Photosynthetic induction upon transfer from low to high light is affected by leaf nitrogen content in tomato

The response of photosynthetic CO2 assimilation to changes of illumination affects plant growth and crop productivity under natural fluctuating light conditions. However, the effects of nitrogen (N) supply on photosynthetic physiology after transition from low to high light are seldom studied. To elucidate this, we measured gas exchange and chlorophyll fluorescence under fluctuating light in tomato (Solanum lycopersicum) seedlings grown with different N conditions. After transition from low to high light, the induction speeds of net CO2 assimilation (AN), stomatal conductance (gs) and mesophyll conductance (gm) delayed with the decline in leaf N content. The times to reach 90% of maximum AN, gs and gm were negatively correlated to leaf N content. This delayed photosynthetic induction in plants grown under low N concentration was mainly caused by the slow induction response of gm rather than that of gs. Furthermore, the photosynthetic induction upon transfer from low to high light was hardly limited by photosynthetic electron flow. These results indicate that decreased leaf N content declines carbon gain under fluctuating light in tomato. Increasing the induction kinetics of gm has the potential to enhance the carbon gain of field crops grown in infertile soil.

The Effect of Low Irradiance on Leaf Nitrogen Allocation and Mesophyll Conductance to CO2 in Seedlings of Four Tree Species in Subtropical China

Low light intensity can lead to a decrease in photosynthetic capacity. However, could N-fixing species with higher leaf N contents mitigate the effects of low light? Here, we exposed seedlings of Dalbergia odorifera and Erythrophleum fordii (N-fixing trees), and Castanopsis hystrix and Betula alnoides (non-N-fixing trees) to three irradiance treatments (100%, 40%, and 10% sunlight) to investigate the effects of low irradiance on leaf structure, leaf N allocation strategy, and photosynthetic physiological parameters in the seedlings. Low irradiance decreased the leaf mass per unit area, leaf N content per unit area (Narea), maximum carboxylation rate (Vcmax), maximum electron transport rate (Jmax), light compensation point, and light saturation point, and increased the N allocation proportion of light-harvesting components in all species. The studied tree seedlings changed their leaf structures, leaf N allocation strategy, and photosynthetic physiological parameters to adapt to low-light environments. N-fixing plants had a higher photosynthesis rate, Narea, Vcmax, and Jmax than non-N-fixing species under low irradiance and had a greater advantage in maintaining their photosynthetic rate under low-radiation conditions, such as under an understory canopy, in a forest gap, or when mixed with other species.

Chlorophyll content and spad value of rice (Oryza sativa l.) under different sowing windows and nutrient management practices

The field experiment was conducted during kharif seasons of 2018 and 2019 in Agronomy research farm ,OUAT on rice using two dates of planting (10th july, 25th july) in main plot and three nutrient management practices (STBFR (Soil test based fertilizer recommendation), STBFR+GM, STBFR+FYM) in sub plot in a split plot design with four replications. Chlorophyll content as well as SPAD values of the crop measured at different growth stages of rice at 30 days interval revealed that chlorophyll a, chlorophyll b, total chlorophyll as well as SPAD values of the crop increased till 60 DAP and thereafter decreased. Early planting recorded higher chlorophyll a value of 2.36 mg g-1 of fresh leaf, chlorophyll b value of 1.26 mg g-1, total chlorophyll value of 3.62 mg g-1 and SPAD value of 44.73, while STBFR + GM treatment registered higher Chlorophyll a value of 2.55 mg g-1, Chlorophyll b value of 1.38 mg g-1, total chlorophyll value of 3.99 mg g-1 and SPAD value of 46.87. Leaf N content as well as grain yield is also found higher in early planting (2.58 %, 5008 kg ha-1) and STBFR + GM (2.74 %, 5015 kg ha-1). Significant positive linear relationship was observed between leaf N content and SPAD value of the crop which ultimately influences grain yield of the crop.

Physiological and root morphological responses in different combinations of rootstock-scion of cacao to water deficit

Grafting is a common practice in cacao cultivation, but it has not been reported whether rootstock-scion combinations respond differently in terms of water transport, growth, or nutrient uptake under varying soil water availability conditions. The effects of water deficits on water potential (Ψf), basal diameter (db), root growth, chlorophyll and leaf concentrations of nitrogen (N) were evaluated in 16 rootstock-scion combinations that resulted from four rootstocks and four scion clones. Grafted seedlings were subjected to two water regimes: 21 days without irrigation (WD) and continuous irrigation (I). Under WD conditions, Ψf tended to be lower when using the EETP800 clone with the four rootstocks, indicating that this clone may have a higher rate of transpiration. The greater Ψf (p <0.05) obtained with the EET400 and EET399 rootstocks-scion combinations indicate higher water uptake capacity by the root systems of these rootstocks, which permits the maintenance of adequate transpiration rates and higher Ψf. The higher db, chlorophyll content and leaf N content obtained in the combinations of scions with the EET400 rootstock under WD impart on this rootstock a more favorable degree of adaptability for tolerating water deficits. However, this tolerance is not associated with increased root growth, which indicates that higher efficiency of water uptake is related to metabolic and physiological processes rather than a larger root surface.

Biochemical and physiological changes in conilon coffee (Coffea canephora) grown under different levels of irradiance

Modern agriculture values the most sustainable and dynamic means of production, which can be promoted through the association between coffee and tree components, aiming at the best use of the land. However, within our understanding of the physiological and biochemical behaviors of the coffee tree, the irradiance limiting conditions are crucial to maximize the potential gains generated in these systems. In this sense, the objective of this study was to evaluate the effects of different levels of irradiance restriction on the physiological and biochemical characteristics of two genotypes of Conilon coffee. The experiment was conducted in a 2 × 3 factorial scheme, corresponding to two Conilon coffee clones and three levels of light intensity restriction (0, 30 and 50%), in a randomized block design with four replications. The synthesis of total chlorophyll b and the leaf N content of the genotypes CL6 and CL12 increased with the reduction of light. On the other hand, there was a reduction in the levels of carbohydrates, amino acids and phenols with the reduction of light intensity. Restricted levels of irradiance caused different changes in the physiological and biochemical characteristics of the studied genotypes, showing genetic divergences between them

A novel approach for nitrogen diagnosis of wheat canopies digital images by mobile phones based on histogram

The accurate and nondestructive assessment of leaf nitrogen (N) is very important for N management in winter wheat fields. Mobile phones are now being used as an additional N diagnostic tool. To overcome the drawbacks of traditional digital camera diagnostic methods, a histogram-based method was proposed and compared with the traditional methods. Here, the field N level of six different wheat cultivars was assessed to obtain canopy images, leaf N content, and yield. The stability and accuracy of the index histogram and index mean value of the canopy images in different wheat cultivars were compared based on their correlation with leaf N and yield, following which the best diagnosis and prediction model was selected using the neural network model. The results showed that N application significantly affected the leaf N content and yield of wheat, as well as the hue of the canopy images and plant coverage. Compared with the mean value of the canopy image color parameters, the histogram could reflect both the crop coverage and the overall color information. The histogram thus had a high linear correlation with leaf N content and yield and a relatively stable correlation across different growth stages. Peak b of the histogram changed with the increase in leaf N content during the reviving stage of wheat. The histogram of the canopy image color parameters had a good correlation with leaf N content and yield. Through the neural network training and estimation model, the root mean square error (RMSE) and the mean absolute percentage error (MAPE) of the estimated and measured values of leaf N content and yield were smaller for the index histogram (0.465, 9.65%, and 465.12, 5.5% respectively) than the index mean value of the canopy images (0.526, 12.53% and 593.52, 7.83% respectively), suggesting a good fit for the index histogram image color and robustness in estimating N content and yield. Hence, the use of the histogram model with a smartphone has great potential application in N diagnosis and prediction for wheat and other cereal crops.

Productivity and gas exchanges of the common bean subjected to inoculation and nitrogen fertilization

Beans are one of the main foods consumed in Brazil. It is considered an essential ingredient in the basic diet of Brazilians. As a management practice, aiming to supply N and increase crop productivity, producers have used the association of seed inoculation with nitrogen fertilization. Thus, the objective of this study is to evaluate the effects of split nitrogen fertilization and seed inoculation on common bean productivity. The experiment was carried out in completely randomized blocks and a 2x2x3 factorial design with four replications. The first factor was seed inoculation (presence or absence) with peat inoculant containing the strains SEMIA 4077 and SEMIA 4080 from R. tropici and the strain SEMIA 4088 from R. freirei. The second factor was the parceling of nitrogen cover fertilization (80+40 and 60+60 kg ha-1 of N at 20 and 40 days after emergence (DAE)). The third factor was time of assessment (50, 65 and 80 DAE). The inoculated bean showed a 5% higher leaf N content than non-inoculated ones. Transpiration and liquid photosynthesis rates were higher in inoculated plants and in those with 60+60 kg ha-1 of N. However, productivity was 13% higher in uninoculated beans regardless of nitrogen fertilization.

Effects of ontogenetic stage and leaf age on leaf functional traits and the relationships between traits in Pinus koraiensis

Investigating the effects of ontogenetic stage and leaf age on leaf traits is important for understanding the utilization and distribution of resources in the process of plant growth. However, few studies have been conducted to show how traits and trait-trait relationships change across a range of ontogenetic stage and leaf age for evergreen coniferous species. We divided 67 Pinus koraiensis Sieb. et Zucc. of various sizes (0.3–100 cm diameter at breast height, DBH) into four ontogenetic stages, i.e., young trees, middle-aged trees, mature trees and over-mature trees, and measured the leaf mass per area (LMA), leaf dry matter content (LDMC), and mass-based leaf nitrogen content (N) and phosphorus content (P) of each leaf age group for each sampled tree. One-way analysis of variance (ANOVA) was used to describe the variation in leaf traits by ontogenetic stage and leaf age. The standardized major axis method was used to explore the effects of ontogenetic stage and leaf age on trait-trait relationships. We found that LMA and LDMC increased significantly and N and P decreased significantly with increases in the ontogenetic stage and leaf age. Most trait-trait relationships were consistent with the leaf economic spectrum (LES) at a global scale. Among them, leaf N content and LDMC showed a significant negative correlation, leaf N and P contents showed a significant positive correlation, and the absolute value of the slopes of the trait-trait relationships showed a gradually increasing trend with an increasing ontogenetic stage. LMA and LDMC showed a significant positive correlation, and the slopes of the trait-trait relationships showed a gradually decreasing trend with leaf age. Additionally, there were no significant relationships between leaf N content and LMA in most groups, which is contrary to the expectation of the LES. Overall, in the early ontogenetic stages and leaf ages, the leaf traits tend to be related to a "low investment-quick returns" resource strategy. In contrast, in the late ontogenetic stages and leaf ages, they tend to be related to a "high investment-slow returns" resource strategy. Our results reflect the optimal allocation of resources in Pinus koraiensis according to its functional needs during tree and leaf ontogeny.

Combining Process Modelling and LAI Observations to Diagnose Winter Wheat Nitrogen Status and Forecast Yield

Climate, nitrogen (N) and leaf area index (LAI) are key determinants of crop yield. N additions can enhance yield but must be managed efficiently to reduce pollution. Complex process models estimate N status by simulating soil-crop N interactions, but such models require extensive inputs that are seldom available. Through model-data fusion (MDF), we combine climate and LAI time-series with an intermediate-complexity model to infer leaf N and yield. The DALEC-Crop model was calibrated for wheat leaf N and yields across field experiments covering N applications ranging from 0 to 200 kg N ha−1 in Scotland, UK. Requiring daily meteorological inputs, this model simulates crop C cycle responses to LAI, N and climate. The model, which includes a leaf N-dilution function, was calibrated across N treatments based on LAI observations, and tested at validation plots. We showed that a single parameterization varying only in leaf N could simulate LAI development and yield across all treatments—the mean normalized root-mean-square-error (NRMSE) for yield was 10%. Leaf N was accurately retrieved by the model (NRMSE = 6%). Yield could also be reasonably estimated (NRMSE = 14%) if LAI data are available for assimilation during periods of typical N application (April and May). Our MDF approach generated robust leaf N content estimates and timely yield predictions that could complement existing agricultural technologies. Moreover, EO-derived LAI products at high spatial and temporal resolutions provides a means to apply our approach regionally. Testing yield predictions from this approach over agricultural fields is a critical next step to determine broader utility.