Estimation of soybean genetic progress in the South of Brazil using multi-environmental yield trials

The success of a genetic breeding program in a certain period can be assessed by the genetic gain observed. Genetic progress can be estimated from the multi environmental trials (MET) data which are routinely carried out by annual species breeding programs for the assessment of new commercial cultivars. A data set of 20 years of MET of advanced soybean lines derived from four breeding programs was used to estimate and to compare the genetic gains obtained for three soybean maturity groups (early, medium and late) in four cropping regions of the State of Rio Grande do Sul. The estimated yield gains ranged from 0.0 to 71.5 kg ha-1 year-1 (3.49% per year), depending on the maturity group and region, which suggests that the genetic breeding effort does not have a similar effect among the maturity groups or benefit the regions equally. There was no evidence of genetic progress for the early maturity group in any of the four regions, whereas gains in Regions I and IV were comparatively greater than those in Regions II and III. The objectives of the soybean breeding program in the region should be redirected. Since not all the experimental lines used to estimate genetic gains were commercially released, the reported genetics gains were achieved by the breeding programs rather than those achieved by the cropping systems.

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ARE TODAY’S DAIRY CATTLE BREEDING PROGRAMS SUITABLE FOR TOMORROW’S PRODUCTION REQUIREMENTS?

Canadian Journal of Animal Science ◽

10.4141/cjas80-034 ◽

1980 ◽

Vol 60 (2) ◽

pp. 253-264 ◽

Cited By ~ 4

Author(s):

A. J. McALLISTER

Keyword(s):

Dairy Cattle ◽

Genetic Improvement ◽

Herd Size ◽

Breeding Program ◽

Genetic Trend ◽

Genetic Progress ◽

Breeding Programs ◽

Holstein Breed ◽

Dairy Cattle Breeding ◽

National Production

In the last decade the dairy cattle population has declined to a level of 1.9 million cows in 1978 with about 56% of these cows bred AI and nearly 20% of the population enrolled in a supervised milk recording program. The decline in cow numbers has been accompanied by an increase in herd size and production per cow. The current breeding program of the dairy industry is a composite of breeding decisions made by AI organizations, breeders who produce young bulls for sampling and all dairymen who choose the sires and dams of their replacement heifers. Estimates of genetic trend from 1958–1975 for milk production in the national milk recorded herd range from 21 to 55 kg per year for the four dairy breeds with Holsteins being 41 kg per year. Both differential use of superior proven sires and improved genetic merit of young bulls entering AI studs contribute to this genetic improvement. Various national production and marketing alternatives were examined. Selection is a major breeding tool in establishing a breeding program to meet national production requirements for milk and milk products once the selection goal is defined. AI and young sire sampling programs will continue to be the primary vehicle for genetic improvement through selection regardless of the selection goal. The current resources of milk-recorded cows bred AI is not being fully utilized to achieve maximum genetic progress possible from young sire sampling indicate that the number of young bulls sampled annually in the Holstein breed could be tripled with the existing milk-recorded and AI bred dairy cow population. Expanded milk recording and AI breeding levels could increase the potential for even further genetic improvement. The potential impact of selection for other traits, crossbreeding and the use of embryo transfer of future breeding programs is highlighted.

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Five decades of black common bean genetic breeding in Brazil

Pesquisa Agropecuária Tropical ◽

10.1590/1983-40632016v4641371 ◽

2016 ◽

Vol 46 (3) ◽

pp. 259-266 ◽

Cited By ~ 4

Author(s):

Leiri Daiane Barili ◽

Naine Martins do Vale ◽

José Eustáquio de Souza Carneiro ◽

Fabyano Fonseca e Silva ◽

Felipe Lopes da Silva

Keyword(s):

Grain Yield ◽

Common Bean ◽

Seed Weight ◽

Regression Models ◽

Plant Architecture ◽

Agronomic Traits ◽

Linear Regression Models ◽

Genetic Progress ◽

Breeding Programs ◽

Genetic Breeding

ABSTRACT The increase in grain yield and other agronomic traits, in common bean cultivars, is due, in large part, to its genetic breeding. This study aimed at estimating the genetic progress for grain yield and other important agronomic traits in black common bean cultivars recommended by Brazilian breeding programs between 1960 and 2013. A randomized blocks design was used, with three replications and 40 black common bean cultivars. The following traits were evaluated: grain yield and appearance, plant architecture, number of pods per plant and seeds per pod and 1,000-seed weight. The genetic progress was estimated from the trait averages over the years, using bissegmented linear regression models that allowed the inference of the exact year in which the black common bean breeding began to present significant genetic progress. For grain yield, the genetic progress was observed from 1988, with an annual gain of 2.42 %. Improvements also occurred to grain appearance (1.85 %), plant architecture (1.35 %), number of pods per plant (2.36 %) and seeds per pod (2.24 %) and 1,000-seed weight (1.42 %), mainly after 1989.

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Genotypic Variation of Different Maturity Groups of Maize (Zea mays L.) for Seed Physiological Quality

Journal of Experimental Agriculture International ◽

10.9734/jeai/2020/v42i530527 ◽

2020 ◽

pp. 139-149

Author(s):

O. Bankole ◽

A. Oluwaranti ◽

S. A. Ajayi ◽

F. E. Awosanmi

Keyword(s):

Crop Production ◽

Seed Quality ◽

Genotypic Variation ◽

Accelerated Ageing ◽

Maturity Group ◽

Early Maturity ◽

Maize Genotypes ◽

Maize Varieties ◽

Late Maturity ◽

Maturity Groups

Maize genotypes of different maturity groups with good seed quality had been developed, but there is little or no information on how the seed quality of the maize genotypes are affected by their maturity groups. Therefore, the objectives of this study were to evaluate maize varieties of different maturity groups for seed quality and determine genotypic variations that exist within the different maturity groups of maize for seed quality. Laboratory experiments were conducted in the Seed Science Laboratory of the Department of Crop Production and Protection, Obafemi Awolowo University, Ile-Ife, Nigeria. Seeds of sixteen maize genotypes of different maturity groups were subjected to imbibition, germination, accelerated ageing, conductivity and seedling vigor tests. The late maturity group (TZLCOMP.4DTF2,TZLCOMP. 1C6/DT.SYN-1-W, WHITEDTSTR/TZLCOMP.1-W, OBASUPER1) gave the best viability, speed of germination and days to complete germination while the extra early maturity group (2009TZEE-ORISTRQPM, 2000SYNEE-WSTR,2013TZEE-WDTSTR, TZEE-WPOPDTC2STRC5F2) had the least performance. The early (2014TZE –YDTSTR, 2013DTESTR–WSYN, EVDT-2000STRC0, 2009DTEWSTRSYN) and extra-early maturity groups had the longest root length and highest root number respectively. However, the different maturity groups of maize evaluated imbibed water at the same rate. TZEE-WPOP DT STR C5 F2, 2013 DTE STR – W SYN, AFLATOXIN R-SYN2, TZL COMP.1 C6/DT. SYN-1-W among extra early, early, intermediate and late maturity groups respectively performed best for viability and vigor tests.

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A unifying concept of animal breeding programs

10.1101/2020.07.08.193201 ◽

2020 ◽

Author(s):

H. Simianer ◽

A. Ganesan ◽

L. Buettgen ◽

N.T. Ha ◽

T. Pook

Keyword(s):

R Package ◽

Companion Paper ◽

Animal Breeding ◽

Breeding Program ◽

General Definition ◽

Full Description ◽

Genetic Progress ◽

Breeding Programs ◽

Definition Of ◽

Transgenic Technologies

ABSTRACTModern animal breeding programs are constantly evolving with advances in breeding theory, biotechnology and genetics. Surprisingly, there seems to be no generally accepted succinct definition of what exactly a breeding program is, neither is there a unified language to describe breeding programs in a comprehensive, unambiguous and reproducible way. In this work, we try to fill this gap by suggesting a general definition of breeding programs that also pertains to cases where genetic progress is not achieved through selection, but e.g. through transgenic technologies, or the aim is not to generate genetic progress, but e.g. to maintain genetic diversity. The key idea of the underlying concept is to represent a breeding program in modular form as a directed graph that is composed of nodes and edges, where nodes represent cohorts of breeding units, usually individuals, and edges represent breeding activities, like ‘selection’ or ‘reproduction’. We claim, that by defining a comprehensive set of nodes and edges it is possible to represent any breeding program of arbitrary complexity by such a graph, which thus comprises a full description of the breeding program. This concept is implemented in a web-based tool (MoBPSweb, available at www.mobps.de) which is described in a companion paper, and has a link to the R-package MoBPS (Modular Breeding Program Simulator) to simulate the described breeding programs. The approach is illustrated by showcasing three different breeding programs of increasing complexity. Finally, potential limitations of the concept are indicated and extensions to other fields, like plant breeding, are discussed.

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Sugarcane Breeding in Reunion: Challenges, Achievements and Future Prospects

Sugar Tech ◽

10.1007/s12355-021-00998-0 ◽

2021 ◽

Author(s):

Thomas Dumont ◽

Laurent Barau ◽

Audrey Thong-Chane ◽

Jordan Dijoux ◽

Mathilde Mellin ◽

...

Keyword(s):

Breeding Program ◽

Large Network ◽

Genetic Progress ◽

Breeding Programs ◽

Selection Scheme ◽

Sugarcane Breeding ◽

Genetics Research ◽

Research Activities ◽

Production Areas ◽

Genetic Context

AbstractAll over the world, sugarcane breeding programs are developing new, high-yielding cultivars that are resistant to major diseases to improve the profitability and sustainability of the sugar-energy industries they serve. In Reunion Island, sugarcane genetic improvement efforts began in 1929. Many challenges had to be overcome. Continuous breeding efforts have been made to develop varietal resistances to control some major diseases and are still going on today. Given the extreme agroclimatic diversity that characterizes the different production areas of the industry, it was necessary to gradually develop a large network of seven decentralized breeding programs to support genetic progress throughout the whole industry. This article provides an overview of the sugarcane breeding program of Reunion. It describes historical achievements and gives detailed information about germplasm development, variety exchanges, breeding program and selection scheme and procedures. A review is also made on applied genetics research activities supporting variety improvement. Further progress depends on the optimized functioning of the current breeding program, which has never been so largely extended in terms of target environments. The article discusses prospects of genomics breeding applications in the complex genetic context of sugarcane, which will require large multidisciplinary collaborations.

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Translational genomics and molecular breeding for enhancing precision and efficiency in crop improvement programs: Some examples in legumes

Indian Journal of Genetics and Plant Breeding (The) ◽

10.31742/ijgpb.79s.1.13 ◽

2019 ◽

Vol 79 (01S) ◽

Author(s):

Abhishek Bohra ◽

Chellapilla Bharadwaj ◽

T. Radhakrishnan ◽

Narendra P. Singh ◽

Rajeev K. Varshney

Keyword(s):

Molecular Breeding ◽

Cropping Systems ◽

Crop Improvement ◽

Great Success ◽

Crop Breeding ◽

Breeding Programs ◽

Genetic Gains ◽

Genomic Resources ◽

Legume Crops ◽

Improvement Programs

Legumes like chickpea, pigeonpea and groundnut are protein rich, nutrient-dense, and nitrogen fixing crops. Their importance is increasingly recognized in view of the urgent need to address burgeoning malnutrition problem and to impart sustainability to cropping systems. Breeding programs in these crops have achieved great success. However, consistent improvement in genetic gains demands integration of innovative tools and technologies with crop breeding programs. Genomic resources are of paramount significance in context of improving the efficiency and precision of crop breeding schemes. The last decade has witnessed a remarkable success in generating unprecedented genomic resources in these crops, thus transforming these genomic orphans into genomic resource rich crops. These genomic resources include array-based genotyping platforms, high-resolution genetic linkage maps/HapMaps, comprehensive transcriptome assemblies and gene expression atlas, and whole genome sequences etc. Further progression from the training phase (development) to breeding (deployment) phase is marked with the current availability of a variety of molecular breeding products in these legume crops. In the present review, we discuss how deployment of the modern genomic resources such as next-generation gene discovery techniques and “gold standard experimental designs” is furthering our knowledge about the genetic underpinnings of trait variation. Also, key success stories demonstrating the power of molecular breeding in these legume crops are highlighted. It is opined that the breeding populations constantly improved by sequence-based breeding approach will greatly help improving breeding traits and the genetic gains accruable from crop breeding programs.

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Allelic state at the microsatellite locus Xgwm261 marking the dwarfing gene Rht8 in Egyptian bread wheat (Triticum aestivum L.) genotypes released from 1947 to 2004

Genetika ◽

10.2298/gensr1502741s ◽

2015 ◽

Vol 47 (2) ◽

pp. 741-750 ◽

Cited By ~ 1

Author(s):

Khaled Salem

Keyword(s):

Allele Frequency ◽

Bread Wheat ◽

Microsatellite Locus ◽

Wheat Breeding ◽

Breeding Program ◽

Early Maturity ◽

Breeding Programs ◽

Dwarfing Gene ◽

Wheat Breeding Program ◽

Wheat Genotypes

Rht8 is widely used in dry environments such as Mediterranean regions where it increases plant adaptability. Variation at the Gatersleben wheat microsatellite Xgwm261 locus, whose 192-bp allele closely linked to the dwarfing gene Rht8, on chromosome 2D within 0.6 cM, was used to screen thirty Egyptian bread wheat genotypes released from (1947-2004) to assess the variation at this locus. There were three microsatellite allelic variants based on size. Screening of this wheat collection showed that the three alleles Xgwm261-165, Xgwm261-174 and Xgwm261-192 bp were the most frequent. The highest allele frequency was observed for a Xgwm261-165 bp fragment (65.52%) followed by a Xgwm261-174 bp fragment (24.14%). However, the allele frequency of a Xgwm261-192 bp fragment among these wheat genotypes was 10.34%. The percentage distribution of dwarfing alleles for the microsatellite locus Xgwm261 in the Egyptian wheat breeding programs was 30, 20, 20 and 30% for the wheat breeding program Giza, Sakha, Gemmiza and Sids, respectively. PIC for Xgwm261 was 0.527. Genetic heritage of Egyptian genotypes at the microsatellite locus Xgwm261 is consequence of new parental components usage, carriers short plant and early maturity attributes and consequent selection progeny with these traits in breeding programs. The present study will be helpful in characterization Egyptian wheat genotypes, as well as in accurate selection of parents for wheat breeding program in Egypt.

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Matoa (Pometia Pinata Foster): Local Fruit Papua and Strategy Development

Beccariana Botanical Research Bulletin ◽

10.30862/bbrp.v7i1.276 ◽

2010 ◽

Vol 7 (1) ◽

Author(s):

Julius D. Nugroho

Keyword(s):

Genetic Resources ◽

Fruit Tree ◽

Breeding Program ◽

Strategy Development ◽

Local Market ◽

Font Size ◽

Breeding Programs ◽

Irian Jaya ◽

Forest Exploitation ◽

Program Strategy

Matoa (Pometia pinnata) is a local fruit of  Papua (formerly called Irian Jaya) which has high potensial to develop as comercial fruit. Highly significant genetic resources of matoa potentially for breeding program in Papua are being threatened as a result of cutting down trees for fruit harvesting and of forest exploitation for timber. Besides the loss of genetic resources facing now, other major problems should be consider for conservation and domestication of this fruit tree species i.e. lack of silviculture and agronomy knowledge for further breeding programs; matoa production only for local market; and inadequate government policy for matoa breeding program. Strategy developed for matoa conservation and domestication should also concern about time limited due to the fast loss of genetic poll. This paper provides a general overview of strategy for conservation and domestication of Pometia pinnata with special reference to Papua.

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Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review

Animals ◽

10.3390/ani11030599 ◽

2021 ◽

Vol 11 (3) ◽

pp. 599

Author(s):

Miguel A. Gutierrez-Reinoso ◽

Pedro M. Aponte ◽

Manuel Garcia-Herreros

Keyword(s):

Dairy Cattle ◽

Production Efficiency ◽

Association Studies ◽

Phenotypic Traits ◽

Progeny Testing ◽

Genome Wide Association Studies ◽

Genetic Progress ◽

Breeding Programs ◽

Increased Risk ◽

Selection Of

Genomics comprises a set of current and valuable technologies implemented as selection tools in dairy cattle commercial breeding programs. The intensive progeny testing for production and reproductive traits based on genomic breeding values (GEBVs) has been crucial to increasing dairy cattle productivity. The knowledge of key genes and haplotypes, including their regulation mechanisms, as markers for productivity traits, may improve the strategies on the present and future for dairy cattle selection. Genome-wide association studies (GWAS) such as quantitative trait loci (QTL), single nucleotide polymorphisms (SNPs), or single-step genomic best linear unbiased prediction (ssGBLUP) methods have already been included in global dairy programs for the estimation of marker-assisted selection-derived effects. The increase in genetic progress based on genomic predicting accuracy has also contributed to the understanding of genetic effects in dairy cattle offspring. However, the crossing within inbred-lines critically increased homozygosis with accumulated negative effects of inbreeding like a decline in reproductive performance. Thus, inaccurate-biased estimations based on empirical-conventional models of dairy production systems face an increased risk of providing suboptimal results derived from errors in the selection of candidates of high genetic merit-based just on low-heritability phenotypic traits. This extends the generation intervals and increases costs due to the significant reduction of genetic gains. The remarkable progress of genomic prediction increases the accurate selection of superior candidates. The scope of the present review is to summarize and discuss the advances and challenges of genomic tools for dairy cattle selection for optimizing breeding programs and controlling negative inbreeding depression effects on productivity and consequently, achieving economic-effective advances in food production efficiency. Particular attention is given to the potential genomic selection-derived results to facilitate precision management on modern dairy farms, including an overview of novel genome editing methodologies as perspectives toward the future.

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Convolutional Neural Networks to Estimate Dry Matter Yield in a Guineagrass Breeding Program Using UAV Remote Sensing

Sensors ◽

10.3390/s21123971 ◽

2021 ◽

Vol 21 (12) ◽

pp. 3971

Author(s):

Gabriel Silva de Oliveira ◽

José Marcato Junior ◽

Caio Polidoro ◽

Lucas Prado Osco ◽

Henrique Siqueira ◽

...

Keyword(s):

Remote Sensing ◽

Dry Matter ◽

Pearson Correlation ◽

Genetic Correlations ◽

Remote Sensing Data ◽

Breeding Program ◽

Yield Traits ◽

Dry Matter Yield ◽

Breeding Programs ◽

Ground Truth Data

Forage dry matter is the main source of nutrients in the diet of ruminant animals. Thus, this trait is evaluated in most forage breeding programs with the objective of increasing the yield. Novel solutions combining unmanned aerial vehicles (UAVs) and computer vision are crucial to increase the efficiency of forage breeding programs, to support high-throughput phenotyping (HTP), aiming to estimate parameters correlated to important traits. The main goal of this study was to propose a convolutional neural network (CNN) approach using UAV-RGB imagery to estimate dry matter yield traits in a guineagrass breeding program. For this, an experiment composed of 330 plots of full-sib families and checks conducted at Embrapa Beef Cattle, Brazil, was used. The image dataset was composed of images obtained with an RGB sensor embedded in a Phantom 4 PRO. The traits leaf dry matter yield (LDMY) and total dry matter yield (TDMY) were obtained by conventional agronomic methodology and considered as the ground-truth data. Different CNN architectures were analyzed, such as AlexNet, ResNeXt50, DarkNet53, and two networks proposed recently for related tasks named MaCNN and LF-CNN. Pretrained AlexNet and ResNeXt50 architectures were also studied. Ten-fold cross-validation was used for training and testing the model. Estimates of DMY traits by each CNN architecture were considered as new HTP traits to compare with real traits. Pearson correlation coefficient r between real and HTP traits ranged from 0.62 to 0.79 for LDMY and from 0.60 to 0.76 for TDMY; root square mean error (RSME) ranged from 286.24 to 366.93 kg·ha−1 for LDMY and from 413.07 to 506.56 kg·ha−1 for TDMY. All the CNNs generated heritable HTP traits, except LF-CNN for LDMY and AlexNet for TDMY. Genetic correlations between real and HTP traits were high but varied according to the CNN architecture. HTP trait from ResNeXt50 pretrained achieved the best results for indirect selection regardless of the dry matter trait. This demonstrates that CNNs with remote sensing data are highly promising for HTP for dry matter yield traits in forage breeding programs.

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