Contents and bioconversion of B-glycoside isoflavones to aglycones in the processing conditions of soybean tempeh.

The objective of this work was to evaluate the effect of the processing conditions of soybean tempeh on the contents of ??glycoside isoflavones and on their bioconversion into aglycones. Different times of soaking (6, 12, and 18 hours), cooking (15, 30, and 45 minutes), and fermentation (18, 24, and 30 hours) with Rhizopus oligosporus at 37°C were evaluated for tempeh preparation. Grains from the cultivar 'BRS 267' were used, and the experiment was carried out according to a central composite design (23). The response functions comprised the contents of genistin, malonyldaidzin, malonylgenistin, daidzein, and genistein, quantified by ultraperformance liquid chromatography (UPLC). Soaking, cooking, and fermentation times change the content, profile, and distribution of the different forms of isoflavones in tempeh. The highest bioconversion of glycoside isoflavones into aglycones occurred in 6?hour soaked soybean grains, whose cotyledons were cooked for 15 minutes and subjected to 18?hour fermentation. RESUMO:O objetivo deste trabalho foi avaliar o efeito das condições de processamento do tempeh de soja sobre o conteúdo de isoflavonas ??glicosídeos e sobre sua bioconversão em agliconas. Diferentes tempos de maceração (6, 12 e 18 horas), cozimento (15, 30 e 45 minutos) e fermentação (18, 24 e 30 horas) com Rhizopus oligosporus a 37°C foram avaliados na preparação do tempeh. Foram utilizados grãos da cultivar 'BRS 267', e o experimento foi realizado de acordo com um delineamento composto central (23). As funções?respostas compreenderam o teor de genistina, malonildaidzina, malonilgenistina, daidzeína e genisteína, quantificadas por cromatografia líquida de ultraeficiência (CLUE). Os tempos de maceração, cozimento e fermentação alteraram o conteúdo, o perfil e a distribuição das diferentes formas de isoflavonas no tempeh. A maior bioconversão de ??glicosídeos em agliconas ocorreu em grãos de soja macerados por 6 horas, cujos cotilédones foram cozidos por 15 minutos e submetidos à fermentação por 18 horas.

Field-oriented assessment of agricultural crops through temporal segmentation of modis VI data.

Monitoring agricultural crops constitutes a vital task for the general understanding of land use spatio-temporal dynamics. This paper presents an approach for the enhancement of current crop monitoring capabilities on a regional scale, in order to allow for the analysis of environmental and socio-economic drivers and impacts of agricultural land use. This work discusses the advantages and current limitations of using 250m VI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for this purpose, with emphasis in the difficulty of correctly analyzing pixels whose temporal responses are disturbed due to certain sources of interference such as mixed or heterogeneous land cover. It is shown that the influence of noisy or disturbed pixels can be minimized, and a much more consistent and useful result can be attained, if individual agricultural fields are identified and each field's pixels are analyzed in a collective manner. As such, a method is proposed that makes use of image segmentation techniques based on MODIS temporal information in order to identify portions of the study area that agree with actual agricultural field borders. The pixels of each portion or segment are then analyzed individually in order to estimate the reliability of the temporal signal observed and the consequent relevance of any estimation of land use from that data. The proposed method was applied in the state of Mato Grosso, in mid-western Brazil, where extensive ground truth data was available. Experiments were carried out using several supervised classification algorithms as well as different subsets of land cover classes, in order to test the methodology in a comprehensive way. Results show that the proposed method is capable of consistently improving classification results not only in terms of overall accuracy but also qualitatively by allowing a better understanding of the land use patterns detected. It thus provides a practical and straightforward procedure for enhancing crop-mapping capabilities using temporal series of moderate resolution remote sensing data.

Detecting outliers and asserting consistency in agriculture ground truth information by using temporal VI data from modis.

Collecting ground truth data is an important step to be accomplished before performing a supervised classification. However, its quality depends on human, financial and time ressources. It is then important to apply a validation process to assess the reliability of the acquired data. In this study, agricultural infomation was collected in the Brazilian Amazonian State of Mato Grosso in order to map crop expansion based on MODIS EVI temporal profiles. The field work was carried out through interviews for the years 2005-2006 and 2006-2007. This work presents a methodology to validate the training data quality and determine the optimal sample to be used according to the classifier employed. The technique is based on the detection of outlier pixels for each class and is carried out by computing Mahalanobis distances for each pixel. The higher the distance, the further the pixel is from the class centre. Preliminary observations through variation coefficent validate the efficiency of the technique to detect outliers. Then, various subsamples are defined by applying different thresholds to exclude outlier pixels from the classification process. The classification results prove the robustness of the Maximum Likelihood and Spectral Angle Mapper classifiers. Indeed, those classifiers were insensitive to outlier exclusion. On the contrary, the decision tree classifier showed better results when deleting 7.5% of pixels in the training data. The technique managed to detect outliers for all classes. In this study, few outliers were present in the training data, so that the classification quality was not deeply affected by the outliers.