The objective of this study was to evaluate gastric emptying (GE) in pediatric patients with functional constipation. GE delay has been reported in adults with functional constipation. Gastric emptying studies were performed in 22 children with chronic constipation, fecal retention and fecal incontinence, while presenting fecal retention and after resuming regular bowel movements. Patients (18 boys, median age: 10 years; range: 7.2 to 12.7 years) were evaluated in a tertiary pediatric gastroenterology clinic. Gastric half-emptying time of water (reference range: 12 ± 3 min) was measured using a radionuclide technique immediately after first patient evaluation, when they presented fecal impaction (GE1), and when they achieved regular bowel movements (GE2), 12 ± 5 weeks after GE1. At study admission, 21 patients had reported dyspeptic symptoms, which were completely relieved after resuming regular bowel movements. Medians (and interquartile ranges) for GE1 and GE2 were not significantly different [27.0 (16) and 27.5 (21) min, respectively (P = 0.10)]. Delayed GE seems to be a common feature among children with chronic constipation and fecal retention. Resuming satisfactory bowel function and improvement in dyspeptic symptoms did not result in normalization of GE data.

O desenvolvimento de modelos agrometeorológicos que possibilitem a estimativa de quebra de produtividade antecipada é importante para subsidiar os programas de previsão de safras de café. Uma boa estimativa da produtividade implica utilização de modelos que considerem os efeitos ambientais aos processos fisiológicos determinantes da produção. Este trabalho teve o objetivo de modificar e parametrizar um modelo matemático agrometeorológico de monitoramento e de estimativa de quebra de produtividade do cafeeiro (Coffea arabica L.), considerando diferentes regiões do Estado de São Paulo. O modelo original se baseia apenas na penalização da produtividade potencial da cultura em função do déficit hídrico quantificado através da relação [1- (ETr/ETp)], ajustadas por coeficientes de sensibilidade da cultura (ky) ocorridos em diferentes fases fenológicas. O modelo foi modificado visando considerar também os efeitos da produtividade do ano anterior e de temperaturas adversas. A parametrização dos coeficientes "ky" indicou os maiores valores durante as fases do florescimento e da granação. O teste do modelo parametrizado indicou valores de coeficientes de correlação "R" entre 0,76 e 0,93, de índices de concordância "d" entre 0,73 e 0,90, de índices de confiança "C" entre 0,60 e 0,84 e de erros aleatórios (Ea), variando de 144 a 558 Kg.ha-1. Os valores de erros sistemáticos (Es) foram relativamente baixos para as Fazendas São Carlos e Monte D'Este (324 e 396 kg ha-1), quando comparados com a E.E. Mococa e Fazenda Serra (744 e 762 kg ha-1), pois apresentaram pequena tendência a superestimar a produtividade. Por esses resultados, verifica-se que o modelo modificado e parametrizado tem potencial para estimar a produtividade do café, podendo servir como subsídio aos trabalhos de previsão de safra.

Agrometeorological models make possible to assess the quantitative influence of climatic variables, such as air temperature and soil water balance on the coffee development and grain production. An agrometeorological model (CAMARGO et al., 2003) that monitor and assess agrometeorological impact on coffee yields just before the beginning of the maturation growth stage was modified and calibrated. Grain yield were collected from adult coffee plantations at four different regions of the State of Sao Paulo, Brazil. The modified agrometeorological model is based in two parts: first, the model estimates the beginning of the floral induction based on accumulated growing degree days, and a critical rainfall depth. The second part is based on penalization of the potential crop grain yield according to the previous yield and the water stress ratio (ETr/ETp), derived by a 10-day soil water balance during different growth stages. These ratios were weighted by derivation of crop phase yield-response sensitivity coefficients (Ky values), in a multiplicative type model. Also, the model considers penalization for minimum and maximum air temperature. An analysis of the sensitivity coefficients values shows that this model gives higher weight to the water relations during flowering and coffee bean formation phases. This period generally occurs between October and January and it will determine the production of the coffee crop. The statistical analysis for actual and estimated coffee grain yield presented a good linear relationship, "R" between 0.76 and 0.93, "d" index of agreement between 0.73 and 0.90, "C" index of performance between 0.60 and 0.84, and "Ea" unsystematic error between 144 and 558 kg ha-1. The values of "Es" systematic error were relatively low, between 324 and 762 kg ha-1, showing a little tendency of the model to overestimate the predicting coffee grain productivity. The results support the overall conclusion that the proposed model shows a good capacity to estimate coffee grain productivity and it is a promising tool for monitoring climatic impacts on coffee grain yields.