Aim Large-scale banana production in Zimbabwe is confined to agro-ecological zone 1, although other regions have managed to produce to a limited extent. This is mainly because of the favourable climatic conditions for banana growth found in this region. Across Zimbabwe, there are zones that can be modified to mimic climatic conditions in agro-ecological zone one. Therefore the aim of the research was to find suitable area that supports banana optimal growth. Location Zimbabwe Time period 36 months Major taxa studied Plantae, Magnoliophyta, Liliopsida, Zingiberales, Musaceae, Musa Methods In this study, new potential production areas were prospected using Maximum Entropy (MaxEnt). The data output was mapped in ArcGIS. An average of training and test Area Under Curve of 0.9380 and 0.976 respectively with a standard deviation of 0.03 was achieved after 10 replication trials. Results The Area Under Curve was represented by showing sensitivity on the y-axis and 1-specificity on the x-axis for all potential thresholds. Based on the bioclimatic data, the outputted model showed Area Under Curve values greater than 0.9 indicating a good prediction ability. Distinction of suitable areas from unsuitable areas was established using an automatic generated threshold. Low suitable areas ranged from 0-0.46, medium suitable areas ranged from 0.46-0.77 and high suitable areas ranged from 0.77-1. Potential production areas lied in the medium range due to a number of factors. An approximate total of 4757.112 km2 was found to be suitable for banana expansion in Zimbabwe and this equates to over USD $ 1,813,715.9844 billion dollars annually in net profit. Main conclusion The major environmental factors affecting banana distribution in Zimbabw were found to be precipitation and temperature therefore irrigation schemes in suitable areas that has water bodies could be of great help towards banana production expansion. Keywords: banana production ,Maxent, GIS, species distribution models

AIMS Doxorubicin-induced cardiotoxicity (DIC) is a significant cause of mortality in cancer care. This study was conducted to establish the frequency of DIC in Zimbabwean breast cancer patients on doxorubicin and to test the DIC predictive power of genetic biomarkers. METHODS A cohort of 50 Zimbabwean breast cancer patients treated with doxorubicin were followed up for 12 months with serial echocardiography and genotyped for UGTA1A6*4, SLC28A3 and RARG. 11% of the patients experienced DIC. RESULTS The frequency of SLC28A3 (rs7853758), UGT1A6*4 (rs17863783) and RARG (rs2229774) was 60.7%, 17.9% and 14.3% respectively. No association between DIC and the three variants was observed. CONCLUSIONS This is the first study on the prevalence of DIC and associated genetic biomarker predictive evaluation in Zimbabwean breast cancer patients. The genetic frequencies observed in our study was different to that reported in other populations. A larger sample size with a longer follow up time will be necessary in future studies.

Aim The efficiency of production depends greatly on knowledge of the plant’s performance (including stress tolerance, nutritional quality and overall yield) and genetics. The review was aimed at gathering information on the conservation of banana germplasm and its potential in breeding programs. Finding out whether banana cultivars being grown in Zimbabwe have been characterized both genetically and morphologically thus creating a catalogue and also assessing production and its impact in Zimbabwean economy. The evaluation of species distribution models that can better extrapolate production to new area within the country. Location Zimbabwe Methods Obtaining information on banana production in Zimbabwe has been done through phone call inquires to research stations and plantations, face to face inquires and literature search on peer-reviewed publications and also greys literature. Results Information obtained through database search was extremely limited. Literature citing banana production in Zimbabwe was not greater than 0.00028%. Interaction with farmers and the department of Agricultural, Technical and Extension Services (AGRITEX) Officers yielded better results showing a clear picture of undocumented relevant banana information. Main Conclusion Characterization of Musa Spp. is a necessity for germplasm conservation, breeding and improved banana production. Currently, there is vast literature on characterized banana accessions across the globe, but limited publicly available information concerning accessions in Zimbabwe. Banana production in Zimbabwe is concentrated in the warm and humid areas and similar climatic conditions are found in areas dotted across Zimbabwe. Using species distribution models, cultivars can be mapped to new environments and this in return expands production area in the country. In so doing, cultivars digital maps are created for ease of banana information access. Cultivar maps and biological information from multi-locational gene banks has great potential for use in banana production improvement programs.