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.     

Effects of irrigation regimes on the yield and water use of strawberry

Summary Strawberry plants (Fragaria x annanasa D. cv Chandler) were grown in field plots and in drainage lysimeters under controlled soil moisture regimes. Four irrigation treatments were established by watering the plants when soil water potential reached -0.01, -0.03,-0.05 and -0.07 MPa. The maximum yield was attained at -0.01 MPa soil water potential. Differences in yield were caused by both changes in the number of fruits per plant and in the fresh weight per fruit. Yield reductions were associated with reductions in total assimilation rate resulting from the decreased assimilatory surface area in plants irrigated at lower soil water potentials. The crop water production function calculated on a fruit fresh weight basis resulted in a yield response factor (K _y) of 1.01.     

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.     

Total Phenolic Levels,In Vitro Antioxidant Properties,and Fatty Acid Profile of Two Microalgae,Tetraselmis marina Strain IMA043 and Naviculoid Diatom Strain IMA053, Isolated from the North Adriatic Sea

This work studied the potential biotechnological applications of a naviculoid diatom (IMA053) and a green microalga (Tetraselmis marina IMA043) isolated from the North Adriatic Sea. Water, methanol, and dichloromethane (DCM) extracts were prepared from microalgae biomass and evaluated for total phenolic content (TPC) and in vitro antioxidant properties. Biomass was profiled for fatty acid methyl esters (FAME) composition. The DCM extracts had the highest levels of total phenolics, with values of 40.58 and 86.14 mg GAE/g dry weight (DW in IMA053 and IMA043, respectively). The DCM extracts had a higher radical scavenging activity (RSA) than the water and methanol ones, especially those from IMA043, with RSAs of 99.65% toward 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)diammonium salt (ABTS) at 10 mg/mL, and of 103.43% against 2,2-diphenyl-1-picrylhydrazyl (DPPH) at 5 mg/mL. The DCM extract of IMA053 displayed relevant copper chelating properties (67.48% at 10 mg/mL), while the highest iron chelating activity was observed in the water extract of the same species (92.05% at 10 mg/mL). Both strains presented a high proportion of saturated (SFA) and monounsaturated (MUFA) fatty acids. The results suggested that these microalgae could be further explored as sources of natural antioxidants for the pharmaceutical and food industry and as feedstock for biofuel production.     

Hexavalent Chromium Removal by Candida sp. in a Concentric Draft-Tube Airlift Bioreactor

The main purpose of this work was to conduct a kinetic study on cell growth and hexavalent chromium [Cr(VI)] removal by Candida sp. FGSFEP in a concentric draft-tube airlift bioreactor. The yeast was batch-cultivated in a 5.2-l airlift bioreactor containing culture medium with an initial Cr(VI) concentration of 1.5 mM. The maximum specific growth rate of Candida sp. FGSFEP in the airlift bioreactor was 0.0244 h^?1, which was 71.83% higher than that obtained in flasks. The yeast strain was capable of reducing 1.5 mM Cr(VI) completely and exhibited a high volumetric rate [1.64 mg Cr(VI) l^?1 h^?1], specific rate [0.95 mg Cr(VI) g^?1 biomass h^?1] and capacity [44.38 mg Cr(VI) g^?1 biomass] of Cr(VI) reduction in the airlift bioreactor, with values higher than those obtained in flasks. Therefore, culture of Candida sp. FGSFEP in a concentric draft-tube airlift bioreactor could be a promising technological alternative for the aerobic treatment of Cr(VI)-contaminated industrial effluents.