Continuous Lighting and High Daily Light Integral Enhance Yield and Quality of Mass-Produced Nasturtium (Tropaeolum majus L.) in Plant Factories

Nasturtium (Tropaeolum majus L.), as a medicinal plant, has a high phenolic content in its leaves and flowers. It is often used in salads as a dietary vegetable. Attracting strong demand, it could be a good candidate crop for a plant factory with artificial lighting (PFAL) that can achieve the mass production of high-quality crops with high productivity by regulating environmental conditions such as light. In this study, two experiments were conducted to investigate the effects of continuous lighting (CL) and different daily light integrals (DLIs) under CL on the growth, secondary metabolites, and light use efficiency (LUE) of nasturtium, all of which are essential in the successful cultivation in PFALs. In Experiment 1, two lighting models, the same DLI of 17.3 mol m⁻² d⁻¹ but different light periods (24 and 16 h) with different light intensities (200 and 300 µmol m⁻² s⁻¹, respectively), were applied to nasturtium. The results showed that leaf production, secondary metabolites, and LUE were higher under the 24-h CL treatment than under the 16-h non-CL treatment. In Experiment 2, three DLI levels (17.3, 25.9, and 34.6 mol m⁻² d⁻¹) under the CL condition were applied. The results showed that the growth parameters were positively correlated with the DLI levels under CL. The lowest DLI had the highest LUE. We conclude that the mass production of nasturtium under CL in PFALs is feasible, and the yield increases as DLI increases from 17.3 to 34.6 mol m⁻² d⁻¹ under CL without causing physiological stress on plants.

Seasonal variation in photosynthetic rates and satellite-based GPP estimation over mangrove forest

In view of increasing anthropogenic influences and global changes, quantification of carbon assimilation through photosynthesis has gained tremendous significance. Precise estimation of Gross Primary Productivity (GPP) is essential for several ecosystem models and is typically done using coarser scale satellite data. The mangrove ecosystem, which offers significant protection to the coastal environment, is one of the critical habitats from a global change point of view. Light use efficiency (LUE) was measured using diurnal in situ photosynthetic rate observations for 13 dominant mangrove species for 3 seasons at each of the three mangrove dominant test-sites situated along the east and west coast of India. Variations in photosynthetic rates among these species were studied for 3 seasons that indicated varying responses of mangrove ecosystem at each site. Among all species, Rhizophora mucronata and Sonneratia apetala indicated higher values at two of the test-sites. IRS Resourcesat-2 LISS-IV datasets were used for the estimation of GPP. Mean GPP for all the sites varied from 1.2 to 7.7 g C m^-2 day^-1 with maximum value of 14.4 g C m^-2 day^-1. Mean values of GPP varied across the sites, based on its maximum LUE values and available photosynthetically active radiation (PAR). The results provide GPP values at much better spatial resolution for a threatened habitat like mangroves that typically survive in a narrow habitat along the coasts.

Monitoring tropical forests under a functional perspective with satellite-based vegetation optical depth

Monitoring ecosystem functions in forests is a priority in a climate change scenario, as climate-induced events may initially alter the functions more than slow-changing attributes, such as biomass. The ecosystem functional properties (EFPs) are quantities that characterize key ecosystem processes. They can be derived by point observations of gas and energy exchanges between the ecosystems and the atmosphere that are collected globally at FLUXNET flux tower sites and upscaled at ecosystem level. The properties here considered describe the ability of ecosystems to optimize the use of resources for carbon uptake. They represent functional forest information, are dependent on environmental drivers, linked to leaf traits and forest structure, and influenced by climate change effects. The ability of vegetation optical depth (VOD) to provide forest functional information is investigated using 2011-2014 satellite data collected by the Soil Moisture and Ocean Salinity mission and using the EFPs as reference dataset. Tropical forests in Africa and South America were analyzed, also according to ecological homogeneous units. VOD jointly with water deficit information explained 93% and 87% of the yearly variability in both flux upscaled maximum gross primary productivity and light use efficiency functional properties, in Africa and South America forests respectively. Maps of the retrieved properties evidenced changes in forest functional responses linked to anomalous climate-induced events during the study period. The findings indicate that VOD can support the flux upscaling process in the tropical range, affected by high uncertainty, and the detection of forest anomalous functional responses. Preliminary temporal analysis of VOD and EFP signals showed fine-grained variability in periodicity, in signal dephasing, and in the strength of the relationships. In selected drier forest types, these satellite data could also support the monitoring of functional dynamics.

Exploring the spatial relationship between airborne-derived red and far-red sun-induced fluorescence and process-based GPP estimates in a forest ecosystem

Terrestrial gross primary productivity (GPP) plays an essential role in the global carbon cycle, but the quantification of the spatial and temporal variations in photosynthesis is still largely uncertain. Our work aimed to investigate the potential of remote sensing to provide new insights into plant photosynthesis at a fine spatial resolution. This goal was achieved by exploiting high-resolution images acquired with the FLuorescence EXplorer (FLEX) airborne demonstrator HyPlant. The sensor was flown over a mixed forest, and the images collected were elaborated to obtain two independent indicators of plant photosynthesis. First, maps of sun-induced chlorophyll fluorescence (F), a novel indicator of plant photosynthetic activity, were successfully obtained at both the red and far-red peaks (r² = 0.89 and p < 0.01, r² = 0.77 and p < 0.01, respectively, compared to top-of-canopy ground-based measurements acquired synchronously with the overflight) over the forested study area. Second, maps of GPP and absorbed photosynthetically active radiation (APAR) were derived using a customised version of the coupled biophysical model Breathing Earth System Simulator (BESS). The model was driven with airborne-derived maps of key forest traits (i.e., leaf chlorophyll content (LCC) and leaf area index (LAI)) and meteorological data providing a high-resolution snapshot of the variables of interest across the study site. The LCC and LAI were accurately estimated (RMSE = 5.66 μg cm^-2 and RMSE = 0.51 m²m^-2, respectively) through an optimised Look-Up-Table-based inversion of the PROSPECT-4-INFORM radiative transfer model, ensuring the accurate representation of the spatial variation of these determinants of the ecosystem's functionality. The spatial relationships between the measured F and modelled BESS outputs were then analysed to interpret the variability of ecosystem functioning at a regional scale. The results showed that far-red F is significantly correlated with the GPP (r² = 0.46, p < 0.001) and APAR (r² = 0.43, p < 0.001) in the spatial domain and that this relationship is nonlinear. Conversely, no statistically significant relationships were found between the red F and the GPP or APAR (p > 0.05). The spatial relationships found at high resolution provide valuable insight into the critical role of spatial heterogeneity in controlling the relationship between the far-red F and the GPP, indicating the need to consider this heterogeneity at a coarser resolution.

Deconvolution of pigment and physiologically related photochemical reflectance index variability at the canopy scale over an entire growing season

The sensitivity of the photochemical reflectance index (PRI) to leaf pigmentation and its impacts on its potential as a proxy for light-use efficiency (LUE) have recently been shown to be problematic at the leaf scale. Most leaf-to-leaf and seasonal variability can be explained by such a confounding effect. This study relies on the analysis of PRI light curves that were generated at the canopy scale under natural conditions to derive a precise deconvolution of pigment-related and physiologically related variability in the PRI. These sources of variability were explained by measured or estimated physiologically relevant variables, such as soil water content, that can be used as indicators of water availability and canopy chlorophyll content. The PRI mainly reflected the variability in the pigment content of the canopy. However, the corrected PRI, which was obtained by subtracting the pigment-related seasonal variability from the PRI measurement, was highly correlated with the upscaled LUE measurements. Moreover, the sensitivity of the PRI to the leaf pigment content may mask the PRI versus LUE relationship or result in an artificial relationship that reflects the relationship of chlorophyll versus LUE, depending on the species phenology.

Optimizing illumination in the greenhouse using a 3D model of tomato and a ray tracer

Reduction of energy use for assimilation lighting is one of the most urgent goals of current greenhouse horticulture in the Netherlands. In recent years numerous lighting systems have been tested in greenhouses, yet their efficiency has been very difficult to measure in practice. This simulation study evaluated a number of lighting strategies using a 3D light model for natural and artificial light in combination with a 3D model of tomato. The modeling platform GroIMP was used for the simulation study. The crop was represented by 3D virtual plants of tomato with fixed architecture. Detailed data on greenhouse architecture and lamp emission patterns of different light sources were incorporated in the model. A number of illumination strategies were modeled with the calibrated model. Results were compared to the standard configuration. Moreover, adaptation of leaf angles was incorporated for testing their effect on light use efficiency (LUE). A Farquhar photosynthesis model was used to translate the absorbed light for each leaf into a produced amount of carbohydrates. The carbohydrates produced by the crop per unit emitted light from sun or high pressure sodium lamps was the highest for horizontal leaf angles or slightly downward pointing leaves, and was less for more upward leaf orientations. The simulated leaf angles did not affect light absorption from inter-lighting LED modules, but the scenario with LEDs shining slightly upward (20(°)) increased light absorption and LUE relative to default horizontal beaming LEDs. Furthermore, the model showed that leaf orientation more perpendicular to the string of LEDs increased LED light interception. The combination of a ray tracer and a 3D crop model could compute optimal lighting of leaves by quantification of light fluxes and illustration by rendered lighting patterns. Results indicate that illumination efficiency increases when the lamp light is directed at most to leaves that have a high photosynthetic potential.