Object-based land-cover change detection applied to Brazilian seasonal savannahs using geostatistical features

A new method for remote-sensing land-use/land-cover (LULC) change detection is proposed to eliminate the effects of forest phenology on classification results. This method is insensitive to spectral changes caused by vegetation seasonality and uses an object-based approach to extract geostatistical features from bitemporal Landsat TM (Thematic Mapper) images. We first create image objects by multiresolution segmentation to extract geostatistical features (semivariogram parameters and indices) and spectral information (average values) from NDVI (normalized difference vegetation index), acquired in the wet and dry seasons, as input data to train a Support Vector Machine algorithm. We also used the image difference traditional change-detection method to validate the effectiveness of the proposed method. We used two classes: (1) LULC change class and (2) seasonal change class. Using the most geostatistical features, the change detection results are considerably improved compared with the spectral features and image differencing technique. The highest accuracy was achieved by the sill (σ² overall variability) semivariogram parameter (95%) and the AFM (area first lag–first maximum) semivariogram index (88.33%), which were not affected by vegetation seasonality. The results indicate that the geostatistical context makes possible the use of bitemporal NDVI images to address the challenge of accurately detecting LULC changes in Brazilian seasonal savannahs, disregarding changes caused by phenological differences, without using a dense time series of remote-sensing images. The challenge of extracting accurate semivariogram curves from objects of long and narrow shapes requires further study, along with the relationship between the scale of segmentation and image spatial resolution, including the type of change and the initial land-cover class.     

Validation of measurement capabilities

The best measurement capabilities (BMCs) of laboratories are usually described at the Accreditation Certificates, for the calibrations they perform. The evaluation of these BMCs is carried out also by interlaboratory comparisons (ILCs), the proficiency testing schemes as described by the ISO Guide 43 and ISO 13528 standard. The National Metrology Institutes traditionally organize the ILCs for the National Accreditation Boards, providing the travelling standards, the reference(s) value(s) and the statistical analysis of the laboratories results. The goal of this article is to discuss the existing approaches for evaluation of ILCs and propose a basis for the validation of laboratories BMCs.     

Cover Image,Volume 98, Issue 3

The cover image, by Elizângela M Ogawa et al., is based on the Research Article Chemical profile of pineapple cv. Vitória in different maturation stages using electrospray ionization mass spectrometry, DOI: 10.1002/jsfa.8561 . Image Credit: José A Ventura.

     

Antioxidant, antiacetylcholinesterase and antimicrobial activities of Cymbopogon schoenanthus L. Spreng (lemon grass) from Tunisia

Aqueous extract, proanthocyanidin rich extract, and organic extracts of Cymbopogon schoenanthus L. Spreng (lemon grass) shoots from three different locations in South Tunisia were screened for their antioxidant, acetylcholinesterase and antimicrobial activities. In addition to the evaluation of these activities, the contents of flavonoids and total phenolic compounds were determined.Antioxidant activity measured by DPPH assay showed that the proanthocyanidin extract exhibited higher antioxidant activity than the aqueous extract. Extract concentration providing 50% inhibition (IC₅₀) ranged from 16.4 ± 6.8 μg/mL to 26.4 ± 6.8 μg/mL. The antioxidant activity was also determined using the β-carotene/linoleic acid bleaching test. The best results (IC₅₀ = 0.11 ± 0.10 mg/mL) were obtained with the proanthocyanidin extract of the plants collected from the desert region (Dhibat).The greatest acetylcholinesterase inhibitory activity (IC₅₀ = 0.23 ± 0.04 mg/mL) was exhibited by the ethyl acetate and methanol extracts of the plants collected from the mountainous region. It seems that extracts obtained with more polar solvents gave better results.The proanthocyanidin extracts showed a good antimicrobial activity against Streptococcus sobrinus at low concentration (MIC = 4 mg/mL). Therefore, these extracts could be used to prevent carious lesions by inhibiting S. sobrinus growth.     

Gender preference in hedonic ratings for espresso and espresso-milk coffees

Espresso, cappuccino and latte are new coffee products entering the daily lives of many consumers. There is increasing consumption of such speciality coffees but no sensory basis for new product development. This study was designed to meet this need. Preference in 100 consumers was studied using six espresso blends of coffee beans. Blends were specifically developed to match key European and North American styles. Products prepared were both espresso and espresso-milk coffees. It was observed that females and males had different preferences for espresso coffee but that this effect was reduced on addition of milk. Gender of target consumer, and end use of espresso, should be thus considered in developing coffee blends. In this way acceptability in specific or target groups of consumers can be maximised. In addition individuals may experience a development of appreciation of coffee character reflected in a change in preference.     

Prevalence of Listeria spp. in feces and carcasses at a lamb packing plant in Brazil

The objective of this work was to study the occurrence of Listeria species in feces and on dressed and cooled carcasses of lambs at a packing plant in Brazil. Listeria spp. were recovered on Oxford and Palcam agars. The 35 fecal samples yielded Listeria welshimeri (20%) and Listeria innocua (8.6%). The 69 carcass samples yielded L. innocua (34.8%), Listeria monocytogenes (4.3%), and Listeria ivanovii (1.5%). More Listeria spp. were recovered with two selective agars than with either agar alone.     

Reduction of Free Fatty Acids in Acidic Nonedible Oils by Modified K10 Clay

Biodiesel is a biofuel obtained from vegetable oils. The oils used as raw materials are usually refined edible vegetable oils. Nonedible acidic oils are unsuitable for biodiesel production unless reduction of the high content in free fatty acids (FFA) of these materials had been achieved. Obtaining a good raw material from unprofitable oils becomes an important research field. Additionally clays have a long history in industrial sorption and catalysis, some being commercially available and with properties that can be modified. In this work we present the results of the use of the montmorillonite clay K10 and two acid modified clays K10(I) and K10(II), in the esterification of stearic acid with methanol and 95 % of methyl stearate was obtained with K10(II). These clays were then used for the first time to reduce the acidity of enhanced FFA sunflower oil and they show to be very effective. Reduction of FFA from 11 to 4 % was obtained with K10(II) mainly due to 94 % conversion of FFA into fatty acid methyl esters (FAME). These clays were also tested with two waste oils, one from domestic use and the other gathered from different restaurants, and showed their ability to lower the acidity of these oils. Reactions were followed by ¹H NMR as well as quantitative determination of FFA and FAME. Clays were characterized by FTIR and XRD.     

Bayesian Outlier Detection in Non‐Gaussian Autoregressive Time Series

This work investigates outlier detection and modelling in non‐Gaussian autoregressive time series models with margins in the class of a convolution closed parametric family. This framework allows for a wide variety of models for count and positive data types. The article investigates additive outliers which do not enter the dynamics of the process but whose presence may adversely influence statistical inference based on the data. The Bayesian approach proposed here allows one to estimate, at each time point, the probability of an outlier occurrence and its corresponding size thus identifying the observations that require further investigation. The methodology is illustrated using simulated and observed data sets.     

Gene expression profiling for understanding chemical causation of biological effects for complex mixtures: a case study on estrogens

Gene expression profiling offers considerable potential for identifying chemical causation of effects induced in exposures to complex mixtures, and for understanding the mechanistic basis for their phenotypic effects. We characterized gene expression responses in livers and gonads of fathead minnow (Pimephales promelas) exposed (for 14-21 days) to estrogenic wastewater treatment works final effluents with varying potencies and assessed the extent to which these expression profiles mapped with those induced by individual steroid estrogens present in the effluents (17beta-estradiol and 17alpha-ethinylestradiol) and, thus, were diagnostic of estrogen exposure. For these studies, we adopted a targeted approach (via real-time PCR) with a suite of 12 genes in liver and 21 genes in gonad known to play key roles in reproduction, growth and development (processes controlled by estrogens) and responses were compared with effects on phenotypic end points indicative of feminization. Gene responses to effluent were induced predominantly in a linear (monotonic) concentration-dependent manner but were complex with many genes responding differently between tissue types and sexes. The gene expression profiles for the estrogenic effluents and the individual steroid estrogens had many common features. There were marked differences in the profiles between the two effluents, however, that were not explained by differences in their estrogenic potencies, suggesting that these may have arisen as a consequence of differences in the contents of other chemicals, which may act directly or indirectly with the estrogen-response pathway to alter estrogen-induced gene expression. These data demonstrate that the patterns of gene expression induced by estrogenic effluents, although complex, can be diagnostic for some of the estrogens they contain and provide insights into the mechanistic basis for the phenotypic effects seen.