2 research outputs found
Effect of levels and timing of application of gibberellic acid on growth and yield components of common beans
This study was conducted to determine the effect of levels and timing
of application of gibberellic acid (GA3) on growth and yield components
of common beans ( Phaseolus vulgaris L.). Experiments were conducted
at the Field Station Farm at the Faculty of Agriculture, University of
Nairobi, Kenya during 1997 and 1998. "Mwezi moja" bean cultivar was
used in study. Gibberellic acid (GA3) was sprayed at 0, 2.5, 5.0 and
7.5 mg l-1 to whole bean plants at 7, 14 or 28 days after emergence
(DAE). The effect of GA3 and timing of application on growth, yield and
yield components was significant (P≤0.05). Applications of GA3
led to increased plant height, leaf area index (LAI), fractional solar
radiation interception, root, shoot and the total dry mass. It also
increased yield per plant, pods per plant, 100-seed mass and harvest
index. The highest seed yields were equivallent to 1854 kg ha-1 in 1997
and 5890 kg ha-1 in 1998. These yields are high as compared to average
national yields of 500 kg ha-1. Significant differences in the
parameters measured were generally observed at 14 DAE in GA3 treated
plants.Cette étude était conduite pour déterminer les effets
des doses et le moment d'application de l'acide gibberellique (GA3) sur
la croissance et les composantes de rendement de l'haricot commun
(Phraseolus vulgaris L.). Les expériences étaient conduites
dans les champs de la station agricole de la Faculté de
l'Agriculture, Université de Naïrobi-Kenya entre 1997 et
1998. La variété « mwezi moja » était
utilisée dans cette étude. L'acide gibberellique était
appliquée à des doses de 0, 2.5, 5.0 et 7.5 mg l-1 à
toute les plantes de haricots à 7, 14 ou 28 jours après
l'émergence (DAE). Les effets de GA3 et le temps d'application sur
la croissance, le rendement et les composantes du rendement
étaient significatifs (P<0.05). L'application de GA3 entraina
l'augmentation de la taille des plantes, indice de surface des
feuilles, la fraction de l'énergie solaire interceptée, les
racines, shoot et la masse total de la matière sèche. Elle
entraina aussi l'augmentation du rendement par plante, gousse par
plante, la masse de 100 graines et l'indice de la récolte. Les
rendements les plus élévés étaient équivalents
à 1854 kg ha-1 en 1997 et 5890 kg ha-1 en 1998. Ces valeurs de
rendements sont élévées par rapport à la myenne
nationale de 500 kg ha-1. Des différences significatives
concernant les paramètres mesurés étaient
généralement observées à 14 jours après
émergence dans les plantes traitées au GA3
The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications
Background:
The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications.
Methods:
ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery.
Results:
The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784.
Conclusions:
This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance.
© 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran