This study investigated the variability of climate parameters and food crop yields in Nigeria. Data were sourced from secondary sources and analyzed using correlation and multivariate regression. Findings revealed that pineapple was more sensitive to climate variability (76.17%), while maize and groundnut yields were more stable with low sensitivity (0.98 and 1.17%). Yields for crops like pineapple (0.31 kg/ha) were more sensitive to temperature, while maize, beans, groundnut, and vegetable yields were less sensitive to temperature with yields ranging from 0.15 kg/ha, 0.21 kg/ha, 0.18 kg/ha, and 0.12 kg/ha respectively. On the other hand, maize, beans, groundnut, and vegetable yields were more sensitive to rainfall ranging from 0.19kg/ha, 0.15kg/ha, 0.22 kg/ha, and 0.18 kg/ha respectively compared to pineapple yields which decreased with increase rainfall (−0.25 kg/ha). The results further showed that for every degree increase in temperature, maize, pineapple, and beans yields decreased by 0.48, 0.01, and 2.00 units at a 5 % level of significance, while vegetable yield decreased by 0.25 units and an effect was observed. Also, for every unit increase in rainfall, maize, pineapple, groundnut, and vegetable yields decreased by 3815.40, 404.40, 11,398.12, and 2342.32 units respectively at a 5% level, with an observed effect for maize yield. For robustness, these results were confirmed by the generalized additive and the Bayesian linear regression models. This study has been able to quantify the impact of temperature on food crop yields in the African context and employed a novel analytical approach combining the correlation matrix and multivariate linear regression to examine climate-crop yield relationships. The study contributes to the existing body of knowledge on climate-induced risks to food security in Nigeria and provides valuable insights for policymakers, farmers, government, and stakeholders to develop effective strategies to mitigate the impacts of climate change on food crop yields through the integration of climate-smart agricultural practices like agroforestry, conservation agriculture, and drought-tolerant varieties into national agricultural policies and programs and invest in climate information dissemination channels to help consider climate variability in agricultural planning and decision-making, thereby enhancing food security in the country.

The study evaluated 33 accessions of groundnut in the field, consisting of 23 landraces from Nasarawa communities in Nigeria and 10 inbred lines. Assessment entailed the determination of plant survivorship, yield related parameters and pathological indices while genetic diversity study was undertaken using SSR and RAPD molecular markers. Data analysis was done on the Minitab 17.0 software. Significant variability was noted in all traits except in pod sizes, seed sizes and % infected seeds. About 33.3% of the accessions had a survival rate of ≥ 70.0% where 9/10 Inbred lines were found with overall yield (kg/ha) ranging from 4.0 ± 1.6 in Akwashiki-Doma to 516.8 ± 46.9 kg/ha in Samnut 24 × ICGV–91328. Five accessions (15.5%) had pathological indices of zero indicating no traces of any disease of any type and they included one landrace called Agric-Dazhogwa and four Inbred lines: Samnut 25 × ICGV–91317, Samnut 26 × ICGV–19324, Samnut 26 × ICGV–91328 and Samnut 26 × ICGV–91319. Coefficients of yield determination R2 by survivorship and pathological index were 50.6% and 15%, respectively. A fit model was established (Yield in kg/ha = –146 − 7.94 × Pi + 5.88 × S). Susceptibility to diseases depends on the type of variety (χ2(32) = 127.67, P = 0.00). Yield was significantly affected by BNR@30 (F = 5.47, P = 0.025, P < 0.05) and DSV@60*RUST@60 interaction effect (F = 4.39, P = 0.044, P < 0.05). The similarity coefficient ranged from 28.57 to 100 in plant morphology. Four varieties had no amplified bands with SSR primers whereas amplified bands were present only in four landraces accessions using the RAPD primer. The dendrogram generated by molecular data gave three groups where genetic similarity ranged from 41.4 to 100.0. The Inbred lines were noted for their high survivorship, good yield and disease resistance. Samnut 24 × ICGV–91328, an inbred line, had the highest yield but was susceptible to diseases. Among the landraces, Agric-Musha, Bomboyi-Dugu and Agric-Dazhogwa were selected for high survivorship and disease resistance. The selected inbred lines and landraces are valuable genetic resources that may harbour useful traits for breeding and they should be presented to the growers based on their unique agronomic values. The highest yielding inbred lines should be improved for resistance to late leaf spot diseases while the outstanding landraces should be improved for yield.