Mónica Balzarini

Effects of salinity on germination and seedling growth of Prosopis flexuosa (D.C.)

Abstract Prosopis flexuosa, the most widespread arboreal legume found on saline soils in Argentina, is regarded as an especially attractive species for the productive recovery of arid and salt-affected areas. The effects of salinity on germination and seedling growth of this species were studied. Salt tolerance during germination was examined in seeds collected from two populations growing either on saline or non-saline soil. Germination was assessed under various NaCl concentrations: 0, 0.2, 0.4, 0.6 and 0.8 M. Significant decreases in germination percentage were observed above 0.2 M NaCl. Variability was higher among individual trees than between populations and highest at 0.4 M NaCl. Salt tolerance at the seedling stage was analysed in 20-day-old seedlings, grown in pots with soil, treated for 90 days with NaCl solutions ranging between 0 and 0.4 M. The average seedling survival percentage for the trial was above 96%. A 50% decrease in final height was observed in the treatment with 0.4 M NaCl, where substrate in the pots had reached a final salt concentration of nearly 1 M NaCl. In Prosopis flexuosa, salt tolerance at the seedling stage appears to be greater than at the germination stage, suggesting that seedlings could be used for afforestation of salt-affected areas.

Delineation of management zones to improve nitrogen management of wheat

The management zone were delineated by using ECa, terrain elevation and soil depth.The response to N fertilization of wheat is different among management zone.The delimiting of management zone improved the N use efficiency (NUE) in wheat.The application of variable N rates increases production system sustainability. Site-specific management of N (NSSM) is an attractive and intuitive approach to increasing N fertilizer use efficiency (NUE) of agricultural systems by adjusting fertilizer rates to the soil characteristics. The objective of this study is to assess: whether delineating of management zone (MZ) within fields improves NUE in wheat (Triticum aestivum L.). This research was carried out at 5 commercial fields (between 26 and 84ha), located in the south-eastern portion of the Province of Buenos Aires, Argentina. The MZ were delineated by using georeferenced measurements of apparent soil electrical conductivity, terrain elevation and soil depth. Spatially referenced wheat yields were recorded with a yield monitor equipped with DGPS. The interaction effect was significant (p<0.05) in most fields, thus indicating that the response to N fertilization is different among MZ. Also, NUE was significantly different (p<0.05) among MZ. The detection of soil spatial variability and the delineation of MZ are now possible on a commercial scale. The delineation of MZ affords the opportunity of variable rate application of N fertilizers on Typic Argiudolls and Petrocalcic Paleudolls, and the minimization of pollution risk due to an excessive application of resources.

Changes in the Concentration of an Allexivirus During the Crop Cycle of Two Garlic Cultivars

Garlic can be infected by a number of viruses, including allexiviruses. The coat protein sequence of an Allexivirus was detected in Argentina and deposited in the EMBL database as Garlic mite-borne filamentous virus (accession number X98991); it has high homology with Garlic virus A (GarV-A). For reliable virus detection, plants should be sampled when virus titer is high to reduce the risk of identifying infected plants as healthy. The objective of this study was to describe fluctuations in the concentration of this Argentine isolate of GarV-A in two garlic cultivars, Morado-INTA and Nieve-INTA, throughout the crop cycle using the double-antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA). Over a 2-year period, for both cultivars, virus concentration was assessed in samples from the tips section of the youngest leaves of GarV-A-infected plants, and from basal sections of both dormant and devernalized cloves of stored bulbs of Morado-INTA. The concentration of GarV-A varied during the crop cycle, but peaked at the beginning and again at the end of the crop cycle. Virus concentration was slightly higher in devernalized cloves compared with dormant cloves of Morado-INTA. No correlation between virus concentration and mean air temperature was observed. The results of this study recommend sampling times at the beginning of the crop cycle at 64 to 81 days after planting, and towards the end of the crop cycle to evaluate for the presence of GarV-A by DAS-ELISA.

Assessing erectile neurogenic dysfunction from heart rate variability through a Generalized Linear Mixed Model framework

BACKGROUND The low (LF) vs. high (HF) frequency energy ratio, computed from the spectral decomposition of heart beat intervals, has become a major tool in cardiac autonomic system control and sympatho-vagal balance studies. The (statistical) distributions of response variables designed from ratios of two quantities, such as the LF/HF ratio, are likely to non-normal, hence preventing e.g., from a relevant use of the t-test. Even using a non-parametric formulation, the solution may be not appropriate as the test statistics do not account for correlation and heteroskedasticity, such as those that can be observed when several measures are taken from the same patient. OBJECTIVES The analyses for such type of data require the application of statistical models which do not assume a priori independence. In this spirit, the present contribution proposes the use of the Generalized Linear Mixed Models (GLMMs) framework to assess differences between groups of measures performed over classes of patients. METHODS Statistical linear mixed models allow the inclusion of at least one random effect, besides the error term, which induces correlation between observations from the same subject. Moreover, by using GLMM, practitioners could assume any probability distribution, within the exponential family, for the data, and naturally model heteroskedasticity. Here, the sympatho-vagal balance expressed as LF/HF ratio of patients suffering neurogenic erectile dysfunction under three different body positions was analyzed in a case-control protocol by means of a GLMM under gamma and Gaussian distributed responses assumptions. RESULTS The gamma GLMM model was compared with the normal linear mixed model (LMM) approach conducted using raw and log transformed data. Both raw GLMM gamma and log transformed LMM allow better inference for factor effects, including correlations between observations from the same patient under different body position compared to the raw LMM. The gamma GLMM provides a more natural distribution assumption of a response expressed as a ratio. CONCLUSIONS A gamma distribution assumption intrinsically models quadratic relationships between the expected value and the variance of the data avoiding prior data transformation. SAS and R source code are available on request.

QTL analysis of resistance to Mal de Río Cuarto disease in maize using recombinant inbred lines

Mal de Rio Cuarto (MRC) is a devastating disease that reduces yield, quality and economic value of maize in Argentina. The objective of the present study was to map quantitative trait loci (QTL) for reactions to MRC from recombinant inbred lines (RILs). Reactions to the endemic MRC disease were evaluated in 145 advanced F 2:6 lines, derived from a cross between a resistant (BLS14) and a susceptible (Mo17) line, at four environments in the temperate semi-arid crop region of Argentina. The evaluations of disease score (SCO), disease incidence (INC) and disease severity (SEV) were carried out on each individual RIL. Low heritability estimates were found across environments for SCO (0·23), INC (0·27) and SEV (0·22). A genetic map of simple sequence repeat (SSR) markers covering a total genetic distance of 1019 cM was built. QTL for resistance to MRC disease were found on different maize chromosomes. Four significant QTL, each explaining between 0·08 and 0·14 of the total phenotypic variation, were located on chromosomes 1, 4 and 10. Two QTL specific to the INC, and one specific to SEV, may be involved in different mechanisms of resistance to MRC. Although MRC reaction is highly affected by environmental effects, the QTL×environment interaction for INC and SEV was low. Most of the QTL for reaction to MRC detected in the present study were mapped to regions of the maize genome containing genes conferring resistance to various pathogens. The significant QTL across environments are good candidates to select for MRC resistance.

Some factors affecting the number of days open in Argentinean dairy herds

The objective of this study was to estimate the relative contribution of factors affecting how quickly cattle become pregnant in Argentine dairy herds. Data from 76,401 cows from 249 dairy herds were analyzed. A hazard model was used to explore days open (DO). The factors considered were milk yield, lactation number, calving season, and breeding technique (i.e., type of service: artificial insemination [AI], or combined service). Cows with lower milk yield had 1.09 to 1.38 higher likelihood to become pregnant than those with higher milk yield (P < 0.0001). The number of DO increased linearly with an increasing number of lactations (P < 0.0001). Cows calving in fall-winter had a shorter interval to conception than those calving in summer. The hazard rate for combined service was 1.27; therefore, cows with combined service were more likely to become pregnant during the observation period than those bred by AI. The difference in DO between cows of high versus low milk yield was smaller when dairies used AI as the main breeding technique than when they used combined service. Furthermore, dairies using mainly combined service had lower milk yield (5693.7 L) than those using mainly AI (7684.4 L). Although lactation number and calving season contributed to explain the number of DO, the influence of production level, the type of service, and the interaction between them was also associated with reproductive efficiency in Argentine dairy herds.

Non-parametric smoothing of multivariate genetic distances in the analysis of spatial population structure at fine scale

Species dispersal studies provide valuable information in biological research. Restricted dispersal may give rise to a non-random distribution of genotypes in space. Detection of spatial genetic structure may therefore provide valuable insight into dispersal. Spatial structure has been treated via autocorrelation analysis with several univariate statistics for which results could dependent on sampling designs. New geostatistical approaches (variogram-based analysis) have been proposed to overcome this problem. However, modelling parametric variograms could be difficult in practice. We introduce a non-parametric variogram-based method for autocorrelation analysis between DNA samples that have been genotyped by means of multilocus-multiallele molecular markers. The method addresses two important aspects of fine-scale spatial genetic analyses: the identification of a non-random distribution of genotypes in space, and the estimation of the magnitude of any non-random structure. The method uses a plot of the squared Euclidean genetic distances vs. spatial distances between pairs of DNA-samples as empirical variogram. The underlying spatial trend in the plot is fitted by a non-parametric smoothing (LOESS, Local Regression). Finally, the predicted LOESS values are explained by segmented regressions (SR) to obtain classical spatial values such as the extent of autocorrelation. For illustration we use multivariate and single-locus genetic distances calculated from a microsatellite data set for which autocorrelation was previously reported. The LOESS/SR method produced a good fit providing similar value of published autocorrelation for this data. The fit by LOESS/SR was simpler to obtain than the parametric analysis since initial parameter values are not required during the trend estimation process. The LOESS/SR method offers a new alternative for spatial analysis.

Effect of puerperal metritis on reproductive and productive performance in dairy cows in Argentina

The objectives of this study were to evaluate the reproductive and productive performance of dairy cows with and without puerperal metritis and to evaluate the effectiveness of using a long-acting ceftiofur preparation. Dairy cows in one dairy farm, calving from July 2009 to January 2010, were examined between 3 and 14 days postpartum and classified on the basis of vaginal discharge into three groups: cows with normal discharge (control; C); cows with a bloody mucus purulent or pathologic nonfetid discharge (PnFD), and cows with bloody mucopurulent or purulent fetid discharge (PFD). Cows in C and PnFD groups were not treated, whereas those in the PFD group were randomly allocated to receive 2.2 mg/kg of ceftiofur subcutaneously behind the ear (PFD-T) or remain untreated (PFD-No T). From the 640 cows examined, 58.2% formed the C group, 13.4% formed the PnFD group, and 28.4% formed the PFD group. Survival curves differed between cows in the C group and PFD-No T group (P = 0.0013) and between PFD-No T versus PFD-T group (P = 0.0006). Survival curves of PnFD were intermediate and did not differ from those in the C group (P = 0.2) and PFD-T group (P = 0.1) but tended to be different from the PFD-No T group (P = 0.056). The postpartum interval to achieve a 25% pregnancy rate was 72 days for cows in the C group, 73 days for the PFD-T group, 83 days for PnFD group, and 95 days for the PFD-No T group. The chance of pregnancy in a cow in the C group was 1.98 times higher (95% confidence interval = 1.33, 3.08) and in cows in the PFD-T group was 2.16 times higher (95% confidence interval = 1.37, 3.50) than that in the PFD-No T group. Finally, the chance of pregnancy in cows in the PnFD group tended to be higher (P = 0.08) than that in the PFD-No T group but did not differ from the other two groups. Cumulative 305-day milk production was higher (P < 0.0001) in C group than those with vaginal discharge, regardless of fetidness and regardless of treatment. It is concluded that puerperal metritis affects the reproductive and productive performance of dairy cows and the treatment with ceftiofur was effective in reducing the adverse effects on reproductive performance but not on milk production.

Genetic variability in Chilean pepino (Solanum muricatum Aiton) fruit

Solanum muricatum Aiton is an herbaceous perennial fruit species native to the Andean region of Colombia, Ecuador, and Peru. In Chile, it was probably introduced in pre-Columbian times as a domesticated species and is presently grown in the coastal areas of the north-central regions of Coquimbo and Valparaiso. The species has been bred, but little information is available on its genetic variability in Chile. To characterize the genetic variability in this species, fruits were collected from 14 different ecotypes and seeds were sown to generate approximately 60 segregants from each accession. Segregants were planted at two different locations to characterize their fruits and fruiting habits. Fruit weight ranged from 30 to 485 g, while length was 3.5 to 16.7 cm, equatorial diameter 3.4 to 9.5 cm, pulp firmness 1.7 to 10 N, and soluble solids content 6.3 to 13.5° Brix. Fruit shape ranged from flat to oblong. When analyzing the estimated variance components with a mixed linear model, most of the variability between different ecotypes was in fruit shape, length, and weight, which resulted in a genetic contribution of 34.6%, 29.3%, and 18.1% of the total variability of these traits, respectively. Genetic variability was also found for pulp firmness and soluble solids content. Therefore, enough variability is available in seed-propagated pepinos from Chilean ecotypes to allow genetic improvement of these fruit quality traits. There was also variability from genotype x environment interactions; therefore, selections must be performed for specific environments or stable selections must be found.

Hierarchical linear mixed models in multi-stage sampling soil studies

The issue of variances of different soil variables prevailing at different sampling scales is addressed. This topic is relevant for soil science, agronomy and landscape ecology. In multi-stage sampling there are randomness components in each stage of sampling which can be taken into account by introducing random effects in analysis through the use of hierarchical linear mixed models (HLMM). Due to the nested sampling scheme, there are several hierarchical sub-models. The selection of the best model can be carried out through likelihood ratio tests (LRTs) or Wald tests, which are asymptotically equivalent under standard conditions. However, when the comparison leads to a restricted hypothesis of variance components, standard conditions are not maintained, which leads to more elaborated versions of LRTs. These versions are not disseminated among environmental scientists. The present study shows the modeling of soil data from a sampling where sites, fields within sites, transects within fields, and sampling points within transects were selected in order to take samples from different vegetation types (open and shade). For soil data, several sub-models were compared using Wald tests, classic LRTs and adjusted LRTs where the distribution of the test statistic under the null hypothesis is the Chi-square mixture of Chi-square distributions. The inclusion of random effects via HLMM and suggested by the latest version of LRT allowed us to detect effects of vegetation type on soil properties that were not detected under a classical ANOVA.