scholarly journals Using Huehn’s Nonparametric Stability Statistics to Investigate Genotype × Environment Interaction

2012 ◽  
Vol 40 (1) ◽  
pp. 293 ◽  
Author(s):  
Rahmatollah KARIMIZADEH ◽  
Mohtasham MOHAMMADI ◽  
Naser SABAGHNIA ◽  
Mohammad Kazem SHEFAZADEH
Keyword(s):  
Nonparametric Statistics ◽  
Environment Interaction ◽  
Breeding Programs ◽  
Local Cultivar ◽  
Stability Statistics ◽  
Stability Results ◽  
Stability Concepts ◽  
Genotype A ◽  
Static Concept ◽  
Selection Of

Genotype × environment interaction (GEI) is of special interest in breeding programs to identify adaptation targets and test locations as well as to determine the most favorable genotypes. There are several nonparametric procedures used to interpret the GEI in multi-environmental trials. The purposes of this investigation were (i) to compare the effect of correction on Huehn’s nonparametric stability statistics and (ii) to use nonparametric statistics for a GEI study on lentil. Nine improved lentil genotypes and one local cultivar were grown in 5 sites during two consecutive years. Results of the nonparametric analysis demonstrated both additive and crossover GEIs. According to uncorrected nonparametric statistics, genotypes G8 and G9 were the most stable and based on corrected nonparametric statistics of Huehn, genotypes G1, G2 and G10 were the most stable. In this investigation, mean of ranks (MR) and coefficient of variation of ranks (CV) with (6)iSwere associated with high mean yield (within the dynamic concept of stability), but the other nonparametric statistics were not positively correlated with mean yield and were identified within a static concept of stability. Results also indicated that corrected nonparametric statistics were not suitable for simultaneous selection of mean yield and stability. Such an outcome could be used to delineate predictive, more rigorous recommendation strategies as well as to help define stability concepts to identify recommendations for lentil and other crops.

Simultaneous selection for high yield and stability in common bean (Phaseolus vulgaris) genotypes

2002 ◽  
Vol 138 (3) ◽  
pp. 249-253 ◽  
Author(s):  
F. MEKBIB
Keyword(s):  
Common Bean ◽  
Genotype By Environment Interaction ◽  
Yield Stability ◽  
High Yield ◽  
Environment Interaction ◽  
Yield Performance ◽  
Simultaneous Selection ◽  
Selection For ◽  
Stability Statistics ◽  
Selection Of

Phenotypic yield stability is a trait of special interest for plant breeders and farmers. This value can be quantified if genotypes are evaluated in different environments. Common bean is the main cash crop and protein source of farmers in many lowland and mid-altitude areas of Ethiopia. An experiment was undertaken to evaluate common bean genotypes for yield performance at Alemaya, Bako and Nazreth in Ethiopia for 3 years. The yield performance of genotypes was subjected to stability analysis and yield-stability statistics were generated to aid the selection of genotypes that were high yielding and very stable. The significant genotype by environment interaction indicated that the relative performance of the varieties altered in the different environments. Genotype yield performance varied ranging from 1511–2216 kg/ha. Simultaneous selection for yield and yield-stability statistics using YS(i) statistics indicated that A 410, GLP x92, Mx-2500-19, G 2816, A-195, 997-CH-1173, Diacol calima, ICA 15541 and AND 635 were both high yielding and stable. Following this study, using farmers’ evaluation and other criteria, GLP x92 and G-2816 were identified as preferred genotypes and were released for further production.

Approaches to rationalising selection of test environments for on-farm lentil variety trials in Mediterranean rainfed cropping systems

2007 ◽  
Vol 58 (4) ◽  
pp. 335 ◽  
Author(s):  
A. Sarker ◽  
M. Singh ◽  
F. El-Ashkar ◽  
W. Erskine ◽  
E. De-Pauw
Keyword(s):  
Cropping Systems ◽  
Genotypic Differences ◽  
Environment Interaction ◽  
Local Cultivar ◽  
Genotype Environment Interaction ◽  
Genotype Cluster ◽  
Yield Responses ◽  
Temporal Interactions ◽  
On Farm ◽  
Selection Of

This study focused on various approaches to rationalising the selection of test environments using on-farm trial data from 5 lentil (Lens culiniaris Medikus subsp. culinaris) genotypes. It was conducted over 3 years in 30 environments across 16 locations in Syria. There was maximum discrimination in the ratio of between-cluster to within-cluster variances, based on genotype yield responses to the environments. Four clusters represented the test locations, reflecting a gradient in the levels of yield and seasonal rainfall. We observed significant genotypic differences and genotype × environment interactions. Genotype × cluster interaction accounted for a substantial portion of the genotype × environment interaction. This supported a reduction in the number of test locations to evaluate genotype and environment interaction. Temporal interactions were either low or insignificant. The improved lines produced stable and significantly higher yields than the local cultivar. The structure of the clusters formed indicated the presence of research stations in each cluster. We recommend that locations for future on-farm testing should include one research location and a farmer field in each cluster (or the mega-zone) so formed. Climatic variables or geographical nearness cannot replace the role of genotype response when rationalising test locations.

scholarly journals Improve Soybean Variety Selection Accuracy Using UAV-Based High-Throughput Phenotyping Technology

2022 ◽  
Vol 12 ◽  
Author(s):  
Jing Zhou ◽  
Eduardo Beche ◽  
Caio Canella Vieira ◽  
Dennis Yungbluth ◽  
Jianfeng Zhou ◽  
...  
Keyword(s):  
High Throughput ◽  
Multispectral Imaging ◽  
Large Population ◽  
Image Features ◽  
Environment Interaction ◽  
Breeding Programs ◽  
Soybean Yield ◽  
Yield Trial ◽  
High Throughput Phenotyping ◽  
Selection Of

The efficiency of crop breeding programs is evaluated by the genetic gain of a primary trait of interest, e.g., yield, achieved in 1 year through artificial selection of advanced breeding materials. Conventional breeding programs select superior genotypes using the primary trait (yield) based on combine harvesters, which is labor-intensive and often unfeasible for single-row progeny trials (PTs) due to their large population, complex genetic behavior, and high genotype-environment interaction. The goal of this study was to investigate the performance of selecting superior soybean breeding lines using image-based secondary traits by comparing them with the selection of breeders. A total of 11,473 progeny rows (PT) were planted in 2018, of which 1,773 genotypes were selected for the preliminary yield trial (PYT) in 2019, and 238 genotypes advanced for the advanced yield trial (AYT) in 2020. Six agronomic traits were manually measured in both PYT and AYT trials. A UAV-based multispectral imaging system was used to collect aerial images at 30 m above ground every 2 weeks over the growing seasons. A group of image features was extracted to develop the secondary crop traits for selection. Results show that the soybean seed yield of the selected genotypes by breeders was significantly higher than that of the non-selected ones in both yield trials, indicating the superiority of the breeder's selection for advancing soybean yield. A least absolute shrinkage and selection operator model was used to select soybean lines with image features and identified 71 and 76% of the selection of breeders for the PT and PYT. The model-based selections had a significantly higher average yield than the selection of a breeder. The soybean yield selected by the model in PT and PYT was 4 and 5% higher than those selected by breeders, which indicates that the UAV-based high-throughput phenotyping system is promising in selecting high-yield soybean genotypes.

ESTIMASI NILAI HERITABILITAS BOBOT IKAN MAS VARIETAS PUNTEN DALAM PROGRAM SELEKSI INDIVIDU

2016 ◽  
Vol 11 (3) ◽  
pp. 217
Author(s):  
Estu Nugroho ◽  
Budi Setyono ◽  
Mochammad Su’eb ◽  
Tri Heru Prihadi
Keyword(s):  
Body Weight ◽  
Selection Response ◽  
Base Population ◽  
Breeding Programs ◽  
Male And Female ◽  
Body Weight Trait ◽  
Population Selection ◽  
Selection For ◽  
Weight Trait ◽  
Selection Of

Program pemuliaan ikan mas varietas Punten dilakukan dengan seleksi individu terhadap karakter bobot ikan. Pembentukan populasi dasar untuk kegiatan seleksi dilakukan dengan memijahkan secara massal induk ikan mas yang terdiri atas 20 induk betina dan 21 induk jantan yang dikoleksi dari daerah Punten, Kepanjen (delapan betina dan enam jantan), Kediri (tujuh betina dan 12 jantan), Sragen (27 betina dan 10 jantan), dan Blitar (15 betina dan 11 jantan). Larva umur 10 hari dipelihara selama empat bulan. Selanjutnya dilakukan penjarangan sebesar 50% dan benih dipelihara selama 14 bulan untuk dilakukan seleksi dengan panduan hasil sampling 250 ekor individu setiap populasi. Seleksi terhadap calon induk dilakukan saat umur 18 bulan pada populasi jantan dan betina secara terpisah dengan memilih berdasarkan 10% bobot ikan yang terbaik. Calon induk yang terseleksi kemudian dipelihara hingga matang gonad, kemudian dipilih sebanyak 150 pasang dan dipijahkan secara massal. Didapatkan respons positif dari hasil seleksi berdasarkan bobot ikan, yaitu 49,89 g atau 3,66% (populasi ikan jantan) dan 168,47 g atau 11,43% (populasi ikan betina). Nilai heritabilitas untuk bobot ikan adalah 0,238 (jantan) dan 0,505 (betina).Punten carp breeding programs were carried out by individual selection for body weight trait. The base population for selection activities were conducted by mass breeding of parent consisted of 20 female and 21 male collected from area Punten, eight female and six male (Kepanjen), seven female and 12 male (Kediri), 27 female and 10 male (Sragen), 15 female and 11 male (Blitar). Larvae 10 days old reared for four moths. Then after spacing out 50% of total harvest, the offspring reared for 14 months for selection activity based on the sampling of 250 individual each population. Selection of broodstock candidates performed since 18 months age on male and female populations separately by selecting based on 10% of fish with best body weight. Candidates selected broodstocks were then maintained until mature. In oder to produce the next generation 150 pairs were sets and held for mass spawning. The results revealed that selection response were positive, 49.89 g (3.66%) for male and 168.47 (11.43%) for female. Heritability for body weight is 0.238 (male) and 0.505 (female).

scholarly journals Disclosing the Nutritional Quality Diversity of Portuguese Common Beans—The Missing Link for Their Effective Use in Protein Quality Breeding Programs

Agronomy ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 221
Author(s):  
Elsa Mecha ◽  
Sofia Natalello ◽  
Bruna Carbas ◽  
Andreia Bento da Silva ◽  
Susana T. Leitão ◽  
...  
Keyword(s):  
Heat Stress ◽  
Amino Acid ◽  
Nutritional Quality ◽  
Dietary Habits ◽  
Protein Quality ◽  
Trypsin Inhibitor Activity ◽  
Environment Interaction ◽  
Individual Amino Acid ◽  
Common Beans ◽  
Breeding Programs

The common bean (Phaseolus vulgaris L.) represents a sustainable and affordable source of protein, namely, to populations with vegetarian dietary habits. Despite the national germplasm genetic diversity, little is known about the Portuguese accessions’ nutritional and protein quality, leading to their underuse in breeding programs. To fill this gap, a representative collection (106 accessions) was cropped under two contrasting environments (traditional versus heat stress) and evaluated in terms of nutritional quality by near-infrared spectroscopy. Protein quality was assessed, under the stressful environment, considering the individual amino acid contents and the activity of trypsin inhibitors through mass spectrometry (LC-MS/MS) and spectrophotometry, respectively. On top of strong genotypic control, the nutritional composition (protein, fat, fiber, moisture and ash) was also highly influenced by the environment and by genotype × environment interaction, with a clear nutritional quality ranking change for the accessions in heat stress conditions. Classified into three clusters, the accessions from the cluster with the highest individual amino acid and protein contents also showed higher trypsin inhibitor activity (TIA). Since different levels of TIA had no translation into contrasting protein digestibility, breeders focusing on common beans’ protein quality improvement, especially under challenging warming climate conditions, may take advantage of this group of accessions.

scholarly journals Combining metabolomic and transcriptomic approaches to assess and improve crop quality traits

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Delphine M. Pott ◽  
Sara Durán-Soria ◽  
Sonia Osorio ◽  
José G. Vallarino
Keyword(s):  
Quality Trait ◽  
Quality Traits ◽  
Crop Species ◽  
Breeding Programs ◽  
Crop Quality ◽  
Crop Varieties ◽  
New Genes ◽  
Technical Advances ◽  
Health Promoting ◽  
Selection Of

AbstractPlant quality trait improvement has become a global necessity due to the world overpopulation. In particular, producing crop species with enhanced nutrients and health-promoting compounds is one of the main aims of current breeding programs. However, breeders traditionally focused on characteristics such as yield or pest resistance, while breeding for crop quality, which largely depends on the presence and accumulation of highly valuable metabolites in the plant edible parts, was left out due to the complexity of plant metabolome and the impossibility to properly phenotype it. Recent technical advances in high throughput metabolomic, transcriptomic and genomic platforms have provided efficient approaches to identify new genes and pathways responsible for the extremely diverse plant metabolome. In addition, they allow to establish correlation between genotype and metabolite composition, and to clarify the genetic architecture of complex biochemical pathways, such as the accumulation of secondary metabolites in plants, many of them being highly valuable for the human diet. In this review, we focus on how the combination of metabolomic, transcriptomic and genomic approaches is a useful tool for the selection of crop varieties with improved nutritional value and quality traits.

scholarly journals Mapping QTL for spike fertility and related traits in two doubled haploid wheat (Triticum aestivum L.) populations

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Nicole Pretini ◽  
Leonardo S. Vanzetti ◽  
Ignacio I. Terrile ◽  
Guillermo Donaire ◽  
Fernanda G. González
Keyword(s):  
Doubled Haploid ◽  
Marker Assisted Selection ◽  
Triticum Aestivum L ◽  
Physiological Model ◽  
Yield Potential ◽  
Breeding Programs ◽  
Per Se ◽  
Genomic Regions ◽  
Fertility Traits ◽  
Selection Of

Abstract Background In breeding programs, the selection of cultivars with the highest yield potential consisted in the selection of the yield per se, which resulted in cultivars with higher grains per spike (GN) and occasionally increased grain weight (GW) (main numerical components of the yield). In this study, quantitative trait loci (QTL) for GW, GN and spike fertility traits related to GN determination were mapped using two doubled haploid (DH) populations (Baguette Premium 11 × BioINTA 2002 and Baguette 19 × BioINTA 2002). Results In total 305 QTL were identified for 14 traits, out of which 12 QTL were identified in more than three environments and explained more than 10% of the phenotypic variation in at least one environment. Eight hotspot regions were detected on chromosomes 1A, 2B, 3A, 5A, 5B, 7A and 7B in which at least two major and stable QTL sheared confidence intervals. QTL on two of these regions (R5A.1 and R5A.2) have previously been described, but the other six regions are novel. Conclusions Based on the pleiotropic analysis within a robust physiological model we conclude that two hotspot genomic regions (R5A.1 and R5A.2) together with the QGW.perg-6B are of high relevance to be used in marker assisted selection in order to improve the spike yield potential. All the QTL identified for the spike related traits are the first step to search for their candidate genes, which will allow their better manipulation in the future.

scholarly journals Identification of the Optimum Environments for the High Yield and Quality Traits of Lentil Genotypes Evaluated in Multi-Location Trials

2021 ◽  
Vol 13 (15) ◽  
pp. 8247
Author(s):  
Dimitrios N. Vlachostergios ◽  
Christos Noulas ◽  
Anastasia Kargiotidou ◽  
Dimitrios Baxevanos ◽  
Evangelia Tigka ◽  
...  
Keyword(s):  
Crude Protein ◽  
Agronomic Traits ◽  
High Yield ◽  
Breeding Programs ◽  
Growing Seasons ◽  
Yield And Quality ◽  
Food And Feed ◽  
Superior Genotypes ◽  
Selection Of ◽  
The Ideal

Lentil is a versatile and profitable pulse crop with high nutritional food and feed values. The objectives of the study were to determine suitable locations for high yield and quality in terms of production and/or breeding, and to identify promising genotypes. For this reason, five lentil genotypes were evaluated in a multi-location network consisting of ten diverse sites for two consecutive growing seasons, for seed yield (SY), other agronomic traits, crude protein (CP), cooking time (CT) and crude protein yield (CPY). A significant diversification and specialization of the locations was identified with regards to SY, CP, CT and CPY. Different locations showed optimal values for each trait. Locations E4 and E3, followed by E10, were “ideal” for SY; locations E1, E3 and E7 were ideal for high CP; and the “ideal” locations for CT were E3 and E5, followed by E2. Therefore, the scope of the cultivation determined the optimum locations for lentil cultivation. The GGE-biplot analysis revealed different discriminating abilities and representativeness among the locations for the identification of the most productive and stable genotypes. Location E3 (Orestiada, Region of Thrace) was recognized as being optimal for lentil breeding, as it was the “ideal” or close to “ideal” for the selection of superior genotypes for SY, CP, CT and CPY. Adaptable genotypes (cv. Dimitra, Samos) showed a high SY along with excellent values for CP, CT and CPY, and are suggested either for cultivation in many regions or to be exploited in breeding programs.

scholarly journals Genetic diversity and population structure of ridge gourd (Luffa acutangula) accessions in a Thailand collection using SNP markers

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Grimar Abdiel Perez ◽  
Pumipat Tongyoo ◽  
Julapark Chunwongse ◽  
Hans de Jong ◽  
Anucha Wongpraneekul ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Germplasm Collection ◽  
Snp Markers ◽  
Fixation Index ◽  
Breeding Programs ◽  
Total Fixation ◽  
Unrooted Phylogenetic Tree ◽  
Luffa Acutangula ◽  
Selection Of

AbstractThis study explored a germplasm collection consisting of 112 Luffa acutangula (ridge gourd) accessions, mainly from Thailand. A total of 2834 SNPs were used to establish population structure and underlying genetic diversity while exploring the fruit characteristics together with genetic information which would help in the selection of parental lines for a breeding program. The study found that the average polymorphism information content value of 0.288 which indicates a moderate genetic diversity for this L. acutangula germplasm. STRUCTURE analysis (ΔK at K = 6) allowed us to group the accessions into six subpopulations that corresponded well with the unrooted phylogenetic tree and principal coordinate analyses. When plotted, the STRUCTURE bars to the area of collection, we observed an admixed genotype from surrounding accessions and a geneflow confirmed by the value of FST = 0.137. AMOVA based on STRUCTURE clustering showed a low 12.83% variation between subpopulations that correspond well with the negative inbreeding coefficient value (FIS =  − 0.092) and low total fixation index (FIT = 0.057). There were distinguishing fruit shapes and length characteristics in specific accessions for each subpopulation. The genetic diversity and different fruit shapes in the L. acutangula germplasm could benefit the ridge gourd breeding programs to meet the demands and needs of consumers, farmers, and vegetable exporters such as increasing the yield of fruit by the fruit width but not by the fruit length to solve the problem of fruit breakage during exportation.

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

Animals ◽  
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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