Search bioRxiv⌕ Search

bioRxiv · 10.1101/2025.02.04.636425

ANALYSIS OF THE IMPACT OF FIVE METHANE MITIGATING FEED ADDITIVES ON MILK PRODUCTION AND ASSOCIATED PARAMETERS ACROSS MULTIPLE COMMERCIAL DAIRY FARMS

Abstract

The effect of methane-mitigating feed additives on dairy cows has been widely explored; however, confusing conclusions have been reached due to factors such as the inclusion of different doses and experimental conditions in which the additives are tested, or even a small sample size. We present the first extensive study assessing the effects of methane-mitigating feed additives on milk production across several commercial dairy farms. This study used a previously developed predictive AI-driven model based on microbiome samples; the model predicts farms where a significant reduction of methane emissions is expected due to the applied feed additives. Thus, in this study, each feed additive was supplied to a large number of farms, widely distributed across different climatic areas in Israel. The data analysis followed two simulated scenarios: (1) a naive approach, where feed additives are supplied indiscriminately, and (2) an optimized approach, where feed additives are supplied only to farms with a high likelihood of being positively impacted in terms of reduced enteric methane emissions (50% of the farms). The results show that each feed additive significantly increased milk production compared to the control groups. This increase in milk production was significantly higher in the optimized scenario. Other related parameters such as somatic cells were also improved. Our results suggest that the feed additives positively affect milk production, reaching a maximum expression when the AI-driven model is applied.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Altshuler, Y., Calvao Chebach, T., Cohen, S., Gatica, J.. 2025-02-08. ANALYSIS OF THE IMPACT OF FIVE METHANE MITIGATING FEED ADDITIVES ON MILK PRODUCTION AND ASSOCIATED PARAMETERS ACROSS MULTIPLE COMMERCIAL DAIRY FARMS. https://doi.org/10.1101/2025.02.04.636425

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Comparing the Influence of Habitat Configuration on Population Connectivity and Genetic Structure Using Congeneric Species Across Multiple Taxa

Abstract Habitat configuration influences population connectivity and, consequently, genetic structure. River networks provide heterogeneous, hierarchically arranged environments that shift drastically from upstream to downstream. We compared congeneric species across Ephemeroptera, Plecoptera, and Trichoptera, emphasizing longitudinal replacement (upstream to downstream) and the rarely studied wet rock (hygropetric) habitats. We surveyed six rivers on the Muroto Peninsula, Japan, qualitatively sampling aquatic insects at 63 sites. Cluster analysis based on the environmental data classified surveyed sites into four clusters. We analyzed a total of 10 species from four genera that exhibit longitudinal replacement patterns within genera. Genetic analyses based on the mitochondrial cytochrome c oxidase subunit I region revealed that upstream species showed higher genetic diversity than downstream species. In contrast, species adapted to hygropetric exhibited the lowest genetic differentiation among all habitat types. A novel contribution of this study is the inclusion of hygropetric species. The surprisingly low differentiation in hygropetric species suggests high connectivity, similar to lentic species. By comparing congeneric taxa across orders within environmentally similar rivers, we reduce phylogenetic and environmental confounds, strengthening inference that habitat configuration and dispersal traits jointly shape genetic structure. These findings provide a new perspective on riverine spatial ecology and underscore the importance of microhabitat-aware comparisons for evolutionary inference.

zoology↗

Late lactation represents the main window for sow-to-piglet transmission of persistent gut strains

The gut microbiota plays a key role in piglet health, and maternal microbial transmission may represent a promising lever to shape early-life microbiota and prevent post-weaning digestive disorders. This study aimed to better characterize sow-to-piglet microbiota transmission and persistence using a long-read metabarcoding approach targeting the 16S-ITS-23S region. Fecal samples (n = 204) were collected from 17 families, a family being as sow and three of her piglets, at multiple stages: late gestation (G110), early (L6) and late lactation (L28) for sows; early lactation (L6), late lactation (L28), and 5 days post-weaning for piglets. To approximate strain-level resolution, a putative strain (PS) approach was developed by clustering ASVs (n = 6064) affiliated with the same species based on abundance covariance (r > 0.9), resulting in 4857 PS. Piglet microbiota progressively diversified during lactation and converged toward that of sow. In sows, 27 {+/-} 6% of PS were persistent from late gestation to late lactation. In piglets, only 4.2 {+/-} 2.5% of PS persisted from d6 to 5 days post-weaning. Persistent PS in piglets were mainly affiliated with Limosilactobacillus reuteri and Lactobacillus amylovorus followed with Holdemanella porci and H. biformis, Lentihominibacter hominis and Dorea formicigenerans. Shared PS were significantly higher within families than between unrelated pairs (p < 0.05). Maternal transmission peaked at the end of lactation (35 {+/-} 7% at L28). Persistent transmitted PS represented 2.7 {+/-} 1.6% (d6-post-weaning) and 15.4 {+/-} 5.6% (d28-post-weaning). Early-transmitted persistent PS were mainly affiliated with Limosilactobacillus reuteri, Lactobacillus amylovorus, and Paraeggerthella hominis, whereas late-transmitted persistent PS were associated with Prevotella spp., Sphaerochaeta globosa, and Bariatricus comes. These findings highlight the significance of maternal transmission in shaping the post-weaning microbiota and identify late lactation as a critical window for microbiota transfer.

zoology↗

RISC-Bound Small RNA Sequencing Provides Insights into Guide Strand Selection and siRNA Trimming and Tailing Following Insecticidal dsRNA Delivery

RNA interference (RNAi) offers a sequence-specific approach to pest control. In insects, Dicer-2 processes double-stranded RNA (dsRNA) into small interfering RNA (siRNA) duplexes, from which the RNA-induced silencing complex (RISC) retains a guide strand. Only antisense-loaded RISC can mediate cleavage of the target transcript. However, how sequence features shape the RISC-bound siRNA pool in pests remains poorly understood, limiting opportunities for sequence optimization. Here, we profiled RISC-bound siRNAs following injection of 34 insecticidal dsRNAs targeting 11 essential genes in Tribolium castaneum larvae. We computationally reconstructed 7,879 siRNA pairs and examined associations between sequence features and strand bias. Differences in GC identity at terminal paired positions 1 to 5, used as a proxy for local thermodynamic asymmetry, correlated with strand bias, with the strongest correlations at the first two paired positions. ORF targeting and reduced predicted antisense self-folding were also associated with higher antisense fractions. Analysis of non-templated terminal additions revealed predominantly 3-prime uridylation, a known signature of small RNA turnover, along with putative 3-prime trimming. Among ORF-associated siRNA pairs, sense strands showed higher relative U-tailing abundance, based on 3-prime uridylated and putatively trimmed-and-3-prime-uridylated reads relative to perfect 21-nt reads, than antisense strands. Antisense strands with the least predicted self-folding also showed low relative U-tailing abundance. These observations are consistent with sequence-dependent contributions from both guide-strand selection and differential post-RISC-loading siRNA retention, although a causal link remains to be established. The identified associations provide a basis for testing whether dsRNA sequence optimization can improve pest control efficacy and reduce off-target activity.

zoology↗