Light deficiency is a growing abiotic stress in rice production. However, few studies focus on shading effects on grain yield and quality of rice in East China. It is also essential to investigate proper nitrogen (N) application strategies that can effectively alleviate the negative impacts of light deficiency on grain yield and quality in rice. A two-year field experiment was conducted to explore the effects of shading (non-shading and shading from heading to maturity) and panicle N application (N_DP, decreased panicle N rate; N_MP, medium panicle N rate; N_IP, increased panicle N rate) treatments on rice yield- and quality-related characteristics. Compared with non-shading, shading resulted in a 9.5–14.8% yield loss (P<0.05), mainly due to lower filled-grain percentage and grain weight. N_MP and N_IP had higher (P<0.05) grain yield than N_DP under non-shading, and no significant difference was observed in rice grain yield among N_DP, N_MP, and N_IP under shading. Compared with N_MP and N_IP, N_DP achieved less yield loss under shading because of the increased filled-grain percentage and grain weight. Shading reduced leaf photosynthetic rate after heading, as well as shoot biomass weight at maturity, shoot biomass accumulation from heading to maturity, and nonstructural carbohydrate (NSC) content in the stem at maturity (P<0.05). The harvest index and NSC remobilization reserve of N_DP were increased under shading. Shading decreased (P<0.05) percentages of brown rice, milled rice, head rice, and amylose content while increasing (P<0.05) chalky rice percentage, chalky area, chalky degree, and grain protein. N_MP demonstrated a better milling quality under non-shading, while N_DP demonstrated under shading. N_DP exhibited both lower chalky rice percentage, chalky area, and chalky degree under non-shading and shading, compared with N_MP and N_IP. N_DP under shading decreased amylose content and breakdown but increased grain protein content and setback, contributing to similar overall palatability to nonshading. Our results suggested severe grain yield and quality penalty of rice when subjected to shading after heading. N_DP improved NSC remobilization, harvest index, and sink-filling efficiency and alleviated yield loss under shading. Besides, N_DP would maintain rice’s milling, appearance, and cooking and eating qualities under shading. Proper N management with a decreased panicle N rate could be adopted to mitigate the negative effects of shading on rice grain yield and quality.

One of the most important objectives for breeders is to develop high-yield cultivars.  The increase in crop yield has met with bottlenecks after the first green revolution, and more recent efforts have been focusing on achieving high photosynthetic efficiency traits in order to enhance the yield.  Leaf shape is a significant agronomic trait of upland cotton that affects plant and canopy architecture, yield, and other production attributes.  The major leaf shape types, including normal, sub-okra, okra, and super-okra, with varying levels of lobe severity, are controlled by a multiple allelic series of the D-genome locus L-D₁.  To analyze the effects of L-D₁ alleles on leaf morphology, photosynthetic related traits and yield of cotton, two sets of near isogenic lines (NILs) with different alleles were constructed in Lumianyan 22 (LMY22) and Lumianyan 28 (LMY28) backgrounds.  The analysis of morphological parameters and the results of virus-induced gene silencing (VIGS) showed that the regulation of leaf shape by L-D₁ alleles was similar to a gene-dosage effect.  Compared with the normal leaf, deeper lobes of the sub-okra leaf improved plant canopy structure by decreasing the leaf area index (LAI) and increasing the light transmittance rate (LTR), and the mid-range LAI of sub-okra leaf also guaranteed the accumulation of cotton biomass.  Although the chlorophyll content (SPAD) of sub-okra leaf was lower than those of the other two leaf shapes, the net photosynthetic rate (P_n) of sub-okra leaf was higher than those of okra leaf and normal leaf at most stages.  Thus, the improvements in canopy structure, as well as photosynthetic and physiological characteristics, contributed to optimizing the light environment, thereby increasing the total biomass and yield in the lines with a sub-okra leaf shape.  Our results suggest that the sub-okra leaf may have practical application in cultivating varieties, and could enhance sustainable and profitable cotton production.

Organic acids are one of the most important factors influencing fruit flavors. The predominant organic acid in most pear cultivars is malic acid, but the mechanism controlling its accumulation remains unclear. In this study, by comparing gene expression levels and organic acid content, we revealed that the expression of PbPH5, which encodes a P_3A-ATPase, is highly correlated with malic acid accumulation in different pear species, with correlation coefficients of 0.932^**, 0.656^*, 0.900^**, and 0.518^* (^*, P<0.05 or ^**, P<0.01) in Pyrus bretschneideri Rehd., P. communis Linn., P. pyrifolia Nakai., and P. ussuriensis Maxim., respectively. Moreover, the overexpression of PbPH5 in pear significantly increased the malic acid content. In contrast, silencing PbPH5 via RNA interference significantly decreased its transcript level and the pear fruit malic acid content. A subcellular localization analysis indicated that PbPH5 is located in the tonoplast. Additionally, a phylogenetic analysis proved that PbPH5 is a PH5 homolog gene that is clustered with Petunia hybrida, Malus domestica, and Citrus reticulata genes. Considered together, these findings suggest PbPH5 is a functionally conserved gene. Furthermore, the accumulation of malic acid in pear fruits is at least partly related to the changes in PbPH5 transcription levels.

Sensitivity analysis (SA) is an effective tool for studying crop models; it is an important link in model localization and plays an important role in crop model calibration and application.  The objectives were to (i) determine influential and non-influential parameters with respect to above ground biomass (AGB), canopy cover (CC), and grain yield of winter wheat in the Beijing area based on the AquaCrop model under different water treatments (rainfall, normal irrigation, and over-irrigation); and (ii) generate an AquaCrop model that can be used in the Beijing area by setting non-influential parameters to fixed values and adjusting influential parameters according to the SA results.  In this study, field experiments were conducted during the 2012–2013, 2013–2014, and 2014–2015 winter wheat growing seasons at the National Precision Agriculture Demonstration Research Base in Beijing, China.  The extended Fourier amplitude sensitivity test (EFAST) method was used to perform SA of the AquaCrop model using 42 crop parameters, in order to verify the SA results, data from the 2013–2014 growing season were used to calibrate the AquaCrop model, and data from 2012–2013 and 2014–2015 growing seasons were validated.  For AGB and yield of winter wheat, the total order sensitivity analysis had more sensitive parameters than the first order sensitivity analysis.  For the AGB time-series, parameter sensitivity was changed under different water treatments; in comparison with the non-stressful conditions (normal irrigation and over-irrigation), there were more sensitive parameters under water stress (rainfall), while root development parameters were more sensitive.  For CC with time-series and yield, there were more sensitive parameters under water stress than under no water stress.  Two parameters sets were selected to calibrate the AquaCrop model, one group of parameters were under water stress, and the others were under no water stress, there were two more sensitive parameters (growing degree-days (GDD) from sowing to the maximum rooting depth (root) and the maximum effective rooting depth (rtx)) under water stress than under no water stress.  The results showed that there was higher accuracy under water stress than under no water stress.  This study provides guidelines for AquaCrop model calibration and application in Beijing, China, as well providing guidance to simplify the AquaCrop model and improve its precision, especially when many parameters are used.  

Anthropogenic activities profoundly influence carbon sequestration in the Eurasian Steppe.  In particular, grazing has been identified as having a major effect on carbon sequestration.  However, the extent to which grazing affects regional patterns or carbon sequestration is unknown.  In this study, we evaluated the impact of regional grazing on grassland carbon sequestration using the Boreal Ecosystem Productivity Simulator (BEPS) and the Shiyomi grazing model.  Model performances were validated against the results from field measurements and eddy covariance (EC) sites.  Model outputs showed that in 2008, the regional net primary productivity (NPP) was 79.5 g C m^–2, and the net ecosystem productivity (NEP) was –6.5 g C m^–2, characterizing the region as a weak carbon source.  The Mongol Steppe (MS) was identified as a carbon sink, whereas the Kazakh Steppe (KS) was either carbon neutral or a weak carbon source.  The spatial patterns of grazing density are divergent between the MS and the KS.  In the MS, livestock was mainly distributed in China with relatively good management, while in the KS livestock was mainly concentrated in the southern countries (especially Uzbekistan and Turkmenistan) with harsh environments and poor management.  The consumption percentages of NPP in Turkmenistan, Tajikistan and Uzbekistan were 5.3, 3.3 and 1.2%, respectively, whereas the percentages in other countries were lower than 1%.  Correspondingly, grazing consumption contributed to the carbon sources of Turkmenistan, Tajikistan and Uzbekistan by 11.6, 6.3 and 4.3%, respectively, while it weakened the carbon sink in Inner Mongolia, China and Mongolia by 1.6 and 0.5%.  This regional pattern should be affected by different sub-regional characteristics, e.g., the continuous degradation of grassland in the southern part of the KS and the restoration of grassland in Inner Mongolia, China.

To optimize both grain yield and quality of low-glutelin rice cultivars under N-fertilizer strategies, two-year field experiments involving three low-glutelin rice cultivars (W1240, W1721, W025) and an ordinary rice cultivar (H9405) with five N treatments were carried out to determine the effects of N application rate and genotype on protein fractions contents and Glutelin/Prolamin ratio (Glu/Pro). The difference of protein fraction concentrations affected by N application rate existed in genotypes. Ordinary rice cultivar had a larger increase in glutlein concentration affected by N application rate than low-glutelin rice cultivars did. Glutelin in H9405 had a increase of 30.6 and 41.0% under the N4 treatment (360 kg N ha–1) when compared with N0 treatment (no fertilizer N) in 2010 and 2011 respectively, while all the low-glutelin rice cultivars showed relatively smaller increases for two years. Variance analysis showed no significant effect of N application rate on glutelin in W1240 and W025 while the effects on albumin, globulin and prolamin were significant in low-glutelin rice. What’s more, N treatment had no significant influence on Glu/Pro ratios in low-glutelin rice cultivars while a significant increase in Glu/Pro ratio was observed in ordinary rice cultivar. So low-gultelin rice cultivars showed a different pattern from ordinary rice cultivars when influenced by N application rate.

Our previous studies showed that the anti-inflammatory effects of Paeonia lactiflora roots extract may be mediated, at least in part, through its gallic acid content, and this effect may be regulated in part by an inhibition on cAMP-phosphodiesterase (PDE). To explore the anti-inflammatory effect and mechanism, the influence of gallic acid on neutrophils PDE4 activity and expression, TNF-α and IL-6 content and rat arthritis model were further studied. PDE4 activity and gene express were calculated respectively by substrate cAMP change examined with HPLC and real-time RT-PCR. The concentration of IL-6 and TNF-α in supernatant were assayed by ELISA method. Model of rat arthritis was caused by complete Freund’s adjuvant. Results showed that gallic acid had a dose-dependent restraint on PDE4 activity of neutrophils in vitro, promoted significantly PDE4A expression (P<0.01), and had no influence on the expressions of PDE4B and 4D. However, PDE4C expression was not detected. Gallic acid could promote IL-6 release (P<0.05), and inhibit TNF-α release of neutrophils (P<0.05). The experiment in vivo showed that gallic acid had obvious restraint on local inflammation of animal model (P<0.05). Therefore, the anti-inflammatory effect of gallic acid may be mediated in part through an inhibition on PDE4 activity and further an increase of IL-6 and a decrease of TNF-α of neutrophils, and this effect seemed to have no relationship with PDE4 expression.

Excessive nitrogen (N) fertilization in intensive agricultural areas such as the plain region of South China has resulted in low nitrogen use efficiency and serious environmental problems. To determine the optimum N application rate, grain yield, apparent nitrogen recovery efficiency (ANRE), apparent N loss, and ammonium (NH3) volatilization under different N application rates in the three years from 2012 to 2014 were studied. The results showed that the relationship between grain yields and N application rate in the three years were well fitted by quadratic equations. When N application rate reached 197 kg ha–1 in 2012, 199 kg ha–1 in 2013 and 196 kg ha–1 in 2014, the plateau of the grain yields appeared. With the increase of N application rate, the ANRE for rice decreased which could be expressed with sigmoidal equation; when N application rate was 305 kg ha–1 in 2012, 275 kg ha–1 in 2013 and 312 kg ha–1 in 2014, the curves of ANRE appeared turing points. Besides, the relationship between soil Nresidual and N application rate was fitted by the quadratic equation and the maximums of soil Nresidual were reached in the three years with the N application rate of 206, 244 and 170 kg ha–1, respectively. Statistical analysis indicated that NH3 volatilization and apparent N loss in three years all increased with the increasing N application rate. When the amount of NH3 volatilization increased to 11.6 kg N ha–1 in 2012, 40.5 kg N ha–1 in 2013 and 57.0 kg N ha–1 in 2014, the apparent N loss in the three years had obvious increase. To determine the optimum N application rate, the average N application on the plateau of the grain yield was considered as the lower limit while the average N application rate at the turning points of ANRE, the residual N in soil and apparent N loss was taken as the upper limit. According to the results in three years, the optimum N application rate for rice in Zhejiang was 197–255 kg ha–1.

The objective of the present study was to evaluate potential adverse effects of diacylglycerol microemulsion (DAGM) inrats/mice. Acute safety evaluation was carried out by giving intragastrically with 20 mL 25% DAG kg-1 body weight ofDAGM or water with two groups of mice. Chronic safety evaluation with 40 male and 40 female Sprague-Dawley rats wascarried out by setting a control group and 3 different dose groups (n=10 male+10 female) administered with DAGM with6.7, 10 and 20 mL kg-1 body weight per day. Relevant parameters of liver and kidney function and biochemistry weredetermined by standard methods at end point. Acute toxicity study revealed the maximum tolerated dose (MTD) ofDAGM was 20 mL kg-1 body weight in mice. No death was observed at the dose of 20 mL kg-1 body weight per day. Chronicsafety evaluation did not show significant changes on hematological, histopathologic, clinical, and biochemical testswhen administered at levels of 6.7, 10 and 20 mL kg-1 body weight per day to rats for 30 d. No significant body weightchanges were observed in different dosages in both male and female rats. Our results suggested that acute and chronicadverse effects were not observed in histology and clinical parameters in both mice and rats. The results suggested thatDAGM is safe at the experimental levels.