Search Results (5)

In 2021, Winter Storm Uri severely affected several Texan agricultural sectors, including dairy production. To understand how dairy producers experienced this extreme weather event, this qualitative phenomenological case study explored perceptions of preparedness, coping strategies, and information needs and preferences for dealing with extreme weather events among dairy producers in Texas, conducting individual semi-structured interviews. The findings indicated that farmers felt unprepared to deal with extreme weather events and suffered significant economic losses due to this lack of preparedness. In response to winter storm Uri, dairy farmers modified traditional operations and management practices to mitigate negative impacts on farm labor, infrastructure, and herds. Our results, along with the existing literature on communication for extreme weather event management, highlighted that dairy farmers do not receive adequate information to effectively prevent and cope with similar occurrences in the future. Consequently, this study recommends exploring effective strategies to help agricultural producers develop plans to manage the effects of extreme weather events. Additionally, it integrates place-based, pluralistic, and demand-driven approaches to identify the best communication practices, enhance timely information dissemination on extreme weather, and strengthen the technical capacities of public and private entities, including Cooperative Extension Systems, as trusted resources for agricultural producers. Full article

A field study was conducted to investigate the effects of selected climate-smart agriculture practices on soil bulk density (ρ), porosity (β), hydraulic conductivity (K_sat), and nutrient dynamics in southeast Texas. Treatment combinations of two types of organic manure (chicken and dairy) with three rates (0, 224, and 448 kg N ha⁻¹) and two levels of biochar (2500 and 5000 kg ha⁻¹) were used in a factorial randomized block design. Bulk density and porosity measurements were conducted on undisturbed soil core samples collected from the topsoil (0–10 cm) of a field cultivated with sweet corn. K_sat was calculated from the steady-state infiltration measured using the Tension Infiltrometer (TI). The ANOVA results indicated that the manure application rates, and biochar levels significantly affected the soil properties. Compared to the control, β increased by 15% and 29% for the recommended and double recommended manure rates. Similarly, hydraulic conductivity increased by 25% in the double-recommended rate plots compared to the control. Also, we applied the concept of non-parametric elasticity to understand the sensitivity of soil physical and chemical properties to K_sat. ρ and β are critical physical properties that are highly sensitive to K_sat. Among soil nutrients, Boron showed the highest sensitivity to K_sat. Hydraulic conductivity can be enhanced by employing selected climate-smart practices and improving water management. Future directions for this study focus on scaling these findings to diverse cropping systems and soil types while integrating long-term assessments to evaluate the cumulative effects of climate-smart practices on soil health, crop productivity, and ecosystem sustainability. Full article

The objective of this study was to evaluate the effects of breed, lactation number, and lameness on lying time, milk yield, milk urea nitrogen concentration (MUN), progesterone concentration (P₄), and the calving-to-conception interval (CCI) of lactating dairy cows in Central Texas. A total of 84 lactating dairy cows (Holsteins, Jerseys, and crossbreeds) from a commercial dairy farm in Central Texas were randomly selected and enrolled in this study from October 2023 to February 2024. Cows (60 ± 7 DIM) were enrolled in cohorts weekly for five weeks and were randomly fitted with an IceQube pedometer (IceRobotics, Edinburgh, UK) to track lying time. Lameness and body condition scores (BCS) were recorded, and blood samples were collected once a week. Parameters of reproductive performance included insemination rate, conception rate, pregnancy rate, and the CCI. Monthly dairy herd improvement association (DHIA) testing included milk yield and MUN concentrations. Breed and lactation number had a significant effect on milk yield, MUN concentration, lying time, BCS, and lameness (p < 0.001). Lactation number had a significant effect on P₄ concentrations (p < 0.001). There was a positive correlation between lameness and milk yield (p = 0.014) and a negative correlation between lameness and MUN concentrations (p = 0.038). Full article

Texas is the third-largest milk-producing state in the U.S., with Central Texas being the second-largest milk-producing region in Texas. The average size of a dairy herd in Texas is 1829 cows. In Central Texas alone, there are 88,000 dairy cows. However, there is a lack of environmental impact research for this region. The overall objective of this case study is to evaluate the net carbon and carbon equivalent balances for a large dairy operation in Central Texas. The dairy selected for this study has a herd size of 5000 milking cows. The data assumptions were made regarding the selected dairy’s performance and production for the 2021 production year. These data include herd size and management, milk production, crop production, feed purchases, and on-farm energy usage. The USDA-Integrated Farm System Model (IFSM) was used to estimate the daily and annual greenhouse gas emissions and environmental footprint of the dairy by quantifying the operation’s carbon footprint based on its 2021 performance and management practices. Research outcomes identify and quantify sources of greenhouse gas (GHG) emissions produced on the dairy farm. Additionally, the carbon footprint (CF) was determined by estimating the CO₂ equivalents (CO₂-eq) emitted or sunk from animal and manure emissions, direct and indirect land emissions, net biogenic and anthropogenic CO₂ emissions, and the production of resource inputs. The results of this case study indicated that the carbon footprint (CF) of the 5000-milking-head dairy in Central Texas was 0.40 lb. of CO₂ per lb. of fat- and protein-corrected milk (FPCM) when considering biogenic CO₂ and 0.83 lb. of CO₂ per lb. of FPCM without biogenic CO₂. Full article

The objectives of this study were to evaluate the effects of a postpartum oral calcium supplementation strategy in multiparous Jersey cows on (1) the odds of clinical mastitis in the first 60 days in milk (DIM); (2) the odds of culling up to 60 DIM; (3) the risk of pregnancy in the first 150 DIM; (4) milk production in the first 15 weeks of lactation. A randomized clinical trial was performed in a dairy herd located in west Texas, United States. A total of 809 cows were used in the final analyses. Overall, postpartum oral calcium supplementation did not influence milk production, reproductive performance, or culling. Among second parity cows, oral calcium supplementation tended to decrease the odds of clinical mastitis in the first 60 DIM compared to controls; however, no differences were observed for cows in parities three and greater. To date, data evaluating the effect of postpartum oral calcium supplementation in multiparous Jersey cows are limited. In our study, oral calcium supplementation tended to reduce clinical mastitis in second parity cows. No positive benefits based on the reduction of culling, and improvement of milk production and reproductive performance were evident for the herd included in this study. Full article