Grass-fed vs. grain-fed beef systems: performance, economic, and environmental trade-offs

2021 ◽  
Author(s):  
S C Klopatek ◽  
E Marvinney ◽  
T Duarte ◽  
A Kendall ◽  
X Yang ◽  
...  
Keyword(s):  
Environmental Impacts ◽  
Mixed Model ◽  
Cropping Systems ◽  
Carcass Quality ◽  
Marbling Score ◽  
Model Framework ◽  
Land Occupation ◽  
Final Body Weight ◽  
Systems Model ◽  
Trade Offs

Abstract Between increasing public concerns over climate change and heightened interest of niche market beef on social media, the demand for grass-fed beef has increased considerably. However, the demand increase for grass-fed beef has raised many producers' and consumers' concerns regarding product quality, economic viability, and environmental impacts that have thus far gone unanswered. Therefore, using a holistic approach, we investigated the performance, carcass quality, financial outcomes, and environmental impacts of four grass-fed and grain-fed beef systems currently being performed by ranchers in California. The treatments included: 1) steers stocked on pasture and feedyard finished for 128 days (CON); 2) steers grass-fed for 20 months (GF20); 3) steers grass-fed for 20 months with a 45-day grain finish (GR45); and 4) steers grass-fed for 25 months (GF25). The data were analyzed using a mixed model procedure in R with differences between treatments determined by Tukey HSD. Using carcass and performance data from these systems, a weaning-to-harvest life cycle assessment (LCA) was developed in the Scalable, Process-based, Agronomically Responsive Cropping Systems model framework, to determine global warming potential (GWP), consumable water use, energy, smog, and land occupation footprints. Final body weight varied significantly between treatments (P <0.001) with the CON cattle finishing at 632 kg, followed by GF25 at 570 kg, GR45 at 551 kg, and GF20 478 kg. Dressing percentage (DP) differed significantly between all treatments (P < 0.001). The DP was 61.8% for CON followed by GR45 at 57.5%, GF25 at 53.4%, and GF20 had the lowest DP of 50.3%. Marbling scores were significantly greater for CON compared to all other treatments (P < 0.001) with CON marbling score averaging 421 (low-choice ≥ 400). Breakeven costs with harvesting and marketing for the CON, GF20, GR45, and GF25 were $6.01, $8.98, $8.02, and $8.33 per kg hot carcass weight (HCW), respectively. The GWP for the CON, GF20, GR45, and GF25 were 4.79, 6.74, 6.65 and 8.31 CO2e/kg HCW, respectively. Water consumptive use for CON, GF20, GR45, and GF25 were 933, 465, 678 and 1250 L /kg HCW, respectively. Energy use for CON, GF20, GR45, and GF25 were 18.7, 7.65, 13.8 and 8.85 MJ /kg HCW, respectively. Our results indicated that grass-fed beef systems differ in both animal performance and carcass quality resulting in environmental and economic sustainability tradeoffs with no system having absolute superiority.

scholarly journals 68 Assessing the Performance of Multiple Grass-fed Beef Production Systems in California

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 46-47
Author(s):  
Sarah C Klopatek ◽  
Toni Duarte ◽  
Crystal Yang ◽  
James W Oltjen
Keyword(s):  
Mixed Model ◽  
Systems Approach ◽  
Production Systems ◽  
Carcass Quality ◽  
Animal Performance ◽  
Beef Production ◽  
Marbling Score ◽  
Final Body Weight ◽  
Whole Systems

Abstract With demand for grass-fed beef continuing to increase, there is an immediate need to determine animal performance and product quality from varying grass-fed systems. Therefore, using a whole systems approach, we investigated the performance and carcass quality of multiple grass-fed beef systems in California. The treatments included: 1) steers stocked on pasture, then feedyard finished for 140 days (CON); 2) steers grass-fed for 20 months (20GF); 3) steers grass-fed for 20 months with a 45-day grain finish (GR45); and 4) steers grass-fed for 25 months (25GF). The data were analyzed using a mixed model procedure in R. Final body weight (FBW) varied significantly between treatments (P < 0.05) with the CON cattle finishing at 626 kg and GF20 finishing with the lowest FBW of 478 kg. There were no significant differences in FBW between GF45 and GF25 treatments (P > 0.05), with FBW equaling 551 kg and 570 kg, respectively. Dressing percentage (DP) differed significantly between all treatments (P < 0.05), with CON DP at 61.8%, followed by GR45 at 57.5%, GF25 at 53.4%, and GF20 at 50.3%. Marbling scores and quality grades were significantly higher for CON compared to all other treatments (P < 0.05), with a marbling score of 421; 14% of CON animals graded select and 85% graded choice or upper choice. Cattle in the GR20 had the lowest marbling score of 285 (P < 0.05); 59% of the GR20 cattle graded select and 41% graded standard. There was no difference in marbling when comparing the GF25 and GR45 (P > 0.5). In addition, carcasses graded similarly between the two treatments with GF25 grading 13% standard 82% select, and 6% choice, GR45 graded 85% select and 15% choice. The findings from this study indicate that varying CA grass-fed beef production systems results in significant differences in both animal performance and meat quality.

96 Assessing the Sustainability of Multiple Grass-fed and Grain-fed Beef Production Systems

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 48-49
Author(s):  
Sarah C Klopatek ◽  
Elias Marvinney ◽  
Xiang Yang ◽  
Alissa Kendall ◽  
James W Oltjen
Keyword(s):  
Environmental Impacts ◽  
Energy Use ◽  
Mixed Model ◽  
Production Systems ◽  
Holistic Approach ◽  
Beef Production ◽  
Model Framework ◽  
Final Body Weight ◽  
Financial Outcomes ◽  
Consumptive Use

Abstract Increased demand for grass-fed beef raises many producers’ and consumers’ concerns regarding product quality, economic viability, and environmental impacts that have gone unanswered. Therefore, using a holistic approach, we investigated the performance, carcass quality, financial outcomes, and environmental impacts of four typical grass-fed and conventional beef systems raised in a Mediterranean climate in the western United States. The treatments included: 1) steers stocked on pasture and feedyard finished for 128 days (CON); 2) steers grass-fed for 20 months (GF20); 3) steers grass-fed for 20 months with a 45-day grain finish (GR45); and 4) steers grass-fed for 25 months (GF25). The data were analyzed using a mixed model procedure in R. Data from these beef production systems, a weaning-to-harvest life cycle assessment (LCA) using the SPARKS-LCA model framework, to determine global warming potential (GWP), consumable water usage, energy, smog, and land use footprints. Final body weight varied significantly between treatments (P < 0.001) with CON finishing at 632 kg, followed by GF25 at 570 kg, GR45 at 551 kg, and GF20 478 kg. Dressing percentage differed significantly between all treatments (P < 0.001) with CON at 61.8%, followed by GR45 at 57.5%, GF25 at 53.4%, and GF20 at 50.3%. Breakeven costs with harvesting and marketing for the CON, GF20, GR45, and GF25 were $6.01, $8.98, $8.02, and $8.33 per kg hot carcass weight (HCW), respectively. The GWP for the CON, GF20, GR45, and GF25 were 4.79, 6.74, 6.65 and 8.31 CO2e/kg HCW, respectively. Water consumptive use for CON, GF20, GR45, and GF25 were 933, 465, 678 and 1245 L /kg HCW, respectively. Energy use for CON, GF20, GR45, and GF25 were 18.69, 7.65, 13.84 and 8.85 MJ /kg HCW, respectively. The results from this study indicate that differences in grass-fed beef management can have profound impacts on food security and sustainability.

scholarly journals Trade-Offs between Economic and Environmental Impacts of Introducing Legumes into Cropping Systems

2016 ◽  
Vol 7 ◽  
Author(s):  
Moritz Reckling ◽  
Göran Bergkvist ◽  
Christine A. Watson ◽  
Frederick L. Stoddard ◽  
Peter M. Zander ◽  
...  
Keyword(s):  
Environmental Impacts ◽  
Cropping Systems ◽  
Trade Offs

scholarly journals Genotype specific P-spline response surfaces assist interpretation of regional wheat adaptation to climate change

2021 ◽  
Author(s):  
Daniela Bustos-Korts ◽  
Martin P Boer ◽  
Karine Chenu ◽  
Bangyou Zheng ◽  
Scott Chapman ◽  
...  
Keyword(s):  
Environmental Quality ◽  
Mixed Model ◽  
Meteorological Data ◽  
Response Surfaces ◽  
Yield Response ◽  
Environment Interaction ◽  
Adaptation To Climate Change ◽  
Model Framework ◽  
Genotype By Environment ◽  
Systems Model

Abstract Yield is a function of environmental quality and the sensitivity with which genotypes react to that. Environmental quality is characterized by meteorological data, soil and agronomic management, whereas genotypic sensitivity is embodied by combinations of physiological traits that determine the crop capture and partitioning of environmental resources over time. This paper illustrates how environmental quality and genotype responses can be studied by a combination of crop simulation and statistical modeling. We characterized the genotype by environment interaction for grain yield of a wheat population segregating for flowering time by simulating it using the APSIM cropping systems model. For sites in the NE Australian wheat-belt, we used meteorological information as integrated by APSIM to classify years according to water, heat and frost stress. Results highlight that the frequency of years with more severe water and temperature stress has largely increased in recent years. Consequently, it is likely that future varieties will need to cope with more stressful conditions than in the past, making it important to select for flowering habits contributing to temperature and water stress adaptation. Conditional on year-types, we fitted yield response surfaces as functions of genotype, latitude and longitude to virtual multi-environment trials. Response surfaces were fitted by two-dimensional P-splines in a mixed-model framework to predict yield at high spatial resolution. Predicted yields demonstrated how relative genotype performance changed with location and year-type and how genotype-by-environment interactions can be dissected. Predicted response surfaces for yield can be used for performance recommendations, quantification of yield stability and environmental characterization.

Hierarchical Modelling of Facial Perceptions: A Secondary Analysis of Aggressiveness Ratings

2020 ◽  
Author(s):  
Mark Christopher Adkins ◽  
Nataly Beribisky ◽  
Stephan Bonfield ◽  
Linda Farmus
Keyword(s):  
Factor Analysis ◽  
Mixed Model ◽  
Structural Information ◽  
Secondary Analysis ◽  
Specific Factor ◽  
Primary Analysis ◽  
Model Framework ◽  
Psychological Science ◽  
Individual Traits ◽  
Confirmatory Factor

The Psychological Science Accelerator’s (PSA) primary project tested for latent structure using exploratory factor analysis and confirmatory factor analysis but we decided to diverge from this approach and model individual traits separately. Our interest mainly was in examining the interplay between “stimulus ethnicity” and “stimulus sex” to discover how differing levels of these criterion differ across region, country, lab etc. While the necessary and prerequisite hierarchical structural information about each trait could certainly be found within the primary project’s dataset, we did not assume that any specific factor structure from the PSA’s primary analysis would necessarily hold, therefore we based our decision to model the data from each trait separately using a mixed model framework.

Farm-Level Economic and Environmental Impacts of Eastern Corn Belt Cropping Systems

jpa ◽  
1993 ◽  
Vol 6 (2) ◽  
pp. 290-296 ◽  
Author(s):  
John C. Foltz ◽  
John G. Lee ◽  
Marshall A. Martin
Keyword(s):  
Environmental Impacts ◽  
Cropping Systems ◽  
Corn Belt ◽  
Farm Level

scholarly journals Variance-based global sensitivity analysis and beyond in life cycle assessment: an application to geothermal heating networks

2021 ◽  
Author(s):  
Marc Jaxa-Rozen ◽  
Astu Sam Pratiwi ◽  
Evelina Trutnevyte
Keyword(s):  
Sensitivity Analysis ◽  
Life Cycle Assessment ◽  
Environmental Impacts ◽  
Spectral Clustering ◽  
Global Sensitivity Analysis ◽  
Sobol Indices ◽  
Global Sensitivity ◽  
Geothermal Heating ◽  
Trade Offs ◽  
Heating Networks

Abstract Purpose Global sensitivity analysis increasingly replaces manual sensitivity analysis in life cycle assessment (LCA). Variance-based global sensitivity analysis identifies influential uncertain model input parameters by estimating so-called Sobol indices that represent each parameter’s contribution to the variance in model output. However, this technique can potentially be unreliable when analyzing non-normal model outputs, and it does not inform analysts about specific values of the model input or output that may be decision-relevant. We demonstrate three emerging methods that build on variance-based global sensitivity analysis and that can provide new insights on uncertainty in typical LCA applications that present non-normal output distributions, trade-offs between environmental impacts, and interactions between model inputs. Methods To identify influential model inputs, trade-offs, and decision-relevant interactions, we implement techniques for distribution-based global sensitivity analysis (PAWN technique), spectral clustering, and scenario discovery (patient rule induction method: PRIM). We choose these techniques because they are applicable with generic Monte Carlo sampling and common LCA software. We compare these techniques with variance-based Sobol indices, using a previously published LCA case study of geothermal heating networks. We assess eight environmental impacts under uncertainty for three design alternatives, spanning different geothermal production temperatures and heating network configurations. Results In the application case on geothermal heating networks, PAWN distribution-based sensitivity indices generally identify influential model parameters consistently with Sobol indices. However, some discrepancies highlight the potentially misleading interpretation of Sobol indices on the non-normal distributions obtained in our analysis, where variance may not meaningfully describe uncertainty. Spectral clustering highlights groups of model results that present different trade-offs between environmental impacts. Compared to second-order Sobol interaction indices, PRIM then provides more precise information regarding the combinations of input values associated with these different groups of calculated impacts. PAWN indices, spectral clustering, and PRIM have a computational advantage because they yield stable results at relatively small sample sizes (n = 12,000), unlike Sobol indices (n = 100,000 for second-order indices). Conclusions We recommend adding these new techniques to global sensitivity analysis in LCA as they give more precise as well as additional insights on uncertainty regardless of the distribution of the model outputs. PAWN distribution-based global sensitivity analysis provides a computationally efficient assessment of input sensitivities as compared to variance-based global sensitivity analysis. The combination of clustering and scenario discovery enables analysts to precisely identify combinations of input parameters or uncertainties associated with different outcomes of environmental impacts.

Using crop simulation to generate genotype by environment interaction effects for sorghum in water-limited environments

2002 ◽  
Vol 53 (4) ◽  
pp. 379 ◽  
Author(s):  
Scott C. Chapman ◽  
Mark Cooper ◽  
Graeme L. Hammer
Keyword(s):  
Cropping Systems ◽  
Target Population ◽  
Genotype By Environment Interaction ◽  
Expected Improvement ◽  
Stress Index ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Systems Model ◽  
Water Stress Index ◽  
Eastern Australia

Multi-environment trials (METs) used to evaluate breeding lines vary in the number of years that they sample. We used a cropping systems model to simulate the target population of environments (TPE) for 6 locations over 108 years for 54 ‘near-isolines’ of sorghum in north-eastern Australia. For a single reference genotype, each of 547 trials was clustered into 1 of 3 ‘drought environment types’ (DETs) based on a seasonal water stress index. Within sequential METs of 2 years duration, the frequencies of these drought patterns often differed substantially from those derived for the entire TPE. This was reflected in variation in the mean yield of the reference genotype. For the TPE and for 2-year METs, restricted maximum likelihood methods were used to estimate components of genotypic and genotype by environment variance. These also varied substantially, although not in direct correlation with frequency of occurrence of different DETs over a 2-year period. Combined analysis over different numbers of seasons demonstrated the expected improvement in the correlation between MET estimates of genotype performance and the overall genotype averages as the number of seasons in the MET was increased.

scholarly journals Multiobjective formulation is an effective method to reduce environmental impacts of livestock feeds

2018 ◽  
Vol 120 (11) ◽  
pp. 1298-1309 ◽  
Author(s):  
Florence Garcia-Launay ◽  
Léonie Dusart ◽  
Sandrine Espagnol ◽  
Sarah Laisse-Redoux ◽  
Didier Gaudré ◽  
...  
Keyword(s):  
Environmental Impacts ◽  
Energy Demand ◽  
Animal Production ◽  
Land Occupation ◽  
Feed Formulation ◽  
Livestock Feeds ◽  
Feed Cost ◽  
Environmental Objectives ◽  
Commercial Farms ◽  
The Cost

AbstractEnvironmental and economic performances of livestock production are related largely to the production of complete feeds provided on commercial farms. Formulating feeds based on environmental and economic criteria appears a suitable approach to address the current challenges of animal production. We developed a multiobjective (MO) method of formulating feed which considers both the cost and environmental impacts (estimated via life cycle assessment) of the feed mix. In the first step, least-cost formulation provides a baseline for feed cost and potential impacts per kg of feed. In the second, the minimised MO function includes normalised values of feed cost and impacts climate change, P demand, non-renewable energy demand and land occupation. An additional factor weights the relative influence of economic and environmental objectives. The potential of the method was evaluated using two scenarios of feed formulation for pig, broiler and young bulls. Compared to baseline feeds, MO-formulated feeds had lower environmental impacts in both scenarios studied (−2 to −48 %), except for land occupation of broiler feeds, and a moderately higher cost (1–7 %). The ultimate potential for this method to mitigate environmental impacts is probably lower than this, as animal supply chains may compete for the same low-impact feed ingredients. The method developed complements other strategies, and optimising the entire animal production system should be explored in the future to substantially decrease the associated impacts.

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