A Bilevel Approach to Transmission Expansion Planning Within a Market Environment

We present a bilevel model for transmission expansion planning within a market environment, where producers and consumers trade freely electric energy through a pool. The target of the transmission planner, modeled through the upper-level problem, is to minimize network investment cost while facilitating energy trading. This upper-level problem is constrained by a collection of lower-level market clearing problems representing pool trading, and whose individual objective functions correspond to social welfare. Using the duality theory the proposed bilevel model is recast as a mixed-integer linear programming problem, which is solvable using branch-and-cut solvers. Detailed results from an illustrative example and a case study are presented and discussed. Finally, some relevant conclusions are drawn.

Effects of postbreeding gonadotropin treatments on conception rates of lactating dairy cows subjected to timed artificial insemination or embryo transfer in a tropical environment

The objective of experiment 1 was to evaluate the effects of treatments with human chorionic gonadotropin (hCG) or GnRH 7 d after induced ovulation on reproductive performance of lactating dairy cows submitted to timed artificial insemination (TAI) or timed embryo transfer (TET). A total of 834 potential breedings were used from 661 lactating Holstein cows (37.3 +/- 0.3 kg of milk/d). Cows had ovulation synchronized and were assigned randomly to receive TAI on d 0 or TET on d 7. Within each group, cows were assigned randomly to receive on d 7 no additional treatment (control; n(TAI) = 156; n(TET) = 126), a 100 mu g i.m. injection of GnRH (n(TAI) = 155; n(TET) = 124), or a 2,500 TU i.m. injection of hCG (ITA = 151; n(TET) = 122). Postbreeding treatment affected the percentages of pregnant cows at TET on d 28 (control: 38.1%; GnRH: 52.4%; hCG: 45.1%) and on d 60 (control: 32.5%; GnRH: 41.1%; hCG: 38.5%), but postbreeding treatment did not affect percentages of pregnant cows at TAT on d 28 (control: 30.1%; GnRH: 32.2%; hCG: 32.4%) or on d 60 (control: 25.6%; GnRH: 27.1%; hCG: 29.8%). The objective of experiment 2 was to evaluate the effect of a treatment with GnRH 7 d after TET on reproductive performance of lactating dairy cows that received a previous GnRH treatment at TET. A total of 285 potential breedings were used from 257 lactating Holstein cows (35.1 +/- 0.8 kg of milk/d). Cows had ovulation synchronized and were assigned for TET on d 7. Immediately after TET, all cows were treated with a 100 mu g i.m. injection of GnRH. on d 14, cows were assigned randomly to receive (G7-14; n = 147) or not (G7; n = 138) an additional injection of GnRH. Pregnancy diagnosis were performed on d 28 and 60. The additional treatment with GnRH on d 14 did not affect the percentages of pregnant cows on d 28 (G7: 48.5%; G7-14: 42.9%) or on d 60 (G7: 39.8%; G7-14: 37.4%). In conclusion, treatment with GnRH or hCG 7 d after induced ovulation increased conception rates in lactating dairy cows submitted to TET, but not in cows submitted to TAI. Moreover, treatment with GnRH 7 d after TET did not enhance reproductive performance of lactating dairy cows that received a previous GnRH treatment at TET.

Genotype x environment interaction for age at first calving in Brazilian and Colombian Holsteins

The objective was to determine whether there is a genotype x environment interaction for age at first calving (AFC) in Holstein cattle in Brazil and Colombia. Data included 51,239 and 25,569 first-lactation records from Brazil and Colombia, respectively. Of 4230 sires in the data, 530 were North American sires used in both countries. Analyses were done using the REML bi-trait animal model, and AFC was considered as a distinct characteristic in each country. Fixed effects of contemporary group (herd-calving year), sire genetic group, and cow genetic group, and random effects of animal and residual variation were included in the model. Average AFC in Brazil and Colombia were 29.5 ± 4.0 and 32.1 ± 3.5 mo, respectively. Additive and residual genetic components and heritability coefficient for AFC in Brazil were 2.21 mo 2, 9.41 mo 2, and 0.19, respectively, whereas for Colombia, they were 1.02 mo 2, 6.84 mo 2, and 0.13, respectively. The genetic correlation of AFC between Brazil and Colombia was 0.78, indicating differences in ranking of sires consistent with a genotype x environment interaction. Therefore, in countries with differing environments, progeny of Holstein sires may calve at relatively younger or older ages compared with contemporary herdmates in one environment versus another.

Thermoeconomic model considering the environment impacts on thermoelectric power plants: Natural gas versus diesel

In this paper a comparative analysis of the environmental impact caused by the use of natural gas and diesel in thermoelectric power plants utilizing combined cycle is performed. The objective is to apply a thermoeconomical analysis in order to compare the two proposed fuels. In this analysis, a new methodology that incorporates the economical engineering concept to the ecological efficiency once Cardu and Baica [1, 2], which evaluates, in general terms, the environmental impacts caused by CO2, SO2, NOx and Particulate Matter (PM), adopting as reference the air quality standards in vigour is employed. The thermoeconomic model herein proposed utilizes functional diagrams that allow the minimization the Exergetic Manufacturing Cost, which represents the cost of production of electricity incorporating the environmental impact effects to study the performance of the thermoelectric power plant [3,4], It follows that it is possible to determine the environmental impact caused by thermoelectric power plants and, under the ecological standpoint, the use of natural gas as a fuel is the best option compared to the use of the diesel, presenting ecological efficiency values of 0.944 and 0.914 respectively. From the Exergoeconomic point of view of, it was found out that the EMC (Exergetic Manufacturing Cost) is better when natural gas is used as fuel compared to the diesel fuel. Copyright © 2006 by ASME.

Buffalo milk production in brazil and colombia: Genotype by environment interaction

The objective of this study was to determine whether there is a genotype by environment interaction (GxE) for dairy buffaloes in Brazil and Colombia. The (co)variance components were estimated by using a bi-trait repeatability animal model with the REML method. Each trait consisted in the milk yield obtained in both countries. Contemporary group (herd, year and season of parity) and age at parity (linear and quadratic covariate) fixed effects, along with the additive genetic, permanent environment, and the residual random effects were included in the model. Genetic, permanent environmental and residual variance and heritabilities were different for both countries. The genetic correlations for milk yield between Brazil and Colombia were low (between 0.10 and 0.13), indicating a GxE interaction between both countries. Knowing that this interaction influences the genetic progress of buffalo populations in Brazil and Colombia, we recommend choosing sires tested in the country they will be used, along with conducting joint genetic evaluations that consider GxE interaction effects.

Genotype by environment interaction in different birth seasons for weight at 240, 365 and 450 days of age in Tabapuã cattle

The objective of this study was to evaluate the effect of genotype by environment interaction (GEI) on the weight of Tabapuã cattle at 240 (W240), 365 (W365) and 450 (W450) days of age. In total, 35,732 records of 8,458 Tabapuã animalswhich were born in the state of Bahia, Brazil, from 1975 to 2001, from 167 sires and 3,707 dams, were used. Two birth seasons were tested as for the environment effect: the dry (D) and rainy (R) ones. The covariance components were obtainedby a multiple-trait analysis using Bayesian inference, in which each trait was considered as being different in each season. Covariance components were estimated by software gibbs2f90. As for W240, the model was comprised of contemporary groups and cow age (in classes) as fixed effects; animal and maternal genetic additive, maternal permanent environmental and residual were considered as random effects. Concerning W365 and W450, the model included only the contemporary aged cow groups as fixed effects and the genetic additive and residual effects of the animal as the random ones. The GEI was assessed considering the genetic correlation, in which values below 0.80 indicated the presence of GEI. Regarding W365 and W450, the GEI was found in both seasons. As for post-weaning weight (W240), the effect of such interaction was not observed. ©2012 Sociedade Brasileira de Zootecnia.

Genotype×production environment interaction for weaning weight in Angus populations of Brazil and Uruguay

The objective of this study was to define production environments by grouping different environmental factors and, consequently, to assess genotype by production environment interactions on weaning weight (WW) in the Angus populations of Brazil and Uruguay. Climatic conditions were represented by monthly temperature means (°C), minimum and maximum temperatures in winter and summer respectively and accumulated rainfall (mm/year). Mode in month of birth and weaning, and calf weight (kg) and age (days) at weaning were used as indicators of management conditions of 33 and 161 herds in 13 and 34 regions in Uruguay and Brazil, respectively. Two approaches were developed: (a) a bi-character analysis of extreme sub-datasets within each environmental factor (bottom and top 33% of regions), (b) three different production environments (including farms from both countries) were defined in a cluster analysis using standardized environmental factors. To identify the variables that influenced the cluster formation, a discriminant analysis was previously carried out. Management (month, age and weight at weaning) and climatic factors (accumulated rainfalls and winter and summer temperatures) were the most important factors in the clustering of farms. Bi or trivariate analyses were performed to estimate heritability and genetic correlations for WW in extreme sub-datasets within environmental factor or between clusters, using MTDFREML software. Heritability estimates of WW in the first approach ranged from 0.27 to 0.54, and genetic correlations between top and bottom sub-datasets within environmental factors, from -0.29 to 0.70. In the cluster approach, heritabilities were 0.58±0.04 for cluster 1, 0.31±0.01 for Cluster 2 and 0.40±0.02 for Cluster 3. Genetic correlations were 0.27±0.08, 0.32±0.09 and 0.33±0.09, between clusters 1 and 2, 1 and 3, and 2 and 3, respectively. Both approaches suggest the existence of genotype x environment interaction for weaning weight in Angus breed of Brazil and Uruguay. © 2012 Elsevier B.V.

NaOCl effect on biofilm produced by Staphylococcus aureus isolated from the milking environment and mastitis infected cows

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

Latent heat loss and sweat gland histology of male goats in an equatorial semi-arid environment

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Reaction norms for the study of genotype-environment interaction for growth and indicator traits of sexual precocity in Nellore cattle

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

Analysis of simple hardware efficiency for temperature measurement in agriculture and environment

This work focuses basically on the design and analysis of simple and low cost hardware systems efficiency for temperature measurement in agricultural area. The main objective is to prove quantitatively, through statistical data analysis, to what extent a simple hardware designed with inexpensive components can be used safely in the indoor temperature measurement in farm buildings, such as greenhouses, warehouse or silos. To verify the of simple hardware efficiency, its data were compared with data from measurements with a high performance LabVIEW platform. This work proved that a simple hardware based on a microcontroller and the LM35 sensor can perform well. It presented a good accuracy but a relatively low precision that can be improved when performed some consecutive signal sampling and then used its average value. Although there are many papers that explain these components, this work has the distinction of presenting a data analysis in numerical form and using high performance systems to ensure critical data comparison.