Relation between swine weight and morphometric measurements

Objective was to define a mathematical model that better explain the relationship of the animals weight depending not only on the animals age but also on the animals morphometric measurements. 40 piglets, half Duroc-Large White blood, were used, 20 males and 20 females, from 3 to 35 days of age (lactation phase) initially weighing 1.518 ± 0.121 kg and from 36 to 66 days of age (calving phase) with a body weight of 7.010 ± 0.704 kg. The animals were weighed weekly on a digital balance. The relationship of animal weight, age and morphometric measurements of male and female piglets were performed using regression models: existing, linear and power. The models were evaluated according to nine criterialinear model was the most adequate to explain the weight of male pigs, while for female pigs was the power. The age of the pig, the shank and palette length, as well as the circumference of the shank jointly explain the weight of the male piglets. The weight of females is explained jointly by age, body length, thorax and hip circumference.


Introduction
Pig farming worldwide is undergoing intense genetic improvement, producing pigs with high growth potential, feed efficiency and good carcass composition (Lima et al., 2018).
Studying growth using a function that describes the entire lifetime of the animal, relating weight and age, has been researched by several authors (Nascimento et al., 2017;Luo et al., 2015).
Studies on growth curves in pig farming relating weight-age have been extensively studied by Luo et al. (2015) and Silva et al. (2013) using logistic model, Nascimento et al. (2017) using the cubic polynomial model and Schinckel et al. (2004) using the quadratic exponential model.
The aforementioned researches, however, did not reach a consensus on which model best explains the pigs weight behavior. Although the use of conventional balance is considered the best way to determine an animal body weight, weight estimation from linear body measurements is gaining space among researchers.
Thus, the objective was to define a mathematical model that better explains the relationship of the animal weight depending not only of age but also of the morphometric measurements.

Methodology
Research had the character of a quantitative study, characterized as experimental research, carried out through techniques of execution and analysis of tests, numerical evaluation and data processing using statistical techniques (Pereira et al., 2018) 40 piglets half-blood Duroc-Large White were used, 20 males and 20 females, from three to 35 days of age (lactation phase) initially weighing 1.518 ± 0.121 kg and from 36 to 66 Research, Society and Development, v. 9, n. 9, e891998013, 2020 (CC BY 4.0) | ISSN 2525-3409 | DOI: http://dx.doi.org/10.33448/rsd-v9i9.8013 4 days of age (brooding phase) with a body weight of 7.010 ± 0.704 kg. The animals were weighed and randomly distributed, by draw, in masonry stalls, keeping one animal per stall.
The animals were housed in an experimental shed with East-West orientation, in stalls measuring 6 m 2 each, with ceramic tile cover and equipped with a masonry feeder and pacifier type water drinker. Feed and water (flow 1,0 L.min -1 ) were given to the piglets at will during the experimental period. The diet provided for the evaluation period was formulated based on corn, soybean meal, vitamin-mineral premix and common salt (Rostagno et al., 2017) (Table 1). The animals were weighed weekly on a digital hook balance with 10g precision. For accuracy during measurement, the animals were restrained using a bag made of fabric that safely supported the entire body of the piglet, attenuating the animals movement during weighing.
Biometric measurements were performed every seven days in order to obtain the following morphometric measurements: body length (BL); thorax circumference (TC); palette length (PL); shank length (SL); shank circumference (SC) and hip circumference (HC) ( Figure 1). The measurements were performed using millimeter tape. The models were evaluated using the model evaluation criteria described in Table 2.
All analyzes were performed using the R-Project version 2.13.1 software.

Results and Discussion
In Figure 2, can be observed that in the evaluation of male pigs, the correlations between all the variables studied are positively correlated (correlation greater than 0.94).  In the evaluation of male pigs, it is noted that in the linear and power models the variables: age of the animal, body length (BL), shank circumference (SC) and palette length (PL) were defined as significant to explain the weight of the animal (Table 3). In the evaluation of the females, verified that in the linear model the variables: age, palette length (PL), shank circumference (SC) and hip (HC) were defined as significant to explain the weight. However, in the power model, the variables: age, body length (BL), thorax circumference (TC) and hip (HC) were the that most explained the animal weight.
The high correlations with live weight indicate that the variables used in the models were sufficient to predict body weight without using a balance, even in very young animals.
High correlation coefficients between body weight and thorax circumference make estimating body weight based on chest circumference an efficient tool. Khanji et al. (2018) estimating the weight of marrãs using an existing model, concluded that the errors are greater than the regression models used in the prediction and explain that more accurate estimates can be obtained when the regression model considers other variables as the physiological state, thoracic perimeter and body length, body score and fat thickness.
According to Vincek et al. (2012), differentiation in the development of different types of tissues (muscle, fat and bone) can be applied with good accuracy to study growth curves in pigs. Walugembe et al. (2014) state that body development can be measured using biometric measurements, being able to predict body weight relatively accurately and correlate them to some carcass characteristics.
Although initially proposed for finishing animals, the research was also carried out on young pigs to predict body weight without using a balance. Assessing linear measurements of piglets at different weaning ages Birteeb et al. (2015) claim that, among linear body measurements, breast circumference is the best predictor of body weight, regardless of the piglets age.
Differences between pig sexes when using measuring tape to evaluate morphometric measurements in farm animals were found by Li et al. (2013), Formenton et al. (2019) and Rahman et al. (2019). The speed of development of a given region of the body advances until reaching the maximum and begins to decrease as the animal phase adulthood. The animals accumulated weight in relation to its age follows a sigmoid curve, composed of a pre-puberty phase of self-acceleration and another post-puberty of deceleration. (Berg & Butterfield, 1976). If there are no food and environmental restrictions, the animal will develop until phase adult weight, following a sigmoidal curve, described by the allometric equation where Y is weight and X the animal age (Sakomura & Rostagno, 2016).
For males verified that, among the seven criteria evaluated, the linear model proved to be more efficient in six. Evaluating the females, verified that the power model presented the best adequacy criteria. The existing model showed the worst model adequacy criteria for both sexes of pigs (Table 4).

Conclusions
The age of the pig, the shank and palette length, as well as the circumference of the shank jointly explain the weight of the male piglets. The weight of females is explained jointly by age, body length, thorax and hip circumference. Biometric variables explain the weight of pigs with high precision power.
To improve the results found, new studies can be used with more morphometric characteristics and their associations with weight of animal.