Canopy Photosynthetic Rate Research Articles

Interrelations between Canopy Architecture and Growth Yield Attribute on Selected Growth Habit Peanut Genotypes

Background: Crop architecture plays a major role in the growth and development of semi determinate crops like peanut.The orientation of branches and leaves in the plant canopy plays a major role in the radiation penetration, which influences the canopy photosynthetic rate and hence the crop productivity. Light penetration and radiation use efficiency effect the drymatter production of many crops. However, links between canopy orientation, growth attributes and yield potentiality of peanut are poorly understood. Hence the aim of the present study was to determine interrelationships among various growth habit peanut genotypes for canopy architecture, canopy photosynthesis, growth parameters and yield attributes. Methods: The experiment was laid out in a randomized block design with ten treatments and replicated thrice. Ten spanish bunch peanut genotypes varying in growth habits viz., decumbent-2, decumbent-3 and erect growth habit.Five plants were selected randomly in each plot by avoiding border rows and recorded canopy traits. Canopy photosynthetic parameters viz., light interception (Lux meter) and photosynthetic rate (IRGA) were recorded at the grand growth period (45 and 60 DAS). Result: Plant height had a significant negative correlation with peg to pod ratio. Among the various canopy architecture traits, wider angle between primary branch and main stem and number of secondary branches per plant established significantly positive correlation with rate of photosynthesis, radiation use efficiency, growth attributes, pod yield, shelling percentage and test weight. Spreading architecture exhibit a higher maximum quantum yield of photosynthesis.

Evaluation of Growth and Photosynthetic Rate of Cucumber Seedlings Affected by Far-Red Light Using a Semi-Open Chamber and Imaging System

Far-red light was excluded in photosynthetic photon flux; however, recent studies have shown that it increases photosynthetic capacity. In addition, there were few studies on the whole canopy photosynthetic rate and continuous changes of morphology on cucumber seedlings affected by far-red light. This study evaluated the effect of conventional white LEDs adding far-red light on cucumber seedlings using a semi-open chamber system for the measurement of the whole canopy gas exchange rate, and the Raspberry Pi-based imaging system for the analysis of a continuous image. In the image, through the imaging system, it was confirmed that far-red light promoted the germination rate of cucumber seedlings and enhanced early growth. However, the dry weight of the shoot and root did not increase. The measured net apparent CO2 assimilation rate was improved by an increasing leaf area during the cultivation period. The conventional white LED light source with added far-red light increased the photosynthetic rate of cucumber seedlings’ whole canopy. However, at the early seedling stage, plant height and leaf area of the whole canopy was increased by far-red light, and it was revealed that the image data saturated faster. It was considered that the photosynthetic efficiency decreased due to a shading effect of the limited planting density of the cell tray. The results found that using appropriate far-red light, considering planting density, could increase the photosynthetic rate of the whole canopy of crops, thereby promoting crop growth, but it was judged that the use of far-red light in the early growth stage of cucumber seedlings should be considered carefully.

Ray-tracing analysis on the far-red induced light-capturing ability of kale

Far-red (FR, 700–800 nm) light has recently been used to regulate phytochrome-mediated morphological responses in vertical farms. Long-term morphological changes in different FR intensities are well known, but changes in photosynthetic capacity have not been sufficiently investigated. The objectives of this study were to quantitatively analyze the growth, photosynthetic responses, and light interception of kale (Brassica oleracea L. var. acephala) depending on the FR fraction. The plants were cultivated at a photosynthetic photon flux density (PPFD) of 240 μmol m−2 s−1 under red and white LEDs with FR LED (peak at 730 nm) for 16 h. The FR fractions determined as FR/R+FR were FR0.07 (control), FR0.28, FR0.60, and FR0.72. To evaluate the morphological and physiological responses in each FR fraction, the growth, chlorophyll content, chlorophyll fluorescence, P700 absorbance change, and photosynthetic rate were measured. Light interception was quantitatively calculated using 3D-scanned plant models with physiological changes and ray-tracing simulations. The dry weight of shoot and root, total petiole length, and leaf area increased with increasing FR fractions. As a result of ray-tracing analysis, the light interception and canopy photosynthetic rate increased with high FR fraction treatment. As the FR fraction increased, the effective quantum yield of photosystem II [Y(II)], the parameters of the JIP test that is related to quantum yield and efficiency for electron transport in photosystem II and photosystem performance indices decreased. Despite the decreased electron transport efficiency, the canopy photosynthetic rate increased in relation to the FR fraction. In conclusion, the increase in the FR fraction increased the yield of kale because of the synergistic improvement in morphological change and canopy photosynthesis.

Optimal water and nitrogen management increases cotton yield through improving leaf number and canopy light environment

Recently-published information on cotton agronomic and light energy use responses to nitrogen (N) under varying water availability is limited in Xinjiang, northwest China. A two-year field experiment was conducted to evaluate the effects of two irrigation patterns (I 400 , conventional irrigation; I 267 , limited irrigation) and three N fertilizer rates (N 320 , 320; N 272 , 272; N 224 , 224 kg N ha −1 ) on leaf number (LN), mean inclination angle (MIA) of leaves, light interception rate (LIR), dry matter accumulation, and seed cotton yield. Under the I 400 condition, seed cotton yield for N 272 was comparable to that for N 320 , but 9.6% higher than that for N 224 . Compared with N 320 , N 272 plots exhibited a 4.7% reduction in biological yield and 4.9% increase in harvest index. N 272 I 400 slightly reduced the leaf number and increased the MIA of the top-canopy, and improved the LN and LIR in the middle canopy, canopy photosynthetic rate (CAP), and dry matter accumulation. In contrast, under I 267 conditions, N 320 significantly increased leaf area and achieved the better LIR, dry matter accumulation, and yield than N 272 and N 224 . The LIR induced by the variation in leaf number was strongly associated with CAP and dry matter accumulation. The LN of the middle canopy likely represented the strong link in photosynthetic response to N rate and water supply. Leaf number was strongly associated with leaf area and was negatively correlated with MIA. These results suggest that leaf number is a key regulatory factor for regulating canopy leaf inclination and light interception. We suggest that estimates of light energy utilization should be included along with leaf number estimates in future efforts to scale from leaf physiology to canopy construction in cotton. • The leaf number determines the canopy light environment and yield of cotton. • Optimal leaf number of middle canopy promoted light interception, photosynthesis capacity, and dry matter production. • N-induced changes in leaf number are important factors in regulating the leaf angle and light capture. • Nitrogen rate for high-yield cotton should be adjusted based on water availability.

Hybrid AI model for estimating the canopy photosynthesis of eggplants.

Modern models for estimating canopy photosynthetic rates (Ac) can be broadly classified into two categories, namely, process-based mechanistic models and artificial intelligence (AI) models, each category having unique strengths (i.e., process-based models have generalizability to a wide range of situations, and AI models can reproduce a complex process using data without prior knowledge about the underlying mechanism). To exploit the strengths of both categories of models, a novel "hybrid" canopy photosynthesis model that combines process-based models with an AI model was proposed. In the proposed hybrid model, process-based models for single-leaf photosynthesis and image analysis first transform raw inputs (environmental data and canopy images) into the single-leaf photosynthetic rate (AL) and effective leaf area index (Lc)), after which AL and Lc are fed into an artificial neural network (ANN) model to predict Ac. The hybrid model successfully predicted the diurnal cycles of Ac of an eggplant canopy even with a small training dataset and successfully reproduced a typical Ac response to changes in the CO2 concentration outside the range of the training data. The proposed hybrid AI model can provide an effective means to estimate Ac in actual crop fields, where obtaining a large amount of training data is difficult.

Modelling Fagus sylvatica stem growth along a wide thermal gradient in Italy by incorporating dendroclimatic classification and land surface phenology metrics.

Calibrating land surface phenology (LSP) with tree rings is important to model spatio-temporal variations in forest productivity. We used MODIS (resolution: 250m) NDVI, WDRVI and EVI series 2000-2014 to derive LSP metrics quantifying phenophase timing and canopy photosynthetic rates of 26 European beech forests covering a large thermal gradient (5-16°C) in Italy. Average phenophase timing changed greatly with site temperature (e.g. growing season 70days longer at low- than high-elevation); average VI values were affected by precipitation. An annual temperature about 12°C (c. 1100m asl) represented a bioclimatic threshold dividing warm from cold beech forests, distinguished by different phenology-BAI (basal area increment) relationships and LSP trends. Cold forests showed decreasing VI values (browning) and delayed phenophases and had negative BAI slopes. Warmer forests tended to increase VI (greening), and positive BAI slopes. NDVI peak, commonly used in global trend assessments, changed with elevation in agreement with changes in wood production. A cross-validation modelling approach demonstrated the ability of LSP to predict average BAI and its interannual variability. Merging sites into bioclimatic groups improved models by amplifying the signal in growth or LSP. NDVI had highest performances when informing on BAI trends; WDRVI and EVI were mostly selected for modelling mean and interannual BAI. WDRVI association with tree rings, tested in this study for the first time, showed that this VI is highly promising for studying forest dynamics. MODIS LSP can quantify forest functioning changes across landscapes and model interannual spatial variations and trends in productivity dynamics under climate change.

Nitrogen rate for cotton should be adjusted according to water availability in arid regions

Recent reports on cotton water use and root-canopy relationship responses to nitrogen (N) fertilizer management under varying water supply in arid regions are limited. This experiment was conducted to estimate cotton water use, root-canopy development, canopy photosynthetic rate (CAP), and yield responses to N application rates under varying water supply levels and to quantify associations between water use processes and N-induced variation in root systems. A two-year field experiment was conducted from 2019 to 2020 at a field site in Xinjiang, China. Cotton root traits and agronomic responses to three N fertilizer application rates (320, 272, and 224 kg N ha −1 ) under two water supply levels (sufficient water supply: 400 mm; limited water supply: 267 mm) were evaluated. Root length density and root dry matter were maximized at 272 kg N ha −1 under sufficient water supply and 320 kg N ha −1 under limited water supply. CAP was strongly associated with crop stage water use induced by root-canopy variation. Under sufficient water, 272 kg N ha −1 substantially increased water use and root growth, slightly inhibited leaf expansion, and substantially improved crop yield compared to 320 and 224 kg N ha −1 . Although net root productivity and live root length declined for 320 kg N ha −1 under limited water supply, yield increase was not limited because of higher CAP and water use induced by the establishment of strong shallow roots. The results demonstrate that moderate N rate (272 kg ha −1 ) under sufficient water supply improves yield through reducing LAI and promoting root growth, while higher N rate (320 kg ha −1 ) under limited water supply achieves high yield through higher CAP, sufficient leaf area, and efficient water uptake under shallow root systems. These findings suggest that both N management strategies and water availability levels should be considered in future efforts to scale from canopy to root level responses in cotton. • The development of roots and canopy jointly determined the water use capacity in crops. • Improving the water use promoted aboveground CAP, dry matter accumulation, and seed cotton yield. • Two N strategies for high cotton yield were proposed under sufficient water and limited water supply. • Root length dynamics from minirhizotron can reflect the crop stage water use during growing season.

A canopy photosynthesis model based on a highly generalizable artificial neural network incorporated with a mechanistic understanding of single-leaf photosynthesis

• A canopy photosynthesis model was built based on an artificial neural network (ANN) • The model was combined with a process-based single-leaf photosynthesis model • The model could predict the canopy photosynthetic rate under various environments • The model was highly generalizable even when training data were scarce Crop productivity is largely dependent on canopy photosynthesis, which is difficult to measure at farming sites. Therefore, real-time estimation of the canopy photosynthetic rate ( A c ) is expected to facilitate effective farm management. For the estimation of A c , two types of mathematical models ( i.e ., process-based models and empirical models) have been used, although both types have their own weaknesses. Process-based models inevitably require many model parameters that are difficult to identify, while empirical models, including artificial neural network (ANN) models, have a low predictive ability outside of the range of training datasets. To overcome these weaknesses, we developed a hybrid canopy photosynthesis model that included components of both process-based models and ANN models. In this hybrid model, the single-leaf photosynthetic rate ( A L ) and leaf area index (LAI) were first estimated from information easily obtainable at farming sites: A L was estimated by the process-based model of A L ( i.e ., the biochemical photosynthesis model of Farquhar et al . (1980)) from environmental data (photosynthetic photon flux density (PPFD), air temperature ( T a ), humidity, and atmospheric CO 2 concentration ( C a )), and the LAI was estimated by an analysis of crop canopy imagery. As highly explainable information for A c , the estimated A L and LAI were input into the ANN model to estimate A c . As such, the ANN model learned the logical relationships between the inputs ( A L and LAI) and the output ( A c ). Detailed validation analysis using nine spinach A c datasets revealed that the hybrid ANN model can estimate A c accurately throughout the whole growth period, even when training and test datasets were obtained in different seasons under different CO 2 concentrations and based on training datasets of only three days. This study highlights the high generalizability of the hybrid ANN model, which is a prerequisite for practical application in environmentally controlled crop production.

Estimation of Photosynthesis Loss Due to Greenhouse Superstructures and Shade Nets: A Case Study with Paprika and Tomato Canopies

In horticultural greenhouses, the photosynthetic photon flux density (I) is inevitably lower than that outside because of interference from greenhouse superstructures (e.g., reflection and absorption of radiation by greenhouse coverings and superstructures). In addition, during hot seasons in many regions, I can be lowered by shade nets installed to reduce excessive radiation. These reductions in I can cause a decrease in the canopy photosynthetic rate (Ac), potentially leading to crop yield losses. This study investigated to what extent Ac is reduced inside a modern greenhouse and under a shade net in comparison with that outside. A simple Ac model (i.e., canopy-scale photosynthesis-light curves) was parameterized based on the measurements of Ac and I for paprika and tomato canopies using the open-chamber method. In addition, based on the measurements of I, linear regression models were derived that related outside I (Iout) with I inside arch-roofed, single-span greenhouses [enveloped with a diffuse ethylene tetrafluoroethylene (ETFE) film; Iin] and I under shade nets (composed of aluminum and polyester strips; Ish). An Ac simulation using these models indicated that on a typical sunny summer day in Japan, Ac inside the greenhouses and under the shade nets (Ac,in and Ac,sh, respectively) corresponded to 91% and 52% of Ac outside (Ac,out) for the paprika canopy (for the tomato canopy, Ac,in and Ac,sh corresponded to 90% and 48% of Ac,out, respectively). The simulated Ac loss was more serious on a cloudy day because of the linear Ac-I response under low I conditions (Ac,in/Ac,out and Ac,sh/Ac,out were 69% and 13%, respectively, for the paprika canopy). The loss of Ac,sh may be alleviated by limiting the shading period to only midday hours.

Effects of elevated CO2 and temperature on soybean growth and gas exchange rates: A modified GLYCIM model

GLYCIM is a comprehensive soybean crop simulator that simulates soil, plant, and atmospheric interactions at the physical and physiological process level. The current research focused on replacing the original photosynthesis equation with a leaf-level coupled energy balance model of photosynthesis, transpiration, and stomatal conductance to more accurately simulate responses to climate change. Soybean gas exchange and growth data from six SPAR (Soil–Plant–Atmosphere Research) chamber experiments at four temperature treatments (24/18 °C, 28/22 °C, 32/26 °C, and 36/30 °C, respectively) under ambient (457 µmol mol−1) CO2 and two temperature treatments (28/22 °C and 32/26 °C, respectively) under elevated (670 µmol mol−1) CO2 were used to evaluate the ability of two GLYCIM model versions, original and modified, for simulating the responses of canopy photosynthesis, transpiration rates and observed harvest data. Simulation results showed that the modified GLYCIM had significantly better agreement with observed canopy photosynthetic and transpiration rates, as exhibited by higher values of IA (seasonal photosynthesis, average 0.86 versus 0.82; transpiration, average 0.95 versus 0.84) and lower values of RMSE (seasonal photosynthesis, average 0.58 versus 0.64 mol CO2 m−2 season−1; transpiration, average 1.99 versus 3.16 mmol H2O m−2 s−1) when compared to the original GLYCIM. The simulation of carbon partitioning to stems, leaves, pod and seed was reasonably accurate for both versions, although leaf and stem growth were under-predicted at warmest temperature treatments at either CO2 level. Overall, the modified GLYCIM provided an improved fit of gas exchange and dry matter over a broad range of temperatures and CO2 levels. Given additional evaluation with field data, these improvements will be useful to study adaptation responses for projected warmer, CO2 enriched, climate.

Effects of Applied Ratio of Nitrogen on the Light Environment in the Canopy and Growth, Development and Yield of Wheat When Intercropped.

Changes in the light environment have an important effect on crop growth and yield. To clarify the effects of intercropping and the application of nitrogen on the yield of wheat and light within the crop canopy, the relationship between light and yield and their response to nitrogen fertilizer were studied. In a 2-year field experiment, the characteristics of growth, light, biomass, and yield of wheat were measured using three cropping arrangements (monocropped wheat, monocropped faba beans, and intercropped wheat/faba beans) and four levels of applied nitrogen, in groups termed N0 (0 kg/ha), N1 (90 kg/ha), N2 (180 kg/ha), and N3 (270 kg/ha). The results demonstrated that the application of nitrogen fertilizer increased wheat plant height, spike leaf length and width, and the number of leaves while significantly decreasing wheat canopy light transmittance (LT) and canopy photosynthetic active radiation transmittance (PART), by 7.5–71.1 and 12.7–75.1%, respectively. There was a significantly increased canopy photosynthetic active radiation interception rate (IPAR) of 7.5–97.8% and an increase in biomass of 9.6–38.4%, of which IPAR, biomass, and yield were highest at the N2 level. Compared with monocropping, intercropping increased parameters of wheat growth to varying degrees. Intercropping decreased LT and PART by 10.8–46.4 and 15.7–58.7%, respectively, but increased IPAR by 0.1–66.0%, wheat biomass and yield by 7.5–17.4 and 27.7–47.2%, respectively. The mean yield of intercropped wheat increased by 35.8% over 2 years, while the mean land equivalent ratio (LER) was 1.36, for which a values greater than 1 indicates that wheat and faba bean intercropping is advantageous. Correlation analysis demonstrated that there was a very significant negative correlation between wheat LT and yield, while simultaneously demonstrating a very significant positive correlation between PART and IPAR with yield, indicating that the efficient interception and utilization of light energy in intercropping was the basis for the higher biomass and yield of wheat. In summary, wheat/faba bean intercropping and the application of nitrogen at 180 kg/ha were effective in increasing wheat yield.

Long-term estimation of the canopy photosynthesis of a leafy vegetable based on greenhouse climate conditions and nadir photographs

In horticultural crop production, accurately estimating the canopy photosynthetic rate (Ac) based on greenhouse climate conditions is of practical value for predicting and controlling crop growth and yield. We developed a method for continuously estimating Ac in a greenhouse from readily obtainable information (i.e., climatic data and canopy photographs) by combining a canopy photosynthesis model with image analysis. The canopy photosynthesis model was based on a sun/shade representation of the crop canopy combined with models of single-leaf photosynthesis, stomatal conductance, mass transfer and leaf energy balance. This combination allowed 1) the incorporation of all major climatic variables (i.e., radiation, CO2 concentration, air temperature, humidity, and wind velocity) into the Ac estimation and 2) the simultaneous estimation of Ac, canopy transpiration rate (Ec), and leaf temperature (TL). The leaf area index (Lc), which changes considerably throughout the growth period of a crop canopy, was evaluated nondestructively from the gap fractions of nadir digital photographs (i.e., the fractions of nonleaf area). The canopy photosynthesis model and image analysis results were combined and used to estimate the Ac, Ec, and TL of spinach canopies grown at ambient and elevated CO2 concentrations (c. 400 and 800 µmol mol−1, respectively). Regardless of the CO2 concentration, the estimates of Ac, Ec, and TL were in good agreement with measurements obtained with the open chamber method throughout the growth period. Analyzing the sensitivity of Ac to input variables revealed that the effects of climatic variables on Ac can vary considerably depending on the Lc and incoming radiation. The proposed method enables not only the estimation of Ac from readily obtainable information but also the quantitative evaluation of the effect of climate control on Ac in horticultural greenhouses.

Effect of flag leaf length of erect panicle rice on the canopy structure and biomass production after heading

ABSTRACT Increasing the yield potential of rice (Oryza sativa) is the main objective of breeders and cultivators engaged in rice improvement programs. Erect panicle (EP) rice is generally high-yielding with panicles that remain non-curved until maturation. The aim of our study was to evaluate the association of agronomic traits with rice productivity in EP rice. Here, we used the recombinant inbred lines (RILs), crosses between Liaojing5 (erect panicle japonica type) and Wanlun422 (high-yielding indica type). The yield varied among the RILs, and the flag leaf length of EP RILs was negatively correlated with the yield; however, the correlation was not significant in the non-EP RILs. The flag leaf length of the EP RILs was also negatively correlated with biomass increase during the late ripening stage. This may reflect the canopy structure of the EP RILs with short flag leaves which had a larger leaf area index in the lower strata. Additionally, the chlorophyll content in the lower leaf significantly differed among the EP RILs with flag leaves of different lengths, resulting in a higher photosynthetic ability of the lower leaf of EP RILs with short flag leaves. In the present study, an EP line, which has the shortest flag leaf, showed a higher yield than Wanlun422 in both years. EP RILs with short flag leaves might show a higher canopy photosynthetic rate in the later ripening stage; therefore, this trait could be a potential phenotypic marker for achieving high yield of EP rice.

Modeling canopy photosynthesis and light interception partitioning among shoots in bi-axis and single-axis apple trees (Malus domestica Borkh.)

Bi-axis training increased vegetative shoot light interception and modeled photosynthetic rate, and reduced fruiting shoot mutual shading and vegetative growth by optimizing canopy structure compared to single-axis in young apple trees. Improving light interception and distribution within canopy are constant objectives of training through manipulating tree architecture. A bi-axis training system with two primary scaffolds has been proposed to improve flowering and dry matter production in apple trees. In this study, ‘Fuji’ apple trees trained using a bi-axis or single-axis training system were compared. Twelve three-dimensional (3D) virtual apple trees were reconstructed by combining 3D digitizing and allometric relationships for three shoot types (vegetative long shoot, VL; fruiting shoot, FS; vegetative short shoot, VS), to evaluate canopy structure impacts on light interception. Light interception efficiency was evaluated by silhouette to total area ratio (STAR). The potential canopy photosynthetic rate was evaluated by the eco-physiological RATP model. The leaf area of VL in bi-axis trained trees was approximately 40% lower than that in single-axis trees. Lower leaf area and more uniform spatial distribution were noted in VL in bi-axis than in single-axis trees. This led to more even spatial light distribution and more shoots having higher STAR in bi-axis than in single-axis trees, regardless of the whole tree or shoot type. In the virtual orchard, bi-axis trees had a 25% and 10% STAR increase in VS and VL, respectively, but a similar STAR for FS compared to single-axis trees. Mutual shading between neighboring trees in the virtual orchard made of bi-axis trees was significantly lower than that with single-axis trees for FS. The modeled canopy net photosynthetic rate was 26% higher in bi-axis than in single-axis trees. With the increase in tree age, the projected leaf area increased, but the porosity of the canopy decreased, and mutual shading increased for the whole canopy and all shoot types, irrespective of training systems. These results indicated that manipulating scaffolds in apple trees can regulate canopy structure, light interception, and vegetative growth during the early developmental stages.

Estimating the leaf area index of bell peppers according to growth stage using ray-tracing simulation and a long short-term memory algorithm

The leaf area index (LAI), which represents crop growth characteristics, is used to calculate canopy photosynthetic rates, set irrigation standards, and predict crop growth. The LAI can be non-destructively and continuously estimated using the light-intensity ratio of the upper and lower crop canopy, but it is affected by solar altitude and external weather conditions. The objective of this study was to develop a method to estimate the LAI of bell peppers (Capsicum annuum L.) using the light-intensity ratio of the upper and lower crop canopy via solar altitude and weather conditions. Growth stages and weather conditions with solar altitude were set using 3D-scanned plant models and ray-tracing simulation, respectively. The light intensities at each location of the canopy for given conditions were calculated using ray-tracing simulation. The relationship between the light-intensity ratio and the LAI was analyzed using a long short-term memory (LSTM) algorithm, which is a type of artificial neural network. According to our results, the ratio varied depending on solar altitude and external weather conditions and exponentially decreased with increasing LAI. This LSTM algorithmic approach was able to quantitatively analyze this complex relationship; compared with a greenhouse experiment for validation, the algorithm was highly accurate (R2 = 0.808). Accuracy further increased when solar altitude and weather conditions were added to the model. Therefore, we conclude that, using this method, the LAI can be accurately measured in a non-destructive and continuous manner.

생육 챔버를 이용하여 광도 및 이산화탄소 농도 변수를 갖는 상추(Lactuca sativa L.)의 군락 광합성 곡선의 효율적 도출 방법

For developing a canopy photosynthesis model, an efficient method to measure the photosynthetic rate in a growth chamber is required. The objective of this study was to develop a method for establishing canopy photosynthetic rate curves of romaine lettuce (Lactuca sativa L.) with light intensity and CO2 concentration variables using controlled growth chamber. The plants were grown in plant factory modules, and the canopy photosynthesis rates were measured in sealed growth chambers made of acrylic (1.0 x 0.8 x 0.5 m). First, the canopy photosynthetic rates of the plants were measured, and then the time constants were compared between two application methods: 1) changing light intensity (340, 270, 200, and 130 μmol·m-2·s-1) at a fixed CO2 concentration (1,000 μmol·mol-1) and 2) changing CO2 concentration (600, 1,000, 1,400, and 1,800 μmol·mol-1) at a fixed light intensity (200 μmol·m-2·s-1). Second, the canopy photosynthetic rates were measured by changing the light intensity at a CO2 concentration of 1,000 μmol·mol-1 and compared with those measured by changing the CO2 concentration at a light intensity of 200 μmol·m-2·s-1. The time constant when changing the CO2 concentration at the fixed light intensity was 3.2 times longer, and the deviation in photosynthetic rate was larger than when changing the light intensity. The canopy photosynthetic rate was obtained stably with a time lag of one min when changing the light intensity, while a time lag of six min or longer was required when changing the CO2 concentration. Therefore, changing the light intensity at a fixed CO2 concentration is more appropriate for short-term measurement of canopy photosynthesis using a growth chamber.

Dissection of mechanisms for high yield in two elite rice cultivars

Understanding mechanisms underlying high yield in elite cultivars and identifying new options to further increase rice yield are major focuses of current rice research. In this work, we develop a general method to tackle the above two challenges using two outstanding indica cultivars, i.e., Huang-Hua-Zhan (HHZ) and Yang-dao 6 (9311), which differ in their strategies to gain high yields. Briefly, HHZ grew slower during seedling stage, whereas accumulated more biomass from tillering to heading stage, and had a shorter leaf photosynthetic functional duration after heading; in contrast, 9311 had stronger seedling vigor, but less biomass accumulation from tillering to heading stage, and longer leaf photosynthetic functional duration after heading. To identify the mechanisms underlying these two different strategies, we dissected factors controlling daily canopy photosynthesis at four different growth stages throughout the growing season using a computational approach. Results showed that higher leaf area index (LAI) due to larger leaf width, regardless of a relatively lower leaf light-saturated photosynthetic rate, contributed to higher canopy photosynthesis and hence stronger seedling vigor of 9311 when LAI was low, whereas these same features decreased canopy photosynthetic rate at young panicle differentiation stage when LAI was high; while instead of increasing canopy photosynthesis to support seedling growth, lower LAI due to smaller leaf width, together with higher leaf light-saturated photosynthetic rate, favored biomass accumulation of HHZ between the late tillering stage and the heading stage. Concurrently, computational simulations revealed that earlier drooping of the panicle of HHZ could increase upper leaves’ light intercept and thus canopy photosynthesis at heading stage by reducing shading from panicles, whereas higher leaf nitrogen content was the most important factor for higher canopy photosynthesis of 9311 during grain filling. Overall, the method presented here can be used to quantitatively identify key factors that limit canopy photosynthetic efficiency of current elite cultivars, which is the basis for crop yield potential, and can be used as targets for rice yield improvement by traditional breeding approaches or by genomic editing technologies.

Hybrid Vigor Induced by Cross-breeding Enhances Canopy Photosynthesis and Fruit Yield of Japanese Sweet Pepper

The effect of hybrid vigor on the fruit yield in Japanese sweet pepper (Capsicum annuum L.) was investigated by comparing dry matter production, canopy light-intercepting characteristics and canopy photosynthesis of F1 cultivars to those of their parent lines. The greater yields in the F1 cultivars were caused by both higher dry matter partitioning rate into fruits and total dry matter production. There was no difference in the leaf photosynthetic capacity between the F1 cultivars and their parent lines. The canopy photosynthetic rate, total dry matter production, and yield showed significantly positive correlations with the photosynthetic photon flux absorbed within the plant canopy. The hybrid vigor caused higher plant statures with richer foliage, which led to more effective vertical profiles of leaf area, light absorption, and photosynthesis within the respective canopies. These factors caused a sufficiently higher canopy photosynthesis to produce greater dry matter production and maintain a higher dry matter partitioning rate into fruits, which resulted in higher yields. These results suggest that the vertical profiles of light-intercepting characteristics and photosynthesis within the canopies, which are evaluated by agro-meteorological methodology, are effective selection indices for breeding plants with higher yields.

Development and Validation of a Canopy Photosynthetic Rate Model of Lettuce Using Light Intensity, CO2 Concentration, and Day after Transplanting in a Plant Factory

Development and Validation of a Canopy Photosynthetic Rate Model of Lettuce Using Light Intensity, CO2 Concentration, and Day after Transplanting in a Plant Factory

Stability of a winter wheat population with high yield and high resource use efficiency

Using the winter wheat cultivar Tainong 18 as the experimental material, we analyzed yield stability from 2012 to 2016 under three different treatments: T1(following typical local field management practices), T2(high-yield: high nitrogen and water were supplied to foster high grain yield), and T3(high-yield, high-efficiency: optimized field management including increasing plant density, reducing nitrogen input and delaying of the sowing date). Yield related phenotypic traits, including the number of ears on the main stem and tillers, leaf area index (LAI), photosynthetically active radiation (PAR) interception, dry matter accumulation and distribution, as well as grain yield, were analyzed over four seasons to determine their relationships with annual radiation, accumulated temperature and precipitation. We then determined grain yield stability for each of the three treatments. The amount and distribution of radiation, accumulated temperature, and precipitation varied greatly within each season. The ears on the main stem represented 38.9%, 58.7%, and 66.9% of the total ears, respectively, for wheat grown in the T1, T2 and T3 treatments, indicating that T1 ears originated mainly from the tillers, T2 ears from both the main stem and the tillers, and T3 ears from the main stem. The T2 and T1 treatments produced the highest and lowest amount of dry matter and grain yield, respectively. Although having relatively lower dry matter accumulation at maturity compared with T2, T3 led to higher grain yield due to high LAI, high PAR interception and utilization, high net canopy photosynthetic rate from booting (especially from 14 days after anthesis) to maturity and a higher harvest index. Among the three treatments, T3 resulted in the lowest annual range, standard deviation, and coefficient of variation for LAI, PAR interception, and dry matter accumulation. Thus, grain yield was most stable in wheat grown in the T3 treatment mainly due to stability in biological production during all four seasons.