Long-term effect of Mali phosphate rock on the grain yield of interspecifics and saltiva rice cultivars on acid soil in a humid forest zone of Côte d’Ivoire

To generate knowledge of upland rice intensification in West Africa, the grain yields of four interspecific cultivars (V2 = WAB450-1 B-P-38-HB; V3 = WAB450-11-1-P-40-HB; V4 = WAB450-11-1-P-40-1-H; and V5 = WAB450-24-3-2-P-18-HB) were compared with that of a soil acidity tolerant sativa (WAB 56-104 = V1) on acid soil at Man in the humid forest zone in Côte d’Ivoire during five cropping seasons (1998, 1999, 2000, 2001 and 2002). Nitrogen and potassium were annually applied at 100 and 50 kg ha-1 respectively. Mali phosphate rock from Tilemsi was applied once in 1998 at 0, 150, 300 and 450 kg P ha-1 in a randomized complete block design with three replications. The results revealed a grain yield ranging from 0.5 t ha-1 to 2.6 t ha-1 with highest productivity of interspecific cultivars V3 and V4 even at 0 kg P ha-1 compared to acid tolerant saltiva (V1). Annual optimum rates of P application were determined at 31.5 and 45 kg P ha-1 respectively for V3 and V4. Applying Mali PR at 31.5 and 45 kg P ha-1 respectively for V3 and V4 was recommended for upland rice intensification in the humid forest zone of Côte d’Ivoire.Keywords: Mali phosphate rock, rice, Côte d’Ivoire, interspecific, acid soil

Application of Artificial Intelligence (AI)in Sustainable Building Lifecycle; ASystematic Literature Review

With buildings accounting for a significant portion of global energy consumption and greenhouse gas emissions, the application of artificial intelligence (AI) holds promise for enhancing sustainability in the building lifecycle. This systematic literature review addresses the current understanding of AI’s potential to optimize energy efficiency and minimize environmental impact in building design, construction, and operation. A comprehensive literature review and synthesis were conducted to identify AI technologies applicable to sustainable building practices, examine their influence, and analyze the challenges of implementation. The review was guided by a meticulous search strategy utilizing keywords related to AI application in sustainable building design, construction, and operation. The findings reveal AI’s capabilities in optimizing energy efficiency through intelligent control systems, enabling predictive maintenance, and aiding design simulation. Advanced machine learning algorithms facilitate data‐driven analysis and prediction, while digital twins provide real‐time insights for informed decision‐making. Furthermore, the review identifies barriers to AI adoption, including cost concerns, data security risks, and challenges in implementation. AI presents a transformative opportunity to enhance sustainability in the built environment, offering innovative solutions for energy optimization and environmentally conscious practices. However, addressing technical and practical challenges will be crucial for the successful integration of AI in sustainable building practices

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Nutrient constraint of rainfed rice production in foot slope soil of Guinea Forest in Côte d’Ivoire

Soil nutrient deficiencies can affect rice yield and grain mineral content wherever they occur, but an understanding of their effect on upland rice production in humid forest zone of West Africa is still limited. Therefore, a nutrient omission trial was conducted on foot slope soil in 2003, 2004 and 2005 in Côte d’Ivoire using rice variety WAB 56–104. The effect on rice grain yield (GY) and nutrient content of complete fertilizer (Fc with nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg) and zinc (Zn)) was compared with Fc from which a specific nutrient was excluded (Fc – N, Fc – P, Fc – K, Fc – Ca, Fc – Mg and Fc – Zn). Before the trial, soil K (0.10 cmol kg−1) and Mg (0.20 cmol kg−1) contents were suitable, but available P-Bray I (4.2 mg kg−1) was found to be deficient. In course of the study, K, Mg and P deficiencies were observed. An antagonistic effect was observed between rice GY and grain concentrations in P, Mg and Ca for treatments Fc – Mg, Fc – P and Fc – K, respectively. Therefore, the use of P, K and Mg fertilizers is recommended for successive cropping seasons in order to rich stable and high rice yield while decreasing of grain concentrations in P, Mg and Ca can be observed