Cao Weixing

Monitoring leaf nitrogen accumulation in wheat with hyper-spectral remote sensing

Abstract Crop nitrogen status is a key indicator for evaluating crop growth, increasing yield and improving grain quality. Non-destructive and rapid assessment of leaf nitrogen is required for improving nitrogen management in wheat production. This study aims at identification of the quantitative relationship between leaf nitrogen accumulation and canopy reflectance spectra in winter wheat (Triticum aestivum L.), and to derive regression equations to monitor N nutrition status in wheat. 3 field experiments were conducted with different N application rates and wheat cultivars across 3 growing seasons, and time-course measurements were taken on canopy spectral reflectance, leaf N content and leaf dry weights under various treatments. In these studies, leaf nitrogen accumulation in wheat increased with increasing nitrogen rates. Canopy reflectance changed with increasing leaf nitrogen accumulation. Sensitivity bands mainly occurred in near infrared and visible light, and strong correlation existed between red light and leaf nitrogen accumulation. The relationships of 8 vegetation indicators and leaf nitrogen accumulation were analyzed using statistical models. Hyper-spectral variables were significantly correlated with leaf nitrogen accumulation, and the relationships between the leaf nitrogen accumulation and SDr/SDb, FD742 and AVHRR-GVI were all highly significant with determination of coefficients (R2) of 0.9163, 0.9097 and 0.9142, respectively, and standard errors (SE) of 1.165, 1.079 and 1.077, respectively. Tests with another independent dataset showed that FD742 and REPIG could be well used to predict leaf nitrogen accumulation in wheat with R2 of 0.8449 and 0.8394, and root mean square error (RMSE) of 0.984 and 1.014, respectively. This suggests that FD742 and REPIG can be used to estimate leaf nitrogen accumulation, of which FD742 performed better in modeling and testing.

Methods on Identification and Screening of Rice Genotypes with High Nitrogen Efficiency

In order to establish methods for indentification and screening of rice genotypes with high nitrogen (N) efficiency, N absorption efficiency (NAE), N utilization efficiency (NUE) and N harvest index (NHI) in ten rice genotypes were investgated at the elongation, booting, heading and maturity stages under six N levels in a pot experiment with soil-sand mixtures at various ratios. NAE in various rice genotypes firstly increased, peaked under a medium nitrogen rate of 0.177 g/kg and then decreased, but NUE and NHI always decreased with increasing nitrogen levels. NAE in various rice genotypes ever increased with growing process and NUE indicated a descending tendency of elongation stage>heading stage>maturity stage>booting stage. N level influenced rice NAE, NUE and NHI most, followed by genotype, and the both effects were significant at 0.01 level. In addition, the interaction effects of genotype and nitrogen level on rice NAE and NUE were significant at 0.01 level, but not significant on rice NHI. Because the maximum differences of NAE and NUE were found at the elongation stage, it was thought to be the most suitable stage for identification and screening these two paremeters. Therefore, the optimum conditions for identification and screening of rice NAE, NUE and NHI in a pot experiment were the nitrogen rate of 0.157 g/kg at the elongation stage, low nitrogen at the elongation stage, and the nitrogen rate of 0.277 g/kg at the maturity stage, respectively.

Monitoring grain protein accumulation dynamics with canopy reflectance spectra in wheat.

Grain protein is an important index indicating wheat quality status, and nondestructive and quick assessments of grain protein accumulation dynamics is necessary for cultural regulation and quality classification in wheat (Triticum aestivum L.) production. The objectives of this study were to determine the relationships between plant nitrogen nutrition status, grain protein accumulation, and canopy reflectance spectra in winter wheat, therefore, to derive regression equations for monitoring grain protein accumulation with canopy hyper-spectral remote sensing. Three types of cultivars, i.e., high protein content (Xuzhou 26 and Yu-mai 34), medium protein content (Yangmai 10, Yangmai 12, and Huaimai 20), and low protein content (Ningmai 9) were used in three field experiments under different nitrogen levels in the growing seasons of 2003–2006. Time-course measurements were taken on canopy hyperspectral reflectance, plant weight, nitrogen content and grain protein accumulation (GPA) during the experimental periods. The results showed that the cumulative value of canopy nitrogen nutrition index (CNNI) from anthesis to specific day were highly correlated with grain protein accumulation at corresponding day across grain filling with the best predictor of plant N accumulation (PNA). According to the regression analyses between vegetation indices and canopy nitrogen nutrition index, several key spectral parameters could accurately estimate the changes in plant N status across different growth stages, nitrogen levels, and growing seasons with the same spectral parameters for each wheat cultivar. According to the technical route of key spectral parameters-canopy N nutrition index-grain protein accumulation, estimating models on grain protein accumulation were constructed on the basis of canopy hyper-spectral parameters by linking the above two models with canopy N nutrition index as intersection in wheat. Tests with other independent dataset showed that the key spectral index SDr/SDb on the basis of the technical route of SDr/SDb-PNA-GNA could be used to predict grain protein accumulation from 7d after anthesis to maturity,with the predictive precision (R2) of 0.954 and the relative error (RE) of 13.1%, respectively. It can be concluded that dynamic change of grain protein accumulation in wheat could be monitored directly with key vegetation spectral index.

Modeling Leaf Length Growth and Leaf Shape in Winter Wheat

A set of empirical equations for calculating the evolution of leaf length through thermal time taking into account leaf position in wheat plants and the nitrogen status of the leaf is presented. A set of equation describing the variation of lamina width along its length thus describing an important feature of leaf shape is also given. The descriptive model is calibrated and validated in field experiments with different nitrogen rates and winter wheat cultivars in two growing seasons. The model had a good performance in predicting leaf length growth, and should be useful for taking into account leaf length and leaf shape in models of wheat growth.

Physico-chemical properties of A- and B-type starch granules in wheat.

以小麦面粉中分离纯化出的A-、B-型淀粉粒为材料，研究其形态及理化特性。淀粉粒扫描电镜形态观察显示，小麦全淀粉中A-、B-型淀粉粒形态差异显著，分离出的A-、B-型淀粉粒无混杂。分离纯化出的A-型和B-型淀粉粒粒径范围分别为4．45×44．46μm和0．47×11．16μm，单位质量数量分别为1．23×10^10g^-1和6．70×10^10g^-1，直链淀粉含量分别为27．70％和22．62％。B-型淀粉粒的膨胀势较大，但糊化值明显小于A-型淀粉粒。重组淀粉中B．型淀粉粒的重量比例小于30％时对淀粉糊化特性影响很大，超过30％后，淀粉粒粒级分布对糊化特性的影响变小。A-and B-type starch granules were isolated and purified from wheat(Triticum aestivum L.) flour to study their physico-chemical properties.Starch granule image of scanning electron microscopy(SEM) showed that there was obvious morpho-logical difference between A-and B-type starch granules,and they could be completely isolated without mixture due to the unique type of starch granule in each group.The diameter of A-type starch granule was 4.45-44.46 μm and there were 1.23×1010 granules per gram starch,whereas the two values of B-type granule were 0.47-11.16 μm and 6.70×1010,respectively.Amylose content in A-and B-type granules was 27.70% and 22.62%,respectively.Compared with the A-type granules,the B-type granules had higher pasting temperature and lower viscosities of peak,breakdown,and setback.The B-type granules contributed greatly to the pasting properties of the reconstituted starches when the fraction of B-type granules was less than 30%.Effects of starch granule size distribution on pasting property of reconstituted starch decreased when the fraction of B-type granules was higher than 30%.