Structural and functional changes in coffee trees after 4 years under free air CO2 enrichment

Carbon gain is coordinated with enhanced stomatal conductance and hydraulic architecture in coffee plants acclimated to elevated [CO2]: The interplay with irradiance supply

We recently demonstrated that, under elevated [CO2] (eCa), coffee (Coffea arabica L.) plants grown at high light (HL), but not at low light (LL), display higher stomatal conductance (gs) than at ambient [CO2] (aCa). We then hypothesized that the enhanced gs at eCa/HL, if sustained at the long-term, would lead to adjustments in hydraulic architecture. To test this hypothesis, potted plants of coffee were grown in open-top chambers for 12 months under HL or LL (ca. 9 or 1 mol photons m-2 day-1, respectively); these light treatments were combined with two [CO2] levels (ca. 437 or 705 μmol mol-1, respectively). Under eCa/HL, increased gs was closely accompanied by increases in branch and leaf hydraulic conductances, suggesting a coordinated response between liquid- and vapor-phase water flows throughout the plant. Still under HL, eCa also resulted in increased Huber value (sapwood area-to-total leaf area), sapwood area-to-stem diameter, and root mass-to-total leaf area, thus further improving the water supply to the leaves. Our results demonstrate that Ca is a central player in coffee physiology increasing carbon gain through a close association between stomatal function and an improved hydraulic architecture under HL conditions.

Crop/Plant Modeling Supports Plant Breeding: II. Guidance of Functional Plant Phenotyping for Trait Discovery

Observable morphological traits are widely employed in plant phenotyping for breeding use, which are often the external phenotypes driven by a chain of functional actions in plants. Identifying and phenotyping inherently functional traits for crop improvement toward high yields or adaptation to harsh environments remains a major challenge. Prediction of whole-plant performance in functional-structural plant models (FSPMs) is driven by plant growth algorithms based on organ scale wrapped up with micro-environments. In particular, the models are flexible for scaling down or up through specific functions at the organ nexus, allowing the prediction of crop system behaviors from the genome to the field. As such, by virtue of FSPMs, model parameters that determine organogenesis, development, biomass production, allocation, and morphogenesis from a molecular to the whole plant level can be profiled systematically and made readily available for phenotyping. FSPMs can provide rich functional traits representing biological regulatory mechanisms at various scales in a dynamic system, e.g., Rubisco carboxylation rate, mesophyll conductance, specific leaf nitrogen, radiation use efficiency, and source-sink ratio apart from morphological traits. High-throughput phenotyping such traits is also discussed, which provides an unprecedented opportunity to evolve FSPMs. This will accelerate the co-evolution of FSPMs and plant phenomics, and thus improving breeding efficiency. To expand the great promise of FSPMs in crop science, FSPMs still need more effort in multiscale, mechanistic, reproductive organ, and root system modeling. In summary, this study demonstrates that FSPMs are invaluable tools in guiding functional trait phenotyping at various scales and can thus provide abundant functional targets for phenotyping toward crop improvement.

Growth and Leaf Gas Exchange Upregulation by Elevated [CO2] Is Light Dependent in Coffee Plants

Coffee (Coffea arabica L.) plants have been assorted as highly suitable to growth at elevated [CO₂] (eC_a), although such suitability is hypothesized to decrease under severe shade. We herein examined how the combination of eC_a and contrasting irradiance affects growth and photosynthetic performance. Coffee plants were grown in open-top chambers under relatively high light (HL) or low light (LL) (9 or 1 mol photons m^-2 day^-1, respectively), and aC_a or eC_a (437 or 705 μmol mol^-1, respectively). Most traits were affected by light and CO₂, and by their interaction. Relative to aC_a, our main findings were (i) a greater stomatal conductance (g_s) (only at HL) with decreased diffusive limitations to photosynthesis, (ii) greater g_s during HL-to-LL transitions, whereas g_s was unresponsive to the LL-to-HL transitions irrespective of [CO₂], (iii) greater leaf nitrogen pools (only at HL) and higher photosynthetic nitrogen-use efficiency irrespective of light, (iv) lack of photosynthetic acclimation, and (v) greater biomass partitioning to roots and earlier branching. In summary, eC_a improved plant growth and photosynthetic performance. Our novel and timely findings suggest that coffee plants are highly suited for a changing climate characterized by a progressive elevation of [CO₂], especially if the light is nonlimiting.

Physiological and Molecular Responses of Woody Plants Exposed to Future Atmospheric CO2 Levels under Abiotic Stresses

Climate change is mainly driven by the accumulation of carbon dioxide (CO2) in the atmosphere in the last century. Plant growth is constantly challenged by environmental fluctuations including heat waves, severe drought and salinity, along with ozone accumulation in the atmosphere. Food security is at risk in an increasing world population, and it is necessary to face the current and the expected effects of global warming. The effects of the predicted environment scenario of elevated CO2 concentration (e[CO2]) and more severe abiotic stresses have been scarcely investigated in woody plants, and an integrated view involving physiological, biochemical and molecular data is missing. This review highlights the effects of elevated CO2 in the metabolism of woody plants and the main findings of its interaction with abiotic stresses, including a molecular point of view, aiming to improve the understanding of how woody plants will face the predicted environmental conditions. Overall, e[CO2] stimulates photosynthesis and growth and attenuates mild to moderate abiotic stress in woody plants if root growth and nutrients are not limited. Moreover, e[CO2] does not induce acclimation in most tree species. Some high-throughput analyses involving omics techniques were conducted to better understand how these processes are regulated. Finally, knowledge gaps in the understanding of how the predicted climate condition will affect woody plant metabolism were identified, with the aim of improving the growth and production of this plant species.

A meta-analysis of responses of C3 plants to atmospheric CO2 : dose-response curves for 85 traits ranging from the molecular to the whole-plant level

Generalised dose-response curves are essential to understand how plants acclimate to atmospheric CO₂ . We carried out a meta-analysis of 630 experiments in which C₃ plants were experimentally grown at different [CO₂ ] under relatively benign conditions, and derived dose-response curves for 85 phenotypic traits. These curves were characterised by form, plasticity, consistency and reliability. Considered over a range of 200-1200 µmol mol^-1 CO₂ , some traits more than doubled (e.g. area-based photosynthesis; intrinsic water-use efficiency), whereas others more than halved (area-based transpiration). At current atmospheric [CO₂ ], 64% of the total stimulation in biomass over the 200-1200 µmol mol^-1 range has already been realised. We also mapped the trait responses of plants to [CO₂ ] against those we have quantified before for light intensity. For most traits, CO₂ and light responses were of similar direction. However, some traits (such as reproductive effort) only responded to light, others (such as plant height) only to [CO₂ ], and some traits (such as area-based transpiration) responded in opposite directions. This synthesis provides a comprehensive picture of plant responses to [CO₂ ] at different integration levels and offers the quantitative dose-response curves that can be used to improve global change simulation models.

Leaf gas exchange and bean quality fluctuations over the whole canopy vertical profile of Arabic coffee cultivated under elevated CO2

Leaves in different positions respond differently to dynamic fluctuations in light availability, temperature and to multiple environmental stresses. The current hypothesis states that elevated atmospheric CO2 (e[CO2]) can compensate for the negative effects of water scarcity regarding leaf gas exchanges and coffee bean quality traits over the canopy vertical profile, in interactions with light and temperature microclimate during the two final stages of berry development. Responses of Coffea arabica L. were observed in the 5th year of a free air CO2 enrichment experiment (FACE) under water-limited rainfed conditions. The light dependent leaf photosynthesis curves (A/PAR) were modelled for leaves sampled from vertical profile divided into four 50-cm thick layers. e[CO2] significantly increased gross photosynthesis (AmaxGross), the apparent quantum yield efficiency, light compensation point, light saturation point (LSP) and dark respiration rate (Rd). As a specific stage response, considering berry ripening, all parameters calculated from A/PAR were insensitive to leaf position over the vertical profile. Lack of a progressive increase in AmaxGross and LSP was observed over the whole canopy profile in both stages, especially in the two lowest layers, indicating leaf plasticity to light. Negative correlation of Rd to leaf temperature (TL) was observed under e[CO2] in both stages. Under e[CO2], stomatal conductance was also negatively correlated with TL, reducing leaf transpiration and Rd even with increasing TL. This indicated coffee leaf acclimation to elevated temperatures under e[CO2] and water restriction. The e[CO2] attenuation occurred under water restriction, especially in A and water use efficiency, in both stages, with the exception of the lowest two layers. Under e[CO2], coffee produced berries in moderate- and high light level layers, with homogeneous distribution among them, contrasted to the heterogeneous distribution under actual CO2. e[CO2] led to increased caffeine content in the highest layer, with reduction of chlorogenic acid and lipids under moderate light and to raised levels of sugar in the shaded low layer. The ability of coffee to respond to e[CO2] under limited soil water was expressed through the integrated individual leaf capacities to use the available light and water, resulting in final plant investments in new reproductive structures in moderate and high light level layers.

Biomass and Leaf Acclimations to Ultraviolet Solar Radiation in Juvenile Plants of Coffea arabica and C. canephora

Despite the negative impacts of increased ultraviolet radiation intensity on plants, these organisms continue to grow and produce under the increased environmental UV levels. We hypothesized that ambient UV intensity can generate acclimations in plant growth, leaf morphology, and photochemical functioning in modern genotypes of Coffea arabica and C. canephora. Coffee plants were cultivated for ca. six months in a mini greenhouse under either near ambient (UVam) or reduced (UVre) ultraviolet regimes. At the plant scale, C. canephora was substantially more impacted by UVam when compared to C. arabica, investing more carbon in all juvenile plant components than under UVre. When subjected to UVam, both species showed anatomic adjustments at the leaf scale, such as increases in stomatal density in C. canephora, at the abaxial and adaxial cuticles in both species, and abaxial epidermal thickening in C. arabica, although without apparent impact on the thickness of palisade and spongy parenchyma. Surprisingly, C. arabica showed more efficient energy dissipation mechanism under UVam than C. canephora. UVam promoted elevated protective carotenoid content and a greater use of energy through photochemistry in both species, as reflected in the photochemical quenching increases. This was associated with an altered chlorophyll a/b ratio (significantly only in C. arabica) that likely promoted a greater capability to light energy capture. Therefore, UV levels promoted different modifications between the two Coffea sp. regarding plant biomass production and leaf morphology, including a few photochemical differences between species, suggesting that modifications at plant and leaf scale acted as an acclimation response to actual UV intensity.

Elevated [CO2] benefits coffee growth and photosynthetic performance regardless of light availability

Despite being evolved in shaded environments, most coffee (Coffea arabica L.) is cultivated worldwide under sparse shade or at full sunlight. Coffee is ranked as greatly responsive to climate change (CC), and shading has been considered an important management strategy for mitigating the harmful CC outcomes on the crop. However, there is no information on the effects of enhanced [CO₂] (eC_a) on coffee performance in response to light availability. Here, we examined how carbon assimilation and use are affected by eC_a in combination with contrasting light levels. For that, greenhouse-grown plants were submitted to varying light levels (16 or 7.5 mol photons m^-2 day^-1) and [CO₂] (ca. 380 or 740 μmol mol^-1 air) over six months. We demonstrated that both high light and eC_a improved growth and photosynthetic performance, independently. Despite marginal alterations in biomass partitioning, some allometric changes, such as higher root biomass-to-total leaf area and lower leaf area ratio under the combination of eC_a and high light were found. Stimulation of photosynthetic rates by eC_a occurred with no direct effect on stomatal and mesophyll conductances, and no signs of photosynthetic down-regulation were found irrespective of treatments. Particularly at high light, eC_a led to decreases in both photorespiration rates and oxidative pressure. Overall, our novel findings suggest that eC_a could tandemly act with shading to mitigate the harmful CC effects on coffee sustainability.

The main effects of elevated CO2 and soil-water deficiency on 1H NMR-based metabolic fingerprints of Coffea arabica beans by factorial and mixture design

The metabolic response of Coffea arabica trees in the face of the rising atmospheric concentration of carbon dioxide (CO₂) combined with the reduction in soil-water availability is complex due to the various (bio)chemical feedbacks. Modern analytical tools and the experimental advance of agronomic science tend to advance in the understanding of the metabolic complexity of plants. In this work, Coffea arabica trees were grown in a Free-Air Carbon Dioxide Enrichment dispositive under factorial design (2²) conditions considering two CO₂ levels and two soil-water availabilities. The ¹H NMR mixture design-fingerprinting effects of CO₂ and soil-water levels on beans were strategically investigated using the principal component analysis (PCA), analysis of variance (ANOVA) - simultaneous component analysis (ASCA) and partial least squares-discriminant analysis (PLS-DA). From the ASCA, the CO₂ factor had a significant effect on changing the ¹H NMR profile of fingerprints. The soil-water factor and interaction (CO₂ × soil-water) were not significant. ¹H NMR fingerprints with PCA, ASCA and PLS-DA analysis determined spectral profiles for fatty acids, caffeine, trigonelline and glucose increases in beans from current CO₂, while quinic acid/chlorogenic acids, malic acid and kahweol/cafestol increased in coffee beans from elevated CO₂. PLS-DA results revealed a good classification performance between the significant effect of the atmospheric CO₂ levels on the fingerprints, regardless of the soil-water availabilities. Finally, the PLS-DA model showed good prediction ability, successfully classifying validation data-set of coffee beans collected over the vertical profile of the plants and included several fingerprints of different extracting solvents. The results of this investigation suggest that the association of experimental design, mixture design, PCA, ASCA and PLS-DA can provide accurate information on a series of metabolic changes provoked by climate changes in products of commercial importance, in addition to minimizing the extra work necessary in classic analytical approaches, encouraging the development of similar strategies.

Transcriptomic Leaf Profiling Reveals Differential Responses of the Two Most Traded Coffee Species to Elevated [CO2]

As atmospheric [CO₂] continues to rise to unprecedented levels, understanding its impact on plants is imperative to improve crop performance and sustainability under future climate conditions. In this context, transcriptional changes promoted by elevated CO₂ (eCO₂) were studied in genotypes from the two major traded coffee species: the allopolyploid Coffea arabica (Icatu) and its diploid parent, C. canephora (CL153). While Icatu expressed more genes than CL153, a higher number of differentially expressed genes were found in CL153 as a response to eCO₂. Although many genes were found to be commonly expressed by the two genotypes under eCO₂, unique genes and pathways differed between them, with CL153 showing more enriched GO terms and metabolic pathways than Icatu. Divergent functional categories and significantly enriched pathways were found in these genotypes, which altogether supports contrasting responses to eCO₂. A considerable number of genes linked to coffee physiological and biochemical responses were found to be affected by eCO₂ with the significant upregulation of photosynthetic, antioxidant, and lipidic genes. This supports the absence of photosynthesis down-regulation and, therefore, the maintenance of increased photosynthetic potential promoted by eCO₂ in these coffee genotypes.

A functional-structural plant model that simulates whole- canopy gas exchange of grapevine plants (Vitis vinifera L.) under different training systems

BACKGROUND AND AIMS

Scaling from single-leaf to whole-canopy photosynthesis faces several complexities related to variations in light interception and leaf properties. To evaluate the impact of canopy strucuture on gas exchange, we developed a functional-structural plant model to upscale leaf processes to the whole canopy based on leaf N content. The model integrates different models that calculate intercepted radiation, leaf traits and gas exchange for each leaf in the canopy. Our main objectives were (1) to introduce the gas exchange model developed at the plant level by integrating the leaf-level responses related to canopy structure, (2) to test the model against an independent canopy gas exchange dataset recorded on different plant architectures, and (3) to quantify the impact of intra-canopy N distribution on crop photosynthesis.

METHODS

The model combined a 3D reconstruction of grapevine (Vitis vinifera) canopy architecture, a light interception model, and a coupled photosynthesis and stomatal conductance model that considers light-driven variations in N distribution. A portable chamber device was constructed to measure whole-plant gas exchange to validate the model outputs with data collected on different training systems. Finally, a sensitivity analysis was performed to evaluate the impact on C assimilation of different N content distributions within the canopy.

KEY RESULTS

By considering a non-uniform leaf N distribution within the canopy, our model accurately reproduced the daily pattern of gas exchange of different canopy architectures. The gain in photosynthesis permitted by the non-uniform compared with a theoretical uniform N distribution was about 18 %, thereby contributing to the maximization of C assimilation. By contrast, considering a maximal N content for all leaves in the canopy overestimated net CO2 exchange by 28 % when compared with the non-uniform distribution.

CONCLUSIONS

The model reproduced the gas exchange of plants under different training systems with a low error (10 %). It appears to be a reliable tool to evaluate the impact of a grapevine training system on water use efficiency at the plant level.

The influence of rising tropospheric carbon dioxide and ozone on plant productivity

Human activities result in a wide array of pollutants being released to the atmosphere. A number of these pollutants have direct effects on plants, including carbon dioxide (CO2 ), which is the substrate for photosynthesis, and ozone (O3 ), a damaging oxidant. How plants respond to changes in these atmospheric air pollutants, both directly and indirectly, feeds back on atmospheric composition and climate, global net primary productivity and ecosystem service provisioning. Here we discuss the past, current and future trends in emissions of CO2 and O3 and synthesise the current atmospheric CO2 and O3 budgets, describing the important role of vegetation in determining the atmospheric burden of those pollutants. While increased atmospheric CO2 concentration over the past 150 years has been accompanied by greater CO2 assimilation and storage in terrestrial ecosystems, there is evidence that rising temperatures and increased drought stress may limit the ability of future terrestrial ecosystems to buffer against atmospheric emissions. Long-term Free Air CO2 or O3 Enrichment (FACE) experiments provide critical experimentation about the effects of future CO2 and O3 on ecosystems, and highlight the important interactive effects of temperature, nutrients and water supply in determining ecosystem responses to air pollution. Long-term experimentation in both natural and cropping systems is needed to provide critical empirical data for modelling the effects of air pollutants on plant productivity in the decades to come.

Potential biomonitoring of atmospheric carbon dioxide in Coffea arabica leaves using near-infrared spectroscopy and partial least squares discriminant analysis

The potencial of Coffea arabica leaves as bioindicators of atmospheric carbon dioxide (CO₂) was evaluated in a free-air carbon dioxide enrichment (FACE) experiment by using near-infrared reflectance (NIR) spectroscopy for direct analysis and partial least squares discriminant analysis (PLS-DA). A supervised classification model was built and validated from the spectra of coffee leaves grown under elevated and current CO₂ levels. PLS-DA allowed correct test set classification of 92% of the elevated-CO₂ level leaves and 100% of the current-CO₂ level leaves. The spectral bands accounting for the discrimination of the elevated-CO₂ leaves were at 1657 and 1698 nm, as indicated by the variable importance in the projection (VIP) score together with the regression coefficients. Seven months after suspension of enriched CO₂, returning to current-CO₂ levels, new spectral measurements were made and subjected to PLS-DA analysis. The predictive model correctly classified all leaves as grown under current-CO₂ levels. The fingerprints suggest that after suspension of elevated-CO₂, the spectral changes observed previously disappeared. The recovery could be triggered by two reasons: the relief of the stress stimulus or the perception of a return of favorable conditions. In addition, the results demonstrate that NIR spectroscopy can provide a rapid, nondestructive, and environmentally friendly method for biomonitoring leaves suffering environmental modification. Finally, C. arabica leaves associated with NIR and mathematical models have the potential to become a good biomonitoring system.

Variations in leaf growth parameters within the tree structure of adult Coffea arabica in relation to seasonal growth, water availability and air carbon dioxide concentration

BACKGROUND AND AIMS

Dynamics in branch and leaf growth parameters, such as the phyllochron, duration of leaf expansion, leaf life span and bud mortality, determine tree architecture and canopy foliage distribution. We aimed to estimate leaf growth parameters in adult Arabica coffee plants based on leaf supporter axis order and position along the vertical profile, considering their modifications related to seasonal growth, air [CO2] and water availability.

METHODS

Growth and mortality of leaves and terminal buds of adult Arabica coffee trees were followed in two independent field experiments in two sub-tropical climate regions of Brazil, Londrina-PR (Cfa) and Jaguariúna-SP (Cwa). In the Cwa climate, coffee trees were grown under a FACE (free air CO2 enrichment) facility, where half of those had been irrigated. Plants were observed at a 15-30 d frequency for 1 year. Leaf growth parameters were estimated on five axes orders and expressed as functions of accumulated thermal time (°Cd per leaf).

KEY RESULTS

The phyllochron and duration of leaf expansion increased with axis order, from the seond to the fourth. The phyllochron and life span during the reduced vegetative seasonal growth were greater than during active growth. It took more thermal time for leaves from the first- to fourth-order axes to expand their blades under irrigation compared with rainfed conditions. The compensation effects of high [CO2] for low water availability were observed on leaf retention on the second and third axes orders, and duration of leaf expansion on the first- and fourth-order axes. The second-degree polynomials modelled leaf growth parameter distribution in the vertical tree profile, and linear regressions modelled the proportion of terminal bud mortality.

CONCLUSIONS

Leaf growth parameters in coffee plants were determined by axis order. The duration of leaf expansion contributed to phyllochron determination. Leaf growth parameters varied according the position of the axis supporter along the vertical profile, suggesting an effect of axes age and micro-environmental light modulations.

Computational botany: advancing plant science through functional–structural plant modelling

The need to integrate the ever-expanding body of knowledge in the plant sciences has led to the development of sophisticated modelling approaches. This special issue focuses on functional–structural plant (FSP) models, which are the result of cross-fertilization between the domains of plant science, computer science and mathematics. FSP models simulate growth and morphology of individual plants that interact with their environment, from which complex plant community properties emerge. FSP models can be used for a broad range of research questions across disciplines related to plant science. This special issue presents the latest developments in FSP modelling, including the novel incorporation of plant ecophysiological concepts and the application of FSP models to address new scientific questions. Additionally, it illustrates the breadth of model evaluation approaches that are performed. FSP modelling is a very active domain of plant research which brings together a wide range of scientific disciplines. It offers the opportunity to address questions in complex plant systems that cannot be addressed by empirical approaches alone, including questions on fundamental concepts related to plant development such as regulation of morphogenesis, as well as on applied concepts such as the relationship between crop performance and plant competition for resources.