In-field automatable tools for the determination of plant - PowerPoint PPT Presentation

In-field automatable tools for the determination of plant physiological responses and fruit quality parameters in ‘September Bright’ nectarines subjected to deficit irrigation strategies Alessio Scalisi Department of Agricultural, Food and Forest Sciences University of Palermo, Italy

Background >Efficiency >Sustainability -Input (ECOs) +Output Orchard management Economic Ecological Precision horticulture e.g. Water saving in orchard management Estimate correctly when and how much water to provide with irrigation based on plant water status, rather than on soil water content/status. Are there any methods for continuous determination of tree water status?

HYPOTHESES • Continuous fruit growth rates and leaf turgor pressure dynamics change under different irrigation treatments in nectarines. • Deficit irrigation applied at different fruit growth stages differently affect tree physiology OBJECTIVES • Find out the most sensitive continuous indicator of water deficit. • Test portable, non-destructive devices for in-field determination of leaf and fruit composition RESEARCH QUESTIONS • Are fruit growth and leaf turgor pressure related to each other? • Can we associate fruit growth and leaf turgor pressure to midday stem water potential ( Ψ stem )? • Are near-infrared (NIR) and fluorescence spectroscopy suitable for in-field non-destructive determination of fruit and leaf composition (e.g. sugars, dry matter and flavonoids)?

• 144 measurement trees Planting density: 2200 Materials & methods trees/ha • 4-years-old trees • Open Tatura system • ‘ September Bright ’ nectarines grafted on ‘ Elberta ’ • Drip irrigation rootstock • 6 randomized blocks

• 6 blocks 144 measurement trees Randomized block design o 12 irrigation treatments ▪ 2 Canopy orientation treatments

Full factorial design (12x2) Fruit growth stages I II IIIa IIIb 0% of ETc 0% of ETc 0% of ETc 0% of ETc Irrigation 20% of ETc 20% of ETc 20% of ETc 20% of ETc IRRIGATION TREATMENTS treatments 40% of ETc 40% of ETc 40% of ETc n.a. • Full irrigation: 100% of ETc 12 treatments CANOPY ORIENTATION TREATMENTS STAGE I STAGE II • 2 treatments (72 West & 72 East trees) West East Fruit diameter STAGE IIIa STAGE IIIb cell division pit hardening cell expansion Multiple measurements were taken over time: sugar accumulation shuck fall • chlorophyll degradation Throughout the day (daily curves) • At weekly intervals • At growth stage intervals fruit physiological maturity and harvest

Equipment used for field measurements • Fruit gauges for continuous measurements of fruit growth • Leaf patch clamp pressure (LPCP) probes for continuous measurements of leaf turgor pressure • Calibit (digital calliper) for fruit diameter measurements • DeltaT AP4 dynamic porometer for leaf stomatal conductance (g s ) • Light trolley and ceptometer for canopy light interception • LICOR 6400 for photosynthesis and leaf fluorescence • SPAD meter (SPAD index) for determination of chlorophyll content • Pressure chamber for determination of stem water potential • DA-meter (IAD index) for determination of chlorophyll degradation • Felix F-750 NIR portable device for determination of SSC and DM • Multiplex Force-A fluorometer for determination of flavonoids 7

Results (p (presented in in red) • Multiple Vs single winter buds – Influence of previous year irrigation treatments • Multiple Vs single spring fruitlets – Influence of previous year irrigation treatments • Fruit diameter • Effective area of shade (estimate of tree vigour and light interception) • Stomatal conductance (g s ) • Trunk cross-sectional area (TCSA) • Leaf photosynthetic activity (Pn) • Efficiency of PSII (ΦPSII) • Leaf relative water content (RWC) • Stem water potential ( Ψ stem ) • Leaf water potential ( Ψ leaf ) • SPAD index • Yield, fruit weight, crop load and flesh firmness • IAD index • Anthocyanin and flavonol indices in fruit and leaves • SSC and DM • Starch and sugars in wood • Leaf turgor pressure dynamics • Fruit growth dynamics

Weather and irrigation Stage I Stage II Stage IIIa Stage IIIb 100 T mean (°C) Stage I Stage II Stage IIIa RH mean (%) Stage IIIb 80 80 5 Solar radiation 14 (MJ m-2) ET 0 Rainfall 60 12 4 VPD 60 10 Rainfall (mm) 40 VPD (kPa) ET 0 (mm) 3 8 40 20 6 2 4 0 100 100 20 T mean 1 RH mean 2 Solar radiation 40 80 80 Solar radiation (MJ m-2) 0 0 0 Temperature (°C) 01/11/17 01/12/17 01/01/18 01/02/18 01/03/18 30 60 60 RH (%) Rainfall Full irrigation (100% of Rainfall + full irrigation 20 40 40 (mm) ET c , mm) (mm) Stage I 64 73 137 10 20 20 Stage II 141 78 219 Stage IIIa 35 81 116 Stage IIIb 3 83 86 0 0 0 Total 243 315 559 01/11/17 01/12/17 01/01/18 01/02/18 01/03/18

Fruit diameter 60 (irrigation HSD treatments 50 aggregated by Fruit diameter (mm) stage) 40 Control DI_I 30 DI_II DI_IIIa DI_IIIb 20 10 Beginning I I<->II II<->IIIa IIIa<->IIIb Harvest 10

35 40 Fruit diameter STAGE I STAGE II 30 38 (in-stage HSD HSD 25 36 weekly trends) 20 34 15 32 DI_0 DI_20 Fruit diameter (mm) DI_40 10 30 Control 5 28 16/10/2017 23/10/2017 30/10/2017 6/11/2017 13/11/2017 12/11/2017 22/11/2017 2/12/2017 12/12/2017 22/12/2017 1/1/2018 48 65 STAGE IIIa STAGE IIIb 46 HSD HSD 60 44 55 42 40 50 38 45 36 34 40 11 1/1/2018 8/1/2018 15/1/2018 22/1/2018 29/1/2018 5/2/2018 10/2/2018 15/2/2018 20/2/2018 25/2/2018 2/3/2018

Tree vigour and light interception (Effective area of shade, EAS) 2017/18 season 0.75 HSD 0.70 Effective area of shade (EAS) 0.65 0.60 summer pruning 0.55 Control DI_I DI_II 0.50 DI_IIIa DI_IIIb 0.45 01/10/17 01/11/17 01/12/17 01/01/18 01/02/18 01/03/18 12

Diurnal stomatal conductance (g s ) Stage II 350 2500 Control PPFD West 300 DI_0 PPFD East DI_20 gs West 2000 DI_40 250 gs East PPFD ( mol m -2 s -1 ) gs (mmol m-2 s-1) 200 1500 150 1000 100 50 500 0 0 7 8 9 10 11 12 13 14 15 16 17 18 19 7 8 9 10 11 12 13 14 15 16 17 18 19 Time of day 13

Diurnal stomatal conductance (g s ) Stage IIIa 350 2500 Control PPFD West 300 DI_0 PPFD East DI_20 gs West 2000 250 DI_40 gs East PPFD ( mol m -2 s -1 ) gs (mmol m-2 s-1) 200 1500 150 1000 100 50 500 0 0 7 8 9 10 11 12 13 14 15 16 17 18 19 7 8 9 10 11 12 13 14 15 16 17 18 19 Time of day 14

Efficiency of PSII ( Ф PSII) Control A DI_40 0.25 DI_20 ns DI_0 0.20 PSII 0.15 a B B ab ab 0.10 b ANOVA and mean separation by Tukey’s multiple comparison test Different letter represent significant differences for p<0.05 0.05 Stage I Stage IIIa Stage IIIb 18

Daily stem water potential ( Ψ stem ) curve -0.5 Stage II Stage IIIa -1.0 -1.5 stem (MPa) -2.0 -2.5 Control -3.0 DI_0 DI_20 -3.5 DI_40 Pre-dawn Pre-dawn 04 07 10 13 16 19 04 07 10 13 16 19 Time of day Error bars represent standard errors. N of replicates for treatment = 6 20

46 SPAD index (i.e. leaf chlorophyll content) 45 44 43 ANOVA: 42 • Irrigation → p<0.001 • Growth stage → p<0.001 45 41 • Canopy Orientation → p<0.001 • Irr Treat * Growth Stage → ns Control 40 44 HSD DI_I • Canopy orientation * growth DI_II SPAD index 39 DI_IIIa 43 stage → p<0.05 DI_IIIb 45 42 Error bars represent standard errors. 44 41 HSD 40 I<>II II<>IIIa IIIa<>IIIb Post-harvest 43 42 Chlorophyll likely to be converted into fruit secondary metabolites (i.e. 41 East West anthocyanins, flavonols, etc) 40 22 I<>II II<>IIIa IIIa<>IIIb Post-harvest

Fluorometer Multiplex 3 Force A on leaves → flavonol index 14 9.4 Control DI-I HSD 9.2 DI-II HSD DI-IIIa 12 DI-IIIb 9.0 Flavonol index Flavonol index 8.8 10 8.6 8.4 8 8.2 6 8.0 I<->II II<->IIIa IIIa<->IIIb Harvest West East Fruit growth stage Canopy Orientation ANOVA: • Irrigation Treatment → p<0.001 • Canopy orientation → p<0.001 • Growth stage → p<0.001 • Error bars represent standard errors. 23 • Irr Treat * Growth Stage → p<0.01

Fluorometer Multiplex 3 Force A on leaves → anthocyanin index 7 4.2 HSD 6 HSD 4.0 Anthocyanin index Anthocyanin index 5 4 3.8 3 Control DI-I DI-II 2 DI-IIIa 3.6 DI-IIIb 1 I<->II II<->IIIa IIIa<->IIIb Harvest West East Fruit growth stage Canopy Orientation ANOVA: • Irrigation Treatment → p<0.001 • Canopy orientation → p<0.001 • Growth stage → p<0.001 • Error bars represent standard errors. • Irr Treat * Growth Stage → p<0.001 24

fruit → Fla Multiplex 3 Force A fluorometer on fr lavonol index 14 Control DI_I HSD 9 DI_II Harvest 12 DI_IIIa DI_IIIb 8 Flavonol index HSD Flavonols index 10 7 8 6 6 5 W E Canopy Orientation 4 05-Feb 12-Feb 19-Feb 26-Feb 04-Mar ANOVA: • Canopy orientation → p<0.001 • Merged Irrigation Treatment (by fruit growth stage) → p<0.01 • Date → p<0.001 • Irrigation Treatment * Date → p<0.05 26