Risk factors associated with sero-positivity to Toxoplasma gondii in captive neotropical felids from Brazil

From September 1995 to February 2001, blood samples were collected from 865 neotropical felids belonging to 8 different species. These animals were housed in 86 institutions located in 78 cities of 20 Brazilian states. Our goal was to identify the risk factors associated with sero-positivity to Toxoplasma gondii in captive neotropical felids from Brazil. All serum samples were tested by the modified agglutination test (MAT), using formalin-fixed whole tachyzoites and mercaptoethanol. For each animal an individual questionnaire was filled with questions about tattoo number, felid species, age, sex, origin, number of animals in the group, introduction of new animals in the group, time in the institution, eating meat previously frozen for a period <7 days in the last 6 months, eating meat of run-over or euthanized animals in the last 6 months, predation of rodents or birds in the last 6 months and presence of domestic cats near the enclosures in the last 6 months. The total sero-prevalence was 55% (95% CI: 52%, 57%). We estimated a prevalence of 46% (95% CI: 40%, 54%) for jaguarundi (Puma yagouaroundi); 58% (95% CI: 53%, 63%) for ocelot (Leopardus pardalis); 50% (95% CI: 45%, 56%) for oncilla (L. tigrinus); 54% (95% CI: 46%, 62%) for margay (L. wiedii); 12% (95% CI: 4%, 31%) for Pampas-cat (L. colocolo); 83% (95% CI: 65%, 93%) for Geoffroy's-cat (L. geoffroyi); 64% (95% CI: 50%, 68%) for jaguar (Panthera onca) and 48% (95% CI: 42%, 54%) for puma (Puma concolor). Multiple logistic regression was used to evaluate the association between the variables in the questionnaire and sero-positivity to T. gondii. We concluded that the independent risk factors for toxoplasmosis were: age >3 years (OR = 4.75 [2.75; 8.2]), eating meat previously frozen for a period <7 days (OR = 2.23 [1.24; 4.01]), and consumption of animals that were run-over or euthanized (OR = 1.64; [1.14; 2.37]).     

Individual efficiency for the use of feed resources in rabbits

A Bayesian procedure, which allows consideration of the individual variation in the feed resource allocation pattern, is described and implemented in 2 sire lines of rabbit (Caldes and R). The procedure is based on a hierarchical Bayesian scheme, where the first stage of the model consists of a multiple regression model of feed intake on metabolic BW and BW gain. In a second stage, an animal model was assumed including batch, parity order, litter size, and common environmental litter effects. Animals were reared during the fattening period (from weaning at 32 d of age to 60 d of age) in individual cages on an experimental farm, and were fed ad libitum with a commercial diet. Body weight (g) and cumulative feed intake (g) were recorded weekly. Individual BW gain (g) and average BW (ABW, g) were calculated from these data for each 7-d period. Metabolic BW (g(0.75)) was estimated as ABW(0.75). The number of animals actually measured was 444 and 445 in the Caldes and R lines, respectively. Marginal posterior distributions of the genetic parameters were obtained by Gibbs sampling. Posterior means (posterior SD) for heritabilities for partial coefficients of regression of feed intake on metabolic BW and feed intake on BW gain were estimated to be 0.35 (0.17) and 0.40 (0.17), respectively, in the Caldes line and 0.26 (0.19) and 0.27 (0.14), respectively, in line R. The estimated posterior means (posterior SD) for the proportion of the phenotypic variance due to common litter environmental effects of the same coefficients of regression were respectively, 0.39 (0.14) and 0.28 (0.13) in the Caldes line and 0.44 (0.22) and 0.49 (0.14) in line R. These results suggest that efficiency of use of feed resources could be improved by including these coefficients in an index of selection.     

Natural hybridization between wheat (Triticum aestivum L.) and its wild relatives Aegilops geniculata Roth and Aegilops triuncialis L.

BACKGROUND

Cultivated bread wheat (Triticum aestivum L.) spontaneously hybridizes with wild/weedy related Aegilops populations, but little is known about the actual rates at which this hybridization occurs under field conditions. It is very important to provide reliable empirical data on this phenomenon in order to assess the potential crop–wild introgression, especially in the context of conducting risk assessments for the commercialization of genetically modified (GM) wheat, as gene flow from wheat to Aegilops species could transfer into the wild species genes coding for traits such as resistance to herbicides, insects, diseases or environmental stresses.

RESULTS

The spontaneous hybridization rates between wheat and A. geniculata and A. triuncialis, which are very abundant in the Mediterranean area, have been estimated for the first time in the northern part of the Meseta Central, the great central plateau which includes the largest area of wheat cultivation in Spain. Hybridization rates averaged 0.12% and 0.008% for A. geniculata and A. triuncialis, respectively. Hybrids were found in 26% of A. geniculata and 5% of A. triuncialis populations, at rates that can be ≤3.6% for A. geniculata and 0.24% for A. triuncialis.

CONCLUSION

The detection of Aegilops spp.–wheat hybrids in Aegilops populations indicates that gene flow can occur, although wheat is considered a crop with a low-to-medium risk for transgene escape. These data on field hybridization rates are essential for GM wheat risk assessment purposes. © 2023 Society of Chemical Industry.     

Detection of Ecballium elaterium in hedgerow olive orchards using a low-cost uncrewed aerial vehicle and open-source algorithms

BACKGROUND

Ecballium elaterium (common name: squirting cucumber) is an emerging weed problem in hedgerow or superintensive olive groves under no tillage. It colonizes the inter-row area infesting the natural or sown cover crops, and is considered a hard-to-control weed. Research in other woody crops has shown E. elaterium has a patchy distribution, which makes this weed susceptible to design a site-specific control strategy only addressed to E. elaterium patches. Therefore, the aim of this work was to develop a methodology based on the analysis of imagery acquired with an uncrewed aerial vehicle (UAV) to detect and map E. elaterium infestations in hedgerow olive orchards.

RESULTS

The study was conducted in two superintensive olive orchards, and the images were taken using a UAV equipped with an RGB sensor. Flights were conducted on two dates: in May, when there were various weeds infesting the orchard, and in September, when E. elaterium was the only infesting weed. UAV-orthomosaics in the first scenario were classified using random forest models, and the orthomosaics from September with E. elaterium as the only weed, were analyzed using an unsupervised algorithm. In both cases, the overall accuracies were over 0.85, and the producer's accuracies for E. elaterium ranged between 0.74 and 1.00.

CONCLUSION

These results allow the design of a site-specific and efficient herbicide control protocol which would represent a step forward in sustainable weed management. The development of these algorithms in free and open-source software fosters their application in small and medium farms. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

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.     

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.     

Measured and estimated water use and crop coefficients of grapevines trained to overhead trellis systems in California’s San Joaquin Valley

The use of overhead trellis systems for the production of dry-on-vine (DOV) raisins and table grapes in California is expanding. Studies were conducted from 2006 to 2009 using Thompson Seedless grapevines grown in a weighing lysimeter trained to an overhead arbor trellis and farmed as DOV raisins for the first two years and for use as table grapes thereafter. Maximum canopy coverage for the two lysimeter vines across years was in excess of 80 %. Seasonal (15 March–31 October) evapotranspiration for the lysimeter vines (ET_Lys) was 952 mm in 2007 (farmed as DOV raisins) and 943 and 952 mm (when farmed as table grapes). The maximum crop coefficient (K _cLys) across all 4 years ranged from 1.3 to 1.4. These maximum values were similar to those estimated using the relationship where K _c is a function of the amount of shaded area measured beneath the canopy at solar noon (K _c = 0.017 × percent shaded area). Covering the lysimeter’s soil surface with plastic (and then removing it) numerous times during the 2009 growing season (1 June–14 September) reduced ET_Lys from an average of 6.4 to 5.6 mm day^?1 and the K _c from 1.07 to 0.93. A seasonal basal K _c (K _cb) was calculated for grapevines using an overhead trellis system with a 13 % reduction in the K _cLys across the growing season.