The cacao swollen shoot disease (CSSD) caused by a complex of badnavirus species presents a major challenge for cacao production in West Africa, especially Ghana and Côte d’Ivoire. In this study, CSSD species detection efficiency, diversity, and geographic distribution patterns in cacao plantations in Ghana and Côte d’Ivoire were investigated through field surveillance, PCR detection assays, sequencing of positive amplicons, and phylogeographic clustering. Cumulatively, the detection efficiency of the tested CSSD primer sets that were targeting the movement protein domain of the virus ranged from 0.15% (CSSD-3 primer) to 66.91% (CSSD-1 primer) on all the symptomatic cacao leaf samples assessed. The identified CSSD species differed phylogenetically and overlapped in distribution, with the cacao swollen shoot Togo B virus (CSSTBV) (n = 588 sequences) being the most prevalent and widely distributed compared to the other CSSD species that were encountered in both countries. Geographically, the cacao swollen shoot CE virus (CSSCEV) species (n = 124 sequences) that was identified was largely restricted to the bordering regions of Ghana and Côte d’Ivoire. These results provide updated knowledge of the geographic distribution of the key CSSD species and their diagnostic efficiency and, thus, provide guidance in identifying locations for structured testing of cacao germplasm and optimal diagnostics for the predominant CSSD species in Ghana and Côte d’Ivoire.

This study was conducted to understand the reinfection pattern of cocoa swollen shoot disease (CSSD) in rehabilitated plots in the cocoa landscape of the Nawa region (Soubré) in Côte d’Ivoire. CSSD was monitored over time on a sample of 200 farms randomly selected from 1200 rehabilitated cocoa farms. Disease epidemiological parameters were assessed through field observations and molecular diagnostic analysis at farm and landscape levels. The results of this study showed that reinfection occurred earlier than expected, with a high disease incidence estimated at 6.95% from 2020 to 2022. Grafting with clones on mature cocoa trees was more susceptible to reinfection than grafting on seedlings and hybrids. The use of PCR as a molecular diagnostic tool indicated missed infections in the current removal strategy when considering the buffer zone recommended in the cutting out process currently in place. Recommendations for the efficient protection of rehabilitated farms after cutting out campaigns are highlighted.

The difficulty of obtaining paired data remains a major bottleneck for learning image restoration and enhancement models for real-world applications. Current strategies aim to synthesize realistic training data by modeling noise and degradations that appear in real-world settings. We propose DeFlow, a method for learning stochastic image degradations from unpaired data. Our approach is based on a novel unpaired learning formulation for conditional normalizing flows. We model the degradation process in the latent space of a shared flow encoder-decoder network. This allows us to learn the conditional distribution of a noisy image given the clean input by solely minimizing the negative log-likelihood of the marginal distributions. We validate our DeFlow formulation on the task of joint image restoration and super-resolution. The models trained with the synthetic data generated by DeFlow outperform previous learnable approaches on three recent datasets. Code and trained models are available at: https://github.com/volflow/DeFlow

This study was conducted to understand the reinfection pattern of cocoa swollen shoot disease (CSSD) in rehabilitation pilot plots in the cocoa landscape on Nawa region (Soubre) in Côte d’Ivoire. For that, the monitoring of CSSD was carried out on a ran-domly selected representative sample size of rehabilitating trials over time by assessing the epidemiological parameters of the disease through field observations combined with molecular samples analysis on-farm and at landscape level. Results showed that the reinfection appeared earlier than expected with high speed of incidence estimated to 6.95 % from 2020 to 2022. Grafting technology with clones on matures cocoa trees seems more susceptible to reinfection compared to grafting on seedling and hybrids. The use of PCR as molecular diagnostic indicated some miss infections in the removal strategy when considering the buffer zone recommended in the cutting out process currently in force. Recommendations for an efficient protection of rehabilitated farms after the cutting out campaigns were highlighted.