Search

Comparative multi-environment trials (METs) of sugarcane genotypes are frequently conducted using a randomized complete-block design (RCBD) within environments. However, blocking does not always ensure spatial variation control because of differential competition for resources among neighboring genotypes. Heterogeneity within trials may also cause between-trial heterocedasticity. This work aims to evaluate different linear mixed models (LMMs) that enable the analysis of spatial correlation and residual heterogeneity among trials for both tons of cane per hectare (TCH) and sucrose content (SC%) in three series of multi-environmental trials conducted to evaluate advanced sugarcane clones. A total of 16 sugarcane trials conducted at different sites and in different crop cycles (age) were analyzed. Individual (age×site combination) and multi-environment analyses were performed. For SC%, the classic RCBD analysis within trial was adequate. For TCH, the anisotropic autoregressive model of order 1 (AR1×AR1) was the best to compare genotype means in most trials, allowing gain in information equivalent, on average, to the addition of 1.6 replicates to the original design. In the case of multi-environment analysis, the AR1×AR1 within-trial with among-trial heteroscedasticity was the best model to compare variety means, both for TCH and SC%. The results showed how a more appropriate mixed model would help avoid commission of judgment errors in sugarcane variety recommendations. [ABSTRACT FROM AUTHOR]

Mechanical damage, which reduces seed quality characteristics, refers to the physical injuries caused on seed during handling, harvesting, and conditioning. In maize (Zea mays L.) susceptibility to mechanical damage depends on genetic and environmental factors. The development of inbred lines with high seed quality and broad adaptability is essential in a breeding program. The objective of this study is to quantify the genotypic, environmental, and genotype-by-environment (GE) interaction effects on the mechanically damaged seed quality of experimental maize inbred lines. Nine lines were tested in six environments defined by the location-seed-shape combinations. Each sample was artificially injured (damage treatment). Seed quality was measured by both the saturated cold test and fast green test. Statistical analyses were performed using AMMI model and results were displayed in GE biplots. Variability due to GE interaction was smaller than or equal to the variability among genotypes. The variation between environments was not always the most important, explaining between 19% and 58% of the total variation. The biplot analysis of susceptibility to mechanical damage evaluated by the fast green test gave evidence that particular patterns can be mainly associated with seed shape, and the biplot of vigor evaluated by the saturated cold test had a tendency to group the environments with the localities. These types of associations suggest some predictability of genotype-by-environment interaction. [ABSTRACT FROM AUTHOR]

Maize (Zea mays L.) containing the leafy (Lfy) gene has not been extensively used in genetic investigations because the gene has been patented. The objective of this study was to obtain genetic information on ear moisture loss rate (EMLR), leaf number above the ear, SPAD chlorophyll of leaves, and harvest index via use of a diallel cross (Griffing's Method 3) of seven leafy parents. Ear moisture loss rate was measured via an electronic probe device (EMLR-P) and the “oven method” (EMLR-O). General combining ability (GCA) was significant for EMLR-P and EMLR-O, but GCA x year interaction existed only for EMLR-O. Thus, multiple-year data are needed for investigations of EMLR-O, which increases evaluation cost. Additive genetic correlation between EMLR-P and EMLR-O was 0.96. Parents Mo17 and 914 had the desirable, negative GCA effects. The number of leaves above the ear was a complex, quantitatively inherited trait, as revealed by significant GCA, specific combining ability (SCA), nonmaternal (reciprocal), and SCA-by-years interaction effects. The cross Mo17 x 914 showed positive SCA effect and parental line B73 showed positive GCA effect for leaf number. For SPAD chlorophyll, GCA and SCA were significant, as were GCA x year and SCA x year interactions. Parents Mo17 and Hy had positive GCA effects and A619 had a negative GCA effect for SPAD chlorophyll. The cross A619 x 914 had undesirable negative SCA effect for SPAD chlorophyll. Harvest index (HI), stover, grain weight, and total dry matter (TDM) had significant GCA and reciprocal effects. To increase HI, B73 and 914 should be desirable parents. Parent Hy possessed favorable GCA and maternal factors to increase stover and TDM. A regression equation for grain weight (GWT) was: GWT = -643.0 + 0.28 TDMlinear + 2221.3 HIlinear(R2 = 90%), suggesting that grain weight can be improved by increasing TDM and HI in the leafy maize used here. [ABSTRACT FROM PUBLISHER]

Given the state of resource degradation encountered in Chaco (Argentina), research on forest recovery methods and management proposals inaccordance with the socioeconomic conditions of the region's inhabitants are imperative. The evaluation of factors that affect the plantation of arboreal species and the management knowledge necessary in the initial afforestation of highly degraded production systems are important elements in the plan for recovery. The present study investigates the importance of the factors: the effect of shrubs, grazing and native species to be planted on the success of afforestation in areascharacterized by a high degree of resource degradation. Its objectives are to evaluate the role of Larrea divaricata 'jarilla' in the survival of Prosopis chilensis (Mol.) Stuntz and Aspidosperma quebracho blanco, and the effects of attenuated levels of domestic grazing on the survival rate of P. chilensis afforestation in real production units. Four areas located in old beds left by the Chancani River, reflecting the degraded soil and forest conditions, were set up as real production units. The vegetation community at each site contained 70% L.divaricata, the dominant species. Prosopis flexuosa D.C. and emergent A. quebracho blanco (quebracho) comprised the arboreal stratum. Experimentally planted quebracho and mesquite seedlings' survival rates differed with respect to the shrub-effect. Shrubs were not found to exert any facilitating effect on the survival rate in mesquite, indicating that mesquite would have a higher survival rate in open spaces. However, shrub presence was found to be somewhat beneficial to survival in quebracho one year after the beginning of the trial. Herbivoreswith and without shrubs were a significant factor decreasing survival in P. chilensis. [ABSTRACT FROM AUTHOR]

Abstract: 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. [Copyright &y& Elsevier]

Abstract: Argentina is an important producer of soybean (Glycine max L. Merr.), with 83% of the crop being cultivated under no tillage. Yield gaps of up to 2000kgha−1 are usually recorded in the main area, even between fields that are at a short distance. Soils are predominantly Argiudolls, with subsurface compacted layers (massive zones without visible macropores, termed delta clods, ΔM). The aims of this work were (i) to identify climatic variables and soil properties that explain seed yield variation in rainfed soybean growing in no-tilled Argiudolls; and (ii) to quantify the relative effect of those soil and climatic variables on field soybean yield. The database, which included 175 cases of soybean crops, was obtained from production fields during four crop seasons, covering a wide range of environmental and soil conditions. Multifactor linear regression was used to assess soybean yield variability and quantify the contribution of climatic and soil traits in the formation of grain yield. Threshold values, such as 180mm of cumulative precipitation during the whole reproductive period and 200mm of available soil water at sowing, separated different situations: (a) environments that were above those values, in which 48–51% of total yield variation was explained by mean daily temperate during seed set, cumulative solar radiation during seed filling, combined with soil variables, such as organic matter content and ΔM, or, alternatively, saturated hydraulic conductivity (K sat); and (b) environments that were below the threshold values, in which precipitation during the whole reproductive period and ΔM or K sat explained 72–88% of total soybean yield variation. Highest soybean yield values were always attained in fields under good soil physical conditions. [Copyright &y& Elsevier]

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. [ABSTRACT FROM AUTHOR]

• Web-based application developed to easily map within field variability. • The software tool enables automatic cleaning of spatial data. • Application was successfully tested in statistical zoning of crop fields. • Multiple data layers classify sites to obtain decision maps. Diverse on-farm agronomic data, gathered via precision agriculture (PA), require depuration and joint analysis of multiple georeferenced field characteristics such as crop yields, and soil and topographic aspects. Multivariate analysis of spatial variability has been recommended to understand variation of data within fields and classify sites into zones of broad similarity to support crop management. However, most of the statistical techniques available for spatial data require advanced skills. Cleaning and statistical analysis of big spatial data can only be effectively implemented if there are easy-to-use computer programs integrating the analytical steps. This paper explains the development and implementation of FastMapping, an interactive web application to automatically clean PA raw data, generate spatial variability field maps, and delineate multivariate management zones. The application uses an interface developed in R language that automatically depurates datafiles; in addition, through automatic spatial interpolation of each variable, it allows us to merge data layers on the same spatial grid in such a way that each site within the agricultural field has values of all the measured variables. On this grid, FastMapping identifies homogeneous zones, in a multivariate and spatial way, and provides data reports including validation of the delineated zones. FastMapping outputs for zone delineation were compared with results from Management Zone Analyst (MZA) software in several fields. The new software yielded a similar zoning to that of MZA and added graphs and statistical results that are lacking in most PA software tools. The flexibility of FastMapping to import, clean and visualize PA data in a single computer environment is highly encouraging. FastMapping can be used by the PA community to support site-specific agricultural management. [ABSTRACT FROM AUTHOR]

Historically, cow selection criteria were developed for conventional milking systems that have regular milking intervals (MI). However, in automatic milking systems (AMS), there is variability in MI within and between cows. These sources of variability provide an opportunity to identify cows with high daily milk yield (DY) and long MI. An extended MI (longer than 16 h in pasture-based systems) has a negative effect on DY. Cows that tolerate extended MI and maintain high DY can be considered more efficient than cows with low DY and long MI, or with high DY but short MI, thereby improving robotic system use. Knowledge of the behavior and parameters of lactation curves of cows in AMS could help farmers to identify cows with a specific lactational phenotype. The objective of this study was to identify individual cows with high DY and long MI within herds, which could reflect increased tolerance to milk accumulation under AMS. A database containing records for 773,483 milking events for one year (July 2016–June 2017) from 4 pasture-based AMS farms was used. Lactation curves within each herd were fitted using several mixed models including fixed effects for the parameters of the lactation curve and random cow effects. Predicted curves of average DY according to parity (multiparous and primiparous) were obtained. The best linear unbiased prediction of the random cow effect allowed us to categorize lactations as having either high or low milk production. The median MI of each lactation was then used to categorize cows as having either short or long MI. Daily yield at the peak of lactation, days to peak and 305-d cumulative milk production were used to compare the effect of DY and MI categories, as well as the DY × MI interaction. Milk production by multiparous and primiparous cows with high DY and long MI was between 35 and 45% higher than that of the low DY and short MI. From all lactations analyzed, the incidence of animals with high DY and long MI across farms was 7.5%. We have identified and quantified a new, AMS-specific, phenotype (the combination of a relatively higher DY with relatively longer MI) with potential to increase use of AMS units. Identifying more efficient animals should help generate new approaches for differential management and for selecting cows in AMS. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Highlights: [•] We propose the use of a new method named KM-sPC to management class delimitation. [•] KM-sPC uses a multivariate algorithm that takes into account spatial correlation. [•] The new method relies on fuzzy k-means clustering of spatial principal components. [•] Management classes were identified using KM-sPC and unconstrained fuzzy k-means method. [•] Differences in yield data between delineated classes were better shown by KM-sPC. [ABSTRACT FROM AUTHOR]

Abstract: 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. [Copyright &y& Elsevier]

• The presence of at least on health problem in dairy cattle negatively affected milk production at peak and 305d cumulative milk production. • Cows with health disorders during the third lactation required more inseminations. • Healthy cows remained in the herd 45 days longer than cows with at least one disease. • There is a high risk of health disorders in dairy cattle at the early stage of lactation. • Clinical disease effects on lactation were not limited to the period of disease progress. In dairy herds, cattle experience different health disorders, and their occurrence during lactation may cause important economic losses. The systematic analysis of productive and health records allows us to identify the risk factors of greatest negative incidence on profitability in commercial dairy farms. The aim of this work was to estimate the effects of clinical diseases on the productive and reproductive performance of dairy cattle. A total of 15,423 lactations (≥3rd lactations) were analyzed; data involved records of three years obtained from 21 commercial dairy farms randomly selected from the main milk-producing provinces in Argentina. Lactations were classified as "with" (WD) or "without" (WOD) clinical diseases. The parameters production at peak (Ppeak) and 305-d cumulative milk production (305DY) were estimated and lactation curves were fitted using the MilkBot model. Statistical differences were found between lactations with at least one clinical disease (305DY 9,861.3 kg; Ppeak 39.5 kg/d) and those WOD (305DY 10,013.6 kg; Ppeak 40.2 kg/d). The reproductive indicators days open and days to culling were derived from survival analysis. Days open showed that 50% of cows with at least one clinical disease became pregnant 181 days (95% CI = 177; 185) after parturition, whereas in cows without clinical disease, pregnancy occurred on average 126 days (95% CI= 121; 132) after parturition. Furthermore, for days to culling , 50% of the diseased cows exhibited a culling time of 518 days (95%CI = 508; 527), whereas healthy cows remained in the herd for a longer period, on average 563 days (95% CI= 541; 586). The results suggest significant residual effects, i.e. the consequences of clinical disease are not limited to the period of disease progress, but extend to periods after the clinical resolution of the disease. [ABSTRACT FROM AUTHOR]

An economic analysis was performed using a bioeconomic simulation model based on production, reproduction, and longevity indicators to compare the profitability (net income per cow) of Swedish Red-and-White × Holstein (S×H) cows and pure Holstein (HOL) cows in commercial dairy farms of the center-south of Córdoba province, Argentina. The reproductive events analyzed in the model were pregnancy, calving, and abortion. The longevity events were culling, sale, and death. The lactation curve for each cow was modeled with a lactation function. Estimations were made for the first, second, and third and later lactations. Income sources were from milk, culled cows, and calves. Costs were from feeding, reproductive program, and replacement heifers. The reproductive cost of a HOL cow per year was greater than that of a S×H crossbred cow (US$6.30). The replacement costs were also higher in pure HOL cows than in S×H cows (US$67.80). The revenues from the sale of calves (US$12.10) and milk production minus the feed cost (US$8.20) were greater for S×H cows than HOL cows. Hence, the S×H cows generated a greater total profit (US$94.40) per cow per year than HOL cows. The present results show that in the studied production systems, S×H crossbred cows are more profitable than HOL cows., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Landscape metrics (LM) play a crucial role in fields such as urban planning, ecology, and environmental research, providing insights into the ecological and functional dynamics of ecosystems. However, in dynamic systems, generating thematic maps for LM analysis poses challenges due to the substantial data volume required and issues such as cloud cover interruptions. The aim of this study was to compare the accuracy of land cover maps produced by three temporal aggregation methods: median reflectance, maximum normalised difference vegetation index (NDVI), and a two-date image stack using Sentinel-2 (S2) and then to analyse their implications for LM calculation. The Google Earth Engine platform facilitated data filtering, image selection, and aggregation. A random forest algorithm was employed to classify five land cover classes across ten sites, with classification accuracy assessed using global measurements and the Kappa index. LM were then quantified. The analysis revealed that S2 data provided a high-quality, cloud-free dataset suitable for analysis, ensuring a minimum of 25 cloud-free pixels over the study period. The two-date and median methods exhibited superior land cover classification accuracy compared to the max NDVI method. In particular, the two-date method resulted in lower fragmentation-heterogeneity and complexity metrics in the resulting maps compared to the median and max NDVI methods. Nevertheless, the median method holds promise for integration into operational land cover mapping programmes, particularly for larger study areas exceeding the width of S2 swath coverage. We find patch density combined with conditional entropy to be particularly useful metrics for assessing fragmentation and configuration complexity., Competing Interests: Declarations. Ethical approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Neurofibromatosis type 1 (NF1) is a multisystemic neurocutaneous disease caused by a heterozygous mutation of the NF1 gene that encodes neurofibromin. Complications include vascular and neurologic abnormalities such as moyamoya syndrome, a cerebrovascular disorder with progressive occlusion of the large intracranial arteries, leading to ischemic events and the formation of abnormal vascular networks. Stenosis of the renal artery is another frequent complication of neurofibromatosis type 1, and it represents the most common cause of secondary hypertension in these patients. The purpose of the article is to describe the clinical manifestations of neurofibromatosis type 1 vasculopathy in 4 patients presenting with a wide range of neurologic and reno-vascular manifestations, as well as to examine current diagnostic management and follow-up, current therapeutic options, and to discuss further perspectives in terms of screening, diagnosis, and treatment., Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.