Survival of white, red and alsike clover at pasture under Nordic organic farming conditions

White clover suited best for cow grazing under organic farming conditions in Middle Finland. However, the clover proportion of all clover mixtures decreased from year to year and varied within grazing season

Annual and seasonal changes in mineral contents (Ca, Mg, P, K and Na) of grazed clover-grass mixtures in organic farming

A grazed field experiment was established in 1995 to evaluate alsike clover (Trifoliun hybridum L.), red clover (Trifolium pratense L.) and white clover (Trifolium repens L.) in clover-grass mixtures under organic farming practices. In this study the effect of seed mixture (alsike clover, red clover, white clover, white and alsike clover or grass mixture), year (1997, 1998) and grazing period (5 per grazing season) on the herbage calcium (Ca), magnesium (Mg), potassium (K) phosphorous (P) and sodium (Na) contents was assessed and the relationships between botanical proportions and herbage mineral contents were studied. Herbage Ca and Na contents varied between the seed mixtures, Ca, Mg, P and Na contents between the years and all measured minerals, except Na, between the grazing periods. The white clover mixture resulted in higher Ca and Na contents. The contents of Ca and Mg were positively related with the proportions of clovers and weeds and were higher in 1997. The contents of P and K were higher in the rainy summer of 1998. The seed mixtures resulted in similar mean K/(Ca + Mg) equivalent ratios, but the Ca/P ratio was higher for the white clover mixture. Mineral rations varied between and within grazing seasons. Under organic practices the supply of minerals in the pasture herbage varied temporally and according to the botanical contents and was unable to meet fully the requirements of dairy cows. Additional mineral feeding is recommended for organic farming systems to balance the dietary mineral contents for grazing cows

Grazing management for Nordic organic dairy farming

The aims of this study were to identify limiting factors and to develop adjusted grazing management for Nordic organic dairy farming conditions. The focus was to combine the aspects of plant, animal and organic production, as they are all involved in organic dairy pastures

Annual and seasonal changes in production and composition of grazed clover-grass mixtures in organic farming

A grazed field experiment based on a randomised block design was conducted in Eastern Finland to evaluate the potential of alsike clover (Trifoliun hybridum L.), red clover (Trifolium pratense L.) and white clover (Trifolium repens L.) to support herbage production from clover-grass mixtures under organic farming practices. The effect of seed mixture (alsike clover, red clover, white clover, white and alsike clover or grass mixture), year (1996, 1997 and 1998) and grazing period (5 per grazing season) on pre- and post-grazing herbage mass (HM), botanical and chemical composition of pregrazing HM and post-grazing sward height was assessed. The nutritive value of herbage for milk production was also considered. Seed mixtures resulted in different pre-grazing HM and post-grazing sward heights, but similar pre- minus post-grazing HM. Compared with other mixtures, the proportion of clover was higher for white clover based mixtures. The white clover mixture had the highest crude protein content and lowest concentrations of cellulose and hemicellulose. In addition to seed mixture, the effect of year and grazing period on measured parameters was significant, highlighting the importance of grazing management. Moderate pasture herbage production of relative high nutritive value was achieved under organic practices, but the supply and nutritive value of herbage was variable and, in some cases, unable to meet the requirements of lactating dairy cows. The proportion of clover in all seed mixtures decreased year on year, and was subject to seasonal variations that altered the nutritional value of herbage. White clover was the most suitable perennial clover for pastures in Eastern Finland

Statistical unfolding of elementary particle spectra: Empirical Bayes estimation and bias-corrected uncertainty quantification

We consider the high energy physics unfolding problem where the goal is to estimate the spectrum of elementary particles given observations distorted by the limited resolution of a particle detector. This important statistical inverse problem arising in data analysis at the Large Hadron Collider at CERN consists in estimating the intensity function of an indirectly observed Poisson point process. Unfolding typically proceeds in two steps: one first produces a regularized point estimate of the unknown intensity and then uses the variability of this estimator to form frequentist confidence intervals that quantify the uncertainty of the solution. In this paper, we propose forming the point estimate using empirical Bayes estimation which enables a data-driven choice of the regularization strength through marginal maximum likelihood estimation. Observing that neither Bayesian credible intervals nor standard bootstrap confidence intervals succeed in achieving good frequentist coverage in this problem due to the inherent bias of the regularized point estimate, we introduce an iteratively bias-corrected bootstrap technique for constructing improved confidence intervals. We show using simulations that this enables us to achieve nearly nominal frequentist coverage with only a modest increase in interval length. The proposed methodology is applied to unfolding the $Z$ boson invariant mass spectrum as measured in the CMS experiment at the Large Hadron Collider.Comment: Published at http://dx.doi.org/10.1214/15-AOAS857 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org). arXiv admin note: substantial text overlap with arXiv:1401.827

Effect of selenite and selenised yeast supplementation on selenium concentration of Finnish organic milk – a farm study.

Experiment was conducted at 15 certified organic dairy farms in Eastern Finland during spring 2008. Farms were allocated to three balanced groups according annual milk yield, herd size and housing system. Three types of selenium (Se) supplementations: selenium yeast (SY), sodium selenite (SS) or their (50:50) combination (SYS) was used. Daily Se doses were adjusted according to milk yield basis (average 3 mg/d). Experimental model was 3 X 3 Latin square, consisting from 3 experiment periods. The length of each period was 28 days. RehuRaisio provided experimental feeds. In the end of each period bulk-tank milk samples were collected and analysed for Se at MTT Agrifood Research Finland. The Se supplementation form was crucial for milk Se concentration (P<0.001), when Se concentration of basic fodder was extreme low (<0.01 mg/kg DM). SS (n=15) resulted to milk Se concentration of 0.012 mg/kg, but SYS (n=15) resulted to 1.9-fold and SY (n=14) to 2.3-fold higher milk Se concentrations