Temporal and Spatial Dynamics of Organ Water Content in Maize with Different Senescence Types.

Understanding the water status of specific organs can be helpful in evaluating the life activities and growth conditions of maize. To accurately judge organ growth conditions and thus design appropriate interventions, it is necessary to clarify the true water dynamics of each maize organ. Using multiple maize cultivars with different growth periods, spatio-temporal water dynamics were analyzed here in the leaves, stalks, and ear components. Leaf water content was found to gradually decrease from both the bottom and top of the plant to the middle, whereas stalk water content decreased sequentially from the top to the bottom. Each successively higher node from the bottom of the plant was associated with decreases of 0.99% and 1.27% water content in the leaves and stalks, respectively. The water dynamics in leaves and internodes showed three clear stages: the slow loss, rapid loss, and balance stage. A water content of 60% appeared to be an irreversible turning point for initiation of senescence. Using normalized growth period as a measure, each of the tested cultivars could be assigned into one of two types based on their water dynamics: stay-water or general type. General-type cultivars had a shorter duration with a high water content and a water loss rate approximately twice as high as that of the stay-water type. This may have been related to the leaf senescence characteristics. However, the stay-water trait did not interfere with water dynamics of the ear components. Therefore, it may not be robust to evaluate the kernel dehydration of maize according to leaf senescence conditions due to the weak correlation between kernel water content and leaf senescence characteristics.

A comparative study on shared-use medicines in Tibetan and Chinese medicine.

BACKGROUND: Tibetan medicine (TM) and traditional Chinese medicine (TCM) are two independent traditional medical systems. Due to geographical factors, the development of Tibetan medicinal theory is relatively independent, but there are still many shared-use medicines in TM and TCM. However, a thorough and comparative study on those medicines is still absent. This study listed shared-use medicines by TM and TCM and analyzed the similarities and dissimilarities of these two medical systems. This paper also aimed to understand mutual influences like the shared history of TM and TCM and to roughly outline the exchanging process between them. METHODS: Shared-use medicines in TM and TCM were listed alphabetically. Information on the scientific name, material name, medicinal parts, and medical efficacy were extracted from publications. Shared-use medicines were grouped according to medicinal properties and medicinal parts used by TM and TCM. The historical origin and current status of clinical prescriptions of shared-use medicines were analyzed. RESULTS: A total of 136 shared-use medicines in TM and TCM were listed. Shared-use medicines that were used for a similar purpose in TM and TCM accounted for 14% of the total, while those used for different purposes accounted for 49% of the total, with some of the latter being commonly used in TCM. Shared-use medicinal herbs that originated from both Tibetan and Han regions accounted for 49% of the total, and those that were imported from South Asia and Southeast Asia were frequently observed in TM. CONCLUSION: Owing to its unique geographical location and cultural diversity, the Tibetan region played a role as a development cradle for various traditional medicinal theories and knowledge. Medicinal knowledge was exchanged between TM and TCM during their parallel independent growth. Shared-use medicines in TM and TCM were mostly determined by flora similarity and medicinal trade, and they marked significant differences in their medicinal properties. However, medicines that were used for similar purposes in TM and TCM presented obvious commercial medicinal characteristic as well as the same chemical profile. The Tibetan region not only provided medicinal usage knowledge of TCM, but also served as a supply of medicinal resources attributing to "high altitude" locations.

Estimation of wheat agronomic parameters using new spectral indices.

Crop agronomic parameters (leaf area index (LAI), nitrogen (N) uptake, total chlorophyll (Chl) content ) are very important for the prediction of crop growth. The objective of this experiment was to investigate whether the wheat LAI, N uptake, and total Chl content could be accurately predicted using spectral indices collected at different stages of wheat growth. Firstly, the product of the optimized soil-adjusted vegetation index and wheat biomass dry weight (OSAVI×BDW) were used to estimate LAI, N uptake, and total Chl content; secondly, BDW was replaced by spectral indices to establish new spectral indices (OSAVI×OSAVI, OSAVI×SIPI, OSAVI×CIred edge, OSAVI×CIgreen mode and OSAVI×EVI2); finally, we used the new spectral indices for estimating LAI, N uptake, and total Chl content. The results showed that the new spectral indices could be used to accurately estimate LAI, N uptake, and total Chl content. The highest R(2) and the lowest RMSEs were 0.711 and 0.78 (OSAVI×EVI2), 0.785 and 3.98 g/m(2) (OSAVI×CIred edge) and 0.846 and 0.65 g/m(2) (OSAVI×CIred edge) for LAI, nitrogen uptake and total Chl content, respectively. The new spectral indices performed better than the OSAVI alone, and the problems of a lack of sensitivity at earlier growth stages and saturation at later growth stages, which are typically associated with the OSAVI, were improved. The overall results indicated that this new spectral indices provided the best approximation for the estimation of agronomic indices for all growth stages of wheat.

[Estimated nitrogen nutrition index based on the hyperspectral for wheat of drip irrigation under mulch].

The accurate wheat management needs a reasonable nitrogen application, and it is one of the key measures for real-time and quantitatively monitoring of nitrogen status to gain the higher yield of wheat. In the present study, two field experiments were conducted with different nitrogen stress and wheat cultivars, the relationship was analyzed between spectral parameters and the partial factor productivity from applied N (PFPn), and the estimating model was established for PFP, in the growth stages of wheat. The result indicated that there was a highly significant correlation between the PFP, and GreenNDVI at jointing, the correlation coefficient (r) was 0.6404, the estimating model of PFPn was established, and the root mean square errors (RMSE) was 0.4597. The result indicated that the PFPn can be effectively estimated by using spectral parameters.

[Monitoring models of the plant nitrogen content based on cotton canopy hyperspectral reflectance].

Cotton production for accurate non-destructive, rapid monitoring of plant nitrogen content there is an urgent demand. Canopy spectral characteristics of the cotton plant and its quantitative relationship between nitrogen content, can achieve non-destructive monitoring of cotton nitrogen. Two consecutive years by different nitrogen test, cotton canopy hyperspectral data collection and simultaneous determination of canopy nitrogen content, analysis of different fertilizer treatments of cotton canopy spectral characteristics and the relationship between nitrogen content of cotton, the results show that: nitrogen content of cotton plant in different periods and spectral reflectance in the visible band (400-700 nm) was negatively related to the near-infrared 700-1300 nm band was a significant positive correlation, and in the short-wave infrared 1300-1800 nm band correlation is more complicated. Canopy scale, the whole growth stage of cotton, the visible band are sensitive to nitrogen content in cotton band, and near-infrared only is the cotton boll nitrogen content of the sensitive band; short-wave infrared band only in the budding period Cotton nitrogen sensitive band. Using nitrogen-sensitive bands in different periods can be constructed Cotton Cotton Nitrogen monitoring indicators.

[Study on hyperspectral estimation of pigment contents in leaves of cotton under disease stress].

The spectrum reflectance and pigment contents of cotton leaves infected with Verticillium wilt were measured in cotton disease nursery and field in different growth phases, and severity level of Verticillium wilt was investigated. The correlation between pigment contents of cotton leaves with Verticillium wilt and spectra reflectance, the first derivative of reflectance and spectral characteristic parameters were analyzed respectively. The estimation models about leaves pigment contents of disease cotton were established and tested. The results indicated that the correlations were best significant between chlorophyll a, b and a+b contents of leaves and spectral reflectance in visible wave bands, the first derivative spectrum at the wavelength regions of blue edge, yellow edge and red edge, and all spectral characteristic parameters (excluding red edge swing Dr). The models of transformed chlorophyll absorption in reflectance index (TCAR) and the new model of normalized difference vegetation index (NDVI [702,758]) had best estimated precision, and the relative errors were in average within 1.3%. Given that the model of NDVI [702,758] is very simple and practical, it was commended as a best model to estimate chlorophyll a, b and a+b contents of disease cotton. This study shows that leaves hyperspectra data can be used to estimate the pigment contents of cotton leaves quantitatively. This conclusion has also great practice and application value for monitoring the growth state and disease influence evaluation on cotton by using hyperspectral remote sensing.

[Monitoring canopy nitrogen status in winter wheat of growth anaphase with hyperspectral remote sensing].

Biomass, leaf area index (LAI) and nitrogen status are important parameters for indicating crop growth potential and photosynthetic productivity in wheat. Nondestructive, quick assessment of leaf dry weight, LAI and nitrogen content is necessary for nitrogen nutrition diagnosis and cultural regulation in wheat production. In order to establish the monitoring model of nitrogen richness in winter wheat of growth anaphase, studying the relationship between the nitrogen richness (NR) containing nitrogen density, LAI and leaf dry weight and the difference of hyperspectral reflectance rates (deltaR), we conducted a comparable experiment with five winter wheat varieties under nitrogen application level of 0, 100, 200 and 400 kg x N x ha(-1). The results indicated the NRs of the different varieties of winter wheat leaves increased with increasing growth stage while in the different nitrogen levels it was sequenced as: NO>N3>N1>N2. Twelve vegetation indices were compared with corresponding NR. The NR had significantly negative correlation to TCARI and VD672 in those vegetation indices, and their correlations (r) arrived at 0.870 and 0.855, respectively. The coefficients of determination (R2) of two models were 0.757 and 0.731 by erecting model with the two indexes and NR Root mean square error (RMSE), relative error (RE) and determination coefficient between measured and estimated NR were employed to test the model reliability and predicting accuracy. Accuracy rates of the models based on TCARI and VD672 achieved 84.56% and 80.13%. The overall results suggested that leaf nitrogen status of growth anaphase in winter wheat has stable relationships with some vegetation indexes, especially index of TCARI and VD672.

[Study on spectrum characteristics of cotton leaf and its estimating with remote sensing under aphid stress].

The spectrum and physical-chemical parameters were measured on cotton leaves infected by aphid with different severity levels (SL) at main cotton growth periods. Meanwhile, the reflectance and physical-chemical parameters of cotton leaves infected by aphid were analyzed and compared in different cotton growth periods and varieties. The sensitivity wave bands of cotton leaves infected by aphid were confirmed, and the estimating models of leaves infected by aphid were established. The results showed that there was a significant difference in the spectrum and physical-chemical parameters of cotton leaves infected by aphid. The thickness, water and Chl. b increased, while Chla, Chl. a+b and Cars content decreased in leaves infected by aphid. Besides, in visible region, the reflectance of cotton leaves infected by aphid has shown going up first and then down in different cotton growth periods and varieties with increasing of SL. However, in NIR region, it has shown discrepancy in varieties. The 434-727 and 648 nm can be used as sensitive and optimal aphid-band for cotton leaves. Estimation models for leaves infected by aphid were all in significant correlation. Among all the models, the model of (R1 589-R648)/ (R1 589+R648) had the best estimation precision, RE was the smallest (0.128), and it was commended as best models to estimate SL of leaves infected by aphid. The study provides an experimental reference for monitoring spectrum of cotton infected by aphid with remote sensing in large areas.

[Hyperspectral inversion models on verticillium wilt severity of cotton leaf].

The correlation of cotton leaf verticillium wilt severity level with raw hyperspectral reflectance, first derivative hyperspectral reflectance, and hyperspectral characteristic parameters was analyzed. Using linear and nonlinear regression methods, the hyperspectral remote sensing retrieval models of verticillium wilt severity level with remote sensing parameters as independent variables were constructed and validated. The result showed that spectral reflectance increased significantly in visible and short infrared wave band with the increase in the severity level, and this is especially significant in visible band. The raw spectral reflectance has the maximum coefficient of determination at 694 nm (R2 = 0.461 6) with severity level and the logarithm model constructed with reflectance at this point is the better one as compared to linear model. By the precision evaluation of retrieval models, the linear model with the first derivative reflectance at 717 nm as independent variable was proved to be the best, with R2 = 0.488 9, RMSE = 0.257 1, and relative error = 12.74%, for the estimation of verticllium wilt severity level of cotton leaf. The results provide a good basis for further studying monitoring mechanism of cotton verticillium wilt by remote sensing data, and have an important application in acquiring cotton disease information using hyperspectral remote sensing.