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Diffuse reflectance mid infra-red spectroscopy combined with machine learning algorithms can differentiate spectral signatures in shallow and deeper soils for the prediction of pH and organic matter content
Get PDFpeer-reviewedPrecision and sustainable agriculture requires information about soil pH and organic matter (OM) content at higher spatial and temporal scales than current agronomic sampling and analytical methods allow. This study examined the accuracy of spectral models using high throughput screening (HTS) in diffuse reflectance mode in mid Infra-red (MIR)/DRIFT combined with machine learning algorithms to predict soil pH(CaCl2) and %OM in shallow and deeper topsoils compared to laboratory methods. Models were developed from an archive of samples taken on a 4 km2 grid from the northern half of Ireland (Terra Soil project), which includes 18,859 samples (9,396 shallow + 9,463 deeper). The application of Cubist models showed that for different depths there are minor different spectral group associations with pH and %OM values. These differences resulted in a loss of accuracy in the extrapolation of the topsoil model to predict values from deeper topsoils or vice versa. Therefore we recommend the use of samples from both depths to build a calibration model.The proposed methodology was able to determine %OM and pH using a unique multivariate regression model for both depths, with RMSEP values of 1.12 and 0.89 %; RPIQ values of 42.34 and 38.48; R2val of 0.9989 and 0.9993 for %OM determinations in shallow and deeper topsoils, respectively. For pH determinations the RMSEP values obtained were 0.25 and 0.34; RPIQ values of 6.04 and 4.94; R2val 0.9385 and 0.8954. Both regression models are classified as excellent predictions models, yielding RPIQ values >4.05 for shallow and deeper topsoils. The results demonstrated the high potential of HTS-DRIFT combined with machine learning algorithms as a rapid, accurate, and cost-effective method to build large soil spectral libraries, displaying predicted results similar to two separate soil laboratory methods (pH and LOI).Geological Survey IrelandTeagas
Full Inversion Tillage (FIT) during pasture renewal as a potential management strategy for enhanced carbon sequestration and storage in Irish grassland soils
Get PDFpeer-reviewedIt has been suggested that the sequestration of CO2 by agricultural soils offers a means to reduce atmospheric greenhouse gas (GHG) concentrations and in turn mitigate the impacts of climate change. Carbon sequestration by grassland soils, which account for more than 60% of agricultural land use in Ireland, could contribute to a successful net reduction of atmospheric GHG emissions in accordance with the COP21 Paris Agreement. However, current estimates of soil carbon sequestration are variable and it is likely that many permanent grasslands are close to saturation. A literature search shows that soil carbon sequestration is enhanced by a variety of different management strategies, although one option that has only been examined to date in New Zealand is full inversion tillage (FIT) during grassland renovation. FIT involves inverting topsoil, generally to depths of 30 cm, resulting in the movement of C-deficient subsoil to the surface and the burying of carbon-rich topsoil. In this review, we hypothesise that over the next ~30 years the new topsoil could incorporate large amounts of soil organic carbon (SOC) from the re-seeded sward vegetation and that the buried carbon will be retained. We assess the current capability of Irish grassland soils to sequester carbon and suggest a potential role of FIT during grassland renovation. An analysis of the distribution of grasslands in Ireland using the Land Parcel Identification System (LPIS) suggests that ~26% of Ireland's agricultural grasslands are suitable for FIT
Inbreeding trends and genetic diversity in purebred sheep populations
Get PDFpeer-reviewedMonitoring the rate of change in inbreeding and genetic diversity within a population is important to guide breeding programmes. Such interest stems from the impact of loss in genetic diversity on sustainable genetic gain but also the impact on performance (i.e. inbreeding depression). The objective of the present study was to evaluate trends in inbreeding and genetic diversity in 43 066 Belclare, 120 753 Charollais, 22 652 Galway, 78 925 Suffolk, 187 395 Texel, and 19 821 Vendeen purebred sheep. The effective population size for each of the six breeds was between 116.0 (Belclare population) and 314.8 (Charollais population). The Charollais population was the most genetically diverse with the greatest number of effective founders, effective ancestors, and effective founder genomes; conversely, the Belclare was the least genetically diverse population with the fewest number of effective founders, effective ancestors, and effective founder genomes for each of the six breeds investigated. Overall, the effective population sizes and the total genetic diversity within each of the six breeds were above the minimum thresholds generally considered to be required for the long-term viability of a population
Diffuse reflectance mid infra-red spectroscopy combined with machine learning algorithms can differentiate spectral signatures in shallow and deeper soils for the prediction of pH and organic matter content
Get PDFpeer-reviewedTerra Soil Collaborative Agreement 2018Precision and sustainable agriculture requires information about soil pH and organic matter (OM) content at higher spatial and temporal scales than current agronomic sampling and analytical methods allow. This study examined the accuracy of spectral models using high throughput screening (HTS) in diffuse reflectance mode in mid Infra-red (MIR)/DRIFT combined with machine learning algorithms to predict soil pH(CaCl2) and %OM in shallow and deeper topsoils compared to laboratory methods. Models were developed from an archive of samples taken on a 4 km2 grid from the northern half of Ireland (Terra Soil project), which includes 18,859 samples (9,396 shallow + 9,463 deeper). The application of Cubist models showed that for different depths there are minor different spectral group associations with pH and %OM values. These differences resulted in a loss of accuracy in the extrapolation of the topsoil model to predict values from deeper topsoils or vice versa. Therefore we recommend the use of samples from both depths to build a calibration model.The proposed methodology was able to determine %OM and pH using a unique multivariate regression model for both depths, with RMSEP values of 1.12 and 0.89 %; RPIQ values of 42.34 and 38.48; R2val of 0.9989 and 0.9993 for %OM determinations in shallow and deeper topsoils, respectively. For pH determinations the RMSEP values obtained were 0.25 and 0.34; RPIQ values of 6.04 and 4.94; R2val 0.9385 and 0.8954. Both regression models are classified as excellent predictions models, yielding RPIQ values >4.05 for shallow and deeper topsoils. The results demonstrated the high potential of HTS-DRIFT combined with machine learning algorithms as a rapid, accurate, and cost-effective method to build large soil spectral libraries, displaying predicted results similar to two separate soil laboratory methods (pH and LOI)
Prevalence and levels of Campylobacter in broiler chicken batches and carcasses in Ireland in 2017–2018
Get PDFpeer-reviewedIn 2008, an EU wide baseline survey of broilers revealed a high Campylobacter prevalence. To assist with industry-wide controls, updated data were required. The primary objective of this study was to establish up-to-date data on Campylobacter carriage and carcass contamination in Irish broilers. Monthly samples were collected from the three largest broiler processing plants in Ireland over a twelve-month period. Samples were taken from both first and final thin birds (partial and full depopulation) from 358 batches of broilers. From each batch, a composite sample of 10 caecal contents (n = 358) and 5 neck skins (n = 1790) were collected and numbers of Campylobacter in each sample were determined. Of the 1790 neck skin samples tested, 53% were Campylobacter positive. Campylobacter was detected in the caecal contents of 66% of all batches tested. Depopulation and/or age had a significant effect on Campylobacter prevalence with 67% of final thin broilers yielding Campylobacter-positive neck skin samples in contrast to 38% of first thin broilers that yielded positive neck skin samples (P ≤ 0.002). A significant seasonal variation was observed in the rate of Campylobacter-positive caecal samples with higher prevalence seen in July (85%) than the colder months of November (61%), December (50%), January (61%) March (57%) and April (59%). Neck skin samples were 7 times more likely to be Campylobacter positive if the caecal contents from the same batch were positive (odds ratio = 7.1; P ≤ 0.0001). The decrease in Campylobacter prevalence observed in neck skin and caecal contents demonstrates the improvements and progress made in reducing prevalences of this important enteropathogen in the Irish poultry industry since the 2008 EU baseline survey. It also provides further supporting data on the impact of thinning, the processing environment and season on Campylobacter prevalence
Development of a syndromic surveillance system for Irish dairy cattle using milk recording data
Get PDFpeer-reviewedIn the last decade and a half, emerging vector-borne diseases have become a substantial threat to cattle across Europe. To mitigate the impact of the emergence of new diseases, outbreaks must be detected early. However, the clinical signs associated with many diseases may be nonspecific. Furthermore, there is often a delay in the development of new diagnostic tests for novel pathogens which limits the ability to detect emerging disease in the initial stages. Syndromic Surveillance has been proposed as an additional surveillance method that could augment traditional methods by detecting aberrations in non-specific disease indicators. The aim of this study was to develop a syndromic surveillance system for Irish dairy herds based on routinely collected milk recording and meteorological data. We sought to determine whether the system would have detected the 2012 Schmallenberg virus (SBV) incursion into Ireland earlier than conventional surveillance methods. Using 7,743,138 milk recordings from 730,724 cows in 7037 herds between 2007 and 2012, linear mixed-effects models were developed to predict milk yield and alarms generated with temporally clustered deviations from predicted values. Additionally, hotspot spatial analyses were conducted at corresponding time points. Using a range of thresholds, our model generated alarms throughout September 2012, between 4 and 6 weeks prior to the first laboratory confirmation of SBV in Ireland. This system for monitoring milk yield represents both a potentially useful tool for early detection of disease, and a valuable foundation for developing similar tools using other metrics
Critically important antimicrobial resistant Enterobacteriaceae in Irish farm effluent and their removal in integrated constructed wetlands
Get PDFpeer-reviewedThis study investigated the ability of Integrated Constructed Wetlands (ICWs) to remove critically important antimicrobial resistant organisms (AROs) from farm wastewater. Influent samples from the untreated farm waste and effluent samples taken at the end of the ICW system were collected monthly from four ICWs, serving four different farm types (suckler, dairy, dairy & poultry and pig). Using selective media to screen for the presence of carbapenemase resistant organisms, plasmid mediated and AmpC β-Lactamase producing organisms (ESBL/pAmpC) and fluoroquinolone resistant organisms, a total of 82 AROs were obtained with the majority being E. coli (n = 79). Statistically significant were the differences on the number of AROs isolated from influent (higher) compared to effluent, as well as a seasonal effect, with less AROs recovered during winter in comparison to other seasons (P < 0.05). On the other hand, there was no significant differences in the recovery of AROs on different farms. The majority of isolates from each of the farms (99%) were multi drug resistant, with 65% resistant to seven or more antimicrobials. A high incidence of tetracycline, trimethoprim/sulfamethoxazole, and ampicillin resistance was common to the isolates from all four farms but there were differences in ESBL levels with 63% of the isolates recovered from Farm 4 (piggery) being ESBLs compared to 18%, 36% and 4.5% recovered from Farms 1 (suckler), 2 (dairy) and 3 (dairy & poultry), respectively. No carbapenemase producing organisms were isolated. Our results showed that ICWs are effective in removing critically important AROs from farm wastewater on all four farm types
Re-assessing the importance of linear type traits in predicting genetic merit for survival in an aging Holstein-Friesian dairy cow population
Get PDFpeer-reviewedThe cumulative improvement achieved in the genetic merit for reproductive performance in dairy populations will likely improve dairy cow longevity; therefore, it is time to reassess whether linear type traits are still suitable predictors of survival in an aging dairy cow population. The objective of the present study was therefore to estimate the genetic correlations between linear type traits and survival from one parity to the next and, in doing so, evaluate if those genetic correlations change with advancing parity. After edits, 152,894 lactation survival records (first to ninth parity) were available from 52,447 Holstein-Friesian cows, along with linear type trait records from 52,121 Holstein-Friesian cows. A series of bivariate random regression models were used to estimate the genetic covariances between survival in different parities and each linear type trait. Heritability estimates for survival per parity ranged from 0.02 (SE = 0.004; first parity) to 0.05 (SE = 0.01; ninth parity). Pairwise genetic correlations between survival among different parities varied from 0.42 (first and ninth parity) to 1.00 (eighth to ninth parity), with the strength of these genetic correlations being inversely related to the interval between the compared parities. The genetic correlations between survival and the individual linear type traits varied across parities for 9 of the 20 linear type traits examined, but the correlations with only 3 of these linear type traits strengthened as the cows aged; these 3 traits were rear udder height, teat length, and udder depth. Given that linear type traits are frequently scored in first parity and are genetically correlated with survival in older parities, they may be suitable early predictors of survival, especially for later parity cows. Additionally, the direction of the genetic correlations between survival and rear udder height, teat length, and udder depth did not change between parities; hence, selection for survival in older parities using these linear type traits should not hinder genetic improvement for survival in younger parities
Pomegranate peel extract – A natural bioactive addition to novel active edible packaging
Get PDFpeer-reviewedThe pomegranate (Punica granatum L.) fruit peel has been renowned for containing high amounts of bioactive phenolic and flavonoid compounds; however, it has been commonly deemed as an agricultural waste product. The present study comprehensively reviews the impact of pomegranate peel extract as an active addition to different edible packaging materials. This review provides an overview of the recent trends and advances in active edible packaging materials enriched with pomegranate peel and their technological properties. Recently, significant advances have been made to extend the shelf life of perishable food and control the release and transport of nutraceuticals and bioactive molecules by using pomegranate fruit and its underutilized components. Pomegranate peel extract within the edible matrix provide good compatibility between peel particles and the matrix, and can enhance structural, mechanical, and biochemical properties such as antioxidant and phenolic content as well as antimicrobial activity. The addition of pomegranate peel extract in an edible matrix and applied to food products could also assist in the retardation of natural pigments, lipid oxidation, microbial contamination and influence shelf life by sustaining organoleptic properties of food products. However, more studies are needed to investigate practical implications related to the effects of pomegranate peel extract on the optical, physical and barrier properties of edible films and coatings
Impact of Cattle Feeding Strategy on the Beef Metabolome
Get PDFpeer-reviewedThe present study explored changes in the meat metabolome of animals subjected to
different finishing systems and growth rates. Thirty-six Angus × Nellore crossbred steers were used
in a completely randomized design with four treatments: (1) feedlot system with high average daily
gain (ADG; FH); (2) feedlot system with low ADG (FL); (3) pasture system with high ADG (PH); and
(4) pasture system with low ADG (PL). After harvest and chilling, Longissimus thoracis (LT) muscle
samples were taken for metabolite profile analysis using nuclear magnetic resonance. Spectrum
was analyzed using chenomx software, and multi- and mega-variate data analyses were performed.
The PLS-DA showed clear separation between FH and PL groups and overlap among treatments
with different finishing systems but similar for matching ADG (FL and PH) treatments. Using a VIP
cut-off of around 1.0, ATP and fumarate were shown to be greater in meat from PL cattle, while
succinate, leucine, AMP, glutamate, carnosine, inosine, methionine, G1P, and choline were greater
in meat from FH. Comparing FL and PH treatments, glutamine, carnosine, urea, NAD+, malonate,
lactate, isoleucine, and alanine were greater in the meat of PH cattle, while G6P and betaine were
elevated in that of FL cattle. Relevant pathways were also identified by differences in growth rate
(FH versus PL) and finishing system were also noted. Growth rate caused a clear difference in meat
metabolism that was highlighted by energy metabolism and associated pathways, while the feeding
system tended to alter protein and lipid metabolism