Genotype-environment Interaction Effects Research Articles

Do Seedlings Derived from Pinewood Nematode-Resistant Pinus thunbergii Parl. Clones Selected in Southwestern Region Perform Well in Northern Regions in Japan? Inferences from Nursery Inoculation Tests

Background and Objectives: To determine whether the progeny of pinewood nematode-resistant Pinus thunbergii Parl. clones selected in the southwestern region of Japan could be successful in reforestation in the northern region, we investigated the magnitude of the genotype–environment interaction effect on the resistance against Bursaphelenchus xylophilus (Steiner and Buhrer) Nickle in P. thunbergii. Materials and Methods: We inoculated P. thunbergii seedlings of six full-sib families, with various resistance levels, with B. xylophilus in nurseries at three experimental sites in the northern and southern regions of Japan. All parental clones of the tested families originated from southwestern Japan, and selection of parental clones for resistance was performed in the same region. Sound rates after nematode inoculation were calculated, and survival analysis, correlation analysis and variance component analysis were performed. Results and Conclusions: Families with high sound rate in the southern region also showed a high sound rate in the northern region. In almost all cases, Spearman’s correlation coefficients for sound rates were more than 0.698 among sites. The variance component of the interaction between site and family was small compared to that of site and family separately. Thus, we conclude that the resistant clones selected in the southern region would retain their genetic resistance in the northern regions.

Identificación de clones de papa con pulpa pigmentada de alto rendimiento comercial y mejor calidad de fritura: Estabilidad y análisis multivariado de la interacción genotipo-ambiente

In the present research, nineteen advanced potato clones with pigmented-fleshed were analyzed in two potato-producing localities in Cajamarca, Peru, during two agricultural seasons, by means of the combined analysis of variance, the model of additive main effects and multiplicative interaction (AMMI) and the Biplot analysis, to analyze the genotype-environment interaction (GEI), in order to select clones with high stability of marketable yield and quality. Multivariate analysis showed differences for the main effects of genotypes, environments and GEI. Which states that the genetic makeup of each clone and the environment influenced the marketable yield and frying color due to the polygenic character that governs these characteristics. The results identified the CIP clone 302299.28 with red and cream fleshed and red skin with low IGA, which indicates that it is a stable clone with high commercial yield with 31.8 t ha-1 and a scale of 2 in the frying color, obtaining a better response to environmental variation. Followed by CIP clone 302281.17 with fleshed and yellow skin, which showed commercial yield stability with 32 t ha-1 and 2.2 of frying color. Likewise, CIP clone 302280.23 of fleshed and violet skin reported a marketable yield of 33.0 t ha-1, and 1.7 on the frying color scale, obtaining quality stability, being a clone for the processing industry in strips, flakes and other derivatives. Therefore, these clones are selected for wide production in Cajamarca.

Genotypic Variability in Some Morpho-Physiological Traits in Different Environments and Their Relationship with Cassava (Manihot esculentaCrantz) Root Yield

Cassava root yield under diverse environments is influenced by morpho-physiological traits that are in turn influenced by genotype, environment, and genotype × environment interaction (GEI). Most GEI analyses in cassava have been limited to root yield with less emphasis on stability of other yield-related traits. This study was carried out to assess the effect of GEI on some morpho-physiological traits in cassava and key traits that are useful for selection in different environments. The study utilized 20 cassava genotypes evaluated in six environments, namely, Fumesua 2013 and 2014, Nyankpala 2013 and 2014 (irrigation), and Nyankpala 2013 and 2014 (no irrigation). The genotypes were arranged in a randomized complete block design (RCBD) with three replications and assessed for a number of morpho-physiological traits, root yield and yield components. The data were subjected to analysis of variance using SAS statistical package. Subsequently, the GGE biplot was used to carry out genotype × environment, genotype × trait, and environment × trait interaction analyses to determine the specificity of genotypic performance and traits linked to particular environments. The results indicated significant (P<0.05) GEI effect on all traits except leaf temperature. The genotype × trait biplot analysis revealed closely related traits and those associated with root yield and genotypes that show weakness in these traits. Both environment × trait biplot and principal component analyses identified traits with higher discriminatory power among genotypes in various environments particularly in the dry environments. These can be used as secondary traits to select drought-tolerant genotypes. From this study, the GGE biplot was useful in identifying traits associated with specific genotypes in different environments to aid in selection. Moderate broad-sense heritability estimates werefound for storage root yield, harvest index, plant height, ratio of storage rootlength to girth, and cassava mosaic disease score indicating that progresscan be made through selection for these traits.

Screening and comprehensive evaluation of rice (Oryza sativa L. subsp. japonica Kato) germplasm resources for nitrogen efficiency in Xinjiang, China

AbstractComprehensive screening of rice (Oryza sativa L. subsp. japonica Kato) germplasm resources with different nitrogen (N) efficiency levels is effective for improving N use efficiency (NUE) while reducing pollution and providing high quality, yield, and efficiency agriculture. We investigated 14 indices of 38 varieties under three N application levels to assess differences among genotypes. Rice varieties were classified for screening and identifying N efficient. Descriptive statistical analysis results indicated significant differences in relative yield, and also in NUE indices (agronomic utilization rate and partial productivity of N fertilizer). The genotype main effects and genotype–environment interaction effects (GGE) biplot analysis was used to evaluate suitable varieties, compare the stable and high yield capabilities of different varieties, find the ideal variety, and describe the correlation, discrimination and representativeness of the indices under different N application levels. Descriptive statistical, discrimitiveness and representativeness and factor analysis were used to select indices, in which the panicle number per plant and soil and plant analyzer development (SPAD) value were the key indices for evaluation and identification. Heatmap and hierarchical cluster analysis based on the average value of evaluation indices, and scatter plot based on the comprehensive value of N efficiency (P) according to formula showed that all varieties could be divided into five types under different N treatments. Our findings work toward developing N efficient rice varieties to improve NUE, reduce N fertilizer application and thus N waste, consequently mitigating the effects of rice production on the environment to ensure food security and sustainable agricultural development.

Adaptation patterns of sixteen alfalfa (Medicago sativa L.) cultivars across contrasting environments of Algeria and implications for the crop improvement

The additive main effects and multiplicative interaction analysis was applied to assess the genotype × environment interaction (GEI) effects and stability for 4-year dry matter yield (DMY) of 16 alfalfa (Medicago sativa L.) cultivars of diversified geographic origin grown in four Algerian environments given by the combination of two water managements (rainfed and irrigated) and two evaluation sites, viz. the sub-humid location of Alger and the semi-arid, salinity-affected site of Hmadna. The analysis of variance (ANOVA) revealed significant variation among cultivars and environments (P<0.001). The GEI was significant (P<0.001) and the environment main effect had greater influence than the genotype effect on long-term yield according to ANOVA. Rainfed conditions had 41.6% and 48.5% lower yield than the irrigated ones in Alger and Hmadna, respectively. Alfalfa cropping in the semiarid location caused lower DMY than in the sub-humid one (– 38.0% under irrigated and –45.2% under rainfed conditions) and a slightly lower persistence over the 4-year period. Outstanding environment-specific cultivar responses were observed, fully justifying the large GEI effects, although the Italian cultivar Sicilian ecotype had remarkable yield stability and good mean yield. The American variety Ameristand 801S and the Moroccan landrace Erfoud 1 were the most salt-tolerant cultivars. The evaluated germplasm, and particularly some exotic cultivars, could be used as parents to breed new varieties more adapted to drought and salinity in the Mediterranean basin.

Evaluation of Genotype × Environment Interaction and Yield Stability Analysis in Peanut Under Phosphorus Stress Condition Using Stability Parameters of AMMI Model

Development of new genotypes with high yield and acceptable level of stability is an important breeding programme. The genotype × environment interaction (GEI) was studied to find out stable high yielders in a field experiment conducted with 52 peanut genotypes for 2 years under two phosphorus levels. Combined analysis of variance showed that environment effect was a predominant source of variation followed by GEI and genotype effect. Study of the AMMI model for GEI indicated that the first three interaction principal components (IPCA1–IPCA3) were highly significant (P < 0.01). Using these significant IPCAs, 12 AMMI stability parameters and simultaneous selection for yield and stability (SSI) were computed. SSI identified genotypes PBS-22080, PBS-22083 and Somnath as the most stable high yielders and PBS-29172 as the least stable low yield. Stability measures such as SIPC, MASI and MASV could be used to identify stable high-yielding genotypes.

Analysis of genotype-environment interaction and yield stability of Thai upland rice (Oryza sativa L.) genotypes using AMMI model

Genotype-environment interaction and stability analysis has been important for plant breeders and plays a vital role in identifying genotypes that are stable or unstable in a given environment. The experiments in this research were conducted to determine the effects of genotype, environment and genotype-environment interaction on grain yield using the AMMI statistical model, and to recognize the most stable rice genotypes among ten genotypes in southern Thailand’s provinces of environments in Songkhla, Satun and Phatthalung. Highly significant differences were shown from the combined analysis for environments with grain yields, revealing that environments were different and indicated change ability between the genotypes and their interactions. The average grain yield assessment of the tested genotypes was around the environments where genotype G8 (Nahng Kian) had the highest grain yield 6234.11 kg/ha. AMMI biplot of the Interaction Principal Component Analysis (IPCA) scores visualized 90.7% for IPCA1 and 9.3% for IPCA2 with the genotypes and environments for grain yield. In the AMMI stability value method, G8 (Nahng Kian) was the most stable genotype followed by the genotypes G2 (Mai Tahk) and G10 (Hawm Jet Ban) Songkhla, Satun and Phatthalung environments.

The study of the association between the C677T polymorphism of the methylenetetrahydrofolate reductase gene and severity of symptoms in patients with schizophrenia

To study the association of the C677T polymorphism of the methylenetetrahydrofolate reductase (MTHFR) gene with the risk of schizophrenia in a large sample, including schizophrenic patients and mentally healthy people, and to investigate the relationship of this polymorphism with the severity of schizophrenia symptoms and genotype-environment interaction effects on these symptoms. The sample for genotyping consisted of 1357 patients with schizophrenia and schizophrenia spectrum disorders and 711 people of the control group. The severity of symptoms was assessed with the PANSS. Obstetrical complications and a traumatic brain injury in medical history were studied as environmental factors. No association was found between MTHFR C677T polymorphism and schizophrenia. There was no genotype effect on the severity of symptoms on the PANSS subscales. The effect of genotype-environment interactions on the severity of schizophrenia symptoms was not detected. The results do not confirm the data of a number of studies on the relationship of MTHFR C677T polymorphism with schizophrenia symptoms.

Mean Performance and Stability in Multi‐Environment Trials II: Selection Based on Multiple Traits

Modeling the genotype × environment interaction (GEI) and quantifying genotypic stability are crucial steps for selecting/recommending genotypes in multi‐environment trials (METs). The efficiency in selection/recommendation could be greater if based on multiple traits, but identifying genotypes that combine high performance and stability across many traits has been a difficult task. In this study, we propose a multi‐trait stability index (MTSI) for simultaneous selection considering mean performance and stability (MPE) in the analysis of METs using both fixed and mixed‐effect models. Data from an MET where 14 traits were assessed in 22 genotypes ofAvena sativaL. were used to illustrate the application of the method. The genotypic stability was quantified for each trait using the weighted average of absolute scores from the singular value decomposition of the matrix of best linear unbiased predictions for the GEI effects generated by an linear mixed‐effect model (WAASB) index (lower is better). A superiority index, WAASBY (higher is better) was calculated to consider the MPE. The selection differential for the WAASBY index ranged from 9.7 to 44.6%. Positive selection differential (1.75% ≤ selection differential ≤ 17.8%) were observed for trait means that wanted to increase and negative (–11.7%) for one variable that wanted to reduce. The negative selection differential observed for WAASB (–63% ≤ selection differential ≤ −12%) suggested that the selected genotypes were more stable. The MTSI should be useful for breeders and agronomists who desire a selection for MPE based on multiple traits because it provides a robust and easy‐to‐handle selection process, accounting for the correlation structure of the traits. The application of the MTSI in future studies is facilitated by a step‐by‐step guide and an R package containing useful functions.Core IdeasThe genotypic stability was quantified in multi‐environment trials (MET) using mixed models.A superiority index that allows weighting between mean performance and stability was used.A multi‐trait stability index (MTSI) for identifying superior genotypes in MET was proposed.Using a real dataset from a MET, stable and high‐performance genotypes were identified.The MTSI should facilitate the genotype selection in a multi‐trait framework.

Normas de reação para peso aos 365 e 550 dias de idade em bovinos Guzerá no Nordeste do Brasil

Objetivou-se avaliar o efeito da interação genótipo ambiente (IGA) sobre os pesos ajustados aos 365 (P365) e 550 (P550) dias de idade de bovinos Guzerá por meio de modelos hierárquicos Bayesianos de norma de reação. O banco de dados utilizado foi cedido pela Associação Brasileira dos Criadores de Zebu (ABCZ) e continha 15169 e 11183 registros para o P365 e P550, respectivamente. Ajustou-se um modelo animal (MA) e modelos hierárquicos de norma de reação com variâncias homogenias e heterogenias em um passo (MHNRHO1P e MHNRHE1P, respectivamente) e dois passos (MHNRHO2P e MHNRHE2P, respectivamente) para avaliar a existência e efeito da IGA. O MHNRHO1P foi o modelo de melhor ajuste. As estimativas de herdabilidade no MA foram de 0,37 e 0,29 para o P365 e P550, respectivamente. Foram obtidos valores de herdabilidade variando de 0,21 a 0,71 para o P365 e 0,06 a 0,93 para o P550 no MHNRHO1P ao longo do gradiente ambiental. As correlações de Spearman entre as classificações dos reprodutores para o P365 e P550 variaram de 0,26 a 0,99 e de -0,99 a 0,99, respectivamente, e as correlações genéticas variaram entre 0,70 a 1,00 e 0,40 a 1,00 para o P365 e P550, respectivamente. Existe IGA em bovinos da raça Guzerá no Nordeste do Brasil para o P365 e P550, sendo necessário considerar a possibilidade de inclusão deste efeito nas avaliações genéticas.

Unraveling the effect of body structure score on phenotypic plasticity for body weight at different ages in Guzerat cattle

The Body structure (BS) is a trait to be considered in the genetic evaluation of beef cattle because it is associated with economically important traits, maintenance requirement, and physiological maturity. Therefore, the objective of this study was to determine the effect of genotype-environment (GxE) interaction considering contemporary group solutions for BW and BS as an environmental gradient (EG) to assess the changes in the body weight (BW). For this BW was measured at 120, 205, 365, 450 and 550 days of age in Guzerat cattle. Phenotypic data from 21,973 Guzerat animals were used to explore the GxE effect among BW, obtained from 150 farms distributed in five Brazilian States provided by the Brazilian Association of Zebu Breeders. A reaction norm model in two-steps was used to estimate the animals’ response to environmental changes. As evidence of GxE, heterogeneity of genetic variance across environments was observed for BW at different ages. Changes in heritability estimates ranged from 0.29 to 0.44 for BW and provided differences in the selection response across different EG levels. The genetic correlations between extreme EG levels indicated a strong effect of GxE interactions. Breeding value for BW at 120 and 205 days of age showed less plasticity than BW at 365, 450, and 550 days of age due to changes in EG. Nevertheless, these results indicate that the BS is an important factor to be considered in genetic evaluations for BW according to the growth phase.

Assessment of Stability and Adaptation Patterns of White Sugar Yield from Sugar Beet Cultivars in Temperate Climate Environments

The yield and yield quality of sugar from the sugar beet (Beta vulgaris L.) and are determined by genotype, environment and crop management. This study was aimed at analyzing the stability of white sugar yield and the adaptation of cultivars based on 36 modern sugar beet cultivars under different environmental conditions. The compatibility of sugar beet cultivars’ rankings between the three growing seasons and between the 11 examined locations was assessed. In addition, an attempt was made to group environments to create mega-environments. From among the 11 examined locations, four mega-environments were distinguished on the basis of the compatibility of the white sugar yield rankings. The assessment of the adaptation of cultivars and the determination of mega-environments was carried out using GGE (genotype main effects plus genotype environment interaction effects) biplots and confirmed by the Spearman rank correlation test performed for cultivars between locations. The cultivars studied were characterized by a high stability of white sugar yield in the considered growing seasons. The high compliance of the sugar yield rankings between the years contributes to a more effective recommendation of cultivars.

Inheritance and variability of productivity traits in hybrids of spring soft wheat of the first to fourth generations

The effects of genotype-environment interaction of nine spring soft wheat varieties and seven hybrid populations F1 - F4 formed using these varieties were determined under the conditions of the Kirov region. The significant influence of environmental conditions on all studied traits was established. The contribution of the “year” factor to the number of grains per head in varieties and hybrids was 10.9 and 13.9%, respectively; to the mass of 1000 grains – 5.8 and 19.5%; to the yield – 47.3 and 41.1%. The genetic component made a significant contribution to the mass of 1000 grains in varieties and hybrids (81.5 and 58.8%), as well as to the number of grains in varieties (38.4%). There was a higher varietal specificity in the manifestation of traits in parental varieties compared to the hybrids. The analysis was done for two component traits of head productivity in a series of generations against the background of the action of various lim-factors, the shifts in their average values and the influence on yield were predicted and determined. The indicator of phenotypic domination (hp) in the first generation was determined according to the number of grains per head (hp = -5.00...+ 7.82) and 1000 grains mass (hp = + 0.23...+ 12.00), the combinations with a high level of heterosis were picked out (Baganskaya 95 x Novosibirskaya 44 and Baganskaya 95 x Aktjube 3). The calculation of the breeding differential and the effectiveness of the selections in contrasting environmental conditions of the second (2016) and third (2017) hybrid generations was carried out. Under the conditions of 2018, the yield of the initial populations varied within 219.0...789.6 g/m2, while the figures for the selected progenies were 317.0...647.6 g/m2. The average yield increase of the progenies that had been selected in the dry year was 56.8 g/m2 in relation to the initial populations (11.1%); the increase of the progenies, selected in the conditions of excess moisture was 10.8 g/m2 (3.0%). The correlation analysis revealed the average positive relationship between the first-generation hp indicator and the selection differential in subsequent generations according to the «1000 grains mass» (r = 0.18...0.63) and «number of grains per head» (r = 0.35...0.37) traits. The correlation was weak between the level of heterosis and the selection reaction (r = -0.12…0.27). The selection of genotypes with a high level of selection differential according to the number of grains per head was more effective than the selection according to the mass of 1000 grains. The correlation coefficient between the degree of phenotypic dominance of traits in the first generation and average values of traits in the F2-F4 generations varied within r = 0.35...0.68 (significant values at 5% level r = 0.75).

Genotype–environment interaction for age at first calving in buffaloes, using the reaction norm model

The objective of this study was to evaluate the genotype-environment interaction effect on age at first calving in buffaloes. The records were analysed using two approaches: (a) standard animal model and (b) reaction norm model. For the reaction norm analysis, two environmental gradients were formed, using age of first calving or milk yield group contemporary average. The results showed differences in the heritability estimates when using the two approaches. The reaction norm model indicated high heritability in more favourable environments and low magnitude genetic correlations between extreme environments. Based on our findings, we verified the significance of the genotype-environment interaction effect on age at first calving in buffaloes.

Multienvironment and Multitrait Genomic Selection Models in Unbalanced Early‐Generation Wheat Yield Trials

The majority of studies evaluating genomic selection (GS) for plant breeding have used single‐trait, single‐site models that ignore genotype × environment interaction (GEI) effects. However, such studies do not accurately reflect the complexities of many applied breeding programs, and previous papers have found that models that incorporate GEI effects and multiple traits can increase the accuracy of genomic estimated breeding values (GEBVs). This study's goal was to test GS methods for prediction in scenarios that simulate early‐generation yield testing by correcting for field spatial variation, and fitting multienvironment and multitrait models on data for 14 traits of varying heritability evaluated in unbalanced designs across four environments. Corrections for spatial variation increased across‐environment trait heritability by 25%, on average, but had little effect on model predictive ability. Results between all models were generally equivalent when predicting the performance of newly introduced genotypes. However, models incorporating GEI information and multiple traits increased prediction accuracy by up to 9.6% for low‐heritability traits when phenotypic data were sparsely collected across environments. The results suggest that GS models using multiple traits and incorporating GEI effects may best be suited to predicting line performance in new environments when phenotypic data have already been collected across a subset of the total testing environments.

Genotype x Environment Interaction for reproductive traits in brazilian Nellore breed cattle

SUMMARY The objective of this study was to evaluate the effect of the genotype-environment interaction (GEI) for scrotal circumference traits measured at different ages, 365 (SC365), 450 (SC450) and 550 (SC550) days of age, and age at first calving (AFC) for Nellore animals raised in different regions of Brazil. For the evaluation, the herds were grouped in the following regions of the country: North, Southeast and Central-west, using information from 26,619, 28,730, 14,476, 15,397 for the traits SC365, SC450, SC550 and AFC respectively. Genetic parameters, as well as the assessment of GEI were performed using Bayesian inference, using the programs of the BLUPF90. The estimated heritabilities were: 0.465 ± 0.021, 0.500 ± 0.022, 0.492 ± 0.026, 0.117 ± 0.017 for SC365, SC450, SC550 and AFC respectively. The results obtained in the analysis, indicated that this interaction was not significant for SC at different ages (genetic correlation, rg&gt; 0.8). For AFC, significant effect of GEI was observed for combinations involving the Northern region (rg&lt;0.8), indicating that this interaction should be considered by the genetic evaluation programs in this region.

Effect of genotype-environment interaction on grain yield of exotic rice (Oryza sativa L.) hybrids

Genotype by environment interaction (GEI) is a major complication in plant breeding. Authors used additive main effects and multiplicative interaction (AMMI) to evaluate the effects of GEI in hybrid rice genotype and their adaptation in three years at four locations. Among rice hybrid genotypes ACI93024 was stable in all environments with high yield potential. Using AMMI analysis AMMI 1 biplot showed the genotypes HS-273, Heera-2, ACI-2 and HRM-02 were highly stable with moderate yield potential but the genotype ACI93024 was more adapted to a wide range of environment than the rest of the genotypes, while BRRI dhan28 indices the lowest stability. ACI-2, LP-70 and Mayna were specifically adapted to the environment of Rangpur, Jessore and Gazipur, respectively. Comilla was identified as stable environment for all the genotypes.

The effects of environmental and genetic factors on the germination of basidiospores in the Cryptococcus gattii species complex

Natural and artificial hybridization has been frequently reported among divergent lineages within and between the two closely related human pathogenic fungi Cryptococcus gattii species complex and Cryptococcus neoformans species complex. However, the biological effects of such hybridization are not well known. Here we used five strains of the C. neoformans species complex and twelve strains of the C. gattii species complex to investigate the potential effects of selected environmental and genetic factors on the germination of their basidiospores from 29 crosses. We found that the germination rates varied widely among crosses and environmental conditions, ranging from 0% to 98%. Overall, the two examined media showed relatively little difference on spore germination while temperature effects were notable, with the high temperature (37 °C) having an overall deleterious effect on spore germination. Within the C. gattii species complex, one intra-lineage VGIII × VGIII cross had the highest germination rates among all crosses at all six tested environmental conditions. Our analyses indicate significant genetic, environmental, and genotype-environment interaction effects on the germination of basidiospores within the C. gattii species complex.

GENOTYPE BY ENVIRONMENT INTERACTION AND YIELD STABILITY OF SOYBEAN GENOTYPES

&lt;p class="abstrakinggris"&gt;Soybean breeding program in Indonesia has been actively involved in improving the genetic yield potential to meet the needs of farmers in different parts of the country. The study aimed to determine the presence of soybean production mega-environments and to evaluate the yield performance and stability of 12 soybean genotypes. Soybean yield performances were evaluated in eight production centers in Indonesia during 2013 growing season. The experiment in each location was arranged in a randomized complete block design with four replications. Parameters observed included grain yield and yield components. The yield data were analyzed using GGE biplot and the yield components data were analyzed using analysis of variance. The results showed that the yield performances of soybean genotypes were highly influenced by genotype-environment interaction (GEI) effects. The yield components were significantly affected by GEI except per plant branch number. The partitioning of the G + GE sum of squares showed that PC1 and PC2 were significant components which accounted for 57.41% and 18.55% of G + GE sum of squares, respectively. Based on the GGE visual assessment, agro-ecology for soybean production in Indonesia was divided into at least three mega-environments. Genotypes 8 and 2 were the best yielding genotypes in the most discriminating environment, but adapted to specific environment, thus highly recommended for that specific location. Genotypes 9 and 10 were stable and had relatively high yield performances across environments. Those genotypes would be recommended to be proposed as new soybean varieties.&lt;/p&gt;

Models of reaction standards for analysis of effects of interaction genotype environment

The objective of this review was to evaluate the effects of environmental genotype interaction in beef cattle through the use of hierarchical models of one - step and two - step reaction standards, with assumptions of homogeneous and heterogeneous residual variances, comparing the results with the Standard animal assessment model. The hierarchical model of one - step reaction standards presented as the best fit to the data to evaluate the effects of the environmental gradient on the animal genotype, among the reviewed studies. Models of reaction norms can bring significant progress in identifying the effects of genotype environment interaction of different races. Leading to increases in the efficiency of production systems, through reported information, which can assist technicians and producers in the choice of specific genetic materials that meet the particularities of the production systems that are inserted.