Search

In vertical farms, the supplementation of far-red light has been widely applied to regulate plant growth and development. However, the relative contribution of far-red to photosynthesis and plant growth in indoor production systems is not sufficiently quantified. This study quantify the photosynthesis and growth responses under different levels of supplemental far-red in lettuce using a 3D modelling approach. Lettuce were cultivated under either white light or red to far-red (R:FR) ratio of 1.6 or 0.8. Measurements of plant morphological traits, leaf photosynthesis, and organ fresh and dry mass were taken and the 3D modelling approach was used to simulate plant photosynthesis and biomass accumulation. Results showed that leaf elevation angle, leaf expansion rate, and plant height significantly increased at each growth stage as the R:FR ratio decreased. Far-red light also promoted plant growth, leading to an increase in the dry and fresh weight of lettuce throughout the entire growth period. However, plants cultivated at low R:FR showed reduced maximum Rubisco carboxylation rate and maximum electron transport rate, which indicated that far-red light reduced the photosynthetic capacity in lettuce. Nevertheless, 3D model simulations demonstrated that plants exposed to enhanced far-red light exhibited increased light interception and whole-plant photosynthesis. The integrated analysis of photosynthetic parameters and plant morphological changes on the photosynthetic rate of the whole plant indicated that the positive effects of plant morphological changes outweighed the negative impacts of photosynthetic parameters. These results implied that far-red light-induced morphological changes enhanced light interception and whole-plant photosynthesis, thereby increased lettuce yield. [ABSTRACT FROM AUTHOR]

The conversion of supplemental greenhouse light energy into biomass is not always optimal. Recent trends in global energy prices and discussions on climate change highlight the need to reduce our energy footprint associated with the use of supplemental light in greenhouse crop production. This can be achieved by implementing "smart" lighting regimens which in turn rely on a good understanding of how fluctuating light influences photosynthetic physiology. Here, a simple fit-for-purpose dynamic model is presented. It accurately predicts net leaf photosynthesis under natural fluctuating light. It comprises two ordinary differential equations predicting: 1) the total stomatal conductance to CO2 diffusion and 2) the CO2 concentration inside a leaf. It contains elements of the Farquhar-von Caemmerer-Berry model and the successful incorporation of this model suggests that for tomato (Solanum lycopersicum L.), it is sufficient to assume that Rubisco remains activated despite rapid fluctuations in irradiance. Furthermore, predictions of the net photosynthetic rate under both 400ppm and enriched 800ppm ambient CO2 concentrations indicate a strong correlation between the dynamic rate of photosynthesis and the rate of electron transport. Finally, we are able to indicate whether dynamic photosynthesis is Rubisco or electron transport rate limited. [ABSTRACT FROM AUTHOR]

Under natural conditions, irradiance frequently fluctuates, causing net photosynthesis rate (A) to respond slowly and reducing the yields. We quantified the genotypic variation of photosynthetic induction in 19 genotypes among the following six horticultural crops: basil, chrysanthemum, cucumber, lettuce, tomato, and rose. Kinetics of photosynthetic induction and the stomatal opening were measured by exposing shade-adapted leaves (50 μmol m–2 s–1) to a high irradiance (1000 μmol m–2 s–1) until A reached a steady state. Rubisco activation rate was estimated by the kinetics of carboxylation capacity, which was quantified using dynamic A vs. [CO2] curves. Generally, variations in photosynthetic induction kinetics were larger between crops and smaller between cultivars of the same crop. Time until reaching 20–90% of full A induction varied by 40–60% across genotypes, and this was driven by a variation in the stomatal opening rather than Rubisco activation kinetics. Stomatal conductance kinetics were partly determined by differences in the stomatal size and density; species with densely packed, smaller stomata (e.g., cucumber) tended to open their stomata faster, adapting stomatal conductance more rapidly and efficiently than species with larger but fewer stomata (e.g., chrysanthemum). We conclude that manipulating stomatal traits may speed up photosynthetic induction and growth of horticultural crops under natural irradiance fluctuations. [ABSTRACT FROM AUTHOR]

• Φ 2 predicted P g,max reduction during drought. • Φ NO predicted incomplete P g,max recovery after drought. • SUCROS-CF model integrating relationships between P g,max , Φ 2 and Φ NO was developed. • SUCROS-CF predicted biomass 7% more accurately than SUCROS97 under severe drought. Predicting biomass production is important for assessing yield losses caused by drought. Photosynthesis-driven crop growth models, such as SUCROS97, tend to overestimate crop production under severe drought, as they ignore slow post-drought recovery kinetics of leaf photosynthesis. In this study, Lilium plants (L. auratum × speciosum 'Sorbonne') were subjected to mild, intermediate and severe drought with different durations (3, 5, 7 and 9 days) at two developmental stages (leaf unfolding and flower bud break stage). Leaf photosynthesis and chlorophyll fluorescence (CF) were measured during and after drought. We found that at both developmental stages, drought significantly reduced light-saturated gross photosynthesis rate (P g,max), which progressively recovered after re-watering. Under mild drought, P g,max recovered fully to non-stress levels by re-watering, whereas under intermediate and severe drought, P g,max did not recover fully. Drought occurring during leaf unfolding had a larger impact on biomass production than drought during bud break. Further, we identified a sigmoidal relationship (r 2 = 0.81) between P g,max and photosystem II operating efficiency (Φ 2) during drought, and highly linear relationships (r 2 = 0.88) between P g,max and the quantum yield of non-regulated energy dissipation (Φ NO) during post-drought recovery. We integrated the aforementioned relationships into SUCROS97, and the extended SUCROS-CF model explicitly accounted for slow and incomplete P g,max recovery in the post-drought phase. Compared to SUCROS97, SUCROS-CF improved biomass prediction by 7%, due to a 19% improvement in P g,max predictions under severe drought. We conclude that to accurately predict productivity during and after severe drought, leaf photosynthetic capacity kinetics need to be considered. Furthermore, CF measurements can be applied to predict leaf photosynthetic capacity during and after drought, enabling rapid drought phenotyping in breeding programs and yield loss assessment in the field. [ABSTRACT FROM AUTHOR]