To determine the growing and yield performance of low nitrogen tolerant maize varieties under fertilized and unfertilized conditions, a study was conducted at the Mvuazi Research Center. Nine varieties were tested with and without fertilizer using the micro-dosing method, following the randomized complete block design with two factors. The results showed a difference among varieties in both crop conditions. The average yield with fertilizer was higher than the yield without fertilizer. The varieties LNTP-W C4 and LNTP-Y C7 registered 5.9 t/ha and 3.6 t/ha respectively under fertilized crop conditions and 7.14t/ha and 7.12t/ha under unfertilized crop conditions. Thus, using Low-N can minimize production costs by improving the productivity of soils low in Nitrogen typical of conditions of the southwestern savanna. KEY WORDS: LOW NITROGEN SOIL, LNTP, MAIZE PRODUCTION, FERTILIZER, SAVANNA, INERA-DRC

To determine the growing and yield performance of low nitrogen tolerant maize varieties under fertilized and unfertilized conditions, a study was conducted at the Mvuazi Research Center. Nine varieties were tested with and without fertilizer using the micro-dosing method, following the randomized complete block design with two factors. The results showed a difference among varieties in both crop conditions. The average yield with fertilizer was higher than the yield without fertilizer. The varieties LNTP-W C4 and LNTP-Y C7 registered 5.9 t/ha and 3.6 t/ha respectively under fertilized crop conditions and 7.14t/ha and 7.12t/ha under unfertilized crop conditions. Thus, using Low-N can minimize production costs by improving the productivity of soils low in Nitrogen typical of conditions of the southwestern savanna.

Genotype assessment across various environments is a basic condition for developing stable and superior genotypes for sustainable maize production in the South-East of the DR Congo. Therefore, this research’s objectives were to identify the performance of newly developed provitamin A maize genotypes in various environments, and to recommend high-performing and stable genotypes for broader adaptation. Eight provitamin A maize genotypes, including one commercial variety, were planted at three sites during two consecutive cropping seasons (2020/2021 and 2021/2022) forming six environments. All genotypes in six environments were planted in a randomized complete block design containing three replications. Two stability analysis approaches, GGE biplot and Eberhart and Russell method are widely used to identify high yielding and stable genotypes. The combined analysis of variance revealed that G and E as well as their interaction (GEI) have significantly affected the emergence rate, cob’s insertion height, days to anthesis and silking, cob length, cob grain weight and grain yield. Average grain yield varied from 8.30 t/ha for PVAH-7L to 9.41 t/ha for PVAH-1L. The Eberhart and Russell method and the CV identified PVAH-1L, PVAH-4L, PVAH-7L and PVAH-6L as the most stable genotypes, but could not reliably identify the high yielding genotypes. On the other hand, the GGE biplot reliably and graphically showed the stable and high-yielding genotypes (PVAH-1L > PVAH-6L) as well as the low-yielding genotypes (PVAH-7 > PVAH-4L). In additional, the GGE biplot showed that L’shi21 was the best test environment for selecting high performing and stable provitamin A maize genotype. The results of this study indicate that PVAH-1L and PVAH-6L are the stable, high-yielding provitamin A maize genotypes in the South-East of the Democratic Republic of the Congo and should be disseminated in this region.

Meteorological stations are rare in the tropics and satellite products often do not perform optimal. This leads to uncertainty in modelled regional climatic trends and may lead to opposing trends in prediction of future climate. This is particularly problematic for the Congo basin, where station coverage decreased significantly during the last few decades. Therefore, here we present a newly digitised dataset of daily temperature and precipitation from the Yangambi biosphere reserve, covering the period 1960 - 2020 (61 years) and located in the heart of the Congo basin. Our results confirm a long-term increase in temperature and temperature extremes since the 1960s, with strong upward trends since the early 1990s. Our results also indicate a drying trend for the dry season and intensification of the wet season since the early 2000s. Ongoing warming and increasing precipitation seasonality and intensity already has a significant impact on crop yields in Yangambi. This calls for urgent development of climate-smart and dynamic agriculture and agroforestry systems. We conclude that systematic digitization and climate recording in the Congo basin will be critical to improve much-needed gridded benchmark datasets of climatic variables.