Advances in Biology & Earth Sciences

This study evaluated the performance of two breeding line spring wheat genotypes (Belyana and Agros) and a check variety (Radmira), under field trials across three production systems, Basic (BPS), Intensive (IPS) and High-Intensive (HIPS), over three seasons (2022-2024). The research focuses on genotype-by-production system interactions and their effects on reproductive traits, yield components, yield and quality traits. A 3 × 3 factorial split-block design with three replications was used, differentiating production systems by input intensity (fertilizers, herbicides, insecticides, fungicides and growth regulators). The study uses two-way analysis to assess variety and production system impact. The objective of the study was to monitor wheat growth under the three production systems by assessing yield traits such as spike length, number of spikelets per spike, number of seeds per spike and weight of seeds per spike. The grain yield and its components were also assessed, including 1000-grain weight, yield and quality traits, such as protein and gluten content. Over the three-year growing seasons, the results we analyzed demonstrated that Radmira consistently demonstrated outstanding performance in terms of spike length (9.81 cm) under the IPS recording (9.62 cm), number of seeds per spike (37.44) obtained with the HIPS (36.89), protein percentage (14.92%) and gluten (25.15%) both under HIPS (with 15.46% protein and 25.24% gluten) making it ideal for baking qualities. On the other hand, the analyses for yield and yield components, such as the number of spikelets per spike, show that the Belyana variety attained the highest (15.29) recorded with IPS (16.24) and the highest grain yield was also achieved with Belyana (4.64 t ha^-1), which was obtained with HIPS (4.91 t ha^-1). However, Agros achieved the highest weight of seed per spike (1.59 g) under the HIPS (1.66 g) and 1000-grain (40.5 g) under HIPS (40.33 g). Our results demonstrated a significant genotype-by-production system interactions this were observed for yield traits, yield components and quality traits, indicating differential genotype responses to input levels for specific yield and quality traits this model can leverage secondary traits to deliver accurate predictions for spring wheat grain yield, allowing breeders, wheat farmers to make a more robust and rapid genotype selection and production systems for wheat productivity and sustainability.