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T-Stór is Teagasc’s Open Access Repository, maintained by the Teagasc Library Service. Stór is the Gaelic word for Repository or Store or Warehouse, and T-Stór is an online “store” of Teagasc Research outputs and related documents. T-Stór collects preserves and makes freely available scholarly communication, including peer-reviewed articles, working papers and conference papers created by Teagasc researchers. Where material has already been published it is made available subject to the open-access policies of the original publishers. About Teagasc
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WO 2018/114971 A1 A method for producing beadsThe current invention relates to a method for producing beads. In particular, the current invention relates to a method for producing microbeads. The invention also relates to a microbead preparation produced by the method of the invention.
AgriBenchmark: Benchmarking Sustainable Nutrient Management on Irish FarmsAgriBenchmark explored the possibilities for benchmarking of nutrient management performance on Irish farms. Teagasc National Farm Survey (NFS) data (2008–2015; 1446 farms) were used to characterise and explore the potential for improvement of farm nutrient management performance and resultant aspects of environmental and economic sustainability through the derivation of three key performance indicators (KPIs) at the farm-gate level: farm nutrient balance (kgha–1), nutrient use efficiency (NUE; %) and profitability (gross margin; €ha–1). In this report, the farm nutrient balance is defined as the farm-gate nutrient imports (fertiliser, feed, animals, etc.) minus the exports (animals, crops, wool and milk). A positive balance (surplus) is considered to represent a nutrient source pressure in terms of the risk of nutrient losses to the wider environment. The data and analyses in this report cover the main, more intensive agricultural systems in Ireland (excluding pig and poultry farms) and are representative of, on average, 61% of farms nationally and 76% of the total utilised agriculture area (UAA; excluding commonage).
Associations between postpartum fertility phenotypes and genetic traits in seasonal-calving, pasture-based lactating dairy cowsThe objective of this study was to evaluate the associations between corpus luteum (CL) status, uterine health, body condition score (BCS), metabolic status, and parity at wk 3 and 7 postpartum in seasonal-calving, pasture-based, lactating dairy cows. The associations between those phenotypes and individual genetic traits were also evaluated. First- and second-parity spring-calving lactating dairy cows (n = 2,600) from 35 dairy farms in Ireland were enrolled. Farms were visited every 2 weeks; cows that were at wk 3 (range 14 to 27 DIM) and wk 7 (range 42 to 55 DIM) postpartum were examined. Body condition score was measured using a scale of 1 to 5 with 0.25 increments. Transrectal ultrasound examination was performed at wk 3 and 7 postpartum to determine presence or absence of CL and ultrasound reproductive tract score. Blood samples were collected at each visit and the concentrations of glucose, β-hydroxybutyrate (BHB), and fatty acids (FA) were analyzed by using enzymatic colorimetry. Cows were grouped into 3 BCS categories [low (≤2.5), target (≥2.75 and ≤3.25), and high (≥3.5)]; 2 CL status categories: (present or absent); 2 uterine health status (UHS) categories (normal and abnormal); and 3 metabolic status categories [good (high glucose, low fatty acids and BHB), poor (low glucose, high fatty acids and BHB), and moderate (all other combinations)]. Fisher's exact test was used to test associations between variables and was supplemented by logistic regression. We found associations between UHS (wk 3 and 7), BCS (wk 3 and 7), parity (wk 3 and 7) metabolic status (wk 3), and predicted transmitting ability for calving interval (PTA for CIV; wk 3) and CL status. Cows that had abnormal UHS, low BCS, primiparity, and poor metabolic status, and were in the quartile with the greatest PTA for CIV were less likely to have had CL present at wk 3 and 7 postpartum. We also found associations between CL status (wk 3 and 7), BCS (wk 3 and 7), parity (wk 3 and 7), and PTA for CIV (wk 3) and UHS. Cows that did not have a CL present had low BCS, primiparity, and that were in the quartile with greatest PTA for CIV, had a greater risk of abnormal UHS at wk 3 and 7 postpartum. We observed strong associations between CL status, UHS, BCS, metabolic status, parity, and individual genetic traits at wk 3 and 7 postpartum in seasonal-calving, pasture-based lactating dairy cows. Achieving target BCS and good metabolic status, and selecting cows based on PTA for CIV, are all expected to increase the likelihood of hastening the resumption of estrous cyclicity and enhancing uterine health during the postpartum period.
Using a reaction‐diffusion model to estimate day respiration and reassimilation of (photo)respiredCO2in leavesMethods using gas exchange measurements to estimate respiration in the light (day respiration Rd) make implicit assumptions about reassimilation of (photo)respired CO2; however, this reassimilation depends on the positions of mitochondria. We used a reaction-diffusion model without making these assumptions to analyse datasets on gas exchange, chlorophyll fluorescence and anatomy for tomato leaves. We investigated how Rd values obtained by the Kok and the Yin methods are affected by these assumptions and how those by the Laisk method are affected by the positions of mitochondria. The Kok method always underestimated Rd. Estimates of Rd by the Yin method and by the reaction-diffusion model agreed only for nonphotorespiratory conditions. Both the Yin and Kok methods ignore reassimilation of (photo)respired CO2, and thus underestimated Rd for photorespiratory conditions, but this was less so in the Yin than in the Kok method. Estimates by the Laisk method were affected by assumed positions of mitochondria. It did not work if mitochondria were in the cytosol between the plasmamembrane and the chloroplast envelope. However, mitochondria were found to be most likely between the tonoplast and chloroplasts. Our reaction-diffusion model effectively estimates Rd, enlightens the dependence of Rd estimates on reassimilation and clarifies (dis)advantages of existing methods.
Methodological Framework for Modelling the Impact of the Agriculture to Forestry Land Use Change at the Farm Level. Data Annex: A Distributional Analysis of the Social and Private Return to Farm Afforestation, Accounting for the Cost of CarbonThere is a growing literature on the use of microsimulation models for agriculture, forestry and land use change (Richardson et al., 2014). Much of this literature addresses issues related to productivity and incomes (O’Donoghue, 2014), however consistent with an increasing global focus on sustainability, there is also increasing interest in combining analyses of both economic and environmental impacts (Ramilan et al., 2011). A sub-field of agricultural microsimulation addresses issues associated with land-use change from agriculture to forestry and vice versa (Ryan and O’Donoghue, 2019; Phimmavong & Keenan, 2020) and vice versa. The former transition is particularly important as it helps to mitigate significant carbon emissions from agriculture. This paper describes the development of a model that incorporates both economic and environmental dimensions of the land-use change from agriculture to forestry.