Fisher's Linear Discriminant Function Research Articles

DISCRIMINANT FACTORS IN THE CHOICES OF TEA PLANT CULTIVARS AMONG SMALLHOLDERS IN BADULLA DISTRICT: MULTIPLE DISCRIMINANT ANALYSIS

This study employed multiple discriminant analysis to examine whether significant differences exist among the different group of tea smallholders in terms of their demographic and farming characteristics and to identify the significant factors influencing in the selection of different tea plant cultivars in Badulla district. The data were collected during the period November to December in 2019 and a sample of 108 tea smallholders has been randomly selected from three major tea producing regions namely Badulla, Haliela and Bandarawela divisions of the Uva region in the district. Frequency analysis reveals that, 43.5% of the tea smallholders chose VP 20/25 while 29.6% and 26.9% of them chose VP 20/23 and CY 9 cultivars respectively. Multiple discriminant analysis showed that, output from each tea plant cultivars and prices of each tea cultivar were the major discriminating variables as well as important influencing factors in selecting tea plant cultivars. Results of Fisher's linear discriminant functions revealed that as output increases, tea small holders are more likely to choose the cultivars VP20/25 and VP20/23 while less likely to select the CY9 cultivar. Similarly, as the price of the tea cultivar increases, they are more likely to adopt the CY9 cultivar than other two in the study. The classification results revealed that 56% of the respondents were correctly classified into three different groups of tea smallholders and the estimated discriminant functions for CY9 (96.6%) and VP 20/23(62.5%) were classified with better accuracy than another group in the study. The findings of the study may assist the tea smallholders in understanding the critical factors in the selection of tea plant cultivars and guide the policymakers to take effective measures in the tea sector in the future.
 
 Keywords: Choices of Tea Plant Cultivars, Demographic and Farming Characteristics, Fisher's Linear Discriminant Functions, Multiple Discriminant Analysis, Tea Smallholders

Biomarkers of coagulation, endothelial function, and fibrinolysis in critically ill patients with COVID‐19: A single‐center prospective longitudinal study

BackgroundImmunothrombosis and coagulopathy in the lung microvasculature may lead to lung injury and disease progression in coronavirus disease 2019 (COVID‐19). We aim to identify biomarkers of coagulation, endothelial function, and fibrinolysis that are associated with disease severity and may have prognostic potential. MethodsWe performed a single‐center prospective study of 14 adult COVID‐19(+) intensive care unit patients who were age‐ and sex‐matched to 14 COVID‐19(−) intensive care unit patients, and healthy controls. Daily blood draws, clinical data, and patient characteristics were collected. Baseline values for 10 biomarkers of interest were compared between the three groups, and visualized using Fisher's linear discriminant function. Linear repeated‐measures mixed models were used to screen biomarkers for associations with mortality. Selected biomarkers were further explored and entered into an unsupervised longitudinal clustering machine learning algorithm to identify trends and targets that may be used for future predictive modelling efforts. ResultsElevated D‐dimer was the strongest contributor in distinguishing COVID‐19 status; however, D‐dimer was not associated with survival. Variable selection identified clot lysis time, and antigen levels of soluble thrombomodulin (sTM), plasminogen activator inhibitor‐1 (PAI‐1), and plasminogen as biomarkers associated with death. Longitudinal multivariate k‐means clustering on these biomarkers alone identified two clusters of COVID‐19(+) patients: low (30%) and high (100%) mortality groups. Biomarker trajectories that characterized the high mortality cluster were higher clot lysis times (inhibited fibrinolysis), higher sTM and PAI‐1 levels, and lower plasminogen levels. ConclusionsLongitudinal trajectories of clot lysis time, sTM, PAI‐1, and plasminogen may have predictive ability for mortality in COVID‐19.

Study on Discrimination Model of Water Inrush Source in Binhuang Mining Area of China

Groundwater flow into the mine by coal mining, which threatens the safety of coal mine. Therefore, it is necessary to identify the source of the water flowing into the coal mine. Taking binhuang mining area in Shaanxi Province as the research background, the discrimination models of six water inrush sources had been studied. The composition of 256 water samples was determined and the water quality characteristics of 6 water sources were analyzed. Fisher linear discriminant function model was established by selecting 9 indexes of water quality components. By testing the discriminant effect, it is considered that the probability of K1L aquifer misjudging as Q aquifer and surface water is high, and the misjudgment rate is 30.4%. Combined with the analysis of geological conditions, it is considered that K1L aquifer has a good hydraulic connection with Q aquifer and surface water. Aiming at the problem of misjudgment, the neural network analysis model is used, and the misjudgment rate is reduced to 0%.

Combined application of MRS and DWI can effectively predict cell proliferation and assess the grade of glioma: A prospective study

In order to assess combined application of MRS and DWI for prediction cell proliferation and grade diagnosis of glioma, We prospectively collected the Cho/Cr, Cho/NAA, Cr/NAA of MRS and tumor parenchyma ADC (ADCT), contralateral mirror brain tissue ADC (ADCH), rADC (rADC = ADCT/ADCH). According to postoperative pathology, the patients were divided into two groups: LGG group and HGG group, compared differences of age, gender, Ki67, MRS, DWI between two groups. Next, we analyzed the correlation between MRS, DWI and Ki67. On this basis, the sensitivity and specificity of MRS, DWI and MRS combined with DWI (MRS + DWI) in diagnosis of glioma grade were evaluated. The differences of Ki67, Cho/Cr, Cho/NAA, Cr/NAA, ADCT, rADC between LGG group and HGG group were statistically significant (p = 0.000, 0.000, 0.000, 0.008, 0.000, and 0.000 respectively). From ROC curve, area under the curve (AUC), sensitivity and specificity of Cho/Cr, Cho/NAA, Cr/NAA, ADCT, rADC, PRE (MRS + DWI) were (0.901, 86.7%, 85.7%), (0.876, 80.0%, 82.1%), (0.704, 63.3%, 71.4%), (0.862, 82.1%, 83.3%), (0.820, 75.0%, 76.7%), (0.920, 86.7%, 89.3%), respectively. Fisher's linear discriminant functions results suggest: Y1 = -20.447 + 3.46•X1 + 17.141•X2 (LGG), Y2 = -19.415 + 4.828•X1 + 14.543•X2 (HGG). Our study suggested that MRS and DWI can effectively predict cell proliferation preoperative. MRS combined with DWI can further improve sensitivity and specificity in assessing the grade of glioma.

Three Group Classification Problem Approach Based on Fuzzy Goal Programming

In this study, a new fuzzy logic and mathematical programming based model was proposed to solve three-group classification problem. Determination of cut-off value, which corresponds to discrimination axis in classification problems, has importance. Status of the cut-off value such as asymmetric triangle fuzzy number, trapezoid fuzzy number and gauss fuzzy number was examined. The proposed approach displayed better performance when compared to Fisher's Linear Discriminant Function and some mathematical programming-based models by using three group data sets used frequently in the literature.

Discrimination and Classification model from Multivariate Exponential Power Distribution

It is common to assume a normal distribution when discriminating and classifying a multivariate data based on some attributes. But when such data is lighter or heavier in both tails than the normal distribution, then the probability of misclassification becomes higher giving unreliable result. This study proposed multivariate exponential power distribution a family of elliptically contoured model as underlining model for discrimination and classification. The distribution has a shape parameter which regulate the tail of the symmetric distribution to mitigate the problem of both lighter and heavier tails data, this generalizes the normal distribution and thus will definitely gives a lower misclassification error in discrimination and classification. The resulting discriminant model was compared with fisher linear discriminant function when applying to real data.

Multifunctional discriminant analysis of morphostructural traits in Nigerian locally adapted turkeys

Abstract Association among biometric traits and characterisation based on sexed-plumage colour of Nigerian locally adapted turkey were investigated using discriminant analysis. Eight morphometric traits were measured to study their phenotypic variations between two plumage colours (Lavender and White). The characters measured were body weight (BW) as well as body dimensions such as wing length (WL), wing span (WS), body length (BL), breast girth (BG), shank length (SL), thigh length (TL) and keel length (KL) taken at 12 weeks of age. The White male turkey was significantly (P < 0.05) heavier and had longer morphometric body traits than its female counterpart, but when compared with the Lavender male and female genotype, the traits did not differ significantly (P > 0.05). High positive and significant (P < 0.05) correlation coefficients were recorded among the various body traits. Coefficients of correlation in Lavender turkey ranged from 0.73 – 0.94, and 0.84 – 0.96 in the White turkey. The highest association with body weight in Lavender was body length (r = 0.80, P < 0.05), and the trio of BW, TL and KL had the stronger association for the White turkey (r = 0.91, P < 0.05). The first, second and third canonical variable or Fisher linear discriminant function explained 52.13 %, 37.48 % and 10.39 %, respectively, of the total variation. The distances between all pair wise were significant (P < 0.05). The greatest distance value (415.16) was between the White male and female turkeys, closely followed by the male White and female Lavender turkey (303.58), while the least distance was between the male and female Lavender. The distance between the populations was significant. It can be concluded that thigh length, breast girth, wing length, wing span and body length can serve as the most discriminating variables in distinguishing between White and Lavender populations.

Classification and Prediction of Student’s GPA using Fisher Linear Discriminant (FLD) Function

Classification and Prediction of Student’s GPA using Fisher Linear Discriminant (FLD) Function

Chemical characterization, fatty acid profile and antioxidant activity of <em>Gustavia macarenensis</em> fruit mesocarp and its oil from the Amazonian region of Ecuador as an unconventional source of vegetable oil

To our knowledge, this study is the first to report on the nutritional characterization, bioactive compounds and antioxidant activity of Amazonian G. macarenensis fruit. The fatty acid profile was determined using a high performance liquid chromatography analysis. The total phenolic content and antioxidant activity were determined using Folin Ciocalteu’s method and by radical scavenging activity, respectively. Moreover, a cluster analysis was carried out in order to classify the G. macarenensis fruit oil according to its fatty acid profile. Seven Fisher linear discriminant functions were obtained from the discriminant analysis. These models allow one to classify new fruits on the basis of their fatty acid profile. A high value for total lipids was obtained (53.57%). Its main components were palmitic and oleic acid. The TPC value (156.49 ± 2.62 mg GAE/Kg of oil) obtained from the G. macarenensis fruit pulp oil is higher than what was reported for some olive oil and Brazilian mango oil varieties.

Three-Dimensional Analysis of Mandibular Angle Classification and Aesthetic Evaluation of the Lower Face in Chinese Female Adults.

Reduction gonioplasty is very popular in East Asia. However, there has been little quantitative criteria for mandibular angle classification or aesthetics. The aim of this study was to investigate the quantitative differences of mandibular angle types and determine the morphologic features of mandibular angle in attractive women. We created a database of skull computed tomography and standardized frontal and lateral photographs of 96 Chinese female adults. Mandibular angle was classified into 3 groups, namely, extraversion, introversion, and healthy group, based on the position of gonion. We used a 5-point Likert scale to quantify attractiveness based on photographs. Those who scored 4 or higher were defined as attractive women. Three types of computed tomography measurements of the mandible were taken, including 4 distances, 4 angles, and 3 proportions. Discriminant analysis was applied to establish a mathematic model for mandibular angle aesthetics evaluation. Significant differences were observed between the different types of mandibular angle in lower facial width (Gol-Gor), mandibular angle (Co-Go-Me), and gonion divergence angle (Gol-Me-Gor) (P < 0.01). Chinese attractive women had a mandibular angle of 123.913 ± 2.989 degrees, a FH-MP of 27.033 ± 2.695 degrees, and a Go-Me/Co-Go index of 2.0. The "healthy" women had a mandibular angle of 116.402 ± 5.373 degrees, a FH-MP of 19.556 ± 5.999 degrees, and a Go-Me/Co-Go index of 1.6. The estimated Fisher linear discriminant function for the identification of attractive women was as follows: Y = -0.1516X1(Co-Go) + 0.128X2(Go-Me) + 0.04936X3(Co-Go-Me) +0.0218X4(FH-MP). Our study quantified the differences of mandibular angle types and identified the morphological features of mandibular angle in attractive Chinese female adults. Our results could assist plastic surgeons in presurgical designing of new aesthetic gonion and help to evaluate lower face aesthetics.

Development of Tianma HPLC fingerprint and discriminant analysis

Tianma(the tuber of Gastrodia eleta) is a widely used and pricy Chinese herb. Its counterfeits are often found in herbal markets, which are the plant materials with similar macroscopic characteristics of Tianma. Moreover, the prices of Winter Tianma(cultivated Tianma) and Spring Tianma(mostly wild Tianma) have significant difference. However, it is difficult to identify the true or false, good or bad quality of Tianma samples. Thus, a total of 48 Tianma samples with different characteristics(including Winter Tianma, Spring Tianma, slice, powder, etc.) and 9 plant species 10 samples of Tianma counterfeits were collected and analyzed by HPLC-DAD-MS techniques. After optimizing the procedure of sample preparation, chromatographic and mass-spectral conditions, the HPLC chromatograms of all those samples were collected and compared. The similarities and Fisher discriminant analysis were further conducted between the HPLC chromatograms of Tianma and counterfeit, Winter Tianma and Spring Tianma. The results showed the HPLC chromatograms of 48 Tianma samples were similar at the correlation coefficient more than 0.848(n=48). Their mean chromatogram was simulated and used as Tianma HPLC fingerprint. There were 11 common peaks on the HPLC chromatograms of Tianma, in which 6 main peaks were chosen as characteristic peaks and identified as gastrodin, p-hydroxybenzyl alcohol, parishin A, parishin B, parishin C, parishin E, respectively by comparison of the retention time, UV and MS data with those of standard chemical compounds. All the six chemical compounds are bioactive in Tianma. However, the HPLC chromatograms of the 10 counterfeit samples were significantly different from Tianma fingerprint. The correlation coefficients between HPLC fingerprints of Tianma with the HPLC chromatograms of counterfeits were less than 0.042 and the characteristic peaks were not observed on the HPLC chromatograms of these counterfeit samples. It indicated the true or false Tianma can be identified by either the similarity or characteristic peaks on HPLC fingerprint. Comparing the Winter Tianma with Spring Tianma showed that the HPLC chromatograms of 15 winter Tianma samples and 11 spring Tianma samples were similar at the mean correlation coefficient of 0.908. But the intensity of the characteristic peaks were different between the two groups of Tianma samples, i.e. the intensity of gastrodin, paishin A and C in winter Tianma was lower than those in spring Tianma. The Winter Tianma and Spring Tianma could be discriminated by either the Fisher unstandardized discrimination function or Linear discriminant function, based on the peak areas of 11 common peaks on HPLC chromatograms as variate.

Sedimentary environment of vermicular red clay in South China

Increasing interest in recent years has focused on vermicular red clay (VRC) in southern China due to its controversial sedimentary environment and provenance. Grain size is a useful way to determine sedimentary environment and provenance. Fisher Linear Discriminant Analysis (LDA) is a common and widely used method for multivariate statistical analysis. Based on a proper training sample set, the LDA can be used to discuss the sediment provenance. In this study, grain size data for 77 Malan loess samples and 41 floodplain deposit samples were used as a training sample set to deduce a Fisher linear discriminant function. Then, 299 VRC samples from 6 Quaternary red clay profiles were analyzed using the discriminant function. Grain size parameters and microscopic images of quartz grains separated from the VRC were evaluated in detail to determine the VRC sedimentary environment in south China. The results show that VRC profiles can be classified into two regions: the Chiang-nan Hilly Region and Wuyi Mountains Region. The VRC samples in the Chiang-nan Hilly Region originated from eolian dust deposits. This VRC is characterized by a higher content of fine particles (<20 μm) and lower average transport kinetic energy than loess in a C-M plot. The quartz grain sizes and microscope images of this VRC suggest that it could be a polyphyletic mixture of far-sourced and near-sourced eolian deposits. The far-sourced eolian deposits share similar provenance with Xiashu loess and were transported by the East Asian winter monsoon. The near-sourced eolian deposits were dust emitted from the adjacent floodplain. In the Wuyi Mountains Region, the rugged topography weakened the dustfall and strengthened the reconstructive effect of hydrodynamic forces during the Quaternary glacial periods. The VRC in this region was reworked strongly by water and retained typical hydraulic characteristics no matter the source.

Comparative morphometric characters of gladiator swimming crab Callinectes pallidus (Rochebrune, 1883) (Crustacea: Decapoda) from two coastal areas in Lagos Southwest Nigeria

The present study compared the morphometric characters of Callinectes pallidus (Rochebrune, 1883) (Crustacea: Decapoda) collected from two coastal areas in Lagos, Nigeria, as a measure of investigating the degree of susceptibility of the species to environmental stress. Thirteen different morphometric characters (distances) which included eye cavity length (ECL), inter-orbital distance (IOD), medial peduncle width (MPW), carapace total length (CTL), carapace total width (CTW), carapace final width (CFW), width of the joining between the propodus and the movable chela thigh (PCT), chela dactylus length (CDL), first movable chela width (FMW), 2nd, 3rd and 4th pereiopod merus width (PMW), merus length (ML), abdomen total length (ATL) and abdomen first suture width (AFW) were measured with precision calliper with an accuracy of 0.01 mm. Differences in mean morphometric distance were tested with T-test and Z-test while the standardized values were examined with fisher's linear discriminant function. 12 morphometric characters except MPW showed a significance different (p &lt; 0.05) for male crabs between the sites while FMW only indicated no sites differences (p &gt; 0.05) in female crabs examined. All the statistical tools employed clearly shown a great distinction in the growth of the crabs across the two sites. Therefore, this preliminary study concluded that C. pallidus from site 2 (Agbara) are more susceptible to environmental stress. However, further research is required to identify these environmental stressors.

&lt;b&gt;Image analysis of coffee seeds submitted to the LERCAFE test

The aim of this experiment was to quantify the stained areas of coffee seeds submitted to the LERCAFE test using image analysis. The seeds used were of the Catuai Vermelho IAC 99 and Paradise cultivars. The physiological quality of the lots was assessed using germination tests, moisture content and a germination speed index. The LERCAFE test was conducted using seeds without parchment immersed in a solution of 3% sodium hypochlorite for 3 hours. Color photographs (RGB) with a resolution of 5 MPx were taken of each seed. The seeds were visually evaluated, and the functions generated from the analyses of the stained and non-stained regions were quantified by the Matlab R2009b program. Classification models were developed based on the Fisher Linear Discriminant Function and the evaluation of the adequacy of the models confusion matrix between the visual references and the classification generated by the linear functions. The image analysis for the creation of Fisher's linear discriminant function in the development of classifiers for the coffee seeds submitted to the LERCAFE test is potentially efficient; however, it remains necessary to test other discriminant functions and quantification methodologies.

Discriminant analysis for the prediction of sand mass distribution in an urban stormwater holding pond using simulated depth average flow velocity data.

The approach of this paper is to predict the sand mass distribution in an urban stormwater holding pond at the Stormwater Management And Road Tunnel (SMART) Control Centre, Malaysia, using simulated depth average floodwater velocity diverted into the holding during storm events. Discriminant analysis (DA) was applied to derive the classification function to spatially distinguish areas of relatively high and low sand mass compositions based on the simulated water velocity variations at corresponding locations of gravimetrically measured sand mass composition of surface sediment samples. Three inflow parameter values, 16, 40 and 80 m(3) s(-1), representing diverted floodwater discharge for three storm event conditions were fixed as input parameters of the hydrodynamic model. The sand (grain size > 0.063 mm) mass composition of the surface sediment measured at 29 sampling locations ranges from 3.7 to 45.5%. The sampling locations of the surface sediment were spatially clustered into two groups based on the sand mass composition. The sand mass composition of group 1 is relatively lower (3.69 to 12.20%) compared to group 2 (16.90 to 45.55%). Two Fisher's linear discriminant functions, F 1 and F 2, were generated to predict areas; both consist of relatively higher and lower sand mass compositions based on the relationship between the simulated flow velocity and the measured surface sand composition at corresponding sampling locations. F 1 = -9.405 + 4232.119 × A - 1795.805 × B + 281.224 × C, and F 2 = -2.842 + 2725.137 × A - 1307.688 × B + 231.353 × C. A, B and C represent the simulated flow velocity generated by inflow parameter values of 16, 40 and 80 m(3) s(-1), respectively. The model correctly predicts 88.9 and 100.0% of sampling locations consisting of relatively high and low sand mass percentages, respectively, with the cross-validated classification showing that, overall, 82.8% are correctly classified. The model predicts that 31.4% of the model domain areas consist of high-sand mass composition areas and the remaining 68.6% comprise low-sand mass composition areas.

On discrimination procedure with mixtures of continuous and categorical variables

ABSTRACTA discrimination procedure, based on the location model is described and suggested for use in situation where the discriminating variables are mixtures of continuous and binary variables. Some procedures that have been previously employed, in a similar situation, like Fisher's linear discriminant function and the logistic regression were compared with this method using error rate (ER). Optimal ERs for these procedures are reported using real and simulated data for the case of varying sample size and number of continuous and binary variables and were used as a measure for assessing the performance of the various procedures. The suggested procedure performed considerably better in the cases considered and never did produce a result that is poor when compared with other procedures. Hence, the suggested procedure might be considered for such situations.

Alternative for the evaluation of coffee seedlings using Fisher's discriminant analysis

One of the applications of Fisher's linear discriminant function (FDF) is its use in transforming multivariate data into a new univariate variable. This then makes possible a new option for the variance analysis of multivariate data, in addition to the multivariate analysis of variance (MANOVA). The aim of this work was to select groups of seven characteristics of quality in coffee seedlings using six criteria for selection, to use the FDF to transform such groupings of characteristics into a new variable, and then to compare interpretation of the results obtained from the univariate and multivariate analyses of variance of the characteristics and this new variable, with a view to its use in evaluating coffee seedlings. A randomised block design was used to assess the effect of organic fertiliser on the formation of seedlings in coffee cv. Catuai Vermelho IAC-44, evaluating the following characteristics: seedling height, diameter, root length, dry weight of shoots and roots, leaf area, number of leaves and total dry weight. According to the selection criteria used, different subsets of the selected characteristics are possible. The use of the FDF is shown to be viable in discriminating between treatments. Univariate analysis of the new variable obtained with the FDF and multivariate analysis (MANOVA) was able to detect differences between the treatments, however, it is simpler to apply FDF methodology.

Sex Determination by Computerized Tomographic Study of Foramen Magnum in Adults

Skeletal remains in the identification of sex have been used for long period. Skull is considered second best, after pelvis in determination of sex. Methods based on morphological characteristics and morphometry have been in use with good accuracy. The standardized radiographic techniques have advantage over morphological methods being calculable and reproducible. The objective of the study was to obtain the reliability of foramen magnum parameters in sex estimation and to test the accuracy of the radiological method adopted. A total of 105 (55 male & 50 female) Three dimensional axial skull base images from the North Karnataka population were selected. Using Fisher's linear discriminant functions test, three parameters namely, the length of left condyle (LLC), width of foramen magnum (WFM) and maximum bicondylar diameter (MBD) emerged to be statistically significant in each sex (p< 0.05) with an overall accuracy of 70.48%, in sex prediction.

A Trivial Linear Discriminant Function

In this paper, we focus on the new model selection procedure of the discriminant analysis. Combining re-sampling technique with k-fold cross validation, we develop a k-fold cross validation for small sample method. By this breakthrough, we obtain the mean error rate in the validation samples (M2) and the 95\% confidence interval (CI) of discriminant coefficient. Moreover, we propose the model selection procedure in which the model having a minimum M2 was chosen to the best model. We apply this new method and procedure to the pass/ fail determination of exam scores. In this case, we fix the constant =1 for seven linear discriminant functions (LDFs) and several good results were obtained as follows: 1) M2 of Fisher's LDF are over 4.6\% worse than Revised IP-OLDF. 2) A soft-margin SVM for penalty c=1 (SVM1) is worse than another mathematical programming (MP) based LDFs and logistic regression . 3) The 95\% CI of the best discriminant coefficients was obtained. Seven LDFs except for Fisher's LDF are almost the same as a trivial LDF for the linear separable model. Furthermore, if we choose the median of the coefficient of seven LDFs except for Fisher's LDF, those are almost the same as the trivial LDF for the linear separable model.

Genetic divergence between genotypes for male and female broilers

ABSTRACT: The aim of this study was to verify the genetic divergence amongst three broiler genotype, from both sexes, by means of a multivariate performance analysis and carcass traits. Nine hundred and ninety sexed, one-day chicks were utilized; belonged to the following genetic groups: Cobb 500, Hubbard Flex, and Ross 308. The study evaluated the daily average weight gain, the daily average ration consumption, feed conversion, body weight, weight and performance for breast, and carcass over the period from 1 to 35, and from 1 to 42 days of age. Performance of the genetic groups was evaluated by means of multivariate analysis of variance and by Fisher's linear discriminant function, using Roy's largest eigenvalue and Roy's union-intersection test for multiple comparisons. The genetic divergence study was carried out through the analysis of canonical variables and through Tocher method. Female animals from Cobb 500, Hubbard Flex, and Ross 308 genetic groups presented different canonical averages from males of the same groups. First two canonical variables explained 88.10% of variation between genetic groups. Genetic divergence between the evaluated groups allowed formation of two clusters with the following genotypes: Cluster 1 - Cobb 500, Hubbard Flex and Ross 308 females; Cluster 2 - Cobb 500, Hubbard Flex and Ross 308 males.