scholarly journals Perspectives for the Use of Quantitative Genetics in Breeding of Autogamous Plants

ISRN Genetics ◽  
2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Magno Antonio Patto Ramalho ◽  
Bruna Line Carvalho ◽  
José Airton Rodrigues Nunes
Keyword(s):  
Quantitative Genetics ◽  
Inbred Lines ◽  
Best Linear Unbiased Predictor ◽  
Breeding Values ◽  
Genetic Gains ◽  
Amount Of Information ◽  
Perennial Plant ◽  
Best Linear Unbiased ◽  
Selection Of ◽  
Better Than

With the increased demand for food, the use of methods and alternatives that increase efficiency in selection of inbred lines is necessary. The use of quantitative genetics plays an important role in this respect, especially when the pedigree method is used in autogamous plants. This study proposes the inclusion of relationship information among progenies using the best linear unbiased predictor (BLUP) to obtain the breeding values of greater accuracy and, consequently, increase genetic gains from the selection. A strategy is proposed that aims to accelerate the program of obtaining perennial plant inbreds and use the greatest amount of information possible in selection so as to attain maximum accuracy. In that way, it would be possible to make inbreds available which are better than the existing ones, with greater frequency, meeting the agribusiness demand involved in production of perennial plants.

scholarly journals PREDICTION OF PHENOTYPIC AND GENOTYPIC VALUES BY BLUP/GWS AND NEURAL NETWORKS

2018 ◽  
Vol 31 (3) ◽  
pp. 532-540 ◽  
Author(s):  
ALISSON ESDRAS COUTINHO ◽  
DIOGO GONÇALVES NEDER ◽  
MAIRYKON COÊLHO DA SILVA ◽  
ELIANE CRISTINA ARCELINO ◽  
SILVAN GOMES DE BRITO ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Breeding Cycle ◽  
Prediction Methods ◽  
Best Linear Unbiased Predictor ◽  
Entire Genome ◽  
Genomic Breeding ◽  
Breeding Values ◽  
Genome Wide ◽  
Best Linear Unbiased

ABSTRACT Genome-wide selection (GWS) uses simultaneously the effect of the thousands markers covering the entire genome to predict genomic breeding values for individuals under selection. The possible benefits of GWS are the reduction of the breeding cycle, increase in gains per unit of time, and decrease of costs. However, the success of the GWS is dependent on the choice of the method to predict the effects of markers. Thus, the objective of this work was to predict genomic breeding values (GEBV) through artificial neural networks (ANN), based on the estimation of the effect of the markers, compared to the Ridge Regression-Best Linear Unbiased Predictor/Genome Wide Selection (RR-BLUP/GWS). Simulations were performed by software R to provide correlations concerning ANN and RR-BLUP/GWS. The prediction methods were evaluated using correlations between phenotypic and genotypic values and predicted GEBV. The results showed the superiority of the ANN in predicting GEBV in simulations with higher and lower marker densities, with higher levels of linkage disequilibrium and heritability.

scholarly journals Biometrical analysis and selection of tetraploid progenies of Panicum maximum using mixed model methods

2004 ◽  
Vol 39 (4) ◽  
pp. 335-341 ◽  
Author(s):  
Rosangela Maria Simeão Resende ◽  
Liana Jank ◽  
Cacilda Borges do Valle ◽  
Ana Lídia Variani Bonato
Keyword(s):  
Mixed Model ◽  
Panicum Maximum ◽  
Hybrid Progeny ◽  
Linear Unbiased Prediction ◽  
Breeding Values ◽  
Green Matter ◽  
Sib Families ◽  
Best Linear Unbiased ◽  
Clonal Test ◽  
Selection Of

The objectives of this work were to estimate the genetic and phenotypic parameters and to predict the genetic and genotypic values of the selection candidates obtained from intraspecific crosses in Panicum maximum as well as the performance of the hybrid progeny of the existing and projected crosses. Seventy-nine intraspecific hybrids obtained from artificial crosses among five apomictic and three sexual autotetraploid individuals were evaluated in a clonal test with two replications and ten plants per plot. Green matter yield, total and leaf dry matter yields and leaf percentage were evaluated in five cuts per year during three years. Genetic parameters were estimated and breeding and genotypic values were predicted using the restricted maximum likelihood/best linear unbiased prediction procedure (REML/BLUP). The dominant genetic variance was estimated by adjusting the effect of full-sib families. Low magnitude individual narrow sense heritabilities (0.02-0.05), individual broad sense heritabilities (0.14-0.20) and repeatability measured on an individual basis (0.15-0.21) were obtained. Dominance effects for all evaluated characteristics indicated that breeding strategies that explore heterosis must be adopted. Less than 5% increase in the parameter repeatability was obtained for a three-year evaluation period and may be the criterion to determine the maximum number of years of evaluation to be adopted, without compromising gain per cycle of selection. The identification of hybrid candidates for future cultivars and of those that can be incorporated into the breeding program was based on the genotypic and breeding values, respectively. The prediction of the performance of the hybrid progeny, based on the breeding values of the progenitors, permitted the identification of the best crosses and indicated the best parents to use in crosses.

scholarly journals Inference of population effect and progeny selection via a multi-trait index in soybean breeding

2020 ◽  
Vol 43 ◽  
pp. e44623
Author(s):  
Leonardo Volpato ◽  
João Romero do Amaral Santos de Carvalho Rocha ◽  
Rodrigo Silva Alves ◽  
Willian Hytalo Ludke ◽  
Aluízio Borém ◽  
...  
Keyword(s):  
Statistical Model ◽  
Variance Components ◽  
Linear Unbiased Prediction ◽  
Soybean Breeding ◽  
Population Effect ◽  
Genetic Gains ◽  
Simultaneous Evaluation ◽  
Superior Genotypes ◽  
Best Linear Unbiased ◽  
Selection Of

The selection of superior genotypes of soybean entails a simultaneous evaluation of a number of favorable traits that provide a comparatively superior yield. Disregarding the population effect in the statistical model may compromise the estimate of variance components and the prediction of genetic values. The present study was undertaken to investigate the importance of including population effect in the statistical model and to determine the effectiveness of the index based on factor analysis and ideotype design via best linear unbiased prediction (FAI-BLUP) in the selection of erect, early, and high-yielding soybean progenies. To attain these objectives, 204 soybean progenies originating from three populations were examined for various traits of agronomic interest. The inclusion of the population effect in the statistical model was relevant in the genetic evaluation of soybean progenies. To quantify the effectiveness of the FAI-BLUP index, genetic gains were predicted and compared with those obtained by the Smith-Hazel and Additive Genetic indices. The FAI-BLUP index was effective in the selection of progenies with balanced, desirable genetic gains for all traits simultaneously. Therefore, the FAI-BLUP index is an adequate tool for the simultaneous selection of important traits in soybean breeding.

scholarly journals Estimating Breeding values for milk production and mastitis traits for Holstein cattle in Egypt

2019 ◽  
Vol 23 (4) ◽  
pp. 159
Author(s):  
Eslam Faid-Allah
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Holstein Cattle ◽  
Phenotypic Variance ◽  
Production Traits ◽  
Linear Unbiased Prediction ◽  
Breeding Values ◽  
Time Parity ◽  
Best Linear Unbiased ◽  
Selection Of

<p class="abstrak2">This study was carried out to evaluate the sires and dams genetically for milk production and mastitis traits in Egyptian 12 herds of Holstein cattle using Best Linear Unbiased Prediction via MTDFREML program. The data was obtained from a commercial farm called Dena, located in Cairo-Alex Desert Road (80 Km), Menofia, Egypt. Data included 4791 cows, 4227 dams and 248 sires that represented the period from 2007 to 2014. Estimating breeding values for milk production traits as cumulative milk yield at 90 days (90-DM), cumulative milk yield at 180 days (180-DM), cumulative milk yield at 270 days (270-DM), cumulative milk yield at 305 days (305-DM), and number of mastitis infection around the season of lactation (MAST). The averages of the 90-DM, 180-DM, 270-DM, 305-DM and MAST were 3026.3±655.1 kg, 5873.3±1081.1 kg, 7891.1±2692.2 kg, 9611.2±1897.9 kg, and 0.712±1.2 time/parity, respectively. Estimates of heritability for the previous traits were 0.11±0.016, 0.15±0.014, 0.18±0.012, 0.22±0.015, and 0.09±0.029, respectively; genetic variance were 47206.2 kg, 175300.6 kg, 1304654.4 kg, 792411.6 kg and 0.12 time/parity, respectively; and phenotypic variance were 429147.6 kg, 1168670.6 kg, 7248079.9 kg, 3601870.9 kg, and 1.35 time/parity, respectively. The EBV values as average, SD, (Min: Max) for sires were 0.0±0.179 (-0.4: 0.66) for MAST, 0.0±86.176 (-263.1: 245.4) for 90-DM, 0.0±227.523 (-600.3: 800.3) for 180-DM, 0.0±413.48 (-323.3: 1277.7) for 270-DM and 0.0±440.26 (-1280.9: 1565.1) for 305-DM. Also, The EBVs for dams were 0.0±0.055 (-0.14: 0.45) for MAST, 0.033±26.24 (-142.8: 103.0) for 90-DM, 0.074±76.81 (-360.2: 289.6) for 180-DM, -0.045±139.66 (-591.9: 529.2) for 270-DM and 0.266±154.1 (-666.3: 617.6) for 305-DM. These results provide that the selection of sires and dams will improve the traits of milk production and mastitis in this herd because of the wide differences in genetic potential among sires and dams.</p>

Implementasi Voip Server Berbasis IPV6 Dengan Raspberry PI

2019 ◽  
Vol 9 (01) ◽  
pp. 47-54
Author(s):  
Rabbai San Arif ◽  
Yuli Fitrisia ◽  
Agus Urip Ari Wibowo
Keyword(s):  
Internet Protocol ◽  
Wireless Transmission ◽  
Raspberry Pi ◽  
Test Results ◽  
Average Delay ◽  
Ipv6 Network ◽  
Ip Network ◽  
Selection Of ◽  
Better Than

Voice over Internet Protocol (VoIP) is a telecommunications technology that is able to pass the communication service in Internet Protocol networks so as to allow communicating between users in an IP network. However VoIP technology still has weakness in the Quality of Service (QoS). VOPI weaknesses is affected by the selection of the physical servers used. In this research, VoIP is configured on Linux operating system with Asterisk as VoIP application server and integrated on a Raspberry Pi by using wired and wireless network as the transmission medium. Because of depletion of IPv4 capacity that can be used on the network, it needs to be applied to VoIP system using the IPv6 network protocol with supports devices. The test results by using a wired transmission medium that has obtained are the average delay is 117.851 ms, jitter is 5.796 ms, packet loss is 0.38%, throughput is 962.861 kbps, 8.33% of CPU usage and 59.33% of memory usage. The analysis shows that the wired transmission media is better than the wireless transmission media and wireless-wired.

Evolution and Selection of Quantitative Traits

2018 ◽  
Author(s):  
Bruce Walsh ◽  
Michael Lynch
Keyword(s):  
Mathematical Models ◽  
Quantitative Genetics ◽  
Complex Traits ◽  
Evolutionary Biology ◽  
Quantitative Traits ◽  
Specific Gene ◽  
Real World Data ◽  
Holistic Treatment ◽  
Genetics And Genomics ◽  
Selection Of

Quantitative traits—be they morphological or physiological characters, aspects of behavior, or genome-level features such as the amount of RNA or protein expression for a specific gene—usually show considerable variation within and among populations. Quantitative genetics, also referred to as the genetics of complex traits, is the study of such characters and is based on mathematical models of evolution in which many genes influence the trait and in which non-genetic factors may also be important. Evolution and Selection of Quantitative Traits presents a holistic treatment of the subject, showing the interplay between theory and data with extensive discussions on statistical issues relating to the estimation of the biologically relevant parameters for these models. Quantitative genetics is viewed as the bridge between complex mathematical models of trait evolution and real-world data, and the authors have clearly framed their treatment as such. This is the second volume in a planned trilogy that summarizes the modern field of quantitative genetics, informed by empirical observations from wide-ranging fields (agriculture, evolution, ecology, and human biology) as well as population genetics, statistical theory, mathematical modeling, genetics, and genomics. Whilst volume 1 (1998) dealt with the genetics of such traits, the main focus of volume 2 is on their evolution, with a special emphasis on detecting selection (ranging from the use of genomic and historical data through to ecological field data) and examining its consequences. This extensive work of reference is suitable for graduate level students as well as professional researchers (both empiricists and theoreticians) in the fields of evolutionary biology, genetics, and genomics. It will also be of particular relevance and use to plant and animal breeders, human geneticists, and statisticians.

Effect of Contact Ratio on Spur Gear Dynamic Load With No Tooth Profile Modifications

1996 ◽  
Vol 118 (3) ◽  
pp. 439-443 ◽  
Author(s):  
Chuen-Huei Liou ◽  
Hsiang Hsi Lin ◽  
F. B. Oswald ◽  
D. P. Townsend
Keyword(s):  
Dynamic Load ◽  
Spur Gear ◽  
Tooth Size ◽  
Contact Ratio ◽  
Gear Dynamics ◽  
Wide Range ◽  
Gear Contact ◽  
Center Distance ◽  
Selection Of ◽  
Better Than

This paper presents a computer simulation showing how the gear contact ratio affects the dynamic load on a spur gear transmission. The contact ratio can be affected by the tooth addendum, the pressure angle, the tooth size (diametral pitch), and the center distance. The analysis presented in this paper was performed by using the NASA gear dynamics code DANST. In the analysis, the contact ratio was varied over the range 1.20 to 2.40 by changing the length of the tooth addendum. In order to simplify the analysis, other parameters related to contact ratio were held constant. The contact ratio was found to have a significant influence on gear dynamics. Over a wide range of operating speeds, a contact ratio close to 2.0 minimized dynamic load. For low-contact-ratio gears (contact ratio less than two), increasing the contact ratio reduced gear dynamic load. For high-contact-ratio gears (contact ratio equal to or greater than 2.0), the selection of contact ratio should take into consideration the intended operating speeds. In general, high-contact-ratio gears minimized dynamic load better than low-contact-ratio gears.

scholarly journals Genetic analysis of three maize husk traits by QTL mapping in a maize-teosinte population

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xiaolei Zhang ◽  
Ming Lu ◽  
Aiai Xia ◽  
Tao Xu ◽  
Zhenhai Cui ◽  
...  
Keyword(s):  
Phenotypic Variation ◽  
Genetic Basis ◽  
Molecular Breeding ◽  
Best Linear Unbiased Predictor ◽  
Maize Line ◽  
Maize Varieties ◽  
Outer Covering ◽  
High Heritability ◽  
Best Linear Unbiased ◽  
Variation Explained

Abstract Background The maize husk consists of numerous leafy layers and plays vital roles in protecting the ear from pathogen infection and dehydration. Teosinte, the wild ancestor of maize, has about three layers of small husk outer covering the ear. Although several quantitative trait loci (QTL) underlying husk morphology variation have been reported, the genetic basis of husk traits between teosinte and maize remains unclear. Results A linkage population including 191 BC2F8 inbred lines generated from the maize line Mo17 and the teosinte line X26–4 was used to identify QTL associated with three husk traits: i.e., husk length (HL), husk width (HW) and the number of husk layers (HN). The best linear unbiased predictor (BLUP) depicted wide phenotypic variation and high heritability of all three traits. The HL exhibited greater correlation with HW than HN. A total of 4 QTLs were identified including 1, 1, 2, which are associated with HL, HW and HN, respectively. The proportion of phenotypic variation explained by these QTLs was 9.6, 8.9 and 8.1% for HL, HN and HW, respectively. Conclusions The QTLs identified in this study will pave a path to explore candidate genes regulating husk growth and development, and benefit the molecular breeding program based on molecular marker-assisted selection to cultivate maize varieties with an ideal husk morphology.

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