Prediction of metabolisable energy concentrations of fresh cut grass using digestibility data measured with non-pregnant non-lactating cows

Pasture-based ruminant production systems are common in certain areas of the world, but energy evaluation in grazing cattle is performed with equations developed, in their majority, with sheep or cattle fed total mixed rations. The aim of the current study was to develop predictions of metabolisable energy (ME) concentrations in fresh-cut grass offered to non-pregnant non-lactating cows at maintenance energy level, which may be more suitable for grazing cattle. Data were collected from three digestibility trials performed over consecutive grazing seasons. In order to cover a range of commercial conditions and data availability in pasture-based systems, thirty-eight equations for the prediction of energy concentrations and ratios were developed. An internal validation was performed for all equations and also for existing predictions of grass ME. Prediction error for ME using nutrient digestibility was lowest when gross energy (GE) or organic matter digestibilities were used as sole predictors, while the addition of grass nutrient contents reduced the difference between predicted and actual values, and explained more variation. Addition of N, GE and diethyl ether extract (EE) contents improved accuracy when digestible organic matter in DM was the primary predictor. When digestible energy was the primary explanatory variable, prediction error was relatively low, but addition of water-soluble carbohydrates, EE and acid-detergent fibre contents of grass decreased prediction error. Equations developed in the current study showed lower prediction errors when compared with those of existing equations, and may thus allow for an improved prediction of ME in practice, which is critical for the sustainability of pasture-based systems.

Prediction of nutrient digestibility and energy concentrations in fresh grass using nutrient composition

Improved nutrient utilization efficiency is strongly related to enhanced economic performance and reduced environmental footprint of dairy farms. Pasture-based systems are widely used for dairy production in certain areas of the world, but prediction equations of fresh grass nutritive value (nutrient digestibility and energy concentrations) are limited. Equations to predict digestible energy (DE) and metabolizable energy (ME) used for grazing cattle have been either developed with cattle fed conserved forage and concentrate diets or sheep fed previously frozen grass, and the majority of them require measurements less commonly available to producers, such as nutrient digestibility. The aim of the present study was therefore to develop prediction equations more suitable to grazing cattle for nutrient digestibility and energy concentrations, which are routinely available at farm level by using grass nutrient contents as predictors. A study with 33 nonpregnant, nonlactating cows fed solely fresh-cut grass at maintenance energy level for 50 wk was carried out over 3 consecutive grazing seasons. Freshly harvested grass of 3 cuts (primary growth and first and second regrowth), 9 fertilizer input levels, and contrasting stage of maturity (3 to 9 wk after harvest) was used, thus ensuring a wide representation of nutritional quality. As a result, a large variation existed in digestibility of dry matter (0.642-0.900) and digestible organic matter in dry matter (0.636-0.851) and in concentrations of DE (11.8-16.7 MJ/kg of dry matter) and ME (9.0-14.1 MJ/kg of dry matter). Nutrient digestibilities and DE and ME concentrations were negatively related to grass neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents but positively related to nitrogen (N), gross energy, and ether extract (EE) contents. For each predicted variable (nutrient digestibilities or energy concentrations), different combinations of predictors (grass chemical composition) were found to be significant and increase the explained variation. For example, relatively higher R(2) values were found for prediction of N digestibility using N and EE as predictors; gross-energy digestibility using EE, NDF, ADF, and ash; NDF, ADF, and organic matter digestibilities using N, water-soluble carbohydrates, EE, and NDF; digestible organic matter in dry matter using water-soluble carbohydrates, EE, NDF, and ADF; DE concentration using gross energy, EE, NDF, ADF, and ash; and ME concentration using N, EE, ADF, and ash. Equations presented may allow a relatively quick and easy prediction of grass quality and, hence, better grazing utilization on commercial and research farms, where nutrient composition falls within the range assessed in the current study.

Evaluating nitrogen utilization efficiency of nonpregnant dry cows offered solely fresh cut grass at maintenance levels

The present study aimed to identify key parameters influencing N utilization and develop prediction equations for manure N output (MN), feces N output (FN), and urine N output (UN). Data were obtained under a series of digestibility trials with nonpregnant dry cows fed fresh grass at maintenance level. Grass was cut from 8 different ryegrass swards measured from early to late maturity in 2007 and 2008 (2 primary growth, 3 first regrowth, and 3 second regrowth) and from 2 primary growth early maturity swards in 2009. Each grass was offered to a group of 4 cows and 2 groups were used in each of the 8 swards in 2007 and 2008 for daily measurements over 6 wk; the first group (first 3 wk) and the second group (last 3 wk) assessed early and late maturity grass, respectively. Average values of continuous 3-d data of N intake (NI) and output for individual cows ( = 464) and grass nutrient contents ( = 116) were used in the statistical analysis. Grass N content was positively related to GE and ME contents but negatively related to grass water-soluble carbohydrates (WSC), NDF, and ADF contents ( < 0.01), indicating that accounting for nutrient interrelations is a crucial aspect of N mitigation. Significantly greater ratios of UN:FN, UN:MN, and UN:NI were found with increased grass WSC contents and ratios of N:WSC, N:digestible OM in total DM (DOMD), and N:ME ( < 0.01). Greater NI, animal BW, and grass N contents and lower grass WSC, NDF, ADF, DOMD, and ME concentrations were significantly associated with greater MN, FN, and UN ( < 0.05). The present study highlighted that using grass lower in N and greater in fermentable energy in animals fed solely fresh grass at maintenance level can improve N utilization, reduce N outputs, and shift part of N excretion toward feces rather than urine. These outcomes are highly desirable in mitigation strategies to reduce nitrous oxide emissions from livestock. Equations predicting N output from BW and grass N content explained a similar amount of variability as using NI and grass chemical composition (excluding DOMD and ME), implying that parameters easily measurable in practice could be used for estimating N outputs. In a research environment, where grass DOMD and ME are likely to be available, their use to predict N outputs is highly recommended because they strongly improved of the equations in the current study.

A geochemical and lead isotopic record from a small pond in a remote equatorial island, Fernando de Noronha, Brazil

A 72 cm long core was collected from Lagoa da Viracao (LV), a small poind in the Fernando de Noronha island, northern Brazil. Sediments from the lower section of the core (20-72 cm depth) contain essentially mineral matter, while in the upper section (0-20 cm depth) mineral matter is mixed with organic matter. Lithogenic conservative elements - Si, Al, Fe, Ti, Co, Cr, Cu, Ba, Ga, Hf, Nb, Ni, Y, V, Zn, Zr and REE - exhibit remarkably constant values throughout the core, with concentrations similar to those of the bedrock. The vertical distribution of soluble elements - Ca, Mg, Na, K, P, Mn and Sr - is also homogeneous, but these elements are systematically depleted in relation to the bedrock. LOI, TOC, Br, Se, Hg and Pb, although showing nearly constant values in the lower section of the core, are significantly enriched in the upper section. The concentration profiles of Br and Se suggest that they may be accounted for by natural processes, related to the slight affinity of these elements for organic matter. On the other hand, the elevated levels of Hg and Pb in recent sediments may be explained by their long-range atmospheric transport and deposition. Furthermore, the isotopic composition of Pb clearly indicates that anthropogenic sources contributed to the Pb burden in the uppermost pond sediments.

Monitoring Surface Displacement of the Colby Green Retaining Pond Dams

The Colby Green is a campus expansion project which began in October of 2003. The construction would result in three new buildings, additional parking, and an elliptical 75,000-squarefoot green southeast of Mayflower Hill Drive. There were also plans for the construction of three run-off management and sediment ponds below the green, to manage flooding of the green. Three drains in the green transport water to the three retaining ponds which slowly disperse water into the surrounding environment. The ponds were created by constructing earthen dams around the drain outlets. The dams are composed of soil, cobbles, and boulders procured from the surrounding excavation site. Unfortunately, earthen dams are susceptible to many types of erosion which result in their failure. In this case the potential for clay and silt from the underlying Presumpscot Formation to mix with the soil in the earthen dams raised concerns with regards to frost action. In order to monitor the surface displacement of the dams I drove 92 poles into the ground in 8 straight lines across the faces of the dams in the fall of 2005. I returned to the sites during and after the spring thaw of 2006, to check for any signs of movement resulting from frost-heave, surface creep, or any other form of mass wasting. Fortunately, there was no recordable sign of movement in the stakes across any of the retaining ponds. The dams appear to be functioning as designed.

Investigating The Sources Of Fresh Water Affecting The Hydrological Balance Of Lakes Enriquillo And Azuei (Hispaniola) – Data Analysis

The Enriquillo and Azuei are saltwater lakes located in a closed water basin in the southwestern region of the island of La Hispaniola, these have been experiencing dramatic changes in total lake-surface area coverage during the period 1980-2012. The size of Lake Enriquillo presented a surface area of approximately 276 km2 in 1984, gradually decreasing to 172 km2 in 1996. The surface area of the lake reached its lowest point in the satellite observation record in 2004, at 165 km2. Then the recent growth of the lake began reaching its 1984 size by 2006. Based on surface area measurement for June and July 2013, Lake Enriquillo has a surface area of ~358 km2. Sumatra sizes at both ends of the record are 116 km2 in 1984 and 134 km2in 2013, an overall 15.8% increase in 30 years. Determining the causes of lake surface area changes is of extreme importance due to its environmental, social, and economic impacts. The overall goal of this study is to quantify the changing water balance in these lakes and their catchment area using satellite and ground observations and a regional atmospheric-hydrologic modeling approach. Data analyses of environmental variables in the region reflect a hydrological unbalance of the lakes due to changing regional hydro-climatic conditions. Historical data show precipitation, land surface temperature and humidity, and sea surface temperature (SST), increasing over region during the past decades. Salinity levels have also been decreasing by more than 30% from previously reported baseline levels. Here we present a summary of the historical data obtained, new sensors deployed in the sourrounding sierras and the lakes, and the integrated modeling exercises. As well as the challenges of gathering, storing, sharing, and analyzing this large volumen of data in a remote location from such a diverse number of sources.

Intra- and extracellular osmotic regulation in the hololimnetic Caridea and Anomura: a phylogenetic perspective on the conquest of fresh water by the decapod Crustacea

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Population structure of pond-raised Macrobrachium amazonicum with different stocking and harvesting strategies

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Water quality and plankton populations in an earthen polyculture pond

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Physical, chemical and microbiological aspects during the dry and rainy seasons in a pond covered by macrophyte used in aquaculture water supply

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multivariate analysis of fresh-cut carambola slices stored under different temperatures

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Dunging gutters filled with fresh water in finishing barns had no effect on the prevalence of Salmonella enterica on Brazilian swine farms

Our aim was to assess the importance of dunging gutters filled with water in finishing barns for the prevalence of pigs shedding Salmonella enterica. Some finishing barns in Brazil are provided with a dunging-gutter system which consists of a continuous water flow at the back of solid-floored adjacent pens. Because there is transfer of faecal material between adjacent pens by water in this system and the faecal-oral route of transmission is so important for enteric pathogens, we tested the hypothesis that the presence of this kind of dunging-gutter system in finishing barns affects the prevalence of slaughter-age pigs shedding salmonella organisms in their faeces. The cross-sectional study was conducted on six farms each having barns with and barns without a dunging-gutter system. Breeding, management, nutritional and seasonal factors were similar in both barns on each farm. The two systems did not differ in prevalence of pigs shedding salmonella organisms. Five S. enterica scrotypes were isolated: S. Agona, S. Javiana, S. Rissen, S. Sandiego and S. Senftenberg. (C) 2002 Elsevier B.V. B.V. All rights reserved.