Heritability and genetic correlations between rumination time and production traits in Holstein dairy cows during different lactation phases

So far, rumination has been used as a proxy for monitoring dairy cow health at farm level. However, investigating its genetic aspects as well as its correlation with other important productive traits may turn this management tool into a new informative selection criterion. However, scientific evidences on genetic correlation among rumination time (RT) and milk production and milk composition are still scarce. Therefore, the objective of this study was to estimate the heritability of RT across three lactation phases and its genetic correlation with milk production, milk composition and somatic cell count (SCC). Results of our study showed that heritability for RT was 0.34 and was constant across lactation. The mean genetic correlations between RT and milk production and composition traits were 0.07 (milk production), ?0.07 (protein yield), ?0.31 (fat yield), and ?0.32 (fat/protein ratio). The mean genetic correlation between RT and the SCC was 0.05.     

Aboveground biomass,transpiration and water use efficiency in eucalypt plantation fertilized with KCl,NaCl and phonolite rock powder

Potassium has important physiological functions in eucalypt plantations, increasing their productivity when applied to soil via mineral fertilizers. There is interest in identifying alternative sources to KCl owing to its high cost and limited reserves. The aim of the study was to test the effect of replacing KCl with NaCl and phonolite rock powder. Two comparisons were made: (1) application of 283 kg ha^?1 of KCl compared with that of 2125 kg ha^?1 of phonolite rock powder (equivalent to 170 kg ha^?1 of K₂O in both treatments); (2) application of 139 kg ha^?1 of NaCl compared with that of 183 kg ha^?1 of KCl (equivalent to 2.33 kmol Na and K, respectively). Radial growth, soil water content, leaf water potential (Ψ), accumulated transpiration, stem volume and biomass increment, as well as water use efficiency (WUE) were evaluated. In the first comparison, both fertilizations presented equal values for all characteristics evaluated. In the second, the accumulated transpiration in trees fertilized with KCl was 17% higher than that in plants fertilized with NaCl. In contrast, the WUE was 20% higher in the trees fertilized with NaCl than in those fertilized with KCl, reflecting the lower water consumption for the same increment in stem volume and biomass. We conclude that phonolite rock powder and NaCl are possible substitutes for conventional K fertilization performed with KCl.

     

Synthetic Aperture Radar (SAR) images improve habitat suitability models

Context

The ability to detect ecological networks in landscapes is of utmost importance for managing biodiversity and planning corridors.

Objectives

The objective of this study was to evaluate the information provided by a synthetic aperture radar (SAR) image for landscape connectivity modeling compared to aerial photographs (APs).

Methods

We present a novel method that integrates habitat suitability derived from remote sensing imagery into a connectivity model to explain species abundance. More precisely, we compared how two resistance maps constructed using landscape and/or local metrics derived from AP or SAR imagery yield different connectivity values (based on graph theory), considering hedgerow networks and forest carabid beetle species as a model.

Results

We found that resistance maps using landscape and local metrics derived from SAR imagery improve landscape connectivity measures. The SAR model is the most informative, explaining 58% of the variance in forest carabid beetle abundance. This model calculates resistance values associated with homogeneous patches within hedgerows according to their suitability (canopy cover density and landscape grain) for the model species.

Conclusions

Our approach combines two important methods in landscape ecology: the construction of resistance maps and the use of buffers around sampling points to determine the importance of landscape factors. This study was carried out through an interdisciplinary approach involving remote sensing scientists and landscape ecologists. This study is a step forward in developing landscape metrics from satellites to monitor biodiversity.

     

Early resynchronization protocols for goats: Progestogens can be used prior to an early pregnancy diagnosis without affecting corpus luteum functionality

This study aimed to evaluate the exogenous progesterone (P4) effect on the luteal function from Day 16 to Day 21 of the oestrous cycle in inseminated goats with unknown pregnancy status. A total of 54 does passed through a short progestin-based synchronization protocol and, on Day 16 of the following oestrous cycle, 27 does received a new P4 device which was retained until Day 21. Blood samples were collected daily from all does during this period, as well as on Day 24. Pregnancy diagnoses were performed on Day 30. Serum P4 values from 26 animals (G_NPSP: Group of non-pregnant does with second sponge: n = 8; G_NPNSP: Group of non-pregnant does without second sponge: n = 6; G_PSP: Group of pregnant does with second sponge: n = 5; G_PNSP: Group of pregnant does without second sponge: n = 7) were determined by radioimmunoassay commercial kits. No P4 differences were found between groups (G_NPSP: 3.1 ± 2.8; 1.7 ± 1.8; 0.4 ± 1.0; and 0.0 ± 0.0 vs. G_NPNSP: 4.4 ± 1.8; 3.0 ± 2.2; 0.8 ± 0.8; and 0.0 ± 0.0 or G_PSP: 4.2 ± 1.0; 3.4 ± 0.6; 3.3 ± 1.6; 3.2 ± 0.9; 3.6 ± 1.2; 3.5 ± 1.3; 2.7 ± 1.3 vs. G_PNSP: 4.4 ± 1.6; 3.6 ± 1.5; 3.7 ± 1.5; 3.8 ± 1.4; 3.2 ± 1.2; 3.1 ± 1.2; 3.6 ± 1.1; D16, D17, D18, D19, D20, D21, D24, respectively) or for the interaction of group and time. In conclusion, a second progestogen device had no effect on luteolysis or early pregnancy in the following oestrous cycle.     

Jack beans and vetiver grass growth on iron ore tailing sediments from the Doce River dam disaster in Brazil: plant growth regulator effects under different edaphic conditions

Journal of Soils and Sediments - After the greatest environmental disaster in the history of Brazil and the deposition of the iron ore tailings in alluvial regions, the process of revegetation for...     

Unravelling the relationship between a seasonal environment and the dynamics of forage growth in grazed swards

It is well reported in the scientific literature that pastures can have similar net forage accumulation when managed with contrasting structures. However, we hypothesized that the dynamics of forage accumulation in grazed swards is linked to seasonal-environmental conditions. Marandu palisadegrass (Brachiaria brizantha [Hochst. ex A. Rich.] was used as the forage species model. The experimental treatments were four grazing heights (10, 20, 30 and 40 cm) allocated to experimental units according to a randomized complete block design with four replicates and evaluated throughout four contrasting environmental seasons (summer, autumn, winter–early spring and late spring). Under rainy and warm periods, greater net forage accumulation was observed in pastures maintained taller; on the contrary, during the mild and dry periods, net forage accumulation rate reduced as grazing height increased. Such patterns of responses were related to compensations between tiller population density and tissues flows during summer and late spring and the reduced capacity of taller canopies to compensate lower population with greater growth rates during autumn and winter–early spring. Grazed swards changed their patterns of forage growth as they transitioned from favourable to more abiotic stressful conditions, suggesting that seasonal adjustments in grazing intensities are necessary in order to maximize forage production.     

Determination of Energy Use Efficiency of some Apple (<Emphasis Type="Italic">Malus x domestica</Emphasis>) Production in Turkey: a Case Study of Eğirdir Region

This research aims to make an analysis of energy use efficiency of apple (‘Starkrimson Delicious’ and ‘Golden Delicious’) production in E?irdir region of Turkey, during the production season of 2012. Production data this research was collected in 2013. In order to determine the energy use efficiency of apple, various surveys have been conducted in 71 apple farms, selected through Simple Random Sampling method, located in E?irdir region of Turkey. The data have been collected through face to face questionnaires and first hand observations. The energy input and output values in apple production have been calculated as 34,703.63 MJ ha^?1 and 95,034 MJ ha^?1, respectively. Energy inputs consist of diesel fuel energy by 29.04?%, chemical fertilizers energy by 24.28?%, machinery energy by 15.70?%, chemical energy by 9.84?%, human labor energy by 8.54?%, electricity energy by 5.63?%, irrigation energy by 3.97?%, farmyard manure energy by 2.88?% and lime energy by 0.12?%. Energy use efficiency, energy productivity, specific energy and net energy in apple production have been calculated as 2.74, 1.16 kg MJ^?1, 0.86 MJ kg^?1 and 60,330.36 MJ ha^?1, respectively. The total energy input consumed has been classified as direct, by 47.17?%, indirect, by 52.83?%, renewable, by 15.38?% and non-renewable, by 74.62?%.     

Environmental drivers of community diversity in a neotropical urban landscape: a multi-scale analysis

Context

Many aquatic communities are linked by the aerial dispersal of multiple, interacting species and are thus structured by processes occurring in both the aquatic and terrestrial compartments of the ecosystem.

Objectives

To evaluate the environmental factors shaping the aquatic macroinvertebrate communities associated with tank bromeliads in an urban landscape.

Methods

Thirty-two bromeliads were georeferenced to assess the spatial distribution of the aquatic meta-habitat in one city. The relative influence of the aquatic and terrestrial habitats on the structure of macroinvertebrate communities was analyzed at four spatial scales (radius = 10, 30, 50, and 70 m) using redundancy analyses.

Results

We sorted 18,352 aquatic macroinvertebrates into 29 taxa. Water volume and the amount of organic matter explained a significant part of the taxa variance, regardless of spatial scale. The remaining variance was explained by the meta-habitat size (i.e., the water volume for all of the bromeliads within a given surface area), the distance to the nearest building at small scales, and the surface area of buildings plus ground cover at larger scales. At small scales, the meta-habitat size influenced the two most frequent mosquito species in opposite ways, suggesting spatial competition and coexistence. Greater vegetation cover favored the presence of a top predator.

Conclusions

The size of the meta-habitat and urban landscape characteristics influence the structure of aquatic communities in tank bromeliads, including mosquito larval abundance. Modifications to this landscape will affect both the terrestrial and aquatic compartments of the urban ecosystem, offering prospects for mosquito management during urban planning.

     

Determination of Energy Input-Output Analysis in Plum (<Emphasis Type="Italic">Prunus domestica</Emphasis> L.) Production

The aim of this research is to compose the energy input-output analysis of plum in Nevsehir province in Turkey. This research was conducted at the plum cultivating facilities during the 2015–2016 production seasons in Nevsehir province of Central Anatolian Region in Turkey. The agricultural input energies and output energies used in plum cultivation were calculated to determine the energy input-output analysis. According to the research findings, the energy inputs in plum cultivation were calculated respectively 3920?MJ ha^?1 (44.99%) chemical fertilizers energy, 1618.91?MJ ha^?1 (18.58%) diesel fuel energy, 1125.85?MJ ha^?1 (12.92%) chemicals energy, 1069.20?MJ ha^?1 (12.27%) machinery energy, 723.24?MJ ha^?1 (8.30%) human labour energy and 255?MJ ha^?1 (2.93%) irrigation water energy. Production output plum yield were calculated as 12,112.50?MJ ha^?1. The energy output/input ratio, specific energy, energy usage efficiency and net energy calculations were calculated respectively as 1.39, 1.37?MJ kg^?1, 0.73?kg MJ^?1 and 3400.30?MJ ha^?1.