Feeding high concentrations of corn dried distillers’ grains decreases methane, but increases nitrous oxide emissions from beef cattle production

2014 ◽  
Vol 127 ◽  
pp. 19-27 ◽  
Author(s):  
Martin Hünerberg ◽  
Shannan M. Little ◽  
Karen A. Beauchemin ◽  
Sean M. McGinn ◽  
Don O’Connor ◽  
...  
2017 ◽  
Vol 60 (4) ◽  
pp. 1209-1221 ◽  
Author(s):  
Heidi M. Waldrip ◽  
Kenneth D. Casey ◽  
Richard W. Todd ◽  
David B. Parker

Abstract. The Texas Panhandle produces approximately 42% of finished beef in the U.S., and cattle production is estimated to contribute 8 Tg carbon dioxide equivalents (CO2e) from nitrous oxide (N2O). Production of N2O in manure is largely a result of biochemical processes that are not static: N2O emission rates are dependent on numerous environmental and chemical factors. Process-based models that estimate N2O emissions from manure in open-lot cattle production systems typically rely on information derived from studies of soil biochemistry. Limited study has been conducted on manure-derived N2O in open-lot beef feedyards. The objectives of this study were to determine variables related to N2O losses from Texas Panhandle feedyards and develop empirical models to predict N2O emissions. Nitrous oxide flux data were collected from a series of 15 non-flow-through, non-steady-state (NFT-NSS) chamber studies (ten chambers per study) conducted from 2012 to 2014 on two commercial beef cattle feedyards. Manure samples (loose surface manure and the underlying manure pack) were analyzed for basic physicochemical properties, soluble carbon (C) and nitrogen (N), and ultraviolet-visible (UV-vis) spectral characteristics related to degree of organic matter (OM) stability and humification. Measured N2O emissions ranged from below detection to 101 mg m-2 h-1 (average 4.8 ±12 mg m-2 h-1) and were positively related to manure H2O content, temperature, and nitrate (NO3-) concentration (p < 0.01). Emissions were negatively related to manure OM, ammonia/ammonium (NH3/NH4+), dissolved C and dissolved N concentrations, and UV-vis parameters related to OM stability (p < 0.05). Based on these data, empirical models were developed and evaluated to predict manure-derived N2O emissions. Model predictions were not significantly different from observed N2O emissions (p < 0.05). The unbounded index of agreement (IA) indicated that model predictions were within 52% to 61% agreement with observations. Inclusion of OM characteristics improved model predictions of high (>30 mg m-2 h-1) N2O emissions but tended to overestimate low emission rates (<20 mg N2O m-2 h-1). This provides evidence for the importance of C stability in limiting manure N2O production. These models may improve parameterization of existing process-based models and are novel methods for predicting feedyard N2O emissions. Keywords: Beef cattle, Feedlot, Feedyard, Greenhouse gas, Manure, Modeling, Nitrous oxide, Organic matter, Urine, UV-vis spectroscopy.


2021 ◽  
pp. 127750
Author(s):  
Milene Dick ◽  
Marcelo Abreu da Silva ◽  
Rickiel Rodrigues Franklin da Silva ◽  
Otoniel Geter Lauz Ferreira ◽  
Manoel de Souza Maia ◽  
...  

2014 ◽  
Vol 160 ◽  
pp. 21-28 ◽  
Author(s):  
Maria Isabel Pravia ◽  
Olga Ravagnolo ◽  
Jorge Ignacio Urioste ◽  
Dorian J. Garrick

2021 ◽  
Vol 194 ◽  
pp. 103247
Author(s):  
Maria Paula Cavuto Abrão Calvano ◽  
Ricardo Carneiro Brumatti ◽  
Jacqueline Cavalcante Barros ◽  
Marcos Valério Garcia ◽  
Kauê Rodriguez Martins ◽  
...  

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 98-99
Author(s):  
Timothy DelCurto ◽  
Sam Wyffels

Abstract Designing research for beef cattle production in rangeland environments is an ongoing challenge for researchers worldwide. Specifically, creating study designs that mirror actual production environments yet have enough observations for statistical inference is a challenge that often hinders researchers in efforts to publish their observations. Numerous journals will accept “case study” or observational results that lack valid statistical inference. However, these journals are limited in number and often lack impact. Approaches are available to gain statistical inference by creating multiple observations within a common group of animals. Approaches to increasing statistical observations will be discussed in this presentation. Modeling animal behavior and performance on extensive rangeland landscapes is commonly practiced in wildlife ecology and, more recently, has been published in Animal Science journals. Additionally, new technology has made it possible to apply treatments (e.g., supplementation studies) to individual animals on extensive environments where large, diverse herds/flocks of cattle/sheep are managed as a single group. Use of individual animal identification (EID) and feed intake technology has opened a wide range of research possibilities for beef cattle production systems research in rangeland environments. Likewise, global positioning system (GPS) collars and activity monitors have created the opportunity to evaluate animal grazing behavior in remote and extensive landscapes. The use of multiple regression models to evaluate resource use in extensive environments will, in turn, help managers optimize beef cattle production and the sustainable use of forage/rangeland resources. Embracing new technologies such as GPS, activity monitors, EID tags, and feed intake monitors combined with multiple regression modeling tools will aid in designing and publishing beef cattle production research in extensive rangeland environments.


2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 430-430
Author(s):  
Andre Pastori D Aurea ◽  
Abmael S da Silva Cardoso ◽  
Lauriston Bertelli Fernandes ◽  
Ricardo Andrade Reis ◽  
Luis Eduardo Ferreira ◽  
...  

Abstract In Brazil beef cattle production is one of the most important activities in the agricultural sector and has an important impact on environmental and resources consumption. In this study assessed greenhouses gases (GHG) impacts from on farms representative productive system and the possible improvements of the production chain. Primary data from animal production index and feeding were collected from 17 farms, which covers 300.000 animals and 220.000 hectares. Emissions of methane, nitrous oxide and carbon dioxide were made using intergovernmental panel on climate change (IPCC) guidelines for national inventories. The GHG inventory included emissions from animals, feeds and operations for animal operation from “cradle to farm gate”. Emissions of each farm were converted to carbon dioxide equivalent (CO2eq) and divided by carcass production. Regression analysis between carbon dioxide equivalent and productive index was run to identify possible hotspot of GHG emissions. A large variation between farms were observed. The GHG yield ranged from 8.63 kg to 50.88 CO2eq kg carcass-1. The productive index age of slaughtering (P < 0.0001), average daily gain (P < 0.0001) and productivity (P = 0.058) per area were positive correlated to GHG yield. While no correlation was found with stocking rate (P = 0.21). Improvements of the production chain could be realized by accurate animal management strategies that reduce the age of slaughtering (feeding and genetic improvements) and gain individual or per area using strategic animal supplementation and pasture management, in order to obtains reduction of GHG emissions of beef cattle.


2021 ◽  
Vol 4 (1) ◽  
pp. e2021020
Author(s):  
Hassan Nima HABIB ◽  
Wessam Monther Mohammed SALEH ◽  
Qutaiba J. GHENI ◽  
Alfred S. KAROMY

2018 ◽  
Vol 96 (10) ◽  
pp. 4076-4086
Author(s):  
Justin W Buchanan ◽  
Michael D MacNeil ◽  
Randall C Raymond ◽  
Ashley R Nilles ◽  
Alison Louise Van Eenennaam

2012 ◽  
Vol 41 (3) ◽  
pp. 775-782 ◽  
Author(s):  
Vinícius do Nascimento Lampert ◽  
Júlio Otávio Jardim Barcellos ◽  
Francisco José Kliemann Neto ◽  
Leonardo Canali Canellas ◽  
Matheus Dhein Dill ◽  
...  

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