Electrophysiological and Behavioral Responses of Cabbage Aphid (Brevicoryne brassicae) to Rosemary (Rosmarinus officinalis) Volatiles, a Potential push Plant for Vegetable push-pull Cropping System.

The cabbage aphid (Brevicoryne brassicae) is a major pest of kale (Brassica oleraceae var. acephala), an important vegetable that is grown worldwide due to its high nutritional and economic value. Brevicoryne brassicae poses a great challenge to B. oleraceae var. acephala production, causing significant direct and indirect yield losses. Farmers overly rely on synthetic insecticides to manage the pest with limited success owing to its high reproductive behavior and development of resistance. This necessitates a search for sustainable alternatives to mitigate these challenges. This study assessed behavioral responses of B. brassicae to odors from rosemary (Rosmarinus officinalis) and B. oleraceae var. acephala headspace volatiles in a Perspex four-arm olfactometer. We identified and quantified volatiles emitted by each of the two plants and those eliciting antennal response using coupled gas chromatography-mass spectrometry (GC-MS) and GC-electroantennograhic detection(GC-EAD), respectively. Our findings revealed that B. brassicae spent more time in the arms of the olfactometer that contained B. oleraceae var. acephala volatiles compared to the arm that held R. officinalis volatiles. Additionally, B. brassicae spent more time in the olfactometer arms with B. oleracea var. acephala compared to the arms holding B. oleracea var. acephala and R. officinalis enclosed together and clean air. GC-MS analysis revealed diverse and higher quantities of volatile compounds in R. officinalis compared to B. oleraceae var. acephala. GC-EAD analysis showed that antennae of B. brassicae detected Linalool, α-Terpineol, Verbenone, Geraniol, Camphor, and Borneol from the volatiles of R. officinalis, and Sabinene, γ-Terpinene, and ß-Caryophyllene from B. oleraceae var. acephala volatiles. Our findings demonstrate the potential of R. officinalis as a repellent plant against B. brassicae and could be utilized as a 'push' plant in an intercropping strategy against this pest.

The soil microbiomes of forest ecosystems in Kenya: their diversity and environmental drivers.

Soil microbiomes in forest ecosystems act as both nutrient sources and sinks through a range of processes including organic matter decomposition, nutrient cycling, and humic compound incorporation into the soil. Most forest soil microbial diversity studies have been performed in the northern hemisphere, and very little has been done in forests within African continent. This study examined the composition, diversity and distribution of prokaryotes in Kenyan forests top soils using amplicon sequencing of V4-V5 hypervariable region of the 16S rRNA gene. Additionally, soil physicochemical characteristics were measured to identify abiotic drivers of prokaryotic distribution. Different forest soils were found to have statistically distinct microbiome compositions, with Proteobacteria and Crenarchaeota taxa being the most differentially abundant across regions within bacterial and archaeal phyla, respectively. Key bacterial community drivers included pH, Ca, K, Fe, and total N while archaeal diversity was shaped by Na, pH, Ca, total P and total N. To contextualize the prokaryote diversity of Kenyan forest soils on a global scale, the sample set was compared to amplicon data obtained from forest biomes across the globe; displaying them to harbor distinct microbiomes with an over-representation of uncultured taxa such as TK-10 and Ellin6067 genera.

Diversity and structure of prokaryotic communities within organic and conventional farming systems in central highlands of Kenya.

Management practices such as tillage, crop rotation, irrigation, organic and inorganic inputs application are known to influence diversity and function of soil microbial populations. In this study, we investigated the effect of conventional versus organic farming systems at low and high input levels on structure and diversity of prokaryotic microbial communities. Soil samples were collected from the ongoing long-term farming system comparison trials established in 2007 at Chuka and Thika in Kenya. Physicochemical parameters for each sample were analyzed. Total DNA and RNA amplicons of variable region (V4-V7) of the 16S rRNA gene were generated on an Illumina platform using the manufacturer's instructions. Diversity indices and statistical analysis were done using QIIME2 and R packages, respectively. A total of 29,778,886 high quality reads were obtained and assigned to 16,176 OTUs at 97% genetic distance across both 16S rDNA and 16S rRNA cDNA datasets. The results pointed out a histrionic difference in OTUs based on 16S rDNA and 16S rRNA cDNA. Precisely, while 16S rDNA clustered by site, 16S rRNA cDNA clustered by farming systems. In both sites and systems, dominant phylotypes were affiliated to phylum Actinobacteria, Proteobacteria and Acidobacteria. Conventional farming systems showed a higher species richness and diversity compared to organic farming systems, whilst 16S rRNA cDNA datasets were similar. Physiochemical factors were associated differently depending on rRNA and rDNA. Soil pH, electrical conductivity, organic carbon, nitrogen, potassium, aluminium, zinc, iron, boron and micro-aggregates showed a significant influence on the observed microbial diversity. The observed higher species diversity in the conventional farming systems can be attributed to the integration of synthetic and organic agricultural inputs. These results show that the type of inputs used in a farming system not only affect the soil chemistry but also the microbial population dynamics and eventually the functional roles of these microbes.

Bacteria and Archaea diversity within the hot springs of Lake Magadi and Little Magadi in Kenya.

BACKGROUND: Lake Magadi and little Magadi are hypersaline, alkaline lakes situated in the southern part of Kenyan Rift Valley. Solutes are supplied mainly by a series of alkaline hot springs with temperatures as high as 86 °C. Previous culture-dependent and culture-independent studies have revealed diverse groups of microorganisms thriving under these conditions. Previous culture independent studies were based on the analysis of 16S rDNA but were done on less saline lakes. For the first time, this study combined illumina sequencing and analysis of amplicons of both total community rDNA and 16S rRNA cDNA to determine the diversity and community structure of bacteria and archaea within 3 hot springs of L. Magadi and little Magadi. METHODS: Water, wet sediments and microbial mats were collected from springs in the main lake at a temperature of 45.1 °C and from Little Magadi "Nasikie eng'ida" (temperature of 81 °C and 83.6 °C). Total community DNA and RNA were extracted from samples using phenol-chloroform and Trizol RNA extraction protocols respectively. The 16S rRNA gene variable region (V4 - V7) of the extracted DNA and RNA were amplified and library construction performed following Illumina sequencing protocol. Sequences were analyzed done using QIIME while calculation of Bray-Curtis dissimilarities between datasets, hierarchical clustering, Non Metric Dimensional Scaling (NMDS) redundancy analysis (RDA) and diversity indices were carried out using the R programming language and the Vegan package. RESULTS: Three thousand four hundred twenty-six and one thousand nine hundred thirteen OTUs were recovered from 16S rDNA and 16S rRNA cDNA respectively. Uncultured diversity accounted for 89.35 % 16S rDNA and 87.61 % 16S rRNA cDNA reads. The most abundant phyla in both the 16S rDNA and 16S rRNA cDNA datasets included: Proteobacteria (8.33-50 %), Firmicutes 3.52-28.92 %, Bacteroidetes (3.45-26.44 %), Actinobacteria (0.98-28.57 %) and Euryarchaeota (3.55-34.48 %) in all samples. NMDS analyses of taxonomic composition clustered the taxa into three groups according to sample types (i.e. wet sediments, mats and water samples) with evident overlap of clusters between wet sediments and microbial mats from the three sample types in both DNA and cDNA datasets. The hot spring (45.1 °C) contained less diverse populations compared to those in Little Magadi (81-83 °C). CONCLUSION: There were significant differences in microbial community structure at 95 % level of confidence for both total diversity (P value, 0.009) based on 16S rDNA analysis and active microbial diversity (P value, 0.01) based on 16S rRNA cDNA analysis, within the three hot springs. Differences in microbial composition and structure were observed as a function of sample type and temperature, with wet sediments harboring the highest diversity.