RESUMEN
Field pea (Pisum sativum L.) is a key cool-season food legume grown in Ethiopia, particularly in the Southeastern Arsi Zone. Although there is potential for field pea production in the area, adopting new and improved varieties is challenging because local farmers frequently prioritize cereal crops over field peas. To tackle this issue, a study was conducted to identify and promote high-yielding, improved field pea varieties suitable for the Southeastern farming community and similar agro-ecologies. The study focused on assessing the relationship between genotype and environment as well as the stability pattern of 14 advanced field pea genotypes. The genotypes were evaluated in eight environments in two consecutive cropping seasons (2014-2015) in southeast Ethiopia. The study utilized a randomized complete block design consisting of four replications. Various parametric stability analyses were used, including joint regression, additive main effect and multiplicative interaction (AMMI), and additive main effect and multiplicative interaction stability value (ASV). The grain yield was significantly influenced by genotype, location, and their interactions. The average grain yield ranged from 2809.5 kg ha-1 to 3509.1 kg ha-1. Eberhart's stability analysis identified stable genotypes: G3, G4, and G8, while G14 was unstable. According to additive main effect and multiplicative interaction stability value (ASV) and yield stability index (YSI), genotypes G12 and G13 had very low ASV values, whereas genotype G4 had very low ASV and YSI values. The AMMI and GGE biplot graphs showed that the principal component axes (PC1) and (PC2) accounted for 64.1 % and 61.36 % of the total variation, respectively. The results indicated that genotypes responded differently to environmental conditions and that the environment also influenced genotype performance. Genotypes G4 and G3 consistently performed well and exhibited remarkable stability, making them excellent cultivars for improving field pea productivity.
RESUMEN
Adzuki bean beetle, Callosobruchus chinensis (L.) (Coleoptera: Bruchidae), is one of the most important pests of pea (Pisum sativum L.) crops in Ethiopia. The study focused on the association of resistance potential in the no-choice test of pea genotypes managed at different fertility levels and trait contributions. Based on the significance of fertility levels, genotypes were grouped into four, six, and five clusters, viz. Under neither rhizobium and phosphorus, rhizobium alone and rhizobium and phosphorus, respectively. Regardless of fertility levels, the inter-cluster distance (D2) values of the two potential clusters were highly significant (P < 0.01). At all fertility levels, the average performance of genotypes in each cluster for individual traits to infestation varied significantly. Genotype distribution patterns tended to group together into a small number of clusters. Eighty genotypes of the pea (Pisum sativum L. subsp. sativum and Pisum sativum L. subsp. abyssinicum A. Braun) were systematically managed under three fertility levels, and the first four principal components accounted for 94%, 92.3%, and 94.2% of the total variation. The primary trait that determines the resistance potential of pea genotypes is the trait susceptibility index (SI), which exhibits highly significant and adverse associations with critical traits such as the date of adult emergency and the percentage of seed coat, while exhibiting highly significant and favorable associations with the remaining traits at all fertility levels. The remaining characteristics showed highly significant positive or negative correlations within and particularly with the characteristics that determine resistance. Therefore, the cultivar "Adi" from "Pisum sativum L. subsp. sativum" had higher susceptibility compared to other genotypes, while the small-seeded pea genotypes "Pisum sativum L. subsp. abyssinicum A. Braun"; fpcoll-1/07, fpcoll-2/07, fpcoll-21/07, and fpcoll-43/07 were moderately resistant.
RESUMEN
BACKGROUND: One-third to two-thirds of operated patients in low-income countries acquire surgical site infection, which is nine times higher when compared to high-resource countries. Identifying the incidence and risk factors that contribute to surgical site infection following cesarean delivery is a step ahead for preventing and reducing the problem. Nonetheless, the distribution of the problem in Addis Ababa, where the rate of cesarean delivery is relatively high compared to other parts of the country, is under investigation. OBJECTIVE: The aim of this study is to assess the incidence of surgical site infection among cesarean deliveries and factors associated with it in selected governmental hospitals found in Addis Ababa, Ethiopia, in 2019. METHOD: A hospital-based prospective cohort study design was employed to follow 175 women, who gave birth by cesarean delivery in selected government hospitals in Addis Ababa, from March 11 to April 9, 2019. Convenience sampling method was used to select study units from the randomly selected hospitals. Descriptive statistics were run for determining the rate of cesarean delivery surgical site infection. Presence and degree of association between outcome and independent variables were computed through bivariate logistic regression analysis and factors that had p < 0.2 significance level in the bivariate logistic regression analysis were considered in the multivariable logistic regression analysis. RESULT: From 166 participants who completed 30-day follow-up, 25 (15%) of the participants developed surgical site infection. Age, gestational age, duration of operation, and ≥5 vaginal examinations showed a significant association with the outcome variable with AOR (95% CI) of ((AOR = 1.504, 95% CI: (1.170 - 1.933, p < 0.2 significance level in the bivariate logistic regression analysis were considered in the multivariable logistic regression analysis. p < 0.2 significance level in the bivariate logistic regression analysis were considered in the multivariable logistic regression analysis. p < 0.2 significance level in the bivariate logistic regression analysis were considered in the multivariable logistic regression analysis. p < 0.2 significance level in the bivariate logistic regression analysis were considered in the multivariable logistic regression analysis. Conclusion and recommendation. Surgical site infection rate is higher and certain associations lost due to small sample size. Further interventional studies with vast sample size are recommended.