DOI: 10.5061/dryad.v41ns1s6k
title: Data from: Acclimation of mango (Mangifera indica cv. Calypso) to canopy light gradients - scaling from leaf to canopy

description: Mango (Mangifera indica), a leading tropical fruit crop, is a prime
 candidate for intensification through modern orchard-management
 techniques, including canopy manipulation to improve light interception.
 This study investigated how leaf-level acclimation to light gradients
 within the canopy of a high-yield, dwarfing mango cultivar (Calypso™)
 could be used to examine integrated canopy-scale responses. We quantified
 foliar morphological, biochemical, and physiological traits across a range
 of canopy positions using this information to model canopy-scale
 productivity within digital-twin representations of mango under both
 conventional open-vase and espalier training canopy systems. Key findings
 demonstrated that leaves exposed to higher light exhibited increased leaf
 mass per area (LMA), nitrogen content, and photosynthetic capacity (Asat),
 but decreased chlorophyll-to-nitrogen ratios and photochemical reflectance
 indices, reflecting trade-offs between light capture and photoprotection.
 Phenolic content increased under high irradiance, indicating investment in
 photoprotective compounds at the expense of net carbon gain. Modelled
 leaf-level net primary productivity (NPP) increased with light
 availability, following a Michaelis-Menten saturating response, with
 diminishing returns under high light. Digital modelling of canopy light
 interception revealed that espalier-trellis training enhanced light
 distribution efficiency per unit leaf area but resulted in a 6.5%
 reduction in total canopy NPP due to a smaller total leaf area. However,
 when normalized by leaf area, the espalier-trellis system showed a 3.6%
 productivity advantage over conventional canopies at the time of year
 modelled. These results highlight the role of canopy structure and
 light-use efficiency play in determining orchard productivity. Integrating
 spatially explicit mechanistic models with LiDAR-derived canopy data
 offers a promising pathway for designing high-density, resource-efficient
 mango orchards. Future work should expand modelling to account for dynamic
 canopy shape throughout the growing season and evaluate the interaction of
 modified canopy structures with environmental stressors, particularly
 under climate variability.
description: Leaf samples from across a range of light environments were
 collected from an even-age cohort over 4 days at the Walkamin Research
 Station of the Queensland Department of Primary Industries, Mango Planting
 System Experiment (17° 8′ 17′′ S145° 25′ 41′′ E; elevation 599 m). The
 site has a 10-year mean daily minimum and maximum temperature of 17.2 ±
 3.3 and 28.1 ± 3.5 °C respectively with a distinct dry/cool, wet/hot
 tropical climate. After characterisation of the
 foliage-specific light environment, data on leaf-level gas exchange were
 collected in-situ using a portable photosynthesis analyser (LI-6400XT,
 LiCOR Biosciences, Lincoln NE, USA). Subsequently, leaves were detached,
 weighed for fresh weight, measured for lamina thickness, scanned  to
 determine leaf area, and analysed for chlorophyll content and light
 transmission/reflectance and by difference absorption for shortwave
 radiation (400-1000nm). Fresh leaves were then wrapped in aluminium foil
 and snap frozen in liquid nitrogen (~20 min after harvest) and held at
 −80°C until lyophilisation. Dried samples were then reweighed to determine
 dry leaf mass and ground to a fine powder before determination of basic
 biochemical characteristics including total C and N,
 δ<sup>13</sup>C, and total phenolic content.
 For detailed methods see accompanying paper
description: # Data from: Acclimation of mango (*Mangifera indica* cv. Calypso) to
 canopy light gradients - scaling from leaf to canopy
 [https://doi.org/10.5061/dryad.v41ns1s6k](https://doi.org/10.5061/dryad.v41ns1s6k) ## Description of the data and file structure Data consists of two .csv files. The first is a temporal dataset for the 11 days preceding sampling and consists of leaf-level light characterization merged with site level meteorological conditions used for modelling of  photosynthesis. The second consists of all leaf-level morphological, physiological and biochemical characterization data determined on collected mango leaves.  ### Files and variables #### File: TP\_2025\_24\_Met\_Data.csv **Description:** Meteorological data used in modelling of photosynthesis including BOM station meteorological conditions and leaf-level light levels. ##### Variables * datetime: format dd/mm/yyyy H:M * Pres: Atmospheric pressure hPa * Temp: Air Temperature (°C) * RH: Relative Humidity (%) * Windspeed: BOM windspeed (m/s) * Radiation: BOM station radiation (w/m2) * Lux: Hobo data logger Lux * Tag: Hobo data logger identity * i.Temp: Temperature recorded by Hobo datalogger (°C) * PPFD: Photosynthetic Photon Flux Density (µmol/m2/s) * time: time from Hobo datalogger (HH:MM:SS) * es: Saturated water vapour (kPa) * VPD: Vapour pressure deficit (kPa) #### File: TP\_2025\_24\_Leaf\_Data.csv **Description:** Summary data of leaf morphological, biochemical and physiological characteristics ##### Variables * Leaf: Unique leaf ID * Tag: Corresponding Hobo data logger * cultivar: Mango cultivar Calypso * PPFD_av: Average daytime PPFD (µmol/m2/s) * PPFD_sum: Total daytime PPFD (mol/m2/day) * Quantile: The 95% of daytime PPFD (µmol/m2/s) * orientation: compass orientation of sampled leaf (°) * cci_mean: Chlorophyl content index * A_sat: Light saturated photosynthesis (µmol/m2/s) * phi: Quantum yield of photosynthesis (µmol/m2/s) * theta: curvature factor of non-rectangular hyperbola * Rd: dark respiration (from light curve) (µmol/m2/s) * LCP: Light compensation point (µmol/m2/s) * LDMC: Leaf dry matter content (g/g) * LMA: Leaf mass per unit area (g/m2) * Leaf_Area: Individual leaf area (cm2) * Leaf_width: individual leaf width (cm) * vcmax: maximum RUBISCO carboxylation rate (µmol/m2/s) * jmax: maximum rate of photosynthetic electron transport (µmol/m2/s) * per_N: percent nitrogen (%) * delta_13C: stable isotope delta 13C content (‰) * TPC: Total Phenolic Content (mg GAE/g) * Starch_per: Total starch content (%) * NSC_per: Total Non-structural carbohydrate (%) * Rs_mean: Reflectance mean (400-1000nm) * As_mean: Absorbance mean (400-1000nm) * Ts_mean: Transmission mean (400-1000nm) * LUEmetricPRI: Light use efficiency metric * daily_sum_PhotosynEB: Modeled NPP over 11-day period (mmol/m2/day) * Chl_A: Chlorophyll content on an area basis (mg/m2) * Chl_M: Chlorophyll content on a mass basis (mg/g) * Chl_N_ratio: Chlorophyll to Nitrogen content (no units) * N_M: Nitrogen content on a mass basis (mg/g) * N_A: Nitrogen content on an areal basis (g/m2) * TPC_A: TPC on an area basis (mgGAE/m2) * DELTA_13C: stable isotope DELTA 13C content (‰)