elevated soil temperature treatments compared to the control. Error bars denote standard error (N=3). Letters denote significant differences among means determined using a Tukey’s mean separation test

(alpha = 0.05)...... 62

Figure 2. 4. Mean tree biomass (grams of dry weight) distribution between roots, stems and leaves for (A) ‘Gala’ and (B) ‘Honeycrisp’ apple cultivars grafted on B9, G41, G890 and M9 rootstocks grown under water-limited or elevated soil temperature treatments compared to the control. Error bars denote standard error for total tree biomass (N=3). Letters denote significant differences among means determined using a Tukey’s mean separation test (α = 0.05)...... 63

Figure 2. 5. Total tree nitrogen, calcium, potassium and magnesium partitioning (%) between roots, stems and leaves for ‘Gala’ and ‘Honeycrisp’ apple scion genotypes grafted on B9, G41,

G890, and M9 rootstocks grown under water-limited or elevated soil temperature treatments compared to untreated control...... 64

Figure 2. 6. Mineral nutrient ratios (K:Ca, N:Ca, Mg:Ca and N+K+Mg:Ca) for leaves of apple rootstocks B9, G41, G890, and M9 grown under water-limited or elevated soil temperature treatments compared to untreated control. Error bars denote standard error (N=3). Letters denote

xiii significant differences among means determined using a Tukey’s mean separation test (alpha =

0.05)...... 65

Figure 3. 1. Soil water content (mm) and soil temperature (°C) during the growing season for the field experiment at WSU Sunrise experimental orchard for 2017 and 2018. 95

Figure 3. 2. Total dry weight of 3-year-old ‘Honeycrisp’ apple trees grafted on Bud-9 (B9), G41,

G890, and M9-T337 (M9) rootstocks under two irrigation treatments. Error bars denote standard error (n=3). Letter case difference account for significant differences between treatments, and different letters account for significant differences among rootstocks. Means determined using a

Tukey’s mean separation test (α=0.05)...... 96

Figure 3. 3. Total tree nitrogen, calcium, potassium and magnesium partitioning (%) between roots, stems and leaves for ‘Honeycrisp’ apple grafted on Bud-9 (B9), G41, G890, and M9-T337

(M9) rootstocks genotypes under two irrigation treatments...... 97

Figure 3. 4. Probability of occurrence of bitter pit presence in fruits at harvest for ‘Honeycrisp’ apple fruit grafted on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotypes...... 98

Figure 3. 5. Probability of occurrence of red color development in fruits at harvest for ‘Honeycrisp’ apple fruit grafted on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotypes...... 99

Figure 3. 6. Probability of occurrence of starch degradation in fruits at harvest for ‘Honeycrisp’ apple fruit grafted on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotypes...... 100

Figure 3. 7. Probability of occurrence of fruits size per tree at harvest for ‘Honeycrisp’ apple fruit grafted on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotypes...... 101

Figure 4. 1. Mean volumetric soil water content (N=3) for well-watered control and drought water- stressed irrigation treatment of ‘Honeycrisp’ one-year-old potted apple trees………………….126

xiv Figure 4. 2. Total precipitation and volumetric soil water content during May to August at

Washington State University experimental orchard for 2017 and 2018. = Irrigation treatments starting point...... 127

Figure 4. 3. Terminal shoot extension for ‘Honeycrisp’ potted trees grafted on Bud-9 (B9), G41,

G890, and M9-T337 (M9) rootstocks under drought (dashed lines) compared to a well-watered control (solid lines). Error bars denote standard error (N=3). Different letters account for significant differences among rootstocks determined using a Tukey’s mean separation test

(α=0.05)...... 128

Figure 4. 4. Terminal shoot extension of ‘Honeycrisp’ apple trees grafted on Bud-9 (B9), G41,

G890 and M9-T337 (M9) rootstocks under field conditions under drought (dashed lines) compared to a well-watered control (solid lines). Different letters account for significant differences among rootstocks by measurement dates (DAFB), and * indicates a significant treatment effect (α=0.05).

Different letters indicated significant differences among means determined using a Tukey’s mean separation test (α=0.05)...... 129

Figure 4. 5. Mean leaf area (cm2) of (A) one-year-old potted ‘Honeycrisp’ apple trees grafted on

Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks grown in a greenhouse and (B) 3-year-old

‘Honeycrisp’ apple trees grafted on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks under field conditions under drought compared to a well-watered control. Error bars denote standard error (N=3). Letter case indicates differences between treatments and different letters account for significant differences among rootstocks within treatments determined using a Tukey’s mean separation test (α=0.05)...... 130

Figure 4. 6. Mid-day stem water potential of (A) one-year-old potted ‘Honeycrisp’ apple trees grafted on Bud-9 (B9), G41, G890, and M9-T337 for 2017 (M9) rootstocks in greenhouse

xv conditions and (B) 3-year-old ‘Honeycrisp’ apple trees grafted on Bud-9 (B9), G41, G890, and

M9-T337 (M9) rootstocks in field conditions under drought compared to a well-watered control.

Error bars denote standard error (N=3). Letter case indicates differences between treatments and different letters account for significant differences among rootstocks within treatments determined using a Tukey’s mean separation test (α=0.05)...... 131

Figure 4. 7. Net photosynthesis, stomatal conductance, and transpiration rate for ‘Honeycrisp’ potted trees grafted on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks under drought compared to a well-watered control. Error bars denote standard error (N=3). Letter case indicates differences between treatments and different letters account for significant differences among rootstocks within treatments determined using a Tukey’s mean separation test (α=0.05)...... 132

Figure 4. 8. Photosynthesis rate, stomatal conductance, and transpiration rate for ‘Honeycrisp’ apple trees grafted on Bud-9 (B9), G41, G890 and M9-T337 (M9) rootstocks in field conditions under different irrigation treatments in 2017 (dark grey bars) and 2018 (light grey bars). Error bars denote standard error (N=3). Letter case indicates differences between treatments and different letters account for significant differences among rootstocks within treatments determined using a

Tukey’s mean separation test (α=0.05)...... 133

Figure 4. 9. Quantum yield of Photosystem II (ΦII) of (A) one-year-old potted ‘Honeycrisp’ apple trees grafted on Bud-9 (B9), G41, G890 and M9-T337 (M9) rootstocks in greenhouse conditions and (B) 3-year-old ‘Honeycrisp’ apple trees grafted on Bud-9 (B9), G41, G890 and M9-T337 (M9) rootstocks in field conditions under drought compared to a well-watered control. Error bars denote standard error (N=3). Letter case indicates differences between treatments and different letters account for significant differences among rootstocks within treatments determined using a Tukey’s mean separation test (α=0.05)...... 134

xvi Figure 4. 10. Leaf (dark grey), root (light grey) and stem (grey) δ13C for ‘Honeycrisp’ apple trees crafted on Bud-9 (B9), G41, G890 and M9-T337 (M9). (A) one-year-old potted trees grown in a greenhouse in 2017, and (B) 3-year-old ‘Honeycrisp’ apple trees grafted on Bud-9 (B9), G41,

G890, and M9-T337 (M9) rootstocks in field conditions under drought compared to a well-watered control. Error bars denote standard error (N=3). Letter case indicates differences between treatments and different letters account for significant differences among rootstocks within treatments determined using a Tukey’s mean separation test (α=0.05)...... 135

Figure 5. 1. Pictures of apple leaf stomata. Representation of ‘Honeycrisp’/Bud-9 (B9) well- watered tree (A) and ‘Honeycrisp’/Bud-9 (B9) under water stress (B). Images taken under increased magnification (40×)…………………………………………………………………..153

Figure 5. 2. Mid-day stem water potential (MPa) for ‘Honeycrisp’ apple cv. grafted on G41, G890, and M.9-T337 (M9) rootstocks genotypes under two irrigation treatments, control, and drought.

Different letters denote a significant difference between treatments. Tukey’s means separation with 95% confidence was used (α=0.05)...... 154

Figure 5. 3. Mid-day stem water potential (MPa) for Bud-9 (B9), G41, G890, and M.9-T337 (M9) rootstocks genotypes under two irrigation treatments, control, and drought. Different letters denote a significant difference between treatments. Tukey’s means separation with 95% confidence was used (α=0.05)...... 155

Figure 5. 4. Mid-day stem water potential (MPa) and soil moisture content (m3/m3) and adjusted linear regression for grafted and un-grafted apple trees grown in a greenhouse in 2018...... 156

Figure 5. 5. Tree growth (cm) for ‘Honeycrisp’ apple cv. grafted on G41, G890, and M.9-T337 rootstocks genotypes under two irrigation treatments, control (solid line), and drought (dash line).

xvii Different letters denote a significant difference between treatments. T-test two samples with 95% confidence was used (α=0.05)...... 157

Figure 5. 6. Tree growth (cm) for Bud-9, G41, G890, and M.9-T337 rootstocks genotypes under two irrigation treatments, control (solid line), and drought (dash line). Stars denote a significant difference between treatments. T-test two samples with 95% confidence was used (α=0.05). .. 158

Figure 5. 7. Leaf, stem, and root area for ‘Honeycrisp’ apple cv. grafted on G41, G890, and M.9-

T337 (M9) rootstocks genotypes under two irrigation treatments, control, and drought. Different letters denote a significant difference between treatments. Tukey’s means separation with 95% confidence was used (α=0.05) (n=3)...... 159

Figure 5. 8. Leaf, stem, and root area for Bud-9 (B9), G41, G890, and M.9-T337 (M9) rootstocks genotypes under two irrigation treatments, control, and drought. Different letters denote a significant difference between treatments. Tukey’s means separation with 95% confidence was used (α=0.05) (n=3). ns = non-significant...... 160

Figure 5. 9. (A) The relationship between transpiration rate and volumetric soil water content and

(B) the relationship between photosynthesis rate and transpiration rate for ‘Honeycrisp’ grafted on

G41, G890, and M.9-T337 (M9) rootstocks genotypes under fully watered conditions (full circles) or water limitations (empty circles). The line represents the adjusted linear regression for the combined data points...... 161

Figure 5. 10. The relationship between transpiration rate and volumetric soil water content and (B) the relationship between photosynthesis rate and transpiration rate for Bud-9 (B9), G41, G890, and M.9-T337 (M9) rootstocks genotypes under fully watered conditions (full circles) or water limitations (empty circles). The line represents the adjusted linear regression for the combined data points...... 162

xviii Figure 5. 11. Stem (light grey bars) and root (dark grey bars) hydraulic conductance (Kg sec-1

MPa) for ‘Honeycrisp’ apple cv. grafted on G41, G890, and M.9-T337 (M9) rootstock genotypes under two irrigation treatments, control, and drought. Different letters denote a significant difference between treatments. Tukey’s means separation with 95% confidence was used (α=0.05)

(n=3). ns = non-significant...... 163

Figure 5. 12. Stem (light grey bars) and root (dark grey bars) hydraulic conductance (Kg sec-1

MPa) measured in transient mode and stem (line) hydraulic conductance (Kg sec-1 MPa) measured in quasi-steady-state (QSS) for Bud-9 (B9), G41, G890, and M.9-T337 (M9) rootstocks genotypes under two irrigation treatments, control, and drought. Different letters denote a significant difference between treatments. Tukey’s means separation with 95% confidence was used (α=0.05)

(n=3). ns = non-significant...... 164

Figure 5. 13. Leaf-blades and graft resistance for ‘Honeycrisp’ apple cv. grafted on G41, G890, and M.9-T337 (M9) rootstocks genotypes under two irrigation treatments, control, and drought.

Different letters denote a significant difference between treatments. Tukey’s means separation with 95% confidence was used (α=0.05) (n=3). ns = non-significant...... 165

Figure 5. 14. Leaf-blades resistance for Bud-9 (B9), G41, G890, and M.9-T337 (M9) rootstocks genotypes under two irrigation treatments, control, and drought. Different letters denote a significant difference between treatments. Tukey’s means separation with 95% confidence was used (α=0.05) (n=3). ns = non-significant...... 166

Figure 5. 15. Stomata density (number mm-2) and area (µm2) for ‘Gala’ and ‘Honeycrisp’ apple cultivars grafted on Bud-9 (B9), G41, G890, and M.9-T337 (M9) rootstocks genotypes under two irrigation treatments, control (dark grey bars), and drought (light grey bars) after 30 days (A, B) and after 60 days (C, D). Different letters denote a significant difference between treatments.

xix Tukey’s means separation with 95% confidence was used (α=0.05) (n=3). ns = non-significant.

...... 167

Figure 5. 16. Stomata density (number mm-2) (A) and area (µm2) (B) of Bud-9 (B9), G41, G890, and M.9-T337 (M9) rootstocks genotypes under two irrigation treatments, control (dark grey bars), and drought (light grey bars). Different letters denote a significant difference between treatments.

Tukey’s means separation with 95% confidence was used (α=0.05) (n=3)...... 168

Dedication

To my mom, for her constant support and love. You are my inspiration, te amo!

To my family, you guys are the engine that keeps me going. Thank you for being my supporters

during all this journey.

To my late father whom I keep always with me in my heart.

xxi CHAPTER ONE: LITERATURE REVIEW

Introduction

Almost one-third of the total area of the world is arid land which frequently relies on irrigation for food production. In most major perennial tree fruit production regions, irrigation is often a necessity. These areas are at risk of seasonal and climatic variations in water supply (Zandalinas et al., 2018). The implications of this are two-fold; 1) As climate change increases, understanding the response of perennial tree fruit species, like apple, to increased soil temperatures and/or periodic water stress is essential to maintain productivity in a warmer future. 2) There are opportunities to use water more efficiently to optimize nutritional balance and improve fruit quality by reducing physiological disorders. The contribution of rootstocks and rootstock-scion interactions to plant responses to abiotic stress are still poorly understood. This thesis will address the gap in knowledge regarding the role of rootstock-scion interactions on plant responses to soil abiotic stress and what implications this has on nutrient uptake and distribution in apple.

Apple

Apple (Malus × domestica Borkh.) is a member of the Rosaceae family and is a specific hybrid complex made up of several wild species such as M. sylvestris Mill., M. pumila and M. sylvestris var. praecox (Pall.). However, Malus sieversii (Ledeb.) Roem. has been identified as the species of origin (Juniper et al., 1998; Korban and Skirvin 1984; Luby, 2003). Apple trees are grown widely globally, even at high elevation sites in the tropics. Apples are consumed fresh, dried, or processed as juice, alcoholic beverages or preserves (Luby, 2003). European colonists brought apples to the Americas where Spanish priests introduced them to Chile and California. In the early

16th and 17th centuries, European settlers brought seeds to established orchards in eastern United

1 States and Canada (Luby, 2003). Currently, the United States is the world´s second-largest producer of apples behind China and followed by Poland, Italy, and France, respectively (U.S.

Apple Association, 2017). The U.S. apple crop annual farm-gate value is close to $4 billion, with an additional $15 billion in related downstream economic activity each year. It is one of the most widely produced horticultural crops in the United States. Apples are grown commercially in 32 states and Washington, New York, Michigan, Pennsylvania, and California are the states with the most apple production. Sixty seven percent of the U.S. crop is grown for fresh consumption, while the remaining 33 percent is used for processing. The United States produces around 200 unique apple cultivars, with more than 100 cultivars readily available in retail stores (Table 1). This diversity of production means that challenges frequently arise with newly released cultivars, such as Honeycrisp, that are popular with consumers but are difficult to grow and/or are susceptible to disorders (U.S. Apple Association, 2017).

‘Honeycrisp’ Apple

The ‘Honeycrisp’ apple (Malus x domestica Borkh.) cultivar was developed at the Minnesota

Agricultural Experiment Station's Horticultural Research Center at the University of Minnesota,

Twin Cities and introduced in 1991 (Luby, 2003; Howard et al. 2017). Honeycrisp was first selected from a seedling block as MN1711 in 1974. ‘Honeycrisp’ is well adapted to northeastern climates. Nonetheless, it has been extensively planted in warmer areas like Washington State

(Serra et al., 2016). Recently, ‘Honeycrisp’ has increased in popularity in Washington state with production increasing from 120 hectares planted in 2000 to 9,150 hectares in 2017 (Gallardo et al., 2015; Serban, 2018). Currently it ranks fifth in the total volume of apples sold in the United

States (U.S. Apple Association, 2017). ‘Honeycrisp’ apple is a high value cultivar. The average

2 packinghouse prices of ‘Honeycrisp’, ‘Fuji’ and ‘Red Delicious’ cultivars grown in Washington between 2003 and 2008, was for ‘Honeycrisp’ apples 128% higher than Fuji and 183% higher than

Delicious (Gallardo et al. 2015). ‘Honeycrisp’ is known for its crispness and juiciness and now has been incorporated into numerous breeding programs in an effort to incorporate its desirable texture traits in addition to other traits such as improved disease resistance and tree vigor into new cultivars (McKay, Bradeen and Luby, 2011). ‘Honeycrisp’ has been widely used as a parent for multiple commercially released cultivars, like ‘Minneiska’, ‘New York ’,‘CN B60’, ‘CN 121’,

‘DS 22’, , ‘MAIA1’, ‘MN55’, and ‘WA 38’ bred by the breading program at Washington State

University (Howard et al. 2017).

Physiological Disorders in ‘Honeycrisp’ Apple

Fruit appearance is a significant factor in determining the marketability of fruit (Reig, Jentsch and

Rosenberger, 2016). Even small blemishes or spots that do not affect flavor or fruit quality can be unmarketable because of appearance. ‘Honeycrisp’, in particular, is susceptible to a wide range of physiological disorders that can lead to significant pre- and post-harvest losses to the apple industry (Rosenberger et al., 2001; Watkins and Nock, 2012). ‘Honeycrisp’ presents a big challenge to growers because of its sensitivity to many physiological disorders. The most serious of these is bitter pit development, both on the tree before harvest and during storage. Bitter pit is an important calcium (Ca) deficiency disorder in apple. It begins with water-soaked symptoms caused by plasma membrane breakdown, followed by tissue disintegration and dehydration, eventually resulting in corky, dark and depressed spots on the fruit surface (Rosenberger et al.,

2001, 2004; de Freitas et al., 2010). In addition to Ca, other factors also affect bitter pit incidence,

3 such as other mineral elements concentrations like nitrogen (N), potassium (K) and magnesium

(Mg), cultivar, rootstock, crop load and postharvest handling (Jemrić et al., 2016).

This cultivar is also susceptible to low-temperature disorders such as soft scald and soggy breakdown. These disorders can occur together, or separately, and soggy breakdown is especially concerning as it often cannot be seen from the outside of the fruit (Shoffe et al., 2016). Soft scald can be developed in prolonged cold storage, and this is the most economically damaging chilling injury observed in Washington State (Hanrahan and McFerson, 2016), and may be stimulated by a late harvest (Tong et al., 2003). The symptoms of soft scald include the development of sharply defined brown lesions on the skin of the apple but can also extend into the flesh. On the other hand, soggy breakdown is an internal disorder, and in worst cases, a complete ring of soft, brown, spongy tissue is present within the apple (Watkins et al., 2004). The control of one disorder can increase the incidence of another. For example, post-harvest treatments such as conditioning the fruit at 10

°C prior to low-temperature storage can limit soft scald incidence but can also stimulate bitter pit emergence in susceptible fruit (Mattheis, Rudell and Hanrahan, 2017). Moreover, excessively high fruit surface temperature can lead to sunburn. Apple sunburn can manifest itself in one of three ways: sunburn browning, sunburn necrosis and photooxidative sunburn (Racsko and Schrader,

2012; Kalcsits, et al., 2017). These conflicting factors make ‘Honeycrisp’ production and storage difficult.

Apple Rootstocks

Like many other fruit trees, apples are a combination of two genetically different parts: the rootstock and the scion (Fazio, Robinson and Aldwinckle, 2015). The rootstock includes the root system and a small portion of the lower trunk. The scion is grafted on to the rootstock and forms

4 the above-ground portion of the tree that produces fruit (Webster and Wertheim, 2003). Rootstocks have been used in tree fruit production for more than 2,000 years. Rootstocks that are used for many stone fruit species (i.e., peaches, apricots, cherries, and plums) are frequently a different species from the scion. Sometimes a rootstock from a different genus like the quince (Cydonia oblonga L.) is commonly used as a rootstock for European pears (Pyrus communis L.). For apple trees, the only species other than M. pumila (including M. sieversii and M. × domestica) that is widely used as a rootstock is M. prunifolia (Wild.) Borkh, seedlings of this species are used as rootstocks in parts of China. Most apple trees grafted onto seedling rootstocks are vigorous and bear fruit with poor fruit size and quality (Webster and Wertheim, 2003).

Rootstocks are an important component for a productive apple orchard because of their importance for water and nutrient uptake, anchorage, precocity, pest and disease protection and stress resistance (Fazio et al., 2013). One of the primary benefits of apple rootstocks is the ability to control tree size and seasonal vegetative growth. Consequentially, rootstocks can also affect flower and fruit number as well as fruit quality (Wünsche and Ferguson, 2010). Dwarfing rootstocks were imported to the United States from Europe in the early 1800s. In 1920, the Malling rootstock series was tested at several research stations in the U.S. This spurred the commercial introduction of dwarfing rootstocks into the United States. Currently, almost all apple orchards in the U.S. and other apple-growing regions of the world are planted on clonal rootstocks (Fallahi et al., 2002).

More recently, the use of dwarfing rootstocks made the establishment of high-density orchards possible and have led to significant increases in orchard productivity and fruit quality (Fallahi and

Westwood, 1984). By using rootstocks with desirable traits, fruit quality has increased, and incidence of disorders has been reduced. However, in some cases, the relationship between rootstock and fruit quality or disorder incidence is still not well understood (Musacchi and Serra,

5 2018). The use of rootstocks from the Malling rootstock series has dominated apple production for almost a century but with the replant disease susceptibility of some of this rootstock series and the introduction of cultivars that are susceptible to fire blight, and nutrient-related disorders, there has been an emphasis on breeding for rootstocks that reduce these problems and increase apple productivity (Fazio, Robinson and Aldwinckle, 2015).

There is a strong demand for new rootstocks that perform better in high-density systems. To meet the demand for new rootstocks, the United States Department of Agriculture-Agricultural

Research Service (USDA-ARS) Apple Rootstock Breeding and Evaluation Program was developed. GENEVA® series rootstocks were released with an emphasis on productivity, yield efficiency, ease of nursery propagation, fire blight resistance, tolerance to extreme temperatures, resistance to the soil pathogens of the sub-temperate regions of the US, and tolerance to apple replant disorder (Auvil, 2016). GENEVA® rootstocks have demonstrated similar productivity and quality compared to the current commercial standards, M.9 and M.26, while introducing increased fire blight and replant disease tolerance in many rootstock trials in North America and other locations worldwide (Table 2) (Autio, 2001; Fallahi et al., 2002; Tworkoski and Fazio, 2011; Autio et al., 2011; Fazio et al., 2012, 2013, 2014; Marini et al., 2012, 2013, 2014; Fallahi, 2012; Fallahi,

Bakhshi and Fallahi, 2013; W. Autio et al., 2013; W. R. Autio et al., 2013; E. Fallahi, Fallahi and

Shafii, 2013; Esmaeil Fallahi, Fallahi and Shafii, 2013; Fallahi and Eichert, 2013; Fallahi, Arzani and Fallahi, 2013; Amiri, Fallahi and Safi-Songhorabad, 2014; Moran, 2014; Neilsen and

Havipson, 2014; Robinson, Fazio and Aldwinckle, 2014; Lordan et al., 2017; Adams et al., 2018).

Plant Nutrient Uptake and Soil Properties

6 Soil contains a combination of mineral nutrients that are heterogeneously distributed within the soil volume. Nutrient movement and uptake from the plant can be by mass flow, diffusion or root interception (Barber, Walker and Vasey, 1963). Mass flow is the movement of dissolved nutrients into a plant as the plant absorbs water for transpiration. Diffusion is the movement of nutrients to the root surface in response to a concentration gradient. When nutrients are found in higher concentrations in one area than another, there is a net movement to the low-concentration area.

Thus, a high concentration in the soil solution and a low concentration at the root causes nutrient movement to the root surface, where they can be taken up. Root interception occurs when its growth causes contact with soil colloids which contain nutrient and the root then absorbs the nutrients (Taiz and Zeiger, 2002). This mechanism, in general, is a minor pathway for nutrient transfer except for phosphorus which strongly relies on root interception for nutrient uptake

(Cornell University, 2010).

Nutrient availability is a function of physical, chemical, and biological interactions in the soil environment. Soil solution is the liquid phase in the soil, where plant nutrients are dissolved and can move into the plant as water is taken up by the roots. This is the medium through which most nutrients are taken up by the plant. Nutrient mobility varies among the essential elements. The mobility of a nutrient in the soil also determines how much can be lost due to leaching or runoff.

- For example, NO3 nitrogen is highly mobile in the soil and will leach easily, while ammonium

+ (NH4 ) can be held on cation exchange sites and is not susceptible to leaching. Meanwhile, phosphorus is relatively immobile in the soil, and is thus less likely to runoff but, at the same time, it is also less available to plants, as it cannot migrate easily through the soil profile. Calcium, magnesium, and potassium are considered immobile since they strongly bind to cation exchange sites on clay and organic matter particles. Sulfur is commonly found in the anion sulfate form

7 - (SO4 ), which does not bind to cation exchange sites and for this is mobile in most soils (Table 3)

(Cornell University, 2010).

Soil characteristics such as texture can also affect nutrient uptake by the plant, like texture, which depends on the proportion of sand, silt, and clay in the soil. High clay content increases Cation

Exchange Capacity (CEC) and thus the ability of the soil to hold nutrients, while high sand content decreases the CEC and nutrient holding capacity, also sandy soils have large pore spaces, allowing more leaching of water and nutrients. Organic matter also increases the CEC of the soil. Soil structure can also affect water and nutrient movement. Soil structure is defined as the arrangement of soil particles into aggregates. A good structure improves water and nutrient movement, penetration, and retention. Large spaces between aggregates allow soil water (and the nutrients dissolved therein) to move more freely, but sometimes resulting in leaching losses. Small or no spaces between aggregates, primarily due to compaction, prevents water from moving through the soil profile, resulting in runoff. Drainage and aeration can affect nutrient loss and solubility. Poorly drained soils are often poorly aerated that can increase nitrogen loss through denitrification, while excessively drained (sandy) soils boost leaching losses (Cornell University, 2010).

Moisture is important for root growth and nutrient uptake. Adequate soil water content will improve absorption of nutrients by diffusion and root interaction and will increase organic matter decomposition, which releases nitrogen, phosphorus, and sulfate. pH affects nutrient availability by changing the nutrient form. For example, the different forms of nitrogen (affected by pH) have different leaching capabilities. pH is also important in nitrogen transformations; mineralization, nitrification, and nitrogen fixation are pH sensitive. Other nutrients may become absorbed or desorbed, precipitated, mineralized, or immobilized at different pH values. Many nutrients are more available in slightly acid soils: phosphorus is most available at a neutral pH (about 6.5);

8 molybdenum is available at high pH and can be toxic to plants. Soil nutrient availability is a factor influencing plant nutrient status. The ability to acquire nutrients from the environment is another important factor. Plant roots are critical to soil resource acquisition. Exploiting genetic diversity in root traits and acquisition of scarce soil resources can significantly enhance resource use efficiency in crop plants (Wells and Yanai, 2000).

Root architecture also plays an important role in nutrient uptake capacity and is defined as the spatial distribution of the root system within the root volume. It fluctuates greatly depending on the plant species, soil composition, and particularly on water and mineral nutrient availability.

Root architecture affects plant productivity and adaptation to different soil conditions like water- limited or high temperatures (Manschadi et al., 2006; Hodge et al., 2009). The root system is strongly affected by both genetic and abiotic environmental signals. Important root architectural traits include shape and structure. The shape of the root system (i.e. growth angle of root axes, lateral root expansion, root depth) define the location and the space the root system occupies in the soil. On the other hand, root structure determines the variety of components of the root system and their functions (Hodge et al., 2009). Plants vary genetically on their capacity to acquire nutrients by having different surface areas of root-soil contact, root exudates and rhizosphere microflora. The amount of available nutrients in the rhizosphere depends of the combination of soil properties, plant characteristics and microorganisms interactions with the roots (Rengel and

Marschner, 2005). Plant roots have the ability to alter their nutrient uptake capacity by altering their physiological, longevity, morphological and architectural characteristics as response to the shoot nutrient demand (Bassirirad, 2000). Rootstock plays a significant role on nutrient uptake because of the importance of roots for nutrient and water absorption and distribution to the scion

(Koepke and Dhingra 2013).

Plant Nutrition

Apart from carbon, hydrogen, and oxygen, plants require 16 other elements to germinate, grow, and reproduce. These elements can be separated into two distinct groups of nutrients: macronutrients which are needed in a high concentration by plants, and micronutrients which are required in lower concentrations (Kirkby, 2011). Macronutrients include nitrogen (N), phosphorus

(P), potassium (K), sulfur (S), calcium (Ca), and magnesium (Mg). Micronutrients include iron

(Fe), manganese (Mn), coper (Cu), zinc (Zn), molybdenum (Mo), boron (B), chlorine (Cl), and nickel (Ni) (Mengel et al., 2001; Taiz and Zeiger, 2002; Kalcsits, 2016). Elemental balance is important since one element, i.e. carbon, or one mineral nutrient at any time can act as a growth limiting factor when absent or in very low rates (Ingestad and Agren, 1995). In some cases, imbalances in plant nutrient ratios such as calcium with potassium, nitrogen, or magnesium can result in increases in physiological disorders such as bitter pit in apple.

Nitrogen is an essential plant nutrient making up between 1-5% of plant dry matter. It is a critical component of proteins, nucleic acids, chlorophyll, co-enzymes, phytohormones and secondary metabolites (Hawkesford et al., 2012). One of the largest users of nitrogen in the plant is Rubisco, which is a critical enzyme for the fixation of carbon dioxide during photosynthesis (Ray et al.,

2003). Phosphorus (P) function is most prominent in nucleic acids, which are a component of DNA and RNA. Phosphate esters and energy-rich phosphates, although present in cells in relatively low concentrations, represent the metabolic energy of cells (Hawkesford et al., 2012). Magnesium

(Mg) is vital for light harvesting by occupying the central position in chlorophyll. It also acts as a cofactor, and an exoteric modulator for >300 enzymes (i.e., carboxylases, phosphatases, kinases,

10 RNA polymerases, and ATPases). About three-quarters of leaf Mg is associated with protein synthesis, and up to 20% with chlorophyll pigments. The remaining fraction is stored in the vacuoles (Verbruggen and Hermans, 2013). Calcium (Ca) is required for a structural role in the cell wall and membranes, as a counter of cations for anions in the vacuole, and as an intracellular messenger (White and Broadley, 2003). Potassium (K) plays essential roles in enzyme activation, protein synthesis, photosynthesis, osmoregulation, stomatal movement, energy transfer, phloem transport, cation-anion balance and stress resistance (Wang et al., 2013). Cations also play a significant role in the regulation of cellular homeostasis. Therefore, high accumulations of one element can limit the localized accumulation of others (White, 2011).

Plant Water use

Water is critical for plant survival and reproduction. Water availability is one of the major limitations to plant productivity, and it regulates the distribution of plant species around the world

(Wood, 2005; Lauri et al., 2016). In the soil, water movement is driven by diffusion, by bulk flow, or a combination of both. Plant water uptake primarily occurs via the roots from soil and is transported through active xylem conduits to the leaves and is then lost to the atmosphere via transpiration. This is known as the soil-plant-atmosphere continuum (Taiz and Zeiger, 2002).

Water movement due to osmosis across membranes depends on a gradient in free energy of water across the membrane which is commonly measured as a difference in water potential (Taiz and

Zeiger, 2002). Water movement through xylem is driven by tension created from vapor pressure differences between the atmosphere and the leaf cells which creates a continuum that holds through cohesion forces between water molecules from leaves, stems, and roots (Salisbury and Ross,

1992).

11 Plants require free water for normal growth and development, leaf water content must remain constant despite atmospheric losses during the process to acquire carbon dioxide for photosynthesis (Wood, 2005). Plants can employ avoidance strategies to survive water limitations.

These include processes by which carbon dioxide is either acquired and separated from water loss either temporally (CAM plants) or spatially (C4 plants). C3 plant species, including apple, cannot temporally or spatially separate carbon dioxide intake from assimilation. Some species can limit water loss through thick cuticles or by developing extremely deep rooting systems that access water sources at increased soil depths (Basset, 2013). The capacity of plants to tolerate fluctuating environments involve morphological and physiological changes (Lauri et al., 2016). Two stages of plant responses to abiotic stress normally occur; short-term reversible physiological regulations

(e.g., stomatal regulation), and long-term acclimatization which involves structural and physiological changes (Lauri et al., 2016).

On the basis of stomatal regulation under water stress conditions, plants are generally classified into two categories: isohydric species, which prevent water potential drop by the early stomatal closure, and anisohydric species, which prioritized photosynthetic gains by keeping stomata open despite larger water potential drops (Klein, 2014; Tombesi et al., 2014). There can also be genotypic variation in anisohydric and isohydric responses. In grapevines, according to Vandeleur

(2009), ‘Chardonay’ shows to be an anisohydric cultivar which when under water stress maintains a small water potential gradient between the xylem and the soil, which could be associated with its the lower vulnerability to embolisms (Alsina et al., 2007). In contrast, ‘Grenache’ is a more isohydric cultivar which requires greater stomatal control to prevent excessively negative xylem water potentials (Schultz, 2003).

12 Drought is considered as the most widespread limitation to crop productivity and yield stability in rain-fed production systems. Consequently, developing cultivars with enhanced drought adaptation and higher yield has been the focus of many crop improvement programs. Root traits can moderate the effects of drought either by increasing the rate of water uptake through increased root distribution or by allowing a greater amount of water extraction through increased root-length at depth (Manschadi et al. 2006; Hammer et al. 2009; Manschadi, et al., 2013). A common response of crop plants to low availability of soil resources is increasing biomass allocation to the root system. Increased carbon allocation to roots bears the cost of reduced carbon distribution to photosynthetic shoot tissues and reproductive organs. For plants to optimize the allocation of resources among various organs, their investment in new growth structures, organs, and processes should be maintained at a level where the cost equals the benefit (Lynch and Ho, 2005).

Enhancing water and nutrient use efficiency in crop plants is a key component of the strategy to sustainable increase of agricultural productivity, reduction of the adverse environmental impacts of agriculture, and meeting the increasing food demand in the coming decades. Root system characteristics play a major role in soil resource acquisition and crop productivity in drought-prone and nutrient-deficient environments. The architecture of plant root systems appears to be particularly important for crop adaptation to multiple abiotic stresses occurring in such environments (Manschadi, et al., 2013). Although water and plant nutrition are inextricably linked, there is little information on how plant water status affects plant nutrient uptake and distribution, particularly for perennial tree species like apple.

13 Plant Responses to Temperature

Plants respond to high temperature in different ways. Adaptation or acclimation to high temperature occurs over different time scales and levels of plant organization. At the cellular level, heat affects a wide range of structures and functions, i.e., lipid properties, causing membranes to become more fluid and thereby disrupting membrane processes (Taiz and Zeinger, 2002). Proteins also have an optimal temperature range for activity. Increased temperatures alter enzyme activity leading to an imbalance in metabolic pathways, and eventually at high-temperature, proteins denature (Larkindale, Mishkind and Vierling, 2005). For example, the inhibition of net photosynthetic assimilates at high temperatures may originate from an inhibition of Rubisco activation by Rubisco activase. Rubisco activase is a stromal enzyme that plays an essential role in the process of Rubisco activation; activase from plants native to warm regions is less sensitive to heat than activase from plants native to cold regions (Haldimann and Feller, 2005; Sharkey,

2005).

The ratio between photosynthesis and respiration is also affected by temperature. Elevated soil temperature can affect root respiration. Higher temperatures generally result in increased rates of root respiration, and the exponential relationship between rates of respiration and temperature has been reported (Pregitzer et al., 2000). The respiration of plant roots is also directly related to nitrogen concentration. Therefore, it is possible that increases in root respiration at high temperatures might be due in part to higher rates of nitrogen mineralization, which would be promoted when the soil is warm and moist (Pregitzer et al., 2000). Net productivity in plants depends on the ratio between photosynthesis and respiration to be greater than one. This balance is highly temperature dependent. At temperatures around 15 °C, the above-mentioned ratio is usually higher than ten, explaining why many plants tend to grow better in temperate regions than

14 in tropical ones (Moretti et al., 2010). But when night temperatures are elevated, respiration increases affecting the net productivity of the plant by reducing the photosynthesis/respiration ratio

(Azcón-Bieto and Osmond, 1983; Lohraseb, Collins and Parent, 2017). Additionally, elevated soil temperatures can cause a reduction of cytokinins in roots and leaves followed by a decrease in leaf chlorophyll content. Leaf water potential has also been reported to increase with increasing root temperature (Gur, Hepner and Shulman, 1979). As climate change pushes average temperatures higher, soil temperatures will also be impacted, and this could lead to changes in plant energy balance, nutrient budgets and/or distribution. Temperature affects the plant's ability to grow, and thus make changes in nutrient uptake. Ideal temperatures vary by plant species and cultivar (Wells and Yanai, 2000).

Photosynthesis and Photoinhibition in Apple

Plants are autotrophic organisms capable of using the energy from the sun to synthesize all their essential components from CO2, water and mineral elements (Taiz and Zeiger, 2002).

Photosynthesis process is an oxidation of water and a reduction of CO2 to form carbohydrates. The reverse of this process, the combustion or oxidation of carbohydrates to form CO2 and water is respiration (Salisbury and Ross, 1992). The main factors limiting photosynthesis are CO2, light, temperature, minerals, and water (Westwood, 1978).

In general, photosynthetic end products like soluble sugars and starch accumulate in leaves following reduced sink demand because high concentrations of end products may inhibit enzyme activity and subsequently decrease photosynthesis. In parallel, with reduced photosynthesis, low sink demand resulted in decreased stomatal conductance (gs); decreasing gs reduces the rate of CO2 entry into leaves and transpiration via stomata, which results in stomatal limitation of

15 photosynthesis, and a subsequent increase in leaf temperature. When leaf temperature is above optimum, photosystem-II (PSII) is damaged and net photosynthetic rate is reduced, leading to non- stomatal limitation. This non-stomatal restriction frequently takes place in field grown trees and mostly under high photosynthetic photon flux and low sink demand. Thus, it has been suggested that decreased gs might be considered as the trigger or promoter and increased Tleaf as the regulator of photosynthesis under low sink demand (Fan et al., 2010).

Photosynthesis is well known to be particularly sensitive to temperature. The problem of high- temperature-dependent reduction of carbon assimilation is further exacerbated by high solar irradiance and leaf temperature can increase several degrees Celsius above air temperature. As a result of changes related with the different solubility of CO2 and O2 and the kinetic properties of

Rubisco, the rate of photorespiration (Pr) increases with increasing temperature, which reduces the net photosynthetic CO2 assimilation rate (Pn). The reduction of Pn associated with an increase of

Pr appears very quickly when a leaf is suddenly exposed to heat stress, but its magnitude is limited and Pn after that continue to decrease over time due to the development of physiological perturbations (Haldimann and Feller, 2005). Inhibition of photosynthesis by heat stress occurs both under photorespiratory and non-photorespiratory conditions which provides additional evidence that reduced Pn at elevated leaf temperatures can only partially be explained by the higher rates of

Pr at high temperature. PSII is a notoriously thermolabile component of the thylakoid membranes, whereas PSI is comparatively heat resistant (Haldimann and Feller, 2005).

The decrease in stomatal conductance reduces transpiration (E), is hypothesize that low E results in an increase in Tleaf above the optimum, causing irreversible damage to chloroplasts, possibly resulting in leaves using a smaller fraction of the absorbed light in electron transport. When light absorption exceeds light utilization in photosynthetic electron transport, excess absorbed light can

16 result in the production of singlet oxygen and increased reactive oxygen species such as superoxide

(O-2) and hydrogen peroxide (H2O2). Plants have evolved many defense mechanisms to minimize photo-oxidative damage. Some studies have shown that non-photochemical quenching (NPQ) of chlorophyll fluorescence can be used as an index of thermal energy dissipation. In fruit trees, NPQ is significantly higher in trees with a low fruit load than in trees with a high fruit load (Duan et al.,

2008). Heat not only damages the oxygen-evolving complex of PSII but also impairs electron transfer within the PSII reaction centers and downstream of PSII. Inactivation of PSII by high temperature is not rapidly reversible. However, thermal damage to PSII often appears only at rather high temperatures, especially when heat stress takes place in the presence of light as it usually happens under natural conditions (Haldimann and Feller 2005). On the other hand, there is evidence that deactivation of Rubisco, caused at least in part by thermal inactivation of Rubisco activase (Salvucci et al., 2001), is the principal cause of the inhibition of photosynthesis in leaves under moderate heat stress (Feller, Crafts-Brandner and Salvucci, 1998). Also, it has been demonstrated in leaves that temperatures at 44–46°C disrupt oxygen-evolving-complex (OEC) by releasing its manganese ion (Strasser, 1997; Hakala et al., 2005; Chen, Li and Cheng, 2008).

Linking Nutrient Dynamics with Plant Productivity and Responses to Abiotic Stress

The impact of climate change on trees being grown in marginal environments has stimulated a renewed interest for efficient resource use to understand the ability for plants to adapt to future climate scenarios (Regnard et al., 2009). Rootstocks, and mainly root systems, play a significant role in the response of apple to elevated temperatures or low water availability. There is little information on rootstock differences in nutrient uptake and water relations under elevated soil temperatures conditions. Drought impacts the nutritional status of plants by impacting uptake and

17 allocation at the whole plant level. Under low soil water content, the rate of diffusion of nutrients from the soil matrix to the absorbing root surface is also reduced (Hu et al., 2007; Duman, 2012).

Additionally, nutrient transport from the roots to the shoots may decrease because of reduced transpiration rates (Montanaro, Dichio and Xiloyannis, 2010; Duman, 2012; Montanaro et al.,

2012; de Freitas et al., 2013). Nutrient transport from the roots to the shoots is also restricted due to decreased active transport and membrane permeability. These factors may all contribute to the association between nutrient accumulation and plant water status (Hu et al. 2007).

Above ground, stomatal conductance and net CO2 assimilation rate in C3 fruit species depend upon environmental conditions such as solar irradiance, air temperature, relative humidity (VPD), soil and plant water status and mineral nutrition (Massonnet et al., 2007). Changes in soil temperature interact with other essential resources like both water and nutrient availability, elevated soil temperatures produce higher roots temperature, and this can influence root growth and often result in higher rates of roots respiration and uptake of water when this is not limited

(Pregitzer et al., 2000). Low soil water content limits plant growth mainly due to the reduction in carbon assimilation which is subject to the balance between photosynthesis and respiration.

Usually, half of the carbon assimilated by photosynthesis is lost by respiration necessary for growth and maintenance, but this balance changes under water stress because of increased stomatal closure. For example, although photosynthesis can decrease up to 100% becoming diminished under severe water stress, respiration rate can either increase or decrease, but will never become zero (Flexas et al., 2006). In the future, as climate change pushes temperatures higher in traditional apple growing regions (Stöckle et al., 2010), mitigation of the impacts of high temperatures will be critical to maintaining orchard productivity and high fruit quality (Kalcsits, Musacchi, et al.,

2017).

18 Scope of Research

My research examined the responses of rootstocks with different levels of vigor to abiotic stress and its impact on calcium, potassium, magnesium and nitrogen uptake and distribution in two contrasting apple cultivars: ‘Gala’ and ‘Honeycrisp.' By understanding how nutrient and water uptake capacity in different rootstocks is affected by either reduced water supply or elevated soil temperatures, a better understanding of the contributions of abiotic stress to elemental balance was obtained. This research strengthened the mechanistic understanding of xylem and phloem water and nutrient fluxes in apple and how those fluxes affect elemental balance and the susceptibility to nutrient-related physiological disorders. This knowledge about nutrient uptake and distribution will guide orchard management decisions to reduce pre- and post-harvest losses in the fruit industry.

Objectives:

1. Determine whether rootstock and/or scion genotype differ in nutrient uptake and

partitioning within plant organs under water limitations or supraoptimal (> 25 °C) soil

temperatures.

2. Investigate how different rootstock genotypes affect nutrient uptake and partitioning for

‘Honeycrisp’ apple cultivar grown in field conditions in a semi-arid climate and how they

response to water limited conditions.

3. Determine the different physiological responses of different rootstock genotypes to drought

and the combination of drought with other abiotic factors in the field.

4. Identify differences in the hydraulic kinetics and anatomical characteristics of four

different rootstock genotypes.

19 References

Adams, S., Lordan, J., Fazio, G., Bugbee, B., Francescatto, P., Robinson, T.L., Black, B., 2018. Effect of scion and graft type on transpiration, hydraulic resistance and xylem hormone profile of apples grafted on Geneva ® 41 and M.9-NICTM29 rootstocks. Sci. Hortic. (Amsterdam). 227, 213–222.

Alsina, M.M., De Herralde, F., Aranda, X., Savé, R., Biel, C., 2007. Water relations and vulnerability to embolism are not related: Experiments with eight grapevine cultivars. Vitis - J. Grapevine Res. 46, 1–6.

Amiri, M.E., Fallahi, E., Safi-Songhorabad, M., 2014. Influence of rootstock on mineral uptake and scion growth of 'Golden delicious' and 'Royal gala' apples. J. Plant Nutr. 37, 16–29.

Autio, W., Robinson, T., Archbold, D., Cowgill, W., Hampson, C., Parra Quezada, R., Wolfe, D., 2013. 'Gala' apple trees on supporter 4, P.14, and different strains of B.9, M.9 and M.26 rootstocks: Final 10-year report on the 2002 NC-140 apple rootstock trial. J. Am. Pomol. Soc. 67, 62–71.

Autio, W., Robinson, T.L., Cowgill, W., Hampson, C., Kushad, M., Lang, G., 2011. Performance of ‘Gala’ Apple Trees on Supporter 4 and Different Strains of B . 9 , M . 9 , and M . 26 Rootstocks as Part of the 2002 NC-140 311–318.

Autio, W.R., 2001. Rootstock and scion interact to affect apple tree performance: Results from the 1990 NC-140 cultivar/rootstock trial. Acta Hortic. 557, 41–46.

Autio, W.R., Krupa, J.S., Clements, J.M., Cowgill, W.P., Magron, R., Sollner-figler, S., 2013. Third-leaf Results from the 2010 NC-140 Apple Rootstock Trial in Massachusetts and New Jersey 78, 19–20.

Auvil, T., 2016. WSU Tree Fruit [WWW Document]. Geneva rootstock Perform.

Azcón-Bieto, J., Osmond, C.B., 1983. Relationship between Photosynthesis and Respiration. Plant Physiol. 71, 574–581.

Barber, S.A., Walker, J.M., Vasey, E.H., 1963. Mechanisms for the Movement of Plant Nutrients from the Soil and Fertilizer to the Plant Root. J. Agric. Food Chem. 11, 204–207.

Basset, C.L., 2013. Water use and drought response in cultivated and wild apples. In: Kourosh, V. (Ed.), Abiotic Stress - Plant Responses and Applications in Agriculture. InTech, pp. 249–275.

Bassirirad, H., 2000. Kinetics of nutrient uptake by roots : responses to global change . New Phytol Kinetics of nutrient uptake by roots : responses to global change. New Phytol. 147, 155–169.

Bondada, B.R., Matthews, M.A., Shackel, K.A., 2005. Functional xylem in the post-veraison grape berry. J. Exp. Bot. 56, 2949–2957.

Chen, L.S., Li, P., Cheng, L., 2008. Effects of high temperature coupled with high light on the balance between photooxidation and photoprotection in the sun-exposed peel of apple. Planta 228, 745–756.

Cornell University, 2010. Northeast region certified crop adviser [WWW Document]. Study Resour. URL https://nrcca.cals.cornell.edu/nutrient/CA1/ de Freitas, S.T., Amarante, C.V.T. d., Dandekar, A.M., Mitcham, E.J., 2013. Shading affects flesh calcium uptake and concentration, bitter pit incidence and other fruit traits in 'Greensleeves' apple. Sci. Hortic. (Amsterdam). 161, 266–272. de Freitas, S.T., Amarante, C.V.T. d., Labavitch, J.M., Mitcham, E.J., 2010. Cellular approach to understand bitter pit development in apple fruit. Postharvest Biol. Technol. 57, 6–13.

Drazeta, L., Lang, A., Morgan, L., Volz, R., Jameson, P.E., 2001. Bitter pit and vascular function in apples. Acta Hortic. 564, 387–392.

Duan, W., Fan, P.G., Wang, L.J., Li, W.D., Yan, S.T., Li, S.H., 2008. Photosynthetic response to low sink demand after fruit removal in relation to photoinhibition and photoprotection in peach trees. Tree Physiol. 28, 123–132.

Duman, F., 2012. Uptake of mineral elements during abiotic stress. In: Ahmad, P., Prasad, M.N.V. (Eds.), Abiotic Stress Responses in Plants: Metabolism, Productivity and Sustainability. Springer, New York, pp. 267–281.

Fallahi, E., 2012. Influence of rootstock and irrigation methods on water use, mineral nutrition, growth, fruit yield, and quality in 'Gala' apple. Horttechnology 22, 731–737.

Fallahi, Esmaeil, Arzani, K., Fallahi, B., 2013a. Long-term leaf mineral nutrition in 'Pacific Gala' apple (Malus x domestica Borkh.) as affected by rootstock type and irrigation system during six stages of tree development. J. Hortic. Sci. Biotechnol. 88, 685–692.

Fallahi, Esmaeil, Bakhshi, D., Fallahi, B., 2013b. Postharvest Fruit Quality and Growth of 'Pacific Gala' Apple Trees at Different Ages as Influenced by Irrigation and Rootstock. Int. J. Fruit Sci. 13, 478–491.

Fallahi, E., Colt, W.M., Fallahi, B., Chun, I.J., 2002. The importance of apple rootstocks on tree growth, yield, fruit quality, leaf nutrition, and photosynthesis with an emphasis on 'FUJI.' Horttechnology 12, 38–44.

Fallahi, E., Eichert, T., 2013. Principles and practices of foliar nutrients with an emphasis on nitrogen and calcium sprays in apple. Horttechnology 23, 542–547.

Fallahi, Esmaeil, Fallahi, B., Shafii, B., 2013c. Irrigation and rootstock influence on water use, tree growth, yield, and fruit quality at harvest at different ages of trees in 'Pacific Gala' apple.

21 HortScience 48, 588–593.

Fallahi, E., Fallahi, B., Shafii, B., 2013. Water use, mineral nutrition, tree growth, yield, and fruit quality of 'Fuji' and 'Gala' apples under various irrigation systems and rootstocks. Acta Hortic. 984, 57–68.

Fallahi, E., Westwood, M.N., 1984. Effects of rootstocks and K and N fertilizers on seasonal apple fruit mineral composition in a high density orchard. J. Plant Nutr. 7, 1179–1201.

Fan, P.G., Li, L.S., Duan, W., Li, W.D., Li, S.H., 2010. Photosynthesis of young apple trees in response to low sink demand under different air temperatures. Tree Physiol. 30, 313–325.

Fazio, G., Kviklys, D., Grusak, M.A., Robinson, T., 2013. Phenotypic Diversity and QTL Mapping of Absorption and Translocation of Nutrients by Apple Rootstocks. Asp. Appl. Biol. 119, 37– 50.

Fazio, G., Kviklys, D., Grusak, M.A., Robinson, T., Genetics, P., Unit, R., 2012. Soil pH, Soil Type and Replant Disease Affect Growth and Nutrient Absorption of Apple Rootstocks. New York State Hortic. Soc. 20, 22–28.

Fazio, G., Robinson, T.L., Aldwinckle, H.S., 2015. The geneva apple rootstock breeding program. plant Breed. Rev. 39, 379–424.

Fazio, G., Wan, Y., Kviklys, D., Romero, L., Adams, R., Strickland, D., Robinson, T., 2014. Dw2, a new dwarfing locus in apple rootstocks and its relationship to induction of early bearing in apple scions. J. Am. Soc. Hortic. Sci. 139, 87–98.

Feller, U., Crafts-Brandner, S.J., Salvucci, M.E., 1998. Moderately High Temperatures Inhibit Ribulose-1,5-Bisphosphate Carboxylase/Oxygenase (Rubisco) Activase-Mediated Activation of Rubisco. Plant Physiol 116, 539–546.

Flexas, J., Bota, J., Galmés, J., Medrano, H., Ribas-Carbó, M., 2006. Keeping a positive carbon balance under adverse conditions: Responses of photosynthesis and respiration to water stress. Physiol. Plant. 127, 343–352.

Gallardo, R.K., Hanrahan, I., Hong, Y.A., Luby, J.J., 2015. Crop load management and the market profitability of ‘Honeycrisp’ apples. Horttechnology 25, 575–584.

Gur, A., Hepner, J., Shulman, Y., 1979. The .influence of root temperature on apple trees. IV. The effect on the mineral nutrition of the tree. J. Hortic. Sci. 54, 313–321.

Hakala, M., Tuominen, I., Keränen, M., Tyystjärvi, T., Tyystjärvi, E., 2005. Evidence for the role of the oxygen-evolving manganese complex in photoinhibition of Photosystem II. Biochim. Biophys. Acta - Bioenerg. 1706, 68–80.

Haldimann, P., Feller, U., 2005. Growth at moderately elevated temperature alters the

22 physiological response of the photosynthetic apparatus to heat stress in pea (Pisum sativum L.) leaves. Plant, Cell Environ. 28, 302–317.

Hammer, G.L., Dong, Z., McLean, G., Doherty, A., Messina, C., Schussler, J., Zinselmeier, C., Paszkiewicz, S., Cooper, M., 2009. Can changes in canopy and/or root system architecture explain historical maize yield trends in the U.S. corn belt? Crop Sci. 49, 299–312.

Hanrahan, I., McFerson, J., 2016. 'Honeycrisp' apple disorders: Soft scald development and management. Acta Hortic. 1120, 165–169.

Hawkesford, M., Horst, W., Kichey, T., Lambers, H., Schjoerring, J., Moller, I.S., White, P., 2012. Function of macronutrients. In: Marschner, P. (Ed.), Mineral Nutrition of Higher Plants. Academic Press, pp. 135–189.

Hodge, A., Berta, G., Doussan, C., Merchan, F., Crespi, M., 2009. Plant root growth, architecture and function, Plant and Soil.

Howard, N.P., van de Weg, E., Bedford, D.S., Peace, C.P., Vanderzande, S., Clark, M.D., Teh, S.L., Cai, L., Luby, J.J., 2017. Elucidation of the ‘Honeycrisp’ pedigree through haplotype analysis with a multi-family integrated SNP linkage map and a large apple (Malus×domestica) pedigree-connected SNP data set. Hortic. Res. 4, 17003.

Hu, Y., Burucs, Z., von Tucher, S., Schmidhalter, U., 2007. Short-term effects of drought and salinity on mineral nutrient distribution along growing leaves of maize seedlings. Environ. Exp. Bot. 60, 268–275.

Ingestad, T., Agren, G.I., 1995. Plant nutrition and growth - Basic principles. Plant Soil 169, 15– 20.

Jemrić, T., Fruk, I., Fruk, M., Radman, S., Sinkovič, L., Fruk, G., 2016. Bitter pit in apples: Pre- and postharvest factors: A review. Spanish J. Agric. Res. 14.

Juniper, B.E., Watkins, R., Harris, S.A., 1998. The origin of the apple. Acta Hortic.

Kalcsits, L., Musacchi, S., Layne, D.R., Schmidt, T., Mupambi, G., Serra, S., Mendoza, M., Asteggiano, L., Jarolmasjed, S., Sankaran, S., Khot, L.R., Espinoza, C.Z., 2017. Above and below-ground environmental changes associated with the use of photoselective protective netting to reduce sunburn in apple. Agric. For. Meteorol. 237–238, 9–17.

Kalcsits, L.A., 2016. Non-destructive measurement of calcium and potassium in apple and pear using handheld X-ray fluorescence. Front. Plant Sci. 7, 442.

Kirkby, E., 2012. Introduction, definition and classification of nutrients. In: Marschner, P. (Ed.), Mineral Nutrition of Higher Plants. Academic Press, pp. 3–5.

Klein, T., 2014. The variability of stomatal sensitivity to leaf water potential across tree species

23 indicates a continuum between isohydric and anisohydric behaviours. Funct. Ecol. 28, 1313– 1320.

Korban, S.S., Skirvin, R.M., 1984. Nomenclature of the cultivated apple. HortScience 19, 177– 180.

Larkindale, J., Mishkind, M., Vierling, E., 2005. Plant responses to high temperature. In: Jenks, M.A., Hasegawa, P.M. (Eds.), Plant Abiotic Stress. Blackwell Publishing Ltd., pp. 100–144.

Lauri, P.É., Barigah, T.S., Lopez, G., Martinez, S., Losciale, P., Zibordi, M., Manfrini, L., Corelli- Grappadelli, L., Costes, E., Regnard, J.L., 2016. Genetic variability and phenotypic plasticity of apple morphological responses to soil water restriction in relation with leaf functions and stem xylem conductivity. Trees - Struct. Funct. 30, 1893–1908.

Lohraseb, I., Collins, N.C., Parent, B., 2017. Diverging temperature responses of CO2 assimilation and plant development explain the overall effect of temperature on biomass accumulation in wheat leaves and grains. AoB Plants plw092.

Lordan, J., Fazio, G., Francescatto, P., Robinson, T., 2017. Effects of apple (Malus × domestica) rootstocks on scion performance and hormone concentration. Sci. Hortic. (Amsterdam). 225, 96–105.

Luby, J., 2003. Taxonomic classification and brief history. In: Ferree, D.C., Warrington, I.J. (Eds.), Apples. Botany, Production and Use. CABI Publishing, Cambridge, MA., pp. 1–14.

Lynch, J.P., Ho, M.D., 2005. Rhizoeconomics: Carbon costs of phosphorus acquisition. Plant Soil 269, 45–56.

Manschadi, A.M., Christopher, J., Devoil, P., Hammer, G.L., 2006. The role of root architectural traits in adaptation of wheat to water-limited environments. Funct. Plant Biol. 33, 823–837.

Manschadi, A.M., Manske, G.G., Vlek, P.L., 2013. Root architecture and resource acquisition: Wheat as a model plant. In: Eshel, A., Beeckman, T. (Eds.), Plant Roots: The Hidden Half. CRC Press, pp. 22.1-22.13.

Marini, R.P., Autio, W.R., Black, B., Cline, J., Cowgill, W.R., Crassweller, R.M., Domoto, P.A., Hampson, C., Moran, R., Quezada, R.A., Robinson, T., Ward, D.L., Wolfe, D., 2013. Return bloom on ’Golden Delicious’ apple trees as affected by previous season ’ s crop density on three rootstocks at 11 locations 67, 73–79.

Marini, R.P., Autio, W.R., Black, B., Cline, J.A., Cowgill, W., Crassweller, R., Domoto, P., Hampson, C., Moran, R., Parra-Quezada, R.A., Robinson, T., Stasiak, M., Ward, D.L., Wolfe, D., 2012. Summary of the NC-140 Apple Physiology Trial: The Relationship Between 'Golden Delicious' Fruit Weight and Crop Density at 12 locations as Influenced by Three Dwarfing Rootstocks. J. Am. Pomol. Soc. 66, 78–90.

24 Marini, R.P., Black, B., Crassweller, R.M., Domoto, P.A., Hampson, C., Moran, R., Robinson, T., Stasiak, M., Wolfe, D., 2014. Performance of 'Golden Delicious' apple on 23 rootstocks at eight locations: A ten-year summary of the 2003 NC-140 dwarf rootstock trial. J. Am. Pomol. Soc. 68, 54–68.

Massonnet, C., Costes, E., Rambal, S., Dreyer, E., Regnard, J.L., 2007. Stomatal regulation of photosynthesis in apple leaves: Evidence for different water-use strategies between two cultivars. Ann. Bot. 100, 1347–1356.

Mattheis, J.P., Rudell, D.R., Hanrahan, I., 2017. Impacts of 1-methylcyclopropene and controlled atmosphere established during conditioning on development of bitter pit in 'Honeycrisp' apples. HortScience 52, 132–137.

Mazzeo, M., Dichio, B., Clearwater, M.J., Montanaro, G., Xiloyannis, C., 2013. Hydraulic resistance of developing Actinidia fruit. Ann. Bot. 112, 197–205.

McKay, S.J., Bradeen, J.M., Luby, J.J., 2011. Prediction of Genotypic Values for Apple Fruit Texture Traits in a Breeding Population Derived from 'Honeycrisp.' J. Am. Soc. Hortic. Sci. 136, 408–414.

Mengel, K., Kirkby, E.A., Kosegarten, H., Appel, T., 2001. Plan nutrients. In: Mengel, K., Kirkby, E.A., Kosegarten, H., Appel, T. (Eds.), Principles of Plant Nutrition. Kluwer Academic, pp. 1–13.

Montanaro, G., Dichio, B., Xiloyannis, C., 2010. Significance of fruit transpiration on calcium nutrition in developing apricot fruit. J. Plant Nutr. Soil Sci. 173, 618–622.

Montanaro, G., Dichio, B., Xiloyannis, C., Lang, A., 2012. Fruit transpiration in kiwifruit: Environmental drivers and predictive model. AoB Plants 2012, 1–9.

Moran, R.E., 2014. Growth and yield of 'Honeycrisp' apple trees with preplant inoculation with Mycorrhizae and soil-incorporates compost. Entomophaga 68, 2–13.

Moretti, C.L., Mattos, L.M., Calbo, A.G., Sargent, S.A., 2010. Climate changes and potential impacts on postharvest quality of fruit and vegetable crops: A review. Food Res. Int. 43, 1824–1832.

Musacchi, S., Serra, S., 2018. Apple fruit quality: Overview on pre-harvest factors. Sci. Hortic. (Amsterdam). 234, 409–430.

Nardini, A., Tyree, M.T., 1999. Root and shoot hydraulic conductance of seven Quercus species. Ann. For. Sci. 56, 371–377.

Neilsen, G., Havipson, C., 2014. 'Honeycrisp' Apple Leaf and Fruit Nutrient Concentration is Affected by Rootstock During Establishment. J. Am. Pomol. Soc. 68, 178–189.

25 Pregitzer, K.S., King, J.S., Burton, A.J., Brown, S.E., 2000. Responses of tree fine roots to temperature. New Phytol. 147, 105–115.

Racsko, J., Schrader, L.E., 2012. Sunburn of Apple Fruit: Historical Background, Recent Advances and Future Perspectives. CRC. Crit. Rev. Plant Sci. 31, 455–504.

Ray, D., Sheshshatee, M.S., Mukhopadhyay, K., Bindumadhava, H., Prasad, T.G., Udaya Kumar, M., 2003. High nitrogen use efficiency in rice genotypes is associated with higher net photosynthetic rate at lower Rubisco content. Biol. Plant. 46, 251–256.

Regnard, J.L., Segura, V., Merveille, N., Durel, C.E., Costes, E., 2009. QTL analysis for leaf gas exchange in an apple progeny grown under atmospheric constraints. Acta Hortic. 814, 369– 374.

Reig, G., Jentsch, P., Rosenberger, D., 2016. Effects of Sunburn Treatments on 'Honeycrisp' in the Hudson Valley in 2015. New York Fruit Q. 24, 5–10.

Rengel, Z., Marschner, P., 2005. Nutrient availability and management in the rhizosphere: Exploiting genotypic differences. New Phytol. 168, 305–312.

Robinson, T.L., Fazio, G., Aldwinckle, H.S., 2014. Characteristics and Performance of Four New Apple Rootstocks from the Cornell-USDA Apple Rootstock Breeding Program 651–656.

Rosenberger, D., Schupp, J., Watkins, C., Iungerman, K., Hoying, S., Straub, D., Cheng, L., 2001. 'Honeycrisp': Promising profit maker or just another problem child? New York State Hortic. Soc. 9, 4–8.

Rosenberger, D.A., Schupp, J.R., Hoying, S.A., Cheng, L., Watkins, C.B., 2004. Controlling bitter pit in ‘Honeycrisp’ apples. Horttechnology 14, 342–349.

Salisbury, F.B., Ross, C.W., 1992a. Cells: Water, solutions, and surfaces. In: Carey, J.C. (Ed.), Plant Physiology. Wadsworth Inc., pp. 1–188.

Salisbury, F.B., Ross, C.W., 1992b. Photosynthesis: Chloroplasts and light. In: Carey, J.C. (Ed.), Plant Physiology. Wadsworth Inc., pp. 207–224.

Salvucci, M.E., Osteryoung, K.W., Crafts-Brandner, S.J., Vierling, E., 2001. Exceptional sensitivity of Rubisco activase to thermal denaturation in vitro and in vivo. Plant Physiol. 127, 1053–1064.

Schultz, H.R., 2003. Differences in hydraulic architecture account for near- isohydric and anisohydric behaviour of two eld-grown. Plant, Cell Environ. 26, 1393–1406.

Serra, S., Leisso, R., Giordani, L., Kalcsits, L., Musacchi, S., 2016. Crop load influences fruit quality, nutritional balance, and return bloom in 'Honeycrisp' apple. HortScience 51, 236– 244.

Sharkey, T.D., 2005. Effects of moderate heat stress on photosynthesis: Importance of thylakoid reactions, rubisco deactivation, reactive oxygen species, and thermotolerance provided by isoprene. Plant, Cell Environ. 28, 269–277.

Shoffe, Y. Al, Nock, J.F., Baugher, T.A., Watkins, C.B., 2016. 'Honeycrisp' – To Condition or Not Condition ? 24, 19–24.

Stöckle, C.O., Nelson, R.L., Higgins, S., Brunner, J., Grove, G., Boydston, R., Whiting, M., Kruger, C., 2010. Assessment of climate change impact on Eastern Washington agriculture. Clim. Change 102, 77–102.

Strasser, B.J., 1997. Donor side capacity of Photosystem II probed by chlorophyll a fluorescence transients. Photosynth. Res. 52, 147–155.

Taiz, L., Zeiger, E., 2002. Transport and translocation of water and solutes. In: Sinauer, A.D. (Ed.), Plant Physiology. Sinauer Associates Inc., pp. 33–46.

Taiz, L., Zeinger, E., 2002. Stress Physiology. In: Sinauer, A.D. (Ed.), Plant Physiology. Sinauer Associates Inc., pp. 593–623.

Tombesi, S., Nardini, A., Farinelli, D., Palliotti, A., 2014. Relationships between stomatal behavior, xylem vulnerability to cavitation and leaf water relations in two cultivars of Vitis vinifera. Physiol. Plant. 152, 453–464.

Tong, C.B.S., Bedford, D.S., Luby, J.J., Propsom, F.M., Beaudry, R.M., Mattheis, J.P., Watkins, C.B., Weis, S.A., 2003. Location and Temperature Effects on Soft Scald in 'Honeycrisp' Apples. HortScience 38, 1153–1155.

Tworkoski, T., Fazio, G., 2011. Physiological and morphological effects of size-controlling rootstocks on “fuji” apple scions. Acta Hortic. 903, 865–872.

Tyerman, S.D., Tilbrook, J., Pardo, C., Kotula, L., Sullivan, W., Steudle, E., 2004. Direct measurement of hydraulic properties in developing berries of Vitis vinifera L . cv Shiraz and Chardonnay. Aust. J. Grape Wine Res. 10, 170–181.

Tyree, M.T., Patino, S., Bennink, J., Alexander, J., 1995. Dynamic measurements of root hydraulic conductance using a high-pressure flowmeter in the laboratory and field. J. Exp. Bot. 46, 83– 94.

US Apple Association, 2017. US. Apple Association [WWW Document]. Statistics (Ber). URL http://usapple.org/all-about-apples/apple-industry-statistics/

Vandeleur, R.K., Mayo, G., Shelden, M.C., Gilliham, M., Kaiser, B.N., Tyerman, S.D., 2009. The Role of Plasma Membrane Intrinsic Protein Aquaporins in Water Transport through Roots: Diurnal and Drought Stress Responses Reveal Different Strategies between Isohydric and

27 Anisohydric Cultivars of Grapevine. Plant Physiol. 149, 445–460.

Verbruggen, N., Hermans, C., 2013. Physiological and molecular responses to magnesium nutritional imbalance in plants. Plant Soil 368, 87–99.

Wang, M., Zheng, Q., Shen, Q., Guo, S., 2013. The critical role of potassium in plant stress response. Int. J. Mol. Sci. 14, 7370–7390.

Watkins, C.B., Nock, J.F., 2012. Controlled-atmosphere Storage of ‘Honeycrisp’ Apples 47, 886– 892.

Watkins, C.B., Nock, J.F., Weis, S.A., Jayanty, S., Beaudry, R.M., 2004. Storage temperature, diphenylamine, and pre-storage delay effects on soft scald, soggy breakdown and bitter pit of 'Honeycrisp' apples. Postharvest Biol. Technol. 32, 213–221.

Wells, C.E., Yanai, R.D., 2000. Building roots in a changing environment: Implications for root longevity Building roots in a changing environment : implications for root longevity 147, 33– 42.

Wertheim, S.J., Webster, A., 2003. Apple Rootstocks. In: Ferre, D.C., Warrington, I.J. (Eds.), Apples. Botany, Production and Use. CABI Publishing, Cambridge, MA.

Westwood, M.N., 1978. The general plant environment. In: Freeman, W.H. (Ed.), Temperate-Zone Pomology. Freeman and Company, pp. 20–40.

White, P.J., 2012. Ion uptake mechanisms of individual cells and roots: Short-distance transport. In: Marschner, P. (Ed.), Mineral Nutrition of Higher Plants. Academic Press, pp. 7–47.

White, P.J., Broadley, M.R., 2003. Calcium in plants. Ann. Bot. 92, 487–511.

Wood, A.J., 2005. Eco-physiological Adaptations to Limited Water Enviornments. Plant Abiotic Stress 1–13.

Wünsche, J.N., Ferguson, I.B., 2010. Crop Load Interactions in Apple, Horticultural Reviews.

Zandalinas, S.I., Mittler, R., Balfagón, D., Arbona, V., Gómez-Cadenas, A., 2018. Plant adaptations to the combination of drought and high temperatures. Physiol. Plant. 162, 2–12.

28 Table 1. 1. The top six apple cultivars grown and consumed in the United States (U.S. Apple

Association, 2017).

Rank US Production US Consumption 1 ‘Red Delicious’ ‘Gala’ 2 ‘Gala’ ‘Red Delicious’ 3 ‘Granny Smith’ ‘Fuji’ 4 ‘Fuji’ ‘Granny Smith 5 ‘Golden Delicious’ ‘Honeycrisp’ 6 ‘Honeycrisp’ ‘Golden Delicious’

Table 1. 2. Relative tree size of Geneva® rootstocks cultivars relative to Bud-9, M9-T337, and

M26 for Washington State (Auvil, 2016).

Percent of Tree Size Geneva Rootstocks Bud-9 M.9-337 M.26 G.65 100 70 50 G.11 140 100 70 G.41 140 100 70 G.935 160 115 80 G.969 160 115 80 G.214 160 115 80 G.210 160 115 80 G.222 160 115 80 G.814 160 115 80 G.16 160 115 80 G.30 200 143 100 G.890 200 143 100 G.202 200 143 100

30 Table 1. 3. Nutrient movement from the soil to the roots for nitrogen, phosphorus, potassium, calcium, magnesium, and sulfur (Cornell University, 2010; Barber et al. 1963).

Nutrient Uptake form Mass Flow Diffusion Root Interception - Nitrate (NO3 ) and Nitrogen X ammonium + (NH4 ) (phosphate 2- (HPO4 and X Phosphorus - H2PO4 ) Potassium K+ X X Calcium Ca2+ X X Magnesium Mg2+ X X - Sulfur sulfate (SO4 ) X X

31 CHAPTER TWO: APPLE SCION AND ROOTSOCK CONTRIBUTE TO NUTRIENT

UPTAKE AND PARTITIONING UNDER DIFFERENT BELOWGROUND

ENVIRONMENTS

Nadia A. Valverdi, Lailiang Cheng, and Lee Kalcsits

This chapter has been already published: Valverdi, N.A., Cheng, L., Kalcsits, L., 2019. Apple Scion and Rootstock Contribute to Nutrient Uptake and Partitioning under Different Belowground Environments. Agronomy 9, 415.

Abstract

Soil environment strongly contributes to tree growth and development, affecting nutrient and water uptake. Composite woody perennials, like apple, are a combination of two genetically different parts: a rootstock and a scion, and yet, the role of each part on nutrient uptake and distribution under differing soil environments has not been previously studied. We tested how water limitations and elevated soil temperatures, applied to different apple rootstocks and scions, affected mineral nutrient uptake and distribution on young apple trees. Two one-year-old potted apple cultivars were grown in a greenhouse, ‘Honeycrisp’ and ‘Gala,’ combined with four rootstocks: G890, G41,

M9, and B9. Belowground abiotic environmental treatments were imposed after trees reached approximately 45 cm height for 60 days. Water limitations reduced aboveground biomass and, to a lesser extent, root biomass. ‘Gala’ and rootstock G890 showed elevated mineral nutrient uptake than ‘Honeycrisp’ and the rest of rootstocks. Additionally, G890 showed a greater plasticity for both biomass and mineral nutrient accumulation. Elevated soil temperatures increased the ratios of K:Ca, N:Ca, Mg:Ca, and (N+K+Mg):Ca in leaf tissue of rootstock G41 and ‘Honeycrisp’. These findings highlight the importance of the use of scion and rootstock genotypes that are adapted to specific soil environments to ensure optimal nutrient uptake.

32 Keywords: Malus domestica; water stress; root-zone temperature; biomass partitioning; nutrient balance

33 Introduction

Water availability is one of the most significant limitations to plant productivity and largely dictates the distribution of plant species around the world (Wood, 2005; Lauri et al., 2016). Many tree fruits producing arid regions are typically exposed to elevated abiotic stress including high light intensity, temperature, and low rainfall that can affect crop yield and quality (Kalcsits, et al.,

2017). Most of these regions frequently rely on irrigation to provide an adequate water supply to maintain orchard productivity (B. H. Liu et al., 2012) and fruit quality (Sofo et al., 2012). These irrigation-dependent regions may experience higher risks from variations in water availability and elevated temperatures in the future (Stöckle et al., 2010; Vano et al., 2010). Although water and plant nutrition are inextricably linked, there is little information on how plant water status affects plant nutrient uptake and distribution, particularly for perennial tree species like apple.

Like many other fruit trees, apple (Malus × domestica Borkh.) trees are a combination of two genetically different parts: a rootstock and a scion. The rootstock constitutes the root system and a small portion of the lower trunk, and the scion form the aboveground portion of the tree

(Wertheim and Webster, 2003). Rootstocks are essential components in productive apple orchards because of their contributions to water and nutrient uptake, anchorage, vigor control, precocity, pest and disease protection, and abiotic stress resistance (Fazio et al., 2013). The root systems in fruit trees are critical for nutrient and water uptake from the soil environment. These highly plastic systems have the capacity to scavenge heterogeneous soil environments to reach water and nutrient-rich regions (Atkinson and Wilson, 1980; Jackson, 2003). Rootstocks have been shown a large degree of genotypic variation in architectural characteristics and phenotypic malleability that may affect how they respond to water supply (Tworkoski, Fazio and Glenn, 2016).

34 Soil abiotic environment plays a vital role in aboveground scion tree growth and development.

Changes in soil temperature have been shown to interact with other essential resources, including both water and nutrient availability (Bassirirad, 2000). Elevated soil temperatures, above 25 °C, can influence root growth, root turnover, and leads to increases in carbon losses due to higher rates of root respiration (Gur, Mizrahi and Samish, 1976; Pregitzer et al., 2000). Changes in root growth and development, and the availability of water and mineral nutrients in the soil matrix, are important factors that may contribute to differential responses of apple rootstocks to the soil environment. These responses include reduced shoot growth, fruit size and quality, and increased floral bud induction (Atkinson et al., 1997). In temperate zones, soil temperature at a constant depth normally increase from spring to summer and then decrease from summer to winter, varying with soil properties and vegetation (Pregitzer et al., 2000), and the vertical distribution of soil nutrients is a result of factors like weathering, atmospheric deposition, and leaching, where plant nutrients cycling is important. An example of this is the high content of potassium and phosphorus in the topsoil layer (20 cm) (Jobbágy et al., 2001). These factors combined with abiotic interactions create high amounts of heterogeneity in the soil that make it difficult to quantify rootstock related responses to field soil environments.

Soil water limitations can impact the nutritional status of plants by affecting the absorption and allocation of nutrients among plant organs. Low water content in the soil reduces the rate of diffusion of nutrients from the soil matrix to the absorbing root surface area (Hu et al., 2007;

Duman, 2012). For macronutrients such as calcium, nitrogen, potassium, and magnesium, its absorption by the plant occurs mainly through mass flow from the soil solution into the xylem via the transpiration flow. Once inside the plant vascular system, nitrogen, potassium, and magnesium can be redistributed through the phloem. Calcium, on the other hand, has low phloem mobility,

35 and for this its capacity for redistribution once it reaches a sink organ (active growing tissue i.e., apical meristems, growing fruits and leaves, root tips) is very limited (White, 2012).

Consequentially, greater rates of water transpiration will result in a greater allocation of mineral nutrients from the root to aboveground tissues. In periods of decreased water availability, transpiration rates and root development are lower affecting the translocation of plant nutrients to aboveground tissues. These factors contribute to the association between nutrient accumulation and plant water status (Hu et al., 2007).

Nutrient ratios have been suggested to be a better indicator of the tree nutritional balance than absolute concentrations (Casierra-posada and Lizarazo, 2004). Some fruit disorders observed in apple that reduce fruit quality and marketability, such as bitter pit, are associated with nutrient imbalances or deficiencies. Bitter pit is a physiological disorder related to calcium content and the ratios of nitrogen, potassium and magnesium to calcium in the fruit (de Freitas, do Amarante and

Mitcham, 2015). Furthermore, rootstocks have been reported to affect bitter pit incidence, which can be aggravated by excessive tree vigor and fruit size, low soil pH, boron deficiency, and environmental stresses such as drought (Rosenberger et al., 2004). These nutrient related disorders may be overcome identifying rootstock genotypes with improved nutrient uptake and partitioning.

Considering that higher temperatures are expected for many apple growing regions (Stöckle et al.,

2010), understanding the effect of elevated soil temperatures and the reductions in water availability on mineral nutrient uptake and distribution by different rootstock and scion cultivars will be critical to maintaining orchard productivity and high fruit quality (Kalcsits, et al., 2017).

The objective of this study was to determine whether rootstock and/or scion genotype differ in nutrient uptake and partitioning within plant organs under water limitations or supraoptimal (> 25

°C) soil temperatures. We hypothesize that different belowground environments will impact

36 nutrient uptake and distribution and that the magnitude of these responses will be dependent on rootstock and scion genotype. This study will provide critical information outlining how scion and rootstock genotypes interact in apple and respond to changes in soil conditions that may be experienced in the near future.

Materials and Methods

Plant Material and Nutrient Composition

The experiment was performed at Washington State University Tree Fruit Research and Extension

Center in Wenatchee, WA (47°26′17.6′′ N, 120°20′48.3′′ W). Two scions, ‘Honeycrisp’ and ‘Gala’ were selected as scion cultivars because of their contrasting susceptibility to calcium-related disorders (White and Broadley, 2003; Rosenberger et al., 2004; de Freitas et al., 2013; Amiri,

Fallahi and Safi-Songhorabad, 2014) and grafted onto four rootstocks with genotypic variation in vigor. Two of the rootstocks were from the Geneva series: G41 (dwarf) and G890 (semi-dwarf).

Rootstock G41 is the most commonly used Geneva rootstock in Washington State, and G890 is the most vigorous of the selections. The other two rootstocks were M9-T337 (M9) (dwarf) which is the standard for the apple industry and breeding programs, and Bud-9 (B9) (dwarf) which is one of the most dwarfing commercially available rootstocks. Rootstock liners were planted in 10.9 L

(diameter: 27 cm, height: 23 cm) pots using a sterile, high porosity growing medium to allow for adequate drainage and aeration (Pro-mix HP, Quakertown, PA, USA) and to avoid mineralization of nutrients by microorganisms. A week after establishment, scion wood was cleft grafted to each rootstock genotype.

Grafted trees were grown in a greenhouse between April and August 2017 under ambient light and humidity with temperatures maintained between 20 and 25 °C. Trees were drip-irrigated daily for

37 30 minutes with emitters that applied 3.78 L h-1 until soil saturation was achieved and fertilized every two weeks (0.5 L per tree) with a water-soluble fertilizer containing 24% total nitrogen

(3.5% ammoniacal nitrogen and 20.5% urea nitrogen), 8% available phosphate (P2O5), 16% soluble potassium (K2O), 0.02% boron, 0.07% water-soluble copper, 0.15% chelated manganese,

0.0005% molybdenum, and 0.06% water-soluble zinc and applied at elemental concentrations of

4.53 mM N, 0.68 mM P, 1.08 mM K, 0.003 mM Cu, 0.007 mM Fe, 0.002 mM Mn, 1.38–5 mM

Mo, and 0.002 mM Zn). Sufficient calcium and sulfur concentrations were present in the mountain- based water source (Public utility district, 2018).

After trees reached 45 cm of height approximately, trees were arranged in a split-plot design with three reps. The main plots consisted of a water-limited treatment (50% field capacity), a heat stress treatment (100% field capacity with potting media heated to 5 °C above the unheated control) and a control with full irrigation (100% field capacity). Subplots consisted of the eight rootstock-scion combinations mentioned above. Field capacity was determined by watering the trees to saturation and, after allowing the media to drain gravimetrically, measuring the volumetric water content twice per week using a capacitance EC-5 soil volumetric content sensor at 10 cm from the tree’s trunk and to 15 cm depth in the pot (Decagon Devices, Pullman, WA, USA) connected to a handheld data logger (Decagon Devices, Pullman, WA, USA). For the water-limited treatment, once soil moisture had been depleted to 50% of field capacity, water was added to elevate soil moisture to just above 60% field capacity. Soil temperature was controlled using a Hydrofarm digital temperature controller (Hydrofarm, Petaluma, CA, USA) connected to heating cables and heating blankets set to elevate the temperature of the root-zone 5°C above ambient temperature.

Pot temperature was recorded every 30 minutes in one pot per block of the heat and control treatments using a HOBO temperature sensor placed 10 cm from the tree’s trunk and to 15 cm

38 depth in the pot (Onset Computer Corp., Bourne, MA, USA). Stem water potential was measured every two weeks using a Scholander system Pressure Chamber Instrument (PMS Instrument Co.,

Albany, OR, USA) at solar noon to monitor plant water status (Shackel et al., 2000).

Destructive Sampling and Mineral Nutrient Analysis

Sixty days after the start of treatment, the trees were divided into roots, stems, and leaves. Roots were carefully washed using tap water to remove potting media. Root, stem, and leaf samples were then dried to a stable weight in a chamber with constant air flow at 25 °C for 30 days. Once dry, all samples were weighed. Leaf samples were ground into a fine powder using a VWR high throughput homogenizer (VWR, Radnor, PA, USA). For stems and roots, samples were initially ground to 20-micron size using a Wiley Mini mill (Thomas Scientific LLC., Swedesboro, NJ,

USA) and then ground to sub-micron size using a VWR high throughput homogenizer (VWR,

Radnor, PA, USA).

For mineral nutrient analysis, 200 mg of roots, stems or leaves were weighed into PTFE tubes, and acid digested using 6 mL of HNO3. After digestion, the solution was filtered with a 0.45 µM PTFE filter (Thermo Fisher Scientific, Waltham, MA, USA). Filtered digests were then diluted 100x and analyzed using an Agilent 4200 microwave plasma-atomic emission spectrometer (MP-AES)

(Agilent, Santa Clara, CA, USA) and run in combination with calcium, potassium, and magnesium

ICP standards for validation (Kalcsits, 2016). Nitrogen content was determined using a PDZ

Europa ANCA-GSL elemental analyzer interfaced to a PDZ Europa 20–20 isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK) at the UC Davis Stable Isotope Facility in Davis, CA,

USA. From these measurements, concentration (mg/g of biomass) was calculated, and this value multiplied by the total biomass of each plant organ, allowing to estimate the plant organ nutrient

39 content (mg). Additionally, stoichiometric ratios of nitrogen to calcium (N:Ca), potassium to calcium (K:Ca), magnesium to calcium (Mg:Ca), and the sum of nitrogen, potassium and magnesium to calcium ((N + K + Mg):Ca) in leaves were calculated.

Data were analyzed by performing an analysis of variance (ANOVA), and a Tukey’s means separation with a confidence of 95% (SAS, ver. 9.4 PROC GLM).

Results

Soil water content in the pots of the water-limited treatment was effectively reduced by 40% approximately compare to the control treatments. Water content of the elevated soil temperature treatment was constantly slightly higher than control due to the use of heating blankets under the pots, possibly slowing water loss after the irrigation events (Fig. 1). Root-zone average temperature was effectively elevated approximately 5 °C than water-limited and control treatments as intended (Fig. 2). Mid-day stem water potential showed that the water-limited treatment caused significantly lower mid-day stem water potential relative to the control while the elevated soil temperature treatment did not affect stem water potential (Fig. 3).

Plant Growth

Leaf biomass, leaf area, stem biomass, and root:shoot ratio were affected differently for each scion and rootstock combination (Table 1). ‘Gala’ had 40% more biomass than ‘Honeycrisp’ with G890; while there was no significant difference between scions with G41, M9, and B9. The rootstock genotypes responded differently to water limitations (Table 1). Root biomass was lower by 30% for G890 in the water-limited treatment compared to the control and elevated soil temperature, but it was not different between treatments for G41, M9, and B9. Soil treatments had significant effects

40 on total plant growth, where the water-limited treatment reduced it on average by 40% compared to the control and elevated soil temperature treatments (Fig. 4). Similarly, the water-limited treatment caused a decrease of about 34% for stem biomass, 50% for leaf biomass, and 60% for leaf area compared to the control. Interestingly, root biomass was affected by scion and was consistently higher for ‘Gala’ than for ‘Honeycrisp.’

Mineral Nutrient Concentration and Partitioning.

Scion genotype had a significant effect on nitrogen concentration in roots, stems, and leaves (Table

2). Nitrogen concentrations in roots and stems were higher in ‘Gala,’ but ‘Honeycrisp’ had higher concentrations in the leaves. Rootstock genotype did not significantly affect nitrogen concentrations in any plant organ. Regarding soil treatments, trees exposed to water-limited conditions showed higher nitrogen concentrations in root and stem but lower in leaf compared to the control. Nitrogen concentrations in leaves and roots were not significantly affected by elevated soil temperatures, unlike stems which had higher values compared to the control but lower than water-limited treatments.

Calcium was less variable than nitrogen, showing greater concentrations in the stems for ‘Gala’ than ‘Honeycrisp’ but no difference for roots or leaves. Calcium concentrations in roots were higher for G41 compared to the other three rootstock genotypes but were not different for stems and leaves among rootstocks. Like nitrogen, root calcium concentrations were greater when trees were exposed to water-limited conditions compared to the control and heat treatments. However, leaf calcium concentrations were lower for trees exposed to both water-limited and elevated soil temperature treatments (Table 2).

41 Root potassium concentrations were not different between ‘Gala’ and ‘Honeycrisp.’ However, potassium concentrations were greater for ‘Gala’ in the stem but greater in leaves of ‘Honeycrisp’.

Rootstock genotype had a significant effect on root potassium concentrations but not on leaves or stems. In roots, potassium concentrations were the lowest for G890 and G41 and the highest for

B9. Soil treatments only had a significant effect on leaf potassium concentrations, where like calcium, leaf potassium concentrations were lower when water was limited or when root temperatures were elevated (Table 2).

‘Honeycrisp’ had higher magnesium concentrations in roots, but ‘Gala’ had higher concentrations in stem and leaves. Among rootstocks, B9 had the lowest magnesium concentrations in roots, stems, and leaves, while G41 had the highest concentration in stems and leaves, and M9 had the highest magnesium concentrations in roots. Similar to nitrogen and calcium, magnesium concentrations in trees under water limitations were greater in the roots and lower in the leaves when comparing to control. Additionally, elevated soil temperatures also resulted in lower leaf magnesium concentrations (Table 2).

For nutrient content, ‘Gala’ accumulated more nitrogen, calcium, potassium, and magnesium in all plant organs, except for magnesium in roots and potassium and nitrogen in leaves. Rootstock

G890 accumulated more nitrogen, calcium, potassium, and magnesium in the roots compared to the other three rootstocks (Table 3). For leaves, the differences in nutrient content were smaller than those for roots. However, largely driven by differences in biomass accumulation, nitrogen, calcium, and magnesium in roots and leaves were lower for B9 compared to the other three rootstocks. With the exception of calcium, rootstock genotype did not affect the accumulation of nutrients into stem tissue (Table 3). Interestingly, soil treatments did not affect overall nutrient content for roots but had a significant effect on aboveground nutrient content. Water limitations

42 strongly reduced nutrient accumulation in both leaves and stems. The only exception was for nitrogen content in stems where soil treatment had no significant effect. Nitrogen, potassium, calcium, and magnesium contents of leaves under water-limited treatment were less than half of the contents of the control treatment. Elevated soil temperatures did not affect nitrogen accumulation in the leaves. However, calcium, potassium, and magnesium content were all lower compared to the control (Table 3).

Nutrient partitioning between plant organs reveals how trees distribute their nutrients under different environment scenarios (Fig. 5). Nitrogen partitioning between roots and leaves was affected by scion genotype. ‘Gala’ had 23% more nitrogen distributed to the roots whereas

‘Honeycrisp’ had 13% more nitrogen distributed to the leaves. As already seen in nutrient content,

G890 had the greatest partitioning of nutrients to the roots compared to the rest of the rootstock genotypes. Correspondingly, G890 accumulated the lowest proportions of nitrogen, calcium, potassium, and magnesium into the stem while B9 partitioned the most (Table 4). Rootstocks responded differently to soil treatments. Root calcium and magnesium content were greater for

G890 and G41 under elevated soil temperatures and water-limited treatment compared to the control, but it was not different for the other two rootstock genotypes tested. Stem calcium content was higher for B9 under water limitations while it was no different for the other three rootstocks

(Fig. 5). G890 with ‘Honeycrisp’ had higher root potassium content than with ‘Gala,’ but B9 with

‘Gala’ had higher root nitrogen content than with ‘Honeycrisp.’

Leaf Nutrient Ratios

Trees under elevated soil temperature showed an imbalance of mineral nutrients in their leaf tissue.

A significant interaction between rootstocks and treatments was obtained, where the K:Ca, N:Ca

43 and Mg:Ca ratios were greater for the rootstock G41 under elevated soil temperatures than the control and water-limited treatments while differences were not significant for G890, M9, and B9 rootstock genotypes (Fig. 6). Furthermore, the K:Ca ratio was greater for ‘Honeycrisp’ scion than for ‘Gala’ among all rootstocks, with ratios of 1.62 ± 0.04 and 1.42 ± 0.04, respectively.

When nitrogen, potassium, and magnesium were combined and expressed as a ratio against calcium, rootstock genotype, scion, and soil treatment all had a significant effect. Yet again, there was a significant interaction between rootstocks and treatments where the rootstock G41 had a higher ratio for elevated soil temperature than for water-limited and control treatments while there was no difference between treatments for G890, M9, and B9 (Fig. 6). Additionally, the (N + K +

Mg):Ca ratio was greater for ‘Honeycrisp’ than for ‘Gala’ with ratios of 3.2 ± 0.08 and 2.7 ± 0.08, respectively.

Discussion

Scion and Rootstock Genotypes, and Soil Environment All Shape Plant Growth and Biomass

Partitioning

Biomass accumulation was lower under water-limited conditions and this effect was mostly driven by decreases in aboveground growth rather than belowground growth (Table 1, Fig. 4). The results reported here agree with previous studies where water supply was reduced for fruit trees that led to reduced leaf area, and hence leaf biomass, while root growth was less affected which increased the root:shoot ratio (Ferguson and Watkins, 1989; Lang, 1990). The effect of dwarfing rootstocks on the scion under water limitations was previously reported with an elevated production of ABA in leaves which could reduce biomass partitioning to the aboveground tissues and increase root tolerance to abiotic stresses by increasing the fine root:coarse root ratio (Lang, 1990; Watkins et

44 al., 2004; Tworkoski, Fazio and Glenn, 2016). In this study, root biomass was affected by scion and was consistently higher for ‘Gala’ than for ‘Honeycrisp’. Also ‘Gala’ accumulated more above- and belowground biomass compared to ‘Honeycrisp’ when in combination with the G890.

Since ‘Gala’ is a more vigorous scion than ‘Honeycrisp’, it is possible that it also supplied more carbohydrates to the rootstock. These results correspond with the previous reporting that scion and rootstock can both affect tree vigor. Effects on plant growth and partitioning by scion and rootstock have been reported for trunk cross-sectional area (TCA), shoot growth, tree height and the number of branches among others, i.e., the rootstock affected the scion height, TCA and weight, while the scion affected the rootstock TCA and, to a lesser extent, the root biomass (Lauri, Maguylo and

Trottier, 2006; Costes and Garcia-Villanueva, 2007; Tworkoski and Fazio, 2015; Lordan et al.,

2017). Scion-rootstock interactions identified in a greenhouse experiment are limited because of no fruit production but these conditions allow for the evaluation of tree growth and development under a controlled environment.

Cultivar Differences in Nutrient Uptake and Partitioning are Independent of Biomass

Accumulation

In this study, ‘Gala’ accumulated more nutrients than ‘Honeycrisp’ (Table 3). In another study using ‘Granny Smith’, ‘Mondial Gala’, ‘Lutz Golden’, and ‘Skyline Supreme’ cultivars, leaf nutrient concentrations among cultivars differed during the growing season, where ‘Mondial Gala’ had the highest nutrient concentrations compared to the other cultivars used (Kucukyumuk and

Erdal, 2011). Here, ‘Gala’ had a dry weight consistently higher than ‘Honeycrisp’, although both scions had the lowest partitioning of nitrogen towards the stems, while for calcium, potassium, and magnesium the lowest sink was the roots (Table 4, Fig. 5). A similar study comparing partitioning

45 for ‘Golden Delicious’, ‘Coxs Orange’ and ‘Gloster’ cultivars showed that roots were the smallest sinks for nitrogen, phosphorus, and potassium while the fruit was the smallest sink for calcium in all cultivars. Moreover, ‘Golden Delicious’ had lower root dry weight and specific leaf weight when the nutrient supply was augmented, while there were no differences for the other two cultivars used (Buwalda and Lenz, 1992). Genotypic variation in translocating nutrients from the soil to various nutrient sinks exists (Fazio et al., 2013) and it is important to consider when developing new cultivars that are less susceptible to nutrient-related disorders and improved nutrient use efficiency.

Rootstock Affects Mineral Nutrient Uptake and Partitioning Independently of Dwarfing Effect

Here, no differences were found for the concentrations of potassium, calcium, nitrogen and magnesium in stems and leaves among rootstocks genotypes. However, the most vigorous rootstock genotypes (G890) had the lowest potassium concentration in root tissue (Table 2). These results are in agreement with previous reports of higher concentrations of calcium and potassium in the leaves for vigorous seedling rootstocks than when grafted on dwarf rootstocks such as M9

(Amiri, Fallahi and Safi-Songhorabad, 2014). Conversely, another study has shown that dwarf rootstock B9 had higher concentrations of calcium, zinc, and manganese in the leaves, but lower concentrations of potassium compared to more vigorous rootstocks such as Supporter4 (Fallahi,

2012). This inconsistency in the results suggests that the effect of dwarfing capacity itself does not affect the nutrient uptake, and other factors such as hydraulic conductivity, xylem anatomy, and the ability of the root system to uptake minerals may be critical (Amiri, Fallahi and Safi-

Songhorabad, 2014). In addition, the independence of dwarfing capacity on nutrient uptake has been previously reported (Fazio et al., 2013).

46 Nutrient content, which integrates biomass, was more closely related to dwarfing capacity. Our results showed a higher content of nitrogen, calcium, potassium, and magnesium on the roots of the G890 rootstock with both cultivars compared to less vigorous rootstocks such as G41, M9, and

B9 (Table 3). These results align with a previous study where a semi-dwarf rootstock (MM106), and a strong rootstock (MM111) had a significantly greater mineral content compared to more dwarf rootstocks (M9 and M26) and were related to the higher root dry weight (Kucukyumuk and

Erdal, 2011). A larger root system increases the soil area explored and increases the absorption capacity of mineral nutrients (Atkinson and Wilson, 1980). In this study, the partitioning of nutrients was similar for all the elements (Table 4), which indicates that the partitioning is not completely dependent on rootstock vigor and that improvements in nutrient uptake and partitioning could be made without compromising vigor control in new rootstocks.

Elevated Soil Temperatures Affect Nutrient Uptake and Partitioning Differently

In this study, elevated soil temperature affected nutrient balance and biomass allocation in apple trees. It was previously reported that root-zone temperatures affect shoot growth and development, including budbreak, bloom, shoot extension growth, photosynthesis, and stomatal conductance

(Greer et al., 2006). Moreover, surface soil temperature was found to be the biggest environmental factor, together with surface soil water content affecting soil respiration, which can be an indicator of root growth and root metabolism (Ceccon et al., 2011). Root temperatures also appear to influence carbon balance between below- and aboveground tissues (Gur, Mizrahi and Samish,

1976). Here, the aboveground biomass for both Geneva rootstocks G890 and G41 was higher when under elevated soil temperatures but was lower for B9 and M9 compared to control (Fig. 4).

Additionally, elevated soil temperature conditions increased the N:Ca and K:Ca ratios in leaves of

47 G41 (Fig. 6). Elevated soil temperatures have been reported to reduce potassium, sodium, calcium, magnesium, and zinc content when soil temperatures were above 25 °C (Gur, Hepner and

Shulman, 1979). Calcium is mainly absorbed by root tips and also by the sites of formation of new branches (Fallahi, 2012; Amiri, Fallahi and Safi-Songhorabad, 2014). Since elevated root temperatures can reduce root growth, calcium absorption capacity may also be lower as a result.

Water Limitations Can Affect Nutrient Uptake and Allocation to Aboveground Organs

Nutrient concentrations under water limitations were higher in structural organs like roots and stems when compared to active growing tissue such as leaves. Under water limitations, the concentration of nitrogen, calcium, and magnesium was lower in root tissues, while in stem tissue only nitrogen concentration was lower, and the concentration of all nutrients was lower in leaves tissues compared to control (Table 2). Similar results were reported on non-irrigated ‘Cox’ and

‘Queen Cox’ apple trees leaves that had lower concentration of nitrogen, magnesium, and manganese than irrigated trees (Greer et al., 2006; Ceccon et al., 2011; Lordan et al., 2017). Under low soil water content, the rate of diffusion of nutrients from the soil matrix to the absorbing root surface is lowered (Atkinson et al., 1997; Jobbágy et al., 2001). Most of the elemental budget of a plant comes from the root system through mass flow carried by the water in the soil medium, driven by a gradient of osmotic potential between the soil solution and the xylem sap (Jackson,

2003a). Additionally, slow root growth under water limitations may also reduce the soil volume occupied by roots, and the nutrient transport from the roots to the shoots may also decrease due to a reduction in transpiration rates (Slowik et al., 1979; Atkinson et al., 1997, 1998; Jackson, 2003b), e.g., in fruiting trees, the overall distribution of calcium between vegetative growth and developing fruit can be affected by changes in transpiration (White and Broadley, 2003; de Freitas et al., 2013;

48 Montanaro et al., 2015; Kalcsits, et al., 2017). Since leaf water potential was lower under water limitations (Fig. 3), stomatal closure results that can reduce the transpiration flow of nutrients via xylem to the aboveground tissues.

Broad Implications on Nutrient Balance and Fruit Disorders under Changing Soil Environments

Even though leaf ratios are difficult to compare to fruit ratios, which have been more extensively described (Casierra-posada and Lizarazo, 2004), physiological disorders such as bitter pit are linked more strongly to the K:Ca, N:Ca, Mg:Ca, and (N + K + Mg):Ca ratios than to calcium content itself (de Freitas, do Amarante and Mitcham, 2015). Our study report higher K:Ca, N:Ca and (N + K + Mg):Ca ratios for ‘Honeycrisp’ apple than ‘Gala,’ which is in concordance with the already known ‘Honeycrisp’ susceptibility to bitter pit (Rosenberger et al., 2004). Moreover, rootstocks G41 and M9 had higher leaf K:Ca and Mg:Ca ratios than B9 and G890 rootstocks showing the differences in nutrient uptake capacity among rootstocks previously reported

(Atkinson et al., 1999; de Freitas et al., 2013; Fazio et al., 2013; Amiri, Fallahi and Safi-

Songhorabad, 2014). Furthermore, elevated soil temperature conditions increased the N:Ca and

K:Ca ratios in the leaves of G41 (Fig. 6), due to lower calcium concentration (Table 2). This may be a function of calcium immobility in the phloem that limits its redistribution between plant organs (Kucukyumuk and Erdal, 2011), since the concentration of calcium was not reduced in root and stem tissues. It was previously reported that optimal soil temperatures for M9, leading to increased potassium accumulation occurs at 25 °C (Gur, Hepner and Shulman, 1979), and similar to the findings reported here, elevated soil temperatures increased potassium uptake from the soil which contributes to an imbalance in the nutrient ratios in the leaves.

49 Conclusions

Water limitations affected biomass partitioning of young apple trees, reducing stem and leaf biomass and, to a lesser extent, root biomass. Through strong reductions in aboveground growth, water limitations decreased mineral nutrient content in both stems and leaves, whereas elevated soil temperatures reduced calcium partitioning to leaves. Most importantly, G890, the rootstock with the most vigor, was the most responsive to water limitations, whereas more dwarfing rootstocks were affected to a lesser degree. Since this study was conducted on potted trees using growing media, field validation is still required to strengthen these results. Nevertheless, it was demonstrated that both rootstock and scion differences contribute to nutrient uptake and partitioning under different soil environments. ‘Gala’ apple trees produced more biomass than

‘Honeycrisp’ trees, and ‘Gala’ trees accumulated more nitrogen in roots whereas ‘Honeycrisp’ trees accumulated more nitrogen in leaves showing the scion effect on the nutrient’s uptake and distribution. Furthermore, rootstock genotypes also contributed significantly although vigor contribution to the nutrient uptake capacity is still unclear. These interactions represent a critical system for understanding how scions and rootstocks interact and, more practically, also provides information on how nutrient management decisions may change under poor soil conditions or water management and depending on rootstock-cultivar selection.

50 References

Amiri, M.E., Fallahi, E., Safi-Songhorabad, M., 2014a. Influence of rootstock on mineral uptake and scion growth of 'Golden delicious' and 'Royal gala' apples. J. Plant Nutr. 37, 16–29.

Amiri, M.E., Fallahi, E., Safi-Songhorabad, M., 2014b. Influence of Rootstock on Mineral Uptake and Scion Growth of ‘Golden Delicious’ and ‘Royal Gala’ Apples. J. Plant Nutr. 37, 16–29.

Atkinson, C.J., Policarpo, M., Webster, A.D., Kuden, A.M., 1999. Drought tolerance of apple rootstocks: Production and partitioning of dry matter. Plant Soil 206, 223–235.

Atkinson, C.J., Taylor, L., Taylor, J.M., Lucas, A.S., 1998. Temperature and irrigation effects on the cropping, development and quality of 'Cox’s Orange Pippin' and 'Queen Cox' apples. Sci. Hortic. (Amsterdam). 75, 59–81.

Atkinson, C.J., Webster, A.D., Vaughan, S., Lucas, A.S., 1997. Effects of root restriction on the physiology of apple tree growth. Acta Hort 451, 587–595.

Atkinson, D., Wilson, S.A., 1980. The growth and distribution of fruit tree roots: Some consequences for nutrient uptake. In: Mineral Nutrition of Fruit Trees: Studies in the Agricultural and Food Sciences. pp. 137–150.

Bassirirad, H., 2000. Kinetics of nutrient uptake by roots : responses to global change . New Phytol Kinetics of nutrient uptake by roots : responses to global change. New Phytol. 147, 155–169.

Buwalda, J.G., Lenz, F., 1992. Effects of cropping , nutrition and water supply on accumulation and distribution of biomass and nutrients for apple trees on ’M9’ root systems. Physiol. Plant. 21–28.

Casierra-posada, F., Lizarazo, L.M., 2004. Estado nutricional de árboles de manzano 'Anna' durante la estación de crecimiento en los altiplanos Colombianos: II. Relaciones e interacciones entre nutrientes. Agron. Colomb. 22, 160–169.

Ceccon, C., Panzacchi, P., Scandellari, F., Prandi, L., Ventura, M., Russo, B., Millard, P., Tagliavini, M., 2011. Spatial and temporal effects of soil temperature and moisture and the relation to fine root density on root and soil respiration in a mature apple orchard. Plant Soil 342, 195–206.

Costes, E., Garcia-Villanueva, E., 2007. Clarifying the Effects of Dwarfing Rootstock on Vegetative and Reproductive Growth during Tree Development: A Study on Apple Trees. Ann. Bot. 100, 347–357. de Freitas, S.T., Amarante, C.V.T. d., Dandekar, A.M., Mitcham, E.J., 2013. Shading affects flesh calcium uptake and concentration, bitter pit incidence and other fruit traits in 'Greensleeves' apple. Sci. Hortic. (Amsterdam). 161, 266–272.

51 de Freitas, S.T., Amarante, C.V.T. d., Labavitch, J.M., Mitcham, E.J., 2010. Cellular approach to understand bitter pit development in apple fruit. Postharvest Biol. Technol. 57, 6–13. de Freitas, S.T., do Amarante, C.V.T., Mitcham, E.J., 2015. Mechanisms regulating apple cultivar susceptibility to bitter pit. Sci. Hortic. (Amsterdam). 186, 54–60.

Fallahi, E., 2012. Influence of rootstock and irrigation methods on water use, mineral nutrition, growth, fruit yield, and quality in 'Gala' apple. Horttechnology 22, 731–737.

Fazio, G., Kviklys, D., Grusak, M.A., Robinson, T., 2013. Phenotypic Diversity and QTL Mapping of Absorption and Translocation of Nutrients by Apple Rootstocks. Asp. Appl. Biol. 119, 37– 50.

Ferguson, I.B., Watkins, C.B., 1989. Bitter pit in apple fruit. Hortic. Rev. (Am. Soc. Hortic. Sci). 289–355.

Greer, D.H., Wünsche, J.N., Norling, C.L., Wiggins, H.N., 2006. Root-zone temperatures affect phenology of bud break, flower cluster development, shoot extension growth and gas exchange of 'Braeburn' (Malus domestica) apple trees. Tree Physiol. 26, 105–111.

Gur, A., Hepner, J., Shulman, Y., 1979. The .influence of root temperature on apple trees. IV. The effect on the mineral nutrition of the tree. J. Hortic. Sci. 54, 313–321.

Gur, A., Mizrahi, Y., Samish, R.M., 1976. The influence of root temperature on apple trees. II. Clonal differences in susceptibility to damage caused by supraoptimal root temperature. J. Hortic. Sci. 51, 195–202.

Jackson, John E., 2003. Apple and pear root systems: Induction, development, structure and function. In: Biology of Apples and Pears. pp. 84–125.

Jackson, J. E., 2003a. Eating quality and its retention. In: The Biology of Apples and Pears. pp. 341–383.

Jackson, J. E., 2003b. Biology of apples and pears. Cambridge University Press, Cambridge, NY.

Jobbágy, E.G., Jackson, R.B., Jobbagy, E.G., Jackson, R.B., 2001. The Distribution of Soil Nutrients with Depth : Global Patterns and the Imprint of Plants Linked references are available on JSTOR for this article: The distribution of soil nutrients with depth: Global

52 patterns and the imprint of plants. Biogeochemistry 53, 51–77.

Kalcsits, L., Musacchi, S., Layne, D.R., Schmidt, T., Mupambi, G., Serra, S., Mendoza, M., Asteggiano, L., Jarolmasjed, S., Sankaran, S., Khot, L.R., Espinoza, C.Z., 2017a. Above and below-ground environmental changes associated with the use of photoselective protective netting to reduce sunburn in apple. Agric. For. Meteorol. 237–238, 9–17.

Kalcsits, L., van der Heijden, G., Reid, M., Mullin, K., 2017b. Calcium Absorption during Fruit Development in ‘Honeycrisp’ Apple Measured Using 44 Ca as a Stable Isotope Tracer. HortScience 52, 1804–1809.

Kalcsits, L.A., 2016. Non-destructive measurement of calcium and potassium in apple and pear using handheld X-ray fluorescence. Front. Plant Sci. 7, 442.

Kucukyumuk, Z., Erdal, I., 2011. Rootstock and cultivar effect on mineral nutrition, seasonal nutrient variation and correlations among leaf, flower and fruit nutrient concentrations in apple trees. Bulg. J. Agric. Sci. 17, 633–641.

Lang, A., 1990. Xylem , Phloem and Transpiration Flows in Developing Apple Fruits. J. Exp. Bot. 41, 645–651.

Lauri, P., Maguylo, K., Trottier, C., 2006. Architecture and Size Relations: An Essay on the Apple ( Malus x domestica , Rosaceae ) Tree. Am. J. Bot. 93, 357–368.

Liu, B.H., Cheng, L., Liang, D., Zou, Y.J., Ma, F.W., 2012. Growth, gas exchange, water-use efficiency, and carbon isotope composition of 'Gale Gala' apple trees grafted onto 9 wild Chinese rootstocks in response to drought stress. Photosynthetica 50, 401–410.

Lordan, J., Fazio, G., Francescatto, P., Robinson, T., 2017. Effects of apple (Malus × domestica) rootstocks on scion performance and hormone concentration. Sci. Hortic. (Amsterdam). 225, 96–105.

Montanaro, G., Dichio, B., Lang, A., Mininni, A.N., Xiloyannis, C., 2015. Fruit calcium accumulation coupled and uncoupled from its transpiration in kiwifruit. J. Plant Physiol. 181, 67–74.

Montanaro, G., Dichio, B., Xiloyannis, C., 2010. Significance of fruit transpiration on calcium nutrition in developing apricot fruit. J. Plant Nutr. Soil Sci. 173, 618–622.

Montanaro, G., Dichio, B., Xiloyannis, C., Lang, A., 2012. Fruit transpiration in kiwifruit: Environmental drivers and predictive model. AoB Plants 2012, 1–9.

Pregitzer, K.S., King, J.S., Burton, A.J., Brown, S.E., 2000. Responses of tree fine roots to temperature. New Phytol. 147, 105–115.

Public utility district, 2018. Water quality 2018 annual report. Wenatchee, Washington.

Rosenberger, D.A., Schupp, J.R., Hoying, S.A., Cheng, L., Watkins, C.B., 2004. Controlling bitter pit in ‘Honeycrisp’ apples. Horttechnology 14, 342–349.

Shackel, K.A., Lampinen, B., Southwick, S., Olson, W., Sibbett, S., Krueger, W., Yeager, J., 2000. Deficit Irrigation in Prunes: Maintaining Productivity with Less Water. HortScience 35, 1063–1066.

Slowik, K., Labanauskas, C.K.K., Stolzy, L.H.H., Zentmyer, G. a. A., 1979. Influence of rootstocks, soil oxygen, and soil moisture on the uptake and translocation of nutrients in young avocado. J. Am. Soc. Hortic. Sci. 104, 172–175.

Sofo, A., Palese, A.M., Casacchia, T., Dichio, B., 2012. Sustainable fruit production in mediterranean orchards subjected to drought stress. In: Ahmad, P., Prasad, M.N.V. (Eds.), Abiotic Stress Responses in Plants: Metabolism, Productivity and Sustainability. Springer, New York, pp. 105–129.

Tworkoski, T., Fazio, G., 2015. Effects of Size-Controlling Apple Rootstocks on Growth , Abscisic Acid , and Hydraulic Conductivity of Scion of Different Vigor. Int. J. Fruit Sci. 369– 381.

Tworkoski, T., Fazio, G., Glenn, D.M., 2016. Apple rootstock resistance to drought. Sci. Hortic. (Amsterdam). 204, 70–78.

Vano, J.A., Scott, M.J., Voisin, N., Stöckle, C.O., Hamlet, A.F., Mickelson, K.E.B., Mcguire, M., Lettenmaier, D.P., 2010. Climate change impacts on water management and irrigated agriculture in the Yakima River Basin, Washington, USA. Clim. Change 102, 287–317.

Wertheim, S.J., Webster, A., 2003. Apple Rootstocks. In: Ferre, D.C., Warrington, I.J. (Eds.), Apples. Botany, Production and Use. CABI Publishing, Cambridge, MA.

White, P.J., 2012. Long-distance Transport in the Xylem and Phloem. In: Marschner, P. (Ed.), Mineral Nutrition of Highr Plants. Elsevier Ltd., Invergowrie, Dundee, UK, pp. 49–70.

White, P.J., Broadley, M.R., 2003. Calcium in plants. Ann. Bot. 92, 487–511.

Wood, A.J., 2005. Eco-physiological Adaptations to Limited Water Enviornments. Plant Abiotic Stress 1–13.

55 Table 2. 1. Root, stem and leaf biomass (grams dry weight), total leaf area (cm2) and root:shoot biomass ratio (±SE; n=3) for ‘Gala’ and ‘Honeycrisp’ apple cultivars in combination with four rootstocks: Bud-9 (B9), G41, G890, and M9-T337 (M9) under water limitations or elevated soil temperatures compared to the control.

Dry weight (g) Root Stem Leaf Leaf Area Scion Rootstock Root:Shoot (g) (g) (g) (cm2) B9 4.1 ±0.1 32.2 ±2.1 15.8 ±0.7 1,758 ±114 0.09 ±0.003 G41 3.0 ±1.2 20.8 ±5.5 17.2 ±4.1 2,186 ±754 0.08 ±0.02

G890 19.5 ±4.7 25.0 ±3.1 19.9 ±3.5 2,610 ±553 0.46 ±0.13

Honeycrisp

' M9 5.6 ±0.9 33.5 ±3.5 28.2 ±2.9 3,565 ±395 0.09 ±0.01 trol

B9 7.3 ±0.8 33.7 ±3.1 20.0 ±3.9 2,182 ±331 0.14 ±0.02 Con G41 9.1 ±0.9 35.0 ±4.9 24.4 ±3.0 3,150 ±407 0.15 ±0.01

Gala G890 24.6 ±1.6 40.6 ±2.3 31.6 ±2.1 3,872 ±279 0.34 ±0.02 M9 8.6 ±0.3 34.2 ±8.2 27.2 ±6.3 3,435 ±706 0.16 ±0.04 B9 2.3 ±1.0 19.3 ±2.7 5.2 ±2.1 496 ±231 0.09 ±0.02

G41 5.2 ±1.3 16.3 ±0.7 8.7 ±1.3 872 ±192 0.21 ±0.04 G890 15.9 ±3.1 15.2 ±1.5 7.6 ±1.4 770 ±166 0.76 ±0.25

Honeycrisp M9 6.6 ±0.9 27.0 ±1.5 15.9 ±0.6 1,629 ±131 0.15 ±0.02 Limited - B9 5.4 ±0.9 30.4 ±1.7 12.1 ±2.8 1,067 ±308 0.13 ±0.03

G41 6.0 ±0.2 16.6 ±3.4 9.3 ±1.6 935 ±232 0.24 ±0.03 Water

Gala G890 17.0 ±4.9 26.1 ±1.9 17.8 ±3.1 1,741 ±261 0.39 ±0.10 M9 5.2 ±2.2 17.6 ±4.1 10.1 ±3.4 1,039 ±253 0.18 ±0.03 B9 1.8 ±0.4 22.3 ±0.3 10.6 ±2.4 1,237 ±262 0.05 ±0.01 G41 3.6 ±0.1 24.7 ±5.1 17.9 ±4.4 2,203 ±550 0.08 ±0.004

G890 24.1 ±5.8 28.2 ±13.0 24.1 ±8.4 1,964 ±1072 0.51 ±0.09

Honeycrisp M9 5.0 ±1.2 30.6 ±8.4 23.2 ±7.0 2,778 ±944 0.10 ±0.01

Heat B9 7.3 ±1.6 37.2 ±1.4 24.5 ±1.4 2,577 ±230 0.12 ±0.02 G41 9.7 ±1.1 39.0 ±1.6 32.7 ±2.2 2,841 ±772 0.13 ±0.01

Gala G890 28.8 ±4.2 48.3 ±14.2 32.6 ±9.4 3,138 ±943 0.43 ±0.12 M9 3.5 ±0.8 20.7 ±2.6 14.9 ±2.5 1,811 ±203 0.10 ±0.01 Treatment 0.2315 0.0112 <0.0001 0.0008 0.1469 Scion 0.0030 0.0028 0.0049 0.0347 <0.0001 Rootstock <0.0001 0.3824 0.0302 0.0377 0.6434 Treatment*Rootstock 0.0354 0.3853 0.3457 0.7042 0.4294 Scion*Rootstock 0.3621 0.0087 0.0155 0.0507 0.0112

56 Table 2. 2. Nitrogen, calcium, potassium, and magnesium concentration (mg/g) for roots, stems and leaves of ‘Gala’ and ‘Honeycrisp’

scion genotypes in combination with Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotype grown in untreated control,

water-limited, or elevated soil temperature treatments. Different letters denote significant differences among columns determined using

a Tukey’s mean separation test (alpha = 0.05). ***, ** and * indicate significance in differences among means at p-values <0.0001,

<0.01 and <0.05, respectively.

Scion Rootstock Treatment

Water- ‘Gala’ ‘Honeycrisp’ B9 G41 G890 M9 Control Limited Heat Nitrogen Roots 36.9 a 28.3 b *** 31.5 a 35.1 a 33.5 a 30.2 a * 29.1 b 40.6 a 28.0 b *** Stems 5.6 a 5.0 b ** 5.3 a 5.2 a 5.0 a 5.5 a 4.3 c 6.6 a 4.9 b ***

57 Leaves 22.8 b 25.7 a ** 23.0 a 24.6 a 24.5 a 24.9 a 25.1 a 22.8 b 24.9 a *

Calcium Roots 15.9 a 15.5 a 14.7 b 19.0 a 14.7 b 14.5 b ** 14.9 b 17.6 a 14.7 b ** Stems 12.0 a 9.2 b *** 11.3 a 9.9 a 10.7 a 10.4 a 10.6 a 11.0 a 10.2 a Leaves 20.8 a 19.5 a 20.6 a 19.2 a 21.1 a 19.8 a 22.6 a 19.6 b 18.4 b ***

Potassium Roots 11.3 a 12.6 a 15.6 a 10.6 bc 8.9 c 12.8 ab *** 12.0 a 12.3 a 11.6 a Stems 8.3 a 7.5 b * 8.1 a 7.8 a 8.0 a 7.8 a 8.2 a 7.4 a 8.1 a Leaves 29.0 b 31.1 a * 28.7 a 31.0 a 39.9 a 30.6 a 33.1 a 27.2 b 29.8 b ***

Magnesium Roots 2.8 b 3.1 a * 2.6 b 3.0 ab 2.9 ab 3.4 a ** 2.7 b 3.3 a 2.9 b ** Stems 1.3 a 0.9 b *** 0.9 b 1.3 a 1.2 ab 1.1 ab * 1.2 a 1.0 a 1.1 a Leaves 4.2 a 3.8 b ** 3.4 b 4.4 a 4.0 a 4.1 a *** 4.4 a 3.6 b 3.9 b ***

Table 2. 3. Nitrogen, calcium, potassium, and magnesium content (mg) for roots, stems and leaves of ‘Gala’ and ‘Honeycrisp’ scion

genotypes in combination with Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotype grown in untreated control, water-

limited, or elevated soil temperature treatments. Different letters denote significant differences among columns determined using a

Tukey’s mean separation test (alpha = 0.05). ***, ** and * indicate significance in differences among means at p-values <0.0001, <0.01

and <0.05, respectively.

Scion Rootstock Treatment Water- ‘Gala’ ‘Honeycrisp’ B9 G41 G890 M9 Control Limited Heat Nitrogen Roots 393 a 235 b *** 156 b 219 b 701 a 180 b *** 309 a 344 a 290 a Stems 168 a 120 b *** 155 a 128 a 149 a 143 a 137 a 140 a 155 a 58 Leaves 492 a 427 a 339 b 464 ab 525 a 511 a * 573 a 253 b 553 a ***

Calcium Roots 173 a 119 b ** 67 b 117 b 316 a 84 b *** 147 a 132 a 159 a Stems 382 a 221 b *** 335 a 255 b 338 a 276 ab * 343 a 235 b 326 a ** Leaves 445 a 318 b ** 316 b 343 ab 461 a 407 ab * 521 a 210 c 414 b ***

Potassium Roots 111 a 82 b ** 72 b 62 b 183 a 69 b *** 104 a 91 a 95 a Stems 273 a 187 b ** 240 a 206 a 260 a 215 a 267 a 159 b 265 a ** Leaves 622 a 519 a * 425 b 576 ab 649 a 632 a * 756 a 290 b 666 a ***

Magnesium Roots 30.2 a 25.3 a 12.2 b 17.9 b 61.8 a 19.1 b *** 26.1 a 26.8 a 30.3 a Stems 43.5 a 23.0 b *** 28.3 a 35.0 a 40.6 a 29.1 a 39.4 a 21.1 b 39.3 a ** Leaves 91.1 a 63.0 b ** 52.7 b 81.8 ab 87.6 a 86.1 a ** 104.2 a 39.2 b 87.8 a ***

Table 2. 4. Nitrogen, calcium, potassium and magnesium partitioning among roots, stems and leaves of ‘Gala’ and ‘Honeycrisp’ apple

scion genotypes in combination with Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotype under untreated control, water-

limited, or elevated soil temperature treatments. Different letters denote significant differences among columns determined using a

Tukey’s mean separation test (alpha = 0.05). ***, ** and * indicate significance in differences among means at p-values <0.0001, <0.01

and <0.05, respectively.

Scion Rootstock Treatment Alloc/Nut Water- (mg) ‘Gala’ ‘Honeycrisp’ B9 G41 G890 M9 Control Limited Heat

Roots Nitrogen 0.35 a 0.27 b *** 0.22 b 0.28 b 0.52 a 0.22 b *** 0.27 b 0.41 a 0.25 b ** 59 Calcium 0.17 a 0.17 a 0.09 c 0.17 b 0.31 a 0.12 c *** 0.14 a 0.22 a 0.15 a Potassium 0.19 a 0.21 a 0.13 b 0.15 b 0.36 a 0.16 b *** 0.15 b 0.28 a 0.17 b ** Magnesium 0.12 a 0.11 a 0.09 b 0.09 b 0.19 a 0.08 b *** 0.09 b 0.16 a 0.09 b **

Stems Nitrogen 0.18 a 0.18 a 0.27 a 0.16 b 0.11 c 0.19 b *** 0.14 b 0.23 a 0.17 b *** Calcium 0.39 a 0.37 a 0.50 a 0.36 bc 0.29 c 0.38 b *** 0.34 b 0.42 a 0.35 ab ** Potassium 0.26 a 0.23 a 0.33 a 0.25 b 0.19 b 0.22 b *** 0.23 a 0.27 a 0.25 a Magnesium 0.27 a 0.26 a 0.35 a 0.25 b 0.23 b 0.25 b *** 0.23 b 0.31 a 0.26 ab **

Leaves Nitrogen 0.47 b 0.54 a *** 0.51 b 0.55 ab 0.37 c 0.59 a *** 0.58 a 0.36 b 0.58 a *** Calcium 0.43 a 0.46 a 0.41 b 0.47 a 0.40 b 0.51 a *** 0.52 a 035 c 0.46 b *** Potassium 0.55 a 0.55 a 0.54 b 0.59 ab 0.45 c 0.62 a *** 0.62 a 0.45 b 0.58 a *** Magnesium 0.61 a 0.62 a 0.55 b 0.66 a 0.58 b 0.66 a *** 0.67 a 0.53 b 0.64 a ***

Control Water-limited 0.5 Heat

0.4

) 3

/m 0.3 3

0.2 Soilmoisture (m

0.1

0.0

Jul 1 Jul 8 Jul 15 Jul 22 Jul 29 Aug 5 Aug 12 Aug 19 Aug 26 Date

Figure 2. 1. Mean soil volumetric water content during the growing season for control, water- limited, and elevated soil temperature treatments.

60 Control Heat 29

C) ° 27

Average temperature ( temperature Average 23

7-Aug 24-Jul 31-Jul 14-Aug 21-Aug 28-Aug Date

Figure 2. 2. Daily average root-zone temperature recorded through the growing season for elevated soil temperature and control treatments.

Figure 2. 3. Mean mid-day stem water potential (MPa) for ‘Gala’ and ‘Honeycrisp’ apple cultivars grafted on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks grown under water-limited

(WL) or elevated soil temperature treatments compared to the control. Error bars denote standard error (n=3). Letters denote significant differences among means determined using a Tukey’s mean separation test (alpha = 0.05).

Figure 2. 4. Mean tree biomass (grams of dry weight) distribution between roots, stems and leaves for (A) ‘Gala’ and (B) ‘Honeycrisp’ apple cultivars grafted on Bud-9 (B9), G41, G890, and M9-

T337 (M9) rootstocks grown under water-limited or elevated soil temperature treatments compared to the control. Error bars denote standard error for total tree biomass (n=3). Letters denote significant differences among means determined using a Tukey’s mean separation test (α

= 0.05).

Figure 2. 5. Total tree nitrogen, calcium, potassium and magnesium partitioning (%) between roots, stems and leaves for ‘Gala’ and ‘Honeycrisp’ apple scion genotypes grafted on Bud-9 (B9),

G41, G890, and M9-T337 (M9) rootstocks grown under water-limited or elevated soil temperature treatments compared to untreated control.

64 65

Figure 2. 6. Mineral nutrient ratios (K:Ca, N:Ca, Mg:Ca and N+K+Mg:Ca) for leaves of apple rootstocks Bud-9 (B9), G41, G890, and

M9-T337 (M9) grown under water-limited or elevated soil temperature treatments compared to untreated control. Error bars denote

standard error (n=3). Letters denote significant differences among means determined using a Tukey’s mean separation test (alpha =

0.05).

CHAPTER THREE: ROOTSTOCK AFFECTS NUTRIENT UPTAKE, DISTRIBUTION,

AND FRUIT QUALITY OF ‘HONEYCRISP’ APPLE DURING ORCHARD

ESTABLISHMENT

Abstract

‘Honeycrisp’ apple is a high value apple cultivar because of its consumer popularity but is challenging to produce in the Pacific Northwest due to its high susceptibility to bitter pit. Bitter pit is related to localized calcium deficiencies and is associated with nutrient imbalances more than the elemental content or concentrations. Rootstock genotypes can affect nutrient acquisition, distribution, and fruit yields. However, the response of these traits among different rootstock genotypes to abiotic stress under semi-arid conditions is relatively unknown. The objective was to evaluate the influence of different rootstocks genotypes on nutrient uptake and partitioning for

‘Honeycrisp’ apple cultivar and their response to water limited conditions. Moreover, the differences among rootstock genotypes on early production fruit quality was assessed.

‘Honeycrisp’ apple trees grafted on four different rootstocks, G41, G890, M9, and B9 were planted at a high density and trained on a slender spindle system. Irrigation treatments consisted of a water- limited treatment maintaining soil water content near 50% FC and a well-watered control with irrigation maintaining soil water content near 100% FC. G890, the most vigorous rootstock, had lower nitrogen and higher potassium concentration in leaves, while B9, the smallest rootstock, had lower potassium and higher nitrogen concentrations. Rootstock genotype did not affect calcium uptake. Interestingly, water-limited conditions increased the nutrient concentration in root and stems but not in leaves. Water-limited trees partitioned more nitrogen and calcium to the roots, while well-water control trees partitioned more nutrients to the stems. Fruit size was larger for

G890 and smallest for B9. Both G41 and G890 had higher bitter pit incidence which was associated

66 with higher potassium concentration in leaves and fruit. These results indicate possible contributions of rootstock vigor to nutrient imbalances in leaves and fruit and more work is needed with a greater number of rootstock genotypes to determine whether rootstock vigor is directly related to the development of physiological disorders.

Keywords: Malus × domestica, carbon isotope composition, leaf gas exchange, vegetative growth, photochemical quenching.

67 Introduction

Malus × domestica Borkh. Cv. ‘Honeycrisp’ apple is a high value apple cultivar because of its consumer popularity. This cultivar was bred by the University of Minnesota apple-breeding program and released in 1990. ‘Honeycrisp’ was first planted in Washington State in 2000 and has expanded from 120 hectares to 9150 hectares in 2017 (Gallardo et al., 2015; Serban, 2018). Despite consumer popularity, ‘Honeycrisp’ is a challenge for growers in the semi-arid conditions of the

Pacific Northwest due to its high susceptibility to physiological disorders such as bitter pit, which normally cause losses of 20% but can be up to 75% in extreme cases (Cheng and Sazo, 2018).

Physiological disorders can be a consequence of the different environmental conditions between where it is being grown at Washington State, a semi-arid climate, from where it was bred in

Minnesota, a cool, temperate climate (Serra et al., 2016). Despite these challenges, Washington

State growers continue planting ‘Honeycrisp’ due to the high economic value of this crop that is almost three times higher than most other cultivars (Cheng and Sazo, 2018). However, losses to bitter pit still continue to limit the long-term sustainability of this cultivar. Physiological disorders such as bitter pit are associated with localized calcium deficiencies (Casierra-Posada et al., 2003;

Rosenberger et al., 2004; de Freitas, do Amarante and Mitcham, 2015). Since calcium is taken up through the plant transpiration stream, elevated temperatures may change the transpiration balance between leaves and fruit and change allocation of calcium to developing fruit (de Freitas, do

Amarante and Mitcham, 2015; Bisbis, Gruda and Blanke, 2019). Rootstocks have also been reported to strongly influence on nutrient acquisition by the soil and distribution in the scion. Fazio et al. (2013) reported a QTL locus for potassium and magnesium that were found to be co-located in the same chromosome in apples, and in the same region than one of the dwarfing loci. This

68 information is being used to improve nutrient acquisition for new apple rootstock selections (Fazio et al., 2019a; Valverdi, Cheng and Kalcsits, 2019).

In horticultural crops, heat and drought can negatively affect plant growth, yield, and quality

(Atkinson et al., 1998; Serra et al., 2016; Kalcsits, et al., 2017; Valverdi, Cheng and Kalcsits,

2019). Climate change forecasts have been updated to account for current emission trajectories and temperatures are forecast to be greater than initially anticipated (Zandalinas et al., 2018).

Extreme weather associated with these changes include extended heat events, drought, and frost that can be challenging for horticultural crops production (Bisbis, Gruda and Blanke, 2019). In many horticultural crops, the impact of these events on productivity has been understudied. This includes how these stress events contribute to overall nutrient acquisition and distribution in these crops. For studies focused on abiotic stress on trees in the field, other environmental conditions may affect tree responses and need to be accounted for in such studies. When conducting field research, the interaction of several types of abiotic stresses such as heat, drought, and light intensity should be taken into consideration since they often occur simultaneously in natural conditions

(Grant, 2012; Kalcsits, et al., 2017; Zandalinas et al., 2018). In the future, the most reliable solution to overcome the impacts of climate change is to develop cultivars and rootstocks that are more tolerant to abiotic stress.

Physiological disorders in the fruit like bitter pit have been reported to be associated with nutrient imbalances more than the elemental content or concentration (Casierra-posada and Lizarazo, 2004; de Freitas, do Amarante and Mitcham, 2015). Rootstocks can influence the scion nutrient content

(Ferguson and Watkins, 1989; Kucukyumuk and Erdal, 2011; Fazio et al., 2013, 2019a; Valverdi,

Cheng and Kalcsits, 2019). Furthermore, environmental conditions influence the rootstock effect on scion nutrient uptake capacity (Serra et al., 2016; Kalcsits, et al., 2017). To mitigate these

69 physiological disorders, several studies with different rootstocks genotypes have been conducted at a local and national level (Tworkoski and Fazio, 2011; Neilsen and Havipson, 2014; Lordan et al., 2017; Reig et al., 2018; Valverdi, Cheng and Kalcsits, 2019). Several GENEVA® series rootstocks have been released with an emphasis on productivity, yield efficiency, ease of nursery propagation, fire blight resistance, tolerance to extreme temperatures, resistance to the soil pathogens of the sub-temperate regions of the US, and tolerance to apple replant disorder (Auvil,

2016). GENEVA® rootstocks have demonstrated similar productivity and quality compared to the current commercial standards, M.9 and M.26, while introducing increased fire blight and replant disease tolerance for many rootstock trials in North America and other locations worldwide (Autio,

2001; Fallahi et al., 2002; Marini et al., 2012, 2014; Fazio, Robinson and Aldwinckle, 2014;

Neilsen and Havipson, 2014; Tworkoski and Fazio, 2016; Lordan et al., 2017; Marini and Fazio,

2018; Fazio et al., 2019b). However, the tolerance of these rootstocks to changes in water supply or how the rootstocks change overall nutrient partitioning and how it relates to productivity, fruit quality, and disorder incidence has not been addressed.

A previous study of this research project has already tested the influence of rootstock genotypes in the nutrient uptake and distribution on ‘Honeycrisp’ under controlled environment conditions

(Valverdi, Cheng and Kalcsits, 2019). Nevertheless, under field conditions, trees are exposed to conditions that can limit their performance such as poor soils, low soil water content, shallow and rocky soils, low air humidity, high light intensity, elevated air temperature, among others (Suzuki et al., 2014). Here, the objective of this research was to investigate how different rootstocks genotypes affect nutrient uptake and partitioning for ‘Honeycrisp’ apple cultivar grown in field conditions in a semi-arid climate and how they response to water limited conditions. Moreover, the differences among rootstock genotypes in early production fruit quality and fruit nutrient

70 concentration was assessed. We hypothesized that rootstocks genotypes will affect the nutrient uptake capacity and this response will be affected by the water limited condition. These results have the potential to better guide rootstock choices for new ‘Honeycrisp’ plantings and provide information on the use of water as a mechanism to improve nutrient acquisition and distribution in a semi-arid environment

Materials and Methods

Plant material

‘Honeycrisp’ apple tress grafted on the four different rootstocks; G41, G890, M9, and B9 were planted in 2016 at WSU-TFREC Sunrise Orchard on a shallow sandy loam soil. Trees were trained as a slender spindle system at a spacing of 0.9 m between trees and 3.6 m between rows. During

2017 and 2018, trees were drip irrigated daily using emitters spaced 30 cm apart that applied 3.78

L h-1 water for two hours (four shifts of 30 min each) daily and based on a soil nutrient analysis, were fertilized in April with 5 kg N, 18 kg P, 52 kg P, 83 kg S, 46 kg Ca, and 15 kg Mg per hectare.

Foliar applications of boron and zinc were applied in April to prevent micronutrient deficiencies.

The experiment was arranged in a completely randomized design with two factors; rootstock (G41,

G890, B9, and M9) and irrigation treatments (control and water-limited). Each plot had five trees with the outer trees acting as border trees and inner three trees were used for measurements.

Soil sampling

In April 2017, twelve soil samples were collected, six at 20 cm and six at 40 cm depth. From each sampling depth, six subsamples were collected using a soil probe and homogenized and send it for nutrient analysis (SoilTest farm consultants, Inc., Moses Lake, WA, USA), for phosphorus,

71 potassium, boron, manganese, copper, iron, calcium, magnesium, and sodium. Additionally, samples were evaluated for cation exchange capacity, total bases, pH, electrical conductivity, organic matter and nitrogen (Table 2).

Treatments

Irrigation treatments consisted of a water-limited treatment where soil water content was maintained near 50% FC and a well-watered control with soil water content maintained near 100%

FC. Field capacity was estimated to be approximately 33% vol/vol following procedures described in Chapter 3. Soil volumetric water content and soil temperature were measured with an ECH2O

5TM soil moisture and temperature probe (Decagon Devices, Pullman, WA, USA) placed in each replicate at 20 cm depth in the herbicide strip directly between trees and two irrigation drip emitters. Each soil probe was interfaced with an EM50G cellular data logger (Decagon Devices,

Pullman, WA, USA) and data was logged every 30 minutes during both years from April to

September. All blossoms were removed from the trees in the two irrigation treatments in both 2017 and 2018. Irrigation treatments were initiated 30 days after full bloom and maintained throughout the growing season for 90 days. During deficit periods, when the volumetric water content fell below 35% of field capacity (approximately 12% vol/vol), water was applied in small amounts to ensure that soil volumetric water content did not exceed 50% of field capacity. Water-limited trees received four applications of 30 min each during a four-hour period once per week.

In 2018, a separate set of trees with fruit was added to the experiment to analyze rootstock effects on fruit quality and fruit nutrient content. After fruit set, trees were thinned to a crop load of 4 fruit cm-2 of trunk cross sectional area. Trees were irrigated fully maintaining soil moisture content to between 85-100%. Trees were harvested at the end of August and total fruit yield per tree and fruit

72 size distribution were measured. A sample of eight fruit from each replicate were used for fruit quality assessments. After harvest, fruit quality was measured using non-destructive and destructive parameters including fruit weight, size, percent of red color, bitter pit incidence, starch index, soluble solid content (°brix) and firmness. Red color coverage was determined using the

Washington State Tree Fruit Research Commission color scale for ‘Honeycrisp’ (Hanrahan, 2012;

Hanrahan and Mendoza, 2012) with values ranging from 1 (0-25% coverage) to 4 (76-100% coverage). The starch index was determined from an equatorial slice from the bottom half of each apple that was sprayed with Lugol’s solution (15 g L-1 potassium iodine and 6 g L-1) using a hang- held spray bottle and left for 10 minutes. Starch content was rated on a scale from 1 (most starch content) to 6 (least starch content) based on visual assessment. Fruit firmness was determined with a fruit texture analyzer (Guss Ltd., Stand, South Africa) with a 10 mm probe and soluble solids was determined with a digital refractometer (PAL-1, Atago Inc. Bellevue, WA, USA).

Mineral Nutrient Analysis

In 2017, five leaves and five first-year stems that were 15 cm in length were collected from each tree 90 days after the start of treatments. Three lateral root sections were also collected at the same time. Roots and leaves were carefully washed using tap water to remove soil or remaining residue.

Root, stem, and leaf samples were then dried in a chamber with constant air flow at 25 °C for 30 days. Once dry, leaf samples were ground into a fine powder using a VWR high throughput homogenizer (VWR, Radnor, PA). For stems and roots, samples were initially ground to 20- micron size using a Wiley Mini mill (Thomas Scientific LLC., Swedesboro, NJ) and then ground to sub-micron size using a VWR high throughput homogenizer (VWR, Radnor, PA). Fruit samples were collected at harvest where a longitudinal peel sample was taken from each apple analyzed

73 for quality, pooled together, and then dried at 60 °C for three days. Samples were then ground into fine powder using a mortar and pestle. For mineral nutrient analysis, 200 mg of roots, stems, leaves or fruit were weighed into PTFE tubes, and acid digested using 6 mL of HNO3. After digestion, the solution was filtered with a 0.45 µM PTFE filter (Thermo Fisher Scientific,

Waltham, MA). Filtered digests were then diluted 100x and analyzed using an Agilent 4200 microwave plasma-atomic emission spectrometer (MP-AES) (Agilent, Santa Clara, CA) and run in combination with calcium, potassium, and magnesium ICP standards for validation (Kalcsits,

2016). Nitrogen content was determined using a PDZ Europa ANCA-GSL elemental analyzer interfaced to a PDZ Europa 20-20 isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK) at the UC Davis Stable Isotope Facility in Davis, CA.

Dry weight determination

After two years of irrigation treatments, whole trees, including roots, were carefully removed from the orchard and separated into leaves, stems and roots. Roots were washed to remove all remaining soil and leaf area was measured using a Licor Li-3100C leaf scanner (Licor Inc., Lincoln, NE,

USA). Plant material was then set to dry in a chamber with constant air flow at 25 °C for 30 days.

Samples were ground and digested in nitric acid to analyze for nutrient concentrations as described above. Elemental concentrations were then multiplied by the total dry weight of each plant part to estimate the plant organ nutrient content (mg) and nutrient partitioning was calculated among the tree parts. Additionally, stoichiometric ratios of nitrogen to calcium (N:Ca), potassium to calcium

(K:Ca), magnesium to calcium (Mg:Ca), and the sum of nitrogen, potassium and magnesium to calcium ((N+K+Mg):Ca) in leaves and fruits were calculated.

74 Air temperature, relative humidity, and wind speed were obtained through the AgWeatherNet weather stations located at the WSU-Sunrise Orchard (Table 1). Data were analyzed by performing an analysis of variance (ANOVA), and a Tukey’s means separation with a confidence of 95%

(SAS, ver. 9.4 PROC GLM). Categorical ordinal variables (percent of red color, starch index and bitter pit incidence) were analyzed using a proportional odds model (SAS, ver. 9.4 PROC GLM), where the model compares the probability of each rootstock of being in the greater levels of the dependent variables (Diaz and Morales, 2009).

Results

Total tree dry weight was significantly lower when water was limited (Fig. 2). G890 had consistently greater leaf, stem and root dry weight than G41, M9 and B9 (Table 3). B9 had the lowest dry weight for leaf and stem but G41 had the lowest root dry weight. Leaf area was also significantly greater for G890. Interestingly, M9 and B9 had higher root:shoot ratio than both

Geneva rootstocks (Table 3). G890 was the most affected by water limitations with a reduction in dry weight of approximately 30% followed by G41 and B9 with 25%, and lastly M9 with a reduction in dry weight of 20% compared to the fully-watered control (Fig. 2).

Nutrient concentrations were affected by both water limitations and rootstock genotype. In 2017, irrigation treatments had a significant effect on nitrogen concentration in roots and stems tissue but not in leaves where nitrogen concentrations were two times greater when water limited compared to the control treatment. Nitrogen concentration was different among rootstocks.

Nitrogen concentrations for M9 was significantly higher than G890 but not than B9 and G41. In

2018, irrigation treatments did not affect nitrogen concentrations. However, B9 had higher root nitrogen concentration than G41, G890 and M9 while for stems it was only higher than G890 and

75 M9, and for leaves, B9 was significantly higher than G890 (Table 4). Calcium concentration was not affected by irrigation treatments nor the rootstocks genotypes in any of the years of the experiment for stems and leaves tissues. However, in 2017, G890 had significantly lower calcium concentrations in the roots than G41, M9 and B9. Furthermore, calcium concentrations were lower overall in 2018 when compare to 2017, especially in leaves (Table 4). In 2017, B9 had the lowest potassium concentrations in both tissues compare to M9 for stems and was lower than G890, G41 and M9 for leaves. In 2018, water-limited trees had higher potassium concentrations in stems than trees that were fully watered. There was a rootstock effect also for stem and leaves where again

B9 had lower concentration than G890 and M9 for stems, and lower than G41, G890 and M9 for leaves. Both G41 and G890 had the highest potassium concentration in leaves in both years (Table

4). Water-limited treatment had higher magnesium concentrations in leaves than the fully-watered control. Rootstock also affected magnesium concentrations. B9 had lower magnesium concentrations in stems than G41 and M9, and G41 had lower concentration than M9 in leaves. In

2018, magnesium concentrations were not affected by water limitations of rootstock genotype for any tissue that was sampled (Table 4).

The large differences in biomass between well-watered and water limited trees translated to differences in overall nutrient content. Well-watered trees had accumulated more nitrogen and magnesium in leaves than trees that were water limited. Nitrogen, calcium, potassium and magnesium were all higher in stems and roots except for nitrogen in roots (Table 5). G890 had higher nitrogen, calcium, potassium and magnesium content in leaves and stems compared to the other rootstocks (Table 5). However, B9 had the greatest root nitrogen content among the rootstocks and M9 the highest magnesium content in roots. Because of differences in biomass, B9

76 had the lowest nutrient content in stems and leaves of all the rootstocks while, for roots, G41 had the lowest nutrient content (Table 5).

Although there were differences in biomass partitioning between treatments, irrigation treatments did not affect overall nutrient partitioning among plant parts (roots, stems and leaves). On the other hand, partitioning of nitrogen, calcium, potassium and magnesium to the roots was consistently higher for B9 while G890 and G41 were the lowest. Conversely, nutrient partitioning to the stems was the lowest for B9 while G41 and G890 had the highest partitioning for all nutrients to the stems. Only calcium and nitrogen partitioning in stems and roots were affected by irrigation treatments. Water-limited trees had higher calcium partitioning to the roots than the control and

M9 and B9 had higher root calcium than G41 and G890. Nitrogen had a significant interaction between rootstock and treatment where only B9 had higher nitrogen in the roots when under water limitations. However, calcium and nitrogen partitioning to the stems was higher for the fully watered control compared to when trees were water limited (Fig. 3). Leaf elemental ratios, including potassium to calcium (K:Ca), nitrogen to calcium (N:Ca), magnesium to calcium

(Mg:Ca), and the sum of nitrogen, potassium and magnesium to calcium (K+N+Mg:Ca) were not affected by irrigation treatment nor rootstocks in either year.

Rootstock genotype had an effect on fruit size, weight, and yield for both years. G890 had larger fruit than B9 (Table 6, Figures 5-7). Fruit firmness was higher for M9 in 2018 and for G890 in

2019. Soluble solids content (SSC) was only different among rootstocks in 2019 where G890 had higher SSC than B9 and G41 (Table 6). Number of fruits per tree was significantly higher for G890 than M9, G41 and B9 in 2018, and was higher for M9 and B 9 than G41 and G890 in 2019. Total weight per tree was significantly higher for M9 than G890, G41 and B9 only in 2019 (Table 6).

Differences between years in the number and weight of fruit per tree shows that 2018 was an off

77 year and 2019 an on year indicating a biennial bearing pattern of ‘Honeycrisp’ for some rootstocks like B9, M9, and G41 but not G890. Rootstock affected bitter pit incidence and red color coverage.

B9 and M9 had a lower probability of bitter pit incidence than G41 and G890 in 2018 and 2019

(Fig. 4). G890 had lower red color coverage than M9 and B9 in 2018 and G41 had higher fruit with red color development than B9, M9 and G890 in 2019 (Fig. 5). The starch clearing score was greater for G41 than G890 (Fig. 6). For both years, regardless of crop load, G890 had the highest amount of fruit above 90 mm in diameter and B9 had the least amount (Fig. 7). G890 had significantly higher fruit potassium concentrations than M9 and B9. G41 had higher fruit magnesium concentration than M9 and B9 (Table 7). Fruit calcium concentrations were not different among rootstocks.

Discussion

The largest impact on nutrient dynamics was a result of water limitations that reduced biomass and changed biomass partitioning to different plant organs. Rootstock also had a significant impact on overall nutrient partitioning. However, nutrient concentrations were also affected indicating that changes to irrigation or rootstock genotype can affect overall uptake of nutrients from the soil and affect their overall transport and distribution within the tree. These differences among rootstocks in leaf and fruit elemental concentrations appear to translate into observed differences in bitter pit incidence and fruit size. There were differences between years, particularly in nutrient concentrations. High temperatures in the spring can accelerate plant growth and organ development (Bisbis, Gruda and Blanke, 2019). This can influence the bud swelling and flower that can affect the remobilization of nutrients such as nitrogen and potassium. Soil nutrient analysis showed an no deficiencies in macro and micronutrients except for phosphorus and sodium which

78 were lower at both depths (Table 2). Nutrient concentrations (mg/g) were higher for 2017 in all parts of the tree than 2018. Since there were none considerable changes in the fertilization program nor the irrigation regime between years, this may have resulted from fertilization practices from the nursery that elevate nutrient concentrations prior to planting. Similarly, Neilsen and Havipson

(2014) also reported decreases in phosphorus, potassium, magnesium, boron, iron, and copper among others from planting of nursery-grown trees up to three years after planting.

The most dwarfing rootstock used in this study, B9, had the highest nitrogen concentration in the roots. In stems and leaves, the most vigorous rootstock, G890, had the lowest nitrogen concentration. Concerning calcium concentration, G890 had the lowest in root. For potassium concentrations, B9 has the lowest in roots and leaves while G890 had the highest in leaves.

Magnesium concentrations were B9 had the lowest in roots and stems. These results are similar to those reported by Fazio et al., 2019 where it was shown that a similar size rootstock CG.5087 than

G890 (Reig et al., 2018; Lordan et al., 2019) had lower nitrogen concentration while B9 and G41 had medium high levels of nitrogen. In that study B9 had low potassium in the leaves and while

B.67-5-32 rootstock, similar size of G890 (Reig et al., 2018; Lordan et al., 2019), and G41 has higher potassium levels in leaves. Additionally, in a potted study, G890 had lower calcium concentrations than the dwarf rootstock G41 in roots (Valverdi, Cheng and Kalcsits, 2019).

Moreover, Neilsen and Havipson, 2014 reported a significant correlation between tree vigor and leaf potassium, phosphorus, boron, coper and calcium. Nevertheless, our results showed a higher potassium concentration in the more vigorous rootstocks, but this was not the case for calcium concentration where there was no vigor effect on leaf calcium. Nutrient concentrations in this study are more in agreement with the concentrations reported in the Neilsen and Havipson, 2014 study than the ones reported in studies done on mature ‘Honeycrisp’ trees and under cooler climates

79 (Cheng and Sazo, 2018; Fazio et al., 2019a). This demonstrates the importance of the consideration on the climatic conditions and stage of development (age) of the orchard when analyzing nutrient concentrations in trees.

Nutrient content integrates dry weight and the results reported in this study correspond with those reported by Fazio et al., 2019 where potassium content was higher in the most vigorous rootstock in the experiment, G890, medium for M9 and G41 and low for the most dwarf rootstock, B9.

However, variation in calcium concentrations observed here differed from Fazio et al., 2019 and

Nielsen and Havipson, 2014. These two studies reported a negative relationship between vigor and leaf calcium concentrations. In contract, in this study, there was no differences in calcium concentrations among the different rootstock genotypes. Differences in calcium content were more closely aligned with differences in dry weight among the different rootstocks. On the other hand, nutrient partitioning between plant parts such as leaves, stems and roots shows how trees allocated and distribute nutrients (Fig. 3). Often potted studies are used to understand nutrient or biomass partitioning in many agricultural crops (Failla et al., 1992; Atkinson et al., 1999; Alemán et al.,

2011; Verbruggen and Hermans, 2013). Interestingly, the results shown here differ than those reported in Valverdi et al., 2019 where G890 had the most partitioning of nutrients to roots and B9 into the stems while here, B9 partitioned more nutrients to the roots and G890 and G41 partitioned more nutrients to the stems. Several factors could contribute to differences in allocation and distribution of nutrients between potted and field studies. This could be caused by limitations in the root volume in the potted experiment in contrast to a field experiment where roots can occupy a greater volume. However, in irrigated growing environments, root volumes rarely exceed the watering zone (Jones, 2004; Hodge et al., 2009) and drip emitters were used in the field study that could have also limited overall root volume. Rootstock did not affect nutrient partitioning to the

80 leaves in any of the studies mentioned. In potted trees, Valverdi et al., 2019 also reported elevated nitrogen and calcium partitioning to the root for water-limited trees. However, they also reported elevated partitioning of these nutrients to the stems. In contrast, nitrogen and calcium partitioning to the stems was higher for the well-watered control treatment in the field that was likely a consequence of elevated shoot vigor when trees were fully irrigated. Nutrient content under water- limited conditions were higher in structural tissue like roots and stems compared to leaves. Nutrient concentration, on the other hand, was higher in roots and stems of water-limited trees but not in leaves. These results are in contrast to previous studies where nutrient concentrations in leaves of water stressed or non-irrigated trees were higher than trees that were well watered (Atkinson et al.,

1998; Valverdi, Cheng and Kalcsits, 2019).

Rootstocks can have a significant influence on fruit quality by affecting fruit size, firmness, fruit color, soluble solids content, and maturity (Musacchi and Serra, 2018). Here, we report a rootstock effect on fruit size and color for ‘Honeycrisp’. G890 had larger fruit and B9 had the smallest but

M9 and G41 had the fruit with most percent of red color, and G890 had the lowest starch degradation (Table 6, Fig. 5, Fig. 6, and Fig. 7). Fruit size and color development are two of the primary considerations in grading fruit and as such, rootstock would have a major impact on fruit commercial grading. Large fruit in ‘Honeycrisp’ are typically more prone to develop bitter pit

(Rosenberger et al., 2004). Fruit size is often positively related to rootstock vigor (Autio, 2001;

Neilsen and Havipson, 2014; Reig et al., 2018). Fallahi et al, 2012, also reported similar results for ‘Gala’ grafted onto different rootstocks. In their study, the most vigorous rootstock, Supporter4, had lower color development and lower starch degradation than more dwarfing rootstocks such as

B9, M9 and G30. Bitter pit incidence was previously reported to be influenced by rootstock genotype (Lordan et al., 2019). In this study, G890 and G41 had higher probability of bitter pit

81 incidence and M9 and B9 had the lowest probability of bitter pit incidence for both years. Lordan et al., 2019 also reported lower bitter pit incidence for B9 and M9, and a high bitter pit incidence for rootstocks of similar vigor than G890 such as CG.5087. Conversely in their study, G41, had low bitter pit incidence for 3 year while our results were consistently high for both years of the study. Fruit potassium and magnesium concentration were higher for both G41 and G890 in this study. Similarly, Fazio et al., 2019 reported that B9 and M9 has medium and medium-low potassium concentrations while G41 and a similar vigor rootstock than G890, B.7-20-21 has medium to high fruit potassium concentrations. Fruit magnesium concentrations were not different for G41, M9 and B.7-20-21 but B9 had lower fruit magnesium concentrations. Smaller fruit size and lower potassium content in the fruit of B9 and M9 rootstocks could, in part, contribute to lower bitter pit incidence observed in these rootstocks (Serra et al., 2016; Kalcsits, et al., 2017; Fazio et al., 2019b). Although other studies were conducted in cooler regions with different growing environments (Lordan et al. 2019; Fazio et al. 2019), differences in fruit nutrient concentrations among rootstock are mostly consistent with those observed here.

Conclusion

Rootstock genotype showed an effect on nutrient acquisition and distribution in young

‘Honeycrisp’ apple trees. Fruit size and bitter pit incidence corresponded to differences in nutrient uptake among rootstock genotypes and the importance on the partitioning and distribution of these nutrients on fruit size, quality, and disorder incidence. Interestingly, water-limited conditions increased the nutrient concentration in reserve or structural tissues such as root and stems but did not affect leaves. Water-limited trees partitioned more nitrogen and calcium to the roots, while well-water control trees had higher nutrient partitioning to the stems. Despite of the differences in

82 climatic conditions among this and other studies, our results agree with those previously reported where more vigorous rootstocks like G890 had lower nitrogen and higher potassium concentrations, and more dwarfing rootstocks such as B9 had lower potassium and higher nitrogen concentrations in leaves. Nonetheless, rootstocks did not show differences in calcium uptake capacity regardless of differences in vigor. For rootstocks with higher vigor, irrigation is more important to control excessive growth which can be detrimental to tree productivity and possibly limit nutrient distribution to fruit. Further research should focus on lifetime evaluation of rootstock differences in orchard production systems that may not be captured in shorter-term experiments.

Furthermore, environmental conditions need to be accounted for in future studies that may account for differences among rootstocks in growth, nutrient acquisition, and partitioning to fruit.

83 References

Alemán, F., Nieves-Cordones, M., Martínez, V., Rubio, F., 2011. Root K + acquisition in plants: The arabidopsis thaliana model. Plant Cell Physiol. 52, 1603–1612.

Atkinson, C.J., Policarpo, M., Webster, A.D., Kuden, A.M., 1999. Drought tolerance of apple rootstocks: Production and partitioning of dry matter. Plant Soil 206, 223–235.

Autio, W.R., 2001. Rootstock and scion interact to affect apple tree performance: Results from the 1990 NC-140 cultivar/rootstock trial. Acta Hortic. 557, 41–46.

Bisbis, M.B., Gruda, N.S., Blanke, M.M., 2019. Securing Horticulture in a Changing Climate—A Mini Review. Horticulturae 5, 56.

Casierra-Posada, F., Cortes, L.F., Ramirez, J., Franco, H.C., 2003. Estado nutricional de arboles de manzano ‘anna’ durante la estacion de crecimiento en los altiplanos colombianos. i. contenido de elementos minerales 21, 75–82.

Casierra-Posada, F., Lizarazo, L.M., 2004. Estado nutricional de árboles de manzano 'Anna' durante la estación de crecimiento en los altiplanos Colombianos: II. Relaciones e interacciones entre nutrientes. Agron. Colomb. 22, 160–169.

Cheng, L., Sazo, M.M., 2018. Why is 'Honeycrisp' so susceptible to bitter pit? Fruit Q. 26, 19–23. de Freitas, S.T., do Amarante, C.V.T., Mitcham, E.J., 2015. Mechanisms regulating apple cultivar susceptibility to bitter pit. Sci. Hortic. (Amsterdam). 186, 54–60.

Diaz, L., Morales, M., 2009. Analisis estadistico de datos categoricos, First eddi. ed. Universidad Nacional de Colombia, Bogota.

Failla, O., Zocchi, G., Treccani, C., Cocucci, S., 1992. Growth, development and mineral content of apple fruit in different water status conditions. J. Hortic. Sci. 67, 265–271.

Fallahi, E., 2012. Influence of rootstock and irrigation methods on water use, mineral nutrition, growth, fruit yield, and quality in 'Gala' apple. Horttechnology 22, 731–737.

Fazio, G., Kviklys, D., Grusak, M.A., Robinson, T., 2013. Phenotypic Diversity and QTL Mapping of Absorption and Translocation of Nutrients by Apple Rootstocks. Asp. Appl. Biol. 119, 37–

84 50.

Fazio, G., Lordan, J., Grusak, M.A., Francescatto, P., Robinson, T.L., 2019a. I. Mineral nutrient profiles and relationships of ‘Honeycrisp’ grown on a genetically diverse set of rootstocks under Western New York climatic conditions. Sci. Hortic. (Amsterdam). 1–19.

Fazio, G., Lordan, J., Grusak, M.A., Francescatto, P., Robinson, T.L., 2019b. I. Mineral nutrient profiles and relationships of ‘Honeycrisp’ grown on a genetically diverse set of rootstocks under Western New York climatic conditions. Sci. Hortic. (Amsterdam). 257, 108686.

Fazio, G., Robinson, T.L., Aldwinckle, H.S., 2014. Geneva Apple Rootstocks Comparison Chart [WWW Document]. Cent. Technol. Licens. Cornell Univ. URL http://www.ctl.cornell.edu/plants/GENEVA-Apple-Rootstocks-Comparison-Chart.pdf

Ferguson, I.B., Watkins, C.B., 1989. Bitter pit in apple fruit. Hortic. Rev. (Am. Soc. Hortic. Sci). 289–355.

Gallardo, R.K., Hanrahan, I., Hong, Y.A., Luby, J.J., 2015. Crop load management and the market profitability of ‘Honeycrisp’ apples. Horttechnology 25, 575–584.

Grant, O.M., 2012. Abiotic Stress Responses in Plants.

Hanrahan, I., 2012. Starch iodine index 'Honeycrisp'.

Hanrahan, I., Mendoza, M., 2012. 'Honeycrisp' color classification scale -%of red.

Hodge, A., Berta, G., Doussan, C., Merchan, F., Crespi, M., 2009. Plant root growth, architecture and function, Plant and Soil.

Jones, H.G., 2004. Irrigation scheduling: Advantages and pitfalls of plant-based methods. J. Exp. Bot. 55, 2427–2436.

Kalcsits, L.A., 2016. Non-destructive measurement of calcium and potassium in apple and pear using handheld X-ray fluorescence. Front. Plant Sci. 7, 442.

Kucukyumuk, Z., Erdal, I., 2011. Rootstock and cultivar effect on mineral nutrition, seasonal nutrient variation and correlations among leaf, flower and fruit nutrient concentrations in

85 apple trees. Bulg. J. Agric. Sci. 17, 633–641.

Lordan, J., Fazio, G., Francescatto, P., Robinson, T., 2017. Effects of apple (Malus × domestica) rootstocks on scion performance and hormone concentration. Sci. Hortic. (Amsterdam). 225, 96–105.

Lordan, J., Fazio, G., Francescatto, P., Robinson, T.L., 2019. II. Horticultural performance of 'Honeycrisp' grown on a genetically diverse set of rootstocks under Western New York climatic conditions. Sci. Horticuhurae 257, 1–10.

Marini, R.P., Black, B., Crassweller, R.M., Domoto, P.A., Hampson, C., Moran, R., Robinson, T., Stasiak, M., Wolfe, D., 2014. Performance of 'Golden Delicious' apple on 23 rootstocks at eight locations: A ten-year summary of the 2003 NC-140 dwarf rootstock trial. J. Am. Pomol. Soc. 68, 54–68.

Marini, R.P., Fazio, G., 2018. Apple rootstocks: History, physiology, management, and breeding. Hortic. Rev. (Am. Soc. Hortic. Sci). 45, 197–312.

Musacchi, S., Serra, S., 2018. Apple fruit quality: Overview on pre-harvest factors. Sci. Hortic. (Amsterdam). 234, 409–430.

Neilsen, G., Havipson, C., 2014. 'Honeycrisp' Apple Leaf and Fruit Nutrient Concentration is Affected by Rootstock During Establishment. J. Am. Pomol. Soc. 68, 178–189.

Reig, G., Lordan, J., Fazio, G., Grusak, M.A., Hoying, S., Cheng, L., Francescatto, P., Robinson, T., 2018. Horticultural performance and elemental nutrient concentrations on ‘Fuji’ grafted on apple rootstocks under New York State climatic conditions. Sci. Hortic. (Amsterdam). 227, 22–37.

Rosenberger, D.A., Schupp, J.R., Hoying, S.A., Cheng, L., Watkins, C.B., 2004. Controlling bitter pit in ‘Honeycrisp’ apples. Horttechnology 14, 342–349.

Serban, C.F., 2018. Preharvest and postharvest management strategies to reduce bitter pit in 'Honeycrisp' apples. Washington State University.

Serra, S., Leisso, R., Giordani, L., Kalcsits, L., Musacchi, S., 2016. Crop load influences fruit quality, nutritional balance, and return bloom in 'Honeycrisp' apple. HortScience 51, 236– 244.

Suzuki, N., Rivero, R.M., Shulaev, V., Blumwald, E., Mittler, R., 2014. Abiotic and biotic stress

86 combinations. New Phytol. 203, 32–43.

Tworkoski, T., Fazio, G., 2011. Physiological and morphological effects of size-controlling rootstocks on 'Fuji' apple scions. Acta Hortic. 903, 865–872.

Tworkoski, T., Fazio, G., 2016. Hormone and growth interactions of scions and size-controlling rootstocks of young apple trees. Plant Growth Regul. 78, 105–119.

Valverdi, N.A., Cheng, L., Kalcsits, L., 2019. Apple Scion and Rootstock Contribute to Nutrient Uptake and Partitioning under Different Belowground Environments. Agronomy 9, 415.

Verbruggen, N., Hermans, C., 2013. Physiological and molecular responses to magnesium nutritional imbalance in plants. Plant Soil 368, 87–99.

Zandalinas, S.I., Mittler, R., Balfagón, D., Arbona, V., Gómez-Cadenas, A., 2018. Plant adaptations to the combination of drought and high temperatures. Physiol. Plant. 162, 2–12.

87 Table 3. 1. Average environmental data from WSU-Sunrise and WSU-TFREC AgWeatherNet weather stations for 2017 and WSU-Sunrise for 2018 of the months April to October.

2017 Air temp. RH W. Speed (°C) (%) (m/s) May 16.30 51.03 1.81 Jun 20.55 40.94 2.20 Jul 26.33 29.50 2.40 Aug 25.02 36.06 1.82 2018 May 19.88 43.64 3.16 Jun 19.93 41.02 3.01 Jul 26.01 31.54 2.89 Aug 23.87 38.13 2.46

88 Table 3. 2. Soil test results for the WSU-Sunrise orchard. Samples taken on April 2017. Dept h P K B Zn Mn Cu Fe Ca Mg Na N (mg/k (mg/k (mg/k (mg/k (mg/k (meq/100g (meq/100g (meq/100g (Kg/h (cm) (mg/kg) g) (mg/kg) g) g) g) g) r) r) r) a) 20 10.7 373 0.19 1.9 2.3 0.7 9.7 6.4 1.7 0.07 73.2 40 8.3 389 0.17 2.4 2.17 0.6 9 6.3 1.7 0.05 64.3 CEC EC NH4 NO3 SO2 OM T. bases Base sat. ESP (meq/100g pH (m.mhos/c (mg/k (mg/k (mg/k (meq/100g ENR (%) (%) (%) r) m) g) g) g) r) 20 8.9 7.1 0.13 2.5 1.9 7.7 1.4 9.2 103.3 0.8 47.7 40 8.7 7.1 0.11 2.5 1.6 7.3 1.1 9.1 104.5 0.6 40.7

Table 3. 3. Root, stem and leaf biomass (grams dry weight), total leaf area (cm2) and root:shoot biomass ratio (± standard error; n = 3)

for ‘Gala’ and ‘Honeycrisp’ apple on cultivars Bud-9 (B9), G41, G890, and M9-T337 (M9) under water limitations or elevated soil

temperatures compared to an untreated control. Values at the bottom correspond to the p-values of factors and its interactions that were

signiﬁcant for at least one variable.

Dry Weight (g) Treatment Rootstock Leaf (g) Stem (g) Root (g) Leaf Area (cm²) Root:Shoot B9 350 ± 30 B 667 ± 140 B 747 ± 70 AB 15406 ± 276 B 0.74 ± 0.04 A G41 426 ± 69 AB 1119 ± 285 B 653 ± 141 B 18893 ± 3701 B 0.42 ± 0.02 B Control G890 536 ± 29 A 1936 ± 227 A 1080 ± 40 A 37151 ± 4088 A 0.45 ± 0.06 B 90 M9 375 ± 61 B 912 ± 190 B 987 ± 131 A 23408 ± 4454 B 0.78 ± 0.04 A

B9 242 ± 34 b 401 ± 45 b 653 ± 67 ab 12634 ± 788 b 1.01 ± 0.05 a Water- G41 336 ± 15 ab 736 ± 37 b 480 ± 61 b 15884 ± 2338 b 0.45 ± 0.05 b limited G890 420 ± 47 a 948 ± 120 a 787 ± 67 a 30322 ± 4455 a 0.57 ± 0.07 b M9 297 ± 39 b 696 ± 109 b 747 ± 35 a 17881 ± 2125 b 0.78 ± 0.01 a Rootstock 0.0047 0.0022 0.0004 0.0013 <0.0001 Treatment 0.006 0.0042 0.001 0.092 0.0120 Rootstock*Treatment 0.97 0.67 0.11 0.90 0.07

Table 3. 4. Nitrogen, calcium, potassium, and magnesium concentration (mg/g) for roots, stems and leaves of ‘Honeycrisp’ apple on

Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotype under two irrigation treatments. Diﬀerent letters denote signiﬁcant

diﬀerences among columns determined using a Tukey’s mean separation test (α = 0.05). Different letters indicate signiﬁcance in

diﬀerences among means at p-value < 0.05.

2017 2018 Rootstock Treatment Rootstock Treatment Water- Water- B9 G41 G890 M9 Control B9 G41 G890 M9 Control limited limited Nitrogen Roots 15.7 a 14.9 a 17.5 a 16.1 a 10.1 b 22.0 a 13.8 a 9.6 b 7.5 b 8.9 b 9.7 a 10.2 a 91 Stems 9.7 a 9.3 a 10.2 a 8.6 a 6.2 b 12.7 a 12.9 a 11.4 ab 9.8 b 10.2 b 11.2 a 11.0 a

Leaves 15.5 ab 16.7 ab 13.8 b 16.8 a 16.3 a 15.1 a 17.1 a 14.6 ab 13.0 b 15.4 ab 14.4 a 15.6 a Calcium Roots 9.1 a 9.3 a 6.4 b 9.5 a 8.7 a 8.4 a 15.0 a 18.0 a 14.0 a 15.6 a 15.4 a 16.0 a Stems 18.8 a 15.0 a 14.6 a 16.3 a 16.1 a 16.3 a 25.4 a 22.4 a 23.2 a 20.8 a 23.2 a 22.6 a Leaves 17.9 a 17.0 a 20.9 a 18.0 a 18.6 a 18.3 a 15.6 a 13.4 a 16.0 a 15.0 a 13.8 a 16.2 a Potassium Roots 8.3 a 7.1 a 8.1 a 7.8 a 8.2 a 7.4 a 9.0 a 7.4 a 8.8 a 7.8 a 8.4 a 8.2 a Stems 7.7 b 10.0 ab 9.1 ab 10.4 a 9.1 a 9.6 a 9.2 b 11.0 ab 11.8 a 12.0 a 10.2 b 11.8 a Leaves 15.0 b 23.0 a 23.0 a 21.8 a 20.1 a 21.4 a 19.0 c 24.6 ab 27.8 a 23.2 b 22.6 a 24.6 a Magnesium Roots 1.6 a 2.1 a 1.9 a 2.1 a 2.0 a 1.9 a 1.8 a 2.2 a 2.0 a 2.2 a 2.2 a 2.2 a Stems 2.3 b 3.0 a 2.5 ab 3.1 a 2.6 a 2.8 a 3.2 a 3.0 a 3.2 a 3.4 a 3.2 a 3.4 a Leaves 2.8 ab 2.3 b 2.6 ab 2.9 a 2.4 b 2.8 a 4.4 a 4.0 a 4.2 a 3.8 a 4.0 a 4.0 a

Table 3. 5. Nitrogen, calcium, potassium, and magnesium content (mg) for roots, stems and leaves of ‘Honeycrisp’ apple on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotype under two irrigation treatments. Different letters denote significant differences among columns determined using a Tukey’s mean separation test (α = 0.05). Different letters indicate significance in differences among means at p-value < 0.05.

Rootstock Treatment Water- B9 G41 G890 M9 Control limited Nitrogen Roots 9660 a 5509 b 7046 ab 7706 ab 8262 a 6699 a Stems 7001 b 11291 ab 14098 a 7966 b 12500 a 7349 b Leaves 5011 a 5575 a 6139 a 4989 a 5931 a 4927 b

Calcium

Roots 10491 a 10156 a 12711 a 13528 a 12932 a 10511 b

Stems 13713 b 20696 b 32100 a 16776 b 25783 a 15859 b Leaves 4498 b 5127 ab 7332 a 4808 b 5728 a 5154 a Potassium Roots 6370 ab 4273 b 8108 a 6872 ab 7275 a 5537 b Stems 4780 c 9931 b 15991 a 9707 bc 11730 a 8475 b Leaves 5531 c 9284 b 13272 a 7837 bc 9780 a 8181 a Magnesium Roots 1332 ab 1277 b 1919 ab 2018 a 1839 a 1434 b Stems 1729 b 2768 b 4509 a 2674 b 3587 a 2253 b

Leaves 1240 b 1506 ab 1995 a 1267 b 1707 a 1297 b

92 Table 3. 6. Fruit quality parameters, number of fruit per tree, yield per tree, individual fruit size (mm), individual fruit weight (g), fruit

firmness (Kg), and fruit soluble solids content (SSC) for ‘Honeycrisp’ apple on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks

genotypes under two irrigation treatments. Different letters denote significant differences among columns determined using a Tukey’s

mean separation test (α = 0.05). Different letters indicate signiﬁcance in diﬀerences among means at p-value < 0.05. Rootstock No. Fruits per Yield per tree Fruit Size Fruit Weight Fruit Firmness Fruit SSC tree (kg) (mm) (g) (kg) (Brix) 2018 B9 10.3 ± 1.1 b 1.4 ± 0.1 a 90.8 ± 1.2 b 307.0 ± 12.1 b 7.7 ± 0.1 a 14.3 ± 0.2 a G41 10.4 ± 1.2 b 1.6 ± 0.2 a 93.2 ± 1.6 ab 342.2 ± 15.3 ab 6.9 ± 0.2 b 14.8 ± 0.3 a G890 16.1 ± 2.2 a 2.5 ± 0.3 a 95.2 ± 1.0 a 346.3 ± 10.3 a 7.3 ± 0.2 ab 14.4 ± 0.2 a M9 14.2 ± 1.0 ab 2.2 ± 0.2 a 92.1 ± 0.9 ab 327.8 ± 8.5 ab 7.8 ± 0.2 a 14.2 ± 0.2 a 2019

B9 35 ± 3.8 a 4.0 ± 0.2 b 83.9 ± 1.1 b 231.6 ± 8.7 c 6.6 ± 0.1 ab 11.9 ± 0.2 b G41 19.1 ± 2.0 b 3.5 ± 0.4 b 91.8 ± 0.9 a 304.7 ± 10.1 ab 6.6 ± 0.1 ab 12.0 ± 0.3 b G890 17.1 ± 3.7 b 2.9 ± 0.4 b 92.8 ± 1.1 a 231.4 ± 11.1 a 6.9 ± 0.1 a 13.4 ± 0.3 a M9 41.1 ± 4.0 a 5.7 ± 0.4 a 89.1 ± 1.2 a 279.1 ± 11.2 b 6.4 ± 0.1 b 12.6 ± 0.2 ab

Table 3. 7. Fruit nutrient concentration (mg/g) for ‘Honeycrisp’ apple on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks

genotypes under two irrigation treatments. Different letters denote significant differences among columns determined using a Tukey’s

mean separation test (α = 0.05). Different letters indicate signiﬁcance in diﬀerences among means at p-value < 0.05. Rootstock Ca K Mg K/Ca Ca K Mg K/Ca (µg/g) (µg/g) (µg/g) ( µg/g ) ( µg/g ) ( µg/g ) 2018 2019 B9 30 a 1048 b 36 b 36 a 10 a 808 b 42 c 75 a G41 20 a 1148 ab 42 a 67 a 14 a 1268 a 82 a 104 a G890 12 a 1276 a 38 ab 81 a 14 a 1348 a 72 ab 95 a M9 26 a 1058 b 36 b 44 a 20 a 970 b 56 bc 53 a

Figure 3. 1. Soil water content (mm) and soil temperature (°C) during the growing season for the field experiment at WSU Sunrise experimental orchard for 2017 and 2018.

Figure 3. 2. Total dry weight of 3-year-old ‘Honeycrisp’ apple trees grafted on Bud-9 (B9), G41,

Tukey’s mean separation test (α=0.05).

Figure 3. 3. Total tree nitrogen, calcium, potassium and magnesium partitioning (%) between roots, stems and leaves for ‘Honeycrisp’ apple grafted on Bud-9 (B9), G41, G890, and M9-T337

(M9) rootstocks genotypes under two irrigation treatments.

Figure 3. 4. Probability of occurrence of bitter pit presence in fruits at harvest for ‘Honeycrisp’ apple fruit grafted on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotypes.

Figure 3. 5. Probability of occurrence of red color development in fruits at harvest for ‘Honeycrisp’ apple fruit grafted on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotypes.

Figure 3. 6. Probability of occurrence of starch degradation in fruits at harvest for ‘Honeycrisp’ apple fruit grafted on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotypes.

100

Figure 3. 7. Probability of occurrence of fruits size per tree at harvest for ‘Honeycrisp’ apple fruit grafted on Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks genotypes.

101 CHAPTER FOUR: APPLE ROOTSTOCK AFFECTS SCION RESPONSES TO WATER

LIMITATIONS UNDER FIELD CONDITIONS

Abstract

Many drought studies are based on short-term experiments under controlled environments, which may not be always applicable to field conditions. Drought stress under field conditions often co- occurs with other stress such as high air and soil temperature, high light irradiance, reduced nutrient availability, soil compaction, among others. In composite plants like apple, both rootstock and scion combine to affect drought response. However, the effect that apple rootstocks genotypes have on scion response to water limitations have not been extensively studied. The objective of this study was to measure physiological responses of different apple rootstock genotypes to water limitations under both field and greenhouse conditions. For both experiments, ‘Honeycrisp’ apple was grafted onto G41, G890, M9, and B9 rootstocks. Two irrigation treatments were established: a drought stress (~50% of field capacity (FC)) and a well-watered control (~100% FC). Leaf gas exchange, mid-day stem water potential, quantum yield of PSII (ΦII) and shoot growth were measured bi-weekly. At the end of each experiment, total leaf area was measured, and root, stem and leaf samples carbon isotope composition (δ13C) was measured. Elevated temperatures and

VPD under field conditions induced a different response among rootstocks under water limitations compared to trees grown in a controlled environment. Under water limitations in the field,

‘Honeycrisp’ grafted onto G890 had lower stomatal conductance, net CO2 exchange rates, ΦII, and ultimately, shoot growth. In contrast, B9 maintained stomatal conductance and shoot growth when water limited and had the most enriched δ13C and lowest stem water potential among

102 rootstock genotypes even under well-watered conditions. These results show how rootstock genotype can affect scion response to water limitations in apple. Furthermore, we demonstrate how field conditions can magnify drought responses that were not observed under more controlled environments in the greenhouse.

Keywords: Malus × domestica, carbon isotope composition, leaf gas exchange, vegetative growth, photochemical quenching.

103 Introduction

Abiotic stress is one of the leading causes of crop losses worldwide (Zandalinas et al., 2018). A common theme across climate change models is the continuation of increases in temperature for the 21st century under all projected scenarios, and the relationship between global temperature and global precipitation is almost linear (Collins et al., 2013). The increase in global temperature is forecast to limit snow accumulation and cause earlier snowmelt at high altitudes resulting in a reduction in water that is supplied for irrigation (Vano et al., 2010). Many tree fruit orchards around the world are in regions that require irrigation making them more susceptible to higher temperatures and water shortages in the future (Marini and Fazio, 2018). Low precipitation, elevated temperatures, and high light intensity in commercial apple growing regions can be a source of abiotic stress reducing yield and adversely affecting plant growth and productivity

(Wunsche et al., 2000; Jackson, 2003; Peck et al., 2006; Kalcsits et al., 2017). To maintain productivity in these regions, it will be important that trees that are tolerant of water limitations and associated abiotic stressors.

Plant responses to drought have been extensively studied for agricultural crops. Under field conditions, crops are subjected to several corresponding abiotic stresses occurring simultaneously and the extrapolation of each individual stress response is often confounded by other variables

(Zandalinas et al., 2018). Drought stress in the field often co-occurs with other stress such as high air and soil temperature, high light irradiance, increased soil salinity, reduced nutrient availability, compacted soils, among others (Grant, 2012). Therefore, plant responses to drought are complex.

Under field conditions, these responses can be synergistically or antagonistically affected by the superposition of several stresses. Plant strategies to cope with drought usually involve a

104 combination of stress avoidance and tolerance strategies which can vary with genotype (Chaves et al., 2011). In the leaf, drought can increase stomata density and reduced leaf area (Elias, 1995) which can be accompanied by a reduction of carbon assimilation and a down-regulation of photochemistry (Chaves et al., 2002). Many water stress studies have been based on short-term experiments under controlled environments, which may not be directly applicable to field conditions. Development of stress-tolerant genotypes to multiple stresses may need to be tested with field experiments to better evaluate its performance under different environmental conditions

(Chaves et al., 2011).

Most tree fruit species are composite plants and consist of a genetically distinct rootstock and scion. Rootstocks have been used for more than 2000 years to improve fruit quality, reduce tree size, induce precocity, and improve disease resistance and water use among other desired traits

(Fazio et al., 2013; Marini and Fazio, 2018). Dwarfing rootstocks were used in England and

America during the 19th century to reduce tree size, avoid biannual bearing, and induce early cropping that generates a faster economic return (Marini and Fazio, 2018). Reducing tree size improves orchard and labor efficiency and, as a result, high density orchards with precision irrigation systems were implemented in almost every tree fruit producing region (Jackson, 2003).

The reduction in tree size also reduces the amount of water required. However, different rootstock genotypes show differences in water use (Jensen et al., 2009, 2012; Liu et al., 2012; Zhou et al.,

2015). It is believed that more vigorous rootstocks, because of their larger root system, are more resistant to drought and can access water deeper in the soil profile. In contrast, dwarfing rootstocks have been shown to adapt better to short-term drought conditions because of elevated ABA concentrations (Fernandez et al., 1997; Tworkoski et al., 2016). However, these responses have

105 been inconsistent and some studies have reported no relation between vigor and drought tolerance

(Atkinson et al., 1999).

Drought conditions can affect photosynthetic rates through stomatal closure induced by internal signaling from the roots via the production of abscisic acid (ABA ) (Davies et al., 2005).

Reductions in photosynthesis rate due to water limitations are related to both stomatal and non- stomatal limitations, meaning that a direct relation between stomatal conductance and photosynthetic rates can often be found when under drought. However, in some plant species, this relationship is not as clear, and photosynthetic rates can decrease more than stomatal conductance, possibly due to a decrease in effects on the carboxylation process (Flexas et al., 2006; Chaves et al., 2009; Zhou et al., 2013, 2014). Additionally, when drought co-occurs with high light intensity and heat, oxidative damage can limit carbon fixation and antioxidants contribute to the protection of the photosynthetic machinery against excitation energy not dissipated via photosystem II (PSII)

(Wingler et al., 1999). Carbon isotope discrimination is a valuable tool to help integrate carbon fixation with plant water status and its coordination with water use in C3 species. Results from earlier studies reported a substantial variation in isotopic values at inter- and intraspecific levels, as well with different environmental growth conditions and with dry-matter composition (Farquhar et al., 1989). When soil water content is reduced, photosynthetic rates, transpiration rate, and stomatal conductance all decrease (Farquhar and Sharkey, 1982). These effects will translate to an increase in isotope composition (δ13C) or a decrease in isotope discrimination (Δ) (Farquhar et al.,

1989; Cui et al., 2009). In apple, Glenn (2014) reported a negative correlation between instantaneous water use efficiency (WUEInst=A/Ec) with leaf carbon isotope discrimination for irrigated and non-irrigated trees.

106 The effect that rootstock genotype has on drought response by the scion has being previously reported (Atkinson et al., 1999, Tworkoski et al., 2016; Marini and Fazio, 2018; Valverdi, Cheng and Kalcsits, 2019). However, differences among rootstocks genotypes in their response to drought and its combination with other abiotic stresses was not extensively studied. The objective of this study was to determine the different physiological responses of different rootstock genotypes to drought and the combination of drought with other abiotic factors in the field. For this, two experiments were conducted: a greenhouse and a field-based experiment using four different rootstock genotypes with ‘Honeycrisp’ apple scion during 2017 and 2018. We hypothesized that rootstock genotype will impact physiological responses to drought, and that co-occurring abiotic stresses in the field will affect these responses when compared to more controlled environments in the greenhouse. This study has implications regarding the evaluation of stress responses in perennial trees and for our understanding of how rootstocks modulate response to water limitations by the scion in apple.

Materials and Methods

The study consisted of a greenhouse experiment conducted at the Washington State University

(WSU) Tree Fruit Research and Extension Center in Wenatchee, WA (47°26'17.6"N

120°20'48.3"W), and a field experiment at WSU-Sunrise experimental orchard in Rock Island,

WA (47°18'35.6"N 120°03'59.5"W) respectively. ‘Honeycrisp’ apple grafted onto four different rootstock genotypes were used. Two of the rootstocks were from the Geneva series: G41 (dwarf) and G890 (semi-dwarf). The other two rootstocks were M9-T337 (M9) (dwarf), and Bud-9 (B9)

107 (dwarf). These rootstocks ranged in dwarfing capacity with G890 considered semi-dwarfing, M9 and G41 considered dwarfing and Bud-9 considered super-dwarfing.

Greenhouse experiment

In 2017, one-year-old potted apple trees were grown in a greenhouse between April and August under ambient light and humidity with temperatures maintained between 20 and 25 °C. Liners of

B9, G41, G890, and M9 rootstocks were planted in 10.9 L pots using a sterile, high porosity growing medium (Pro-mix HP, Quakertown, PA, USA) to allow for adequate drainage and aeration. A week after establishment, scion wood was cleft grafted to each rootstock genotype.

‘Honeycrisp’ was selected as scion cultivar because of its growing popularity among consumers and its difficulty to grow under Washington State environmental conditions (Watkins et al., 2004;

Rosenberger et al., 2004). Trees were drip-irrigated daily for 30 min with emitters of that applied

3.78 L h-1 until soil saturation was achieved and fertilized every two weeks (0.5 L per tree) with a water-soluble fertilizer (Scotts Miracle-Gro, Marysville, OH, USA) containing 24% total nitrogen

(3.5% ammoniacal nitrogen and 20.5% urea nitrogen), 8% available phosphate (P2O5), 16% soluble potassium (K2O), 0.02% boron, 0.07% water-soluble copper, 0.15% chelated manganese,

0.0005% molybdenum, and 0.06% water-soluble zinc. 0.5 L of nutrient solution with 4.53 mM N,

0.68 mM P, 1.08 mM K, 0.003 mM Cu, 0.007 Fe, 0.002 mM Mn, 1.38-5 mM Mo, and 0.002 mM

Zn. Sufficient calcium and sulfur concentrations were present in the mountain-based water source

(Public utility district, 2018). After trees reached 45 cm in height, trees were arranged in a split- plot design with two irrigation treatments as main plots and rootstock as subplots. The treatments consisted of a well-watered control with full irrigation that was maintained at 100% field capacity; and a water limited treatment where soil moisture was maintained at 50% of field capacity. Field

108 capacity was determined by watering the trees to saturation and, after allowing the media to drain gravimetrically, measuring the volumetric water content using a capacitance EC-5 small soil moisture sensor at 10 cm from the tree’s trunk and to 15 cm depth in the pot (Decagon Devices,

Pullman, WA, USA) connected to a handheld data logger (Decagon Devices, Pullman, WA, USA).

For the drought stress treatment, once soil moisture had been depleted to 50% of field capacity, water was added to elevate soil moisture above 60% field capacity (Fig. 1). To be able to maintain the soil moisture content at the desired level, soil moisture was measured twice per week.

Physiological measurements

Physiological measurements were performed biweekly during 60 days. Shoot elongation was determined by measuring stem length from the graft union to the apical meristem at every measurement interval. Leaf gas exchange (photosynthetic rate, transpiration rate, and stomatal conductance) was measured on a fully mature expanded sun-exposed leaf using a Li-6400XT gas exchange system (Li-Cor, Inc., Lincoln, NE, USA) where photosynthetically active radiation inside the chamber was set to 1,500 µmol m-2s-1 to avoid confounding effects of variation in light.

-1 Leaf temperature was maintained at 25 °C, Reference CO2 were set to 400 µmol mol , and the chamber window was 2 cm2. Mid-day stem water potential was measured using a Scholander system Pressure Chamber Instrument (PMS Instrument Co., Albany, OR, USA) at solar noon

(Shackel, 2000) to monitor the plant water status. Additionally, quantum yield of Photosystem

(PS) II (ΦII) was measured using a sun-exposed leaf at solar noon using a Photosynq instrument

(Venturit, Inc., Lansing, MI, USA). At the end of the experiment, the total leaf area was measured using a Li-Cor Li-3100C leaf scanner (Li-cor Inc, Lincoln, NE, USA) at TFREC-WSU Wenatchee laboratory.

109

Field experiment

In 2016, a completely randomized experiment consisting of ‘Honeycrisp’ grafted on the four different rootstocks; G41, G890, M9, and B9 was planted at WSU-TFREC Sunrise Orchard at a spacing of 0.9 m between trees and 3.6 m between rows on a shallow sandy loam soil and trained as a slender spindle system. In 2017 and 2018, trees were drip irrigated daily using emitters spaced

30 cm apart that applied 3.78 L h-1 water for two hours (four sets of 30 min each) daily which exceeded evapotranspiration rates and were fertilized using standard commercial practices. The experiment was arranged in a completely randomized design with two factors; rootstock (G41,

G890, B9, and M9) and irrigation treatments (control and drought). Each plot had five trees with the three trees on the inside used for measurements. The treatments consisted of a water limited treatment where soil moisture was held at approximately 50% of field capacity and a well-watered control where soil moisture was kept at or near 100% FC (Fig. 2). Field capacity was determined early in the season by collecting soil from the plot and then thoroughly saturated with water while measuring the volumetric soil water content every 30 minutes using a capacitance Em50G 2.24 sensor (Decagon Devices, Pullman, WA, USA), connected to the DataTrack 3.15 program

(Decagon Devices, Pullman, WA, USA). After letting the water gravimetrically drain for one day, maximum soil water content to represent field capacity was determined. In the field, three capacitance sensors per row (12 in total) were installed at the beginning of the season (April) to monitor volumetric water content (m3/m3) every 30 min using Em50G 2.24 sensors (Decagon

Devices, Pullman, WA, USA) with DataTrack 3.15 program (Decagon Devices, Pullman, WA).

Irrigation treatments were initiated after petal fall and lasted for 90 days. For trees exposed to water limitations, once soil moisture had been depleted to 50% of field capacity, water was applied to

110 allow soil moisture to replenish to above 60% of field capacity (approximately one full day per week). Soil water content in the pots of the drought treatment in the greenhouse was effectively reduced by 40% approximately compared to the control treatment (Fig. 1), and for the field experiment, soil water content in the drought treatment was effectively reduced by approximately

50% compared to well-watered trees (Fig. 2).

Physiological measurements

Similar to the greenhouse experiment, physiological measurements were performed biweekly during the growing season (~90 days). One tree was selected from each replicate for uniformity of vigor and health and physiological parameters were measured. Leaf gas exchange, mid-day stem water potential and quantum yields photosystem II (ΦII) were measured as described above using two leaves per tree instead. Shoot growth was monitored bi-weekly on three extension shoots per tree on the three middle trees per replicate. At the end of the growing season, before leaf fall, leaf area was estimated in 2017 using a CI-203 Handheld laser leaf area meter (CID Bio-Science,

Camas, WA, USA) by measuring and averaged 30 leaves and then multiplying it by the total number of leaves per tree for each replicate. In 2018, trees were destructively sampled before leaf fall, and the total leaf area was measured using Li-3100C leaf scanner (Li-cor Inc, Lincoln, NE,

USA).

Carbon Isotope Sampling

At the end of each experiment, samples were collected for roots, stems, and leaves. Roots were carefully washed using tap water to remove potting media and soil residues. Root, stem, and leaf samples were then dried to a stable weight in a chamber with constant air flow at 25 °C for 30

111 days. Once dry, well-mixed subsamples of each plant tissue was ground for carbon isotope analysis. Leaf samples were ground into a fine powder using a VWR high throughput homogenizer

(VWR, Radnor, PA, USA). For stems and roots, samples were initially ground to 20-micron size using a Wiley Mini mill (Thomas Scientific LLC., Swedesboro, NJ, USA) and then ground to sub- micron size using a VWR high throughput homogenizer (VWR, Radnor, PA, USA). Then isotope capsules were prepared using 3 µg for roots and leaves and 10 µg for stem tissue were weighed into tin capsules (Costech Analytical Technologies, Inc., Valencia, CA, USA) using a high precision analytical balance (XSE105 DualRange, Mettler Toledo, Greifensee, Switzerland).

Samples were then sent for δ13C analysis using a PDZ Europa ANCA-GSL elemental analyzer interfaced to a PDZ Europa 20-20 isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK) at the UC Davis Stable Isotope Facility in Davis, CA.

Environmental data such as air temperature, relative humidity, wind speed, total precipitation, and solar radiation were obtained through the AgWeatherNet weather stations located at the WSU-

Sunrise Orchard and WSU-TFREC (Table 1). Data were analyzed by performing a multivariate analysis of variance (MANOVA) given that data were correlated across time due to the same trees were evaluated during the growing season. Additionally, a Tukey’s means separation test with a confidence of 95% (SAS, ver. 9.4 PROC GLM).

Results

Both rootstock and water limitations affected vegetative growth and overall leaf area in the greenhouse and field. In the greenhouse, shoot growth was higher for M9 than B9 but there was no treatment effect in any of the rootstocks used (Fig. 3). However, there were differences in how rootstocks responded to water limitations between the greenhouse and field experiments. For the

112 field experiment, drought significantly reduced shoot growth for all rootstock genotypes.

Rootstock genotype also affected seasonal shoot growth. G890 and G41 had significantly higher shoot growth then M9 and B9 (Fig. 4). Seasonal shoot extension between treatments did not separate until August when shoot growth slowed for trees that were water limited. When fully watered, G890 had the highest shoot elongation with a total shoot length of more than 70 cm at the end of the experiment. B9 had the lowest shoot elongation with an average shoot length of less than 40 cm (Fig. 4). Total leaf area was lower when trees were water limited for all rootstocks in the greenhouse where M9 had the greatest leaf area and B9 had lowest (Fig. 5A). Under field conditions, water limitations did not significantly affect leaf area for either year in the field.

Nevertheless, G890 had consistently greater leaf area then G41, M9, and B9 in both years (Fig.

5B). Stem water potential was lower for trees exposed to water limitations for all rootstocks for both greenhouse and field experiments (Fig. 6). In the greenhouse, G890 showed greater differences between the fully watered control and trees where water was limited than other rootstock genotypes. In the field, water limitations led to a convergence of stem water potential where there were differences among rootstocks that were fully watered but not when water was limited in 2018.

Elevated temperatures and VPD under field conditions induced a different response among rootstocks under water limitations compared to greenhouse grown trees (average greenhouse VPD

= 1 kPa) (Table 1). Interestingly, rootstocks responded differently between the two different experiments. For net photosynthesis, stomatal conductance and transpiration rate in the greenhouse, differences between irrigation treatments were significant (Fig. 7) but the differences between trees that were water limited or well-watered were greater in the field (Fig. 8). In the greenhouse, stomatal conductance and transpiration were greater for B9 compared to M9 (Fig. 7;

113 P<0.05) but net CO2 exchange rates were not different among rootstocks. In the field, net CO2 exchange rates for drought-stressed trees were lower than trees that were well-watered only in

2018 and B9 had lower net CO2 exchange rates than G890, and G41. G890 had the highest net

CO2 exchange rates both years (Fig. 7). Stomatal conductance was approximately 30-40% lower when water limited in the greenhouse and were much more variable in the field. In 2017, stomatal conductance was lower when water limited compared to well-water control trees for all rootstocks and B9 had lower stomatal conductance than G890 and G41. However, in 2018, rootstock G890 had significantly lower stomatal conductance when trees were under drought-stress but B9 showed no differences between trees that were water limited and well-watered trees. Patterns in mean transpiration rates were similar to stomatal conductance for both the greenhouse and the field (Fig.

7 and 8). In the field experiment, in 2017, all rootstock genotypes had a treatment effect when under drought-stress and B9 had lower transpiration rates than the other rootstocks tested.

Similarly to stomatal conductance, G890 had lower transpiration rates when water limited but transpirations rates for B9 and G41 were not different between treatments in 2018 (Fig. 8).

Quantum yield of photosystem II (ΦII) was lower for trees that were water limited in the greenhouse and in 2018 in the field but not for 2017 (Fig. 9). Rootstock genotype did not affect

ΦII for either experiment. On the other hand, carbon isotopic composition (δ13C) of leaves, roots and stems was more positive when trees were water limited in the greenhouse experiment (Fig.

10). For trees that were well watered, there were no significant differences between δ13C of stems and leaves. However, root δ13C was more positive for well-watered trees in the greenhouse and the field. These effects were the same for all rootstocks tested in this experiment. For the field experiment, leaf δ13C was unaffected by water limitations. However, stem and root δ13C were greater for trees that were water limited compared to the control in 2017 and 2018. For 2017, leaf

114 δ13C was less than stem and root δ13C when water limited. However, in 2018, root δ13C was less than leaf and stem δ13C. Leaf δ13C was greater for B9 than G890, G41, and M9 in 2017 and in

2018 root and stem δ13C were lower for G890 than B9, G41 and M9.

Discussion

Drought resistance refers to the ability of one genotype to perform better than others during drought stress (Basset, 2013). Many studies only examine leaf-level responses to drought and root traits are often overlooked (Bauerle et al., 2008). For composite plants such as apple, these traits can be important in affecting above ground plant growth and development (Atkinson et al., 1999).

In this study, leaf gas exchange was lower in the scion under water limitations for all rootstock genotypes. Furthermore, each rootstock genotype responded differently under greenhouse conditions compared to the field (Fig. 7 and 8). Stomatal closure is one of the earliest plant responses to drought stress in relation to plant water potential (Grant, 2012). Here, under water limitations, lower stem water potential was followed by a corresponding decrease in stomatal conductance (Fig. 7 and 8). These results follow similar patterns to those reported by Solari, 2006 and Liu, 2012 who stated that water limitations reduced gas exchange differently among rootstocks suggesting that rootstocks can influence net CO2 exchange rate, stomatal conductance, and transpiration rate.

In the field, rootstock vigor appeared to contribute to response to water limitations (Atkinson,

2000). G890, the most vigorous rootstock, had the greatest stomatal conductance when under well- watered conditions but also showed the greatest decrease under water limitations. Interestingly,

B9 had the highest stomatal conductance in the greenhouse when water limited (Fig. 7) but the lowest in the field for both years (Fig. 8). Reductions in net CO2 exchange rates when water limited

115 can be caused by a reduction in stomatal conductance and/or lead to the inhibition of rubisco (Zhou et al., 2014). Trees grown under field conditions experience increased temperatures and light intensities that can magnify differences in responses to water limitations. For trees under greenhouse conditions, net CO2 exchange and stomatal conductance were both reduced by water limitations. On the other hand, for trees under field conditions, net CO2 exchange was lower when trees were water limited for all rootstock genotypes. However, stomatal conductance was not as linked to net CO2 exchange rates in the field. Stomatal conductance was only lower for G890 when water limited while there were no differences between treatment for B9 and G41 (Fig. 8). Different responses of rootstock genotypes to drought have been previously reported where dwarfing rootstocks, such as B9, had better short-term responses to drought by having higher concentrations of endogenous ABA (Lordan et al., 2017) possibly allowing for tighter regulation of stomatal conductance. Alternatively, more vigorous rootstocks with bigger root systems may be more plastic and adaptable to long-term responses (Tworkoski et al., 2016). These differences between potted and field trees could be due to constraints on root systems that may have been less developed in a potted system and, unlike the field, would not have been able to scavenge for water at deeper depths when water limited.

The inhibition of the photosynthetic apparatus can be quantified by measuring the efficiency of

Photosystem II photochemistry which is an indicator of overall photosynthesis (Maxwell and

Johnson, 2000; Malnoë, 2018). Zhou, 2013 suggested that reductions in apparent carboxylation could occur from reductions in net CO2 exchange that are not accompanied by changes in stomatal conductance. Quantum yields of Photosystem II (ΦII) reported in this study correspond with those reported by Massacci and Jones, 1990 that reported lower ΦII values as non-photochemically quenched energy increased. This was observed in this study, where trees that were water limited

116 in the greenhouse were also exposed to indirect sunlight irradiance (Fig. 9A). Reductions in ΦII could also be explained by a reduction of intercellular CO2 following closure of stomata inducing downregulation of the photosynthetic apparatus (Chaves et al., 2002).

When plants are water limited, a common response is a reduction in net CO2 exchange, stomatal conductance, and transpiration. These effects should also correspond with an increase on δ13C

(Farquhar and Sharkey, 1982). Farquhar, 1989 stated that for long-term observations under both controlled environments and field conditions, plants that are water limited should have higher leaf

δ13C than well-watered trees. The δ13C composition of plant samples integrates the carbon absorption of the different organs in the growth season, which can quantify longer-term effects of water stress that may not be captured by time point measurements such as leaf gas exchange (Cui et al., 2009). In this study, for trees grown in a greenhouse environment all trees part (roots, stem and leaves) had higher δ13C when under water limitations. However, for trees under field conditions, leaves did not show differences between treatments while stem and roots did. There were also differences among rootstock genotypes. B9 has higher leaf δ13C than G890, G41 and

M9 (Fig. 10). Similarly, Chaves, 2002 reported higher δ13C in seed and stems at the end of the growing season for two lupin species under drought but no differences in leaves and roots compared to the well-watered control plant. The presence of differences in δ13C signals among plant organs may depend on the timing of carbon movement to that developing organ. Organ development that falls outside the timing of water limitations likely would not produce differences in δ13C composition between treatments (Cernusak et al., 2009). However, carbon sinks that acquire carbon during periods of water limitation would likely show greater differences in δ13C.

There were strong differences between greenhouse and field experiments that showcase differential response to environments among rootstock genotypes. Adaptive changes in plants

117 growing in different environments have been clearly demonstrated in several species (Ackerly et al., 2000). Woody plants can usually withstand periods of drought through acclimatization which involves changes in plant structure and function. Increase in the root to leaf biomass ratio, osmotic adjustments and stomatal closure can lead to an increased ability to avoid or tolerate dehydration

(Osorio et al., 1998). Similar responses were observed here where leaf area and stomatal conductance were lower for trees that were water limited (Fig. 5, 7 and 8). Lawlor and Tezara,

2009 stated that slowly imposing water stress results in an adaptation of the trees by limiting growth and total leaf area which can affect whole plant productivity even when leaf-level net CO2 exchange rates are not different. As previously mentioned by Grant, 2012 a reduction in net CO2 exchange rates can lead to a reduction in vegetative growth. This was observed here where trees under drought stress showed a smaller shoot growth especially at the end of the season than those of well-water control in conjunction with lower photosynthesis rate (Fig. 4 and 8). Furthermore, rootstocks with naturally lower vigor such as B9 showed lower net CO2 exchange rates compared to more vigorous rootstocks like G890. Osorio, 1998 concluded that drought limited biomass allocation to growth in Eucalyptus globulus and, therefore, limits plant size resulting from stomatal closure and reduced leaf area. While not measured here, short-term responses to drought can include reductions on stomatal conductance due to chemical compounds synthesized in the drying roots, i.e. ABA, which can lead to reductions in internal CO2 concentrations and a reduction in light use efficiency that can upregulate long-term adaptive pathways that may affect the photosynthetic apparatus (Chaves et al., 2002) then resulting in a reduction of vegetative growth.

Here, when trees were grown in a greenhouse, a steady reduction of photosynthesis, stomatal conductance and transpiration resulted in a consistent increase of δ13C in all plant tissues and a reduction in the photochemical quenching (ΦII) for all rootstock genotypes. Under more controlled

118 conditions in the greenhouse, rootstock effect was only significant for leaf area and stomatal conductance (Fig. 5 and 7). Conversely, under field conditions, there was a rootstock effect for almost all the variables except for ΦII. Under field conditions, drought stress can also be associated with elevated temperatures and high light intensity stresses occurring simultaneously (Chaves et al., 2002). However, in a greenhouse environment, these interactions can be minimized. Tree response to water limitations under field conditions can involve adjustments to co-occurring stresses descried above (Chaves et al., 2002; Zandalinas et al., 2018). The maintenance of crop yield and quality through improved tolerance to environmental stresses such as drought, high light intensity, and high temperature, as well as biotic stresses associated with climate change, remains a crucial challenge to maximize future crop productivity (Hüner et al., 2016). Apple, like other perennial tree fruit, require a consistent water supply, mature slowly, and rely on the production of high quality, blemish-free produce are more susceptible to drought stress compared to annual crops (Grant, 2012; Sofo et al., 2012). Therefore, a better understanding of the capacity to adapt to forecasted warming condition is required.

Conclusion

In this study, G890 was the most sensitive to water limitations as was previously reported by

Valverdi et al (2019). Here, we emphasize the importance of field studies for screening phenotypic responses of rootstock genotypes to abiotic stress. Although physiological parameters such as net gas exchange and shoot growth were greater under well-watered conditions, these variables were affected more greatly for G890 compared to rootstocks with less vigor such as B9. This may demonstrate greater plasticity to drought for G890 than other rootstock genotypes. On the other hand, B9 was more efficient on maintaining tree size and stomatal conductance under water

119 limitations and had the most positive δ13C composition and lowest stem water potential when water limited. These results suggest a genotypic distinction between rootstocks in their response to water limitations. Caution must be taken when phenotypic and physiological responses to drought are assessed in controlled environment conditions. Here we showed how field condition experiments can reveal the genotypic differences among rootstocks that appear to showcase different strategies to adapt or acclimate to lower soil moisture. Future research is required to identify the mechanisms by which different rootstocks genotypes respond to water limitations under field conditions.

120 References Ackerly, D.D., Duddley, S.A., Sultan, S.E., Schmitt, J., Coleman, J.S., Linder, C.R., Sandquist, D.R., Geber, M.A., Evans, A.S., Dawson, T.E., Lechowicz, M.J., 2000. The Evolution of Plant Ecophysiological Traits: Recent Advances and Future Directions. Bioscience 50, 979– 995.

Atkinson, C.J., Policarpo, M., Webster, a. D., Kingswell, G., 2000. Drought tolerance of clonal Malus determined from measurements of stomatal conductance and leaf water potential. Tree Physiol. 20, 557–563.

Atkinson, C.J., Policarpo, M., Webster, A.D., Kuden, A.M., 1999. Drought tolerance of apple rootstocks: Production and partitioning of dry matter. Plant Soil 206, 223–235.

Basset, C.L., 2013. Water use and drought response in cultivated and wild apples. In: Kourosh, V. (Ed.), Abiotic Stress - Plant Responses and Applications in Agriculture. InTech, pp. 249–275.

Bauerle, T.L., Smart, D.R., Bauerle, W.L., Stockert, C., Eissenstat, D.M., 2008. Root foraging in response to heterogeneous soil moisture in two grapevines that differ in potential growth rate. New Phytol. 179, 857–866.

Chaves, M.M., Flexas, J., Pinheiro, C., 2009. Photosynthesis under drought and salt stress: Regulation mechanisms from whole plant to cell. Ann. Bot. 103, 551–560.

Chaves, M.M., Miguel Costa, J., Madeira Saibo, N.J., 2011. Recent Advances in Photosynthesis Under Drought and Salinity, 1st ed, Advances in Botanical Research. Elsevier Ltd.

Chaves, M.M., Pereira, J.S., Maroco, J., Rodrigues, M.L., Ricardo, C.P.P., Osório, M.L., Carvalho, I., Faria, T., Pinheiro, C., 2002. How plants cope with water stress in the field. Photosynthesis and growth. Ann. Bot. 89, 907–916.

Collins, M., Knutti, R., Arblaster, J., Dufresne, J.-L., Fichefet, T., Friedlingstein, P., Gao, X., Gutowski, W.J., Johns, T., Krinner, G., Shongwe, M., Tebaldi, C., Weaver, A.J., Wehner, M., 2013. Long-term climate change: Projections, commitments and irraversibility. In: Stocker, T.F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V., Midgley, P.M. (Eds.), Climate Change 2013: The Physical Science Basis. Contribution of Working Group 1 to the Fifth Assesment Report or the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, NY, pp. 1029–1136.

Cui, N.B., Du, T.S., Kang, S.Z., Li, F.S., Hu, X.T., Wang, M.X., Li, Z.J., 2009. Relationship between stable carbon isotope discrimination and water use efficiency under regulated deficit irrigation of pear-jujube tree. Agric. Water Manag. 96, 1615–1622.

Davies, W.J., Kudoyarova, G., Hartung, W., 2005. Long-distance ABA Signaling and Its Relation to Other Signaling Pathways in the Detection of Soil Drying and the Mediation of the PlantÕs Response to Drought. J. Plant Growth Regul. 24, 285–295.

121 Elias, P., 1995. Stomata density and size of apple trees growing in irrigated and non irrigated conditions. Biol. Bratislava 50, 115–118.

Farquhar, G.D., Ehleringer, J.R., Hubick, K.T., 1989. Discrimination and Photosynthesis. Annu. Rev. Plant Biol. 40, 503–537.

Farquhar, G.D., Sharkey, T.D., 1982. Stomatal Conductance and Photosynthesis. Annu. Rev. Plant Physiol. 33, 317–345.

Fazio, G., Kviklys, D., Grusak, M.A., Robinson, T., 2013. Phenotypic Diversity and QTL Mapping of Absorption and Translocation of Nutrients by Apple Rootstocks. Asp. Appl. Biol. 119, 37– 50.

Fernandez, R.T., Perry, R.L., Flore, J.A., 1997. Drought response of young apple trees on three rootstocks: Growth and development. J. Am. Soc. Hortic. Sci. 122, 14–19.

Glenn, D.M., 2014. An analysis of ash and isotopic carbon discrimination (δ13C) methods to evaluate water use efficiency in apple. Sci. Hortic. (Amsterdam). 171, 32–36.

Grant, O.M., 2012. Abiotic Stress Responses in Plants.

Hüner, N.P.A., Dahal, K., Bode, R., Kurepin, L. V., Ivanov, A.G., 2016. Photosynthetic acclimation, vernalization, crop productivity and ‘the grand design of photosynthesis.’ J. Plant Physiol. 203, 29–43.

Jackson, J.E., 2003. Biology of apples and pears. Cambridge University Press, Cambridge, NY.

Jensen, P.J., Halbrendt, N., Fazio, G., Makalowska, I., Altman, N., Praul, C., Maximova, S.N., Ngugi, H.K., Crassweller, R.M., Travis, J.W., McNellis, T.W., 2012. Rootstock-regulated gene expression patterns associated with fire blight resistance in apple. BMC Genomics 13.

Jensen, P.J., Makalowska, I., Altman, N., Fazio, G., Praul, C., Maximova, S.N., Crassweller, R.M., Travis, J.W., McNellis, T.W., 2009. Rootstock-regulated gene expression patterns in apple tree scions. Tree Genet. Genomes 6, 57–72.

Lawlor, D.W., Tezara, W., 2009. Causes of decreased photosynthetic rate and metabolic capacity in water-deficient leaf cells: A critical evaluation of mechanisms and integration of processes.

122 Ann. Bot. 103, 561–579.

Liu, B., Li, M., Cheng, L., Liang, D., Zou, Y., Ma, F., 2012. Influence of rootstock on antioxidant system in leaves and roots of young apple trees in response to drought stress. Plant Growth Regul. 67, 247–256.

Lordan, J., Fazio, G., Francescatto, P., Robinson, T., 2017. Effects of apple (Malus × domestica) rootstocks on scion performance and hormone concentration. Sci. Hortic. (Amsterdam). 225, 96–105.

Malnoë, A., 2018. Photoinhibition or photoprotection of photosynthesis? Update on the (newly termed) sustained quenching component qH. Environ. Exp. Bot. 154, 123–133.

Marini, R.P., Fazio, G., 2018. Apple rootstocks: History, physiology, management, and breeding. Hortic. Rev. (Am. Soc. Hortic. Sci). 45, 197–312.

Massacci, A., Jones, H.G., 1990. Use of simultaneous analysis of gas-exchange and chlorophyll fluorescence quenching for analysing the effects of water stress on photosynthesis in apple leaves. Trees 4, 1–8.

Maxwell, K., Johnson, G.N., 2000. Growth and chlorophyll a ﬂuorescence in Erythrina crista-galli L.pdf. J. Exp. Bot. 51, 659–668.

Osorio, J., Osorio, M.L., Chaves, M.M., Pereira, J.S., 1998. Water deficits are more important in delaying growth than in changing patterns of carbon allocation in Eucalyptus globulus. Tree Physiol. 18, 363–373.

Peck, G.M., Andrews, P.K., Reganold, J.P., Fellman, J.K., 2006. Apple orchard productivity and fruit quality under organic, conventional, and integrated management. HortScience 41, 176– 182.

Public utility district, 2018. Water quality 2018 annual report. Wenatchee, Washington.

Shackel, K.A., Lampinen, B., Southwick, S., Olson, W., Sibbett, S., Krueger, W., Yeager, J., 2000. Deficit Irrigation in Prunes : Maintaining Productivity with Less Water. HortScience 35, 1063–1066.

Solari, L.I., Johnson, S., Dejong, T.M., 2006. Relationship of water status to vegetative growth and leaf gas exchange of peach (Prunus persica) trees on different rootstocks. Tree Physiol. 26, 1333–1341.

123 Tworkoski, T., Fazio, G., Glenn, D.M., 2016. Apple rootstock resistance to drought. Sci. Hortic. (Amsterdam). 204, 70–78.

Valverdi, N.A., Cheng, L., Kalcsits, L., 2019. Apple Scion and Rootstock Contribute to Nutrient Uptake and Partitioning under Different Belowground Environments. Agronomy 9, 415.

Wingler, A., Quick, W.P., Bungard, R.A., Bailey, K.J., Lea, P.J., Leegood, R.C., 1999. The role of photorespiration during drought stress: An analysis utilizing barley mutants with reduced activities of photorespiratory enzymes. Plant, Cell Environ. 22, 361–373.

Wunsche, J.N., Palmer, J.W., Greer, D.H., 2000. Effects of crop load on fruiting and gas-exchange characteristics of ’Braeburn’/M.26 apple trees at full canopy. J. Am. Soc. Hortic. Sci. 125, 93–99.

Zandalinas, S.I., Mittler, R., Balfagón, D., Arbona, V., Gómez-Cadenas, A., 2018. Plant adaptations to the combination of drought and high temperatures. Physiol. Plant. 162, 2–12.

Zhou, S., Duursma, R.A., Medlyn, B.E., Kelly, J.W.G., Prentice, I.C., 2013. How should we model plant responses to drought? An analysis of stomatal and non-stomatal responses to water stress. Agric. For. Meteorol. 182–183, 204–214.

Zhou, S., Medlyn, B., Sabaté, S., Sperlich, D., Colin Prentice, I., 2014. Short-term water stress impacts on stomatal, mesophyll and biochemical limitations to photosynthesis differ consistently among tree species from contrasting climates. Tree Physiol. 34, 1035–1046.

Zhou, Y.Q., Qin, S.J., Ma, X.X., Zhang, J.E., Zhou, P., Sun, M., Wang, B.S., Zhou, H.F., Lyu, D.G., 2015. Effect of interstocks on the photosynthetic characteristics and carbon distribution of young apple trees during the vigorous growth period of shoots. Eur. J. Hortic. Sci. 80, 296– 305.

124 Table 4. 1. Average environmental data for April to October in 2017 and 2018 at Wenatchee, WA.

Vapor Air Relative Wind Soil Solar Pressure Temperature Humidity Speed Temperature Radiation Deficit (°C) (%) (m/s) (°C) (MJ/m2) (kPa) 2017 April 10.46 54.07 1.89 11.28 16.89 0.58 May 16.30 51.03 1.81 16.96 22.56 0.89 June 20.55 40.94 2.20 22.22 24.53 1.42 July 26.33 29.50 2.40 27.77 27.24 2.38 August 25.02 36.06 1.82 27.03 20.59 2.02 September 17.83 50.74 1.23 22.14 13.77 0.98 October 8.96 63.39 1.25 13.77 10.11 0.42 2018 April 11.05 53.58 2.33 11.94 16.65 0.61 May 19.88 43.64 3.16 20.03 22.49 1.32 June 19.93 41.02 3.01 23.50 24.58 1.38 July 26.01 31.54 2.89 28.86 26.37 2.30 August 23.87 38.13 2.46 27.77 18.80 1.79 September 17.60 44.53 2.12 22.84 15.45 1.11 October 9.70 67.31 1.28 14.19 9.53 0.39

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Figure 4. 1. Mean volumetric soil water content (N=3) for well-watered control and drought water- stressed irrigation treatment of ‘Honeycrisp’ one-year-old potted apple trees.

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Figure 4. 2. Total precipitation and volumetric soil water content during May to August at

Washington State University experimental orchard for 2017 and 2018. = Irrigation treatments starting point.

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Figure 4. 3. Terminal shoot extension for ‘Honeycrisp’ potted trees grafted on Bud-9 (B9), G41,

(α=0.05).

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Figure 4. 4. Terminal shoot extension of ‘Honeycrisp’ apple trees grafted on Bud-9 (B9), G41,

Different letters indicated significant differences among means determined using a Tukey’s mean separation test (α=0.05).

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Figure 4. 5. Mean leaf area (cm2) of (A) one-year-old potted ‘Honeycrisp’ apple trees grafted on

Bud-9 (B9), G41, G890, and M9-T337 (M9) rootstocks grown in a greenhouse and (B) 3-year-old

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Figure 4. 6. Mid-day stem water potential of (A) one-year-old potted ‘Honeycrisp’ apple trees grafted on Bud-9 (B9), G41, G890, and M9-T337 for 2017 (M9) rootstocks in greenhouse conditions and (B) 3-year-old ‘Honeycrisp’ apple trees grafted on Bud-9 (B9), G41, G890, and

M9-T337 (M9) rootstocks in field conditions under drought compared to a well-watered control.

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Tukey’s mean separation test (α=0.05).

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Figure 4. 10. Leaf (dark grey), root (light grey) and stem (grey) δ13C for ‘Honeycrisp’ apple trees crafted on Bud-9 (B9), G41, G890 and M9-T337 (M9). (A) one-year-old potted trees grown in a greenhouse in 2017, and (B) 3-year-old ‘Honeycrisp’ apple trees grafted on Bud-9 (B9), G41,

135

CHAPTER FIVE: ROOTSTOCK AND SCION GENOTYPES AFFECT HYDRAULICS

AND ANATOMICAL FEATURES OF APPLE TREES UNDER WATER STRESS

Abstract

The movement of water from the soil through the plant is driven by a difference in water potential between the atmosphere and the soil. Grafted plants have been previously reported to increase hydraulic resistance (inverse of conductance) of the stem. Although graft union in trees was previously studied, there are a few studies that evaluate this healing stage when trees are under drought. This is why the objective of this study was to identify differences in the hydraulic kinetics and anatomical characteristics of four different rootstock genotypes; Bud-9 (B9), G41, G890, and

M.9-337 (M9) and their combinations with two cultivars, ‘Gala’ and ‘Honeycrisp’ when under water stress. For this, hydraulic conductance of stems and roots, hydraulic resistance of leaf blades and grafts union, and stomata density and size were measured. Stem hydraulic conductance was only reduced by water stress when trees were un-grafted. Root hydraulic conductance was not affected by the water stress treatment for grafted trees nor un-grafted trees. Leaf-blades resistance was higher for water-stressed trees only for grafted trees, while graft union resistance had no treatment effect. For stomata density, for all trees was increased by the water stress treatment while size was reduced together with total leaf area. We could see that as more resistances are added to the hydraulic system of plants (graft, scion vascular connection, leaves), the hydraulic conductivity of each organ is affected in different ways where the most sensitive is the stem hydraulic conductivity while not the root hydraulic conductivity. Graft union was not a significant component of the grafted vascular system in this study and water stress did not affect the graft union hydraulic resistance. This shows that anatomical adaptations like increasing stomata density and maintaining hydraulic conductance can be survival strategies to overcome adverse conditions.

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Key Words: stomata density, drought, Malux x domestica, hydraulic resistance, hydraulic conductance

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Introduction

The capacity to move water from the soil through the leaves is a critical factor affecting all plant processes. This movement is driven by a difference in water potential between the atmosphere and the soil (Taiz and Zeiger, 2010). The soil-plant-atmosphere continuum has been extensively studied (McDowell, Brodribb and Nardini, 2019). Active and passive water transport through the plant is a complex evolved system prepared to adapt to different soil conditions such as salinity, metals toxicity, heat, and drought (Steudle, 2011; Lobet et al., 2014). Rapid shifts in climate are placing pressure on these adapted systems to maintain plant growth (Collins et al., 2013).

Furthermore, there is an increased need to develop agricultural plants with high productivity under increasingly stressful abiotic conditions. These changes are increasing the pressure on the plasticity and adaptation capacity of plant to tolerate extreme environmental events (Steudle, 2000;

Zandalinas et al., 2018).

Unlike many agricultural crop species, tree fruits are composite plants formed from a combination of a genetically distinct scion with a genetically different rootstock. Rootstocks have been used in tree fruit production for over 2000 years to improve productivity by the resistance to diseases, resistance to drought and other soil abiotic stresses, precocity, and dwarfing capacity (Wertheim and Webster, 2003). These two portions of the plant are used to impart selected traits on a developing tree but the interactions between them are poorly understood. However, it is recognized that these interactions are critical for regulating growth and affects plant responses to environmental conditions.

Water movement through the plant is driven by the tension created by the stem and leaves through transpiration. Water is then absorbed by the roots from the soil to meet this increase in tension.

When there is a shortage of water in the soil (drought), desiccating roots produce abscisic acid

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(ABA) and it is used as a signaling messenger to the above-ground portion of the tree to induce a reduction in the water loss by transpiration through stomata regulation (Tsuda and Tyree, 2000;

Schultz, 2003; Romero, Botía and Keller, 2017). If low soil water availability continues, reductions in growth will occur in addition to physiological changes that are better suited to functioning under water limitations (Zhou et al., 2014). If water deficits continue for too long, losses in productivity, desiccation and eventual death will occur (Steudle, 2011). The thresholds for drought and desiccation differ by plant species and cultivar (Hoekstra, Golovina and Buitink, 2001). These thresholds can be improved upon through a stronger understanding of the physiological responses of a crop to water limitations and targeted plant breeding to reduce losses in productivity or death under water limitations.

These responses may involve short, mid, and long-term changes in the plant. Short term responses may include the reduction of water loss through changes in stomatal control. Midterm responses may include changes to either above or below ground architecture and growth habits that can affect water loss, light interception, soil water access, and susceptibility to parallel abiotic stresses such as elevated soil temperature when soil moisture is lower. Long term responses may include anatomical changes such changes in stomatal density and size, suberization of roots, reduction of xylem vessels, and changes in hydraulic conductance of stems, roots, and leaves (Bauerle et al.

2011; Steudle, 2011). With composite plants, the graft union can also contribute to responses to water limitations since the union is often a discontinuous connection of xylem vessels that are critical for water transport from the roots. Grafted plants have been previously reported to increase hydraulic resistance (inverse of conductance) of the stem, but this resistance has been reported to decrease as the graft union becomes more developed and can approach zero after up to one year

(Gascó et al., 2007; Koepke and Dhingra, 2013).

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Here, the objective of this study was to identify differences in the hydraulic kinetics and anatomical characteristics of four different rootstock genotypes; Bud-9 (B9), G41, G890, and M.9-337 (M9) including their combinations with ‘Honeycrisp’ when exposed to water limitations. We hypothesized that changes in hydraulics and anatomical characteristics when water limited will differ between rootstock genotypes and scion cultivars and that these differences will be enhanced by the graft union. The results of this study will provide information on the interaction between scion and rootstocks in composite plants and how rootstocks can affect scion response to water limitations in apple.

Materials and Methods

Plant Material

Four different rootstock genotypes; B9, G41, M9, and G890 were acquired from Willow Drive

Nursery Inc (Ephrata, WA) in 2017 and 2018. Rootstock liners were planted in 10.9 L pots using a sterile growing medium of high porosity to allow for adequate drainage and aeration (Pro-mix,

Quakertown, PA, USA). A week after planting the first rootstocks, ‘Honeycrisp’ was grafted onto a second set of trees for each rootstock genotype using the cleft graft technique. Trees were drip- irrigated daily and were fertilized bi-weekly using a water-soluble commercial fertilizer

(ScottsMiracle-Gro, Marysville, OH, USA) diluted in water as recommended by the product (2 g. per 3.78 lt.) and applying 0.5 L pot-1. The fertilizer contained 24% of total nitrogen where 3.5% was ammoniacal nitrogen and 20.5% was urea nitrogen; 8% of available phosphate (P2O5); 16% of soluble potash (K2O); 0.02% of boron; 0.07% of water-soluble copper; 0.15% of chelated manganese; 0.0005% molybdenum and 0.06% of water-soluble zinc. The nutrients derived from ammonium sulfate, potassium phosphate, potassium chloride, urea, urea phosphate, boric acid,

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copper sulfate, iron EDTA, manganese EDTA, sodium molybdate, and zinc sulfate respectively.

The trees were grown in a greenhouse with ambient light conditions and with temperature maintained between 20 and 25℃ for 60 days until the trees had reached 45 cm tall. At the start of the experiment, trees were arranged in a split-plot experimental design with two treatments; water stress and control with three replications for each rootstock and cultivar/rootstock combination.

The treatments consisted of a well-watered control with a full irrigation (100% field capacity

(FC)); a water stress (drought) treatment with irrigation at 50% of FC. Soil field capacity was determined by watering the trees to saturation and then measuring the volumetric water content using a capacitance EC-5 small soil moisture sensor (Decagon Devices, Pullman, WA) connected to a handheld data logger (Decagon Devices, Pullman, WA, USA). Once soil moisture had reached

50% of field capacity, enough water was added to increase soil moisture to above 60% of field capacity. The experiment was conducted for 60 days at which point, trees were destructively sampled.

Anatomical measurements

Stomatal density was measured in 2017 using the peel method (Wilson, Pusey and Otto, 1981;

Gitz and Baker, 2009). One fully developed leaf (between 3rd and 4th leaf) per tree was collected from each replicate at 30 and 60 days of water stress for trees with ‘Honeycrisp’ as the scion and at 60 days for the ungrafted trees. Peels were prepared within 48 hours of sampling for stomata count and measurements. To get the stomatal print, abaxial trichomes were removed with water, and the leaf patted dry. Then, superglue (Loctite® Brand, Henkel Corporation,Westlake, Ohio,

USA) was applied to the abaxial side of the leaf. Immediately after, a clean glass microscope slide was pressed into the super glue. The leaf was held in place for 15 seconds then was quickly

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removed before completely drying to avoid the epidermal of being removed. Two prints per slide were set, one taken from each side of the midrib (Fig. 1). Two images were aquired per stomatal print using a compound research microscope with a build in camera of 3.0 MP and using an objective lens of 40× using a microscope (215 series, Fisher Scientific Education, Hampton, NH,

USA). Counts and measurements were manually acquired using ImageJ-win64 software. The average stomata area (length × width in µm2) and number per mm2 was calculated for each leaf.

Hydraulic conductance measurements

Tree growth, leaf gas exchange, and stem water potential were assessed every two weeks using a

Licor-6400TX (LICOR, Lincoln, NE, USA), and a Scholander pressure chamber (PMS Instrument

Co., Albany, OR, USA). Soil moisture was measured every week using a capacitance EC-5 small soil moisture sensor (Decagon Devices, Pullman, WA) connected to a handheld data logger

(Decagon Devices, Pullman, WA). Sixty days after applying irrigation treatments, root and stem hydraulic conductance was measured using an HPFM-XP 3rd Generation (Dynamax.inc, Fresno,

CA, USA) described by Tyree et al., 1995 and following the methodology explained in Nardini and Tyree, 1999 for stems and roots. The HPFM is an apparatus designed to inject water into the base of roots or stems at an increasing or constant pressure causing water flow. Two types of measurements were made for stems. (1) Quasi-steady-state measurements in which the pressure was kept constant foe about 1 hour until all air space in the leaves were fill with water and a constant flow was observed. (2) Transient measurements in which the pressure was increased every 2-4 seconds and the corresponding changes in flow are measured. A plot between flow versus presure is used to estimate conductance (K) from the slope. Leaf and graft union resistance

(for grafted trees) was also measured using the methodology described in Trifilo et al., 2010.

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Initially, pots containing roots were submerged in water to minimize soil hydraulic resistance. For this approach, the stem was cut at around 5 cm below the graft union and kept in water. The rootstock cambium was then removed using a razor blade and the stem was then attached to the

HPFM apparatus using a rubberized airtight connection. For root hydraulic conductance, the transient measurement mode was used. Stems were first measured below the graft union (with the graft portion attached to the tree) and then cut again above the graft union and measured to estimate contributions of the graft union to stem hydraulic resistance. The quasi-steady state method followed by a transient measurement was used for the ungrafted trees and the quasi-steady state for the grafted trees. Leaf hydraulic conductance was measured after stem hydraulic conductance.

For this, all leaves were removed, and a second quasi-steady-state measurement was performed to measure leaf resistance. For transient mode, tree measurements were done for each plant part.

Stems, root, and leave area were measured to calculate the hydraulic conductance. Stem ares was calculated using a cone area formula measuring stem length and base and top diameters with a meter and an electronic caliper (Equation 1). Leaf and root area were measured using Li-Cor Li-

3100C leaf scanner (Li-cor Inc, Lincoln, NE, USA) at TFREC-WSU Wenatchee laboratory.

퐶표푛푒 푎푟푒푎 = 휋 ∗ ((푅1 ∗ 퐺) + (푅2 ∗ 퐺) + 푅12 + 푅22 (Equation 1)

Where

퐺 = √푙2 + (푅2 − 푅1)2 (Equation 2)

Where R1 is the ratio at the base of the stem and R2 the ratio at the apical side of the stem. G is the generatrix calculated acording to equation 2.

Data were analyzed by performing an analysis of variance (ANOVA), linear regressions, and a

Tukey’s means separation with a confidence of 95% (SAS, ver. 9.4 PROC GLM, and Excel,

Microsoft Office 365 ProPlus).

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Results

Midday stem water potential was significantly lower for all rootstock genotypes, whether grafted or ungrafted, when exposed to water limitation (Fig. 2 and 3). Midday stem water potential was closely correlated with soil moisture (r=0.76; Fig. 4). Although stem water potential was associated with soil moisture, the time to translate these responses to differences in tree growth took longer.

Tree growth was only affected by treatment at 60 days of water limitations compared to the fully watered control. However, rootstock genotype significantly affected the response to water supply.

Growth was lower for G890 and M9 under water limitations compared to the fully watered control, but growth was not different between treatments for B9 (Fig. 5). For ungrafted rootstock genotypes, tree growth was unaffected by water supply, but rootstock genotype affected tree growth. Interestingly, B9 was always the largest and M9 was always the smallest of all the rootstocks (Fig. 6). Water limitations reduced root and stem biomass for all rootstock genotypes but more significantly reduced leaf biomass (Fig. 7). On the other hand, when rootstocks where left un-grafted, water supply did not affect biomass for any of rootstocks used (Fig. 8).

Foliar transpiration rates were lower when trees were water limited and transpirations rates were significantly correlated with soil moisture content. The slopes of the regression lines were greater for grafted trees (~10) than ungrafted trees (~6.5) (P<0.0001). However, the coefficient of determination was lower for ungrafted tress (0.22) compared to grafted trees (0.36; Fig. 9A and

10A). Net photosynthetic rates were also significantly correlated with transpirations rates.

However, there was not significantly different between treatments, both sets of trees slope was ~2 and coefficients of determination were 0.78 and 0.63 for grafted and ungrafted trees, respectively

(Fig. 9B and 10B).

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Root hydraulic conductance (RK) and stem hydraulic conductance (SK) were not significantly different among rootstock genotypes for both grafted and ungrafted trees. However, SK was lower for M9 and G41 when water limited compared to the fully watered control (Fig. 11). For ungrafted trees, transient measurements of stem hydraulic conductance (SKT) were lower for all rootstock genotypes when water was limited than well-watered trees. On the other hand, the difference between quasi-steady state measurement of stem hydraulic conductance (SKQSS) of water limited and fully watered trees was affected by rootstock genotype. B9, G41, and G890 had lower conductance when under water stress while M9 was not affected by water limitations (Fig. 12).

For grafted trees, leaf resistance was significantly higher for all rootstock genotypes when under water stress, but graft union resistance was not significantly affected by water limitations (Fig. 13).

On the other hand, leaf resistance was higher for ungrafted trees when under water stress for all the rootstocks, but these differences were not significant (Fig. 14).

About stomata density (number) and size (area), grafted trees of ‘Honeycrisp’ on B9, G41, G890 and M9 after 30 days of water stress showed no treatment effect but had a rootstock genotype effect where with stomatal size. G41 reduced the stomata size when under water stress and other rootstock genotypes did not at 30 days of water limitations. Stomatal density was greater for B9 at

60 days of water limitations compared to the fully watered control. B9 and G890 had lower average stomatal area when under water stress (Fig. 15). Stomatal density was greater and stomatal area was smaller for ungrafted G41 and M9 when under water stress in comparison with well-watered control (Fig. 16).

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Discussion

Decreases in stem water potential under decreasing soil moisture can lead to reductions in tree growth. Water stress reducing tree growth has been extensively documented (Jones, Lakso and

Syvertsen, 1985; Atkinson et al., 1999; Romero, Botía and Keller, 2017), and rootstock and scion genotypes can affect this response (Atkinson et al., 1999; Fazio et al., 2014; Tworkoski, Fazio and

Glenn, 2016). Biomass partitioning between root, stem, and leaves had been previously reported to be affected by water stress with a stronger reduction on above-ground organs (stems and leaves) than on roots (Buwalda and Lenz, 1992; Atkinson et al., 1999; Valverdi, Cheng and Kalcsits,

2019). Here we demonstrate how drought responses in the scion lead to reductions in above-ground growth. In contrast, when rootstocks were ungrafted, reductions in growth were non-significant

(Fig. 5 and 6).

Graft union hydraulic resistance has been reported to be a significant barrier for water and nutrient transport, and is thought to contribute to the dwarfing potential for some rootstocks (Atkinson et al., 2003). Some studies have reported lower graft resistance as time from grafting increased

(Koepke and Dhingra, 2013). Similarly, Gascó et al., (2007) in a study on Olea europea observed that complete vascularization of the graft union occurred after at least three months. This time was required for the development of proper hydraulic function and young grafted trees may be more sensitive to any environmental stress. These findings support our observations where graft union resistance was not significantly different in the control but was higher when water limitations were imposed (Fig. 13).

Low stem water potential are expected to be associated with a low hydraulic conductance and low transpiration rates (Nardini and Tyree, 1999). Here, water limitations caused a reduction in stem water potential in all tress and had a significant linear relationship with soil moisture content (Fig.

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2, 3 and 4). However, decreases in hydraulic conductance was only observed for stem hydraulic conductance of ungrafted trees while root hydraulic conductance was not affected by water limitations (Fig. 11 and 12). This could be due to composite water transport through the roots reported by Steudle (2011) where it was suggested that water movement through the roots is constituted of apoplastic and symplastic transport. Under low transpiration rates, only symplastic transport is used. However, as transpiration increases, root hydraulic conductivity can increase as apoplastic transport contributes to a greater proportion of water movement. Furthermore, other physiological adjustment like root suberization or reductions in root growth can occur under water stress that can alter water transport dynamics in the root system. In this study, even when soil moisture and transpiration rate showed a significant linear relation for both ungrafted and grafted trees (Fig. 9A and 10B), root hydraulic conductance was not affected by water limitations. Naridini and Tyree (1999) suggested the normalization of root hydraulic conductance to leaf area instead of root area because of the difficulty in isolating complete root systems and this increases the error associated with this measurement, suggestion that should be taken into consideration for further studies in root hydraulic conductance.

The connection between transpiration and photosynthesis caused by fluxes of water and CO2 through the stomata is often predictable (McDowell et al., 2019). Plants invest in hydraulic capacity to maintain stomata conductance for maximum photosynthesis under favorable conditions

(Dewar et al., 2018). In this study, a clear relationship between transpiration and net photosynthesis was observed (Fig. 9B and 10B). Reductions of stem hydraulic conductance can be interpreted as an indirect measurement of the presence of embolisms or anatomical adaptations such as the reduction of xylem vessels number or size (Bauerle et al., 2011) which can negatively affect photosynthesis even after relief from water stress implying long term effects on plant health

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and productivity (Kannenberg, Novick and Phillips, 2019). Many studies have reported that leaf hydraulic conductance (the inverse of leaf resistance) declines during drought periods, and this decline is largely due to stem xylem cavitation (Nardini et al., 2003; Trifilò et al., 2003; Trifilo et al., 2010). Here we reported higher leaf resistance only for grafted trees when under water stress, while for ungrafted trees there was no effect from water limitations (Fig. 13 and 14) which also corresponded to negative effects on shoot growth and leaf area (Fig. 5-8).

Mean stomatal area and density for apple leaves can vary with environmental conditions, season, and leaf age (Jones, Lakso and Syvertsen, 1985). Here, ‘Honeycrisp’ cultivar averaged 361 stomata per mm-2 with a range of 322-408 between rootstocks for well-watered control while for trees under water stress for 60 days the average stomatal density was 504 stomata mm-2. The average stomata density for ungrafted rootstock genotypes was 365 stomata mm-2 for well-watered trees and 443 stomata mm-2 for water limited trees (Fig. 15C and 16A). The stomata densities observed here are in the same range as those reported in previous studies. In Pyrus malus, Gindel 1969 reported that irrigated trees averaged 444 stomata mm-2 and non-irrigated trees had 534 stomata mm-2. Similarly, Elias 1995 reported leaf stomata densities of 288 stomata mm-2 for irrigated and

389 stomata mm-2 for non-irrigated ‘Golden Delicious’ apple trees. The size of stomata also has implications on gas exchange across the leaf surface. Elias, 1995 did not report a significant difference in stomata dimensions between irrigation treatments. In contrast, Gindel 1969 reported differences in stomata length between treatments where stomata length was longer for irrigated trees than non-irrigated trees. Here, ‘Honeycrisp’ grafted onto B9 and G890 had larger stomata when trees were well-watered than when trees were under water-stress while stomata were no different in size between irrigation treatments for M9 and G41. In contrast, M9 and G41 had larger stomata when trees were well-watered compared to trees that were water limited while stomata

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size was not different between treatments for B9 and G890 when there was no scion grafted onto the rootstock genotypes (Fig. 15D and 16B).

Conclusion

The hydraulic vascular system can be simply described as a chain of resistances that affect water flow across the soil-plant-atmosphere continuum (Steudle, 2011). In our study, we observed increases in resistance as water moved through the plant (roots, graft union, scion, and leaves).

The hydraulic conductivity of each organ was affected in different ways where the most sensitive was the stem hydraulic conductivity and root hydraulic conductivity was the least sensitive to water limitations. Stomatal conductance and leaf gas exchange parameters are not simple to correlate with anatomical features such as stomata density and size (Elias, 1995) since these factors are dynamic and adapt to conserve hydraulic function in the plant. Roots are a more complex system from where different water uptake mechanisms and pathways can be utilized to increase or reduce hydraulic conductance in response to changes in the environment. The stem, on the other hand, fully depends on the xylem vascular system, and any adversity such as cavitation or embolism increases resistance and stimulates stress responses in leaves that limit growth and productivity in apple. Here, we present evidence that rootstock genotype can affect hydraulic conductance and leaf stomata traits that contribute to the physiological response to water limitations in apple.

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References

Atkinson, C.J., Else, M.A., Taylor, L., Dover, C.J., 2003. Root and stem hydraulic conductivity as determinants of growth potential in grafted trees of apple (Malus pumila Mill.). J. Exp. Bot. 54, 1221–1229.

Atkinson, C.J., Policarpo, M., Webster, A.D., Kuden, A.M., 1999. Drought tolerance of apple rootstocks: Production and partitioning of dry matter. Plant Soil 206, 223–235.

Bauerle, T.L., Centinari, M., Bauerle, W.L., 2011. Shifts in xylem vessel diameter and embolisms in grafted apple trees of differing rootstock growth potential in response to drought. Planta 234, 1045–1054.

Dewar, R., Mauranen, A., Mäkelä, A., Hölttä, T., Medlyn, B., Vesala, T., 2018. New insights into the covariation of stomatal, mesophyll and hydraulic conductances from optimization models incorporating nonstomatal limitations to photosynthesis. New Phytol. 217, 571–585.

Elias, P., 1995. Stomata density and size of apple trees growing in irrigated and non irrigated conditions. Biologia-Bratislava- 50, 115–115.

Gascó, A., Nardini, A., Raimondo, F., Gortan, E., Motisi, A., Lo Gullo, M.A., Salleo, S., 2007. Hydraulic kinetics of the graft union in different Olea europaea L. scion/rootstock combinations. Environ. Exp. Bot. 60, 245–250.

Gindel, I., 1969. Stomatal Number and Size as Related to Soil Moisture in Tree Xerophytes in Israel. Ecology 50, 263–267.

Gitz, D.C., Baker, J.T., 2009. Methods for creating stomatal impressions directly onto archivable slides. Agron. J. 101, 232–236.

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Hoekstra, F.A., Golovina, E.A., Buitink, J., 2001. Mechanism of plant desiccation tolerance. Trends Plant Sci. 6, 431–438.

Jones, H.G., Lakso, A.N., Syvertsen, J.P., 1985. Physiological control of water status in temperate and subtropical fruit trees. Hortic. Rev. (Am. Soc. Hortic. Sci). 7, 301–344.

Kannenberg, S.A., Novick, K.A., Phillips, R.P., 2019. Anisohydric behavior linked to persistent hydraulic damage and delayed drought recovery across seven North American tree species. New Phytol. 222, 1862–1872.

Koepke, T., Dhingra, A., 2013. Rootstock scion somatogenetic interactions in perennial composite plants. Plant Cell Rep. 32, 1321–1337.

Lobet, G., Couvreur, V., Meunier, F., Javaux, M., Draye, X., 2014. Plant water uptake in drying soils. Plant Physiol. 164, 1619–1627.

McDowell, N.G., Brodribb, T.J., Nardini, A., 2019. Hydraulics in the 21st century. New Phytol. 224, 537–542.

Nardini, A., Salleo, S., Raimondo, F., 2003. Changes in leaf hydraulic conductance correlate with leaf vein embolism in Cercis siliquastrum L. Trees - Struct. Funct. 17, 529–534.

Nardini, A., Tyree, M.T., 1999. Root and shoot hydraulic conductance of seven Quercus species. Ann. For. Sci. 56, 371–377.

Romero, P., Botía, P., Keller, M., 2017. Hydraulics and gas exchange recover more rapidly from severe drought stress in small pot-grown grapevines than in field-grown plants. J. Plant Physiol. 216, 58–73.

Schultz, H.R., 2003. Differences in hydraulic architecture account for near- isohydric and anisohydric behaviour of two eld-grown. Plant, Cell Environ. 26, 1393–1406.

Steudle, E., 2000. Water uptake by roots: Effects of water deficit. J. Exp. Bot. 51, 1531–1542.

Steudle, E., 2011. Hydraulic architecture of vascular plants. In: Lüttge, U., Beck, E., Bartels, D. (Eds.), Plant Desiccation Tolerance. Springer-Verlag, Berlin, Heidelberg, pp. 185–207.

Taiz, L., Zeiger, E., 2010. Plant Physiology, Annals of Botany.

Trifilò, P., Gascó, A., Raimondo, F., Nardini, A., Salleo, S., 2003. Kinetics of recovery of leaf hydraulic conductance and vein functionality from cavitation-induced embolism in sunflower. J. Exp. Bot. 54, 2323–2330.

Trifilo, P., Raimondo, F., Lo Gullo, M.A., Nardini, A., Salleo, S., 2010. Hydraulic connections of leaves and fruit to the parent plant in Capsicum frutescens (hot pepper) during fruit ripening. Ann. Bot. 106, 333–341.

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Tsuda, M., Tyree, M.T., 2000. Plant hydraulic conductance measured by the high pressure flow meter in crop plants. J. Exp. Bot. 51, 823–828.

Tworkoski, T., Fazio, G., Glenn, D.M., 2016. Apple rootstock resistance to drought. Sci. Hortic. (Amsterdam). 204, 70–78.

Tyree, M.T., Patino, S., Bennink, J., Alexander, J., 1995. Dynamic measurements of root hydraulic conductance using a high-pressure flowmeter in the laboratory and field. J. Exp. Bot. 46, 83– 94.

Valverdi, N.A., Cheng, L., Kalcsits, L., 2019. Apple Scion and Rootstock Contribute to Nutrient Uptake and Partitioning under Different Belowground Environments. Agronomy 9, 415.

Wertheim, S.J., Webster, A., 2003. Apple Rootstocks. In: Ferre, D.C., Warrington, I.J. (Eds.), Apples. Botany, Production and Use. CABI Publishing, Cambridge, MA.

Wilson, C.L., Pusey, P.L., Otto, B.E., 1981. Plant epidermal sections and imprints using various techniques have been used for permanent mount. Can. J. Plant Sci. 61, 781–783.

Zandalinas, S.I., Mittler, R., Balfagón, D., Arbona, V., Gómez-Cadenas, A., 2018. Plant adaptations to the combination of drought and high temperatures. Physiol. Plant. 162, 2–12.

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Figure 5. 2. Mid-day stem water potential (MPa) for ‘Honeycrisp’ apple cv. grafted on G41, G890, and M.9-T337 (M9) rootstocks genotypes under two irrigation treatments, control, and drought.

Different letters denote a significant difference between treatments. Tukey’s means separation with 95% confidence was used (α=0.05).

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Figure 5. 4. Mid-day stem water potential (MPa) and soil moisture content (m3/m3) and adjusted linear regression for grafted and un-grafted apple trees grown in a greenhouse in 2018.

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Figure 5. 5. Tree growth (cm) for ‘Honeycrisp’ apple cv. grafted on G41, G890, and M.9-T337 rootstocks genotypes under two irrigation treatments, control (solid line), and drought (dash line).

Different letters denote a significant difference between treatments. T-test two samples with 95% confidence was used (α=0.05).

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Figure 5. 7. Leaf, stem, and root area for ‘Honeycrisp’ apple cv. grafted on G41, G890, and M.9-

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Figure 5. 9. (A) The relationship between transpiration rate and volumetric soil water content and

(B) the relationship between photosynthesis rate and transpiration rate for ‘Honeycrisp’ grafted on

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Figure 5. 11. Stem (light grey bars) and root (dark grey bars) hydraulic conductance (Kg sec-1

(n=3). ns = non-significant.

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Figure 5. 12. Stem (light grey bars) and root (dark grey bars) hydraulic conductance (Kg sec-1

(n=3). ns = non-significant.

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Figure 5. 13. Leaf-blades and graft resistance for ‘Honeycrisp’ apple cv. grafted on G41, G890, and M.9-T337 (M9) rootstocks genotypes under two irrigation treatments, control, and drought.

Different letters denote a significant difference between treatments. Tukey’s means separation with 95% confidence was used (α=0.05) (n=3). ns = non-significant.

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Figure 5. 15. Stomata density (number mm-2) and area (µm2) for ‘Gala’ and ‘Honeycrisp’ apple cultivars grafted on Bud-9 (B9), G41,

G890, and M.9-T337 (M9) rootstocks genotypes under two irrigation treatments, control (dark grey bars), and drought (light grey bars)

after 30 days (A, B) and after 60 days (C, D). Different letters denote a significant difference between treatments. Tukey’s means

separation with 95% confidence was used (α=0.05) (n=3). ns = non-significant.

Tukey’s means separation with 95% confidence was used (α=0.05) (n=3).

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CHAPTER SIX: CONCLUSION AND FUTURE WORK

Introduction

My project examined the responses to abiotic stress of rootstocks with different levels of vigor and how this response impacts calcium, potassium, magnesium, and nitrogen uptake and distribution in young apple trees. By understanding how nutrient and water uptake capacity in different rootstocks is affected by either reduced water supply or elevated soil temperatures, a better understanding of how the interconnected physiological interactions between the rootstock, scion and the environment affects elemental balance was obtained.

Objectives:

1. Determine whether rootstock and/or scion genotype differ in nutrient uptake and

partitioning within plant organs under water limitations or supraoptimal (> 25 °C) soil

temperatures.

2. Investigate how different rootstock genotypes affect nutrient uptake and partitioning for

‘Honeycrisp’ apple cultivar grown in field conditions in a semi-arid climate and how they

response to water limited conditions.

3. Determine the different physiological responses of different rootstock genotypes to

drought and the combination of drought with other abiotic factors in the field.

4. Identify differences in the hydraulic kinetics and anatomical characteristics of four

different rootstock genotypes.

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Conclusion

Water limitations affected biomass partitioning of young apple trees, reducing stem and leaf biomass and, to a lesser extent, root biomass. Through strong reductions in aboveground growth, water limitations decreased mineral nutrient content in both stems and leaves, whereas elevated soil temperatures reduced calcium partitioning to leaves. Most importantly, G890, the rootstock with the most vigor, was the most responsive to water limitations, whereas more dwarfing rootstocks were affected to a lesser degree in both potted and field grown trees. Both rootstock and scion genotypic differences contributed to differences in nutrient uptake and partitioning under contrasting soil environments. ‘Gala’ apple trees produced more biomass than ‘Honeycrisp’ trees, and ‘Gala’ trees accumulated more nitrogen in roots whereas ‘Honeycrisp’ trees accumulated more nitrogen in leaves showing how scion genotype can affect nutrient’s uptake and distribution.

Furthermore, rootstock genotypes also contributed significantly to nutrient uptake and allocation although the association between vegetative vigor and nutrient uptake remains unclear.

Rootstock genotype showed an effect on nutrient acquisition and distribution in young

‘Honeycrisp’ apple trees. During early phases of orchard development, fruit size and bitter pit incidence corresponded to differences in nutrient uptake among rootstock genotypes and the importance on the partitioning and distribution of these nutrients on fruit size, quality, and disorder incidence. Interestingly, water-limited conditions increased the nutrient concentrations in reserve or structural tissues such as root and stems but did not affect leaves. Water-limited trees partitioned more nitrogen and calcium to the roots, while well-water control trees had higher nutrient partitioning to the stems. More vigorous rootstocks like G890 had lower nitrogen and higher potassium concentrations, and more dwarfing rootstocks such as B9 had lower potassium and

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higher nitrogen concentrations in leaves. Nonetheless, rootstocks did not show differences in calcium uptake capacity regardless of differences in vigor.

Here, the importance of field studies for screening phenotypic responses of rootstock genotypes to abiotic stress are emphasized. Although physiological parameters such as net gas exchange and shoot growth were greater under well-watered conditions, these variables were affected more greatly for G890 compared to rootstocks with less vigor such as B9. These contrasting responses may demonstrate greater plasticity to drought for G890 than other rootstock genotypes. These results suggest a genotypic distinction between rootstocks in their response to water limitations.

These differences appear to showcase different strategies to tolerate water limitations.

Water movement in plants primarily occurs through the xylem conduits and is driven by the transpiration stream. In our study, increasing number of factors can have an effect on plant hydraulic resistance that can affect leaf function, plant growth, and ultimately has implications for fruit growth and productivity in field environments. The most sensitive plant organ to water limitations was the stem which had low hydraulic conductivity under water limitations. Through changes in root mortality, roots may be better able to limit embolisms compared to the less structurally plastic stems. Stomatal conductance and leaf gas exchange parameters do not simply correlate with anatomical features such as stomata density and size and hydraulic conductance.

These parameters are continuously changing to adapt and maintain plant hydraulic vascular system for survival. We demonstrated that stomata traits are affected and that can have a long-term effect on plant hydraulic function.

Here, I demonstrate an improved understanding on how scions and rootstocks interact with the soil and air environment. More practically, I also provided information on how nutrient management decisions may change under poor soil conditions or water management and depending on

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rootstock-cultivar selection. Furthermore, we highlight the importance of matching rootstock traits with scion traits which can both vary physiologically that can impact growth and nutrient balance.

For rootstocks with higher vigor, irrigation is more important to control excessive growth which can be detrimental to tree productivity and possibly limit nutrient distribution to fruit. This knowledge about nutrient uptake and distribution will guide orchard management decisions to reduce pre- and post-harvest losses in the fruit industry.

Future work

Further research should focus on lifetime evaluation of rootstock differences in orchard production systems that may not be captured in shorter-term experiments.

Future research is also required to identify the specific mechanisms and pathways by which different rootstocks genotypes respond to water limitations under field conditions.

Furthermore, environmental conditions need to be accounted for in future studies that may account for differences among rootstocks in growth, nutrient acquisition, and partitioning to fruit.

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