The scale mismatch between remote sensing observations and state variables simulated by crop growth models decreases the reliability of crop yield estimates. To overcome this problem, we implemented a two-step data-assimilation approach: first, we generated a time series of 30-m-resolution leaf area index (LAI) by combining Moderate Resolution Imaging Spectroradiometer (MODIS) data and three Landsat TM images with a Kalman filter algorithm (the synthetic KF LAI series); second, the time series were assimilated into the WOFOST crop growth model to generate an ensemble Kalman filter LAI time series (the EnKF-assimilated LAI series). The synthetic EnKF LAI series then drove the WOFOST model to simulate winter wheat yields at 1-km resolution for pixels with wheat fractions of at least 50%. The county-level aggregated yield estimates were compared with official statistical yields. The synthetic KF LAI time series produced a more realistic characterization of LAI phenological dynamics. Assimilation of the synthetic KF LAI series produced more accurate estimates of regional winter wheat yield ( = 0.43; root-mean-square error (RMSE) = 439 kg ha ) than three other approaches: WOFOST without assimilation (determination coefficient = 0.14; RMSE = 647 kg ha ), assimilation of Landsat TM LAI ( = 0.37; RMSE = 472 kg ha ), and assimilation of S-G filtered MODIS LAI ( = 0.49; RMSE = 1355 kg ha ). Thus, assimilating the synthetic KF LAI series into the WOFOST model with the EnKF strategy provides a reliable and promising method for improving regional estimates of winter wheat yield.
Wheat is one of the most important cereals, whose growth and development is strongly limited by drought. This study investigated the physiological and metabolic response of six winter wheat cultivars to drought with the emphasis on the induction of dominant metabolites affected by the treatment and genotypes or both. The plants were exposed to a moderate (non-lethal) drought stress, which was induced by withholding watering for six days under controlled greenhouse conditions. A decline in CO2 assimilation (Pn) and transpiration rate, stomata closure, a decrease in relative water content (RWC) and increase of malondialdehyde content were observed in drought-treated plants of all cultivars. These changes were most pronounced in Ellvis, while Soissons was able to retain the higher RWC and Pn. Among the studied metabolites, sugars (sucrose, glucose, fructose, several disaccharides), organic acids (malic acid, oxalic acids), amino acids (proline, threonine, gamma-aminobutyric acid (GABA), glutamine) and sugar alcohols such as myo-inositol accumulated to higher levels in the plants exposed to drought stress in comparison with the control. The accumulation of several metabolites in response to drought differed between the genotypes. Drought induced the production of sucrose, malic acid and oxalic acid, unknown organic acid 1, unknown disaccharide 1, 2 and 3, GABA, L-threonine, glutamic acid in four (Soissons, Zitarka, Antonija or Toborzo) out of six genotypes. In addition, Soissons, which was the most drought tolerant genotype, accumulated the highest amount of unknown disaccharide 5, galactonic and phosphoric acids. The two most drought sensitive cultivars, Srpanjka and Ellvis, demonstrated different metabolic adjustment in response to the stress treatment. Srpanjka responded to drought by increasing the amount of glucose and fructose originated from hydrolyses of sucrose and accumulating unidentified sugar alcohols 1 and 2. In Ellvis, drought caused inhibition of photosynthetic carbon metabolism, as evidence by the decreased Pn, gs, RWC and accumulation levels of sugar metabolites (sucrose, glucose and fructose). The results revealed the differences in metabolic response to drought among the genotypes, which drew attention on metabolites related with general response and on those metabolites which are part of specific response that may play an important role in drought tolerance.
Real-time, nondestructive monitoring of crop nitrogen (N) status is important for precise N management in winter wheat production. Nadir viewing passive multispectral sensors have limited utility for measuring the N status of winter wheat in middle and bottom layers, and multi-angular remote sensors may instead improve detection of whole canopy physiological and biochemical parameters. Our objective was to improve the predictive accuracy and angular stability of leaf nitrogen concentration (LNC) measurement by constructing a novel Angular Insensitivity Vegetation Index (AIVI). We quantified the relationship between LNC and ground-based multi-angular hyperspectral reflectance in winter wheat ( L.) across different growth stages, plant types, N rates, planting density, ecological sites and years. The optimum vegetation indices (VIs) obtained from 17 traditional indices reported in the literature were tested for their stability in estimating LNC at 13 view zenith angles (VZAs) in the solar principal plane (SPP). Overall the back-scatter direction gave improved index performance, relative to the nadir and forward-scattering direction. Red-edge VIs (e.g., mND705, GND [750,550], NDRE, RI-1dB) were highly correlated with LNC. However, the relationships strongly depended on experimental conditions, and these VIs tended to saturate at the highest LNC (4.5%). To further overcome the influence of different experimental conditions and VZAs on VIs, we developed a novel index, Angular Insensitivity Vegetation Index (AIVI), based on red-edge, blue and green bands. Our new model showed the highest association with LNC ( = 0.73–0.87) compared to traditional VIs. Investigating AIVI predictive accuracy in measuring LNC across view zenith angles (VZAs) revealed that performance was the highest at − 20° and was relatively homogenous between − 10° and − 40°. This provided a united, predictive model across this wide-angle range, which enhances the possibility of N monitoring by using portable monitors. Testing of the models with independent data gave of 0.84 at − 20°, and 0.83 across the range of − 10° to − 40°, respectively. These results suggest that the novel AIVI is more effective for monitoring LNC than previously reported VIs for predicting accuracy, monitoring model stability and view angle independency. More generally, our model indicates the importance of accounting for angular effects when analyzing VIs under different experimental conditions.
Crop yields are influenced by growing season length, which are determined by temperature and agronomic management, such as sowing date and changes in cultivars. It is essential to quantify the interaction between climate change and crop management on crop phenology to understand the adaptation of farming systems to climate change. Historical changes in winter wheat phenology have been observed across the Loess Plateau of China during 1981–2009. The observed dates of sowing, emergence, and beginning of winter dormancy were delayed by an average of 1.2, 1.3, and 1.2 days decade , respectively. Conversely, the dates of green-up (regrowth after winter dormancy), anthesis, and maturity advanced by an average of 2.0, 3.7, and 3.1 days decade , respectively. Additionally, the growth duration (sowing to maturity), overwintering period, and vegetative phase (sowing to anthesis) shortened by an average of 4.3, 3.1, and 5.0 days decade , respectively. The changes in phenological stages and phases were significantly negatively correlated with a temperature increase during this time. Differently to most other phase changes, the reproductive phase (anthesis to maturity) prolonged by an average of 0.7 day decade , but this was spatially variable. The prolonged reproductive phase was due to advanced anthesis dates and consequently caused the reproductive phase to occur during a cooler part of the season, which led to an extended reproductive phase. Applying a crop simulation model using a field-tested standard cultivar across locations and years indicated that the simulated phenological stages have accelerated with the warming trend more than the observed phenological stages. This indicated that, over the last decades, later sowing dates and the introduction of new cultivars with longer thermal time requirement have compensated for some of the increased temperature-induced changes in wheat phenology.
Grain yield is a trait of paramount importance in the breeding of all cereals. In wheat (Triticum aestivum L.), yield has steadily increased since the Green Revolution, though the current rate of increase is not forecasted to keep pace with demand due to growing world population and increasing affluence. While several genome-wide association studies (GWAS) on yield and related component traits have been performed in wheat, the previous lack of a reference genome has made comparisons between studies difficult. In this study, a GWAS for yield and yield-related traits was carried out on a population of 322 soft red winter wheat lines across a total of four rain-fed environments in the state of Virginia using single-nucleotide polymorphism (SNP) marker data generated by a genotyping-by-sequencing (GBS) protocol. Two separate mixed linear models were used to identify significant marker-trait associations (MTAs). The first was a single-locus model utilizing a leave-one-chromosome-out approach to estimating kinship. The second was a sub-setting kinship estimation multi-locus method (FarmCPU). The single-locus model identified nine significant MTAs for various yield-related traits, while the FarmCPU model identified 74 significant MTAs. The availability of the wheat reference genome allowed for the description of MTAs in terms of both genetic and physical positions, and enabled more extensive post-GWAS characterization of significant MTAs. The results indicate a number of promising candidate genes contributing to grain yield, including an ortholog of the rice aberrant panicle organization (APO1) protein and a gibberellin oxidase protein (GA2ox-A1) affecting the trait grains per square meter, an ortholog of the Arabidopsis thaliana mother of flowering time and terminal flowering 1 (MFT) gene affecting the trait seeds per square meter, and a B2 heat stress response protein affecting the trait seeds per head.
Five modern cultivars of winter wheat ( L.): Yangmai16 (Y16), Yangmai 15 (Y15), Yangfumai 2 (Y2), Yannong 19 (Y19) and Jiaxing 002 (J2) were investigated to determine the impacts of elevated ozone concentration (E-O ) on photosynthesis-related parameters and the antioxidant system under fully open-air field conditions in China. The plants were exposed to E-O at 1.5 times the ambient ozone concentration (A-O ) from the initiation of tillering to final harvest. Pigments, gas exchange rates, chlorophyll fluorescence, antioxidants contents, antioxidative enzyme activity and lipid oxidation were measured in three replicated plots throughout flag leaf development. Results showed that significant O effects on most variables were only found during the mid-grain filling stage. Across five cultivars, E-O significantly accelerated leaf senescence, as indicated by increased lipid oxidation as well as faster declines in pigment amounts and photosynthetic rates. The lower photosynthetic rates were mainly due to non-stomatal factors, e.g. lower maximum carboxylation capacity and electron transport rates. There were strong interactions between O and cultivar in photosynthetic pigments, light-saturated photosynthesis rate and chlorophyll a fluorescence with O -sensitive (Y19, Y2 and Y15) and O -tolerant (J2, Y16) cultivars being clearly differentiated in their responses to E-O . E-O significantly influenced the antioxidative enzymes but not antioxidant contents. Significant interactions between O and cultivar were found in antioxidative enzymes, such as SOD and CAT, but not in stomatal conductance ( ). Therefore, it can be concluded that antioxidative enzymes rather than or antioxidants are responsible for the differential responses to E-O among cultivars. These findings provide important information for the development of accurate modeling O effects on crops, especially with respect to the developmental stage when O damage to photosynthesis becomes manifest.
Although N fertilizers are not acidic, their inputs to soil are acid forming. As a result of the long-term use of N fertilizers, soils in the Great Plains are becoming more acidic and this acidity may become a yield-limiting factor. In 1970, long-term plots were initiated to compare sources (anhydrous NH3, NH4NO3, urea, and S-coated urea), application rates (34, 68, 136, and 272 kg N ha(-1)), and an untreated check (0 N) on wheat (Triticum aestivum L.) grain yield, soil pH, exchangeable base cations, and Al saturation. For the soil properties evaluated, significant differences among the different N sources did not exist aft er 30 annual applications of N fertilizer. The long-term N fertilization significantly reduced soil pH in the surface soil layer (0-15 cm), especially at the higher application levels. Soil pH decreased with time and was significantly related to the amount of total N applied for each N source. Nitrogen fertilization with each N source significantly increased exchangeable Al and Al saturation (Al-sat) but decreased exchangeable base cations (Ca2+ and Mg2+). Both exchangeable Al and Al-sat increased with increasing N rate and were inversely related to soil pH. Despite decreased soil pH levels to <5.0 as early as 1980 in the experiment, significant reductions of wheat yield did not occur until 1995. Reductions in yield occurring between 1995 and 2002 coincided with the greatest change in soil pH occurring during the same time period.
To ascertain genetic diversity, population structure and linkage disequilibrium (LD) among a representative collection of Chinese winter wheat cultivars and lines, 90 winter wheat accessions were analyzed with 269 SSR markers distributed throughout the wheat genome. A total of 1,358 alleles were detected, with 2 to 10 alleles per locus and a mean genetic richness of 5.05. The average genetic diversity index was 0.60, with values ranging from 0.05 to 0.86. Of the three genomes of wheat, ANOVA revealed that the B genome had the highest genetic diversity (0.63) and the D genome the lowest (0.56); significant differences were observed between these two genomes (P0.1), with a whole genome LD decay distance of approximately 2.2 cM (r(2)>0.1, P<0.001). Evidence from genetic diversity analyses suggest that wheat germplasm from other countries should be introduced into Chinese winter wheat and distant hybridization should be adopted to create new wheat germplasm with increased genetic diversity. The results of this study should provide valuable information for future association mapping using this Chinese winter wheat collection.
Understanding the historical variability of winter wheat yield in China can provide insights into future wheat production security and adaptation measures. In this study, two indices, i.e., yield gap percentage ( ) and yield variation difference ( ), were employed to investigate the winter wheat relatively yield level and yield variability from 1980 to 2010 in 1340 counties in China using a county-level dataset and a crop model (APSIM-Wheat). The study area was classified into four types of regions with different yield patterns: relatively high-yield level and high stability (RHY-RHS), relatively high-yield level and low stability (RHY-RLS), relatively low-yield level and high stability (RLY-RHS), and relatively low-yield level and low stability (RLY-RLS). Relatively high-yield levels in terms of were found in the eastern parts of the Northern China Plain (NC) and the Yellow and Huai River Valleys (YH), the southern area of Xinjiang (XJ), and the northern part of the Middle and Lower Yangtze Valleys (YV), as well as a small section in the middle of Southwestern China (SW). Yield potential was more stable than the actual yield in most of the study regions, with positive . A decreasing trend was observed in both the and over the three decades. Consequently, the county percentage of RHY-RHS and RHY-RLS increased but the percentage of RLY-RHS and RLY-RLS decreased over the three decades, indicating improved winter wheat yield level and yield stability in China, which might be attributed to the development of agricultural technology and breeding. Nonetheless, there are still some vulnerable areas in need of further attention. Western NC and southern YH are regions with a potentially stable yield in the future. Given that YH accounts for a large proportion of winter wheat production in China, further investigation should be conducted to identify the underlying causes of the low-yield level and high yield variability in YH.
Turbulent fluxes at the land surface measured by the Eddy Covariance (EC) technique are typically considerably less than the difference between net radiation and ground heat flux. This is known as the energy balance closure (EBC) problem. It is crucial for validating land surface models as it provokes substantial uncertainty to the magnitude and partitioning of energy fluxes. The gap in the energy balance calls for searching for additional energy terms in the soil-plant-atmosphere system. To evaluate the contribution of these minor storage terms to the measured EBC, we conducted an experimental study to evaluate the contribution of these minor storage terms to measured EBC in the Kraichgau region in southwest Germany over two consecutive growing seasons (2015 and 2016). The measured and calculated minor storage terms comprised the enthalpy change in the plant canopy ( ), the air enthalpy change ( ), the energy consumption and release by photosynthesis and respiration ( ), and the atmospheric moisture change ( ). Furthermore, the soil heat storage ( ) was determined at different locations within the EC footprint and compared to the single point measurements of at the EC station. Calorimetric and harmonic analysis were performed to compute ground heat flux. had the strongest effect in improving EBC due to the high net CO uptake during the productive phase of plant growth. In 2015, all minor storage terms together increased EBC by 5.0% on average, with a maximum value of 7.4% in May, while the improvement in 2016 was 6.8% on average and 8.4% in May. Ground heat flux computed with the harmonic analysis based on plate data narrowed the EBC by 3% more than the calorimetric method. In summary, a better EBC can be achieved by considering minor storage terms and applying a harmonic analysis to ground heat flux data. Regarding future research, we recommend to focus on year-round measurements of energy terms because energy stored during the growing season might be lost from the system during the rest of the year. Nonetheless, the significant contribution of minor energy terms to EBC indicates that turbulent energy fluxes are most likely overestimated when all the missing energy is assumed to be turbulent–the typical approach when fluxes are corrected by the Bowen ratio post-closure method for instance.