Variations in the Phenolic Contents of Cocoyam Clones in Correlation to Resistance to Pythium Myriotylum
Phenolic compounds from leaves and roots of infected and healthy cocoyam clones resistant (RO1075), tolerant (RO1043), and susceptible (RO1157) to Pythium myriotylum were quantified and tested for their in vitro fungitoxicity on the causal agent of the cocoyam root rot disease. All clones, infected or not, have phenolic compounds showing fungitoxic activity. The phenolic content of the tolerant and susceptible clones is less than that observed in the resistant one meanwhile in the resistant clone RO1075, a large increase in phenolic content is observed particularly in the roots during attack by pathogen.
Assessing relationship between phenolic compounds and resistance to Phytophthora megakarya using two cocoa (Theobroma cacao) families
Black pod disease is an important fungal infection in cocoa ( Theobroma cacao L.) which causes high production losses. In Cameroon, these losses reached 80% of cocoa production depending on ecological zones. In order to contribute to the efficiency of selection methods used in resistance or tolerance to black pod disease with the aim of improving on cocoa farming, the content of phenolic compounds was analyzed on the genotypes of two hybrid families (F79:♀T 79/467 x♂SNK 13 and F13:♀SNK 13 x♂T 79/467 ) of cocoa which are different in productivity and vulnerability to black pod disease. After artificial inoculation of the pods by mycelium of Phytophthora megakarya , the content of the phenolic compounds significantly increased in all genotypes of the two families. The heterosis effect of each family revealed a higher variability within both families. These results alike showed that productive and tolerant genotypes (F1307, 1314, F7902 and F7928) have a high phenols content and positive heterosis meanwhile the less tolerant and productive genotypes (F1321, F1326, F7904 and F7911) have a weak content and negative heterosis Keywords: Cocoa, disease, tolerance, heterosis effect, phenolic compounds, hybrid progenies African Journal of Biotechnology Vol 13(29) 2956-2965
Texture Feature Extraction of RGB, HSV, YIQ and Dithered Images using GLCM, Wavelet Decomposition Techniques
When changing the format of an image from simple RGB to HSV, YIQ and Dithered image, the characteristics of image also change. In this paper, the similar images in the above formats are retrieved using statistical and structural retrieving techniques i.e. GLCM (Gray Level Co-occurrence Matrix) and Wavelet Decomposition techniques. The best results are coming for dithered, HSV images by using GLCM technique for feature extraction and by using Wavelet decomposition; HSV images are giving the best results. While other formats also give the correct retrieval but from the accuracy point of view, HSV images are retrieved with better accuracy using both techniques.