Northeast Agricultural University

About: Northeast Agricultural University is a education organization based out in Harbin, China. It is known for research contribution in the topics: Population & Oxidative stress. The organization has 14428 authors who have published 9850 publications receiving 126705 citations. The organization is also known as: Dōngběi Nóngyè Dàxué.

Crop Production under Drought and Heat Stress: Plant Responses and Management Options

Abstract: Abiotic stresses are one of the major constraints to crop production and food security worldwide. The situation has aggravated due to the drastic and rapid changes in global climate. Heat and drought stress are undoubtedly the two most important stresses having huge impact on growth and productivity of the crops. It is very important to understand the physiological, biochemical and ecological interventions related to these stresses for better management. A wide range of plant responses to these stresses could be generalized into morphological, physiological and biochemical responses. Interestingly, this review provides a detailed account of plant responses to heat and drought stresses with special focus on highlighting the commonalities and differences. Crop growth and yields are negatively affected by sub-optimal water supply and abnormal temperatures due to physical damages, physiological disruptions and biochemical changes. Both these stresses have multi-lateral impacts and therefore, complex in mechanistic action. A better understanding of plant responses to these stresses has pragmatic implication for remedies and management. A comprehensive account of conventional as well as modern approaches to deal with heat and drought stresses have also been presented here. A side-by-side critical discussion on salient responses and management strategies for these two important abiotic stresses provides a unique insight into the phenomena. A holistic approach taking into account the different management options to deal with heat and drought stress simultaneously could be a win-win approach in future.

Producing more grain with lower environmental costs

Abstract: In an experiment across China to test integrated soil–crop system management for rice, wheat and maize against current practice, improvements in grain yield are equivalent to high-input techniques, but nutrient use, nutrient loss and greenhouse gas emissions are lower than current practice. Integrated soil–crop system management is a technique that aims to maximize yield and minimize environmental impact by adapting cropping systems to local conditions through optimal nutrient application, seasonal timing and the use of the best crop varieties. Fusuo Zhang and colleagues report the results of a China-wide test of this technique for the three main cereal crops — rice, wheat and maize. In comparisons with current practice and high input techniques, the authors find that the integrated system achieves yield improvements equivalent to high input techniques but with lower nutrient use, nutrient loss and greenhouse gas emissions than those found with the current practice. Agriculture faces great challenges to ensure global food security by increasing yields while reducing environmental costs1,2. Here we address this challenge by conducting a total of 153 site-year field experiments covering the main agro-ecological areas for rice, wheat and maize production in China. A set of integrated soil–crop system management practices based on a modern understanding of crop ecophysiology and soil biogeochemistry increases average yields for rice, wheat and maize from 7.2 million grams per hectare (Mg ha−1), 7.2 Mg ha−1 and 10.5 Mg ha−1 to 8.5 Mg ha−1, 8.9 Mg ha−1 and 14.2 Mg ha−1, respectively, without any increase in nitrogen fertilizer. Model simulation and life-cycle assessment3 show that reactive nitrogen losses and greenhouse gas emissions are reduced substantially by integrated soil–crop system management. If farmers in China could achieve average grain yields equivalent to 80% of this treatment by 2030, over the same planting area as in 2012, total production of rice, wheat and maize in China would be more than enough to meet the demand for direct human consumption and a substantially increased demand for animal feed, while decreasing the environmental costs of intensive agriculture.

Chloroquine inhibits autophagic flux by decreasing autophagosome-lysosome fusion.

Abstract: Macroautophagy/autophagy is a conserved transport pathway where targeted structures are sequestered by phagophores, which mature into autophagosomes, and then delivered into lysosomes for degradati...

Quercetin, Inflammation and Immunity

Abstract: In vitro and some animal models have shown that quercetin, a polyphenol derived from plants, has a wide range of biological actions including anti-carcinogenic, anti-inflammatory and antiviral activities; as well as attenuating lipid peroxidation, platelet aggregation and capillary permeability. This review focuses on the physicochemical properties, dietary sources, absorption, bioavailability and metabolism of quercetin, especially main effects of quercetin on inflammation and immune function. According to the results obtained both in vitro and in vivo, good perspectives have been opened for quercetin. Nevertheless, further studies are needed to better characterize the mechanisms of action underlying the beneficial effects of quercetin on inflammation and immunity.

Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies

Abstract: False positives in a Genome-Wide Association Study (GWAS) can be effectively controlled by a fixed effect and random effect Mixed Linear Model (MLM) that incorporates population structure and kinship among individuals to adjust association tests on markers; however, the adjustment also compromises true positives. The modified MLM method, Multiple Loci Linear Mixed Model (MLMM), incorporates multiple markers simultaneously as covariates in a stepwise MLM to partially remove the confounding between testing markers and kinship. To completely eliminate the confounding, we divided MLMM into two parts: Fixed Effect Model (FEM) and a Random Effect Model (REM) and use them iteratively. FEM contains testing markers, one at a time, and multiple associated markers as covariates to control false positives. To avoid model over-fitting problem in FEM, the associated markers are estimated in REM by using them to define kinship. The P values of testing markers and the associated markers are unified at each iteration. We named the new method as Fixed and random model Circulating Probability Unification (FarmCPU). Both real and simulated data analyses demonstrated that FarmCPU improves statistical power compared to current methods. Additional benefits include an efficient computing time that is linear to both number of individuals and number of markers. Now, a dataset with half million individuals and half million markers can be analyzed within three days.