Water pH and active ingredient concentration are two of the most important variables to consider in the manufacturing process of fungicides. If these variables do not meet the required standards, the quality of the product may be compromised and lead to poor fungicide performance when water is used as the application carrier, which is in most cases. Given the correlation between the variable...

The fungicide benomyl inhibited spore germination and hyphal length of the arbuscular mycorrhizal fungus Glomus mosseae when applied at doses of 21.25 microg/ml (agronomic dose), 10.62 microg/ml and 10 microg/ml. G. mosseae was able to germinate in the presence of 2.12 microg/ml of benomyl, and the percentage of spore germination was unaffected by dosis of 0.1, 0.01 and 0.001 microg/ml of the f...

The aim of detecting outliers in a multivariate sample can be pursued in diierent ways. We investigate here the performance of several simultaneous multivariate outlier identiication rules based on robust estimators of location and scale. It has been shown that the use of estimators with high nite-sample breakdown point in such procedures yields a good behaviour with respect to the prevention o...

Mepanipyrim is an anilinopyrimidine fungicide used worldwide for crop protection. With the aim of developing useful immunoreagents for mepanipyrim immunoanalysis, two new functionalized derivatives were prepared and antibodies were generated. Affinity and specificity were assessed by direct and indirect competitive ELISA using homologous and heterologous conjugates. Although all antibodies were...

The minimum regularized covariance determinant method (MRCD) is a robust estimator for multivariate location and scatter, which detects outliers by fitting matrix to the data. Its regularization ensures that well-conditioned in any dimension. MRCD assumes non-outlying observations are roughly elliptically distributed, but many datasets not of form. Moreover, computation time increases substanti...

It is important to preprocess high-throughput data generated from microarray or mass spectrometry experiments in order to obtain a successful analysis. Outlier detection is an important preprocessing step. For outlier detection, upper and lower fences (Q3+1.5IQR and Q1 − 1.5IQR) of the differences are often used in statistics, where Q1=lower 25% quantile, Q3=upper 25% quantile, and IQR = Q3 − Q...

In tracer kinetic studies for extracting biological information, measurement noise and error in the kinetics could affect the reliability of the estimated biological parameters. While the effect of statistical noise has been studied extensively before, the effect of outliers has not been addressed as much. In this study, we described an algorithm for detecting and removing outliers. Computer si...

In this paper, we propose a robust Kalman filter and smoother for the errors-invariables (EIV) state space model subject to observation noise with outliers. We introduce the EIV problem with outliers and then we present the minimum covariance determinant (MCD) estimator which is highly robust estimator to detect outliers. As a result, a new statistical test to check the existence of outliers wh...

Low-cost urban air quality sensor networks are increasingly used to study the spatio-temporal variability in air pollutant concentrations. Recently installed low-cost urban sensors, however, are more prone to result in erroneous data than conventional monitors, e.g., leading to outliers. Commonly applied outlier detection methods are unsuitable for air pollutant measurements that have large spa...