English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This study aimed to develop equations to predict the empty body weight (EBW) using the shrunk body weight (SBW) of water buffaloes of three genetic groups (GG:Jafarabadi, Mediterranean, and Murrah; n = 65 for each GG), considering possible variations among GG. One-hundred-ninety-five non-castrated males (390±32 days of age; 327±51.96 kg of initial body weight - BW) from two years of similar experiments were used. Animals of each GG were allocated in collective pens for 28 days of adaptation period. Diet and water were offered ad libitum. Animal SBW were recorded at the beginning and every 28 days until the averages SBW reached the values determined (420, 480, and 540kg of SBW). After slaughter and to obtain the EBW, the non-carcass components of each animal [blood, paws, head, leather, tail, gastrointestinal tract (GIT), liver, kidneys, internal fat, and other internal organs] were weighed. The full GIT of each animal was weighed to obtain the total weight, and then emptied, washed, drained, and weighed to obtain the weight of the GIT content. Initially, data were analyzed using UNIVARIATE procedure in SAS. SBW recorded prior to slaughter were categorized according to SBW proposed considering the coefficient of variation below 10% for each GG to increase the precision of the data used, which decreased the initial n to 104 animals. Equations were developed and tested for GG effect using GLM and REG procedures in SAS. Tendency of GG effect was detected (P = 0.06). Thus, different prediction equations were determined for each GG, and a general prediction equation was developed for the three GG (Table 1). In conclusion, the results suggest it is possible to use distinct equations to predict the EBW according to GG as well as a general equation can be also used, resulting in high predictions of EBW of water buffaloes finished in feedlot.

PSVII-8 Equations for prediction of empty body weight of water buffaloes finished in feedlot