Achieving Body Weight Adjustments for Feeding Status and Pregnant or Non-Pregnant Condition in Beef Cows

<div><p>Background</p><p>Beef cows herd accounts for 70% of the total energy used in the beef production system. However, there are still limited studies regarding improvement of production efficiency in this category, mainly in developing countries and in tropical areas. One of the limiting factors is the difficulty to obtain reliable estimates of weight variation in mature cows. This occurs due to the interaction of weight of maternal tissues with specific physiological stages such as pregnancy. Moreover, variation in gastrointestinal contents due to feeding status in ruminant animals is a major source of error in body weight measurements.</p><p>Objectives</p><p>Develop approaches to estimate the individual proportion of weight from maternal tissues and from gestation in pregnant cows, adjusting for feeding status and stage of gestation.</p><p>Methods and Findings</p><p>Dataset of 49 multiparous non-lactating Nellore cows (32 pregnant and 17 non-pregnant) were used. To establish the relationships between the body weight, depending on the feeding status of pregnant and non-pregnant cows as a function of days of pregnancy, a set of general equations was tested, based on theoretical suppositions. We proposed the concept of pregnant compound (PREG), which represents the weight that is genuinely related to pregnancy. The PREG includes the gravid uterus minus the non-pregnant uterus plus the accretion in udder related to pregnancy. There was no accretion in udder weight up to 238 days of pregnancy. By subtracting the PREG from live weight of a pregnant cow, we obtained estimates of the weight of only maternal tissues in pregnant cows. Non-linear functions were adjusted to estimate the relationship between fasted, non-fasted and empty body weight, for pregnant and non-pregnant cows.</p><p>Conclusions</p><p>Our results allow for estimating the actual live weight of pregnant cows and their body constituents, and subsequent comparison as a function of days of gestation and feeding status.</p></div

Relationship among non-pregnant shrunk body weight and non-pregnant empty body weight in Nellore cows.

<p>The continuous line represents the estimation of non-pregnant empty body weight from non-pregnant shrunk body weight using <<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112111#pone.0112111.e019" target="_blank">Equation 16</a>>.</p

Set of general theoretical assumptions used to establish cows BW adjustments.

<p>Set of general theoretical assumptions used to establish cows BW adjustments.</p

Ingredients and chemical composition of the diet.

<p>¹Zinc sulfate (56.3%), manganese sulfate (26.2%), copper sulfate (16.8%), potassium iodate (0.37%), cobalt sulfate (0.23%) and sodium selenite (0.10%).</p><p>²NDF_ap = neutral detergent fiber corrected to ash and protein, iNDF = indigestible neutral detergent fiber and NFC = non fibrous carbohydrates.</p><p>Ingredients and chemical composition of the diet.</p

Relationship between days of pregnancy and weight of fresh udder in Nellore cows.

<p>The continuous line represents the estimation of the weight of fresh udder for a cow with the average shrunk body weight and body condition score (494 kg and 5.6, respectively) of the cows used in this study.</p

Summary of cross-validation statistics from the predictive models generated.

<p>¹SBW = shrunk body weight, GU = gravid uterus, UT_np = uterus of the cow in non-pregnant condition, UD_np = udder of the cow in non-pregnant condition, EBW = empty body weight.</p><p>²SD = standard error, RMSE = root mean square of error, MAE = mean of absolute error, and R = correlation between the estimated and observed values.</p><p>Summary of cross-validation statistics from the predictive models generated.</p

Comparative primer efficiency as calculated by geNorm Excel and geNorm SAS.

<p>Comparative primer efficiency as calculated by geNorm Excel and geNorm SAS.</p

Relative expression of this MT-CO2 target gene when normalized with poor ranked reference genes and the best reference genes using Pfaffl method.

<p>This Figure shows the effect of incorrect selection of reference gene in the gene expression of target gene. Two best ranked reference genes (HMBS and HPRT1) and the two poor ranked reference genes (TFRC and B2M). The results also include standard errors (SE_R) and two-tailed P values by Student's t test. A single asterisk indicates P-value < 0.05.</p

Normality test (Shapiro-Wilk).

<p>*<i>P</i>-values > 0.05 indicate a normal distribution.</p><p>Normality test (Shapiro-Wilk).</p

Descriptive statistics and expression level of reference genes obtained by BestKeeper (n = 52).

<p>Abbreviations: Cq: quantification cycle; GM [Cq]: geometric Cq mean; AM [Cq]:arithmetic Cq mean; Min [Cq] and Max [Cq]: Cq threshold values; SD [±Cq]: Cq standard deviation; CV [%Cq]: variance coefficient expressed as percentage of Cq level; SD and CV are indicated in bold.</p><p>Descriptive statistics and expression level of reference genes obtained by BestKeeper (n = 52).</p