Effects of environmental and housing system factors on ammonia and greenhouse gas emissions from cattle barns: A meta-analysis of a global data collation.

This study provides a meta-analysis on the relationships between cattle barn CH4, NH3 and N2O emission rates and their key drivers (i.e., housing type, floor type, environmental conditions). Understanding these relationships is essential to reduce uncertainties in emission inventories and suggest targeted mitigation measures. The total number of daily emission rates included in the analysis was 139 for CH4, 293 for NH3 and 100 for N2O emissions. Emission rates in the database showed a large variation with 45-803.5 g/LU d-1 for CH4, 0.036-146.7 gN LU-1 d-1 for NH3, and 0.002-18 gN LU-1 d-1 for N2O emissions. Despite the high emission variability, significant effects were identified·NH3 showed positive correlation with air temperature; NH3 emissions differed between housing types but not between floor types·NH3 emissions from tied stalls were lower than the ones from cubicle housing regardless of the floor type. Additionally, NH3 emissions from loose housings were lower than the ones from cubicle housing·NH3 and N2O emission rates from temperate wet zones were lower than the ones from temperate dry zones. CH4 emission rates were affected by environmental factors only and not by housing and floor type, showing negative correlation with air temperature and humidity. The factors investigated can be suggested as ancillary variables and descriptors when cattle barn emissions are measured, in order to make best use of emission data. Country-specific data of these key drivers can be included into national inventories to adapt them to different agroecosystems and support targeted policies.

DATAMAN: A global database of methane, nitrous oxide, and ammonia emission factors for livestock housing and outdoor storage of manure.

Livestock manure management systems can be significant sources of nitrous oxide (N2 O), methane (CH4 ), and ammonia (NH3 ) emissions. Many studies have been conducted to improve our understanding of the emission processes and to identify influential variables in order to develop mitigation techniques adapted to each manure management step (animal housing, outdoor storage, and manure spreading to land). The international project DATAMAN (http://www.dataman.co.nz) aims to develop a global database on greenhouse gases (N2 O, CH4 ) and NH3 emissions from the manure management chain to refine emission factors (EFs) for national greenhouse gas and NH3 inventories. This paper describes the housing and outdoor storage components of this database. Relevant information for different animal categories, manure types, livestock buildings, outdoor storage, and climatic conditions was collated from published peer reviewed research, conference papers, and existing databases published between 1995 and 2021. In the housing database, 2024 EFs were collated (63% for NH3 , 19.5% for CH4 , and 17.5% for N2 O). The storage database contains 654 NH3 EFs from 16 countries, 243 CH4 EFs from 13 countries, and 421 N2 O EFs from 17 countries. Across all gases, dairy cattle and swine production in temperate climate zones are the most represented animal and climate categories. As for the housing database, the number of EFs for the tropical climate zone is under-represented. The DATAMAN database can be used for the refinement of national inventories and better assessment of the cost-effectiveness of a range of mitigation strategies.

High throughput pH bioassay demonstrates pH adaptation of Rhizobium strains isolated from the nodules of Trifolium subterraneum and T. repens.

The purpose of developing this high throughput assay was to determine whether there was evidence of pH adaptation in strains of rhizobia which nodulate subterranean clover (SC) and white clover (WC), and whether this was related to the pH of the soil of origin. pH is a first-order factor influencing the niche preferences of soil microorganisms and has been convincingly shown to be a key driver of soil bacterial communities. Naturalised strains of Rhizobium spp. that are pH-adapted may have the potential to better compete and/or persist in acidic or alkaline soils compared with introduced commercial strains. Three pilot studies were conducted to design the optimised bioassay. This bioassay tested the effect of pH-amended yeast mannitol broth (seven pH values from pH 4.5-9.0), across three time points, on the in vitro growth of 299 Rhizobium strains isolated from the nodules of SC and WC. The media pH where strains demonstrated fastest growth was related to the pH of the soil that strains were isolated from. However, the correlation between media pH and soil pH was strongly influenced by the growth of strains from alkaline soils (alkaline adaptation), especially in strains isolated from SC nodules.

DNA methylation analysis using bisulphite-based amplicon sequencing of individuals exposed to maternal tobacco use during pregnancy, and offspring conduct problems in childhood and adolescence.

Maternal tobacco smoking during pregnancy is a large driver of health inequalities and a higher prevalence of conduct problem (CP) has been observed in exposed offspring. Further, maternal tobacco use during pregnancy can also alter offspring DNA methylation. However, currently, limited molecular evidence has been found to support this observation. Thus we aim to examine the association between maternal tobacco use in pregnancy and offspring CP, to determine whether offspring CP is mediated by tobacco exposure-induced DNA methylation differences. Understanding the etiology of the association between maternal tobacco use and offspring CP will be crucial in the early identification and treatment of CP in children and adolescents. Here, a sub group of N =96 individuals was sourced from the Christchurch Health and Development Study, a longitudinal birth cohort studied for over 40 years in New Zealand. Whole blood samples underwent bisulphite-based amplicon sequencing at 10 loci known to play a role in neurodevelopment, or which had associations with CP phenotypes. We identified significant (P CYP1A1 , ASH2L and MEF2C in individuals with CP who were exposed to tobacco in utero . We conclude that environmentally-induced DNA methylation differences could play a role in the observed link between maternal tobacco use during pregnancy and childhood/adolescent CP. However, larger sample sizes are needed to produce an adequate amount of power to investigate this interaction further.

Ammonia and nitrous oxide emission factors for excreta deposited by livestock and land-applied manure.

Manure application to land and deposition of urine and dung by grazing animals are major sources of ammonia (NH3 ) and nitrous oxide (N2 O) emissions. Using data on NH3 and N2 O emissions following land-applied manures and excreta deposited during grazing, emission factors (EFs) disaggregated by climate zone were developed, and the effects of mitigation strategies were evaluated. The NH3 data represent emissions from cattle and swine manures in temperate wet climates, and the N2 O data include cattle, sheep, and swine manure emissions in temperate wet/dry and tropical wet/dry climates. The NH3 EFs for broadcast cattle solid manure and slurry were 0.03 and 0.24 kg NH3 -N kg-1 total N (TN), respectively, whereas the NH3 EF of broadcast swine slurry was 0.29. Emissions from both cattle and swine slurry were reduced between 46 and 62% with low-emissions application methods. Land application of cattle and swine manure in wet climates had EFs of 0.005 and 0.011 kg N2 O-N kg-1 TN, respectively, whereas in dry climates the EF for cattle manure was 0.0031. The N2 O EFs for cattle urine and dung in wet climates were 0.0095 and 0.002 kg N2 O-N kg-1 TN, respectively, which were three times greater than for dry climates. The N2 O EFs for sheep urine and dung in wet climates were 0.0043 and 0.0005, respectively. The use of nitrification inhibitors reduced emissions in swine manure, cattle urine/dung, and sheep urine by 45-63%. These enhanced EFs can improve national inventories; however, more data from poorly represented regions (e.g., Asia, Africa, South America) are needed.

DATAMAN: A global database of nitrous oxide and ammonia emission factors for excreta deposited by livestock and land-applied manure.

Nitrous oxide (N2 O), ammonia (NH3 ), and methane (CH4 ) emissions from the manure management chain of livestock production systems are important contributors to greenhouse gases (GHGs) and NH3 emitted by human activities. Several studies have evaluated manure-related emissions and associated key variables at regional, national, or continental scales. However, there have been few studies focusing on the drivers of these emissions using a global dataset. An international project was created (DATAMAN) to develop a global database on GHG and NH3 emissions from the manure management chain (housing, storage, and field) to identify key variables influencing emissions and ultimately to refine emission factors (EFs) for future national GHG inventories and NH3 emission reporting. This paper describes the "field" database that focuses on N2 O and NH3 EFs from land-applied manure and excreta deposited by grazing livestock. We collated relevant information (EFs, manure characteristics, soil properties, and climatic conditions) from published peer-reviewed research, conference papers, and existing databases. The database, containing 5,632 observations compiled from 184 studies, was relatively evenly split between N2 O and NH3 (56 and 44% of the EF values, respectively). The N2 O data were derived from studies conducted in 21 countries on five continents, with New Zealand, the United Kingdom, Kenya, and Brazil representing 86% of the data. The NH3 data originated from studies conducted in 17 countries on four continents, with the United Kingdom, Denmark, Canada, and The Netherlands representing 79% of the data. Wet temperate climates represented 90% of the total database. The DATAMAN field database is available at http://www.dataman.co.nz.

Insights in Human Hair Curvature by Proteome Analysis of Two Distinct Hair Shapes.

Scalp hair is a universal human characteristic, and a wide range of hair shape and color variations exists. Although differences in human scalp hair shape are visually apparent, the underpinning molecular insights are yet to be fully explored. This work reports the determination of differences at the protein level between two distinct groups of hair shape: very straight samples versus very curly hair samples. An in-depth highresolution liquid-chromatography mass spectrometry proteome analysis study was performed on hair samples from 50 individuals (pooled in 10 × 5 samples) with very curly hair and 50 subjects with very straight hair (pooled in 10 × 5 samples) to decipher differences between the two experimental groups at the protein level. Our results demonstrate that a distinction between the two experimental groups (very straight vs. very curly) can be made based on their overall protein profiles in a multivariate analysis approach. Further investigation of the protein expression levels between these two groups pinpointed 13 unique proteins which were found to be significantly different between the two groups, with an adjusted p-value < 0.05 and a fold change of more than two. Although differences between the very curly and the very straight hair sample groups could be identified, linkage between population differences and curl phenotype is currently unknown and requires further investigation.

Global Research Alliance N2 O chamber methodology guidelines: Statistical considerations, emission factor calculation, and data reporting.

Static chambers are often used for measuring nitrous oxide (N2 O) fluxes from soils, but statistical analysis of chamber data is challenged by the inherently heterogeneous nature of N2 O fluxes. Because N2 O chamber measurements are commonly used to assess N2 O mitigation strategies or to determine country-specific emission factors (EFs) for calculating national greenhouse gas inventories, it is important that statistical analysis of the data is sound and that EFs are robustly estimated. This paper is one of a series of articles that provide guidance on different aspects of N2 O chamber methodologies. Here, we discuss the challenges associated with statistical analysis of heterogeneous data, by summarizing statistical approaches used in recent publications and providing guidance on assessing normality and options for transforming data that follow a non-normal distribution. We also recommend minimum requirements for reporting of experimental and metadata of N2 O studies to ensure that the robustness of the results can be reliably evaluated. This includes detailed information on the experimental site, methodology and measurement procedures, gas analysis, data and statistical analyses, and approaches to generate EFs, as well as results of ancillary measurements. The reliability, robustness, and comparability of soil N2 O emissions data will be improved through (a) application, and reporting, of more rigorous methodological standards by researchers and (b) greater vigilance by reviewers and scientific editors to ensure that all necessary information is reported in scientific publications.

Global Research Alliance N2 O chamber methodology guidelines: Flux calculations.

A critical step in determining soil-to-atmosphere nitrous oxide (N2 O) exchange using non-steady-state chambers is converting collected gas concentration versus time data to flux values using a flux calculation (FC) scheme. It is well documented that different FC schemes can produce different flux estimates for a given set of data. Available schemes differ in their theoretical basis, computational requirements, and performance in terms of both accuracy and precision. Nonlinear schemes tend to increase accuracy compared with linear regression but can also decrease precision. The chamber bias correction method can be used if soil physical data are available, but this introduces additional sources of error. Here, the essential theoretical and practical aspects of the most commonly used FC schemes are described as a basis for their selection and use. A gold standard approach for application and selection of FC schemes is presented, as well as alternative approaches based on availability of soil physical property data and intensity of sample collection during each chamber deployment. Additional criteria for scheme selection are provided in the form of an error analysis tool that quantifies performance with respect to both accuracy and precision based on chamber dimensions and sampling duration, soil properties, and analytical measurement precision. Example error analyses are presented for hypothetical conditions illustrating how such analysis can be used to guide FC scheme selection, estimate bias, and inform design of chambers and sampling regimes.

ACE inhibitory peptides in standard and fermented deer velvet: an in silico and in vitro investigation.

BACKGROUND: The use of deer velvet antler (DVA) as a potent traditional medicine ingredient goes back for over 2000 years in Asia. Increasingly, though, DVA is being included as a high protein functional food ingredient in convenient, ready to consume products in Korea and China. As such, it is a potential source of endogenous bioactive peptides and of 'cryptides', i.e. bioactive peptides enzymatically released by endogenous proteases, by processing and/or by gastrointestinal digestion. Fermentation is an example of a processing step known to release bioactive peptides from food proteins. In this study, we aimed to identify in silico bioactive peptides and cryptides in DVA, before and after fermentation, and subsequently to validate the major predicted bioactivity by in vitro analysis. METHODS: Peptides that were either free or located within proteins were identified in the DVA samples by liquid chromatography-tandem mass spectrometry (LC-MS/MS) followed by database searching. Bioactive peptides and cryptides were identified in silico by sequence matching against a database of known bioactive peptides. Angiotensin-converting enzyme (ACE) inhibitory activity was measured by a colorimetric method. RESULTS: Three free bioactive peptides (LVVYPW, LVVYPWTQ and VVYPWTQ) were solely found in fermented DVA, the latter two of which are known ACE inhibitors. However matches to multiple ACE inhibitor cryptides were obtained within protein and peptide sequences of both unfermented and fermented DVA. In vitro analysis showed that the ACE inhibitory activity of DVA was more pronounced in the fermented sample, but both unfermented and fermented DVA had similar activity following release of cryptides by simulated gastrointestinal digestion. CONCLUSIONS: DVA contains multiple ACE inhibitory peptide sequences that may be released by fermentation or following oral consumption, and which may provide a health benefit through positive effects on the cardiovascular system. The study illustrates the power of in silico combined with in vitro methods for analysis of the effects of processing on bioactive peptides in complex functional ingredients like DVA.

A new haplotype of the coconut rhinoceros beetle, Oryctes rhinoceros, has escaped biological control by Oryctes rhinoceros nudivirus and is invading Pacific Islands.

The coconut rhinoceros beetle (CRB; Oryctes rhinoceros) is a major pest of coconut and oil palm, but the discovery and release of Oryctes rhinoceros nudivirus (OrNV) in the 1960s and 70s suppressed the pest such that no new invasions of uninfested islands by CRB were reported for over 30years after implementation of the biocontrol programme. Surprisingly, a highly damaging outbreak was reported from Guam (2007), which could not be controlled by OrNV. Subsequently, new invasions have been reported from Port Moresby, Papua New Guinea (2009); O'ahu, Hawai'i (2013); and Honiara, Solomon Islands (2015). We have found that all of these outbreaks have been caused by a previously unrecognized haplotype, CRB-G, which appears to be tolerant to OrNV. PCR analysis shows that OrNV is generally present at high incidence in established populations of CRB, but is generally absent from the invasive CRB-G populations. CRB-G from Guam was not susceptible to OrNV infection by oral delivery, but injection of the virus did cause mortality. Further genetic analysis shows that CRB populations can be divided into a number of clades that coincide with the endemic and invasive history of the beetle. Analysis suggests that CRB-G originated in Asia, though the precise location remains to be discovered.

Starch phosphorylation in potato tubers is influenced by allelic variation in the genes encoding glucan water dikinase, starch branching enzymes I and II, and starch synthase III.

Starch phosphorylation is an important aspect of plant metabolism due to its role in starch degradation. Moreover, the degree of phosphorylation of starch determines its physicochemical properties and is therefore relevant for industrial uses of starch. Currently, starch is chemically phosphorylated to increase viscosity and paste stability. Potato cultivars with elevated starch phosphorylation would make this process unnecessary, thereby bestowing economic and environmental benefits. Starch phosphorylation is a complex trait which has been previously shown by antisense gene repression to be influenced by a number of genes including those involved in starch synthesis and degradation. We have used an association mapping approach to discover genetic markers associated with the degree of starch phosphorylation. A diverse collection of 193 potato lines was grown in replicated field trials, and the levels of starch phosphorylation at the C6 and C3 positions of the glucosyl residues were determined by mass spectrometry of hydrolyzed starch from tubers. In addition, the potato lines were genotyped by amplicon sequencing and microsatellite analysis, focusing on candidate genes known to be involved in starch synthesis. As potato is an autotetraploid, genotyping included determination of allele dosage. Significant associations (p < 0.001) were found with SNPs in the glucan water dikinase (GWD), starch branching enzyme I (SBEI) and the starch synthase III (SSIII) genes, and with a SSR allele in the SBEII gene. SNPs in the GWD gene were associated with C6 phosphorylation, whereas polymorphisms in the SBEI and SBEII genes were associated with both C6 and C3 phosphorylation and the SNP in the SSIII gene was associated with C3 phosphorylation. These allelic variants have potential as genetic markers for starch phosphorylation in potato.

Bayesian estimation of the sensitivity and specificity of individual fecal culture and Paralisa to detect Mycobacterium avium subspecies paratuberculosis infection in young farmed deer.

A Bayesian latent class model was used to estimate the sensitivity and specificity of an immunoglobulin G1 serum enzyme-linked immunosorbent assay (Paralisa) and individual fecal culture to detect young deer infected with Mycobacterium avium subsp. paratuberculosis. Paired fecal and serum samples were collected, between July 2009 and April 2010, from 20 individual yearling (12-24-month-old) deer in each of 20 South Island and 18 North Island herds in New Zealand and subjected to culture and Paralisa, respectively. Two fecal samples and 16 serum samples from 356 North Island deer, and 55 fecal and 37 serum samples from 401 South Island deer, were positive. The estimate of individual fecal culture sensitivity was 77% (95% credible interval [CI] = 61-92%) with specificity of 99% (95% CI = 98-99.7%). The Paralisa sensitivity estimate was 19% (95% CI = 10-30%), with specificity of 94% (95% CI = 93-96%). All estimates were robust to variation of priors and assumptions tested in a sensitivity analysis. The data informs the use of the tests in determining infection status at the individual and herd level.

Assigning the source of human campylobacteriosis in New Zealand: a comparative genetic and epidemiological approach.

Integrated surveillance of infectious multi-source diseases using a combination of epidemiology, ecology, genetics and evolution can provide a valuable risk-based approach for the control of important human pathogens. This includes a better understanding of transmission routes and the impact of human activities on the emergence of zoonoses. Until recently New Zealand had extraordinarily high and increasing rates of notified human campylobacteriosis, and our limited understanding of the source of these infections was hindering efforts to control this disease. Genetic and epidemiological modeling of a 3-year dataset comprising multilocus sequence typed isolates from human clinical cases, coupled with concurrent data on food and environmental sources, enabled us to estimate the relative importance of different sources of human disease. Our studies provided evidence that poultry was the leading cause of human campylobacteriosis in New Zealand, causing an estimated 58-76% of cases with widely varying contributions by individual poultry suppliers. These findings influenced national policy and, after the implementation of poultry industry-specific interventions, a dramatic decline in human notified cases was observed in 2008. The comparative-modeling and molecular sentinel surveillance approach proposed in this study provides new opportunities for the management of zoonotic diseases.

Source attribution of food-borne zoonoses in New Zealand: a modified Hald model.

A Bayesian approach was developed by Hald et al.((1)) to estimate the contribution of different food sources to the burden of human salmonellosis in Denmark. This article describes the development of several modifications that can be used to adapt the model to different countries and pathogens. Our modified Hald model has several advantages over the original approach, which include the introduction of uncertainty in the estimates of source prevalence and an improved strategy for identifiability. We have applied our modified model to the two major food-borne zoonoses in New Zealand, namely, campylobacteriosis and salmonellosis. Major challenges were the data quality for salmonellosis and the inclusion of environmental sources of campylobacteriosis. We conclude that by modifying the Hald model we have improved its identifiability, made it more applicable to countries with less intensive surveillance, and feasible for other pathogens, in particular with respect to the inclusion of nonfood sources. The wider application and better understanding of this approach is of particular importance due to the value of the model for decision making and risk management.