Biology subjects

Etaware, P. M.

Publications and source records attributed to Etaware, P. M..

4 recordsLinked to original sources

bioRxiv2021

Spatial and regional directory of tropical Auricularia mushrooms in Southwest, Nigeria

Bioremediation of wastelands and dumpsites in Africa is fast declining due to reduced mushroom populations. In the past, the forest of Africa was teaming with mushrooms, but nowadays; mushrooms are severely exploited, resulting in gradual drift to extinction. Mushrooms have the tendency to degrade recalcitrant wastes and absorb heavy metals (Bio-accumulation). Unless concerted efforts are made to rejuvenate or rescue the surviving mushroom population, Africa will one day be overshadowed by wastes. The mushroom diversity in Southwest, Nigeria was determined by both morphological and molecular markers, 14 primers (OPB-11, OPB-12, OPB-15, OPB-20, OPB-21, OPH-3, OPH-5, OPH-10, OPH-15, OPT-1, OPT-5, OPT-7, OPT-10 and OPT-19) produced polymorphism with the test samples under electrophoresis gel (PCR and RAPD). Using standard morphological markers, Auricularia auricula was found to be evenly distributed across 8 locations in Ekiti and Osun, 6 locations in Ogun, 5 locations in Oyo and 4 locations in Lagos. There was none identified in Ondo. Auricularia polytricha was found in abundance in all the locations in Ondo. Lagos only had 3 out of its outline Stations graced with the presence of A. polytricha, whereas, Ogun, Ekiti, Osun and Oyo had no records of A. polytricha. From the genetic dissimilarity chart, 6 clusters of mushroom, sub-characterized into 3 distinct species (Auricularia polytricha, A. auricula and an unrelated Auricularia outlier species) and 5 cultivars were obtained in the region of Southwest, Nigeria. The population of all the Auricularia mushrooms currently present in Southwest, Nigeria was effectively captioned (Location, type and identity) by this research.

molecular biology↗

bioRxiv2021

Biotransformation of agro-industrial waste to wealth in Africa through mushroom farming

Discarding Waste in open drainages, water bodies and unauthorized dumpsites is a common practice in Africa that is deleterious to the global ecosystem. Global warming, flooding and land encroachment are direct impact of these actions. Therefore, a proposed eco-friendly solution to efficient waste management in Africa is "Mushroom Farming". The region between Latitude 6.43-7.95{degrees}N and Longitude 2.88-5.24{degrees}E (Nigeria) was the research focus. Mushroom samples were collected, identified, coded and geo-tagged in the field, while Laboratory analyses and mushroom cultivation was conducted in NIHORT and University of Ibadan. The result showed that postharvest waste (rice straw) was best for spawning (Ek1-8[->]23days, LA1-8[->]21days, OG1-8[->]20days, and OY1-8[->]22days), while agro-waste from Gliricidium sepium facilitated early pin head emergence (26days) and fruiting (28days). Also, agro-waste from Cedrela odorata facilitated early maturation (3days after fruiting), and those from Mangifera indica, G. sepium and C. odorata, improved yield (9.05g), pileus size (4.24g) and dry matter (3.01g), respectively. The Laboratory analyses showed that LA1-8 had the best N2, Na and Ca contents (13.59, 70.49 and 61.90mg/100g, respectively), while fat, fibre and carbohydrate contents were highest in samples from EK1-8 (6.60%), OS1-8 (25.13%) and OG1-8 (54.23%), respectively. Mushroom farming is the key to efficient transformation of waste to wealth in Africa.

plant biology↗

bioRxiv2018

ETAPOD: A forecast model for prediction of black pod disease Outbreak in Nigeria

The misuse of toxic fungicides by indigenous cocoa farmers in Nigeria stem from their inability to predict the time for black pod disease (BPD) outbreak. Prediction of possible time for BPD outbreak will provide spotlight on areas under massive BPD invasion, minimise fungicide misuse and increase control accuracy. The Multiple Regression Model (MRM): Y=+{beta}1X1+{beta}2X2+...+{beta}nXn where Y is Nx1 matrix of response variable, X1,X2,...Xn are NxK matrices of regressors, and {beta}1,{beta}2,...{beta}n regression coefficients was used in model development. Eight models (MRM1-MRM8) were fitted from real life BPD data. The performances of the models were ascertained using SER, RMSEpred and R-SqAdj. Prediction(s) made by the best fitted model was compared to real life observations (Monthly BPD Occurrence (MBO), Total Annual Occurrence (TAO), and Average Annual Occurrence (AAO), respectively). The preferred model was MRM5 (ETAPOD) followed by MRM4, MRM1, MRM2, and MRM3 in terms of SER (0.22, 0.39, 0.45, 0.45 and 0.45), RMSEpred.(0.30, 039, 0.46, 0.46 and 0.46) and R-SqAdj.(0.67, 0.49, 0.32, 0.32, and 0.31), respectively. Predictions on BPD outbreak made by ETAPOD showed that MBO, TAO and AAO for some selected stations i.e. Owena and Waasimi were 9.05, 72.3 and 6.0% compared with observed BPD values of 9.5, 70.0, and 5.8%, respectively. Adaagba, Iyanfoworogi, and Owode-Igangan had 9.43, 77.8, and 6.5% as their predicted BPD values compared with the observed values of 9.0, 53.5, and 4.46%, respectively. ETAPOD performed better than other models and its predicted values were within the range of real life occurrence.

plant biology↗

bioRxiv2018

Black pod disease profile: Monitoring its outbreak in Southwest, Nigeria

Black pod disease (BPD) has been and still remains a major threat to cocoa farmers worldwide due to its annual recurrence, fast spread and highly destructive nature. The disease has caused great anxiety in many cocoa producing communities due to the inability of indigenous cocoa farmers to determine when and where BPD outbreak will take place. Twelve (12) stations were structured from four important cocoa-producing States in the Southwestern region of Nigeria. An investigation of BPD outbreak was conducted in 2015/2016 within these regions. Infected cocoa pods and topsoil samples were collected for laboratory analysis. Pests attack, cherelle wilt and BPD outbreak were seasonal with 50% chances of occurrence in all the stations. Black pod diseases outbreak was recorded in all the States (100%) during the rainy season. The disease was at its peak in August 2015 in almost all the stations (station 1 (30.0%), station 3 (23.0%), station 11 (16.0%), station 4 (9.0%), station 5 (7.0%), and station 8 (3.0%). The height of disease severity was in September 2015 (station 1 (100.0%), station 3 (96.7%), station 5 (85.7%), station 11 (84.3%), and station 4 (70.0%), with station 8 reaching the 100% mark in October 2015. Most cocoa farmlands are now being abandoned, unless concerted efforts are made to effectively manage the disease, BPD will greatly reduce cocoa production in Nigeria and around the world.

plant biology↗