The objective of the study was to investigate the relative abundance and effect of post-harvest treatment on total phenolics (TP) and total alkaloids in the leaves and bark of Carissa edulis and Zanthoxylum chalybeum, which would give an indication of the suitability of leaves as alternative sources of medicine in these plant species. Results indicated higher levels of total phenolics than total alkaloids in both of the species under both freezing and air drying conditions. While more alkaloids were found in leaves compared to bark, there was no difference in abundance of phenols between the plant parts of both species. Air drying preserved more TPs than freezing and the opposite was true for alkaloids. For sustainability, leaves are recommended as an alternative source of medicine instead of the preferred root or stem bark. However, the choice of whether to dry or freeze will depend on the specific compound of interest. Assessment of spatial variability of medicinal properties is highly recommended.

Establishing the genetic diversity and population structure of a species can guide the selection of appropriate conservation and sustainable utilization strategies. Next-generation sequencing (NGS) approaches are increasingly being used to generate multi-locus data for genetic structure determination. This study presents the genetic structure of a fodder species -Trema orientalisbased on two genome-wide high-throughput diversity array technology (DArT) markers; silicoDArT and single nucleotide polymorphisms (SNPs). Genotyping of 119 individuals generated 40,650 silicoDArT and 4767 SNP markers. Both marker types had a high average scoring reproducibility (>99%). Genetic relationships explored by principal coordinates analysis (PCoA) showed that the first principal coordinate axis explained most of the variation in both the SilicoDArT (34.2%) and SNP (89.6%) marker data. The average polymorphic information content did not highly differ between silicoDArT (0.22) and SNPs (0.17) suggesting minimal differences in informativeness in the two groups of markers. The, mean observed (H_o) and expected (H_e) heterozygosity were low and differed between the silicoDArT and SNPs respectively, estimated at H_o= 0.08 and H_e= 0.05 for silicoDArT and H_o= 0.23 and H_e= 0.19 for SNPs. The population ofT.orientaliswas moderately differentiated (F_ST = 0.20–0.53) and formed 2 distinct clusters based on maximum likelihood and principal coordinates analysis. Analysis of molecular variance revealed that clusters contributed more to the variation (46.3–60.8%) than individuals (32.9–31.2%). Overall, the results suggest a high relatedness of the individuals sampled and a threatened genetic potential ofT.orientalisin the wild. Therefore, genetic management activities such as ex-situ germplasm management are required for the sustainability of the species. Ex-situ conservation efforts should involve core collection of individuals from different populations to capture efficient diversity. This study demonstrates the importance of silicoDArT and SNP makers in population structure and genetic diversity analysis ofTrema orientalis, useful for future genome wide studies in the species.

Incorporating chemical traits in breeding requires the estimation of quantitative genetic parameters, especially the levels of additive genetic variation. This requires large numbers of samples from pedigreed populations. Conventional wet chemistry procedures for chemotyping are slow, expensive and not a practical option. This study focuses on the chemical variation in Pinus radiata, where the near infrared (NIR) spectral properties of the needles, bark and roots before and after exposure to methyl jasmonate (MJ) and artificial bark stripping (strip) treatments were investigated as an alternative approach. The aim was to test the capability of NIR spectroscopy to (i) discriminate samples exposed to MJ and strip assessed 7, 14, 21 and 28 days after treatment from untreated samples, and (ii) quantitatively predict individual chemical compounds in the three plant parts. Using principal components analysis (PCA) on the spectral data, we differentiated between treated and untreated samples for the individual plant parts. Based on partial least squares–discriminant analysis (PLS-DA) models, the best discrimination of treated from non-treated samples with the smallest root mean square error cross-validation (RMSECV) and highest coefficient of determination (r²) was achieved in the fresh needles (r² = 0.81, RMSECV= 0.24) and fresh inner bark (r² = 0.79, RMSECV = 0.25) for MJ-treated samples 14 days and 21 days after treatment, respectively. Using partial least squares regression, models for individual compounds gave high (r²), residual predictive deviation (RPD), lab to NIR error (PRL) or range error ratio (RER) for fructose (r² = 0.84, RPD = 1.5, PRL = 0.71, RER = 7.25) and glucose (r² = 0.83, RPD = 1.9, PRL = 1.14, RER = 8.50) and several diterpenoids. This provides an optimistic outlook for the use of NIR spectroscopy-based models for the larger-scale prediction of the P. radiata chemistry needed for quantitative genetic studies.