Geographic Object-Based Analysis of Airborne Multispectral Images for Health Assessment of Capsicum annuum L. Crops

Vegetation health assessment by using airborne multispectral images throughout crop production cycles, among other precision agriculture technologies, is an important tool for modern agriculture practices. However, to really take advantage of crop fields imagery, specialized analysis techniques are needed. In this paper we present a geographic object-based image analysis (GEOBIA) approach to examine a set of very high resolution (VHR) multispectral images obtained by the use of small unmanned aerial vehicles (UAVs), to evaluate plant health states and to generate cropland maps for Capsicum annuum L. The scheme described here integrates machine learning methods with semi-automated training and validation, which allowed us to develop an algorithmic sequence for the evaluation of plant health conditions at individual sowing point clusters over an entire parcel. The features selected at the classification stages are based on phenotypic traits of plants with different health levels. Determination of areas without data dependencies for the algorithms employed allowed us to execute some of the calculations as parallel processes. Comparison with the standard normalized difference vegetation index (NDVI) and biological analyses were also performed. The classification obtained showed a precision level of about 95 % in discerning between vegetation and non-vegetation objects, and clustering efficiency ranging from 79 % to 89 % for the evaluation of different vegetation health categories, which makes our approach suitable for being incorporated at C. annuum crop’s production systems, as well as to other similar crops. This methodology can be reproduced and adjusted as an on-the-go solution to get a georeferenced plant health estimation

Factores de riesgo asociados a recaída de enfermedad por reflujo gastroesofágico en pacientes de primer nivel de atención exitosamente tratados con inhibidor de la bomba de protones [Risk factors associated with gastroesophageal reflux disease relapse in primary care patients successfully treated with a proton pump inhibitor]

Resumen Antecedentes No existen estudios en primer nivel de atención sobre factores asociados a recaída de enfermedad por reflujo gastroesofágico (ERGE). Objetivo Identificar factores de riesgo asociados a recaída de ERGE en pacientes de primer nivel de atención que respondieron adecuadamente a un tratamiento corto con inhibidor de la bomba de protones. Pacientes y métodos Estudio de cohorte, se incluyeron casos incidentes de ERGE. Se dio tratamiento con omeprazol durante 4 semanas. Se aplicó ReQuest y un cuestionario de factores de riesgo. Se determinó la tasa de éxito terapéutico y de recaída a las 4 y 12 semanas después de suspender el tratamiento. Se realizó análisis de regresión logística de los posibles factores de riesgo para recaída de ERGE. Resultados De 83 pacientes, 74 (89.16%) respondieron al tratamiento. Los síntomas recurrieron en 36 pacientes (48.64%) a las 4 semanas y en 13 pacientes (17.57%) a las 12 semanas; recaída acumulada: 66.21%. En el análisis multivariado RM (intervalo de confianza del 95%): escolaridad básica o menor 24.95 (1.92-323.79), sobrepeso 1.76 (0.22-13.64), obesidad 0.25 (0.01-3.46), consumo de 4-12 tazas de café al mes 1.00 (0.12-7.84), cítricos 14.76 (1.90-114.57), AINE 27.77 (1.12-686.11), chocolate 0.86 (0.18-4.06), ácido acetilsalicílico 1.63 (0.12-21.63), tabaquismo 0.51 (0.06-3.88), bebidas carbonatadas 4.24 (0.32-55.05), picante de 7-16 veces/mes 1.39 (0.17-11.17), picante ≥ 20 veces/mes, 4.06 (0.47-34.59) de recaída de ERGE a las 12 semanas de suspender tratamiento. Conclusiones La tasa de recaída posterior al tratamiento corto con omeprazoI fue alta. El consumo de cítricos y el consumo de AINE incrementaron la posibilidad de recaída de ERGE. Abstract Background There are no studies on the factors associated with gastroesophageal reflux disease (GERD) relapse in primary care patients. Aim To identify the risk factors associated with GERD relapse in primary care patients that responded adequately to short-term treatment with a proton pump inhibitor. Patients and methods A cohort study was conducted that included GERD incident cases. The patients received treatment with omeprazole for 4 weeks. The ReQuest questionnaire and a risk factor questionnaire were applied. The therapeutic success rate and relapse rate were determined at 4 and 12 weeks after treatment suspension. A logistic regression analysis of the possible risk factors for GERD relapse was carried out. Results Of the 83 patient total, 74 (89.16%) responded to treatment. Symptoms recurred in 36 patients (48.64%) at 4 weeks and in 13 patients (17.57%) at 12 weeks, with an overall relapse rate of 66.21%. The OR multivariate analysis (95% CI) showed the increases in the possibility of GERD relapse for the following factors at 12 weeks after treatment suspension: basic educational level or lower, 24.95 (1.92-323.79); overweight, 1.76 (0.22-13.64); obesity, 0.25 (0.01-3.46); smoking, 0.51 (0.06-3.88); and the consumption of 4-12 cups of coffee per month, 1.00 (0.12-7.84); citrus fruits, 14.76 (1.90-114.57); NSAIDs, 27.77 (1.12-686.11); chocolate, 0.86 (0.18-4.06); ASA 1.63 (0.12-21.63); carbonated beverages, 4.24 (0.32-55.05); spicy food 7-16 times/month, 1.39 (0.17-11.17); and spicy food ≥ 20 times/month, 4.06 (0.47-34.59). Conclusions The relapse rate after short-term treatment with omeprazole was high. The consumption of citrus fruits and NSAIDs increased the possibility of GERD relapse

Use of family structure information in interaction with environments for leveraging genomic prediction models

The characterization of genomes with great detail offered by the modern genotyping platforms have opened a venue for accurately predicting the genotype-by-environment interaction (GE) effects of untested genotypes in different environmental conditions. Already developed statistical models have shown the advantages of including the GE interaction component in the prediction context using molecular markers, pedigree, or both. In order to leverage the family information of highly structured populations when pedigree data is not available, we developed a model that uses the family membership instead. The proposed model extends the reaction norm model by including the interaction between families and environments (FE). A representative fraction of a soybean Nested Association Mapping population (16,187 grain yield records) comprising 38 bi-parental families (1358 genotypes) observed in 18 environments (2011, 2012, and 2013) was used to contrast the proposed model with three conventional prediction models. Two cross- validation scenarios (prediction of tested [CV2] and untested [CV1] genotypes) with a twofold design (50% for training and testing sets) were used for mimicking prediction situations that breeders face in fields. Results showed that the family factor in interaction with environments explains a sizable amount of the phenotypic variability. This helped to improve the predictive ability with respect to the main effects model (GBLUP) around 41% (CV2) and 49% (CV1), and about 17% with respect to the conventional reaction norm model. The inclusion of the FE term not only improved the global results but also significantly increased the prediction accuracy of those environments where the conventional models showed a very poor performance. These results show the importance of taking into consideration the family structure existing in breeding programs for improving the selection strategies in multi-parental populations

Programas sociales, pobreza y participación ciudadana

Esta publicación tiene por objeto establecer, empíricamente, la complementariedad entre el Estado y la sociedad civil en el marco de las políticas sociales y la lucha contra la pobreza

Programas sociales, pobreza y participación ciudadana

Esta publicación tiene por objeto establecer, empíricamente, la complementariedad entre el Estado y la sociedad civil en el marco de las políticas sociales y la lucha contra la pobreza