Market Participation of Smallholder Pigeon Pea Farmers in Makueni County, Kenya

This study sought to assess the factors that influence market participation of the smallholder pigeon pea farmers in Makueni County, Kenya. A stratified sampling procedure was used to obtain information from 198 respondents and the information was captured through the use of a structured questionnaire. Results show that 70% of the farmers in the study participated in the market as sellers. A Tobit Model was used to analyse the socio economic and institutional factors affecting participation. The results revealed that gender of household head, household size, off-farm income, price, membership to a farmer’s organization and access to market information influenced market participation. This study recommends first, the intensified use of improved pigeon pea cultivar to increase the marketable surplus. Secondly, strengthening and transformation of the existing farmer organisations into marketing groups so as to enhance market linkages to more lucrative markets and reduce transaction costs. Thirdly, investment in telecommunication platforms so as to ensure timely market information such as price, quantities and varieties required are disseminated to the farmers e.g. through mobile phones. Keywords: market participation, smallholder farmers, pigeon pea DOI: 10.7176/JESD/10-16-12 Publication date: August 31st 201

Abscisic Acid Mediates Drought-Enhanced Rhizosheath Formation in Tomato

The rhizosheath, commonly defined as soil adhering to the root surface, may confer drought tolerance in various crop species by enhancing access to water and nutrients under drying stress conditions. Since the role of phytohormones in establishing this trait remains largely unexplored, we investigated the role of ABA in rhizosheath formation of wild-type (WT) and ABA-deficient (notabilis, not) tomatoes. Both genotypes had similar rhizosheath weight, root length, and root ABA concentration in well-watered soil. Drying stress treatment decreased root length similarly in both genotypes, but substantially increased root ABA concentration and rhizosheath weight of WT plants, indicating an important role for ABA in rhizosheath formation. Neither genotype nor drying stress treatment affected root hair length, but drying stress treatment decreased root hair density of not. Under drying stress conditions, root hair length was positively correlated with rhizosheath weight in both genotypes, while root hair density was positively correlated with rhizosheath weight in well-watered not plants. Root transcriptome analysis revealed that drought stress increased the expression of ABA-responsive transcription factors, such as AP2-like ER TF, alongside other drought-regulatory genes associated with ABA (ABA 8′-hydroxylase and protein phosphatase 2C). Thus, root ABA status modulated the expression of specific gene expression pathways. Taken together, drought-induced rhizosheath enhancement was ABA-dependent, but independent of root hair length

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