Elevated CO2 increases, while high temperature decreases, rice yield. We hypothesized that the interplay between these opposite effects varies across genotypes and these variations are associated with the ability of genotypes to avoid and tolerate stress. We evaluated a Japonica genotype (Changyou5) and an Indica genotype (Yangdao6) under combinations of two CO2 levels (ambient and enriched to 590 μmol mol-1) and two canopy temperatures (ambient and warmed by 2.0 °C) in a temperature by free-air CO2 enrichment (T-FACE) system over two seasons. The elevated CO2 fully offset the adverse effects of the elevated temperature on grain yield of Yangdao6 but failed to do so for Changyou5. In Yangdao6 yield increased by 20.0%, while in Changyou5 it decreased by 7.8% under the combined elevated CO2 and elevated temperature. This genotypic difference was partly due to higher leaf-nitrogen content of cv. Yangdao6, resulting in superior light conversion efficiency. However, it was explained more by a smaller decrease in spikelet fertility (and thus harvest index) in Yangdao6, mainly resulting from lower panicle temperature during flowering. The lower panicle temperature in Yangdao6 was due to earlier flowering hours as well as to higher panicle nitrogen content that presumably led to greater transpirational cooling. The above key genotypic traits could be explored in rice breeding programs to improve yield resilience to climate change.

AbstractElevated CO2 concentration has been reported to decrease grain nutrient concentrations and thus worsen nutritional deficiency and hidden hunger. One nutritional aspect is mineral content, yet mineral bioavailability can be limited by the presence of phytic acid. Given that future climate scenarios predict elevated global temperature driven by elevated atmospheric CO2 concentrations, we used Temperature by Free‐Air CO2 Enrichment (T‐FACE) field experiments to investigate whether elevated temperature alters the effects of elevated CO2 on grain mineral concentrations, grain mineral yields, and their bioavailability in a range of wheat and rice genotypes. We found that the negative effects of elevated CO2 were compensated for by positive effects of elevated temperature. As a result, the combined elevated CO2 and elevated temperature increased concentrations of some minerals by up to ~15% in both rice and wheat relative to control conditions. Moreover, the combined elevated CO2 and elevated temperature did not significantly change total yields of some minerals despite lower grain yields. The combined CO2 and temperature elevation increased phytic acid concentration in rice by 18.1% but decreased it in wheat by 3.5%. The mineral bioavailability, estimated as the mole ratio of phytic acid to minerals in rice and wheat grains, was limited by the combined CO2 and temperature elevation in only a few cases. Our results indicate that under future climate conditions of elevated temperature and CO2, the nutritional quality of rice and wheat with respect to minerals may remain unchanged.

Global dimming reduces incident global radiation but increases the fraction of diffuse radiation, and thus affects crop yields; however, the underlying mechanisms of such an effect have not been revealed. We hypothesized that crop source-sink imbalance of either carbon (C) or nitrogen (N) during grain filling is a key factor underlying the effect of global dimming on yields. We presented a practical framework to assess both C and N source-sink relationships, using data of biomass and N accumulation from periodical sampling conducted in field experiments for wheat and rice from 2013 to 2016. We found a fertilization effect of the increased diffuse radiation fraction under global dimming, which alleviated the negative impact of decreased global radiation on source supply and sink growth, but the source supply and sink growth were still decreased by dimming, for both C and N. In wheat, the C source supply decreased more than the C sink demand, and as a result, crops remobilized more pre-heading C reserves, in response to dimming. However, these responses were converse in rice, which presumably stemmed from the more increment in radiation use efficiency and the more limited sink size in rice than wheat. The global dimming affected source supply and sink growth of C more significantly than that of N. Therefore, yields in both crops were dependent more on the source-sink imbalance of C than that of N during grain filling. Our revealed source-sink relationships, and their differences and similarities between wheat and rice, provide a basis for designing strategies to alleviate the impact of global dimming on crop productivity.

Predicting biomass production is important for assessing yield losses caused by drought. Photosynthesis-driven crop growth models, such as SUCROS97, tend to overestimate crop production under severe drought, as they ignore slow post-drought recovery kinetics of leaf photosynthesis. In this study, Lilium plants (L. auratum x speciosum 'Sorbonne') were subjected to mild, intermediate and severe drought with different durations (3, 5, 7 and 9 days) at two developmental stages (leaf unfolding and flower bud break stage). Leaf photosynthesis and chlorophyll fluorescence (CF) were measured during and after drought. We found that at both developmental stages, drought significantly reduced light-saturated gross photosynthesis rate (P-g,P-max), which progressively recovered after re-watering. Under mild drought, P-g,P-max recovered fully to non-stress levels by re-watering, whereas under intermediate and severe drought, P-g,P-max did not recover fully. Drought occurring during leaf unfolding had a larger impact on biomass production than drought during bud break. Further, we identified a sigmoidal relationship (r(2) = 0.81) between P-g,P-max and photosystem II operating efficiency (Phi(2)) during drought, and highly linear relationships (r(2) = 0.88) between P-g,P-max and the quantum yield of non-regulated energy dissipation (FNO) during post-drought recovery. We integrated the aforementioned relationships into SUCROS97, and the extended SUCROS-CF model explicitly accounted for slow and incomplete P-g,P-max recovery in the post-drought phase. Compared to SUCROS97, SUCROS-CF improved biomass prediction by 7%, due to a 19% improvement in P-g,P-max predictions under severe drought. We conclude that to accurately predict productivity during and after severe drought, leaf photosynthetic capacity kinetics need to be considered. Furthermore, CF measurements can be applied to predict leaf photosynthetic capacity during and after drought, enabling rapid drought phenotyping in breeding programs and yield loss assessment in the field.

Crops show considerable capacity to adjust their photosynthetic characteristics to seasonal changes in temperature. However, how photosynthesis acclimates to changes in seasonal temperature under future climate conditions has not been revealed. We measured leaf photosynthesis (A(n)) of wheat (Triticum aestivum L.) and rice (Oryza sativa L.) grown under four combinations of two levels of CO2 (ambient and enriched up to 500 mu mol/mol) and two levels of canopy temperature (ambient and increased by 1.5-2.0 degrees C) in temperature by free-air CO2 enrichment (T-FACE) systems. Parameters of a biochemical C-3-photosynthesis model and of a stomatal conductance (g(s)) model were estimated for the four conditions and for several crop stages. Some biochemical parameters related to electron transport and most g(s) parameters showed acclimation to seasonal growth temperature in both crops. The acclimation response did not differ much between wheat and rice, nor among the four treatments of the T-FACE systems, when the difference in the seasonal growth temperature was accounted for. The relationships between biochemical parameters and leaf nitrogen content were consistent across leaf ranks, developmental stages, and treatment conditions. The acclimation had a strong impact on g(s) model parameters: when parameter values of a particular stage were used, the model failed to correctly estimate g(s) values of other stages. Further analysis using the coupled g(s)-biochemical photosynthesis model showed that ignoring the acclimation effect did not result in critical errors in estimating leaf photosynthesis under future climate, as long as parameter values were measured or derived from data obtained before flowering.

Global dimming, a decadal decrease in incident global radiation, is often accompanied with an increase in the diffuse radiation fraction, and, therefore, the impact of global dimming on crop production is hard to predict. A popular approach to quantify this impact is the statistical analysis of historical climate and crop data, or use of dynamic crop simulation modelling approach. Here, we show that statistical analysis of historical data did not provide plausible values for the effect of diffuse radiation versus direct radiation on rice or wheat yield. In contrast, our field experimental study of 3 years demonstrated a fertilization effect of increased diffuse radiation fraction, which partly offset yield losses caused by decreased global radiation, in both crops. The fertilization effect was not attributed to any improved canopy light interception but mainly to the increased radiation use efficiency (RUE). The increased RUE was explained not only by the saturating shape of photosynthetic light response curves but also by plant acclimation to dimming that gradually increased leaf nitrogen concentration. Crop harvest index slightly decreased under dimming, thereby discounting the fertilization effect on crop yields. These results challenge existing modelling paradigms, which assume that the fertilization effect on crop yields is mainly attributed to an improved light interception. Further studies on the physiological mechanism of plant acclimation are required to better quantify the global dimming impact on agroecosystem productivity under future climate change.

Low light spell, one of the major causes of reduction in global radiation (global dimming), has become a new challenge to crop production. For assessing impacts of low light spells on wheat yield, we proposed a low light index (LLI) and quantified the effects of low light spell conditions occurring at different development stages on five key crop parameters of wheat (leaf photosynthetic capacity, photosynthetic initial light-use efficiency, specific leaf area, dry matter partitioning index for green leaf and harvest index) as functions of LLI using data from field experiments with different levels (50%, 66% and 84% of reduction in incident radiation from ambient) and durations (2d, 4d, 6d and 8d) of shading treatments. These functions were then incorporated into the generic process-based crop growth model SUCROS97 to develop a model, called SUCROS_LL hereafter, for assessing potential yield loss of wheat caused by low light spells. SUCROS_LL was validated and tested using independent data from field shading experiments and 19 agro-meteorological experimental stations, and then used for assessing the potential yield loss of wheat caused by low light spells in the Middle-Lower Reaches of Yangtze River Basin during 1961-2010. Our field experimental data showed that responses of wheat parameters and yield to low light depended on not only LLI, but also the development stages. Plant adaptive responses cannot fully mitigate the negative effects of short-term substantial reduction in incident radiation on wheat crop yield. Compared with SUCROS97, SUCROS_LL significantly improved prediction accuracy of wheat yield by 37% under field shading experimental conditions and 29% under natural low light spell conditions at the 19 agro-meteorological experimental stations. The simulated potential yield loss of wheat caused by low light spells averaged over 1961-2010 increased from the North (below 10%) to the South (above 40%) in the studied region. Potential yield loss averaged over the whole studied region was estimated to increase from the 1960s to the 1990s by 2.9% per decade, but decrease in the 2000s by 9.1% per decade. Although potential wheat-yield loss caused by-low-light spells has-been-decreased in the past decade in the studied region, the trends of global dimming suggests that breeding/choice of cultivars with better morphological plasticity in response to light availability is in need to mitigate the negative effects of reduction in incident radiation on wheat growth and yield. (C) 2017 Elsevier B.V. All rights reserved.

Accurately predicting photosynthesis in response to water and nitrogen stress is the first step toward predicting crop growth, yield and many quality traits under fluctuating environmental conditions. While mechanistic models are capable of predicting photosynthesis under fluctuating environmental conditions, simplifying the parameterization procedure is important toward a wide range of model applications. In this study, the biochemical photosynthesis model of Farquhar, von Caemmerer and Berry (the FvCB model) and the stomatal conductance model of Ball, Woodrow and Berry which was revised by Leuning and Yin (the BWB-Leuning-Yin model) were parameterized for Lilium (L. auratum × speciosum "Sorbonne") grown under different water and nitrogen conditions. Linear relationships were found between biochemical parameters of the FvCB model and leaf nitrogen content per unit leaf area (Na), and between mesophyll conductance and Na under different water and nitrogen conditions. By incorporating these Na-dependent linear relationships, the FvCB model was able to predict the net photosynthetic rate (An) in response to all water and nitrogen conditions. In contrast, stomatal conductance (gs) can be accurately predicted if parameters in the BWB-Leuning-Yin model were adjusted specifically to water conditions; otherwise gs was underestimated by 9% under well-watered conditions and was overestimated by 13% under water-deficit conditions. However, the 13% overestimation of gs under water-deficit conditions led to only 9% overestimation of An by the coupled FvCB and BWB-Leuning-Yin model whereas the 9% underestimation of gs under well-watered conditions affected little the prediction of An. Our results indicate that to accurately predict An and gs under different water and nitrogen conditions, only a few parameters in the BWB-Leuning-Yin model need to be adjusted according to water conditions whereas all other parameters are either conservative or can be adjusted according to their linear relationships with Na. Our study exemplifies a simplified procedure of parameterizing the coupled FvCB and gs model that is widely used for various modeling purposes.

Leaf photosynthesis of crops acclimates to elevated CO2 and temperature, but studies quantifying responses of leaf photosynthetic parameters to combined CO2 and temperature increases under field conditions are scarce. We measured leaf photosynthesis of rice cultivars Changyou 5 and Nanjing 9108 grown in two free-air CO2 enrichment (FACE) systems, respectively, installed in paddy fields. Each FACE system had four combinations of two levels of CO2 (ambient and enriched) and two levels of canopy temperature (no warming and warmed by 1.0-2.0°C). Parameters of the C3 photosynthesis model of Farquhar, von Caemmerer and Berry (the FvCB model), and of a stomatal conductance (gs ) model were estimated for the four conditions. Most photosynthetic parameters acclimated to elevated CO2 , elevated temperature, and their combination. The combination of elevated CO2 and temperature changed the functional relationships between biochemical parameters and leaf nitrogen content for Changyou 5. The gs model significantly underestimated gs under the combination of elevated CO2 and temperature by 19% for Changyou 5 and by 10% for Nanjing 9108 if no acclimation was assumed. However, our further analysis applying the coupled gs -FvCB model to an independent, previously published FACE experiment showed that including such an acclimation response of gs hardly improved prediction of leaf photosynthesis under the four combinations of CO2 and temperature. Therefore, the typical procedure that crop models using the FvCB and gs models are parameterized from plants grown under current ambient conditions may not result in critical errors in projecting productivity of paddy rice under future global change.

The decrease of solar radiation and increase of diffuse radiation proportion caused by haze affect crop productivity. To investigate the impacts of changed radiation by haze on the crop growth, a device that simulating haze-caused radiation changes was designed and tested in an open field during 2013 and 2014. Based on air quality index (AQI), haze is classified into three levels: mild, moderate and heavy haze. The changes of solar radiation under each level of haze condition are determined based on the relationship between AQI and radiation conditions. Global radiation decreases by 11%-21%, 22%- 32%, 33%-54% under mild, moderate, heavy haze while corresponding diffuse radiation proportion are 51%-59%, 60%-68%, 69%-87%, respectively. The optical properties (transmittance, scattering and spatial distribution of visible spectrum) of different thickness and layers of PE film used in the device were experimentally tested as covering materials to simulate radiation conditions under the moderate and heavy haze conditions. Based on the solar height and azimuth angles during crop growing season, the minimum plot area was determined as 20 m2 to secure 4 m2 shading area in a plot from 10:00 to 14:00. The haze simulator was designed as a cuboid with 5 m (east-west)×4 m (north-south) × 2 m (above the ground) with the cover material installed on top and without obstacle at the 4 sides to allow free air flow and heat exchange. The device was applied and tested in rice paddy field during two rice growing seasons (2013 and 2014). Solar radiation and other microclimate factors were automatically monitored and 30 minutes average values were recorded during the experiments. The results showed that the changes of total radiation and diffuse radiation proportion under different treatments matched the change scopes of solar radiation under moderate and heavy levels of haze. The spatial distribution of visible spectrum under treatment conditions was not significantly different from that under natural haze conditions. The differences of air, water and soil temperature between shading treatments and control were less than ±0.5℃ in most of the time, and the differences of air humidity between shading treatments and control were 4%-5%. The canopy thermal image showed no significant difference between shading treatment and control at rice heading stage in 2014. These results indicated that the device designed in this study can be used to simulate haze-caused radiation conditions in open field and has the potential to provide effective field experimental means for investigating the effects of haze on crops.

[Objectives]Functional-structural models(FSPM) are models describing the development of the structure of plant as governed by physiological processes,which can be a valuable tool for examining how physiology and morphology interact in determining plant processes.However,the output of process-based crop growth model is organ dry weight,which cannot be used directly to simulate the change of the organ structure.The aim of this study was to quantify the relationship between organ dry weight and external quality traits of ornamental plants,so as to link the output of crop growth model to the input of structural model,which was an important step for developing a functional-structural model.[Methods]For this purpose,three experiments with different planting dates(July 12,2007; October 12,2007; October 30,2007) and densities(16.00,11.10 and 8.16 plant·m-2) were conducted in a multi-span Venlo type greenhouse of Nanjing(32°N,118°E) from July 2007 to April 2008.The cultivar used in the experiments was Euphorbia pulcherrima Willd‘Red China'which is one of the main greenhouse pot flowers in the world and the most popular festival flowers in China.The plot with 50 plants for each density treatment with three replicas was arranged in a randomized block design.In all experiments,3 plants of each plot(9 plants per treatment) were randomly selected for non-destructive external quality measurements once every 7 days after planting.The non-destructive measurements include canopy diameter(Cd),leaf number(N),plant height(H),diameter of the main stem(Dst),ratio of canopy diameter to plant height(Rdh) and diameter of flower canopy(Cdf).One plant of each plot(3 plants per treatment) was randomly selected for destructive measurements once every development stage after planting.The destructive measurements include leaf dry weight(Wlv),stem dry weight(Wst) and bract dry weight per plant(Wbr).The relationship between organ dry weight and external quality of pot planted poinsettia was quantified based on the experimental data.Independent experimental data were used to validate the quantitative relationship.[Results]The results showed that our research gave satisfactory predictions of exter-nal quality traits for pot planted poinsettia grown in greenhouse.The coefficient of determination(R2) and the relative root mean squared error(rRMSE) between the predicted and measured value of pot planted poinsettia were,respectively,0.97 and 5.07% for canopy diameter,0.96 and 9.16% for number of leaves,0.96 and 6.26% for plant height,0.93 and 5.62% for diameter of main stem,0.94 and 3.70% for ratio of canopy diameter to plant height and 0.96 and 10.60% for diameter of flower canopy.[Conclusions]The quantitative relationship developed in this study constructs a bridge between functional model and structural model and it lays a foundation for developing a functional-structural model of pot planted poinsettia.Further evaluation is needed when applying this quantitative relationship to a wider range of variety and environment conditions.

Elevated CO2 and temperature strongly affect crop production, but understanding of the crop response to combined CO2 and temperature increases under field conditions is still limited while data are scarce. We grew wheat (Triticum aestivum L.) and rice (Oryza sativa L.) under two levels of CO2 (ambient and enriched up to 500 μmol mol−1) and two levels of canopy temperature (ambient and increased by 1.5–2.0 °C) in free‐air CO2 enrichment (FACE) systems and carried out a detailed growth and yield component analysis during two growing seasons for both crops. An increase in CO2 resulted in higher grain yield, whereas an increase in temperature reduced grain yield, in both crops. An increase in CO2 was unable to compensate for the negative impact of an increase in temperature on biomass and yield of wheat and rice. Yields of wheat and rice were decreased by 10–12% and 17–35%, respectively, under the combination of elevated CO2 and temperature. The number of filled grains per unit area was the most important yield component accounting for the effects of elevated CO2 and temperature in wheat and rice. Our data showed complex treatment effects on the interplay between preheading duration, nitrogen uptake, tillering, leaf area index, and radiation‐use efficiency, and thus on yield components and yield. Nitrogen uptake before heading was crucial in minimizing yield loss due to climate change in both crops. For rice, however, a breeding strategy to increase grain number per m2 and % filled grains (or to reduce spikelet sterility) at high temperature is also required to prevent yield reduction under conditions of global change.

This experiment was c onducted to investigate the effects of increased atmospheric temperature and CO 2 concentration during crop growth on the chemical composition and in vitro rumen fermentation characteristics of wheat straw.The field experiment was carried out from November 2012 to June 2013 at Changshu（31°32'93 "N,120°41'88" E） agro-ecological experimental station.A total of three treatments were set.The concentration of CO 2 was increased to 500 umol/mol in the first treatment（CO 2 group）.The temperature was increased by 2 ℃ in the second treatment（TEM group） and the concentration of CO 2 and temperature were both increased in the third treatment（CO 2 + TEM group）.The mean temperature and concentration of CO 2 in control group were 10.5 ℃ and413 umol/mol.At harvesting,the wheat straws were collected and analyzed for chemical composition and in vitro digestibility.Results showed that dry matter was significantly increased in all three treatments.Ether extracts and neutral detergent fiber were significantly increased in TEM and CO 2 + TEM groups.Crude protein was significantly decreased in CO 2 + TEM group.In vitro digestibility analysis of wheat straw revealed that gas production was significantly decreased in CO 2 and CO 2 + TEM groups.Methane production was significantly decreased in TEM and CO 2 + TEM groups.Ammonia nitrogen and microbial crude protein were significantly decreased in all three treatments.Total volatile fatty acids were significantly decreased in CO 2 and CO 2 + TEM groups.In conclusion,the chemical composition of the wheat straw was affected by temperature and CO 2 and the in vitro digestibility of wheat straw was reduced,especially in the combined treatment of temperature and CO 2 .

The aim of this study was to quantitatively investigate the impacts of nitrogen on growth dynamics and yield, so as to facilitate the optimization of nitrogen management for muskmelon crop in plastic greenhouse. For this purpose, four experiments with different levels of nitrogen treatment and planting dates on muskmelon ( Cucumis melo L. ‘Nanhaimi’ and ‘Xizhoumi 25’) were conducted in plastic greenhouse located at Sanya from Nov. 2012 to Sept. 2014. The quantitative relationship between leaf nitrogen content and growth dynamics and yield of muskmelon was determined and incorporated into a photosynthesis-driven crop growth model (SUCROS). Independent experimental data were used to validate the model. The critical leaf nitrogen content at flowering stage for muskmelon ‘Nanhaimi’ and ‘Xizhoumi 25’ were 19.8 and 21.0 mg·g −1 . The coefficient of determination ( r 2 ) and the relative root-mean-squared error (rRMSE) between the predicted and measured value of growth dynamics and yield were, respectively, 0.91 and 10.8% for leaf area index (LAI), 0.90 and 19.6% for dry weight of shoot (DWSH), 0.76 and 30.3%, 0.82 and 21.1%, and 0.92 and 11.9% for dry weight of leaf (DWL), stem (DWST), and fruit (DWF), 0.91 and 17.3%, 0.89 and 13.9%, 0.86 and 27.8%, and 0.88 and 20.6% for soluble sugar content (SU), soluble protein content (PR), vitamin C content (VC), and soluble solids content (SO) of fruit, and 0.90 and 10.1% for fresh weight of fruit (FWF). The model could be used for the optimization of nitrogen management for muskmelon production in plastic greenhouse. Further calibration and test would be needed during the application of the model in wider range of conditions and muskmelon cultivars.

氮素是影响花卉生长与外观品质的重要营养元素。定量研究氮素对温室切花百合外观品质的影响,可为切花百合氮素管理提供决策支持。以百合‘索邦’和‘西伯利亚’为材料,根据不同定植期、生长中后期不同速效氮素水平处理试验,以冠层累积吸收辐热积（PTI）为发育尺度,以现蕾期叶片累积氮含量为植株氮素特征指标,定量分析氮素对切花百合外观品质指标（叶面积指数、株高、出叶数、第1花蕾长度与第1花蕾直径）和出花率的动态影响。在此基础上,建立氮素对切花百合外观品质影响的模拟模型,并用独立的试验数据对模型进行检验。结果表明,模型对叶面积指数、株高、出叶数、第1花蕾长度、第1花蕾直径、一级花、二级花、三级花和四级花的预测效果较好,预测值与实测值之间基于1∶1线的决定系数（r2）分别为0.92、0.85、0.86、0.91、0.88、0.88、0.88、0.91和0.91,相对回归估计标准误（rRMSE）分别为0.09、0.10、0.14、0.13、0.12、0.18、0.15、0.18和0.21。研究建立的模型为长江中下游地区温室切花百合生产中氮素的优化管理提供了模型工具,也为露地栽培切花百合生产中氮素的优化管理提供了参考。

The integration of functional and structural crop models can be valuable for examining how physiology and morphology interact in determining plant processes. The output of functional crop growth models, however, is organ dry weight which cannot be used directly as input for structural models. The aim of this study was to quantify the relationships between organ dry weight and morphological (external quality) traits of plants so as to bridge the functional and structural crop growth models. Using chrysanthemum (Chrysanthemum morifolium 'Jinba') as a case study, four experiments with different planting dates were conducted in a lean-to type greenhouse from 2006 to 2008. Plant height, number of green leaves per plant and flower-head diameter was, respectively, determined as a function of organ dry weight and stem diameter was determined as a function of plant height. Independent experimental data were used to validate the model. The results show that the model developed in this study can predict the external quality traits of chrysanthemum plants satisfactory. The coefficient of determination between the predicted and measured data was 0.99 for plant height, 0.94 for number of green leaves per plant, 0.99 for flower-head diameter and 0.80 for stem diameter. Further evaluation is needed when applying this model to a wider range of variety and environment.

Because of the rapid development of transgenic maize, the potential effect of transgene flow on seed purity has become a major concern in public and scientific communities. Setting a proper isolation distance in field experiments and seed production is a possible solution to meet seed-quality standards and ensure adventitious contamination of products is below a specific threshold. By using a Gaussian plume model as basis and data recorded by meteorological stations as input, we have established a simple regionally applicable maize gene-flow model for prediction of the maximum threshold distances (MTD) at which gene-flow frequency is equal to or lower than a threshold value of 1 or 0.1 % (MTD1%, MTD0.1%). After optimization of the model variables, simulated outcrossing rate was a good fit to data obtained from field experiments (y = 1.156x, R 2 = 0.8913, n = 30, P < P 0.01). In the process of model calibration, it was found that only 15.82 % of the total amount of the pollen released by each plant participated in the dispersal process. The variable “a” for genetic pollen competitiveness between donor and recipient was introduced into our model, for the “Zinuo18” and “Su608” used, “a” was 17.47. Finally, the model was successfully used in the spring maize-growing region of Northeast China. The range of MTD1% and MTD0.1% in this region varied from 10 m to 49 m and from 17 m to 125 m, respectively.

为准确诊断和防治设施蔬菜病害提供有效工具,本研究系统收集了设施蔬菜作物(黄瓜、番茄和辣椒)43种病害的症状特征和相关病害防治管理知识,将病害的典型症状和一般症状进行特征提取,依据专家经验形成203条知识规则,将病害诊断知识数值化与产生式规则相结合对知识进行有效的表达,建立了病害诊断与管理知识库.以SQL Server 2005作为数据库管理工具,建立了系统动态数据库.数据库用于存放用户输入病症信息、已知病症事实和推理过程产生的中间信息及最终结论.采用最佳优先搜索作为搜索策略,使用正向推理和正反混合推理,利用我们前期建立的“一步诊断”和“深入诊断”两个诊断推理模型实现病害诊断.利用Visual Studio 2008作为开发工具,综合集成知识库、数据库和推理模型,建立了基于Web的设施蔬菜病害诊断与防治管理专家系统.系统具有病害查询、病害诊断、病害防治与管理方法等查询与咨询功能,此外,专家也可在后台随时更新和添加新的蔬菜作物及病害.本研究建立的系统可为主要设施栽培蔬菜作物(黄瓜、番茄和辣椒)43种病害的早期诊断和防治管理提供决策支持.

【Objective】In order to assess the impacts of low level of radiation caused by cloudy or rainy weather conditions on wheat crop production,it is necessary to quantify the effects of low level of radiation on wheat growth and yield.【Method】Field experiments with three weak gluten winter wheat(Triticum aestivum L.) cultivars Yangmai 15,Yangmai 13 and Ningmai 9 were conducted during the three growing seasons.Shading treatments with four radiation intensities(100%,50%,34% and 16% of natural radiation) and four durations(2 d,4 d,6 d and 8 d) at milk filling stage in the three grown seasons were designed to simulate the low level of radiation caused by cloudy or rainy weather conditions.Based on the experimental data,the impacts of low level of radiation on wheat growth processes and yield were quantitatively analyzed,and the impacting factors of low level of radiation on photosynthesis,leaf area index and harvest index were determined,respectively.These functions were then integrated with the SUCROS model to develop a dynamic model for predicting the effects of low level of radiation at milk filling stage on the growth and yield of wheat.Independent experimental data were used to validate the model.【Result】 The critical daily total photosynthetically active radiation(PAR) and duration were determined as 3.71 MJ.m-2 and 2 d for leaf net photosynthetic rate;3.71 MJ.m-2 and 4 d for leaf area index,biomass production and grain yield.Model validation results showed that the determination coefficient(R2) between the predicted and measured values of leaf net photosynthetic rate,leaf area index,total biomass production and grain yield were 0.78,0.88,0.96 and 0.96,respectively,and the relative root mean squared error(rRMSE) were 5.69%,12.46%,3.32% and 5.24%,respectively.【Conclusion】The model developed in this study gave satisfactory predictions of the impacts of low level of radiation at milk filling stage on wheat growth and grain yield,hence,can be used for assessing the impacts of low level of radiation caused by cloudy or rainy weather conditions on wheat production.