Effect of Sowing Density on the Growth and Yield of Two Hybrid Varieties of Maize (Zea mays L.) in Dschang, West Cameroon

Abstract

Maize (Zea mays L.) is vital to Cameroon's agricultural sector, supporting food security and economic stability. Despite production efforts, yields remain low, necessitating agronomic interventions. This study assessed the effect of sowing density on the growth and yield of two hybrid maize varieties, Pannar 12 and Kabamanoj F1, in Dschang, Cameroon. A completely randomized block design with a split-plot arrangement and three replications was used, with variety as the main plot and sowing density as the subplot. The study was conducted at the Faculty of Agronomy and Agricultural Sciences, University of Dschang, Cameroon, from February to June, 2023. Four sowing densities were tested: 62,500 plants/ha, 83,333 plants/ha, 62,500 plants/ha, and 71,428 plants/ha. Growth parameters, including plant height, collar diameter, and number of leaves per plant, were recorded at different growth stages. Yield components such as ear diameter, ear length, grain weight, and total yield were also assessed. Statistical analyses included ANOVA, LSD tests for mean separation, and Pearson correlation analysis. Sowing density significantly influenced the number of leaves per plant (P < 0.05), with the highest at 62,500 plants/ha (11.60) and the lowest at 83,333 plants/ha (9.58) at 42 days after sowing. Variety significantly affected ear diameter (P < 0.01), with Pannar 12 (51.70 mm) outperforming Kabamanoj F1 (50.34 mm). Grain weight was variety-dependent but unaffected by sowing density. Correlation analysis showed significant positive relationships between yield and growth parameters such as leaf length (r = 0.54**), stalk height (r = 0.55**), and collar diameter (r = 0.56**). Higher sowing densities reduced individual plant growth but optimized total plot yield. The Pannar 12 variety at 62,500 plants/ha is recommended for maximizing maize productivity in Dschang. These findings provide valuable agronomic insights for optimizing maize production in similar agro-ecological zones.