# Light-driven genotype-environment interactions in coffee: Comparing hybrids and parental lines under a controlled shade gradient

Athina Koutouleas, Linnea Cutler-Tucker, Miroslava Rakocevic, Hervé

Etienne, Anders Ræbild

► To cite this version:

Athina Koutouleas, Linnea Cutler-Tucker, Miroslava Rakocevic, Hervé Etienne, Anders Ræbild. Light-driven genotype-environment interactions in coffee: Comparing hybrids and parental lines under a controlled shade gradient. Agroforestry Systems, 2025, 99, pp.271. 10.1007/s10457-025-01376-5. hal-05430863

HAL Id: hal-05430863

https://hal.science/hal-05430863v1

Submitted on 24 Dec 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Light-driven genotype–environment interactions in coffee: comparing hybrids and parental lines under a controlled shade gradient

Athina Koutouleas · Linnea Cutler-Tucker · Miroslava Rakocevic · Hervé Etienne · Anders Ræbild

Received: 31 July 2025 / Accepted: 24 October 2025 / Published online: 4 November 2025
© The Author(s) 2025

**Abstract** Low light is a characteristic of coffee agroforestry systems, yet the optimal shade level for establishing such systems remains unclear. Furthermore, the effects of reduced light on the growth and physiology of juvenile *Coffea arabica* F1 hybrids have not been fully explored. This study examined gene-by-environment interactions among coffee hybrids and their parental lines across a controlled shade gradient in a greenhouse. The tested *C. arabica* included landrace accessions (i.e. ‘ET531’,

‘MS’, ‘T4905’, and ‘Rume Sudan’), pure lines (i.e. ‘Caturra’, ‘T5296’, ‘Marsellesa’ and ‘IAPAR59’), and F1 hybrids (i.e. ‘H1’, ‘H3’, ‘Mariana’, and ‘Starmaya’). Plants were grown under five shade treatments intercepting 0, 35, 58, 73, and 88% of ambient light (ranging from ~10 to 800 µmol m⁻² s⁻¹) to simulate agroforestry light environments. Shade significantly influenced all measured traits, including photosynthetic parameters, chlorophyll a fluorescence, aboveground biomass, specific leaf area, total leaf area, growth rate and leaf count. Notably, the line varieties ‘Caturra’ and ‘Marsellesa’ and hybrid ‘Starmaya’ demonstrated comparatively enhanced vegetative performance when grown under shade (i.e., shade level of 35 – 88%), particularly in leaf count (ca. 75% more), plant height (ca. 75% taller), and stem dry mass (50% greater). Wild Ethiopian accessions ‘ET531’ and ‘Rume Sudan’ exhibited distinctive plant height responses, reflecting their unique genetic adaptation patterns to shade, with plant height and apical dominance increasing, as a photomorphogenetic response to avoid the shade. These findings offer preliminary insights to inform the selection of *C. arabica* genotypes suitable for coffee agroforestry systems based on juvenile plants.

**Keywords** Agroforestry · Coffee · Biomass · Photosynthesis · Leaf area

A. Koutouleas (✉) · L. Cutler-Tucker · A. Ræbild
Department of Geosciences and Natural Resource
Management, University of Copenhagen, Rolighedsvej 23,
1958 Frederiksberg C, Denmark
e-mail: atk@ign.ku.dk

A. Koutouleas
Branch Bounty Institute of Tropical Agricultural Research
(BBI), Julatten, QLD 4871, Australia

M. Rakocevic
Plant Physiology Laboratory (LMGV), State University
of North Fluminense (UENF), Campos dos Goytacazes,
RJ 28013-602, Brazil

H. Etienne
CIRAD (Centre de Coopération Internationale en
Recherche Agronomique Pour de Développement), UMR
DIADE, F-34398 Montpellier, France

H. Etienne
UMR DIADE (Diversity, Adaptation, Development
of Plants), University of Montpellier, CIRAD, IRD,
F-34398 Montpellier, France
Introduction

Agroforestry systems (AFS) have been heralded as
a climate-resilient practice for coffee production
(Camargo 2010; Bertrand et al. 2011; Duangsodsri
et al. 2019; de Sousa et al. 2019; Marraccini et al.
2019; Koutouleas et al. 2022a, b, c, 2025). Given
that shaded-coffee plants in AFS benefit from a more
regulated microclimate and daytime cooling effect
compared to full sun cultivation, coffee plants grown
in these systems are expected to have better surviv-
ability for changing climates (Tscharntke et al. 2011;
Li et al. 2015). Other benefits include improved soil
fertility, reduced soil evaporation, total organic matter
and nutrient cycling (Villarreyna et al. 2020; Koutou-
leas et al. 2022a). There is, however, a reluctance to
recommend the use of shade in coffee farming due to
inconsistent reports on growth, phenology and pro-
ductivity (Clemens and Simán, 1993; DaMatta 2004;
Campanha et al. 2004a, b; Koutouleas et al. 2022a, b,
c, 2025). As a result, there is a common perception
that shade reduces coffee growth and productivity due
to lower light availability compared to full-sun condi-
tions. This perception often discourages farmers and
agricultural advisors from adopting shade-based cul-
tivation systems.

The wild gene pool of the *Coffea* species provides
a reservoir of genetic diversity from which commer-
cial varieties of *C. arabica* can be developed, with the
potential for adaptation to changing environmental
conditions and consumer demands (Pohlan & Jans-
sens 2010; Davis, 2011; Bawin 2022). Given this,
there has been a concerted effort by coffee breeding
programs to expand the genetic resources of *C. ara-
bica* available to breeders by way of F1 (“Fillial 1”)
hybrids (Bertrand et al. 2005b, c, a; Marraccini et al.
2019; Etienne et al. 2021; Labroo et al. 2021; Breitler
et al. 2022). However, these breeding efforts have
been focussed on yield as well as pest and disease
resistance and not considered AFS. Hence, there is a
lack of data concerning these new hybrids’ suitability
to AFS environments.

Studying the growth and physiology of juvenile
coffee plants provides valuable insights into future
genotype-environment interactions (Zhang et al.
2017; Rakocevic et al. 2020; Bernado et al. 2021).
Growth traits such as plant height, leaf count, and
biomass allocation can reveal genotypic variation
of different coffee cultivars before maturity (Kufa

& Burkhardt 2015; Rakocevic et al. 2023; de Souza
et al. 2025). Juvenile performance can also act as a
proxy for long-term field performance (Chekol et al.
2023), which provides valuable insight for breed-
ing programs aiming to improve yield, resilience, or
adaptation to agroecological zones or more sustain-
able farming systems (such as AFS).

Photomorphogenesis is the light-regulated devel-
opmental process by which plants alter their growth,
form, and gene expression due to changes in light
intensity, direction, wavelength, photoperiod (day
length) or light quality (e.g., red:far-red ratio), as is
experienced by all understory plants in AFS (Kami
et al. 2010).

Under shade, *C. arabica* undergoes a range of
physiological and morphological adjustments to adapt
to reduced light availability. Maximum quantum effi-
ciency of photosystem II ($F_v/F_m$) tends to increase or
remain stable compared to full sun, indicating less
photoinhibition (DaMatta et al. 2007; Moat et al.
2017). While net photosynthesis declines under deep
shade due to low light, moderate shade can sus-
tain relatively high photosynthetic rates in coffee. In
very low light, photosynthetic rate drops, but light-
use efficiency may improve (Cannell 1985; DaMatta
2004; Ricci et al. 2011). The light saturation point of
*C. arabica* can vary from 300 – 600 µmols m⁻² s⁻¹,
depending on whether it has been grown in the shade
or full sun (Friend 1984). Coffee leaf area increases
under shaded environments, both at the individual
leaf and whole-plant level. Leaves tend to become
larger, thinner (i.e. higher specific leaf area), and
more horizontally oriented to maximise light capture
(Morais et al. 2003; DaMatta & Ramalho 2006). Bio-
mass accumulation generally decreases with increas-
ing shade because total photosynthetic carbon gain is
reduced (Beer et al. 1998; Campanha et al. 2004a, b;
DaMatta et al. 2007).

The hypothesis of this study was that juvenile F1
hybrids of *C. arabica* exhibit better growth and physi-
ology traits under shaded environments compared to
pure lines (though they were not bred with this inten-
tion), demonstrated by higher maximum quantum
efficiency of photosystem II ($F_v/F_m$), net photosyn-
thesis, leaf area and biomass accumulation values. To
test this hypothesis, we designed a greenhouse experi-
ment testing the adaptive potential of four hybrids and
their parents in terms of physiology and growth under
varying levels of artificial shade. This experimental
design was intended to simulate varying shade levels which may occur within different coffee AFS.

# Methods

## Experimental design

Different coffee genotypes (Table. 1) were cloned by vegetative micropropagation at CIRAD, Montpellier, France and transported to a tropical greenhouse at University of Copenhagen, Denmark after 1 month of growth (June 2018). Upon arrival, plants were repotted into 17 cm size pots with 2 L of peat soil (pH 5.5 – 6.5) (Urnjord, AB Horto, Sollentuna, Sweden). Genetic material of the *C. arabica* originated from both Ethiopian wild types and Latin American landraces (Table. 1). A total of 165 plants were used in the experiment, of which 12 died during the study period (spread across all shade treatments however, frequently occurring under the highest shade level), five of which were ‘MS’, five ‘H3’, one ‘H1’ and one ‘Starmaya’ clone.

Throughout the experiment, the plants were kept well-watered with daily irrigation and a regular schedule of fertigation with nutrient enriched water (Pioneer Basis© N-P-K Makro with micronutrients, Limonest Cedex, France) provided three times a week in spring/summer and once per week during autumn/ winter months). Sticky traps and biological control agents (BCA) were used as the primary plant protection against sap-sucking insects (i.e. aphids and lice). Larvae of *Eretmoceru* spp. (from BIOBEST, Westerlo, Belgium) and *Chrysoperia carnea* (from Borregård BioPlant, Århus, Denmark) were released in the greenhouse as BCA. Overhead watering of the coffee plants was conducted prior to BCA release in order to increase the relative humidity, which promotes growth and development of the larvae.

Light levels were assessed on four occasions (14th, 19th and 20th September and 1st October 2018) using a LI-250R Quantum Sensor (LI-COR, Lincoln, Nebraska, USA) and monitored by an external meteorological station positioned on the roof of the greenhouse (providing air temperature, global radiation, and relative humidity data) (Fig. 2). Plants were exposed to 12-hours of supplementary light by 600-WATT high pressure sodium lamps in the greenhouse providing 130–200 µmol m² s⁻¹ at the

top of the canopy. However, external daylength did vary from tropical conditions due to the northern hemispheric location (up to 17 hours in the summer months). The greenhouse environment was set to daytime and nighttime minimum temperatures set at 24 and 17 °C, respectively.

The photosynthetic photon flux density (PPFD) µmol m⁻² s⁻¹ was calculated according to Knauer et al. (2018), as shown in Eq. 1:

$$PPFD = R_g * \text{Frac PAR} * J \text{ to mol} \quad (1)$$

where: **Rg**: global radiation (W m⁻²); **Frac PAR**: fraction of incoming solar irradiance that is photosynthetically active radiation (PAR); defaults to 0.5; **J to mol**: Conversion factor from J m⁻² s⁻¹ (= W m⁻²) to µmol (quanta) m⁻² s⁻¹; defaults to 4.57.

The environmental conditions which coffee plants were exposed to in the greenhouse varied across the seasons (in terms of air temperature, PPFD and relative humidity) (Fig. 1). The diurnal average PPFD (not supplemented) during daylight hours (outside the greenhouse) ranged from 19 – 88 µmol m⁻² s⁻¹ in the winter, 270 – 462 µmol m⁻² s⁻¹ in the spring months, 399 – 516 µmol m⁻² s⁻¹ in the summer and 85 – 287 µmol m⁻² s⁻¹ in the autumn months. The average air temperature in the greenhouse was less varied (due to automated temperature control), only exceeding the set limits in the summer months (average 23.6 °C in June and 23.15 °C in August). Relative humidity (%) varied from a minimum of 24% (in April) to a maximum of 100% (in June and August) and averaged 57 – 71% across other months of the year (Fig. 1).

Initial morphological measurements were taken on June 15th and 18th 2018. Based on these measurements the clones were separated into three blocks according to their initial height, with block one containing the smallest plants, block two containing medium sized plants and block three containing the largest plants. Each of these blocks was further separated into five shade treatment subplots by random selection. Each of the light treatments in their corresponding blocks included 11 plants, one of each of the clones. Shade treatments were applied by attaching different numbers of black plastic nets to small metal scaffolds surrounding each subplot. Coffee plants were grown under these shade net scaffolds for the duration of the experiment. Five
<table><caption>**Table 1** Description of *Coffea arabica* plant material in shaded greenhouse trial.</caption><thead><tr><th>Genotype</th><th>Genetic background (all considered within C. arabica species)</th><th>Phenotype</th><th>Genetic structure</th><th>Status in trial</th><th>No. plants</th><th>References</th></tr></thead><tbody><tr><td>'Caturra'</td><td>Natural mutation of the 'Bourbon' variety (Bourbon-Typica group)</td><td>A compact (aka. Dwarf) architecture with closely spaced second-ary branches. This phenotype allows for more fruit production within confined spaces, therefore lending itself to intensive cultivation through higher density planting, often in full sun.</td><td>American pure line cultivar</td><td>Mother of 'H3'</td><td>15</td><td>World Coffee Research Variety catalogue</td></tr><tr><td>'ET531'</td><td>A wild accession originat-ing in Ethiopia (CATIE collection)</td><td>Tall stature with inter-spersed nodes and branches.</td><td>Landrace accession</td><td>Father of 'H3'</td><td>15</td><td>Bertrand et al. 1999</td></tr><tr><td>'H3'</td><td>Hybrid cross between C. arabica 'Caturra' and Ethiopian landrace accession 'ET531'</td><td>Intermediate stature (i.e. between dwarf and tall) with exceptional cup quality.</td><td>F1 hybrid</td><td>Offspring of 'Caturra' crossed with 'ET531'</td><td>10</td><td>ECOM-CIRAD commercial hybrid variety<br>Bertrand et al. 2005b, c, a; Marie et al. 2020</td></tr><tr><td>'T5296'</td><td>Derived from the cross between Timor hybrid CIFC '832/2' and 'Villa Sarchi', with further backcrosses in Villa Sarchi</td><td>A compact (small-medium) stature plant with good cup quality, resistance to coffee leaf rust (CLR) and coffee berry disease (CBD)</td><td>American pure line intro-gressed Sarchimor</td><td>Mother of 'H1'</td><td>14</td><td>World Coffee Research Variety catalogue</td></tr><tr><td>'Rume Sudan'</td><td>A wild accession originat-ing in Ethiopia</td><td>Tall stature with inter-spersed nodes and branches. With known resistance genes for cof-fee berry disease.</td><td>Landrace accession</td><td>Father of 'H1'</td><td>15</td><td>Gimase et al. 2020</td></tr></tbody></table>

<figure><img src="image_2.png" /></figure>
<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Genotype</th><th>Genetic background (all considered within C. arabica species)</th><th>Phenotype</th><th>Genetic structure</th><th>Status in trial</th><th>No. plants</th><th>References</th></tr></thead><tbody><tr><td>'H1' aka. Centro-americano</td><td>Hybrid cross between rust resistant T5296 and the Ethiopian landrace 'Rume Sudan'</td><td>A high yielding semi-dwarf hybrid, with green leaf tips, large bean size and exceptional cup quality. 'H1' exhibits some resistance to CLR and CBD and tolerance to nematodes Meloidogyne exigua.</td><td>F1 hybrid</td><td>Offspring of 'T5296' crossed with 'Rume Sudan'</td><td>15</td><td>ECOM-CIRAD commercial hybrid variety Marie et al. 2020</td></tr><tr><td>'Marsellesa'</td><td>Line variety derived from the an initial crossing Timor hybrid '832/2' and 'Villa Sarchi' CIFC 971/10</td><td>A high yielding dwarf hybrid with green leaf tips and an average bean size. 'Marsellesa' was selected for complete resistance to CLR and to CBD.</td><td>Introgressed Sarchimor pure line</td><td>Father of 'Starmaya'</td><td>15</td><td>ECOM-CIRAD commercial pure line variety Georget et al. 2019a, b; Marie et al. 2020</td></tr><tr><td>'Male Sterile' aka 'MS'</td><td>A wild accession originating in Ethiopia named 'T 4905'</td><td>A sterile male reported by CATIE (Turrialba, Costa Rica)</td><td>Landrace accession</td><td>Mother of both 'Starmaya' and 'Mariana'</td><td>9</td><td>Dufour et al. 1997</td></tr><tr><td>'Starmaya'</td><td>A hybrid of 'MS' and 'Marsellesa'</td><td>A semi-dwarf hybrid, with green leaf tips and large bean size. 'Starmaya' was selected for its high yields and adaptability to biotic and abiotic stresses.</td><td>F1 hybrid</td><td>Offspring of 'Marsellesa' crossed with 'MS'</td><td>15</td><td>ECOM-CIRAD commercial hybrid variety Georget et al. 2019a, b; Marie et al. 2020</td></tr><tr><td>'IAPAR59'</td><td>A hybrid cross between Timor hybrid '832/2' and 'Villa Sarchi'.</td><td>A compact (small-medium) hybrid with a large grain size; exhibiting some resistance to CLR and to nematode species Meloidogyne exigua.</td><td>Introgressed Sarchimor</td><td>Father of 'Mariana'</td><td>15</td><td>Sera et al. 2011</td></tr><tr><td>'Mariana'</td><td>Hybrid cross between a sterile male 'MS' and 'IAPAR59'</td><td>A compact (small-medium) hybrid.</td><td>F1 hybrid</td><td>Offspring of 'IAPAR59' crossed with 'MS'</td><td>15</td><td>ECOM-CIRAD commercial hybrid variety</td></tr></tbody></table>
<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Genotype</th><th>Genetic background (all considered within C. arabica species)</th><th>Phenotype</th><th>Genetic structure</th><th>Status in trial</th><th>No. plants</th><th>References</th></tr></thead><tbody><tr><td></td><td></td><td></td><td></td><td></td><td>153</td><td></td></tr><tr><td></td><td>Total number of plants</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

light treatments were applied during the experiment exposing the coffee plants to an average light level from 10 – 800 µmol (Table 2).

Plants were acclimatised to the shade treatments for one month after which all measurements were conducted from July 29th to November 5th, 2018. After this period, all plants were harvested, and their total biomass was recorded.

## Gas-exchange measurements

Rates of photosynthesis and transpiration were measured using the CIRAS-1 and CIRAS-3 portable photosynthesis systems (PP Systems, Amesbury, Massachusetts, USA) equipped with PLC broad leaf cuvettes. The cuvettes were placed on the most recently fully developed leaf of each plant (avoiding self-shaded leaves) and left on the leaf until the CO₂ differential stabilised, at which point a measurement was recorded. Net photosynthesis ($A_{net}$), stomatal conductance ($g_s$) and intracellular CO₂ concentration ($C_i$) were measured between the hours of 09:00am – 12:00pm on sunny days using the ambient light in the treatments (leaf temperature = 21.5 – 32.5 °C).

## Chlorophyll a fluorescence

Chlorophyll a fluorescence measurements were conducted using a MINI-PAM II photosynthesis yield analyzer (WALZ, Effeltrich, Germany). Prior to measurements, leaves were dark adapted for 30 minutes with the purpose-made leaf clips. $F_v/F_m$ was measured, which represents the maximum efficiency at which photosystem II (PSII) can convert absorbed light into chemical energy when all PSII reaction centers are open (i.e. after dark adaptation) (Lichtenthaler et al. 2005). It is calculated as shown in Eq. 2:

$$F_v/F_m = (F_m - F_0)/F_m \quad (2)$$

where: $F_0$ = minimum fluorescence (all PSII reaction centers open); $F_m$ = maximum fluorescence (all PSII centers closed after a saturating light pulse); $F_v$ = variable fluorescence = $F_m - F_0$.

## Agronomical measurements

Final plant morphology was measured on November 5th 2018). Morphological attributes measured include

<figure><img src="image_3.png" /></figure>
<figure><img src="image_4.png" /><figcaption>**Fig. 1** Climate data (top to bottom) showing A the monthly relative humidity (%) , B air temperature (°C) and C photosynthetic photon flux density (PPFD) in the greenhouse throughout the study period (based on daily hour data from</figcaption></figure>

2020). Average monthly values are indicated by the solid lines, while minimum and maximum values are shown by the shaded areas

<table><caption>**Table 2** Light values manipulated with shade nets during the experimental period.</caption><thead><tr><td>Shade level (aka. light treatment)</td><td>No. of shade nets</td><td>Light transmission (%)</td><td>Light interception (%)</td><td>Average light measured (µmol m<sup>-2</sup> s<sup>-1</sup>)</td></tr></thead><tbody><tr><td>1</td><td>0</td><td>100</td><td>0</td><td>400 – 800</td></tr><tr><td>2</td><td>1</td><td>65</td><td>35</td><td>100 – 500</td></tr><tr><td>3</td><td>2</td><td>42</td><td>58</td><td>50 – 300</td></tr><tr><td>4</td><td>3</td><td>27</td><td>73</td><td>30 – 200</td></tr><tr><td>5</td><td>5</td><td>12</td><td>88</td><td>10 – 80</td></tr></tbody></table>
the height of each plant, the number of leaves, and the total and specific leaf area and the total above ground biomass. The destructive measurements of total leaf area were executed using the Winfolia software (Regent Instruments Inc., Ottawa, Ontario, Canada). The total above ground biomass was assessed by removing all leaves from the stem of the plant, then cutting off the stem from the roots, and subsequently drying the stem and leaves in a drying oven for two days at a temperature of 75 °C before being weighed.

The total relative growth rate of each plant was calculated as the natural log of the initial height of the plant subtracted from the natural log of the final height of the plant, divided by the overall length of the study (in days).

## Statistical analysis

All collected data were analysed with linear mixed-effects models in R version 3.6 (R Core Team 2019) using the package ‘lme4’ (Kuznetsova et al. 2017). PCA was used as a multivariate analysis to demonstrate patterns between all coffee plant physiological and agronomic traits and genotypes. This was determined by geometrically projecting data onto principal components (PCs) and finding the best summary of the data using a limited number of PCs to describe trends (Lever et al. 2017). PCA was conducted on the raw data set from each of the studies using the ‘prcomps’ function in R. The “scale” and “centre” options were set to ‘TRUE’ so that all of the variables had an equally weighted effect in the PCA (Holland 2008). Trait sets were illustrated as vectors; their relationship to one another and contribution to data variance was illustrated using “biplots” (signified by the arrow orientation and length, respectively).

The relationship between the measured traits (response variables) and the interaction between shade levels (n = 5) and genotype (fixed effects, n= 11) was analysed, while accounting for random effects due to block (n = 5), as shown in Eq. 3:

$$Y_{ijk} = \mu + \alpha_{i} + \beta_{j} + (\alpha\beta)_{ij} + p_{k} \quad (3)$$

where: $Y_{ijk}$ is the observed trait value, $\mu$ is the overall mean, $\alpha_i$ represents the fixed effect of shade (as a factor), $\beta_j$ is the fixed effect of genotype (as a factor), $(\alpha\beta)_{ij}$ is the interaction between shade and genotype, and $p_k$ is the random effect of block. The model

output was then compiled into a summary table for interpretation. When a significant effect of genotype on the trait was detected, pairwise comparisons of genotypes were conducted using the ‘emmeans’ package, along with compact letter displays to indicate significant differences. These comparisons were based on least square means averaged across all shade levels, allowing for a comprehensive evaluation of genotype performance. A post-hoc Tukey’s Honest Significant Difference (HSD) test was conducted following ANOVA (p >0.05) to identify pairwise differences between group means while controlling for Type I error.

## Results

The PCA contribution plot (Fig. 2) indicated that several variables strongly influence the distribution of samples along the first two principal components. $C_i$ (intercellular CO$_2$ concentration) and $A_{net}$ (net photosynthesis) showed the highest contributions, suggesting they played a major role in differentiating plants in this analysis. Similarly, leaf count, tree height, total foliage dry mass, and $g_s$ (stomatal conductance) also contributed notably, indicating that traits related to growth and gas exchange are key drivers of variance in the dataset. In contrast, stem dry mass and $F_v/F_m$ showed relatively weak contributions, implying they explained less of the variability captured by PC1 and PC2. The clustering and directionality of arrows further suggested strong positive correlations among several growth traits (e.g., tree height, leaf count, foliage dry weight).

Data did not cluster according to genotype (Fig. 3A), as shown by the substantial overlap among ellipses representing different genetic groups. This suggested that most of the observed phenotypic variation was not attributable to genetic origin—whether the clone was a landrace accession, pure line, or F1 hybrid—but was instead driven by environmental factors such as shade level. Data could, however, be clearly differentiated based on shade treatment, with particularly distinct separation observed between the 0 and 88% shade levels (Fig. 3B). This indicated that light availability had a strong influence on the measured traits.

The boxplots illustrated the effects of increasing shade levels (0, 35, 58, 73, and 88%) on a range of
<figure><img src="image_5.png" /><figcaption>**Fig. 2** Contribution of variables to the first two principal components (Dim1 and Dim2). The length and direction of arrows indicate the strength and orientation of each variable's contribution to the principal components. Colour coding reflects the degree of contribution, with blue (low contribution) to red (high contribution). Variables that contribute most are those furthest from the origin along the corresponding axis</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>**Fig. 3** Principal component analysis (PCA) of physiological and morphological data grouped according to the **A** different coffee genotypes and **B** five light treatments (0–88%)</figcaption></figure>
**Fig. 4** Shade effects on coffee morphological and physiological traits. A maximum PSII efficiency, $F_{v}/F_{m}$; B leaf photosynthetic rate, $A_{net}$; C specific leaf area; D total above ground biomass (average per plant), E relative growth rate, F stomatal conductance and G intracellular CO$_{2}$ concentration of juvenile coffee plants. Means ± SE are shown, and different letters indicate statistically significant differences among shade levels. Each value represents a mean of approximately 30 individuals

<figure><img src="image_7.png" /></figure>
<table><caption>**Table 3** Likelihood ratio tests assessing the effects of shade, genotype, and their interaction on measured plant traits. Significant effects are indicated by *p*-values and significance levels (*p* < 0.05 = *, < 0.01 = **, < 0.001 = ***)</caption><thead><tr><th>Trait</th><th>Fixed Effects</th><th>Chi<sup>2</sup></th><th>df</th><th>p-value</th><th>Significance</th></tr></thead><tbody><tr><td rowspan="3">C<sub>i</sub> (µmol mol<sup>-1</sup>)</td><td>Shade</td><td>13.89</td><td>4</td><td>0.0077</td><td>**</td></tr><tr><td>Genotype</td><td>70.84</td><td>10</td><td>3.05e-11</td><td>***</td></tr><tr><td>Shade × Genotype</td><td>99.97</td><td>39</td><td>2.95e-07</td><td>***</td></tr><tr><td rowspan="3">F<sub>v</sub>/F<sub>m</sub></td><td>Shade</td><td>30.28</td><td>4</td><td>4.30e-06</td><td>***</td></tr><tr><td>Genotype</td><td>28.48</td><td>10</td><td>0.0015</td><td>**</td></tr><tr><td>Shade × Genotype</td><td>38.08</td><td>39</td><td>0.5117</td><td>ns</td></tr><tr><td rowspan="3">g<sub>s</sub> (mmol m<sup>-2</sup> s<sup>-1</sup>)</td><td>Shade</td><td>1.62</td><td>4</td><td>0.8051</td><td>ns</td></tr><tr><td>Genotype</td><td>39.43</td><td>10</td><td>2.133e-05</td><td>***</td></tr><tr><td>Shade × Genotype</td><td>55.16</td><td>39</td><td>0.0447</td><td>*</td></tr><tr><td rowspan="3">Leaf area (cm<sup>2</sup>)</td><td>Shade</td><td>3.56</td><td>4</td><td>0.4682</td><td>ns</td></tr><tr><td>Genotype</td><td>2.78</td><td>10</td><td>0.9862</td><td>ns</td></tr><tr><td>Shade × Genotype</td><td>15.33</td><td>39</td><td>0.9998</td><td>ns</td></tr><tr><td rowspan="3">Leaf count (average per plant)</td><td>Shade</td><td>54.23</td><td>4</td><td>4.72e-11</td><td>***</td></tr><tr><td>Genotype</td><td>97.12</td><td>10</td><td>&lt; 2.2e-16</td><td>***</td></tr><tr><td>Shade × Genotype</td><td>93.73</td><td>39</td><td>2.11e-06</td><td>***</td></tr><tr><td rowspan="3">A<sub>net</sub> (µmol m<sup>-2</sup> s<sup>-1</sup>)</td><td>Shade</td><td>19.54</td><td>4</td><td>0.0006</td><td>***</td></tr><tr><td>Genotype</td><td>22.36</td><td>10</td><td>0.0134</td><td>*</td></tr><tr><td>Shade × Genotype</td><td>41.67</td><td>39</td><td>0.3556</td><td>ns</td></tr><tr><td rowspan="3">Specific leaf area (cm<sup>2</sup>/g)</td><td>Shade</td><td>10.66</td><td>4</td><td>0.0306</td><td>*</td></tr><tr><td>Genotype</td><td>15.65</td><td>10</td><td>0.1100</td><td>ns</td></tr><tr><td>Shade × Genotype</td><td>69.99</td><td>39</td><td>0.0017</td><td>**</td></tr><tr><td rowspan="3">Stem dry mass (g)</td><td>Shade</td><td>34.95</td><td>4</td><td>4.76e-07</td><td>***</td></tr><tr><td>Genotype</td><td>20.25</td><td>10</td><td>0.0269</td><td>*</td></tr><tr><td>Shade × Genotype</td><td>97.37</td><td>39</td><td>6.76e-07</td><td>***</td></tr><tr><td rowspan="3">Total foliage dry mass (g)</td><td>Shade</td><td>9.63</td><td>4</td><td>0.0472</td><td>*</td></tr><tr><td>Genotype</td><td>20.27</td><td>10</td><td>0.0268</td><td>*</td></tr><tr><td>Shade × Genotype</td><td>58.44</td><td>39</td><td>0.0234</td><td>*</td></tr><tr><td rowspan="3">Plant height (cm)</td><td>Shade</td><td>23.89</td><td>4</td><td>8.41e-05</td><td>***</td></tr><tr><td>Genotype</td><td>112.23</td><td>10</td><td>&lt; 2.2e-16</td><td>***</td></tr><tr><td>Shade × Genotype</td><td>98.06</td><td>39</td><td>5.44e-07</td><td>***</td></tr></tbody></table>

not only shapes core physiological and morphological traits yet also exposes meaningful variation in how different coffee genotypes adjust and perform through photomorphogenesis.

Light availability drives major variation in coffee traits

The light environment was the primary factor structuring phenotypic variation (Fig. 3B), with data clustered distinctly by shade treatment, particularly between the extremes (0% vs. 88%), confirming that shade had a strong influence on the overall plant phenotype (Matos et al. 2009; César et al. 2013; Rodríguez-López et al. 2014). This finding is supported

by previous studies identifying coffee as a facultative shade species, displaying characteristics typical of sun-adapted plants alongside traits that enable acclimation to shaded environments (Fahl et al. 1994). It is important to acknowledge that shade nets and greenhouse screens can modify the spectral quality of light reaching plants (Kotilainen et al. 2018), which may have influenced the experimental outcomes. However, because the shade nets used in this study were black, they likely caused a uniform reduction across all wavelengths rather than selectively filtering specific parts of the light spectrum. Genotype effects were less pronounced than shade effects in the multivariate space (Fig. 3A), with considerable overlap between genetic groups. This suggests that environmental
plasticity to shade may dominate intrinsic genetic
differences under the conditions tested, especially in
early growth stages (Campa et al. 2017). This is likely
caused by the so-called genetic bottleneck in the C.
arabica species, with cultivars and hybrids showing
very little genetic variation due to their shared origin,
reproductive biology, and evolution (Lashermes et al.
1999, 2009).

Physiological responses reveal shade tolerance trade-offs

A key question frequently raised by coffee farmers
and advisers concerns the optimal level of shade for
coffee cultivation. Recent research has suggested the
presence of shade optima for yield in both C. arabica
and C. canephora species to be under 40% (Piato
et al. 2020; Koutouleas et al. 2022b). The physiologi-
cal data demonstrated that different traits responded
in contrasting ways to increasing shade (Fig. 4A-D).
F/Fm increased slightly under higher shade, con-
sistent with reduced photoinhibition and better pho-
tochemical efficiency under lower light. This trend
aligns with literature indicating that PSII efficiency
can be maintained or even improved in shaded envi-
ronments where excess light stress is reduced (Franck
et al. 2006; Matos et al. 2009; de Souza et al. 2023).
However, Anet declined significantly with increasing
shade, particularly under 88% shade (Fig. 4B), indi-
cating that carbon assimilation was strongly light-lim-
ited despite the photochemical machinery remaining
intact. These findings illustrate a classic physiologi-
cal trade-off: while photoprotection improves under
shade, the carbon economy of the plant is constrained
due to reduced photon flux (DaMatta 2004). Specific
leaf area increased under shade (Fig. 4C), reflecting
thinner and broader leaves—morphological adapta-
tions that enhance light capture in low-light environ-
ments (Kufa & Burkhardt 2015). Yet, adjustments in
SLA were insufficient to offset reductions in total bio-
mass, which both declined sharply under high shade
(Fig. 4D). These findings are consistent with classical
coffee studies which have repeatedly stated that while
shade promotes photochemical efficiency and leaf-
level morphological adjustments, overall resource
acquisition and growth are still compromised
(Muschler 2001; DaMatta 2004; Bote & Struik 2011).
Since the lowest shade level applied in this study was
35%, future research should consider testing milder

shade levels to assess whether coffee growth and per-
formance can approach those observed under full sun,
while still providing some degree of photoprotection.

Not all F1 hybrids are performing high under shade

The generation of *C. arabica* F1 hybrids has been an approach to addressing the genetic bottleneck of the species. While these hybrids have shown a stability in their phenotypes across different environments, as well as improved plant vigour, yield and bean quality compared to their parental lines (Bertrand et al. 2005b, c, a, 2011; Toniutti et al., 2017; Georget et al. 2019a, b; Marie et al. 2020; Dilas-Jiménez et al., 2022), they have not been specifically bred for shaded environments (Bertrand et al. 2005b, c, a; Breitler et al. 2022). Given this, there is a need to evaluate their growth and performance under different shade levels to gauge their suitability to future coffee-AFS (Koutouleas et al. 2023).

Despite the strong environmental effect, signifi-
cant genotypic variation emerged in several traits,
as shown in both the statistical analysis (Table 3)
and marginal mean comparisons (Figs. 5, 6, 7, 8).
Genotypes such as ‘Caturra’ and ‘Starmaya’ con-
sistently ranked highest in leaf count and stem dry
mass (Figs. 5 and 6), suggesting superior biomass
accumulation capacity under shaded environments.
Notably, ‘Starmaya’, an F1 hybrid, also exhibited one
of the greatest plant heights (Fig. 7), similar to the
tall-growing landraces ‘ET531’ and ‘Rume Sudan’
which grow in forests, and are therefore adapted to
shade. Increased plant height under shaded condi-
tions reflects an adaptive architecture due to photo-
morphogenesis responses (Rakocevic et al. 2012;
Cardoso-Magaña et al. 2024), which occur as a result
of low light intensity (Muschler 2001) and light qual-
ity modifications. The stable performance of juvenile
‘Caturra’, ‘Starmaya’, and ‘Marsellesa’ under shade
suggests they are strong candidates for agroforestry
systems.

Under shade, ‘Marsellesa’ has been found to
strongly favour vegetative growth at the expense of
production, deeming this genotype unsuitable for
AFS environments (Breitler et al. 2022). This means
that the floral induction process is redirected under
shade toward the production of vegetative buds. Con-
trastingly, ‘Starmaya’, does not undergo this photo-
morphogenic response, as it maintains its production
<figure><img src="image_8.png" /><figcaption>**Fig. 5** Estimated marginal means ± standard error of leaf count for all evaluated hybrids and pure lines, averaged across all shade treatments. Different letters indicate statistically significant differences among genotypes (Tukey's HSD, *p* < 0.05)</figcaption></figure>

<figure><img src="image_9.png" /><figcaption>**Fig. 6** Estimated marginal means ± standard error of stem dry mass (g) for all evaluated coffee genotypes (hybrids and pure lines), averaged across all shade treatments. Different letters indicate statistically significant differences among genotypes (Tukey's HSD, *p* < 0.05). Data for genotype 'MS' were not recorded</figcaption></figure>

under levels up to 30% shade (Rigal et al. 2023). This is a common characteristic of *C. arabica* hybrids that maintain high production levels under shade (Bertand et al. 2011).

The coffee genotypes ‘H1’ and ‘IAPAR 59’ had the lowest stem dry mass indicating potentially reduced growth potential under the tested conditions. The low genotype stature (i.e. plant height) of some of

<figure><img src="image_10.png" /></figure>
<figure><img src="image_11.png" /><figcaption>**Fig. 7** Estimated marginal means ± standard error of coffee plant height (cm) for all evaluated genotypes, averaged across all shade treatments. Different letters indicate statistically significant differences among genotypes (Tukey's HSD, *p* < 0.05)</figcaption></figure>

<figure><img src="image_12.png" /><figcaption>**Fig. 8** Fv/Fm of 11 coffee genotypes grown under full sun. Bars represent estimated marginal means ± standard errors. Different letters above the bars indicate statistically significant differences based on post-hoc comparisons</figcaption></figure>

the genotypes tested is closely linked to the breeding, especially for 'IAPAR 59' which has been bred for its compact canopy (among other traits) (Sera 2001). This

low stature makes it suitable for higher-density planting and mechanical harvesting, especially in intensive, modern coffee growing zones such as southern Brazil.
Interestingly, $F_v/F_m$ measurements under full sun (Fig. 8) revealed that some genotypes, such as ‘H3’, ‘Mariana’ and ‘MS’, were more susceptible to photoinhibition, while others (e.g., ‘Starmaya’, ‘Rume Sudan’, ‘Marsellesa’) also showed signs of decreased PSII efficiency under full sun conditions (due to $F_v/F_m$ values lower than 0.83). This points to an overall stress response in juvenile coffee plants under full sun conditions.

Based on our overall findings, the hypothesis that juvenile F1 hybrids of *C. arabica* would outperform pure lines under shaded environments was only partially supported by the greenhouse data. While some genotypes, particularly ‘Starmaya’, demonstrated favourable responses, not all hybrids consistently outperformed pure lines across all traits. For example, the pure line ‘Caturra’ showed comparable performance to the hybrids in several growth metrics, suggesting that certain non-hybrid genotypes may also possess traits conducive to shaded conditions. Furthermore, $A_{net}$ declined significantly under high shade in all genotypes, including all hybrids, indicating that light limitation constrained carbon assimilation regardless of genetic background. This suggests that though some hybrids may hold promise for shaded agroforestry systems, their advantage is not uniform across all physiological and morphological traits, pointing to the need for trait-specific selection rather than assuming blanket superiority of hybrids in low-light environments. It is also important to note that the plants assessed in this study were still in their juvenile, pre-productive phase. As such, their responses likely reflect early-stage photomorphogenesis adjustments to shade, which may differ from those exhibited by adult, reproductively active plants (Campa et al. 2017).

## Conclusion

This study demonstrates that shade exerts strong, multidimensional impacts on juvenile coffee plants, influencing physiology, morphology, and growth. While light availability is the dominant driver of phenotypic variation, significant genotypic differences and interaction effects highlight the role of genetic background in modulating plant responses. Juvenile traits such as leaf count, plant height and stem mass, showed varying sensitivities to both

shade and genotype, indicating that these characteristics may serve as valuable targets for selecting and breeding coffee cultivars adapted to shaded environments. The coffee genotypes ‘Caturra’, ‘Starmaya’, and ‘Marsellesa’ demonstrate promising growth and physiological performance as juvenile plants under shaded conditions. Future work could explore how these early-stage responses to the environment translate to long-term productivity in the field, as well as the interaction with other environmental factors such as elevated temperature or water scarcity.

**Acknowledgements** This work was conducted within the framework of the European Union’s Horizon 2020 research and innovation programme through the BREEDCAFS project (Breeding Coffee for Agroforestry Systems, www.breedcafs.eu), 2017–2021), funded under grant agreement No. 727934. Additional funding was provided by the Ministry of Foreign Affairs of Denmark, administered by the Danida Fellowship Centre (grant No. 23–06-KU). We extend our appreciation to the Department of Geosciences and Natural Resource Management for access to research facilities and equipment. We gratefully acknowledge the BREEDCAFS Coffee Adapt team in Montpellier for supplying the coffee plants and assisting with logistics and coordination. Special thanks to Associate Professor Aske Skovmand Bosselmann for his repeated visits to our experiment and for providing encouragement as well as valuable expert guidance. We are deeply grateful to the University of Copenhagen greenhouse staff—Kurt Dahl, Theodor Emil Bolsterli, and Naja Jessen—for their exceptional care and dedication to plant health. Your expertise made it possible for our coffee plants to survive the Nordic winter. Finally, we thank the anonymous peer reviewers for their time and help in further defining this work.

**Author Contributions** Conceptualization was conducted by AR, HE & MR. Data collection was conducted by AK and LT. Analysis of data and writing (of the original draft) was conducted by AK and LT. All authors contributed to the writing and editing of the final version of the manuscript.

**Funding** Open access funding provided by Copenhagen University. This work was funded by and carried out in the context of the European Union’s Horizon 2020 (H2020) research and innovation program by the BREEDCAFS (Breeding Coffee for Agroforestry Systems, www.breedcafs.eu) project (2017-2021) under the grant agreement No 727934. We are also grateful to funding provided by the Ministry of Foreign Affairs of Denmark and administered by Danida Fellowship Centre under the grant number 23–06-KU.

**Data Availability** No datasets were generated or analysed during the current study.

## Declarations

**Conflicts of interest** The authors declare no competing interests.
**Ethics approval** Not applicable.

**Consent to participate** Not applicable.

**Consent for publication (include appropriate statements)** Not applicable.

**Open Access** This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

## References

Alemu A, Dufera E (2017) Climate smart coffee (*Coffea arabica*) production. Am J Data Min Knowl Discov 2(2):62–68. https://doi.org/10.11648/j.ajdmkd.20170202.14

Bawin, Y. (2022). Genetic variation in wild and cultivated Arabica coffee (*Coffea arabica* L.): Evolutionary origin, global distribution, and its effect on fungal disease incidence in Southwest Ethiopia. https://lirias.kuleuven.be/3768296?limo=0

Beer J, Muschler R, Kass D, Somarriba E (1998) Shade management in coffee and cacao plantations. Agroforest Syst 38(1):139–164. https://doi.org/10.1023/A:1005956528316

Bellasio C, Beerling DJ, Griffiths H (2016) An excel tool for deriving key photosynthetic parameters from combined gas exchange and chlorophyll fluorescence: theory and practice. Plant Cell Environ 39(6):1180–1197. https://doi.org/10.1111/pce.12560

Bernado WDP, Rakocevic M, Santos AR, Ruas KF, Baroni DF, Abraham AC, Pireda S, Oliveira DDS, Cunha MD, Ramalho JC, Campostrini E (2021) Biomass and leaf acclimations to ultraviolet solar radiation in juvenile plants of *Coffea arabica* and *C. canephora*. Plants 10(4):640. https://doi.org/10.3390/plants10040640

Bertrand B, Etienne H, Cilas C, Charrier A, Baradat P (2005a) *Coffea arabica* hybrid performance for yield, fertility and bean weight. Euphytica 141(3):255–262

Bertrand B, Etienne H, Cilas C et al (2005b) *Coffea arabica* hybrid performance for yield, fertility and bean weight. Euphytica 141:255–262. https://doi.org/10.1007/s10681-005-7681-7

Bertrand B, Etienne H, Cilas C, Charrier A, Baradat P (2005c) *Coffea arabica* hybrid performance for yield, fertility and bean weight. Euphytica 141(3):255–262. https://doi.org/10.1007/s10681-005-7681-7

Bertrand B, Alpizar E, Lara L, Santacreo R, Hidalgo M, Quijano JM, Montagnon C, Georget F, Etienne H (2011) Performance of *Coffea arabica* F1 hybrids in agroforestry and full-sun cropping systems in comparison with American pure line cultivars. Euphytica 181(2):147–158. https://doi.org/10.1007/s10681-011-0372-7

Bertrand, B., Aguilar, G., Santacreo, R., & Anzueto, F. (1999). El mejoramiento genético en América Central. In: *Proceedings of the III International Seminar on Biotechnology in the Coffee Agro industry, Londrina*. https://www/documentation.ird.fr/hor/fdi:010022391

Bertrand, B., Breitler, J-C., Georget, F., Penot, E., Bordeaux, M., Marraccini, P., et al. (2019). New varieties for innovative agroforestry coffee systems. In: *The agroecological transition of agricultural systems in the Global South, Côte, F. X., Poirier-Magona, E., Perret, S., Roudier, P., Rapidel, B., & Thirion, M. C. (eds.) (2019). Quae Editor, Versailles, pp. 161-176. https://doi.org/10.35690/978-2-7592-3057-0*

Bote, A.D., & Struik, P.C. (2011). Effects of shade on growth, production and quality of coffee (*Coffea arabica*) in Ethiopia. *Journal of Horticulture and Forestry, 3*(11), 336-341. https://academicjournals.org/journal/JHF/article-full-text-pdf/454B9711885

Breitler JC, Etienne H, Léran S, Marie L, Bertrand B (2022) Description of an arabica coffee ideotype for agroforestry cropping systems: a guideline for breeding more resilient new varieties. Plants 11(16):2133. https://doi.org/10.3390/plants11162133

Bunce J (2018) Three methods of estimating mesophyll conductance agree regarding its CO₂ sensitivity in the Rubisco-limited Ci range. Plants 7(3):62. https://doi.org/10.3390/plants7030062

Camargo MBPD (2010) The impact of climatic variability and climate change on Arabic coffee crop in Brazil. Bragantia 69(1):239–247. https://doi.org/10.1590/S0006-87052010000100030

Campa C, Urban L, Mondolot L, Fabre D, Roques S, Lizzi Y, Aarrouf J, Doulbeau S, Breitler JC, Letrez C, Toniutti L, Bertrand B, La Fisca P, Bidel LPR, Etienne H (2017) Juvenile coffee leaves acclimated to low light are unable to cope with a moderate light increase. Front Plant Sci 8:1126. https://doi.org/10.3389/fpls.2017.01126

Campanha MM, Santos RHS, Martinez HEP, Freitas GB, García SLR, Finger FL (2004a) Growth and yield of coffee plants in agroforestry and monoculture systems in Minas Gerais. Braz Agrofor Syst 63(2):75–82. https://doi.org/10.1023/B:AGFQ.0000049431.33392.76

Campanha MM, Santos RHS, de Freitas GB, Martinez HEP, García SLR, Finger FF (2004b) Growth and yield of coffee plants in agroforestry and monoculture systems in Minas Gerais, Brazil. Agroforest Syst 63(1):75–82. https://doi.org/10.1023/B:AGFQ.0000049435.22512.2d

Cannell MGR (1985) Physiology of the coffee crop. In: Clifford MN, Willson KC (eds) Coffee: Botany, biochemistry and production of beans and beverage. Croom Helm, pp 108–134

Cardoso-Magaña AJ, Montero-Cortés MI, Qui-Zapata JA, Chávez-Rodríguez AM, Mancilla-Margalli NA, López-Velázquez JC, Farias-Cervantes VS, Andrade-González I, Rivera-Rodríguez DM, Bejarano-Rebolledo F (2024)
Effect of light quality on the seed germination and development of coffee seedlings (*Coffea arabica*). Plants 13(13):1772. https://doi.org/10.3390/plants13131772

Cassamo CT, Mangueze AV, Leitão AE, Pais IP, Moreira R, Campa C, Chieule R, Reis FO, Marques I, Scotti-Campos P, Lidon FC (2022) Shade and altitude implications on the physical and chemical attributes of green coffee beans from Gorongosa Mountain, Mozambique. *Agronomy* 12(10):2540. https://doi.org/10.3390/agronomy12102540

César FRCF, Matsumoto SN, Viana AES, Bonfim JA (2013) Morphological plasticity of three coffee cultivars under light gradient. Coffee Sci 8(3):317–324

Charbonnier F, Le Maire G, Dreyer E, Casanoves F, Christina M, Dauzat J, Eitel JU, Vaast P, Vierling LA, Roupsard O (2013) Competition for light in heterogeneous canopies: application of MAESTRA to a coffee (*Coffea arabica* L.) agroforestry system. Agric for Meteorol 181:152–169. https://doi.org/10.1016/j.agrformet.2013.07.010

Charbonnier F, Roupsard O, Le Maire G, Guillemot J, Casanoves F, Lacointe A, Vaast P, Allinne C, Audebert L, Cambou A, Clément-Vidal A (2017) Increased light-use efficiency sustains net primary productivity of shaded coffee plants in agroforestry system. Plant Cell Environ 40(8):1592–1608. https://doi.org/10.1111/pce.12964

Chazdon RL, Pearcy RW, Lee DW, Fetcher NED (1996) Photosynthetic responses of tropical forest plants to contrasting light environments. *Tropical forest plant ecophysiology*. Springer, US, Boston, MA, pp 5–55

Chekol H, Bezuayehu Y, Warkineh B, Shimber T, Mierek-Adamska A, Dąbrowska GB, Degu A (2023) Unraveling drought tolerance and sensitivity in coffee genotypes: insights from seed traits, germination, and growth-physiological responses. Agriculture 13(9):1754. https://doi.org/10.3390/agriculture13091754

Clemens, H., & Simán, J. (1993). Tecnología y desarrollo del sector cafetalero en Nicaragua: Caracterización del manejo del cultivo del café en la IV Región, ciclo 1990/91. Universidad Nacional Autónoma de Nicaragua, Facultad de Ciencias Económicas, Escuela de Economía Agrícola.

DaMatta FM (2004) Ecophysiological constraints on the production of shaded and unshaded coffee: a review. Field Crops Res 86(2–3):99–114. https://doi.org/10.1016/j.fcr.2003.09.001

DaMatta FM, Ramalho JDC (2006) Impacts of drought and temperature stress on coffee physiology and production: a review. Braz J Plant Physiol 18(1):55–81. https://doi.org/10.1590/S1677-04202006000100006

DaMatta FM, Ronchi CP, Maestri M, Barros RS (2007) Ecophysiology of coffee growth and production. Braz J Plant Physiol 19:485–510. https://doi.org/10.1590/S1677-04202007000400014

Davis AP, Tosh J, Ruch N, Fay MF (2011) Growing coffee: *Psilanthus* (Rubiaceae) subsumed on the basis of molecular and morphological data; implications for the size, morphology, distribution and evolutionary history of *Coffea*. Bot J Linn Soc 167(4):357–377. https://doi.org/10.1111/j.1095-8339.2011.01177.x

de Sousa K, van Zonneveld M, Holmgren M, Kindt R, Ordoñez JC (2019) The future of coffee and cocoa agroforestry in a warmer Mesoamerica. Sci Rep 9(1):8828. https://doi.org/10.1038/s41598-019-45491-7

de Souza AH, de Oliveira US, Oliveira LA, de Carvalho PH, de Andrade MT, Pereira TS, Gomes Junior CC, Cardoso AA, Ramalho JD, Martins SC, DaMatta FM (2023) Growth and leaf gas exchange upregulation by elevated [CO₂] is light dependent in coffee plants. Plants 12(7):1479. https://doi.org/10.3390/plants12071479

de Souza GA, Baroni DF, Bernado WDP, Santos AR, Barcellos LCDS, Barcelos LF, Correia LZ, de Almeida CM, Verdin Filho AC, Rodrigues WP, Ramalho JC (2025) Leaf to root morphological and anatomical indicators of drought resistance in *Coffea canephora* after two stress cycles. Agriculture 15(6):574. https://doi.org/10.3390/agriculture15060574

Dilas-Jiménez JO, Zelada Valqui H, Carrasco Barturén W, Muaguza-Vassallo C (2022) Phenotypic performance evaluation of the coffee variety marsellesa® over 1400 meters asl as an alternative for coffee growing. Cienc Y Tecnol Agropecu 23(3)

Duangsodsri T, Villain L, Vestalys IR, Michalet S, Abdallah C, Breitler JC, Bordeaux M, Villegas AM, Raherimandimby M, Legendre L, Etienne H (2020) 5-CQA and mangiferin, two leaf biomarkers of adaptation to full sun or shade conditions in *Coffea arabica* L. Metabolites 10(10):383. https://doi.org/10.3390/metabo10100383

Duangsodsri, T., Leran, S., Villegas, A.M., Vestalys, I., Artins, A., Etienne, H., Breitler, J.C., Villain, L., Bertrand, B., & Campa, C., (2019). A global approach to decipher molecular basis of coffee tree adaptation to shade. CIRAD. https://agritrop.cirad.fr/592969/

Dufour, M., Anthony, F., Bertrand, B., & Eskes, A. (1997). Identification de caféiers mâle-stériles de *Coffea arabica* au CATIE, Costa Rica. Accessed via [https://agritrop.cirad.fr/389641/1/document_389641.pdf] on 9th January 2023

Etienne, H., Georget, F., Ruiz, T., Bordeaux, M., Leroy, T., Penot, E., Marraccini, P., Vaast, P., Courtel, P., Turreira-Garcia, N. &Ehabe, E.E., (2021). Enhancing the adoption worldwide of Arabica hybrids through implementation of on-farm trials, transfer of propagation techniques and stakeholder dialog platforms. ASIC. https://agritrop.cirad.fr/598811/

Fahl JI, Carelli MLC, Vega J, Magalhães AC (1994) Nitrogen and irradiance levels affecting net photosynthesis and growth of young coffee plants (*Coffea arabica* L.). J Horvic Sci 69(1):161–169. https://doi.org/10.1080/14620316.1994.11515262

Franck N, Vaast P, Génard M, Dauzat J (2006) Soluble sugars mediate sink feedback down-regulation of leaf photosynthesis in field-grown *Coffea arabica*. Tree Physiol 26(5):517–525. https://doi.org/10.1093/treephys/26.4.517

Friend DJC (1984) Shade adaptation of photosynthesis in *Coffea arabica*. Photosynth Res 5(4):325–334. https://doi.org/10.1007/BF00034977

Georget F, Marie L, Alpizar E, Courtel P, Bordeaux M, Hidalgo JM, Marraccini P, Breitler JC, Déchamp E, Poncon C, Etienne H (2019a) Starmaya: the first arabica F1 coffee hybrid produced using genetic male sterility. Front Plant Sci. https://doi.org/10.3389/fpls.2019.01344

<figure><img src="image_13.png" /></figure>
Georget F, Marie L, Alpizar E, Courtel P, Bordeaux M, Hidalgo JM, Marraccini P, Breitler JC, Déchamp E, Poncon C, Etienne H (2019b) Starmaya: the first arabica F1 coffee hybrid produced using genetic male sterility. Front Plant Sci 10:1344. https://doi.org/10.3389/fpls.2019.01344

Gimase JM, Thagana WM, Omondi CO, Cheserek JJ, Gichimu BM, Gichuru EK, Ziyomo C, Sneller CH (2020) Genome-Wide association study identify the genetic loci confering resistance to coffee berry disease (Colletotrichum kahawae) in *Coffea arabica* var. Rume Sudan. Euphytica 216(6):1-17. https://doi.org/10.1007/s10681-020-02621-x

Holland, S. M. (2008). Principal components analysis (PCA). Department of Geology, University of Georgia, Athens, GA, 30602-2501. Accessed via [http://strata.uga.edu/software/pdf/pcaTutorial.pdf] on 28th December 2022.

Kami C, Lorrain S, Hornitschek P, Fankhauser C (2010) Light-regulated plant growth and development. Curr Top Dev Biol 91:29-66. https://doi.org/10.1016/S0070-2153(10)91002-8

Knauer J, El-Madany TS, Zaehle S, Migliavacca M (2018) Bigleaf—an R package for the calculation of physical and physiological ecosystem properties from eddy covariance data. PLoS ONE 13(8):e0201114. https://doi.org/10.1371/journal.pone.0201114

Kotilainen T, Robson TM, Hernandez R (2018) Light quality characterization under climate screens and shade nets for controlled-environment agriculture. PLoS ONE 13(6):e0199628. https://doi.org/10.1371/journal.pone.0199628

Koutouleas A, Collinge DB, Ræbild A (2022a) Alternative plant protection strategies for tomorrow's coffee. Plant Pathol 00:1-21. https://doi.org/10.1111/ppa.13676

Koutouleas A, Sarzynski T, Bertrand B, Bordeaux M, Bosselmann AS, Campa C, Etienne H, Turreira-García N, Léran S, Markussen B, Marraccini P (2022b) Shade effects on yield across different *Coffea arabica* cultivars—how much is too much? A Meta-Anal Agron Sustain Dev 42(4):1-13. https://doi.org/10.1007/s13593-022-00788-2

Koutouleas A, Sarzynski T, Bordeaux M, Bosselmann AS, Campa C, Etienne H, Turreira-García N, Rigal C, Vaast P, Ramalho JC, Marraccini P, Ræbild A (202c) Shaded-coffee: a nature-based strategy for coffee production under climate change? A review. Front Sustain Food Syst 6:877476. https://doi.org/10.3389/fsufs.2022.877476

Koutouleas A, Blunt C, Bregar A, Hansen JK, Ræbild A, Etienne H, Georget F (2023) Effects of interspecific grafting of *Coffea arabica* and elevation on coffee growth, yield, and quality attributes in Costa Rica. Sci Horvic 320:112162. https://doi.org/10.1016/j.scienta.2023.112162

Koutouleas A, Bosselmann AS, Rahn E (2025) Is agroforestry a sustainable management system for future coffee production? Advances in Botanical Research. Academic Press, Cambridge, pp 207-246

Kufa T, Burkhardt J (2015) Physiological growth response in seedlings of Arabica coffee genotypes under contrasting nursery microenvironments. Plant 3(5):47. https://doi.org/10.11648/j.plant.20150305.11

Kumar D, Tieszen LL (1980) Photosynthesis in *Coffea arabica*. I. Effects of light and temperature. Exp Agric 16(1):13-19. https://doi.org/10.1017/S0014479700010656

Kuznetsova A, Brockhoff PB, Christensen RH (2017) LmerT-est package: tests in linear mixed effects models. J Stat Softw 82(13):1-26

Labroo MR, Studer AJ, Rutkoski JE (2021) Heterosis and hybrid crop breeding: a multidisciplinary review. Front Genet 12:643761. https://doi.org/10.3389/fgene.2021.643761

Lashermes P, Combes MC, Robert J, Trouslot P, D'Hont A, Anthony F, Charrier A (1999) Molecular characterisation and origin of the *Coffea arabica* L. genome. Mol Gen Genet MGG 261(2):259-266. https://doi.org/10.1007/s004380050965

Lee DW, Baskaran K, Mansor M, Mohamad H, Yap SK (1996) Irradiance and spectral quality affect Asian tropical rain forest tree seedling development. Ecology 77:568-580. https://doi.org/10.2307/2265631

Lever J, Krzywinski M, Altman N (2017) Principal component analysis. Nat Methods 14:641-642. https://doi.org/10.1038/nmeth.4346

Li Y, Zhao M, Motesharrei S, Mu Q, Kalnay E, Li S (2015) Local cooling and warming effects of forests based on satellite observations. Nat Commun 6:6603. https://doi.org/10.1038/ncomms7603

Lichtenthaler HK, Buschmann C, Knapp M (2005) How to correctly determine the different chlorophyll fluorescence parameters and the chlorophyll fluorescence decrease ratio $R_{Fd}$ of leaves with the PAM fluorometer. Photosynthetica 43(3):379-393. https://doi.org/10.1007/s11099-005-0062-6

Marie L, Abdallah C, Campa C, Courtel P, Bordeaux M, Navarini L, Lonzarich V, Bosselmann AS, Turreira-García N, Alpizar E, Georget F (2020) G×E interactions on yield and quality in *Coffea arabica*: new F1 hybrids outperform American cultivars. Euphytica 216(5):1-17. https://doi.org/10.1007/s10681-020-02608-8

Marraccini, P., Vaast, P., Nguyen, T.T.H., Nguyen, T.Q.C., Vu, H.T., Nguyen, Q.T., Nguyen, T.D., Do, N.V., Georget, F., Pruvot-Woehl, S., & Luu, N.Q., (2019). BREEDCAFS (Breeding Coffee for Agroforestry Systems) project in Vietnam. CIRAD. https://agritrop.cirad.fr/592828/

Matos FS, Wolfgramm R, Gonçalves FV, Cavatte PC, Ventrella MC, DaMatta FM (2009) Phenotypic plasticity in response to light in the coffee tree. Environ Exp Bot 67(2):421-427. https://doi.org/10.1016/j.envexpbot.2009.06.018

Moat J, Williams J, Baena S, Wilkinson T, Gole TW, Challa ZK, Davis AP (2017) Resilience potential of the Ethiopian coffee sector under climate change. Nat Plants 3:17081. https://doi.org/10.1038/nplants.2017.81

Morais H, Medri ME, Anorim DP, Caramori PH, Ribeiro AMA (2003) Modifications in leaf anatomy of *Coffea arabica* caused by shade. Braz J Plant Physiol 15(2):107-116. https://doi.org/10.1590/S1677-04202003000200005

Muschler RG (2001) Shade improves coffee quality in a sub-optimal coffee-zone of Costa Rica. Agroforest Syst 51:131-139. https://doi.org/10.1023/A:1010603320653

Philippe L, Benoît B, Hervé E (2009) Breeding coffee (*Coffea arabica*) for sustainable production. *Breeding Plantation*
*Tree Crops: Tropical Species.* Springer, New York, pp 525–543

Piato K, Lefort F, Subía C, Caicedo C, Calderón D, Pico J et al (2020) Effects of shade trees on robusta coffee growth, yield and quality. A Meta-Anal Agron Sustain Dev 40:38. https://doi.org/10.1007/s13593-020-00642-3

Pohlan HAJ, Janssens MJ (2010) Growth and production of coffee. Soils, Plant Growth Crop Prod 3:101

R Core Team. (2019). *R: A language and environment for statistical computing* (Version 3.6.0) [Computer software]. R Foundation for Statistical Computing. https://www.R-project.org/

Rakocevic M, Janssens M, Scherer R (2012) Light responses and gender issues in the domestication process of yerba-mate, a subtropical evergreen. In: Bezerra AD, Ferreira TS (eds) Evergreens: Types, Ecology and Conservation. Nova Science Publishers, New York, pp 63–96

Rakocevic M, Braga KSM, Batista ER, Maia AHN, Scholz MBS, Filizola HF (2020) The vegetative growth assists to reproductive responses of Arabic coffee trees in a long-term FACE experiment. Plant Growth Regul 91(2):305–316. https://doi.org/10.1007/s10725-020-00607-2

Rakocevic M, Baroni DF, de Souza GAR, Bernado WDP, De Almeida CM, Matsunaga FT, Rodrigues WP, Ramalho JC, Campostrini E (2023) Correlating *Coffea canephora* 3D architecture to plant photosynthesis at a daily scale and vegetative biomass allocation. Tree Physiol 43(4):556–574. https://doi.org/10.1093/treephys/tpac138

Ricci MSF, Covre AM, Partelli FL, Vieira HD, Espindola MC (2011) Photosynthetic behavior of *Coffea arabica* and *C. canephora* under different light levels. Rev Bras De Fisiol Veg 23(2):203–213. https://doi.org/10.1590/S0103-31312 011000200009

Rigal, C., Nguyen, C., Hoang, T., Nguyen, V., Sarzynski, T., Marraccini, P., Vaast, P. & Etienne, H. 2023. Effect of shading on performances of new Arabica coffee varieties in Northwest Vietnam. ASIC.

Rodríguez-López NF, Martins SC, Cavatte PC, Silva PE, Morais LE, Pereira LF, Reis JV, Ávila RT, Godoy AG, Lavinski AO, DaMatta FM (2014) Morphological and physiological acclimations of coffee seedlings to growth over a range of fixed or changing light supplies. Environ Exp Bot 102:1–10. https://doi.org/10.1016/j.envexpbot. 2014.01.008

Salgado PR, Favarin JL, Leandro RA, Lima Filho OFD (2008) Total phenol concentrations in coffee tree leaves during fruit development. Scientia Agricola 65:354–359. https:// doi.org/10.1590/S0103-90162008000400005

Sera T (2001) Coffee genetic breeding at IAPAR. Cropp Breed Appl Biotechnol. https://doi.org/10.13082/1984-7033. v01n02a08

Sera, T., Shigueoka, L. H., Sera, G. H., Azevedo, J. A. D., Carvalho, F. G., & Andreazi, E. (2011). Nova seleção da cultivar de café Iapar 59 com grãos mais graúdos. http:// www.sapc.embrapa.br/arquivos/consorcio/spcb_anais/ simposio7/272.pdf

Siles P, Harmand JM, Vaast P (2010) Effects of *Inga densiflora* on the microclimate of coffee (*Coffea arabica* L.) and overall biomass under optimal growing conditions in Costa Rica. Agroforest Syst 78(3):269–286. https://doi. org/10.1007/s10457-009-9241-y

Toniutti L, Breitler JC, Etienne H, Campa C, Doulbeau S, Urban L, Lambot C, Pinilla JCH, Bertrand B (2017) Influence of environmental conditions and genetic background of arabica coffee (*C. arabica* L) on leaf rust (*Hemileia vastatrix*) pathogenesis. Front Plant Sci 8:2025. https:// doi.org/10.3389/fpls.2017.02025

Tscharntke T, Clough Y, Bhagwat SA, Buchori D, Faust H, Hertel D, Hölscher D, Juhrbandt J. Kessler M, Perfecto I, Scherber C (2011) Multifunctional shade-tree management in tropical agroforestry landscapes–a review. J Appl Ecol 48(3):619–629. https://doi.org/10.1111/j.1365-2664. 2010.01939.x

Vaast P, Bertrand B, Perriot JJ, Guyot B, Genard M (2006) Fruit thinning and shade improve bean characteristics and beverage quality of coffee (*Coffea arabica* L.) under optimal conditions. J Sci Food Agric 86(2):197–204. https:// doi.org/10.1002/jsfa.2338

van der Vossen H, Bertrand B, Charrier A (2015) Next generation variety development for sustainable production of arabica coffee (*Coffea arabica* L.): a review. Euphytica 204:243–256. https://doi.org/10.1007/s10681-015-1398-z

Villarreyna R, Avelino J, Cerda R (2020) Ecosystem-based adaptation: effect of shade trees on ecosystem services in coffee plantations. Agron Mesoam 31(2):499–516. https:// doi.org/10.15517/am.v31i2.37591

Zhang ZX, Cai ZQ, Liu GZ, Wang H, Huang L, Cai CT (2017) Effects of fertilization on the growth, photosynthesis, and biomass accumulation in juvenile plants of three coffee (*Coffea arabica* L.) cultivars. Photosynthetica. https://doi. org/10.1007/s11099-016-0237-3

**Publisher's Note** Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Terms and Conditions

Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”),
for small-scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are
maintained. By accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use
(“Terms”). For these purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.

These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription (to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will apply.

We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as detailed in the Privacy Policy.

While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that
Users may not:

1. use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access control;

2. use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is otherwise unlawful;

3. falsely or misleadingly imply or suggest endorsement, approval, sponsorship, or association unless explicitly agreed to by Springer Nature in writing;

4. use bots or other automated methods to access the content or redirect messages

5. override any security feature or exclusionary protocol; or

6. share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal content.

In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue, royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any other, institutional repository.

These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.

To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied with respect to the Springer Nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law, including merchantability or fitness for any particular purpose.

Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed from third parties.

If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not expressly permitted by these Terms, please contact Springer Nature at

onlineservice@springernature.com