Shedding Light on the Galaxy Luminosity Function

From as early as the 1930s, astronomers have tried to quantify the statistical nature of the evolution and large-scale structure of galaxies by studying their luminosity distribution as a function of redshift - known as the galaxy luminosity function (LF). Accurately constructing the LF remains a popular and yet tricky pursuit in modern observational cosmology where the presence of observational selection effects due to e.g. detection thresholds in apparent magnitude, colour, surface brightness or some combination thereof can render any given galaxy survey incomplete and thus introduce bias into the LF. Over the last seventy years there have been numerous sophisticated statistical approaches devised to tackle these issues; all have advantages -- but not one is perfect. This review takes a broad historical look at the key statistical tools that have been developed over this period, discussing their relative merits and highlighting any significant extensions and modifications. In addition, the more generalised methods that have emerged within the last few years are examined. These methods propose a more rigorous statistical framework within which to determine the LF compared to some of the more traditional methods. I also look at how photometric redshift estimations are being incorporated into the LF methodology as well as considering the construction of bivariate LFs. Finally, I review the ongoing development of completeness estimators which test some of the fundamental assumptions going into LF estimators and can be powerful probes of any residual systematic effects inherent magnitude-redshift data.Comment: 95 pages, 23 figures, 3 tables. Now published in The Astronomy & Astrophysics Review. This version: bring in line with A&AR format requirements, also minor typo corrections made, additional citations and higher rez images adde

Effect of oils sources on blood lipid parameters of commercial laying hens

The experiment was carried out to verify if total cholesterol, HDL-cholesterol and triacylglicerol plasma levels are affected when laying hens are fed rations containing different dietary oil sources. One hundred sixty 50 week-old hens, assigned to four treatments with five replicates using 8 hens per replicate were used. The experimental period was of 84 days divided in 3 cycles of 28 days each. In the last day of each cycle, blood samples of 2 hens per replicate were randomly choose and blood samples were collected. On the other hand, blood was also collected at 7 am, 11 am and 3 pm aiming to study the daily changes of these lipids. Blood lipid parameters were not affected by different dietary oil sources (p > 0.05); however, HDL-cholesterol did change during the day, giving evidence that this lipid is indeed involved in the egg yolk formation

Performance of layers fed diets containing different oils

A trial was carried out at the Animal Science Department of the Federal University of Viçosa to evaluate the performance of heavy and light layers. During four periods of twenty-eight days, 432 layers in the second production cycle, being 216 Hy Line W36 (light birds) and 216 Hy Line Brown (heavy birds), were used. A completely randomized experimental design with a 1+(4x2x2) factorial arrangement (one control treatment, four oil sources, two inclusion levels, and two genetic lines) with four replicates of six birds per experimental unit, was applied. The treatments consisted of diets containing 16.5% crude protein, formulated to supply the nutritional requirements, and the inclusion of each oil source at 2 or 4%. Soybean, canola, linseed and fish oils were used. The control diet did not contain any oil. The studied parameters were: feed intake (g/hen/day), egg production (%), egg weight (g), egg mass (g/hen/day), feed conversion ratio (kg feed /dozen of eggs and per kg eggs). Oil levels and sources did not influence egg mass, feed conversion ratio (per kg eggs and dozen eggs), or egg production. During the first three periods, independently of oil source or genetics, eggs from layers fed 4% oil were the heaviest, except for those of light birds fed soybean oil during the third period, which egg weight was similar for the 2 and 4% levels. Light layers presented lower feed intake and better feed conversion ratio (per kg eggs and dozen eggs) as compared to heavy layers, and there was no influence of the evaluated oil sources on feed intake

Cholesterol levels and nutritional composition of commercial layers eggs fed diets with different vegetable oils

This experiment aimed at evaluating the effects of the supplementation of different vegetable oils at different levels to the diet of commercial layers on egg cholesterol levels and nutritional composition (proteins, total solids, lipids, and ashes) for 112 days. Birds were distributed according to a completely randomized experimental design with 10 treatments (T1 - control; T2 - inclusion of 2.5% rapeseed oil; T3 - inclusion of 2.5% canola oil; T4 - inclusion of 2.5% soybean oil; T5 - inclusion of 5% rapeseed oil; T6 - inclusion of 5% canola oil; T7 - inclusion of 5% soybean oil; T8 - inclusion of 2.5% rapeseed oil + 2.5% soybean oil; T9 - inclusion 2.5% canola oil + 2.5% soybean oil; T10 - inclusion of 2.5% rapeseed oil + 2.5% canola oil) of six replicates of eight birds each, totaling 480 birds. Yolk cholesterol levels and nutritional composition were determined on days 20, 60 and 112 days of the experimental period. Data obtained during the experimental period were submitted to analysis of variance. Egg yolks produced by layer fed oils presented lower cholesterol levels after 20 days of inclusion in the experimental diets. on days 60 and 112, cholesterol levels were higher. It was concluded that supplementing layer diets with vegetable oils rich in polyunsaturated fatty acids does not change the nutritional composition of egg yolks. The supply of diets containing oils rich in polyunsaturated fatty acids does not reduce yolk cholesterol content.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)UNESP FMVZ Department of Animal ProductionUNESP FCA Department of Agro-industrial Management and TechnologyUNIFENAS Department of Animal ScienceUNESP FMVZ Department of Animal ProductionUNESP FCA Department of Agro-industrial Management and Technolog