Nutritive Parameters Evolution of Maize Seeds Conserved by Triple Bagging System and Biopesticides (Lippia multiflora and Hyptis suaveolens Leaves) in Cote d’Ivoire

This study, initiated in Côte d'Ivoire, aimed to evaluate the effectiveness of the triple bagging system associated or not with biopesticides on the conservation of biochemical parameters, in particular its nutritional potential according to a central composite design (CCD). It was carried in Côte d'Ivoire at Laboratory of Biochemistry and Food Science from March 2016 to September 2017. Shelf life, biopesticides rate and interactions between shelf life and biopesticides had a significant influence on the biochemical characteristics of maize. The polypropylene bag (control) had the highest values after eighteen (18) months of moisture storage (9.02% to 16.99%) and showed very high fibre losses (P<0.001) (5.78% to 4.28%), total sugars (2.62% to 1.30%), reducing sugars (0.47% to 0.27%), starch (75.20% to 46.10%), fat (5.51% to 3.33%), protein (8.60% to 6.87%), total carbohydrate (75.20% to 71.51%), ash (1.68% to 1.30%) and energy value (384.78% to 343.48%). Concerning the triple bagging system without biopesticides, the variation is similar to the treatments that received the biopesticides up to 9.5 months of storage before presenting values almost similar to the control bag after the 18 months of storage. While triple bagging systems with the presence of biopesticides after 18 months of storage show slight variations in moisture (9.02% to 12.47%), fibre (5.78% to 5.56%), total sugars (2.62% to 1,88%), reducing sugars (0.47% to 0.37%), starch (75.20% to 60.03%), fat (5.51% to 5.00%), protein (8.60% to 7.84%), total carbohydrates (75.20% to 72.69%), ash (1.68% to 1.50%) and energy value (384.78% to 368.93%). The results of these tests show that maize grains stored in the presence of biopesticides best retain their biochemical characteristics. Also, the results indicate that the rate of 1.01% biopesticides could be recommended for maintaining all biochemical parameters up to 18 months of storage.

A partition bagging ensemble learning algorithm for Parkinson's speech data mining / 生物医学工程学杂志

Methods for achieving diagnosis of Parkinson's disease (PD) based on speech data mining have been proven effective in recent years. However, due to factors such as the degree of disease of the data collection subjects and the collection equipment and environment, there are different categories of sample aliasing in the sample space of the acquired data set. Samples in the aliased area are difficult to be identified effectively, which seriously affects the classification accuracy of the algorithm. In order to solve this problem, a partition bagging ensemble learning is proposed in this article, which measures the aliasing degree of the sample by designing the the ratio of sample centroid distance metrics and divides the training set into multiple subsets. And then the method of transfer training of misclassified samples is used to adjust the results of subset partitioning. Finally, the optimized weights of each sub-classifier are used to integrate the test results. The experimental results show that the classification accuracy of the proposed method is significantly improved on two public datasets and the increasement of mean accuracy is up to 25.44%. This method not only effectively improves the classification accuracy of PD speech dataset, but also increases the sample utilization rate, providing a new idea for the diagnosis of PD.

Building a Prediction System of Influenza Epidemics with LASSO Regression Model and Baidu Search Query Data / 中国卫生统计

Objective To evaluate the performance of a prediction system built with LASSO regression model and Baidu search query data.Methods Based on a strategy using a combination of Bagging and multi-measure optimization method,this study proposed an ensemble LASSO regression model which had an obviously improved performance,and applied it to predict the epidemics of influenza in China.Results The results showed that the improved model had significantly smaller prediction error rates than that of the conventional LASSO regression model for influenza cases during the study period of 2011-2015.This study designed an open source R package,SparseLearner,which was conveniently used and further developed.Conclusion The combination of Bagging and multi-measure optimization method is an efficient strategy to improve the performance of LASSO regression model.The proposed ensemble LASSO regression model in this study can be applied for the prediction of infectious diseases epidemics.

A Study on Model Performance for Ethanol Precipitation Process of Lonicera japonica by NIR Based on Bagging-PLS and Boosting-PLS algorithm / 分析化学

ToprovidethemethodologyforrapidqualityevaluationofLonicerajaponica,wehaveestablished the stable quantitative model of near infrared spectroscopy ( NIR) . The performance of Bagging partial least squares (Bagging-PLS) model and Boosting partial least squares (Boosting-PLS) model was compared with that partial least squares ( PLS ) model based on the NIR data of ethanol precipitation process of Lonicera japonica. On this basis, the performance of these two models after variables selection was also studied by the methods of siPLS ( synergy interval partial least squares ) and CARS ( competitive adaptive reweighted sampling) . The experimental results showed that the prediction performance of Bagging-PLS and Boosting-PLS models was superior to PLS model with the latent factor of 10 . The band of 820-1029 . 5 nm and 1030-1239. 5 nm for the first batch was selected by the method of siPLS. In addition, the band of 820-1029. 5 nm and 1030-1239. 5 nm was selected for the second batch sample in the same method. Furthermore, the method of CARS was taken to select variables for the two batches samples with 5-fold cross-validation and 10-fold cross-validation. And the lowest RMSECV( root mean square error of cross-validation) values were used to take subset. Compared to the model performance without the method of CARS, the RMSEP value of the Bagging-PLS model and Boosting-PLS model for the concentration of chlorogenic acid reduced by 0 . 02-0 . 04 g/L and rp(correlation coefficient of prediction)value increased by 4%-5%. Generally, Bagging-PLS and Boosting-PLS could be regarded as rapid prediction methodsfor NIR quantitative models of ethanol precipitation process of Lonicera japonica.

Qualidade de frutos de caqui 'Jiro' ensacados com diferentes embalagens / Fruit quality of 'Jiro' japanese persimmon fruits bagged with different types of packings

A técnica de ensacamento de frutos vem sendo utilizadas por muitos produtores, visando a melhorqualidade de frutos, redução de aplicação de agrotóxicos e diminuição dos danos provocados porpragas e doenças. O presente trabalho avaliou a qualidade de frutos de caquizeiro 'Jiro' ensacados comdiferentes tipos de embalagens. O experimento foi conduzido no pomar de caquizeiro da FazendaExperimental do Canguiri da UFPR, localizada em Pinhais-PR. A adubação e o manejo do pomar foirealizado de forma orgânica. Os tratamentos foram: saco plástico microperfurado, saco de papel pardo,saco de papel manteiga, saco de jornal e testemunha sem ensacamento. O delineamento experimental foiem blocos ao acaso com cinco repetições, sendo cada planta considerada um bloco. Cada parcela foicomposta de 20 frutos. O ensacamento foi realizado após a queda fisiológica dos frutos jovens,procurando-se distribuir os tipos de sacos aleatoriamente dentro de cada planta. A avaliação foi realizadaapós 77 dias do ensacamento, verificando-se o número de frutos colhidos por parcela, massa dos frutos,diâmetro dos frutos, número de frutos em cada categoria de maturação, número de frutos infectados porsujeira-de-mosca (Schyzothyrium pomi) e teor de sólidos solúveis. Houve diferença entre os tratamentosapenas na incidência de sujeira-de-mosca e na porcentagem de coloração dos frutos. O ensacamento decaqui com sacos de jornal ou papel pardo reduziu a incidência do fungo S. pomi e a coloração daepiderme dos frutos. O tamanho e teor de sólidos solúveis não foram influenciados pelo ensacamento.

The bagging technique of fruits comes being used by many producers, aiming at the fruit quality,reduction of application of agro toxics and reduction of the damages caused by insects and diseases.The present work evaluated the quality of bagging fruits of 'Jiro' japanese persimmon with differenttypes of bags. The experiment was lead in the orchard of Japanese persimmon of the Experimental Farmof the Canguiri of the UFPR, located in Pinhais-PR. The fertilization and the management of the orchardwere entirely organic. The treatments had been: microperforated plastic bag, brown kraft paper bag,butter-like paper bag, newspaper bag and without bagging. The experimental design used was randomizedblocks with five replicates, being each plant considered a block. Each parcel was composed by 20 fruits.The bagging was made after the physiological fall of the young fruits, distributing the types of bags aleatorely inside each plant. The evaluation was 77 days after bagging, verifying the number of fruitsharvested, mass of the fruits, diameter of the fruits, number of fruits in each category of maturation,number of fruits attacked with Schyzothyrium pomi and soluble solids content. The results were significantonly in the incidence of S. pomi and in the percentage of coloration of the fruits. The bagging withnewspaper and brown kraft bags reduced the incidence of S. Pomi and the color of fruits. The size andthe soluble solids content were not affected by bagging