Genomic selection of eight fruit traits in pear

Genomic selection (GS) has the potential to improve selection efficiency and shorten the breeding cycle in fruit tree breeding. In this study,we evaluated the effect of prediction methods, marker density and the training population (TP) size on pear GS for improving its performance and reducing cost. We evaluated GS under two scenarios:(1) five-fold cross-validation in an interspecific pear family;(2) independent validation. Based on the cross-validation scheme, the prediction accuracy (PA) of eight fruit traits varied between 0.33 (fruit core vertical diameter)and 0.65 (stone cell content). Except for single fruit weight, a slightly better prediction accuracy (PA) was observed for the five parametrical methods compared with the two non-parametrical methods. In our TP of 310 individuals, 2 000 single nucleotide polymorphism (SNP) markers were sufficient to make reasonably accurate predictions. PAs for different traits increased by 18.21%-46.98%when the TP size increased from 50to 100, but the increment was smaller (-4.13%-33.91%) when the TP size increased from 200 to 250. For independent validation, the PAs ranged from 0.11 to 0.45 using rrBLUP method. In summary, our results showed that the TP size and SNP numbers had a greater impact on the PA than prediction methods. Furthermore, relatedness among the training and validation sets, and the complexity of traits should be considered when designing a TP to predict the test panel.

Systematic Review on Critical Factors and Their Optimization for Solar Cell Performance Enhancement

Solar cells and other renewable energy sources are crucial in today's world where sustainability and environmental consciousness is at peak.Because of this,creating the optimal capacity is a fair aim for the operators of such technologies.The transformation of solar energy into either electricity by means of photovoltaics or into useable fuel by means of photo electrochemical cells remained a primary objective for research organizations and development sectors.In this piece,we will take a look back at the history of solar cells and examine their progression through the generations.The significant aspects which have an impact on the solar cells' performance are also discussed.This article provides a comprehensive and in-depth overview of the important aspects that affect the solar cells' performance,as well as a discussion of the application of bio-inspired optimization algorithms to improve the parameters of solar cells.Reviewing critical factors and their optimization for solar cell performance enhancement is crucial.It helps identify key performance factors,understand limitations,and challenges,and identify effective optimization strategies.By evaluating trade-offs and synergies,it guides future research and informs industrial applications,leading to more efficient and sustainable solar cell technologies.

Study of Thermally Induced Vibration of Non-Homogeneous Trapezoidal Plate with Parabolically Thickness Variation in Both Directions

The present analysis demonstrates the thermal effect on vibrations of a symmetric, non-homoge- neous trapezoidal plate with parabolically varying thickness in both directions. The variation in Young’s modulus and mass density is the main cause for the occurrence of non-homogeneity in plate’s material. In this consideration, density varies linearly in one direction. The governing differential equations have been derived by Rayleigh-Ritz method in order to attain fundamental frequencies. With C-S-C-S boundary condition, a two term deflection function has been considered. The effect of structural parameters such as taper constants, thermal gradient, aspect ratio and non-homogeneity constant has been investigated for first two modes of vibration. The obtained numerical results have been presented in tabular and graphical form.

Study of Temperature Behaviour on Thermally Induced Vibration of Non-Homogeneous Trapezoidal Plate with Bi-Linearly Varying Thickness

The main aim of the present work is to study the linear temperature behaviour of a non-homogeneous trapezoidal plate whose thickness varies linearly in both directions. The temperature behaviour considered linear along the length of the plate. Non-homogeneity in plate arises due to variation in density along the length of the plate. The two-term deflection function with clamped-simply supported-clamped-simply supported boundary condition is taken into consideration. The effect of structural parameters such as taper constants, thermal gradient, non-homogeneity constant and aspect ratio has been studied. Rayleigh-Ritz method is used to solve the governing differential equations and to obtain the fundamental frequencies for the first two modes of vibration. Results are presented in graphical form.

Accuracy and responses of genomic selection on key traits in apple breeding

The application of genomic selection in fruit tree crops is expected to enhance breeding eficiency by increasing prediction accuracy,increasing selection intensity and decreasing generation interval.The objectives of this study were to assess the accuracy of prediction and selection response in commercial apple breeding programmes for key traits.The training population comprised 977 individuals derived from 20 pedigreed fllsib families.Historic phenotypic data were available on 10 traits related to productivity and fruit external appearance and genotypic data for 7829 SNPs obtained with an llumina 20K SNP array.From these data,a genome-wide prediction model was built and subsequently used to calculate genomic breeding values of five application fllsib families.The application families had genotypes at 364 SNPs from a dedicated 512 SNP array,and these genotypic data were extended to the high-density level by imputation.These five families were phenotyped for 1 year and their phenotypes were compared to the predicted breeding values.Accuracy of genomic prediction across the 10 traits reached a maximum value of 0.5 and had a median value of 0.19.The accuracies were strongly affected by the phenotypic distribution and heritability of traits.In the largest family,significant selection response was observed for traits with high heritability and symmetric phenotypic distribution.Traits that showed non-significant response often had reduced and skewed phenotypic variation or low heritability.Among the five application families the accuracies were uncorrelated to the degree of relatedness to the training population.The results underline the potential of genomic prediction to accelerate breeding progress in outbred fruit tree crops that still need to overcome long generation intervals and extensive phenotyping costs.

Genotyping-by-sequencing of pear (Pyrus spp.) accessions unravels novel patterns of genetic diversity and selection footprints

Understanding of genetic diversity and marker-trait relationships in pears(Pyrus spp.)forms an important part of gene conservation and cultivar breeding.Accessions of Asian and European pear species,and interspecific hybrids were planted in a common garden experiment.Genotyping-by-sequencing(GBS)was used to genotype 214 accessions,which were also phenotyped for fruit quality traits.A combination of selection scans and association analyses were used to identify signatures of selection.Patterns of genetic diversity,population structure and introgression were also investigated.About 15000 high-quality SNP markers were identified from the GBS data,of which 25%and 11%harboured private alleles for European and Asian species,respectively.Bayesian clustering analysis suggested negligible gene flow,resulting in highly significant population differentiation(Fst=0.45)between Asian and European pears.Interspecific hybrids displayed an average of 55%and 45%introgression from their Asian and European ancestors,respectively.Phenotypic(firmness,acidity,shape and so on)variation between accessions was significantly associated with genetic differentiation.Allele frequencies at large-effect SNP loci were significantly different between genetic groups,suggesting footprints of directional selection.Selection scan analyses identified over 20 outlier SNP loci with substantial statistical support,likely to be subject to directional selection or closely linked to loci under selection.

Prediction of genetic value for sweet cherry fruit maturity among environments using a 6K SNP array

The timing of fruit maturity is an important trait in sweet cherry production and breeding.Phenotypic variation for phenology of fruit maturity in sweet cherry appears to be under strong genetic control,but that control might be complicated by phenotypic instability across environments.Although such genotype-by-environment interaction(G×E)is a common phenomenon in crop plants,knowledge about it is lacking for fruit maturity timing and other sweet cherry traits.In this study,1673 genome-wide SNP markers were used to estimate genomic relationships among 597 weakly pedigree-connected individuals evaluated over two seasons at three locations in Europe and one location in the USA,thus sampling eight‘environments’.The combined dataset enabled a single meta-analysis to investigate the environmental stability of genomic predictions.Linkage disequilibrium among marker loci declined rapidly with physical distance,and ordination of the relationship matrix suggested no strong structure among germplasm.The most parsimonious G×E model allowed heterogeneous genetic variance and pairwise covariances among environments.Narrow-sense genomic heritability was very high(0.60–0.83),as was accuracy of predicted breeding values(>0.62).Average correlation of additive effects among environments was high(0.96)and breeding values were highly correlated across locations.Results indicated that genomic models can be used in cherry to accurately predict date of fruit maturity for untested individuals in new environments.Limited G×E for this trait indicated that phenotypes of individuals will be stable across similar environments.Equivalent analyses for other sweet cherry traits,for which multiple years of data are commonly available among breeders and cultivar testers,would be informative for predicting performance of elite selections and cultivars in new environments.

Turbocharging introgression breeding of perennial fruit crops:a case study on apple

The allelic diversity of primitive germplasm of fruit crops provides a useful resource for introgressing novel genes to meet consumer preferences and environmental challenges.Pre-breeding facilitates the identification of novel genetic variation in the primitive germplasm and expedite its utilisation in cultivar breeding programmes.Several generations of pre-breeding could be required to minimise linkage drag from the donor parent and to maximise the genomic content of the recipient parent.In this study we investigated the potential of genomic selection(GS)as a tool for rapid background selection of parents for the successive generation.A diverse set of 274 accessions was genotyped using random-tag genotyping-by-sequencing,and phenotyped for eight fruit quality traits.The relationship between‘own phenotypes’of 274 accessions and their general combining ability(GCA)was also examined.Trait heritability influenced the strength of correspondence between own phenotype and the GCA.The average(across eight traits)accuracy of predicting own phenotype was 0.70,and the correlations between genomic-predicted own phenotype and GCA were similar to the observed correlations.Our results suggest that genome-assisted parental selection(GAPS)is a credible alternative to phenotypic parental selection,so could help reduce the generation interval to allow faster accumulation of favourable alleles from donor and recipient parents.

Apple whole genome sequences:recent advances and new prospects

In 2010,a major scientific milestone was achieved for tree fruit crops:publication of the first draft whole genome sequence(WGS)for apple(Malus domestica).This WGS,v1.0,was valuable as the initial reference for sequence information,fine mapping,gene discovery,variant discovery,and tool development.A new,high quality apple WGS,GDDH13 v1.1,was released in 2017 and now serves as the reference genome for apple.Over the past decade,these apple WGSs have had an enormous impact on our understanding of apple biological functioning,trait physiology and inheritance,leading to practical applications for improving this highly valued crop.Causal gene identities for phenotypes of fundamental and practical interest can today be discovered much more rapidly.Genome-wide polymorphisms at high genetic resolution are screened efficiently over hundreds to thousands of individuals with new insights into genetic relationships and pedigrees.High-density genetic maps are constructed efficiently and quantitative trait loci for valuable traits are readily associated with positional candidate genes and/or converted into diagnostic tests for breeders.We understand the species,geographical,and genomic origins of domesticated apple more precisely,as well as its relationship to wild relatives.The WGS has turbo-charged application of these classical research steps to crop improvement and drives innovative methods to achieve more durable,environmentally sound,productive,and consumer-desirable apple production.This review includes examples of basic and practical breakthroughs and challenges in using the apple WGSs.Recommendations for“what’s next”focus on necessary upgrades to the genome sequence data pool,as well as for use of the data,to reach new frontiers in genomics-based scientific understanding of apple.

Fine-mapping and validation of the genomic region underpinning pear red skin colour

Red skin colour is an important target trait in various pear breeding programmes.In this study,the genetic control of red skin colour was investigated in an interspecific population derived using the descendants of the red sport European pear cultivar‘Max Red Bartlett’(MRB)and the red-blushed Chinese pear cultivar‘Huobali’.Approximately 550 seedlings from nine families were phenotyped for red skin over-colour coverage(Ocolcov)and the intensity of red over-colour(Ocolint)on a 0–9 scale,and genotyped using genotyping-by-sequencing.Genome-wide association analyses were conducted using 7500 high-quality single nucleotide polymorphisms(SNPs).Genomic regions on linkage groups(LG)4 and 5 were found to be associated,and the best SNP(S578_25116)on LG4 accounted for~15%of phenotypic variation in Ocolcov and Ocolint.The association of S578_25116 with Ocolcov and Ocolint was successfully validated in a sample of~200 European and Asian pear accessions.The association with red skin at locus S578_25116 was not present in Asian pear accessions,suggesting its close proximity to the MRB’s Cardinal gene.Several putative candidate genes,including MYB transcription factors(PCP027962 and PCP027967),were identified in the quantitative trait locus region on LG4 and await functional validation.

Use of Isoproturon Imprinted Polymer Membranes as a Selective Recognition Platform in a Resistance Based Electrochemical Sensor

Methacrylic acid with isoproturon has been utilized to prepare molecularly imprinted polymeric (MIP) membrane on Whatman filter paper no. 5 for selective electrochemical estimation of isoproturon pesticide. MIP membrane was prepared by radical polymerization and characterized using Ultra Violet spectrophotometer, Fourier Transform Infra Red (FTIR) spectroscopy and Scanning Electron Microscopy (SEM). Contact angle study was used to determine the surface energy of the MIP membrane and electrical conductivity measurements were performed by applying a small-amplitude alternating voltage (20 mV) with frequencies varying from 20 Hz to 80 kHz generated by a low-frequency wave form generator. Different isoproturon concentrations in samples were tested and analyzed. Results indicate linear increase in membrane resistance with increasing isoproturon in 10-3 to 10-6 M range. The selectivity of the electrochemical sensor was confirmed by testing isoproturon in presence of the structurally related compounds monouran and diuran. Results reveal highly selective and sensitive sensor, which can be employed for regular estimation of isoproturon in fields.

A Hybrid Offline-Online Approach to Adaptive Downlink Resource Allocation Over LTE

Radio resource management mechanisms in current and future wireless networks is expected to face an enormous challenge due to the ever increasing demand for bandwidth and latency sensitive applications on mobile devices. This is because an optimal resource allocation scheme which attempts to multiplex the available bandwidth in order to maximize Quality of service(QoS), will pose an exponential computational burden at eNodeB. In order to minimize such computational overhead, this work proposes a hybrid offline-online resource allocation strategy which effectively allocates all the available resources among flows such that their QoS requirements are satisfied. The flows are firstly classified into priority buckets based on real-time criticality factors. During the offline phase, the scheduler attempts to maintain the system load within a pre-specified safe threshold value by selecting an appropriate number of buckets. This offline selection procedure makes use of supervisory control theory of discrete event systems to synthesize an offline scheduler. Next, we have devised an online resource allocation strategy which runs on top of the offline policy and attempts to minimize the impact of the inherent variability in wireless networks. Simulation results show that the proposed scheduling framework is able to provide satisfactory QoS to all end users in most practical scenarios.

农村母牛在受精和未受精发情期内血红蛋白与某些血清生化成分的含量

曾有人报道发情期间的血红蛋白和血清中某些生化成分,会影响母牛的受精状况及其繁殖行为。据推测各种生化成分的缺乏或过剩是与家畜受精状况有联系的。进行本研究是为了查明农村难归类的母牛,在受精和未受精的发情期内某些生化成分的含量。 材料和方法 将26头鉴定为发情的母羊供作试验,在发情中期—后期(发情12—20小时),用优质精液(50％活精子)人工授精。人工授精45天后,经直肠检查诊断妊娠,已妊娠母牛,归入受精发情期组,其余归入未受精发情期组。

Are environment-related technologies key to unlock the path towards sustainable development:An econometric analysis

The objective of this study is to investigate the correlation between energy intensity and environmentrelated technology in industrialized countries.By utilizing panel data from 23 countries over a span of 32 years(1990-2021),this research aims to contribute to the comprehension of the role of green innovation in sustainable development.The study employs the Stochastic Impacts by Regression on Population,Affluence,and Technology model while controlling for variables including population growth,gross domestic product in purchasing power parity,Information and Communication Technology capital deepening,renewable energy consumption,and green innovation represented by research and development expenditure on environment-related technology.The results of the analysis,employing panel unit root tests,cross-sectional dependence tests,and a Method of Moments quantile regression,reveal that green innovation has a positive influence on diminishing energy intensity,with a more substantial impact at higher quantiles.Moreover,ICT capital deepening is determined to have a positive and noteworthy effect on reducing energy intensity.The findings of this study offer valuable insights for policymakers in their endeavours to accomplish sustainable development goals.

Extreme-phenotype GWAS unravels a complex nexus between apple(Malus domestica)red-flesh colour and internal flesh browning

The genetic link between apple red flesh(RF)coloration and the internal flesh browning disorder(FBD)is a major challenge when breeding high fruit quality RF apple cultivars.A genome-wide association study(GWAS)was conducted in a population of about 900 red-leaved seedlings to identify genomic regions and putative candidate genes using whole genome sequencing of the pools of extreme phenotypes(XP)for the RF colour coverage(using the weighted cortex index(WCI))and FBD.This study identified novel genomic regions contributing to WCI and FBD variation in the red-leaved seedlings.The FBD-associated regions were enriched for genes regulating senescence,heat shock proteins,cytochrome P450,ascorbate metabolism and pectin methyl esterases.Although there were no significant regions in common for WCI and FBD,there were several genes(e.g.MYB85,MYB66,ethylene insensitive 3,DNAJ heat shock protein,WRKY7,and NAC42)enriched commonly between the genomic regions associated with these traits,potentially underpinning the genetic connection between WCI and FBD.Some of the differentially expressed genes between the R6:MdMYB10 and white-fleshed‘control’apples resided within the GWAS hotspot for WCI(e.g.chalcone synthase,UDP-Glycosyl transferase)and FBD(e.g.Rho GTPase activating protein,lipoxygenase 1,phytoene synthase)–validating the XP-GWAS findings.Paralogs of several genes resided in the trait-associated genomic regions,suggesting that whole genome duplication plays an important role in the regulation of these traits.Adverse genetic correlations between WCI and sensory traits were observed,and strategies to develop FBD-free high fruit quality RF cultivars are discussed.

Predicting morbidity and mortality in acute pancreatitis in an Indian population:a comparative study of the BISAP score,Ranson’s score and CT severity index

Objective:Our aim was to prospectively evaluate the accuracy of the bedside index for severity in acute pancreatitis(BISAP)score in predicting mortality,as well as intermediate markers of severity,in a tertiary care centre in east central India,which caters mostly for an economically underprivileged population.Methods:A total of 119 consecutive cases with acute pancreatitis were admitted to our institution between November 2012 and October 2014.BISAP scores were calculated for all cases,within 24 hours of presentation.Ranson’s score and computed tomography severity index(CTSI)were also established.The respective abilities of the three scoring systems to predict mortality was evaluated using trend and discrimination analysis.The optimal cut-off score for mortality from the receiver operating characteristics(ROC)curve was used to evaluate the development of persistent organ failure and pancreatic necrosis(PNec).Results:Of the 119 cases,42(35.2%)developed organ failure and were classified as severe acute pancreatitis(SAP),47(39.5%)developed PNec,and 12(10.1%)died.The area under the curve(AUC)results for BISAP score in predicting SAP,PNec,and mortality were 0.962,0.934 and 0.846,respectively.Ranson’s score showed a slightly lower accuracy for predicting SAP(AUC 0.956)and mortality(AUC 0.841).CTSI was the most accurate in predicting PNec,with an AUC of 0.958.The sensitivity and specificity of BISAP score,with a cut-off of≥3 in predicting mortality,were 100%and 69.2%,respectively.Conclusions:The BISAP score represents a simple way of identifying,within 24 hours of presentation,patients at greater risk of dying and the development of intermediate markers of severity.This risk stratification method can be utilized to improve clinical care and facilitate enrolment in clinical trials.

Comparative study of multiple cancellous screws versus sliding hip screws in femoral neck fractures of young adults

Purpose： Both cannulated cancellous screw （CCS） and sliding hip screw （SHS） are used in femoral neck fracture fixations, hut which is superior is yet to be determined. This study was aimed to compare the clinicoradiological outcome of femoral neck fracture treated with SHS or CCS in young adults. Methods： Adults （16-60 years） with femoral neck fracture were divided into Group I fixed with SHS and Group 2 fixed with three CCS after closed reduction. Pain relief, functional recovery and postoperative radiographs at 6 weeks, 3 months, 6 months and then yearly for upto 4 years were analyzed. Results： Group 1 （n = 40） achieved radiological union at mean of Z6 months, with the union rate of 8Z5% （n = 35）, avascular necrosis （AVN） rate of 7.5% （n - 3） and mean Harris Hip Score （HHS） of 86.15 at the end of 4 years. In Group 2 （n = 45） these parameters were union at Z1 months, union rate of 82.22% （n = 37）, AVN rate of 6.67% （n = 3） and HHS of 88.65. Comparative results were statistically insignificant. Conclusion： There is no significant difference in clinicoradiological outcome between the two implants.

A novel method to investigate voltage stability of IEEE-14 bus wind integrated system using PSAT

The maximum demand of power utilization is increasing exponentially from base load to peak load in day to day life.This power demand may be either industrial usage or household applications.To meet this high maximum power demand by the consumer,one of the options is the integration of renewable energy resources with conventional power generation methods.In the present scenario,wind energy system is one of the methods to generate power in connection with the conventional power systems.When the load on the conventional grid system increases,various bus voltages of the system tend to decrease,causing serious voltage drop or voltage instability within the system.In view of this,identification of weak buses within the system has become necessary.This paper presents the line indices method to identify these weak buses,so that some corrective action may be taken to compensate for this drop in voltage.An attempt has been made to compensate these drops in voltages by integration of renewable energy systems.The wind energy system at one of the bus in the test system is integrated and the performance of the system is verified by calculating the power flow(PF)using the power system analysis tool box(PSAT)and line indices of the integrated test system.The PF and load flow results are used to calculate line indices for the IEEE-14 bus test system which is simulated on PSAT.

A GIS-based methodology for safe site selection of a building in a hilly region

Worker safety during construction is widety accepted, but the selection of safe sites for a building is generally not considered. Safe site selection （SSS） largely depends upon compiling, analyzing , and refining the information of an area where a building is tikety to be tocated. The locationat and topographical aspects of an area located in hilly regions pray a major rote in SSS, but are generally neglected in traditional and CAD-based systems used for site setection. Architects and engineers select a site based on their judgment, knowledge, and experience, but issues related to site safety are generally ignored. This study reviewed the existing literature on site selection techniques, building codes, and approaches of existing standards to identify various aspects cruciat for SSS in hilly regions. A questionnaire survey was conducted to identify various aspects that construction professionats consider critical for SSS. This study exptored the apptication of geographic information systems （GIS） in modeting the locational and topographical aspects to identify areas of suitabitity. A GIS-based methodotogy for locating a safe site that satisfies various spatial safety aspects was devetoped.

Fuzzy–frequency ratio model for avalanche susceptibility mapping

Avalanche activities in the Indian Himalaya cause the majority of fatalities and responsible for heavy damage to the property.Avalanche susceptibility maps assist decision-makers and planners to execute suitable measures to reduce the avalanche risk.In the present study,a probabilistic data-driven geospatial fuzzy–frequency ratio(fuzzy–FR)model is proposed and developed for avalanche susceptibility mapping,especially for the large undocumented region.The fuzzy–FR model for avalanche susceptibility mapping is initially developed and applied for Lahaul-Spiti region.The fuzzy–FR model utilized the six avalanche occurrence factors(i.e.slope,aspect,curvature,elevation,terrain roughness and vegetation cover)and one referent avalanche inventory map to generate the avalanche susceptibility map.Amongst 292 documented avalanche locations from the avalanche inventory map,233(80%)were used for training the model and remaining 59(20%)were used for validation of the map.The avalanche susceptibility map is validated by calculating the area under the receiver operating characteristic curve(ROC-AUC)technique.For validation of the results using ROC-AUC technique,the success rate and prediction rate were calculated.The values of success rate and prediction rate were 94.07%and 91.76%,respectively.The validation of results using ROC-AUC indicated the fuzzy–FR model is appropriate for avalanche susceptibility mapping.