Possibilities of Using Morphometrics Characteristics as a Tool for Body Weight Prediction in Turkish Hair Goats (Kilkeci)

2009 ◽  
Vol 5 (1) ◽  
pp. 52-59 ◽  
Author(s):  
M.A. Cam ◽  
M. Olfaz ◽  
E. Soydan
Keyword(s):  
Body Weight ◽  
Weight Prediction

scholarly journals Prediction of Body Weight of a Person Lying on a Smart Mat in Nonrestraint and Unconsciousness Conditions

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3485 ◽  
Author(s):  
Tae-Hwan Kim ◽  
Youn-Sik Hong
Keyword(s):  
Neural Network ◽  
Body Weight ◽  
Evaluation Criteria ◽  
The Body ◽  
Average Error ◽  
Average Weight ◽  
Prototype System ◽  
Grid Structure ◽  
Predict Body Weight ◽  
Weight Prediction

We want to predict body weight while lying in bed for an elderly patient who is unable to move by himself/herself. To this end, we have implemented a prototype system that estimates the body weight of a person lying on a smart mat in nonrestraint and unconsciousness conditions. A total of 128 FSR (force sensing resistor) sensors were placed in a 16 × 8-grid structure on the smart mat. We formulated three methods based on the features to be applied: segmentation, average cumulative sum of pressure, and serialization. All the proposed methods were implemented with four different machine-learning models: regression, deep neural network (DNN), convolutional neural network (CNN), and random forest. We compared their performance using MAE and RMSE as evaluation criteria. From the experimental results, we chose the serialization method with the DNN model as the best model. Despite the limitations of the presence of dead space due to the wide spacing between the sensors and the small dataset, the MAE and the RMSE of the body weight prediction of the proposed method was 4.608 and 5.796, respectively. That is, it showed an average error of ±4.6 kg for the average weight of 72.9 kg.

Living body weight prediction from handprint anthropometry among adult minang ethnic of Indonesia

2020 ◽  
Vol 23 (1and2) ◽  
pp. 26
Author(s):  
Haslinda D Noorhafizah ◽  
Moorthy T Nataraja ◽  
R Revathi ◽  
Henky
Keyword(s):  
Body Weight ◽  
Living Body ◽  
Weight Prediction

scholarly journals Short communication: Verifying Holstein heifer heart girth to body weight prediction equations

2017 ◽  
Vol 100 (10) ◽  
pp. 8451-8454 ◽  
Author(s):  
A.J. Heinrichs ◽  
B.S. Heinrichs ◽  
C.M. Jones ◽  
P.S. Erickson ◽  
K.F. Kalscheur ◽  
...  
Keyword(s):  
Body Weight ◽  
Short Communication ◽  
Prediction Equations ◽  
Weight Prediction

scholarly journals Evaluation of body weight prediction Equations in growing heifers

2017 ◽  
Vol 39 (2) ◽  
pp. 201 ◽  
Author(s):  
Marcia De Oliveira Franco ◽  
Marcos Inácio Marcondes ◽  
José Maurício de Souza Campos ◽  
Denise Ribeiro de Freitas ◽  
Edenio Detmann ◽  
...  
Keyword(s):  
Body Weight ◽  
Prediction Equations ◽  
Weight Prediction

scholarly journals In vivo prediction of live weight and carcass traits using body measurements in indigenous guinea fowl

2012 ◽  
Vol 28 (1) ◽  
pp. 137-146
Author(s):  
D.M. Ogah
Keyword(s):  
Body Weight ◽  
Carcass Traits ◽  
Live Weight ◽  
Guinea Fowl ◽  
Chest Circumference ◽  
Carcass Weight ◽  
Meat Production ◽  
Body Measurements ◽  
Weight Prediction ◽  
Breast Weight

The objectives of this study were to evaluate the relationship between live measurements and carcass traits, and develop linear regression models to predict live weight and set of carcass traits in an indigenous guinea fowl. Twenty eight adult indigenous birds of both sexes were used for the study. Live weight and body measurements were obtained before slaughter while carcass traits were taken on hot carcass. Result obtained from descriptive statistics showed that, mean performance were 1208?6.86g, 22.17?0.13 cm, 8.94?0.07cm, 2.96?0.03cm, 34.23?0.19cm, 850.15?7.18g, 267.23?1.69g, 72.39?0.64g and 70.38% for body weight, body length, thigh length, keel length, chest circumference, carcass weight, breast weight, thigh weight and dressing percentage. All the traits except for keel length were positively (P<0.001) correlated to body weight. Chest circumference had the highest predictive power in live weight estimate (R2.558), while body weight stand out as the single most important variable in carcass weight and breast weight prediction (R2.820 and .902) This suggest that carcass weight and breast weight prediction can best be obtained using body weight, providing direction in developing model for selection and improvement of guinea fowl for meat production.

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