Novel genetic parameters for genetic residual feed intake in dairy cattle using time series data from multiple parities and countries in North America and Europe.

Residual feed intake is viewed as an important trait in breeding programs that could be used to enhance genetic progress in feed efficiency. In particular, improving feed efficiency could improve both economic and environmental sustainability in the dairy cattle industry. However, data remain sparse, limiting the development of reliable genomic evaluations across lactation and parity for residual feed intake. Here, we estimated novel genetic parameters for genetic residual feed intake (gRFI) across the first, second, and third parity, using a random regression model. Research data on the measured feed intake, milk production, and body weight of 7,379 cows (271,080 records) from 6 countries in 2 continents were shared through the Horizon 2020 project GenTORE and Resilient Dairy Genome Project. The countries included Canada (1,053 cows with 47,130 weekly records), Denmark (1,045 cows with 72,760 weekly records), France (329 cows with 16,888 weekly records), Germany (938 cows with 32,614 weekly records), the Netherlands (2,051 cows with 57,830 weekly records), and United States (1,963 cows with 43,858 weekly records). Each trait had variance components estimated from first to third parity, using a random regression model across countries. Genetic residual feed intake was found to be heritable in all 3 parities, with first parity being predominant (range: 22-34%). Genetic residual feed intake was highly correlated across parities for mid- to late lactation; however, genetic correlation across parities was lower during early lactation, especially when comparing first and third parity. We estimated a genetic correlation of 0.77 ± 0.37 between North America and Europe for dry matter intake at first parity. Published literature on genetic correlations between high input countries/continents for dry matter intake support a high genetic correlation for dry matter intake. In conclusion, our results demonstrate the feasibility of estimating variance components for gRFI across parities, and the value of sharing data on scarce phenotypes across countries. These results can potentially be implemented in genetic evaluations for gRFI in dairy cattle

Estimation of genetic parameters for feed efficiency traits using random regression models in dairy cattle.

Feed efficiency has become an increasingly important research topic in recent years. As feed costs rise and the environmental impacts of agriculture become more apparent, improving the efficiency with which dairy cows convert feed to milk is increasingly important. However, feed intake is expensive to measure accurately on large populations, making the inclusion of this trait in breeding programs difficult. Understanding how the genetic parameters of feed efficiency and traits related to feed efficiency vary throughout the lactation period is valuable to gain understanding into the genetic nature of feed efficiency. This study used 121,226 dry matter intake (DMI) records, 120,500 energy corrected milk (ECM) records, and 98,975 metabolic body weight (MBW) records, collected on 7,440 first lactation Holstein cows from 6 countries (Canada, Denmark, Germany, Spain, Switzerland, and United States of America), from January 2003 to February 2022. Genetic parameters were estimated using a multiple-trait random regression model with a fourth order Legendre polynomial for all traits. Weekly phenotypes for DMI were re-parameterized using linear regressions of DMI on ECM and MBW, creating a measure of feed efficiency that was genetically corrected for ECM and MBW, referred to as genomic residual feed intake (gRFI). Heritability (SE) estimates varied from 0.15 (0.03) to 0.29 (0.02) for DMI, 0.24 (0.01) to 0.29 (0.03) for ECM, 0.55 (0.03) to 0.83 (0.05) for MBW, and 0.12 (0.03) to 0.22 (0.06) for gRFI. In general, heritability estimates were lower in the first stage of lactation compared with the later stages of lactation. Additive genetic correlations between weeks of lactation varied, with stronger correlations between weeks of lactation that were close together. The results of this study contribute to a better understanding of the change in genetic parameters across the first lactation, providing insight into potential selection strategies to include feed efficiency in breeding programs

Understanding micro-processes of community building and mutual learning on Twitter: a ‘small data’ approach

This article contributes to an emerging field of ‘small data’ research on Twitter by presenting a case study of how teachers and students at a sixth-form college in the north of England used this social media platform to help construct a ‘community of practice’ that enabled micro-processes of recognition and mutual learning. Conducted as part of a broader action research project that focused on the ‘digital story circle’ as a site of, and for, narrative exchange and knowledge production, this study takes the form of a detailed analysis of a departmental Twitter account, combining basic quantitative metrics, close reading of selected Twitter data and qualitative interviews with teachers and students. Working with (and sometimes against) Twitter's platform architecture, teachers and students constructed, through distinct patterns of use, a shared space for dialogue that facilitated community building within the department. On the whole, they were able to overcome justified anxieties about professionalism and privacy; this was achieved by building on high levels of pre-existing trust among staff and by performing that mutual trust online through personal modes of communication. Through micro-processes of recognition and a breaking down of conventional hierarchies that affirmed students' agency as knowledge producers, the departmental Twitter account enabled mutual learning beyond curriculum and classroom. The significance of such micro-processes could only have been uncovered through the detailed scrutiny that a ‘small data’ approach to Twitter, in supplement to some obvious virtues of Big Data approaches, is particularly well placed to provide

The Resilient Dairy Genome Project - a general overview of methods and objectives related to feed efficiency and methane emissions.

The Resilient Dairy Genome Project (RDGP) is an international large-scale applied research project that aims to generate genomic tools to breed more resilient dairy cows. In this context, improving feed efficiency and reducing greenhouse gases from dairy is a high priority. The inclusion of traits related to feed efficiency (e.g., dry matter intake [DMI]) or greenhouse gases (e.g., methane emissions [CH4]) relies on available genotypes as well as high quality phenotypes. Currently, 7 countries, i.e., Australia [AUS], Canada [CAN], Denmark [DNK], Germany [DEU], Spain [ESP], Switzerland [CHE], and United States of America [USA] contribute with genotypes and phenotypes including DMI and CH4. However, combining data is challenging due to differences in recording protocols, measurement technology, genotyping, and animal management across sources. In this study, we provide an overview of how the RDGP partners address these issues to advance international collaboration to generate genomic tools for resilient dairy. Specifically, we describe the current state of the RDGP database, data collection protocols in each country, and the strategies used for managing the shared data. As of February 2022, the database contains 1,289,593 DMI records from 12,687 cows and 17,403 CH4 records from 3,093 cows and continues to grow as countries upload new data over the coming years. No strong genomic differentiation between the populations was identified in this study, which may be beneficial for eventual across-country genomic predictions. Moreover, our results reinforce the need to account for the heterogeneity in the DMI and CH4 phenotypes in genomic analysis

Molecular Arrangement of a Mixture of Organosulfur Surfactants at the Aqueous Solution Vapor Interface Studied by Photoelectron Intensity and Angular Distribution Measurements and Molecular Dynamics Simulations

Photoelectron angular distributions PADs from aqueous solution surfaces reveal details of the spatial arrangement of solute molecules at the solution gas phase interface. This is demonstrated here for mixed equimolar aqueous solutions of dimethyl sulfoxide dimethyl sulfone CH3 2SO CH3 2SO2 and dimethyl sulfoxide dimethyl sulfite CH3 2SO CH3 2SO3 , all molecules having a propensity to reside near the solution surface. Although the surface active molecules coexist at the surface, CH3 2SO2 yields a more intense sulfur 2p surface photoelectron signal than CH3 2SO, and for CH3 2SO3, the effect is even larger. To understand this behavior, we have for one of the solutions mixtures, CH3 2SO CH3 2SO2, performed PAD measurements. Surprisingly, both molecules exhibit almost identical PADs, implying that the emitted photoelectrons have experienced a similar limited amount of scattering interactions. Hence, the molecules reside at the same distance with respect to the solution vacuum interface rather than CH3 2SO2 being closer to the surface than CH3 2SO, as one may have assumed based on the relative photoelectron signal intensities. Instead, the relative surface and bulk concentrations of the two compounds differ. We also report S 2p photoelectron spectra from single component dimethyl sulfide, CH3 2S, aqueous solutions measured at a single detection angle. The exceptionally large surface propensity of CH3 2S is recognized by a narrow, gas phase like photoelectron spectrum, revealing that CH3 2S experiences very few hydration interactions. Experimentally observed trends in surface activity for the different molecules, which are complemented here by molecular dynamics simulations, agree with findings obtained with other surface sensitive techniques. New information on the surface structure of mixed solutions is uniquely obtained from the anisotropic angular distributions of the photoelectron

Transient IR Spectroscopic Observation of Singlet and Triplet States of 2‑Nitrofluorene: Revisiting the Photophysics of Nitroaromatics

The dynamics of 2-nitrofluorene (2-NF) in deuterated acetonitrile is studied using UV pump, IR probe femtosecond transient absorption spectroscopy. Upon excitation to the vibrationally excited S₁ state, the excited-state population of 2-NF branches into two different relaxation pathways. One route leads to intersystem crossing (ISC) to the triplet manifold within a few hundred femtoseconds and the other to internal conversion (IC) to the ground state. The experiments indicate that after relaxation to the energetic minimum on S₁, 2-NF undergoes internal conversion to the ground state in about 15 ps. IC within the triplet manifold is also observed as the initially populated triplet state relaxes to T₁ in about 6 ps. Rotational anisotropy measurements corroborate the assignment of the transient IR frequencies and indicate a rotational diffusion time of 2-NF in the solvent of about 14 ps. The combined set of results provides a unified picture of the dynamics in photoexcited 2-NF. This to our knowledge is the first example using femtosecond vibrational spectroscopy for the study of the fundamental photoinduced processes in nitroaromatic compounds

Constructing a digital storycircle: digital infrastructure and mutual recognition

Building on the principles of the digital storytelling movement, this article asks whether the narrative exchange within the ‘storycircles’ of storymakers created in face-to-face workshops can be further replicated by drawing on digital infrastructure in specific ways. It addresses this question by reporting on the successes and limitations of a five-stream project of funded action research with partners in north-west England that explored the contribution of digital infrastructure to processes of narrative exchange and the wider processes of mutual recognition that flow from narrative exchange. Three main dimensions of a digital storycircle are explored: multiplications, spatializations (or the building of narratives around sets of individual narratives), and habits of mutual recognition. Limitations relate to the factors of time, and levels of digital development and basic digital access