A SUPERIORITY MEASURE OF CULTIVAR PERFORMANCE FOR CULTIVAR × LOCATION DATA

1988 ◽  
Vol 68 (1) ◽  
pp. 193-198 ◽  
Author(s):  
C. S. LIN ◽  
M. R. BINNS
Keyword(s):  
Maximum Response ◽  
Environment Interaction ◽  
Mean Square ◽  
Screening Process ◽  
Location Data ◽  
Genotype Environment Interaction ◽  
The Mean ◽  
The Difference ◽  
Cultivar Assessment ◽  
Cultivar Responses

A measure of cultivar general superiority for cultivar × location data is defined as the distance mean square between the cultivar’s response and the maximum response averaged over all locations. Since the maximum response is the upper boundary in each location, a small mean square indicates general superiority of the test cultivar. The method requires that all test cultivars be balanced over locations but not necessarily the checks. The advantage of the proposed method are: (i) The checks provide only a plausible maximum response for each location and are not required for assessing the test cultivars. Thus checks do not have to be present in all locations. This allows a greater flexibility for a breeder to choose locally adapted cultivars as checks without unduly increasing the size of a regional trial. (ii) The measure of general superiority consists of only one parameter, thus simplifying the screening process considerably. A subsidiary parameter for interaction can be used to indicate lack of general adaptability. (iii) The difference between the mean of the maximum response averaged over all locations and the mean of the best cultivar provides useful information as to how many cultivars are needed to achieve optimum productivity for the entire region, (iv) The specific adaptability of a cultivar can be identified by plotting the maximum and the test cultivar responses on the location means.Key words: Genotype × environment interaction, cultivar assessment, regional trial

PROCEDURAL APPROACH FOR ASSESSING CULTIVAR-LOCATION DATA: PAIRWISE GENOTYPE-ENVIRONMENT INTERACTIONS OF TEST CULTIVARS WITH CHECKS

1985 ◽  
Vol 65 (4) ◽  
pp. 1065-1071 ◽  
Author(s):  
C. S. LIN ◽  
M. R. BINNS
Keyword(s):  
Simple Procedure ◽  
Trial Data ◽  
Assessment Process ◽  
Environment Interaction ◽  
Cluster Analyses ◽  
Location Data ◽  
Procedural Approach ◽  
Genotype Environment Interaction ◽  
Complementary Nature ◽  
Cultivar Assessment

A simple procedure for assessing cultivar-location data is proposed. The procedure consists of comparisons between checks and each of the test cultivars to find those test cultivars for which comparison with the checks can be done ignoring variability among locations, and to isolate those for which a location-by-location comparison is advisable. Since the level at which a comparison-wise genotype-environment interaction is deemed to be important can be set by the user, this represents a great simplification of the assessment process. A set of regional trial data was used as an example to demonstrate the approach. The complementary nature of this method with cluster analyses which group cultivars or locations is discussed.Key words: Genotype-environment interaction, cultivar assessment, barley yield

scholarly journals On an extension of the stochastic linearization

1993 ◽  
Vol 15 (4) ◽  
pp. 1-6
Author(s):  
Di Paola Mario ◽  
Nguyen Dong Anh
Keyword(s):  
Nonlinear Systems ◽  
Nonlinear Equation ◽  
Random Excitation ◽  
Linearization Method ◽  
Mean Square ◽  
Fundamental Idea ◽  
Stochastic Linearization ◽  
The Mean ◽  
The Difference

Stochastic linearization method is one of the most useful tools for analysis of nonlinear systems under random excitation. The fundamental idea of the classical stochastic linearization consists in replacing the original nonlinear equation by a linear one in such a way that the difference between two equations is minimized in the mean square value. In this paper a new version of the stochastic linearization is proposed. It is shown that for two nonlinear systems considered the new version gives good results for both the weak and strong nonlinearities.

scholarly journals INFLUENCE OF DIFFERENT VERSIONS ARTIFICIAL INSEMINATION OF GILTS OF THEIR TRAITS OF THE REPRODUCTIVE ABILITY CONSOLIDATION

2018 ◽  
Vol 56 ◽  
pp. 130-135
Author(s):  
M. V. Tserenyuk ◽  
O. M. Tserenyuk
Keyword(s):  
Artificial Insemination ◽  
Reproductive Capacity ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Reproductive Ability ◽  
Coefficient Of Variability ◽  
Current Instruction ◽  
The Mean ◽  
The Difference ◽  
The Impact

In addition to assessing the absolute performance of animals, the impact of certain technological approaches, breeding influence and other external organized factors on the consolidation of pigs groups on certain grounds should be evaluated. Breeding consolidation is a desirable breeding process that is realized through more motivated consolidation of intra-breeding structural units for maintaining a significant level of intergroup differentiation and variability. If the issue relates to the rearing young animals that are introduced into the herd, this is the most urgent issue that needs to be monitored. The purpose of the research is to determine the consociality of the main signs of reproductive ability of the gilts, which are checked at different rates of artificial insemination of sows of the main herd. The research was carried out at the Shubs`ke farm in the Bogoduhivsky District of Kharkiv Oblast at the pig farm for the pure breeding of the Welsh breed pigs (breeding reproductive status from 2014). In order to evaluate the optimal multiplicity (from single to triple), a gilts with a total of 30 heads was selected. The main indicators of reproductive ability of gilts (multiplicity, weight of nest at birth and excommunication and keeping piglets before weaning on day 28) were evaluated. Recalculation on the weight of the litter at weaning at the weight of the nest at extermination in 60 days was carried out in accordance with the current instruction on the boning of pigs. The results of researches were worked out according to traditional methods by the method of variation statistics. Consolidation of individual indicators of reproductive capacity of gilts was calculated to the total number of evaluated animals. In the previous stage of the research, it was found that the use of multiple insemination of gilts compared to single insemination is positively reflected at the level of their reproductive ability. A decrease in the percentage of non-productive inseminants in animal groups has been established. Triple insemination of gilts allows for 1.14 piglets to be obtained more compared to single insemination of the same pigs (p < 0.01). Also, for three times insemination of gilts, in comparison with single insemination, larger nest for weaning were obtained (by 14.24 kg, converted to 60th day p < 0.01). At the same time, the reduction in the keeping of piglets to weaning for increase frequency of insemination of gilts. According to the multiplicity of gilts, the most consolidated level of symptoms per group was obtained for single insemination. Increasing the multiplicity of insemination negatively affected the consolidation of the multiplicity of the piglets (as for determining the coefficients of phenotypic consolidation due to the mean square deviation, so, and for determining the coefficient of variability). The least consolidated in terms of multiplicity were uterus for double insemination. It should also be noted that there is little difference, in general, on the indicators of the theonotypical consolidation of the multiplicity of piglets between different groups of animals. So this difference between the most contrasting groups was 0.447 points for determining the coefficients due to the mean square deviation and 0.397 points for the determination due to the coefficient of variability, respectively. By weight of the same litters at birth, the most consolidated group was gilts, which was inseminated twice. The least consolidated are trimmed three times, respectively. The difference as a whole, according to the indicators of the theonotype consolidation of the mass of the litter’s piglets at birth, between different groups of pigs was even smaller. The difference between the most contrasting groups was 0.270 points for determining the coefficients due to the mean square deviation and 0.260 points for the determination due to the coefficient of variability, respectively. On the basis of the mass of the litter at weaning, the most consolidated level of symptoms was obtained in the group of gilts for triple insemination. The least consolidated group, respectively, was gilts for single insemination. At the same time, on the basis of the weight of the litter at weaning, the slightest differences were obtained after the consolidation of the signs between different groups of pigs. The difference between the most contrasting groups was 0.173 points for determining the coefficients due to the mean square deviation and 0.248 points for the determination due to the coefficient of variation, respectively. At different rates of insemination of gilts, there are no significant differences between the groups between the groups in terms of the consolidation of signs of reproductive ability. Also, there was no clear effect on increasing the multiplicity of insemination of gilts to the consolidation of their signs of reproductive qualities.

scholarly journals The nth-order moment of the nuclear charge density and contribution from the neutrons

2019 ◽  
Vol 2019 (11) ◽  
Author(s):  
Haruki Kurasawa ◽  
Toshio Suzuki
Keyword(s):  
Charge Density ◽  
Electron Scattering ◽  
Nuclear Charge ◽  
Order Moment ◽  
Proton Density ◽  
Neutron Density ◽  
Mean Square ◽  
Relativistic Expression ◽  
The Mean ◽  
The Difference

Abstract The relativistic expression for the $n$th-order moment of the nuclear charge density is presented. For the mean square radius (msr) of the nuclear charge density, the non-relativistic expression, which is equivalent to the relativistic one, is also derived consistently up to $1/M^2$ with use of the Foldy–Wouthuysen transformation. The difference between the relativistic and non-relativistic expressions for the msr of the point proton density is also discussed. The $n(\ge 4)$th-order moment of the nuclear charge density depends on the point neutron density. The fourth-order moment yields useful information on the msr of the point neutron density, and is expected to play an important role in electron scattering off neutron-rich nuclei.

scholarly journals Investigation of genotype-environment interaction by cluster analysis in animal experiments

1994 ◽  
Vol 74 (4) ◽  
pp. 607-612 ◽  
Author(s):  
C. Y. Lin ◽  
C. S. Lin
Keyword(s):  
Cluster Analysis ◽  
Key Words ◽  
Animal Experiment ◽  
Animal Experiments ◽  
Environment Interaction ◽  
Mean Square ◽  
Ge Interaction ◽  
Interaction Structure ◽  
Genotype Environment Interaction ◽  
Animal Data

The conventional ANOVA (F ratio of GE interaction mean squares to error mean square) provides a means to test if GE interaction is significant, but it does not tell us which factor levels are significantly different or how they are interacting. To answer the latter question, plant researchers developed a technique to group genotypes for similarity of GE interactions and through the resulting groups to explore the GE interaction structure. The basic idea of the technique is to stratify genotypes (or environments) into subgroups such that GE interactions among genotypes (or environments) are homogeneous within groups but heterogeneous among groups. This technique is introduced in this paper using an animal experiment as an example for illustration. The possibilities and limitations of applying this technique to animal data are also discussed. Key words: Genotype-environment interaction, cluster analysis

scholarly journals Multiattribute Response of Maize Genotypes Tested in Different Coastal Regions of Brazil

2011 ◽  
Vol 2011 ◽  
pp. 1-6
Author(s):  
Lúcio Borges de Araújo ◽  
Mario Varela Nualles ◽  
Mirian Fernandes Carvalho Araújo ◽  
Carlos Tadeu dos Santos Dias
Keyword(s):  
Principal Components ◽  
Environment Interaction ◽  
Coastal Regions ◽  
Multivariate Response ◽  
Genotype Environment Interaction ◽  
Maize Genotypes ◽  
The Mean ◽  
Components Analysis ◽  
And Performance ◽  
Main Effects

This work applies the three mode principal components analysis to analyze simultaneously the multiple attributes; to fit of models with additive main effects and multiplicative interaction effects (AMMI models) and the regressions models on sites (SREG models); to evaluate, respectively, the multivariate response of the genotype × environment interaction and the mean response of 36 genotypes of corn tested in 4 locations in Brazil. The results were presented by joint plots to identify the best genotypes for their adaptability and performance in the set of attributes.

Selecting stable and high-yielding sorghum cultivars for the semi-arid tropics

1994 ◽  
Vol 74 (4) ◽  
pp. 759-762
Author(s):  
O. P. Dangi ◽  
R. I. Hamilton ◽  
C. S. Lin ◽  
D. Andre ◽  
J. J. Johnson
Keyword(s):  
High Yield ◽  
Annual Rainfall ◽  
Environment Interaction ◽  
Mean Square ◽  
Stability Parameters ◽  
The North ◽  
Genotype Environment Interaction ◽  
Northern Cameroon ◽  
The Stability ◽  
Extreme North

A sorghum breeding program was reactivated in 1981 and selected cultivars, along with local checks, were evaluated in two experiments in the sorghum growing region of northern Cameroon. Experiment 1 was conducted in the Extreme North Province where annual rainfall ranges from 450 to 850 mm. Experiment 2 was conducted in the North Province where annual rainfall exceeds 850 mm. The objective of the study was to select a high yield and high stability sorghum cultivar for each region. The cultivar's responses were investigated using two analyses: the adaptability analysis and the stability analysis. The former used the method of superiority measure, defined by distance mean square between the test cultivar and the maximum (the highest yield in the location), and the latter used type 4 stability parameter, defined by the years within location mean square averaged over all locations. The conceptual separation of adaptability and stability facilitated the cultivars assessment. The results showed that in exp. 1, three cultivars S–35, CS–54 and CS–61 had similar adaptability and stability, while in the exp. 2, S–34 was best in terms of yield but was unstable due to susceptibility to grain mold. In contrast, the second best cultivar CS–63 was poorer in the high-yielding environments but was more stable than S–34. Key words: Sorghum, genotype-environment interaction, adaptability, stability parameters

GENOTYPE-ENVIRONMENT INTERACTION VARIANCES IN YIELD TRIALS OF FALL RYE

1970 ◽  
Vol 50 (1) ◽  
pp. 77-80 ◽  
Author(s):  
P. J. KALTSIKES
Keyword(s):  
Genotype By Environment Interaction ◽  
Western Canada ◽  
Environment Interaction ◽  
First Order ◽  
Genotype By Environment ◽  
Genotype Environment Interaction ◽  
Yield Difference ◽  
The Mean ◽  
Yield Trials ◽  
Interaction Variance

Estimates of genotype by environment interaction variances were obtained from the western Canada Co-operative fall rye tests grown in 1963–1967. All first-order interactions and the second-order interactions were significantly greater than zero at the 0.05 level of probability. Although the estimate of cultivar by year interaction variance was relatively small, it accounted for 40% of the variance of a cultivar mean when only three years of testing were considered. However, testing in 20 locations for three years with four replicates could detect yield differences of approximately 10% of the mean of the highest yielding cultivar. If further reduction of the yield difference detectable is desired, more locations should be included in the test.

Yield Stability of Different Elite Wheat Lines under Drought and Irrigated Environments using AMMI and GGE Biplots

2021 ◽  
Vol 9 (2) ◽  
pp. 98-106
Author(s):  
Dipendra Regmi ◽  
Mukti Ram Poudel ◽  
Bishwas K.C. ◽  
Padam Bahadur Poudel
Keyword(s):  
Principal Component ◽  
Environment Interaction ◽  
Lattice Design ◽  
Genotype Environment Interaction ◽  
Stability Model ◽  
Winter Crop ◽  
Ideal Line ◽  
Genotype Evaluation ◽  
The Mean ◽  
Wheat Lines

Wheat is the principal winter crop in Nepal. Drought affects 44% of the lands of the total wheat area in the country with a yield loss of 15–20%. This research focuses to minimize this loss through the identification of high-yielding lines stable across the drought stress and irrigated environments. The experiment was conducted in Alpha Lattice Design with 20 genotypes replicated twice with five blocks per replication from November 2019 to April 2020. The findings showed that genotypes, environments, and genotype-environment interaction have a highly significant effect on grain yield and explained 28.95%, 52.57%, and 18.47% of variation on yield, respectively. The which-won-where model revealed elite line NL 1420 is the most responsive line in the drought environment, followed by BL 4407, while elite line NL 1179 is the most stable line in irrigated environment. The mean vs stability model with principal component 1 and 2 explaining 65.76% and 34.24% respectively, showed that elite line NL 1420, BL 4407, BL 4919, Bhrikuti are both high yielding and stable lines while line NL 1179, Gautam, and NL 1384 are less stable in both test environments. Similarly, the ranking genotypes model indicated lines close to the ideal line are NL 1420, BL 4407, BL 4919, Bhrikuti as the most representative line for genotype evaluation. Thus, elite wheat line NL 1420 and NL 1179 are recommended as specifically adapted to drought and irrigated environments, respectively, and elite line NL 1420, BL 4407, BL 4919, Bhrikuti are recommended for further evaluation for stability. Int. J. Appl. Sci. Biotechnol. Vol 9(2): 98-106

scholarly journals Genotype × environment interaction in Tribolium castaneum

1964 ◽  
Vol 5 (3) ◽  
pp. 335-340 ◽  
Author(s):  
J. F. Kidwell ◽  
A. E. Freeman ◽  
L. H. Haverland ◽  
G. M. H. Rolfes
Keyword(s):  
Relative Humidity ◽  
Tribolium Castaneum ◽  
Total Variance ◽  
Direct Selection ◽  
Environment Interaction ◽  
Breeding Values ◽  
Genotype Environment Interaction ◽  
The Mean ◽  
Selection For ◽  
C 30

An experiment was conducted with the flour beetle, Tribolium castaneum to investigate genotype-environment interaction. Ninety-two matings of one male and three females were made at random from a large panmictic population. The females were transferred to individual containers after 4 days. Six daughters were randomly selected from each sire–dam pair and individually mated to unrelated males. Three of the six were placed in an incubator (33·3°C., 45% relative humidity) and three in a cabinet at room conditions (22·2–26·7°C., 30–35% relative humidity) and allowed to produce eggs during a 3-day period. Progeny were counted as pupae and larvae. The traits studied were number of pupae and number of pupae plus number of larvae. A transformation to (X +1)½ was required. A conventional least-squares model was employed, and a large environmental effect was observed. In the incubator the mean number of pupae was 13·4 and of pupae + larvae was 20·1 while the corresponding figures for room conditions were 3·3 and 9·2. Genotype-environment interaction accounted for 3·7 to 6·7% of the total variance for (pupae + 1)½ and 2·1 to 8·3% for (pupae + larvae+ 1)½. Heritability of the traits was essentially the same in both environments. The interaction was due to an increasing difference between environments in production associated with increasing breeding values of the sire, and to small changes in rank of breeding values on the two environments. As a result of the interaction, selection in one environment for production on the other would be expected to be only 71 to 72% as effective as direct selection for (pupae + 1)½ and 62 to 86% for (pupae + larvae + 1)½ even though the fraction of the total variance attributed to genotype-environmental interaction was less than 10%.

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