Fertility of Holstein cows and heifers submitted to timed artificial insemination and receiving one or two doses (12 h apart) of semen

The objective of this retrospective study was to assess the effect of receiving a single (n = 50,285) or double (n = 4392) artificial insemination (AI), 12 h apart, within a timed artificial insemination protocol on pregnancy per AI (P/AI) in nulliparous heifers (inseminated with either sex-sorted or conventional semen) and pluriparous Holstein cows in a commercial dairy herd. Also, this study aimed to investigate the relationship between temperature-humidity index (THI) and time of the first AI and fertility. Fertility of cows receiving two AI with normothermia (THI <68) was higher (p < .05) than cows receiving a single AI (42.9% vs. 36.4%). P/AI of cows receiving two AI with severe heat stress (THI >85) was higher (p < .05) than cows receiving a single AI (21.0% vs. 12.6%). Regardless of heat stress conditions, applying the first AI in the morning increased (p < .05) P/AI in cows with double AI than in cows whose first AI occurred in the afternoon (38.4 vs. 33.3%). With moderate heat stress, and sexed-sorted semen, P/AI to timed AI was higher (65.0 vs. 51.9%; p < .05) in heifers receiving double AI than those serviced once. It was concluded that double AI, 12 h apart, enhanced fertility at timed AI than herd mates with a single AI, particularly with heat stress at breeding.     

Genomic prediction for meat and carcass traits in Nellore cattle using a Markov blanket algorithm

This study was carried out to evaluate the advantage of preselecting SNP markers using Markov blanket algorithm regarding the accuracy of genomic prediction for carcass and meat quality traits in Nellore cattle. This study considered 3675, 3680, 3660 and 524 records of rib eye area (REA), back fat thickness (BF), rump fat (RF), and Warner–Bratzler shear force (WBSF), respectively, from the Nellore Brazil Breeding Program. The animals have been genotyped using low-density SNP panel (30 k), and subsequently imputed for arrays with 777 k SNPs. Four Bayesian specifications of genomic regression models, namely Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression methods were compared in terms of prediction accuracy using a five folds cross-validation. Prediction accuracy for REA, BF and RF was all similar using the Bayesian Alphabet models, ranging from 0.75 to 0.95. For WBSF, the predictive ability was higher using Bayes B (0.47) than other methods (0.39 to 0.42). Although the prediction accuracies using Markov blanket of SNP markers were lower than those using all SNPs, for WBSF the relative gain was lower than 13%. With a subset of informative SNPs markers, identified using Markov blanket, probably, is possible to capture a large proportion of the genetic variance for WBSF. The development of low-density and customized arrays using Markov blanket might be cost-effective to perform a genomic selection for this trait, increasing the number of evaluated animals, improving the management decisions based on genomic information and applying genomic selection on a large scale.     

Histomorphological changes between short and long days in ovary guanacos (Lama guanicoe)

This is the first morpho-histological comparison of guanaco ovaries between reproductive (long-days) and non-reproductive (short-days) seasons, and oestrogen receptor-alpha (ERα) and beta (ERβ) detection. Different stages of follicle development were found in the cortical area, but no corpus luteum was detected. The size and frequency of antral follicles and large atretic follicles were higher in long-day ovaries than short-days, consistent with ovarian activity in this season. Differential expression of ERα and ERβ was observed in follicles at different stages of development between short and long days. These data reveal histological and molecular differences between reproductive and non-reproductive seasons of guanaco ovaries.     

Using midday stem water potential for scheduling deficit irrigation in mid–late maturing peach trees under Mediterranean conditions

Irrigation techniques that reduce water applications are increasingly applied in areas with scarce water resources. In this study, the effect of two regulated deficit irrigation (RDI) strategies on peach [Prunus persica (L.) Batsch cv. “Catherine”] performance was studied over three growing seasons. The experimental site was located in Murcia (SE Spain), a Mediterranean region. Two RDI strategies (restricting water applications at stage II of fruit development and postharvest) based on stem water potential (Ψ_s) thresholds (?1.5 and ?1.8 MPa during fruit growth and ?1.5 and ?2.0 MPa during postharvest) were compared to a fully irrigated control. Soil water content (θ_v), Ψ_s, gas exchange parameters, vegetative growth, crop load, yield and fruit quality were determined. RDI treatments showed significantly lower values of θ_v and Ψ_s than control trees when irrigation water was restricted, causing reductions in stomatal conductance and photosynthesis rates. Vegetative growth was reduced by RDI, as lower shoot lengths and pruning weights were observed under those treatments when compared to control. However, fruit size and yield were unaffected, and fruit quality was slightly improved by RDI. Water savings from 43 to 65 % were achieved depending on the year and the RDI strategy, and no negative carryover effect was detected during the study period. In conclusion, RDI strategies using Ψ_s thresholds for scheduling irrigation in mid–late maturing peach trees under Mediterranean conditions are viable options to save water without compromising yield and even improving fruit quality.     

Factors underlying the investment decision in energy-saving systems in Dutch horticulture

In the Netherlands the greenhouse sector is a major user of energy. It accounts for 7% of the total national energy use and for 79% of the total energy use in agriculture. In order to sustain this sector on the long term, it is important that its use of energy is lowered. One way of reducing energy use by horticultural producers is investing in energy-saving systems. The purpose of this paper is to provide a better understanding of the investment behavior of firm operators in the adoption of energy-saving systems. Research objectives of the paper are (1) to analyze factors underlying the decision to invest, (2) to explore factors underlying the optimal size of investments. Three investment theories were used to construct an empirical model of investment. Consequently, this model was estimated in a two-stage procedure to analyze the factors influencing the decision of farmers to invest and the level of investments. The paper ends with policy implications.     

The effect of salinity on corn yield using the CERES-maize model

In most cases, when calculating soil water availability, only thewater content is considered. The effect of salinity on the wiltingpoint is neglected. The objective of this work is to use asimulation model (CERES-maize) in order to predict cornyields as a function of water salinity under severalenvironmental, agrotechnical, and plant characteristics. A modelis presented in which the wilting point is a function of the soilsalt content. At high salinity, the water content at wilting pointis higher than at low salinity, resulting in an insufficient amountof available water and, therefore, a reduced yield. The modelwas used to simulate several theoretical and experimentalsituations for forage corn and grain corn. Simulation resultsshowed that nitrogen fertilization increases the salinity thresholdvalue and the yield sensitivity (rate of yield reduction per unitof salinity). The also showed that forage corn is more sensitiveto salinity than grain corn. If the soil is not leached, a heaviersoil texture has a higher salinity threshold value. On the otherhand, if the soil is leached, the soil texture has no influence onthe salinity threshold value and the yield is less sensitive tosalinity in sandy soils. The determination coefficient (r²= 0.75) indicated that the results of the simulations were in goodagreement with the field data.     

Habitat quality,not habitat amount,drives mammalian habitat use in the Brazilian Pantanal

Landscape Ecology - An understanding of species-habitat relationships is required to assess the impacts of habitat fragmentation and degradation. To date, habitat modeling in fragmented landscapes...