Crop Photosynthesis Research Articles

The residual effects of bensulfuron-methyl on growth and photosynthesis of soybean and peanut

The effects of various concentrations of bensulfuron-methyl residues (BSM, 0-500 μg kg-1) on the growth and photosynthesis of soybean and peanut were studied. Shoot length, root length, root-to-shoot ratio, and biomass of soybean and peanut seedlings declined with the increase of BSM residue concentrations. As the concentration of BSM increased, SPAD value, net photosynthetic rate, stomatal limitation, stomatal conductance, and transpiration rate also declined with varying extent, but dark respiration rate and intercellular CO2 concentration increased gradually. PSII maximum quantum yield, actual quantum yield, and electron transport rate were significantly reduced by the BSM residues in soil, and the reduction was mostly attributed to the decrease in photochemical quenching coefficient. The results showed that photosynthesis in both crops was limited by nonstomatal factors. The residues of BSM caused reversible damage in PSII reaction centers and decrease the proportion of available excitation energy used for photochemistry.

高CO2浓度对杂交水稻光合作用日变化的影响——FACE研究

PDF HTML阅读 XML下载 导出引用 引用提醒 高CO2浓度对杂交水稻光合作用日变化的影响——FACE研究 DOI: 10.5846/stxb201509261974 作者: 作者单位: 扬州大学 江苏省作物遗传生理国家重点实验室培育点/粮食作物现代产业技术协同创新中心;扬州大学 环境科学与工程学院;中国科学院 南京土壤研究所;中国科学院 南京土壤研究所,扬州大学 江苏省作物遗传生理国家重点实验室培育点/粮食作物现代产业技术协同创新中心,扬州大学 江苏省作物遗传生理国家重点实验室培育点/粮食作物现代产业技术协同创新中心,扬州大学 环境科学与工程学院,扬州大学 环境科学与工程学院,中国科学院 南京土壤研究所;中国科学院 南京土壤研究所,扬州大学 江苏省作物遗传生理国家重点实验室培育点/粮食作物现代产业技术协同创新中心,扬州大学 江苏省作物遗传生理国家重点实验室培育点/粮食作物现代产业技术协同创新中心 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金面上项目（31571597，31371563，31171460）；国家自然科学基金国际（地区）合作与交流项目（31261140364）；中国博士后科学基金资助项目（2015M581870）；江苏省博士后科研资助计划（1501077C）；江苏高校优势学科建设工程项目资助 Effect of increasing atmospheric CO2 concentration on photosynthetic diurnal variation characteristics of hybrid rice: a FACE study Author: Affiliation: Jiangsu Key Laboratory of Crop Genetics and Physiology/ Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University,Jiangsu Key Laboratory of Crop Genetics and Physiology/ Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University,,,,,,Jiangsu Key Laboratory of Crop Genetics and Physiology/ Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:大气二氧化碳（CO2）浓度增高导致全球变暖，但作为光合作用底物促进绿色作物的光合作用。为了明确高CO2浓度对杂交水稻结实期光合日变化的影响，2014年利用稻田FACE（Free Air CO2 Enrichment）平台，以生产上曾创高产纪录的两个杂交稻新组合甬优2640和Y两优2号为供试材料，设置环境CO2和高CO2浓度（增200 μmol/mol）两个水平，测定杂交稻抽穗期和灌浆中期光合作用日变化和成熟期生物量。结果表明，高CO2浓度环境下两组合抽穗期叶片净光合速率均大幅增加（全天平均52%），但灌浆中期的平均增幅减半，其中Y两优2号这种光合下调表现更为明显。大气CO2浓度升高使两杂交稻组合抽穗和灌浆中期叶片气孔导度均大幅下降，导致蒸腾速率下降而水分利用效率大幅增加，Y两优2号气孔导度和蒸腾速率对CO2的响应上午大于下午，而甬优2640表现相反。尽管大气CO2浓度升高使杂交稻结实期不同时刻胞间CO2浓度均大幅增加，但对气孔限制值特别是胞间CO2与空气CO2浓度之比多无显著影响，两品种趋势一致。大气CO2浓度升高对甬优2640地上部生物量及其组分的影响明显大于Y两优2号，CO2与品种间多存在互作效应。以上结果表明，与甬优2640相比，Y两优2号最终生产力从高CO2浓度环境中获益较少可能与该品种生长后期存在明显的光合适应有关，但这种光合适应似乎不是由气孔限制造成的。 Abstract:The rising of atmospheric carbon dioxide (CO2) concentration has been blamed for global warming, but it promotes the leaf photosynthesis of crops because CO2 is the main substrate for photosynthesis. In order to understand the effect of elevated CO2 concentration on diurnal courses of CO2 uptake of hybrid rice, a paddy field experiment utilizing free air CO2 enrichment (FACE) technology was undertaken to determine diurnal courses of leaf photosynthesis at heading and middle grain filling stages, and its association with the final productivity of rice at maturity. Two hybrid rice variety Yongyou 2640 (YY 2640) and YLiangyou No.2 (YLY 2) were grown in the ambient CO2 and the elevated CO2 concentration (200 μmol/mol above ambient) from plant transplanting until grain maturity. Elevated CO2 concentration significantly increased net photosynthetic CO2 assimilation of flag leaves of two hybrids by 52% on average at heading, but the enhancement was reduced to half at the middle grain filling stage. This photosynthesis acclimation was more pronounced in YLY 2. Elevated CO2 concentration significantly decreased stomatal conductance of two hybrids at both heading and grain filling stages, resulting in lower transpiration and higher water use efficiency. Greater CO2 responses of leaf transpiration and stomatal conductance were observed in the morning for YLY 2, but YY 2640 showed higher CO2 effects in the afternoon. Growth at elevated CO2 concentration significantly increased intercellular CO2 concentration, but had no clear effects on the ratio of intercellular to air CO2 concentration and stomata limitation value, and the same trend was observed for the two varieties. The CO2 effects on the above-ground biomass and its components were greater in YY 2640 than YLY 2, and it was reflected in the significant CO2 by variety interactions. The results indicated that compared with YY 2640, the lower CO2 gain on final productivity of YLY 2 might result from photosynthesis acclimation at the late growth stage, and this down-regulation in leaf photosynthesis was not caused by stomatal limitation. 参考文献 相似文献 引证文献

Climatic Variability and its Implications on Agricultural Productivity in Central Punjab

Enhanced greenhouse effect due to anthropogenic activities has resulted in climatic changes and their adverse impacts on agricultural productivity. Different regions of earth are experiencing climatic changes of varying magnitudes. To deal with the situation; there is a dire need of temporal analysis of climatic records to quantify the climatic changes and their likely impacts on agricultural productivity. In the present investigation, long term climatic records of central Punjab (Ludhiana) w.r.t. maximum temperature (Tmax), minimum temperature (Tmin), relative humidity (RH), wind speed (WS), sunshine hours (SSH) and open pan evaporation (PE) for a period of 47 years (1970 to 2016) were analysed on monthly, seasonal and annual basis. Analysis indicated significant annual increase in mean minimum temperature (@0.06°C), relative humidity (@1.3per cent) and decrease in wind speed (@0.67 km day−1), sunshine hours (@0.03 hr day−1) and open pan evaporation (@ 6.0 mm), whereas no significant trend has been observed in maximum temperature. Monthly variability in minimum temperature indicated the highest rate of increase (0.7°C per decade) during reproductive growth and maturity period of rabi (February and March) and Kharif (September and October) crops, which can have adverse effects on their productivity. Similarly increase in relative humidity and decrease in wind speed and sunshine hours can have serious implications on occurrence of insect-pests, rate of crop photosynthesis and yields indicating a dire need of exploring genetic and agronomic manipulations to counterbalance the adverse effects of climate change, minimize climatic risks and sustain agricultural productivity in the region.

Expression of cyanobacterial FBP/SBPase in soybean prevents yield depression under future climate conditions.

Predictions suggest that current crop production needs to double by 2050 to meet global food and energy demands. Based on theory and experimental studies, overexpression of the photosynthetic enzyme sedoheptulose-1,7-bisphosphatase (SBPase) is expected to enhance C3 crop photosynthesis and yields. Here we test how expression of the cyanobacterial, bifunctional fructose-1,6/sedoheptulose-1,7-bisphosphatase (FBP/SBPase) affects carbon assimilation and seed yield (SY) in a major crop (soybean, Glycine max). For three growing seasons, wild-type (WT) and FBP/SBPase-expressing (FS) plants were grown in the field under ambient (400 μmol mol−1) and elevated (600 μmol mol−1) CO2 concentrations [CO2] and under ambient and elevated temperatures (+2.7 °C during daytime, +3.4 °C at night) at the SoyFACE research site. Across treatments, FS plants had significantly higher carbon assimilation (4–14%), Vc,max (5–8%), and Jmax (4–8%). Under ambient [CO2], elevated temperature led to significant reductions of SY of both genotypes by 19–31%. However, under elevated [CO2] and elevated temperature, FS plants maintained SY levels, while the WT showed significant reductions between 11% and 22% compared with plants under elevated [CO2] alone. These results show that the manipulation of the photosynthetic carbon reduction cycle can mitigate the effects of future high CO2 and high temperature environments on soybean yield.

Characterization of the heterooligomeric red-type rubisco activase from red algae

The photosynthetic CO2-fixing enzyme ribulose 1,5-bisphosphate carboxylase/oxygenase (rubisco) is inhibited by nonproductive binding of its substrate ribulose-1,5-bisphosphate (RuBP) and other sugar phosphates. Reactivation requires ATP-hydrolysis-powered remodeling of the inhibited complexes by diverse molecular chaperones known as rubisco activases (Rcas). Eukaryotic phytoplankton of the red plastid lineage contain so-called red-type rubiscos, some of which have been shown to possess superior kinetic properties to green-type rubiscos found in higher plants. These organisms are known to encode multiple homologs of CbbX, the α-proteobacterial red-type activase. Here we show that the gene products of two cbbX genes encoded by the nuclear and plastid genomes of the red algae Cyanidioschyzon merolae are nonfunctional in isolation, but together form a thermostable heterooligomeric Rca that can use both α-proteobacterial and red algal-inhibited rubisco complexes as a substrate. The mechanism of rubisco activation appears conserved between the bacterial and the algal systems and involves threading of the rubisco large subunit C terminus. Whereas binding of the allosteric regulator RuBP induces oligomeric transitions to the bacterial activase, it merely enhances the kinetics of ATP hydrolysis in the algal enzyme. Mutational analysis of nuclear and plastid isoforms demonstrates strong coordination between the subunits and implicates the nuclear-encoded subunit as being functionally dominant. The plastid-encoded subunit may be catalytically inert. Efforts to enhance crop photosynthesis by transplanting red algal rubiscos with enhanced kinetics will need to take into account the requirement for a compatible Rca.

Impact of anatomical traits of maize (Zea mays L.) leaf as affected by nitrogen supply and leaf age on bundle sheath conductance

The mechanism of photosynthesis in C4 crops depends on the archetypal Kranz-anatomy. To examine how the leaf anatomy, as altered by nitrogen supply and leaf age, affects the bundle sheath conductance (gbs), maize (Zea mays L.) plants were grown under three contrasting nitrogen levels. Combined gas exchange and chlorophyll fluorescence measurements were done on fully grown leaves at two leaf ages. The measured data were analysed using a biochemical model of C4 photosynthesis to estimate gbs. The leaf microstructure and ultrastructure were quantified using images obtained from micro-computed tomography and microscopy. There was a strong positive correlation between gbs and leaf nitrogen content (LNC) while old leaves had lower gbs than young leaves. Leaf thickness, bundle sheath cell wall thickness and surface area of bundle sheath cells per unit leaf area (Sb) correlated well with gbs although they were not significantly affected by LNC. As a result, the increase of gbs with LNC was little explained by the alteration of leaf anatomy. In contrast, the combined effect of LNC and leaf age on Sb was responsible for differences in gbs between young leaves and old leaves. Future investigations should consider changes at the level of plasmodesmata and membranes along the CO2 leakage pathway to unravel LNC and age effects further.

Using Different Regression Methods to Estimate Leaf Nitrogen Content in Rice by Fusing Hyperspectral LiDAR Data and Laser-Induced Chlorophyll Fluorescence Data

Nitrogen is an essential nutrient element in crop photosynthesis and yield improvement. Thus, it is urgent and important to accurately estimate the leaf nitrogen contents (LNC) of crops for precision nitrogen management. Based on the correlation between LNC and reflectance spectra, the hyperspectral LiDAR (HSL) system can determine three-dimensional structural parameters and biochemical changes of crops. Thereby, HSL technology has been widely used to monitor the LNC of crops at leaf and canopy levels. In addition, the laser-induced fluorescence (LIF) of chlorophyll, related to the histological structure and physiological conditions of green plants, can also be utilized to detect nutrient stress in crops. In this study, four regression algorithms, support vector machines (SVMs), partial least squares (PLS) and two artificial neural networks (ANNs), back propagation NNs (BP-NNs) and radial basic function NNs (RBF-NNs), were selected to estimate rice LNC in booting and heading stages based on reflectance and LIF spectra. These four regression algorithms were used for 36 input variables, including the reflectance spectral variables on 32 wavelengths and four peaks of the LIF spectra. A feature weight algorithm was proposed to select different band combinations for the LNC retrieval models. The determination coefficient (R2) and the root mean square error (RMSE) of the retrieval models were utilized to compare their abilities of estimating the rice LNC. The experimental results demonstrate that (I) these four regression methods are useful for estimating rice LNC in the order of RBF-NNs > SVMs > BP-NNs > PLS; (II) The LIF data in two forms, including peaks and indices, display potential in rice LNC retrieval, especially when using the PLS regression (PLSR) model for the relationship of rice LNC with spectral variables. The feature weighting algorithm is an effective and necessary method to determine appropriate band combinations for rice LNC estimation.

Changes in leaf area, nitrogen content and canopy photosynthesis in soybean exposed to an ozone concentration gradient

Influences of ozone (O3) on light-saturated rates of photosynthesis in crop leaves have been well documented. To increase our understanding of O3 effects on individual- or stand level productivity, a mechanistic understanding of factors determining canopy photosynthesis is necessary. We used a canopy model to scale photosynthesis from leaf to canopy, and analyzed the importance of canopy structural and leaf ecophysiological characteristics in determining canopy photosynthesis in soybean stands exposed to 9 concentrations of [O3] (37–116 ppb; 9-h mean). Light intensity and N content peaked in upper canopy layers, and sharply decreased through the lower canopy. Plant leaf area decreased with increasing [O3] allowing for greater light intensity to reach lower canopy levels. At the leaf level, light-saturated photosynthesis decreased and dark respiration increased with increasing [O3]. These data were used to calculate daily net canopy photosynthesis (Pc). Pc decreased with increasing [O3] with an average decrease of 10% for an increase in [O3] of 10 ppb, and which was similar to changes in above-ground dry mass production of the stands. Absolute daily net photosynthesis of lower layers was very low and thus the decrease in photosynthesis in the lower canopy caused by elevated [O3] had only minor significance for total canopy photosynthesis. Sensitivity analyses revealed that the decrease in Pc was associated with changes in leaf ecophysiology but not with decrease in leaf area. The soybean stands were very crowded, the leaves were highly mutually shaded, and sufficient light for positive carbon balance did not penetrate to lower canopy leaves, even under elevated [O3].

Reducing the carbon footprint of greenhouse grown crops: re-designing LED-based production systems

To fulfill the market demand for year-round high-quality production, the use of assimilation light has increased over the last decades by 10% per year and continues to expand. The electrical consumption involved largely contributes to the high CO2 emission of greenhouse horticulture. Following the Kyoto protocol, the emission of greenhouse gases should be reduced. Light-emitting diodes (LEDs) can contribute to the reduction in carbon footprint by their high efficiency in converting electricity into light. Due to their low heat emission, LEDs can be positioned within the canopy, which allows the design of new, low-carbon production systems. Inter-canopy LED lighting is already commercially used on a small scale. This paper describes the steps taken to further optimize LED-based production systems. Since it is impossible to test all possible strategies of using LED lighting, a 3D functional-structural plant model was used to do scenario calculations to determine the light interception of the canopy and crop photosynthesis at different positions and orientations of the LEDs. Orienting inter-lighting LEDs 30° downwards positively affected the light interception by the crop, provided that there was sufficient leaf area below the LEDs to prevent light loss to the floor. Replacing the conventional high-pressure sodium (HPS) lamps by LED lamps (efficiency 2.3 μmol J-1) reduced the carbon footprint of a tomato crop by approximately 15%, due to a combination of the higher efficiency of LEDs and an increased use of thermal energy to maintain plant temperatures. These calculations were validated in a greenhouse trial, where the production and energy consumption of a HPS+LED hybrid system was compared to those of a LED top-lighting and LED inter-lighting combination. Plant development and production levels were comparable, whereas the electrical consumption in the LED+LED system was 37% lower than under HPS+LED lighting. Approximately half of the reduction in electricity was used for additional heat input to maintain plant development rate, which agreed well with the carbon footprint calculations. Work in the near future will focus on plant architecture and LEDs with altered light emission patterns, aiming to design new LEDbased production systems, which combine a high production level with a low-carbon footprint.

Evaluation of diffusing properties of greenhouse covering materials

Modern greenhouse covering and screen materials are able to transform direct sunlight into diffuse light. After entering the greenhouse the sunlight is scattered and penetrates the crop where it is absorbed and used for photosynthesis. Diffuse light has been shown to increase light interception of crops, increase crop photosynthesis and results in higher yields. Many different types of diffuse covering materials are available, and growers select materials based on crop, outside climate where the greenhouse is located and market situation. Earlier measurement methods to evaluate diffuse covering materials have been proposed (Hemming et al., 2008) and are mainly based on the measurement and evaluation of the hemispherical light transmittance, the average amount of light coming into the greenhouse (Nijskens et al., 1985; Papadakis et al., 2000) and the Haze (e.g., ASTM-D1003-07), the average amount of scattered light reaching the crop. A more detailed evaluation of the angular and spectral light transmittance of materials is needed (Hemming et al., 2014), including the spatial distribution of scattered light, or the way light is scattered by a material. In this paper we propose a new method of measuring the spatial distribution of scattered light by a bi-directional transmittance distribution function (BTDF) measurement. By comparing the BTDF values of a diffuse covering or screen material with the BTDF values of a Lambertian diffuser, we calculate one simple value for material characterisation, the F-scatter. F-scatter is a more representative value for the scattering properties of a material than Haze. The detailed material scatter properties can be used for further raytracing analysis of materials in greenhouses with a specific roof construction, at a specific location for any moment of the year. It can also be used for 3D functional crop models in the future.

One crop breeding cycle from starvation? How engineering crop photosynthesis for rising CO2 and temperature could be one important route to alleviation.

Global climate change is likely to severely impact human food production. This comes at a time when predicted demand for primary foodstuffs by a growing human population and changing global diets is already outpacing a stagnating annual rate of increase in crop productivity. Additionally, the time required by crop breeding and bioengineering to release improved varieties to farmers is substantial, meaning that any crop improvements needed to mitigate food shortages in the 2040s would need to start now. In this perspective, the rationale for improvements in photosynthetic efficiency as a breeding objective for higher yields is outlined. Subsequently, using simple simulation models it is shown how predicted changes in temperature and atmospheric [CO2] affect leaf photosynthetic rates. The chloroplast accounts for the majority of leaf nitrogen in crops. Within the chloroplast about 25% of nitrogen is invested in the carboxylase, Rubisco, which catalyses the first step of CO2 assimilation. Most of the remaining nitrogen is invested in the apparatus to drive carbohydrate synthesis and regenerate ribulose-1:5-bisphosphate (RuBP), the CO2-acceptor molecule at Rubisco. At preindustrial [CO2], investment in these two aspects may have been balanced resulting in co-limitation. At today's [CO2], there appears to be over-investment in Rubisco, and despite the counter-active effects of rising temperature and [CO2], this imbalance is predicted to worsen with global climate change. By breeding or engineering restored optimality under future conditions increased productivity could be achieved in both tropical and temperate environments without additional nitrogen fertilizer. Given the magnitude of the potential shortfall, better storage conditions, improved crop management and better crop varieties will all be needed. With the short time-scale at which food demand is expected to outpace supplies, all available technologies to improve crop varieties, from classical crop breeding to crop genetic engineering should be employed. This will require vastly increased public and private investment to support translation of first discovery in laboratories to replicated field trials, and an urgent re-evaluation of regulation of crop genetic engineering.

Cultivar variation in cotton photosynthetic performance under different temperature regimes

Cotton (Gossypium hirsutum L.) yields are impacted by overall photosynthetic production. Factors that influence crop photosynthesis are the plants genetic makeup and the environmental conditions. This study investigated cultivar variation in photosynthesis in the field conditions under both ambient and higher temperature. Six diverse cotton cultivars were grown in the field at Stoneville, MS under both an ambient and a high temperature regime during the 2006-2008 growing seasons. Mid-season leaf net photosynthetic rates (P N) and dark-adapted chlorophyll fluorescence variable to maximal ratios (Fv/Fm) were determined on two leaves per plot. Temperature regimes did not have a significant effect on either P N or Fv/Fm. In 2006, however, there was a significant cultivar × temperature interaction for P N caused by PeeDee 3 having a lower P N under the high temperature regime. Other cultivars' P N were not affected by temperature. FM 800BR cultivar consistently had a higher P N across the years of the study. Despite demonstrating a higher leaf Fv/Fm, ST 5599BR exhibited a lower P N than the other cultivars. Although genetic variability was detected in photosynthesis and heat tolerance, the differences found were probably too small and inconsistent to be useful for a breeding program.

Rubisco catalytic properties of wild and domesticated relatives provide scope for improving wheat photosynthesis.

Rubisco is a major target for improving crop photosynthesis and yield, yet natural diversity in catalytic properties of this enzyme is poorly understood. Rubisco from 25 genotypes of the Triticeae tribe, including wild relatives of bread wheat (Triticum aestivum), were surveyed to identify superior enzymes for improving photosynthesis in this crop. In vitro Rubisco carboxylation velocity (V c), Michaelis-Menten constants for CO2 (K c) and O2 (K o) and specificity factor (S c/o) were measured at 25 and 35 °C. V c and K c correlated positively, while V c and S c/o were inversely related. Rubisco large subunit genes (rbcL) were sequenced, and predicted corresponding amino acid differences analysed in relation to the corresponding catalytic properties. The effect of replacing native wheat Rubisco with counterparts from closely related species was analysed by modelling the response of photosynthesis to varying CO2 concentrations. The model predicted that two Rubisco enzymes would increase photosynthetic performance at 25 °C while only one of these also increased photosynthesis at 35 °C. Thus, under otherwise identical conditions, catalytic variation in the Rubiscos analysed is predicted to improve photosynthetic rates at physiological CO2 concentrations. Naturally occurring Rubiscos with superior properties amongst the Triticeae tribe can be exploited to improve wheat photosynthesis and crop productivity.

The Effect of Elevated Ozone Concentrations with Varying Shading on Dry Matter Loss in a Winter Wheat-Producing Region in China.

Surface-level ozone pollution causes crop production loss by directly reducing healthy green leaf area available for carbon fixation. Ozone and its precursors also affect crop photosynthesis indirectly by decreasing solar irradiance. Pollutants are reported to have become even more severe in Eastern China over the last ten years. In this study, we investigated the effect of a combination of elevated ozone concentrations and reduced solar irradiance on a popular winter wheat Yangmai13 (Triticum aestivum L.) at field and regional levels in China. Winter wheat was grown in artificial shading and open-top-chamber environments. Treatment 1 (T1, i.e., 60% shading with an enhanced ozone of 100±9 ppb), Treatment 2 (T2, i.e., 20% shading with an enhanced ozone of 100±9 ppb), and Control Check Treatment (CK, i.e., no shading with an enhanced ozone of 100±9 ppb), with two plots under each, were established to investigate the response of winter wheat under elevated ozone concentrations and varying solar irradiance. At the field level, linear temporal relationships between dry matter loss and cumulative stomatal ozone uptake were first established through a parameterized stomatal-flux model. At the regional level, ozone concentrations and meteorological variables, including solar irradiance, were simulated using the WRF-CMAQ model (i.e., a meteorology and air quality modeling system). These variables were then used to estimate cumulative stomatal ozone uptake for the four major winter wheat-growing provinces. The regional-level cumulative ozone uptake was then used as the independent variable in field data-based regression models to predict dry matter loss over space and time. Field-level results showed that over 85% (T1: R2 = 0.85 & T2: R2 = 0.89) of variation in dry matter loss was explained by cumulative ozone uptake. Dry matter was reduced by 3.8% in T1 and 2.2% in T2 for each mmol O3·m-2 of cumulative ozone uptake. At the regional level, dry matter loss in winter wheat would reach 50% under elevated ozone concentrations and reduced solar irradiance as determined in T1, and 30% under conditions as determined in T2. Results from this study suggest that a combination of elevated ozone concentrations and reduced solar irradiance could result in substantial dry matter loss in the Chinese wheat-growing regions.

Impacts of reduced model complexity and driver resolution on cropland ecosystem photosynthesis estimates

Landscape and regional estimates of crop photosynthesis are required to support research into food security, carbon (C) cycling and land surface processes. Quantifying C uptake by cropland ecosystems is complicated by spatial heterogeneity. A major challenge is to upscale the detailed understandings embodied in process models that have been validated at specific sites with high resolution inputs. At landscape scales the input requirements for such complex models are generally unavailable (e.g. site specific parameters, hourly meteorological data), and the computing demands are prohibitive. We demonstrate a simplified crop C aggregated canopy model (ACM) predicting daily photosynthesis, requiring minimal parameters. This simple model emulates a high resolution model (SPAc, half-hourly time-steps; simulating leaf to canopy processes) whilst using coarser-scale (daily) drivers. Based on the SPAc model outputs, Bayesian inference is used to calibrate the simple photosynthesis model scalar coefficients at eight European cereal crop sites. We test whether a single calibration, generated from only four of the sites (i.e. calibration sites), is effective across all sites (i.e. including independent validation sites). We further investigate the error introduced by using regional meteorological drivers over local observations. We show that, compared to photosynthesis estimated from eddy covariance at the sites, the simple model produced comparable results to the complex model: both models explained a similar proportion of daily variability in photosynthesis (mean R2=0.78 for ACM, 0.77 for SPAc), and had similar model error (mean RMSE=2.89gm−2 d−1 for ACM, 3.20gm−2 d−1 for SPAc). Thus, the simple model, which has much reduced computational requirements, shows no reduction in model reliability and offers a simple means to upscale a critical process. We discuss the importance of the simple model in regional to continental-scale data assimilation schemes.

Analysis of chlorophyll content and its correlation with yield attributing traits on early varieties of maize (Zea mays L.)

Chlorophyll has direct roles on photosynthesis and hence closely relates to capacity for photosynthesis, development and yield of crops. With object to explore the roles of chlorophyll content and its relation with other yield attributing traits a field research was conducted using fourteen early genotypes of maize in RCBD design with three replications. Observations were made for Soil Plant Analysis Development (SPAD) reading, ear weight, number of kernel row/ear, number of kernel/row, five hundred kernel weight and grain yield/hectare and these traits were analyzed using Analysis of Variance (ANOVA) and correlation coefficient analysis. SPAD reading showed a non-significant variation among the genotypes while it revealed significant correlation with no. of kernel/row, grain yield/hectare and highly significant correlation with no. of kernel row/ear and ear weight which are the most yield determinative traits. For the trait grain yield/ha followed by number of kernel row/ear genotype ARUN-1EV has been found comparatively superior to ARUN-2 (standard check). Grain Yield/hectare was highly heritable (>0.6) while no. of kernel / row, SPAD reading, ear weight, number of kernel row/ear were moderately heritable (0.3-0.6). Correlation analysis and ANOVA revealed ARUN-1EV, comparatively superior to ARUN-2 (standard check), had higher SPAD reading than mean SPAD reading with significant correlation with no. of kernel/row, no. of kernel row/ear, ear weight and grain yield/ha which are all yield determinative traits . This showed positive and significant effect of chlorophyll content in grain yield of the maize.Journal of Maize Research and Development (2015) 1(1):134-145DOI: http://dx.doi.org/10.5281/zenodo.34263

Effects of straw mulching on maize photosynthetic characteristics and rhizosphere soil micro-ecological environment

Straw mulching is an effective measure to improve soil properties, crop growth, and yield. To further understand the advantage mechanisms of straw mulching, a field experiment with seven straw mulching levels (0 to 18 000 kg ha-1) was conducted to study the effects of straw mulching on maize (Zea mays L.) photosynthesis and rhizosphere soil micro-ecological environment. Results showed that maize chlorophyll content was evidently affected by straw mulching, and the highest chlorophyll content was at 12 000 kg ha-1 (M4). Straw mulching could significantly improve the photosynthetic characteristics of maize, and the difference between M4 and 0 kg ha-1 (M0) was significant. There was as trend change in soil microbe quantity; it first increased and then decreased with increasing straw mulching levels, and the most suitable straw mulching level for different types of microorganisms was 9000 kg ha-1 (M3) or M4. Straw mulching significantly enhanced soil enzyme urease, invertase, dehydrogenase, and protease activities, but when the straw mulching level reached a certain level, the effect of straw mulching was no longer apparent and even had some adverse effects at straw mulching levels higher than 15 000 kg ha-1 (M5). Yield in M4 (10 186.84 kg ha-1) was the highest compared with M0 (9365.12 kg ha-1), and yield significantly increased by 8.8%. Correlation analyses indicated that the soil microbe quantity and aforementioned enzyme activities were all significantly and positively correlated with maize chlorophyll content, photosynthetic rate, and yield. Findings suggest that straw mulching can apparently increase soil microbe quantity and enzyme activities and improve crop photosynthesis and yield; the M4 level is the most reasonable straw mulching level in this study under comprehensive consideration, and a straw mulching level that is too high (over M5) will have some negative effects.

Advantages of diffuse light for horticultural production and perspectives for further research.

Plants use diffuse light more efficiently than direct light, which is well established due to diffuse light penetrates deeper into the canopy and photosynthetic rate of a single leaf shows a non-linear response to the light flux density. Diffuse light also results in a more even horizontal and temporal light distribution in the canopy, which plays substantial role for crop photosynthesis enhancement as well as production improvement. Here we show some of the recent findings about the effect of diffuse light on light distribution over the canopy and its direct and indirect effects on crop photosynthesis and plant growth, and suggest some perspectives for further research which could strengthen the scientific understanding of diffuse light modulate plant processes and its application in horticultural production.

The effect of reducing the heating set point on the photosynthesis, growth, yield and fruit quality in greenhouse tomato production

Lowering the temperature set point for heating is an important method of reducing energy consumption, and hence carbon dioxide emissions, in greenhouse tomato production. Nonetheless, this measure is rarely applied in Central European and North American greenhouses due to the high value of the product, worries about a decline in yield and quality, and the prices of fossil fuels, which continue to be relatively moderate. Temperature decreases can only be introduced successfully if the constraints of ecological and economic feasibility involved are known. To this end, two experiments were conducted in which tomato plants were cultivated at day and night heating set points of 20/18, 16/14 and 11/9°C, respectively. In all of the treatments, the set points for opening the ventilation were an air temperature of 27°C and 80% relative air humidity. Crop photosynthesis appeared to be unaffected by the temperature set point for heating, although the concentrations of leaf soluble sugar and starch increased significantly at low temperatures compared to at high temperatures. The reduction in the temperature set points also appeared to have no impact on the total production of dry matter, the dry matter fraction allocated to the fruit and, thus, the total fruit yield. However, each one Kelvin reduction in temperature resulted in a 3.5-day increase in the time required for fruit to develop and, thus, in a considerable delay of the first harvest. This delay was balanced out by higher yields generated in later harvests. The temperature of the fruit itself rather than that of the complete plant was responsible for this delay. Surprisingly, the reduction in temperature had little effect on the quality of the fruit: the mass of single fruits increased significantly as temperature decreased. However, there was no effect on the fruit reducing sugar content, and only a slight decrease in fruit titratable acid content. From an ecological perspective, carbon dioxide emissions caused by tomato production can be cut considerably by reducing the heating set points without affecting yield and only having a slight effect on the quality of the fruit. From an economic perspective, any loss of profit due to the delay of harvests would have to be balanced out by the savings generating by turning down the heating.

Modeling crop water use in an irrigated maize cropland using a biophysical process-based model

Summary Accurate modeling of crop water use or evapotranspiration ( ET ) is needed to understand the hydrologic cycle and improve water use efficiency. Biophysical process-based multilayer models can capture details of the nonlinear interaction between microclimate and physiology within the canopy and thus accurately simulate ET . In this study, we extended a process-based multilayer model, ACASA, which explicitly simulated many of the nonlinear biophysical processes within each of ten crop canopy sublayers and then integrated to represent the complete crop canopy. Based on the original ACASA model, we made the improved modifications including four added modules (C 4 crop photosynthesis, water stress response of stomatal conductance, crop morphological changes, and heterogeneous root water uptake), and two adjusted calculation procedures (soil evaporation resistance and hydraulic characteristic parameters). Key processes were parameterized for the improved ACASA model using observations. The simulated canopy ET was validated using eddy covariance measurements over an irrigated maize field in an arid inland region of northwest China. The improved ACASA model predicted maize ET for both half-hourly and daily time-scales. The improved model also predicted the reduction in maize ET under the condition of soil water deficit. Soil evaporation, an important component of maize ET , was also satisfactorily simulated in the improved model. Compared to the original ACASA model, the improved model yielded an improved estimation of maize ET . Using the improved model, we found that maize ET was nonlinearly affected by changes in leaf area index and photosynthetic capacity through canopy conductance. In general, the improved ACASA model, a biophysical process-based multilayer model, can be used to diagnose and predict crop ET , and draw some insights into the nonlinear interactions between crop canopy and ambient environment.