Chemical variation and implications on repellecy activity of Tephrosia vogelii (Hook f.) Essential oils against Sitophilus zeamais Motschulsky

Chemical variability in the components of T. vogelii essential oils from eastern Uganda was identified using principal component analysis (PCA) and Agglomerative hierarchical clustering (AHC). Based on the profiles of the compounds of farnesene family three chemotypes were found: farnesol (chemotype 1), springene (β- Springene and α-Springene) and the β-Farnesene were distinctive in chemotype 2 and a mixed variety of farnesol and the Springene. In the three cases, alkybenzenes; o-xylene, m-xylene and ethylbenzene were significant components in the oil. 1,4-dihydroxy-p-menth-2-ene, 5,9-undecadien-2-one, 6,10-dimethyl, and 3-cyclohexen-1-carboxaldehyde,3,4-dimethyl were other prominent constituents. The yields of the essential oils did not vary significantly however the chemical composition varied with harvesting time during the rainy and dry seasons. In choice repellency tests, chemotype 1 and chemotype 2 were more active against Sitophilus zeamais than mixed chemotype. Farnesol was found to be effective only at a higher concentration as a


Introduction
Tephrosia vogelii (Hook f.) is a pesticidal plant, in Africa found mainly in the tropics [1]. It is also called fish poison [2]. It is a soft woody branching herb with dense foliage and can grow up to 0.5-4.0 m tall [3] It occurs in climates with an annual rainfall of 850-2650 mm, annual mean temperature of 12.5-26.2 o C and is found up to 2100 m above sea level [3]. Attempts have been made in eastern and southern Africa to promote T. vogelii for wider application as a pesticide source through earlier reports [4]- [5]. Previous reports however indicate that some plants like Tephrosia vogelii (Hook f.) and Lippia javanica (Burm. f.) can exhibit an extreme variation of bioactive principles from the same species [6]- [7]. [6] showed that some crude extracts of the leaves of T. vogelii possessed rotenoids and were thus pesticidal materials (chemotype1) while others are non-pesticidal due to lack of rotenoids (chemotype 2). This variation was thus based on the profiles of the flavonoids. Additionally, recent reports have indicated three chemotypes of T. vogelii materials from East Africa (Kenya and Tanzania) through phytochemical analysis [8]. These variations in the phytocompounds would affect the pesticidal activities of these plants pausing limitation to their use which would slow their adoption. T. vogelii volatile extracts have not been widely exploited for insecticidal activities.
To the best of our knowledge, there had been no reports of chemical variation on the essential oils of T.vogelii species that exists. The aim of the study was to at investigate chemical variation in the constituents and composition of the essential oils T. vogelii collected from different locations in eastern Uganda and evaluate the implications this would have on pesticidal application against stored pest, S. zeamais.

Plant collection and sites
Collection of plant materials took place in Butaleja district, eastern Uganda. Two plant collection sites were considered for the study; Mazimasa sub-county, Nampologoma Parish, Muyago village and Kachonga sub-county, Kyadongo parish, and Kyadongo B village.
Kachonga sub-county surrounds the Doho Wetland found in Mazimasa sub-county and the area is ten kilometres from Mbale Town (33° 55′ to 34° 05′ E and 0° 50′ to 1° 00′ N). The coordinates of the district are: 00 56' N, 33 57' E. The district (Butaleja District) area is approximately 653.1km 2 . The altitude of the district ranges from 1050 m to 1100 m above sea level. Several tropical climate conditions with average temperatures between 16 0 C and 29 0 C occur due to different altitudes. The mean annual rainfall varies between 1500 mm to 1,750 mm and received within four months [9]. The bimodal rainfall peaks are; March-May and August-September [10]. The soil is sandy with low organic content although some clay soils transferred from neighboring volcanic mountain in Mbale district form along rivers [9].

Plant Materials and Botanical Identification
Different plant leaf materials of T. vogelii plant species were collected from Muyago and Kyadongo villages, Butaleja District, eastern Uganda. Leafy materials were collected from branches, air dried and stored. To determine the effect of geographical and seasonal variations in the existence of T. vogelii chemotypes, collection of plant materials was done within two major seasonal rainfall patterns in the district: rainy season (March-May, and August-September) and dry season (January and June-July) ( Table 1) from two different villages.

Extraction
Each sample of plant leaf materials (20g) was hydro-distilled for 4hrs using a Clevenger apparatus set up as prescribed by British pharmacotia for essential oils. The oils were collected using a Pasteur pipette and dried using anhydrous sodium sulphate. The dry oil was then put in a small weighed dark brown bottle (5mL) and refrigerated at 4 0 C for analysis. For pesticidal evaluation, more masses of the sample were hydro-distilled.

Identification of compounds with Gas Chromatography (GC)
GC analysis was done using Brunker 300 Gas Chromatograph equipped with FID detector for Kovats indices determination [11].

Mass spectrometry (GC/MS)
The essential oil was analyzed by a Bruker 300-MS along with the 431-GC and CP-8400 is based on the equivalent 5 or 10μL stock of compound used due to different densities) for the linear regression curves were prepared from synthetic reference materials. These were run on the same day of the sample analysis and regression equations obtained by plotting peak areas against the concentration levels. For compounds whose standards were available, quantification was done. For unavailable standards, compounds were grouped into chemical classes (hydrocarbons, alkylbenzenes, aldehydes, alcohols, etc.) and subclasses (monoterpenes, sesquiterpenes, oxygenated monoterpenes etc.) and a semi-quantification approach was carried out using one (or more) reference standard per group. The compound composition was then expressed as percentage peak area i.e.

Constituent percentage peak area= (Xs )*100/(1000 x R)
where Xs is the constituent concentration of with respect to its peak area (ppb/µg mL -1 ) relative to peak area in the injection volume (1µL =1000ppb), and R is the recovery (R was taken as 100% since average recovery on spiking was 93.1±9.8, n=11).

Principal component analysis (PCA) and Agglomerative hierarchical clustering (AHC) of major chemical components from oils of T. vogelii species
PCA and AHC were performed on the data to group components and samples into clusters using statistical software SPSS for Windows version 25. PCA is a statistical tool that aims to represent the variation present in the data. It allows similarities and differences between data to be seen easily. During PCA, values in the loadings matrix were obtained through the transformation of data from correlated to new uncorrelated variables called principal components [13]. PCA was performed on a combined set of data from the two locations giving 19 samples × 23 variables for PCA. Analysis followed the standardization of data using Varimax rotation. Factor loadings generated indicate the correlations of each chemical constituent with its corresponding component. Loading scores which were greater than 5% of the variance of a given variable were considered however only loadings higher than an absolute value of 0.23 were considered meaningful throughout the analysis.
AHC is an algorithm that brings together related objects into clusters. The clustering makes it easier to see the correlations. The endpoint is having clusters that are distinctive other cluster and the objects with in a cluster are very similar. AHC based on the Euclidean distance was used to analyse seasonal and geographical influence on the yield and composition of the samples of T. vogelii. Finally, the classification of samples was done based on the composition and chemical constituents.

Pesticidal evaluation
The repellency and fumigant toxicity for the different varieties were evaluated for selected samples (Tv1kyb, Tv4kyc and TV4muyc).

Rearing of weevils
Plastic containers were used to bleed colonies of the S. zeamais. Initial stocks of weevils was obtained from infected maize from a market in Mthatha, Eastern Cape province of South Africa. Culturing occurred at 25-29 °C, 60 ± 5% RH and a photoperiod of 12:12 dark: light.

Repellence bioassay against S. zeamais
Repellence assay was done using the area preference method [14]. Here Petri dishes (9.0 × 1.2) cm and discs of filter paper half (31.8 cm 2 ) were used. Different levels of the test solutions; 1, 5 and 10 μL/mL of essential oils corresponding to 0.03, 0.16 and 0.31 μL of oil per cm 3 respectively were used to check for the repellent potential of essential oils. Whatman filter papers were cut into two halves. To one half was applied the oil treatment uniformly using a micropipette. To the other half was a control treatment of 1.0 mL of hexane. Both treated halves were allowed to dry so that the solvent could evaporate completely. The halves were then attached with cellophane tape in a manner that would avoid the seepage of the test samples from one disc to another and placed at the bottom of each petri dish. Thirty mixed sex-adult S. zeamais were released at the center of each disc and the petri dish was covered and kept in the dark at 25 to 29.5 0 C. Three replicates were done for each test solution of the essential oil. The numbers of the weevils in both the treated and untreated filter paper disc were counted after 1, 12, 24, 48 and 72 hours.
Percentage repellency (PR) was calculated using the formula in equation 1: The experiments were repeated twice with three replicates each time and separate controls were set in all the replicates in a completely randomized design. The data for the treatment means were compared using analysis of variance (ANOVA) and separated by the Fisher LSD test at P ˂ 0.05, after being log10 transformed using statistical software SPSS for Windows version 25 for heterogeneity correction. Data was presented as mean percentage repellency± SEM (SEM is a standard error of the mean)

Chemical constituents and composition of essential oils
Yellow distillates whose percentage yield ranged between 0.18±0.01% to 0.22±0.01% (w/w) dry weight for samples from Kyadongho B (Table 2) and 0.16±0.00% to 0.22±0.01% (w/w) dry weight for Muyago samples (Table 3) was obtained from the hydro distillation of leaf materials.      The densities of these oils were between 0.959±0.013 and 1.087±0.016 g/mL for oils extracted from Kyadongo B samples and for Muyago samples, it varied between 0.942±0.001g/mL and1.030±0.030g/mL. The compositions were expressed as mean peak areas (%±SEM) of the major compounds quantified from sample sites of the two study areas.

Chemotypes of T. vogelii
To determine the correlation of major components between various T. vogelii samples, PCA and AHC were performed on the data. Principal component analysis led to a total of 8 factors extracted (i.e. whose eigenvalues were greater than unity) and the loading scores were

Effect of season variation on the percentage yield and major composition of the oils
Two seasons variations were considered in the study: rain season and dry season represented with the green pattern and red pattern respectively (Figure 3). The rainfall bimodal peaks in the district occur between March to May and August-September. Samples obtained during this time were: Tv1muya, Tv2muya, Tv3muya, Tv3muyb, Tv3muyc, Tv2kya, Tv2kyb, Tv2kyc, Tv2kyd, and Tv3kya. During the dry season, harvest occurred in January and June and these samples were: Tv1Kya, Tv1kyb, Tv1kyc, Tv4kya, Tv4kyb, Tv4kyc, Tv4muya, Tv4muyb, and Tv4muyc. Considering this, there was no significant difference between the percentage oil yield between the two seasons and from the two sampled areas.

Evaluation of the Repellency potential of the chemotypes of the volatile constituents of T. vogelii
Repellency potential of TV4 Kyc (Farnesol chemotype) and TV4 Muya (Springene chemotype) was also evaluated and results indicate that there was no much difference in their repellency effect against S. zeamais ( Figure 6). The preference index of TV4kyc (farnesol type) oil for gainst S. zeamais ranged between 0.0 to -0.7, 0.0 to -0.5 and -0.  The implications of this chemical variation on the fumigant toxicity were studied and results indicated a significant difference between the farnesol chemotype and the springene chemotype (P ˂ 0.05, Fisher LSD test) at a lower dose (Table 4). Springene chemotype could exhibit a higher fumigant effect probably due to synergistic factors. However at a higher concentration; the effect is not so different for the three chemical varieties.

Conclusion
Investigation of chemical varieties in the essential oils of T. vogelii species from the eastern part of Uganda has revealed three chemotypes based on the profiles of farnesene compounds; one that possesses the farnesol, and the other that has the springene and β-farnesene type; all from the farnesene family and a mixed chemotype of the two. The geographical and seasonal variation could not affect the amount of the oil significantly however; the composition and the constituents of the oils were affected by the harvest period. Evaluation of the repellency effects on these chemical varieties of T. vogelii showed that chemotype 1 and 2 were similarly active but more than chemotype 3, against S. zeamais. At a lower concentration, there was no significant repellency effect between chemotype 1 and 2. At higher concentrations though, the effect could change. Notwithstanding, the repellent effect of these varieties of T. vogelii still holds. The complementary part of all other compounds found in the same oils plays a crucial role in the overall repellent effect of this oil. However, more study is needed that aims to optimize and standardize the chemical varieties and harvesting period needed for recommendation to smallhold farmers especially under field conditions before it can be adopted more widely.