Characterization of water intake in beef cattle: test length guidelines, water intake prediction, and genetic parameters

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dc.contributor.author Ahlberg, Cashley Marie
dc.date.accessioned 2018-05-16T18:17:42Z
dc.date.available 2018-05-16T18:17:42Z
dc.date.issued 2018-08-01
dc.identifier.uri http://hdl.handle.net/2097/38950
dc.description.abstract In the future, water may not be as readily available due to an increase in competition from a growing human population, wildlife, and other agricultural sectors. To better understand water demands in the beef industry, water intake has to be accurately measured. It also critical to understand if water intake is a heritable trait and to determine its relationship to other production traits. This dissertation examines the number of days to accurately measure water intake in beef cattle, how to predict water intake in beef cattle using individual intakes, and estimates genetic parameters for water intake, dry matter intake (DMI), average daily gain (ADG), water efficiency measures, feed efficiency measures, and carcass traits. Study 1 investigates the test duration required to accurately measure water intake. Water intakes were collected over 70 d and shortened test periods (7 day intervals) were correlated with the full 70 day test to determine the minimum number of days required to accurately measure water intake. Water intake can be collected over a 35 to 42-day test period, with a minimal decrease in accuracy. Study 2 developed a water intake prediction equation that included different weather variables and average daily temperature (TAVG), average relative humidity (HVAG), solar radiation (SRAD), and wind speed (WSPD). Water intakes and feed intakes on individual animals were collected over a 70-day period along with (TAVG), (HVAG), (SRAD), (WSPD) for each day. Five different prediction equations were developed: summer, winter, slick bunk feed management, ad libitum feed management, and overall. All models included variables of DMI, metabolic mid test weight, TAVG, HAVG, SRAD, and WSPD, with R-squared values ranging from 0.34 to 0.41. Study 3 investigated the relationships between water intake and DMI, ADG, and water and feed efficiency traits. Variance components and genetic correlations were estimated using single-step genomic best linear unbiased prediction (GBLUP), incorporating genotypes on approximately 150,000 single nucleotide polymorphisms. Water intake was moderately heritable (0.39) and had moderate genetic correlations with DMI and residual feed intake, high genetic correlations with residual water intake, water to gain ratio, and feed to gain ratio, and had a low genetic correlation with ADG. Study 4 investigated the relationship between water intake and carcass traits. Single-Step GBLUP was used to estimate variance components and genetic correlations between water intake and carcass traits. Similar to study 3, water intake was moderately heritable (0.42). Water intake was moderately correlated with hot carcass weight (0.38), back fat (0.36), yield grade (0.29), and final body weight (0.29), but had a low genetic correlation with longissimus muscle area (0.08) and marbling (0.17). More research must be done to determine the relationships between water intake and other economically important traits in beef cattle and to better understand how environment and genetic background affect water intake. Improvements in water efficiency could decrease the amount of water cattle consume and assist producers in managing on-farm water resources during times of water scarcity. en_US
dc.description.sponsorship Agriculture and Food Research Initiative Competitive Grant No. 2014-67004-21624 from the U. S. Department of Agriculture National Institute of Food and Agriculture en_US
dc.language.iso en_US en_US
dc.subject Water intake en_US
dc.subject Beef cattle en_US
dc.subject Test duration en_US
dc.subject Genetic parameters en_US
dc.subject Water efficiency en_US
dc.subject Carcass traits en_US
dc.title Characterization of water intake in beef cattle: test length guidelines, water intake prediction, and genetic parameters en_US
dc.type Dissertation en_US
dc.description.degree Doctor of Philosophy en_US
dc.description.level Doctoral en_US
dc.description.department Department of Animal Sciences and Industry en_US
dc.description.advisor Megan Rolf en_US
dc.date.published 2018 en_US
dc.date.graduationmonth August en_US


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