Dry Matter Yield of Perennial Ryegrass Cultivars under Mechanical Cutting and Animal Grazing

Perennial ryegrass evaluation trials are essential to identifying and promoting the most productive cultivars for use at farm level to maximise sward productivity (Grogan and Gilliland 2011). Cultivar testing is predominantly conducted under simulated grazing trials to predict dry matter yield (DMY) performance under animal grazing. Previous studies have shown a high correlation in DMY between these two defoliation methods (Camlin and Stewart 1975; Creighton et al. 2010). In contrast, Binnie and Chestnutt (1991) demonstrated that swards grazed by animals had higher DMY performance than those exposed to simulated grazing managements. Animal pressures such as pulling, treading and nutrient return are not present in a simulated grazing management. The objective of this study was to determine if a relationship exists between the DMY of perennial ryegrass cultivars exposed to mechanical cutting compared to animal grazing

Utjecaj prinosa pašnjaka i pašnog obroka na kvalitetu travnjaka, unos paše i proizvodnju mlijeka.

Sixty-four Holstein-Friesian cows were randomly assigned to one of four treatments (M15, M20, H15 and H20) in a 2x2 factorial design, by considering: two pre-grazing pasture mass levels (PM, kg DM/ha): medium (M-1,600) vs. high (H-2,400); and two pasture allowance levels (PA, kg DM/cow/day): low (15) vs. high (20). Two periods (PI vs. PII) were studied. Sward density and pre-grazing sward height were higher in high compared to medium pre-grazing PM swards in PI (P<0.001, 255 vs. 235 kg DM/cm/ha and P<0.001, 14.8 vs. 10.9 cm, respectively) and PII (P<0.001, 216 vs. 196 kg DM/cm/ha and P<0.001, 14.3 vs. 13.0 cm, respectively). Lower post-grazing sward height and higher pasture utilization were obtained in low compared to high PA swards in PI (P<0.001, 4.1 vs. 4.9 cm and P<0.001, 98.8 vs. 89.9 %, respectively) and PII (P<0.001, 4.3 vs. 5.0 cm and P<0.001, 97.1 vs. 89.9 %, respectively). Pasture crude protein content and pasture organic matter digestibility were higher in medium compared to high pre-grazing PM swards in PI (P<0.001, 210 vs. 176 g/kg DM and P<0.05, 846 vs. 836 g/kg DM, respectively) and PII (P<0.05, 212 vs. 192 g/kg DM and P<0.05, 828 vs. 821 g/kg DM, respectively). This was due to higher leaf and lower dead proportions in medium than in high pre-grazing PM swards. Pasture dry matter intake (PDMI) (P<0.001, 16.5 vs. 14.7 kg DM/cow/day), milk yield (MY) (P<0.01, 23.8 vs. 22.7 kg/day) and milk solids yield (MSY) (P<0.05, 1.69 vs. 1.61 kg/cow) were higher in high compared to low PA swards in PI. Higher PDMI (P<0.001, 15.7 vs. 14.1 kg DM/cow/day), MY (P<0.001, 15.4 vs. 13.6 kg/day) and MSY (P<0.01, 1.19 vs. 1.08 kg/cow) were also found in high than in low PA swards in PII. The highest (P<0.001) milk output per ha (16,983 kg/ha) and milk solids per ha (1,268 kg/ha) were found in the group of dairy cows grazing in the M20 swards.Šezdeset četiri holštaj-frizijske krave nasumično su razvrstane u četiri skupine (M15, M20, H15 i H20), uzevši u obzir 2x2 faktorijalni dizajn s obzirom na: dvije razine prinosa pašnjaka prije napasivanja (PM, kg DM/ha) - srednja (M-1600) naprema visoka (H-2400), te dvije razine pašnog obroka (PA, kg DM / krava /dan) - niski (15) naprema visoki (20). Istražena su dva razdoblja (PI naprema PII). Između travnjaka s visokim i srednjim prinosom prije napasivanja (PM), u prvom razdoblju utvrđene su razlike s obzirom na gustoću travnjaka (P<0,001; H = 255 naprema M = 235 kg DM/cm/ha) i visinu trave (P<0,001; H = 14,8 naprema M = 10,9 cm). U drugom razdoblju, statistička značajnost i razlike između navedenih skupina iznosili su P<0,001; H = 216 naprema M = 196 kg DM/cm/ha i P<0,001; H = 14,3 naprema M = 13,0 cm. Najniža visina trave i najviša iskoristivost pašnjaka nakon napasivanja utvrđene su usporedbom niskog i visokog pašnog obroka tijekom prvog razdoblja (P<0,001; niski = 4,1 naprema visoki = 4,9 cm te P<0,001; niski = 98,8 naprema visoki = 89,9%) kao i tijekom drugog razdoblja (P<0,001; niski = 4,3 naprema visoki = 5,0 cm te P<0,001; niski = 97,1 naprema visoki = 89,9%). Sadržaj sirovih proteina i probavljivost organske tvari tijekom prvog razdoblja bili su viši kod pašnjaka sa srednjim prinosom pašnjaka prije napasivanja u odnosu na pašnjake s visokom razinom prinosa prije napasivanja (P<0,001; M = 210 naprema H = 176 g/kg DM i P<0,05; M = 846 naprema H = 836 g/kg DM. Tijekom drugog razdoblja, statistička značajnost i vrijednosti navedenih pokazatelja iznosili su (P<0,05; M = 212 naprema H = 192 g/kg DM i P<0,05; M = 828 naprema H = 821 g/kg DM). Navedeno se može pripisati većem udjelu lišća i manjem udjelu uvenule mase na pašnjacima sa srednjim prinosom prije napasivanja u odnosu na pašnjake s visokim prinosom prije napasivanja. Usporedba niskog i visokog pašnog obroka tijekom prvog razdoblja, pokazala je statistički značajne razlike za unos suhe tvari pašom (P<0,001; niski = 16,5 naprema visoki = 14,7 kg DM/krava/dnevno), proizvodnju mlijeka (P<0,01; niski = 23,8 naprema. visoki = 22,7 kg/day) te proizvodnju krute tvari mlijeka (P<0,05; niski = 1,69 naprema. visoki = 1,61 kg/krava). Tijekom drugog razdoblja, viši unos suhe tvari pašom utvrđen kod visokoga pašnog obroka u odnosu na niski pašni obrok (P<0,001; visoki = 15,7 naprema niski = 14,1 kg DM/krava/dnevno), viša je bila i proizvodnja mlijeka (P<0,001; visoki = 15,4 naprema niski = 13,6 kg/day) te proizvodnja krute tvari mlijeka (P<0,01; visoki = 1,19 naprema niski = 1,08 kg/krava). Najviša proizvodnja mlijeka po hektaru (P<0,001; 16,983 kg/ha) i krute tvari mlijeka po hektaru (1,268 kg/ha) utvrđena je kod krava koje su napasivane u skupini M20 travnjaka

Utjecaj prinosa pašnjaka i pašnog obroka na kvalitetu travnjaka, unos paše i proizvodnju mlijeka.

Sixty-four Holstein-Friesian cows were randomly assigned to one of four treatments (M15, M20, H15 and H20) in a 2x2 factorial design, by considering: two pre-grazing pasture mass levels (PM, kg DM/ha): medium (M-1,600) vs. high (H-2,400); and two pasture allowance levels (PA, kg DM/cow/day): low (15) vs. high (20). Two periods (PI vs. PII) were studied. Sward density and pre-grazing sward height were higher in high compared to medium pre-grazing PM swards in PI (P<0.001, 255 vs. 235 kg DM/cm/ha and P<0.001, 14.8 vs. 10.9 cm, respectively) and PII (P<0.001, 216 vs. 196 kg DM/cm/ha and P<0.001, 14.3 vs. 13.0 cm, respectively). Lower post-grazing sward height and higher pasture utilization were obtained in low compared to high PA swards in PI (P<0.001, 4.1 vs. 4.9 cm and P<0.001, 98.8 vs. 89.9 %, respectively) and PII (P<0.001, 4.3 vs. 5.0 cm and P<0.001, 97.1 vs. 89.9 %, respectively). Pasture crude protein content and pasture organic matter digestibility were higher in medium compared to high pre-grazing PM swards in PI (P<0.001, 210 vs. 176 g/kg DM and P<0.05, 846 vs. 836 g/kg DM, respectively) and PII (P<0.05, 212 vs. 192 g/kg DM and P<0.05, 828 vs. 821 g/kg DM, respectively). This was due to higher leaf and lower dead proportions in medium than in high pre-grazing PM swards. Pasture dry matter intake (PDMI) (P<0.001, 16.5 vs. 14.7 kg DM/cow/day), milk yield (MY) (P<0.01, 23.8 vs. 22.7 kg/day) and milk solids yield (MSY) (P<0.05, 1.69 vs. 1.61 kg/cow) were higher in high compared to low PA swards in PI. Higher PDMI (P<0.001, 15.7 vs. 14.1 kg DM/cow/day), MY (P<0.001, 15.4 vs. 13.6 kg/day) and MSY (P<0.01, 1.19 vs. 1.08 kg/cow) were also found in high than in low PA swards in PII. The highest (P<0.001) milk output per ha (16,983 kg/ha) and milk solids per ha (1,268 kg/ha) were found in the group of dairy cows grazing in the M20 swards.Šezdeset četiri holštaj-frizijske krave nasumično su razvrstane u četiri skupine (M15, M20, H15 i H20), uzevši u obzir 2x2 faktorijalni dizajn s obzirom na: dvije razine prinosa pašnjaka prije napasivanja (PM, kg DM/ha) - srednja (M-1600) naprema visoka (H-2400), te dvije razine pašnog obroka (PA, kg DM / krava /dan) - niski (15) naprema visoki (20). Istražena su dva razdoblja (PI naprema PII). Između travnjaka s visokim i srednjim prinosom prije napasivanja (PM), u prvom razdoblju utvrđene su razlike s obzirom na gustoću travnjaka (P<0,001; H = 255 naprema M = 235 kg DM/cm/ha) i visinu trave (P<0,001; H = 14,8 naprema M = 10,9 cm). U drugom razdoblju, statistička značajnost i razlike između navedenih skupina iznosili su P<0,001; H = 216 naprema M = 196 kg DM/cm/ha i P<0,001; H = 14,3 naprema M = 13,0 cm. Najniža visina trave i najviša iskoristivost pašnjaka nakon napasivanja utvrđene su usporedbom niskog i visokog pašnog obroka tijekom prvog razdoblja (P<0,001; niski = 4,1 naprema visoki = 4,9 cm te P<0,001; niski = 98,8 naprema visoki = 89,9%) kao i tijekom drugog razdoblja (P<0,001; niski = 4,3 naprema visoki = 5,0 cm te P<0,001; niski = 97,1 naprema visoki = 89,9%). Sadržaj sirovih proteina i probavljivost organske tvari tijekom prvog razdoblja bili su viši kod pašnjaka sa srednjim prinosom pašnjaka prije napasivanja u odnosu na pašnjake s visokom razinom prinosa prije napasivanja (P<0,001; M = 210 naprema H = 176 g/kg DM i P<0,05; M = 846 naprema H = 836 g/kg DM. Tijekom drugog razdoblja, statistička značajnost i vrijednosti navedenih pokazatelja iznosili su (P<0,05; M = 212 naprema H = 192 g/kg DM i P<0,05; M = 828 naprema H = 821 g/kg DM). Navedeno se može pripisati većem udjelu lišća i manjem udjelu uvenule mase na pašnjacima sa srednjim prinosom prije napasivanja u odnosu na pašnjake s visokim prinosom prije napasivanja. Usporedba niskog i visokog pašnog obroka tijekom prvog razdoblja, pokazala je statistički značajne razlike za unos suhe tvari pašom (P<0,001; niski = 16,5 naprema visoki = 14,7 kg DM/krava/dnevno), proizvodnju mlijeka (P<0,01; niski = 23,8 naprema. visoki = 22,7 kg/day) te proizvodnju krute tvari mlijeka (P<0,05; niski = 1,69 naprema. visoki = 1,61 kg/krava). Tijekom drugog razdoblja, viši unos suhe tvari pašom utvrđen kod visokoga pašnog obroka u odnosu na niski pašni obrok (P<0,001; visoki = 15,7 naprema niski = 14,1 kg DM/krava/dnevno), viša je bila i proizvodnja mlijeka (P<0,001; visoki = 15,4 naprema niski = 13,6 kg/day) te proizvodnja krute tvari mlijeka (P<0,01; visoki = 1,19 naprema niski = 1,08 kg/krava). Najviša proizvodnja mlijeka po hektaru (P<0,001; 16,983 kg/ha) i krute tvari mlijeka po hektaru (1,268 kg/ha) utvrđena je kod krava koje su napasivane u skupini M20 travnjaka

Evaluating automatic LFG f-structure annotation for the Penn-II treebank

Lexical-Functional Grammar (LFG: Kaplan and Bresnan, 1982; Bresnan, 2001; Dalrymple, 2001) f-structures represent abstract syntactic information approximating to basic predicate-argument-modifier (dependency) structure or simple logical form (van Genabith and Crouch, 1996; Cahill et al., 2003a) . A number of methods have been developed (van Genabith et al., 1999a,b, 2001; Frank, 2000; Sadler et al., 2000; Frank et al., 2003) for automatically annotating treebank resources with LFG f-structure information. Until recently, however, most of this work on automatic f-structure annotation has been applied only to limited data sets, so while it may have shown lsquoproof of conceptrsquo, it has not yet demonstrated that the techniques developed scale up to much larger data sets. More recent work (Cahill et al., 2002a,b) has presented efforts in evolving and scaling techniques established in these previous papers to the full Penn-II Treebank (Marcus et al., 1994). In this paper, we present a number of quantitative and qualitative evaluation experiments which provide insights into the effectiveness of the techniques developed to automatically derive a set of f-structures for the more than 1,000,000 words and 49,000 sentences of Penn-II. Currently we obtain 94.85% Precision, 95.4% Recall and 95.09% F-Score for preds-only f-structures against a manually encoded gold standard

A computational model of postprandial adipose tissue lipid metabolism derived using human arteriovenous stable isotope tracer data

Given the association of disturbances in non-esterified fatty acid (NEFA) metabolism with the development of Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease, computational models of glucose-insulin dynamics have been extended to account for the interplay with NEFA. In this study, we use arteriovenous measurement across the subcutaneous adipose tissue during a mixed meal challenge test to evaluate the performance and underlying assumptions of three existing models of adipose tissue metabolism and construct a new, refined model of adipose tissue metabolism. Our model introduces new terms, explicitly accounting for the conversion of glucose to glyceraldehye-3-phosphate, the postprandial influx of glycerol into the adipose tissue, and several physiologically relevant delays in insulin signalling in order to better describe the measured adipose tissues fluxes. We then applied our refined model to human adipose tissue flux data collected before and after a diet intervention as part of the Yoyo study, to quantify the effects of caloric restriction on postprandial adipose tissue metabolism. Significant increases were observed in the model parameters describing the rate of uptake and release of both glycerol and NEFA. Additionally, decreases in the model’s delay in insulin signalling parameters indicates there is an improvement in adipose tissue insulin sensitivity following caloric restriction.</p

Common risk alleles for schizophrenia within the major histocompatibility complex predict white matter microstructure

Recent research has highlighted the role of complement genes in shaping the microstructure of the brain during early development, and in contributing to common allele risk for Schizophrenia. We hypothesised that common risk variants for schizophrenia within complement genes will associate with structural changes in white matter microstructure within tracts innervating the frontal lobe. Results showed that risk alleles within the complement gene set, but also intergenic alleles, significantly predict axonal density in white matter tracts connecting frontal cortex with parietal, temporal and occipital cortices. Specifically, risk alleles within the Major Histocompatibility Complex region in chromosome 6 appeared to drive these associations. No significant associations were found for the orientation dispersion index. These results suggest that changes in axonal packing - but not in axonal coherence - determined by common risk alleles within the MHC genomic region – including variants related to the Complement system - appear as a potential neurobiological mechanism for schizophrenia

Leveraging genomic annotations and pleiotropic enrichment for improved replication rates in schizophrenia GWAS

Most of the genetic architecture of schizophrenia (SCZ) has not yet been identified. Here, we apply a novel statistical algorithm called Covariate-Modulated Mixture Modeling (CM3), which incorporates auxiliary information (heterozygosity, total linkage disequilibrium, genomic annotations, pleiotropy) for each single nucleotide polymorphism (SNP) to enable more accurate estimation of replication probabilities, conditional on the observed test statistic (“z-score”) of the SNP. We use a multiple logistic regression on z-scores to combine information from auxiliary information to derive a “relative enrichment score” for each SNP. For each stratum of these relative enrichment scores, we obtain nonparametric estimates of posterior expected test statistics and replication probabilities as a function of discovery z-scores, using a resampling-based approach that repeatedly and randomly partitions meta-analysis sub-studies into training and replication samples. We fit a scale mixture of two Gaussians model to each stratum, obtaining parameter estimates that minimize the sum of squared differences of the scale-mixture model with the stratified nonparametric estimates. We apply this approach to the recent genome-wide association study (GWAS) of SCZ (n = 82,315), obtaining a good fit between the model-based and observed effect sizes and replication probabilities. We observed that SNPs with low enrichment scores replicate with a lower probability than SNPs with high enrichment scores even when both they are genome-wide significant (p < 5x10-8). There were 693 and 219 independent loci with model-based replication rates ≥80% and ≥90%, respectively. Compared to analyses not incorporating relative enrichment scores, CM3 increased out-of-sample yield for SNPs that replicate at a given rate. This demonstrates that replication probabilities can be more accurately estimated using prior enrichment information with CM3

Online dietary intake estimation : The food4me food frequency questionnaire

Copyright ©Hannah Forster, Rosalind Fallaize, Caroline Gallagher, Clare B O’Donovan, Clara Woolhead, Marianne C Walsh, Anna L Macready, Julie A Lovegrove, John C Mathers, Michael J Gibney, Lorraine Brennan, Eileen R Gibney. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 09.06.2014. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.Dietary assessment methods are important tools for nutrition research. Online dietary assessment tools have the potential to become invaluable methods of assessing dietary intake because, compared with traditional methods, they have many advantages including the automatic storage of input data and the immediate generation of nutritional outputs. Objective: The aim of this study was to develop an online food frequency questionnaire (FFQ) for dietary data collection in the Food4Me study and to compare this with the validated European Prospective Investigation of Cancer (EPIC) Norfolk printed FFQ. Methods: The Food4Me FFQ used in this analysis was developed to consist of 157 food items. Standardized color photographs were incorporated in the development of the Food4Me FFQ to facilitate accurate quantification of the portion size of each food item. Participants were recruited in two centers (Dublin, Ireland and Reading, United Kingdom) and each received the online Food4Me FFQ and the printed EPIC-Norfolk FFQ in random order. Participants completed the Food4Me FFQ online and, for most food items, participants were requested to choose their usual serving size among seven possibilities from a range of portion size pictures. The level of agreement between the two methods was evaluated for both nutrient and food group intakes using the Bland and Altman method and classification into quartiles of daily intake. Correlations were calculated for nutrient and food group intakes. Results: A total of 113 participants were recruited with a mean age of 30 (SD 10) years (40.7% male, 46/113; 59.3%, 67/113 female). Cross-classification into exact plus adjacent quartiles ranged from 77% to 97% at the nutrient level and 77% to 99% at the food group level. Agreement at the nutrient level was highest for alcohol (97%) and lowest for percent energy from polyunsaturated fatty acids (77%). Crude unadjusted correlations for nutrients ranged between .43 and .86. Agreement at the food group level was highest for other fruits (eg, apples, pears, oranges) and lowest for cakes, pastries, and buns. For food groups, correlations ranged between .41 and .90. Conclusions: The results demonstrate that the online Food4Me FFQ has good agreement with the validated printed EPIC-Norfolk FFQ for assessing both nutrient and food group intakes, rendering it a useful tool for ranking individuals based on nutrient and food group intakes.Peer reviewedFinal Published versio

Discovery and Statistical Genotyping of Copy-Number Variation from Whole-Exome Sequencing Depth

Sequencing of gene-coding regions (the exome) is increasingly used for studying human disease, for which copy-number variants (CNVs) are a critical genetic component. However, detecting copy number from exome sequencing is challenging because of the noncontiguous nature of the captured exons. This is compounded by the complex relationship between read depth and copy number; this results from biases in targeted genomic hybridization, sequence factors such as GC content, and batching of samples during collection and sequencing. We present a statistical tool (exome hidden Markov model [XHMM]) that uses principal-component analysis (PCA) to normalize exome read depth and a hidden Markov model (HMM) to discover exon-resolution CNV and genotype variation across samples. We evaluate performance on 90 schizophrenia trios and 1,017 case-control samples. XHMM detects a median of two rare

Rare chromosomal deletions and duplications increase risk of schizophrenia

Schizophrenia is a severe mental disorder marked by hallucinations, delusions, cognitive deficits and apathy, with a heritability estimated at 73 - 90% ( ref. 1). Inheritance patterns are complex, ..