The effect of methyl jasmonate (MeJA) sprayed on cotton healthy leaves was evaluated in terms of inherent bioactive chemicals induction. The total phenolic content significantly increased after MeJA 5.0 mM treatments compared to the other tested concentrations (0; 2.5; 10; 15; 20 mM). Among the eleven phenolic compounds which were found except for ferulic acid, gossypetin, gossypol, 3-p-coumaroylquinic acid, and piceatannol were identified as major phenolic constituents of cotton. Their content also significantly increased after the MeJA treatment. In addition, gossypol increased 64 times compared to the control, in the 5.0 mM MeJA treatment. Furthermore, cichoric acid, chlorogenic acid, and pterostilbene are synthesizedde novoin leaves of MeJA-treated plant. Treatment of cotton leaves with MeJA 5.0 mM followed 72 h of incubation hampered the expression ofFusariumwilt caused byFusarium oxysporium f. sp. vasinfectum(FOV). MeJA efficiency was concentration and incubation time dependent. Disease severity on MeJA-treated leaves was significantly lower as compared to the control. Therefore, the high content of gossypetin, gossypol, 3-p-coumaroylquinic acid, ferulic acid, and piceatannol and the presence of cichoric acid, chlorogenic acid, and pterostilbene in plants treated with MeJA, contrary to the control, are essential to equip the cotton compounds with defences or phytoalexins against FOV.

Garcinia kola Heckel, called "petit cola" in Côte d'Ivoire and "bitter kola" in Nigeria, is a Non-Timber Forest Product of great socioeconomic importance. Unfortunately, this species is threatened due to overexploitation and deforestation. This study tested the effect of leaf area on stem cuttings to regenerate vegetatively in a non-mist poly-propagator without using exogenous hormones. Three stem cuttings types: greenwood, softwood and hardwood (12 -15 cm in length) were collected from 24-month years old seedlings. The two top leaves of each cutting type were conserved at different leaf area: 0 cm 2 , 28.25 cm 2 , 56.5 cm 2 , 84.75 cm 2 and 113 cm 2 (entire leaf area). Observations were made on rooting, sprouting and leafing abilities of cuttings depending to treatments applied. Results showed that all cutting types have presented good ability to shooting and rooting. Cuttings with 113 cm 2 leaf areas presented the best rooting (94.44% ± 2.42%) and shouting (95.55% ± 2.42%) percentage and longest primary root length (12.03 ± 0.50 cm). Hardwood, softwood and greenwood cuttings with 113 cm 2 leaf area had the best rooting percentage (96.66% ± 3.33%, 96.66% ± 5.77% and 90.00% ± 5.77% respectively). The longest primary root length (13.50 ± 0.97 cm) was observed to greenwood cuttings with 113 cm 2 leaf area. Regenerated plants in the forest presented well survival percentage (96.66%). This study shows that it is possible to regenerate entire plants by cuttings without using

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The purpose of this study is to determine the morphological diversity and distribution of Garcinia kola Heckel (Clusiaceae) in two preferential agroecological growth areas in Côte d'Ivoire, for the sustainable management of the species. Ninety-four (94) trees of G. kola were sampled in Affery (south) and Biankouma (west) and characterized on the basis of 13 quantitative characteristics of the fruit, the general appearance of a plant, leaves and seeds. This study revealed the existence of very significant variability and differences within the trees sampled for most characteristics. Very strong correlations were found among the characteristics of the fruits. On the basis of these characteristics, it emerged that the fruits of the Biankouma area are larger than those of Affery. Multivariate analyses show that diversity is structured with tree distribution into four distinct groups based on the following discriminating characteristics: fruit height (Hfr), leaf width (largF), seed mass (Mgr) and trunk diameter (Dm). These parameters can be used as a basis for selecting and maintaining the high variability of G. kola. Analysis of the geographical distribution of trees, based on the nearest neighbour model, revealed an aggregate distribution in both areas.