Differential response of root morphology to potassium deficient stress among rice genotypes varying in potassium efficiency

Disparity in the root morphology of six rice(Oryza sativa L.) genotypes varying in potassium(K) efficiency was studied with three K levels:5 mg/L(low),10 mg/L(moderate) and 40 mg/L(adequate) in hydroponic culture. Morphological parameters included root length,surface area,volume and count of lateral roots,as well as fine(diameter<0.2 mm) and thick(diameter>0.2 mm) roots. The results indicate that the root growth of all genotypes was reduced under low K,but moderate K deficiency increased the root length of the efficient genotypes. At deficient and moderate K levels,all the efficient rice genotypes developed more fine roots(diameter<0.2 mm) than the inefficient ones. Both fine root count and root surface area were found to be the best parameters to portray K stress in rice. In accordance with the root morphology,higher K concentrations were noted in shoots of the efficient genotypes when grown at moderate and deficient K levels,indicating that root morphology parameters are involved in root uptake for K and in the translocation of K up to shoots. K deficiency affected not only the root morphology,but also the root ultra-structure. The roots of high-efficient genotypes had stronger tolerance to K deficient stress for root membrane damage,and could maintain the developed root architecture to adapt to the low K growth medium.

Prediction of Anoxic Sulfide Biooxidation Under Various HRTs Using Artificial Neural Networks

Objective During present investigation the data of a laboratory-scale anoxic sulfide oxidizing （ASO） reactor were used in a neural network system to predict its performance. Methods Five uncorrelated components of the influent wastewater were used as the artificial neural network model input to predict the output of the effluent using back-propagation and general regression algorithms. The best prediction performance is achieved when the data are preprocessed using principal components analysis （PCA） before they are fed to a back propagated neural network. Results Within the range of experimental conditions tested, it was concluded that the ANN model gave predictable results for nitrite removal from wastewater through ASO process. The model did not predict the formation of sulfate to an acceptable manner. Conclusion Apart from experimentation, ANN model can help to simulate the results of such experiments in finding the best optimal choice for ASO based denitrification. Together with wastewater collection and the use of improved treatment systems and new technologies, better control of wastewater treatment plant （WTP） can lead to more effective maneuvers by its operators and, as a consequence, better effluent quality.

Reimagining safe lithium applications in the living environment and its impacts on human,animal,and plant system

Lithium's(Li)ubiquitous distribution in the environment is a rising concern due to its rapid proliferation in the modern electronic industry.Li enigmatic entry into the terrestrial food chain raises many questions and uncertainties that may pose a grave threat to living biota.We examined the leverage existing published articles regarding advances in global Li resources,interplay with plants,and possible involvement with living organisms,especially humans and animals.Globally,Li concentration(<10 e300 mg kg
1)is detected in agricultural soil,and their pollutant levels vary with space and time.High mobility of Li results in higher accumulation in plants,but the clear mechanisms and specific functions remain unknown.Our assessment reveals the causal relationship between Li level and biota health.For example,lower Li intake(<0.6 mM in serum)leads to mental disorders,while higher intake(>1.5 mM in serum)induces thyroid,stomach,kidney,and reproductive system dysfunctions in humans and animals.However,there is a serious knowledge gap regarding Li regulatory standards in environmental compartments,and mechanistic approaches to unveil its consequences are needed.Furthermore,aggressive efforts are required to define optimum levels of Li for the normal functioning of animals,plants,and humans.This review is designed to revitalize the current status of Li research and identify the key knowledge gaps to fight back against the mountainous challenges of Li during the recent digital revolution.Additionally,we propose pathways to overcome Li problems and develop a strategy for effective,safe,and acceptable applications.

Whole-Genome Resequencing of a Worldwide Collection of Rapeseed Accessions Reveals the Genetic Basis of Ecotype Divergence

Rapeseed (Brassica napus),an important oilseed crop,has adapted to diverse climate zones and latitudes by forming three main ecotype groups,namely winter,semiwinter,and spring types. However,genetic variations underlying the divergence of these ecotypes are largely unknown. Here,we report the global pattern of genetic polymorphisms in rapeseed determined by resequencing a worldwide collection of 991 germplasm accessions.A total of 5.56 and 5.53 million singlenucleotide polymorphisms (SNPs)as Well as 1.86 and 1.92 million InDels were identified by mapping reads to the reference genomes of "Darmor-bzh"and "Tapidor,"respectively.We generated a map of allelic drift paths that shows splits and mixtures of the main populations,and revealed an asymmetric evolution of the two subgenomes of B.napus by calculating the genetic diversity and linkage disequilibrium parameters.Selective-sweep analysis revealed genetic changes in genes orthologous to those regulating various aspects of plant development and response to stresses.A genome-wide association study identified SNPs in the promoter regions of FLOWERING LOCUS T and FLOWERING LOCUS C orthologs that corresponded to the different rapeseed ecotype groups. Our study provides important insights into the genomic footprints of rapeseed evolution and flowering-time divergence among three ecotype groups,and will facilitate screening of molecular markers for accelerating rapeseed breeding.

Effects of previous drying of sediment on root functional traits and rhizoperformance of emerged macrophytes

Purpose of the current study was to investigate the effects of constantly wet and dried-rewetted sediments on root functional traits of emerged macrophytes and their nutrients removal abilities.It is based on the hypothesis that root characteristics and nutrients removal abilities of plants will be altered in the course of sediment desiccation.Four emerged macrophytes including two fibrous-root plants(Canna indica and Acorus calamus)and two thick-root plants(Alocasia cucullata and Aglaonema commutatum)were investigated for their root functional traits and rhizoperformance in both wet and dried-rewetted sediments.Results showed that sediment desiccation followed by rewetting substantially altered the root functional traits(root surface area,radial oxygen loss,and root activity)of plants due to adverse changes in morphological characteristics(porosity,bulk density,particle density)of dried-rewetted sediments than by wet sediments.Consequently,limited plants growth and removal of nitrogen(N),phosphorus(P)and dissolved organic carbon(DOC)were recorded in driedrewetted sediments and their pore water than in wet sediments.Radial oxygen loss from plant roots correlated positively with root functional traits,plants growth,and removal of N,P and DOC from pore water and sediment in both sediment types.Among the macrophyte species,the fibrous-root plants having advantages root functional traits,greatly influenced the rhizospheric conditions(pH,dissolved oxygen and redox potential),and demonstrated higher N,P and DOC reduction from both sediment types.While,the thick-rooted plants with thick diameter roots(D>1 mm)and higher rhizome exhibited longer life-span in both sediment types.