Evaluation of Three Mathematical Functions to Describe the Relationship Between Body Weight, Body Condition and Testicular Dimensions in Yankasa Sheep

Yakubu, Abdulmojeed; Musa-Azara, I.S.

doi:10.4067/s0717-95022013000400036

Cited by 10 publications

(5 citation statements)

References 24 publications

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“…The best fitting models found in our study were also determined to be the best fitting ones in rams in the study by Yakubu and Musa-Azara (2013). For instance, these authors reported estimation of body weight from testicle length and diameter appeared to be better under the cubic model based on higher R 2 values.…”

Section: Gsi Modellingsupporting

confidence: 72%

Age-related linear and nonlinear modelling of semen quality parameters in Miranda donkeys

Martins‐Bessa

Quaresma

Leiva³

et al. 2021

Italian Journal of Animal Science

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In endangered donkey populations, reproductive performance is one the most important areas to study, provided its connection with conservation opportunities. Among reproductive traits, the knowledge on the evolution of seminal qualitative and quantitative parameters may achieve a particular relevance given its implication with improved or more efficient fertility and fecundation chances. The aim of the present study was to model the gonadosomatic index and the quantitative and qualitative seminal parameters along age in Miranda donkeys. Forty semen collections from 8 Miranda donkeys from 2.8 and 21.6 years of age, were fitted to eleven linear and nonlinear models. Cubic function modelling reported the best-fitting properties for almost all variables, except for sperm concentration (exponential model). Cubic model presented a slightly higher ability to capture interindividual variability than less parametrically complex models and more computationally complex models, such as exponential or logarithmic. Senility may course with and larger numbers of abnormal morphology spermatozoa, and also reduced sperm concentration and motility. HIGHLIGHTSTestis reach mature size rapidly which may be ascribed to a breed factor. Age promotes ejaculate volume increase and concentration reduction. Reduced motility may ascribe to increased abnormal morphology spermatozoa. Major age-related changes are linked to testicular functions degeneration.

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Section: Gsi Modellingsupporting

confidence: 72%

Age-related linear and nonlinear modelling of semen quality parameters in Miranda donkeys

Martins‐Bessa

Quaresma

Leiva³

et al. 2021

Italian Journal of Animal Science

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“…Phenotypic correlation between body weight and age (weeks) was computed separately for birds on deep litter and those kept in cages. The relationship between body weight and age was also established using Linear and Quadratic regression models and these were fitted as described in Yakubu and Muza-Azara [18]. The Goodness of fit was determined using the coefficient of determination (R 2 ), adjusted R 2 , mean square error (MSE) and root mean square error (RMSE).…”

Section: Discussionmentioning

confidence: 99%

Modelling Growth Of Dual-purpose Sasso Hens In The Tropics Using Different Algorithms

Yakubu¹,

Madaki²

2017

genetics-molecular-biology

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This study was embarked upon to evaluate body weight (BW) from age (weeks) of Sasso hens in Nasarawa State, Nigeria. A total of one hundred and eight (108) Sasso hens aged 30 weeks were randomly selected from a larger stock kept at the Livestock Farm. Fifty-four of these birds were kept on deep litter while another fifty-four were reared in battery cages. The birds in each system of management were replicated three times with eighteen birds per replicate in a completely randomized design. In both deep litter and battery cage systems, data were collected on weekly body weights of birds from week 31-52 of rearing. Only data from forty (battery cage) and forty-three (deep litter) surviving birds were eventually used for further analyses. Effect of housing system on BW was subjected to T-Test. Phenotypic correlation between body weight (BW) and age of birds was established in both systems of rearing. Linear, Quadratic, Gompertz, Artificial Neural Network (ANN) and the Classification and Regression Tree (CRT) models were used to predict BW from the age (including housing system for CRT model) of birds. There was no significant (P=0.558) difference in the total average weekly BW of birds on deep litter (3.38 ± 0.12 kg) and those in cages (3.37 ± 0.12 kg). The prediction of BW from age was best fitted using the ANN model in both the deep litter (R 2 , adjusted R 2 , RMSE and significance level were 87.0%, 87.0%, 0.04 and 0.000) and battery cage (R 2 , adjusted R 2 , RMSE and significance level were 99.0%, 99.0%, 0.01 and 0.000) systems. The CRT model, however, predicted the optimal BW to be greater than 32.5, but not above 47.5 weeks of age with R 2 value of 93.4%. The present findings may be exploited in mapping out appropriate management practices geared towards increased production.

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“…The findings of this study is also in line with the report of (Cankaya et al, 2014) who noted that cubic regression model gave best values when comparing with other models for the first lactation curve of jersey cows. Yakubu et al, (2013) also reported that cubic model appeared to produce better goodness of fit when traits are considered singly. The result also agreed with the report of Druet et al, (2003) and Silvestre et al, (2006) who used the Wood models and cubic spline regression models for modeling lactation curves.…”

Section: Resultsmentioning

confidence: 94%

Milk yield prediction between Bunaji Holstein Friesian cross bred and Holstein Frisian cows using linear, cubic and quadratic models

2018

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The aim of this study was to compare three different models (Linear, cubic and quadratic) to find best model for predicting milk yield. Data originated from the monthly milk yields records of 251 Bunaji Holstein Friesian crossed and Holstein Friesian cows from 2010 to 2015. The daily milk yield data were regressed against time (day of lactation) for individual cow, using the procedure of SAS, (2002). The resulting polynomial regression coefficients (linear, quadratic and cubic) were then subjected to variance of analysis. All models provided an acceptable level of accuracy in predicting milk yield for Bunaji Holstein Friesian crossed and Holstein Friesian cows, but cubic model is observed to be the most suitable with (R 2) values of (0.659, 0.582, 0.810 and 0.621) followed by quadratic model (0.447, 0.516, 0.614 and 0.605) while linear model has the least R 2 values (0.02, 0.496, 0.548 and 0.309) in all the study farms.

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Evaluation of Three Mathematical Functions to Describe the Relationship Between Body Weight, Body Condition and Testicular Dimensions in Yankasa Sheep

Cited by 10 publications

References 24 publications

Age-related linear and nonlinear modelling of semen quality parameters in Miranda donkeys

Age-related linear and nonlinear modelling of semen quality parameters in Miranda donkeys

Modelling Growth Of Dual-purpose Sasso Hens In The Tropics Using Different Algorithms

Milk yield prediction between Bunaji Holstein Friesian cross bred and Holstein Frisian cows using linear, cubic and quadratic models

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